From f257d38b66f00f544aab5817fe66eb9fe78a8b0f Mon Sep 17 00:00:00 2001 From: Zafir Stojanovski Date: Wed, 19 Jun 2024 11:36:54 +0200 Subject: [PATCH 001/194] [New Task] Add Paloma benchmark (#1928) * init paloma benchmark * pre-process in utils function * add `task_alias` * updated task aliases * Update paloma_dolma-v1_5.yaml * Update paloma_twitterAAE_HELM_fixed.yaml * Update paloma_dolma_100_programing_languages.yaml --------- Co-authored-by: Lintang Sutawika --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/paloma/README.md | 68 +++++++++++++++++++ lm_eval/tasks/paloma/paloma.yaml | 22 ++++++ .../tasks/paloma/paloma_4chan_meta_sep.yaml | 4 ++ .../tasks/paloma/paloma_c4_100_domains.yaml | 4 ++ lm_eval/tasks/paloma/paloma_c4_en.yaml | 4 ++ lm_eval/tasks/paloma/paloma_dolma-v1_5.yaml | 4 ++ ...paloma_dolma_100_programing_languages.yaml | 4 ++ .../paloma/paloma_dolma_100_subreddits.yaml | 4 ++ .../paloma/paloma_falcon-refinedweb.yaml | 4 ++ lm_eval/tasks/paloma/paloma_gab.yaml | 4 ++ .../paloma/paloma_m2d2_s2orc_unsplit.yaml | 4 ++ .../paloma/paloma_m2d2_wikipedia_unsplit.yaml | 4 ++ .../paloma/paloma_manosphere_meta_sep.yaml | 4 ++ lm_eval/tasks/paloma/paloma_mc4.yaml | 4 ++ lm_eval/tasks/paloma/paloma_ptb.yaml | 4 ++ lm_eval/tasks/paloma/paloma_redpajama.yaml | 4 ++ .../paloma/paloma_twitterAAE_HELM_fixed.yaml | 4 ++ lm_eval/tasks/paloma/paloma_utils.py | 2 + lm_eval/tasks/paloma/paloma_wikitext_103.yaml | 4 ++ 20 files changed, 157 insertions(+) create mode 100644 lm_eval/tasks/paloma/README.md create mode 100644 lm_eval/tasks/paloma/paloma.yaml create mode 100644 lm_eval/tasks/paloma/paloma_4chan_meta_sep.yaml create mode 100644 lm_eval/tasks/paloma/paloma_c4_100_domains.yaml create mode 100644 lm_eval/tasks/paloma/paloma_c4_en.yaml create mode 100644 lm_eval/tasks/paloma/paloma_dolma-v1_5.yaml create mode 100644 lm_eval/tasks/paloma/paloma_dolma_100_programing_languages.yaml create mode 100644 lm_eval/tasks/paloma/paloma_dolma_100_subreddits.yaml create mode 100644 lm_eval/tasks/paloma/paloma_falcon-refinedweb.yaml create mode 100644 lm_eval/tasks/paloma/paloma_gab.yaml create mode 100644 lm_eval/tasks/paloma/paloma_m2d2_s2orc_unsplit.yaml create mode 100644 lm_eval/tasks/paloma/paloma_m2d2_wikipedia_unsplit.yaml create mode 100644 lm_eval/tasks/paloma/paloma_manosphere_meta_sep.yaml create mode 100644 lm_eval/tasks/paloma/paloma_mc4.yaml create mode 100644 lm_eval/tasks/paloma/paloma_ptb.yaml create mode 100644 lm_eval/tasks/paloma/paloma_redpajama.yaml create mode 100644 lm_eval/tasks/paloma/paloma_twitterAAE_HELM_fixed.yaml create mode 100644 lm_eval/tasks/paloma/paloma_utils.py create mode 100644 lm_eval/tasks/paloma/paloma_wikitext_103.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index fcb727e9..9d99e42f 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -70,6 +70,7 @@ | okapi/mmlu_multilingual | Tasks that involve reading comprehension and information retrieval challenges. | Multiple (34 languages) | | [okapi/truthfulqa_multilingual](okapi/truthfulqa_multilingual/README.md) | Tasks that involve reading comprehension and information retrieval challenges. | Multiple (31 languages) | | [openbookqa](openbookqa/README.md) | Open-book question answering tasks that require external knowledge and reasoning. | English | +| [paloma](paloma/README.md) | Paloma is a comprehensive benchmark designed to evaluate open language models across a wide range of domains, ranging from niche artist communities to mental health forums on Reddit. | English | | [paws-x](paws-x/README.md) | Paraphrase Adversaries from Word Scrambling, focusing on cross-lingual capabilities. | English, French, Spanish, German, Chinese, Japanese, Korean | | [pile](pile/README.md) | Open source language modelling data set that consists of 22 smaller, high-quality datasets. | English | | [pile_10k](pile_10k/README.md) | The first 10K elements of The Pile, useful for debugging models trained on it. | English | diff --git a/lm_eval/tasks/paloma/README.md b/lm_eval/tasks/paloma/README.md new file mode 100644 index 00000000..54ad5fef --- /dev/null +++ b/lm_eval/tasks/paloma/README.md @@ -0,0 +1,68 @@ +# Paloma + +### Paper +Title: Paloma: A Benchmark for Evaluating Language Model Fit + +Abstract: https://arxiv.org/abs/2312.10523v1 + +Paloma is a comprehensive benchmark designed to evaluate open language models across a wide range of domains, ranging from niche artist communities to mental health forums on Reddit. It assesses the performance of various models across 585 distinct domains. + +Homepage: https://allenai.org/olmo + + +### Note + +If you are running the entire `paloma` benchmark (or just `paloma_dolma_100_programing_languages`) with a HuggingFace model, make sure to pass `logits_cache=False` to `--model_args`, for example: +``` +lm_eval --model hf --model_args pretrained=EleutherAI/pythia-160m,logits_cache=False --tasks paloma +``` + + +### Citation +``` +@article{paloma, + title={{Paloma}: A Benchmark for Evaluating Language Model Fit}, + author={Magnusson, Ian and Bhagia, Akshita and Hofmann, Valentin and Soldaini, Luca and Harsh Jha, Ananya and Tafjord, Oyvind and Schwenk,Dustin and Walsh, Evan Pete and Elazar, Yanai and Lo, Kyle and Groenveld,Dirk and Beltagy,Iz and Hajishirz,Hanneneh and Smith, Noah A. and Richardson,Kyle and Dodge,Jesse}, + journal={technical report}, + year={2023}, + url={https://paloma.allen.ai/} +} +``` + +### Groups and Tasks + +#### Groups + +* `paloma` + +#### Tasks + +* `paloma_4chan_meta_sep` +* `paloma_c4_100_domains` +* `paloma_c4_en` +* `paloma_dolma_100_programing_languages` +* `paloma_dolma_100_subreddits` +* `paloma_dolma-v1_5` +* `paloma_falcon-refinedweb` +* `paloma_gab` +* `paloma_m2d2_s2orc_unsplit` +* `paloma_m2d2_wikipedia_unsplit` +* `paloma_manosphere_meta_sep` +* `paloma_mc4` +* `paloma_ptb` +* `paloma_redpajama` +* `paloma_twitterAAE_HELM_fixed` +* `paloma_wikitext_103` + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [ ] Is the task an existing benchmark in the literature? + * [ ] Have you referenced the original paper that introduced the task? + * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/paloma/paloma.yaml b/lm_eval/tasks/paloma/paloma.yaml new file mode 100644 index 00000000..84983e58 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma.yaml @@ -0,0 +1,22 @@ +group: + - paloma +dataset_path: allenai/paloma +output_type: loglikelihood_rolling +validation_split: val +test_split: test +doc_to_text: "" +doc_to_target: !function paloma_utils.doc_to_target +should_decontaminate: true +doc_to_decontamination_query: !function paloma_utils.doc_to_target +metric_list: + - metric: word_perplexity + aggregation: weighted_perplexity + higher_is_better: false + - metric: byte_perplexity + aggregation: weighted_perplexity + higher_is_better: false + - metric: bits_per_byte + aggregation: bits_per_byte + higher_is_better: false +metadata: + version: 1 diff --git a/lm_eval/tasks/paloma/paloma_4chan_meta_sep.yaml b/lm_eval/tasks/paloma/paloma_4chan_meta_sep.yaml new file mode 100644 index 00000000..a5a34c1e --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_4chan_meta_sep.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_4chan_meta_sep +task_alias: 4chan Corpus +dataset_name: 4chan_meta_sep diff --git a/lm_eval/tasks/paloma/paloma_c4_100_domains.yaml b/lm_eval/tasks/paloma/paloma_c4_100_domains.yaml new file mode 100644 index 00000000..0357e40f --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_c4_100_domains.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_c4_100_domains +task_alias: C4-100-domains +dataset_name: c4_100_domains diff --git a/lm_eval/tasks/paloma/paloma_c4_en.yaml b/lm_eval/tasks/paloma/paloma_c4_en.yaml new file mode 100644 index 00000000..404d0b37 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_c4_en.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_c4_en +task_alias: C4 +dataset_name: c4_en diff --git a/lm_eval/tasks/paloma/paloma_dolma-v1_5.yaml b/lm_eval/tasks/paloma/paloma_dolma-v1_5.yaml new file mode 100644 index 00000000..da02846a --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_dolma-v1_5.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_dolma-v1_5 +task_alias: Dolma V1.5 +dataset_name: dolma-v1_5 diff --git a/lm_eval/tasks/paloma/paloma_dolma_100_programing_languages.yaml b/lm_eval/tasks/paloma/paloma_dolma_100_programing_languages.yaml new file mode 100644 index 00000000..bd264dd3 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_dolma_100_programing_languages.yaml @@ -0,0 +1,4 @@ +include: _paloma_template +task: paloma_dolma_100_programing_languages +task_alias: 100 PLs +dataset_name: dolma_100_programing_languages diff --git a/lm_eval/tasks/paloma/paloma_dolma_100_subreddits.yaml b/lm_eval/tasks/paloma/paloma_dolma_100_subreddits.yaml new file mode 100644 index 00000000..89ef7ad5 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_dolma_100_subreddits.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_dolma_100_subreddits +task_alias: Dolma-100-subreddits +dataset_name: dolma_100_subreddits diff --git a/lm_eval/tasks/paloma/paloma_falcon-refinedweb.yaml b/lm_eval/tasks/paloma/paloma_falcon-refinedweb.yaml new file mode 100644 index 00000000..284a7a0f --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_falcon-refinedweb.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_falcon-refinedweb +task_alias: Falcon Refinedweb +dataset_name: falcon-refinedweb diff --git a/lm_eval/tasks/paloma/paloma_gab.yaml b/lm_eval/tasks/paloma/paloma_gab.yaml new file mode 100644 index 00000000..fbd6a959 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_gab.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_gab +task_alias: Gab Corpus +dataset_name: gab diff --git a/lm_eval/tasks/paloma/paloma_m2d2_s2orc_unsplit.yaml b/lm_eval/tasks/paloma/paloma_m2d2_s2orc_unsplit.yaml new file mode 100644 index 00000000..0298588e --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_m2d2_s2orc_unsplit.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_m2d2_s2orc_unsplit +task_alias: M2D2 S2ORC +dataset_name: m2d2_s2orc_unsplit diff --git a/lm_eval/tasks/paloma/paloma_m2d2_wikipedia_unsplit.yaml b/lm_eval/tasks/paloma/paloma_m2d2_wikipedia_unsplit.yaml new file mode 100644 index 00000000..a3f2e243 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_m2d2_wikipedia_unsplit.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_m2d2_wikipedia_unsplit +task_alias: M2D2 Wikipedia +dataset_name: m2d2_wikipedia_unsplit diff --git a/lm_eval/tasks/paloma/paloma_manosphere_meta_sep.yaml b/lm_eval/tasks/paloma/paloma_manosphere_meta_sep.yaml new file mode 100644 index 00000000..e4dbf489 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_manosphere_meta_sep.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_manosphere_meta_sep +task_alias: Manosphere Corpus +dataset_name: manosphere_meta_sep diff --git a/lm_eval/tasks/paloma/paloma_mc4.yaml b/lm_eval/tasks/paloma/paloma_mc4.yaml new file mode 100644 index 00000000..7ccbea81 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_mc4.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_mc4 +task_alias: mC4-en +dataset_name: mc4 diff --git a/lm_eval/tasks/paloma/paloma_ptb.yaml b/lm_eval/tasks/paloma/paloma_ptb.yaml new file mode 100644 index 00000000..73087f5f --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_ptb.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_ptb +task_alias: Penn Treebank +dataset_name: ptb diff --git a/lm_eval/tasks/paloma/paloma_redpajama.yaml b/lm_eval/tasks/paloma/paloma_redpajama.yaml new file mode 100644 index 00000000..bf4ddad5 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_redpajama.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_redpajama +task_alias: RedPajama +dataset_name: redpajama diff --git a/lm_eval/tasks/paloma/paloma_twitterAAE_HELM_fixed.yaml b/lm_eval/tasks/paloma/paloma_twitterAAE_HELM_fixed.yaml new file mode 100644 index 00000000..96075682 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_twitterAAE_HELM_fixed.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_twitterAAE_HELM_fixed +task_alias: Twitter AAE +dataset_name: twitterAAE_HELM_fixed diff --git a/lm_eval/tasks/paloma/paloma_utils.py b/lm_eval/tasks/paloma/paloma_utils.py new file mode 100644 index 00000000..adf88fd5 --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_utils.py @@ -0,0 +1,2 @@ +def doc_to_target(doc): + return str(doc["text"]) diff --git a/lm_eval/tasks/paloma/paloma_wikitext_103.yaml b/lm_eval/tasks/paloma/paloma_wikitext_103.yaml new file mode 100644 index 00000000..b10c4dbb --- /dev/null +++ b/lm_eval/tasks/paloma/paloma_wikitext_103.yaml @@ -0,0 +1,4 @@ +include: paloma.yaml +task: paloma_wikitext_103 +task_alias: Wikitext-103 +dataset_name: wikitext_103 -- GitLab From ead2964e40e3570114c9675622c1a56b638ad4a1 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Wed, 19 Jun 2024 09:45:19 -0400 Subject: [PATCH 002/194] Fix Paloma Template yaml (#1993) * init paloma benchmark * pre-process in utils function * add `task_alias` * updated task aliases * Update paloma_dolma-v1_5.yaml * Update paloma_twitterAAE_HELM_fixed.yaml * Update paloma_dolma_100_programing_languages.yaml * update on names * fix paloma template issue --------- Co-authored-by: Zafir Stojanovski Co-authored-by: Zafir Stojanovski Co-authored-by: Lintang Sutawika --- lm_eval/tasks/paloma/{paloma.yaml => _paloma_template} | 0 lm_eval/tasks/paloma/paloma_4chan_meta_sep.yaml | 4 ++-- lm_eval/tasks/paloma/paloma_c4_100_domains.yaml | 4 ++-- lm_eval/tasks/paloma/paloma_c4_en.yaml | 2 +- lm_eval/tasks/paloma/paloma_dolma-v1_5.yaml | 2 +- lm_eval/tasks/paloma/paloma_dolma_100_subreddits.yaml | 4 ++-- lm_eval/tasks/paloma/paloma_falcon-refinedweb.yaml | 4 ++-- lm_eval/tasks/paloma/paloma_gab.yaml | 4 ++-- lm_eval/tasks/paloma/paloma_m2d2_s2orc_unsplit.yaml | 2 +- lm_eval/tasks/paloma/paloma_m2d2_wikipedia_unsplit.yaml | 2 +- lm_eval/tasks/paloma/paloma_manosphere_meta_sep.yaml | 4 ++-- lm_eval/tasks/paloma/paloma_mc4.yaml | 4 ++-- lm_eval/tasks/paloma/paloma_ptb.yaml | 4 ++-- lm_eval/tasks/paloma/paloma_redpajama.yaml | 2 +- lm_eval/tasks/paloma/paloma_twitterAAE_HELM_fixed.yaml | 2 +- lm_eval/tasks/paloma/paloma_wikitext_103.yaml | 2 +- 16 files changed, 23 insertions(+), 23 deletions(-) rename lm_eval/tasks/paloma/{paloma.yaml => _paloma_template} (100%) diff --git a/lm_eval/tasks/paloma/paloma.yaml b/lm_eval/tasks/paloma/_paloma_template similarity index 100% rename from lm_eval/tasks/paloma/paloma.yaml rename to lm_eval/tasks/paloma/_paloma_template diff --git a/lm_eval/tasks/paloma/paloma_4chan_meta_sep.yaml b/lm_eval/tasks/paloma/paloma_4chan_meta_sep.yaml index a5a34c1e..5f3c67d9 100644 --- a/lm_eval/tasks/paloma/paloma_4chan_meta_sep.yaml +++ b/lm_eval/tasks/paloma/paloma_4chan_meta_sep.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_4chan_meta_sep -task_alias: 4chan Corpus +task_alias: 4chan dataset_name: 4chan_meta_sep diff --git a/lm_eval/tasks/paloma/paloma_c4_100_domains.yaml b/lm_eval/tasks/paloma/paloma_c4_100_domains.yaml index 0357e40f..dbbde2d4 100644 --- a/lm_eval/tasks/paloma/paloma_c4_100_domains.yaml +++ b/lm_eval/tasks/paloma/paloma_c4_100_domains.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_c4_100_domains -task_alias: C4-100-domains +task_alias: C4 100 Domains dataset_name: c4_100_domains diff --git a/lm_eval/tasks/paloma/paloma_c4_en.yaml b/lm_eval/tasks/paloma/paloma_c4_en.yaml index 404d0b37..c8681dfb 100644 --- a/lm_eval/tasks/paloma/paloma_c4_en.yaml +++ b/lm_eval/tasks/paloma/paloma_c4_en.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_c4_en task_alias: C4 dataset_name: c4_en diff --git a/lm_eval/tasks/paloma/paloma_dolma-v1_5.yaml b/lm_eval/tasks/paloma/paloma_dolma-v1_5.yaml index da02846a..f816e107 100644 --- a/lm_eval/tasks/paloma/paloma_dolma-v1_5.yaml +++ b/lm_eval/tasks/paloma/paloma_dolma-v1_5.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_dolma-v1_5 task_alias: Dolma V1.5 dataset_name: dolma-v1_5 diff --git a/lm_eval/tasks/paloma/paloma_dolma_100_subreddits.yaml b/lm_eval/tasks/paloma/paloma_dolma_100_subreddits.yaml index 89ef7ad5..958812c5 100644 --- a/lm_eval/tasks/paloma/paloma_dolma_100_subreddits.yaml +++ b/lm_eval/tasks/paloma/paloma_dolma_100_subreddits.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_dolma_100_subreddits -task_alias: Dolma-100-subreddits +task_alias: 100 Subreddits dataset_name: dolma_100_subreddits diff --git a/lm_eval/tasks/paloma/paloma_falcon-refinedweb.yaml b/lm_eval/tasks/paloma/paloma_falcon-refinedweb.yaml index 284a7a0f..1e9bbe6e 100644 --- a/lm_eval/tasks/paloma/paloma_falcon-refinedweb.yaml +++ b/lm_eval/tasks/paloma/paloma_falcon-refinedweb.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_falcon-refinedweb -task_alias: Falcon Refinedweb +task_alias: Falcon dataset_name: falcon-refinedweb diff --git a/lm_eval/tasks/paloma/paloma_gab.yaml b/lm_eval/tasks/paloma/paloma_gab.yaml index fbd6a959..4ecbdc9d 100644 --- a/lm_eval/tasks/paloma/paloma_gab.yaml +++ b/lm_eval/tasks/paloma/paloma_gab.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_gab -task_alias: Gab Corpus +task_alias: Gab dataset_name: gab diff --git a/lm_eval/tasks/paloma/paloma_m2d2_s2orc_unsplit.yaml b/lm_eval/tasks/paloma/paloma_m2d2_s2orc_unsplit.yaml index 0298588e..947ec22f 100644 --- a/lm_eval/tasks/paloma/paloma_m2d2_s2orc_unsplit.yaml +++ b/lm_eval/tasks/paloma/paloma_m2d2_s2orc_unsplit.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_m2d2_s2orc_unsplit task_alias: M2D2 S2ORC dataset_name: m2d2_s2orc_unsplit diff --git a/lm_eval/tasks/paloma/paloma_m2d2_wikipedia_unsplit.yaml b/lm_eval/tasks/paloma/paloma_m2d2_wikipedia_unsplit.yaml index a3f2e243..890de2f7 100644 --- a/lm_eval/tasks/paloma/paloma_m2d2_wikipedia_unsplit.yaml +++ b/lm_eval/tasks/paloma/paloma_m2d2_wikipedia_unsplit.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_m2d2_wikipedia_unsplit task_alias: M2D2 Wikipedia dataset_name: m2d2_wikipedia_unsplit diff --git a/lm_eval/tasks/paloma/paloma_manosphere_meta_sep.yaml b/lm_eval/tasks/paloma/paloma_manosphere_meta_sep.yaml index e4dbf489..93fa2bf0 100644 --- a/lm_eval/tasks/paloma/paloma_manosphere_meta_sep.yaml +++ b/lm_eval/tasks/paloma/paloma_manosphere_meta_sep.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_manosphere_meta_sep -task_alias: Manosphere Corpus +task_alias: Manosphere dataset_name: manosphere_meta_sep diff --git a/lm_eval/tasks/paloma/paloma_mc4.yaml b/lm_eval/tasks/paloma/paloma_mc4.yaml index 7ccbea81..4cffc874 100644 --- a/lm_eval/tasks/paloma/paloma_mc4.yaml +++ b/lm_eval/tasks/paloma/paloma_mc4.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_mc4 -task_alias: mC4-en +task_alias: mC4 dataset_name: mc4 diff --git a/lm_eval/tasks/paloma/paloma_ptb.yaml b/lm_eval/tasks/paloma/paloma_ptb.yaml index 73087f5f..d0f762c3 100644 --- a/lm_eval/tasks/paloma/paloma_ptb.yaml +++ b/lm_eval/tasks/paloma/paloma_ptb.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_ptb -task_alias: Penn Treebank +task_alias: PTB dataset_name: ptb diff --git a/lm_eval/tasks/paloma/paloma_redpajama.yaml b/lm_eval/tasks/paloma/paloma_redpajama.yaml index bf4ddad5..238a04c5 100644 --- a/lm_eval/tasks/paloma/paloma_redpajama.yaml +++ b/lm_eval/tasks/paloma/paloma_redpajama.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_redpajama task_alias: RedPajama dataset_name: redpajama diff --git a/lm_eval/tasks/paloma/paloma_twitterAAE_HELM_fixed.yaml b/lm_eval/tasks/paloma/paloma_twitterAAE_HELM_fixed.yaml index 96075682..474d8417 100644 --- a/lm_eval/tasks/paloma/paloma_twitterAAE_HELM_fixed.yaml +++ b/lm_eval/tasks/paloma/paloma_twitterAAE_HELM_fixed.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_twitterAAE_HELM_fixed task_alias: Twitter AAE dataset_name: twitterAAE_HELM_fixed diff --git a/lm_eval/tasks/paloma/paloma_wikitext_103.yaml b/lm_eval/tasks/paloma/paloma_wikitext_103.yaml index b10c4dbb..4781603b 100644 --- a/lm_eval/tasks/paloma/paloma_wikitext_103.yaml +++ b/lm_eval/tasks/paloma/paloma_wikitext_103.yaml @@ -1,4 +1,4 @@ -include: paloma.yaml +include: _paloma_template task: paloma_wikitext_103 task_alias: Wikitext-103 dataset_name: wikitext_103 -- GitLab From 78a54e1448ccb8c05ab3e83c110e0386316206a2 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Wed, 19 Jun 2024 09:59:06 -0400 Subject: [PATCH 003/194] Log `fewshot_as_multiturn` in results files (#1995) * log fewshot_as_multiturn in general tracker args * Update evaluator.py --------- Co-authored-by: Lintang Sutawika --- lm_eval/evaluator.py | 1 + lm_eval/loggers/evaluation_tracker.py | 3 +++ 2 files changed, 4 insertions(+) diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index bca48c11..2378b3ea 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -271,6 +271,7 @@ def simple_evaluate( model_args=model_args, system_instruction=system_instruction, chat_template=lm.chat_template if apply_chat_template else None, + fewshot_as_multiturn=fewshot_as_multiturn, ) results = evaluate( diff --git a/lm_eval/loggers/evaluation_tracker.py b/lm_eval/loggers/evaluation_tracker.py index 985c9853..6aa7f25b 100644 --- a/lm_eval/loggers/evaluation_tracker.py +++ b/lm_eval/loggers/evaluation_tracker.py @@ -48,6 +48,7 @@ class GeneralConfigTracker: model_name_sanitized: str = None system_instruction: str = None system_instruction_sha: str = None + fewshot_as_multiturn: bool = None chat_template: str = None chat_template_sha: str = None start_time: float = None @@ -80,6 +81,7 @@ class GeneralConfigTracker: model_args: str, system_instruction: str, chat_template: str, + fewshot_as_multiturn: bool, ) -> None: """Logs model parameters and job ID.""" self.model_source = model_source @@ -91,6 +93,7 @@ class GeneralConfigTracker: ) self.chat_template = chat_template self.chat_template_sha = hash_string(chat_template) if chat_template else None + self.fewshot_as_multiturn = fewshot_as_multiturn def log_end_time(self) -> None: """Logs the end time of the evaluation and calculates the total evaluation time.""" -- GitLab From a08bc3c8bf8b3114e2e19ca93929450355523d50 Mon Sep 17 00:00:00 2001 From: Yazeed Alnumay <61038456+Yazeed7@users.noreply.github.com> Date: Wed, 19 Jun 2024 19:08:37 +0300 Subject: [PATCH 004/194] Added ArabicMMLU (#1987) * Added ArabicMMLU * Rename `ammlu` to `arabicmmlu` --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/arabicmmlu/README.md | 40 ++++++ .../tasks/arabicmmlu/_default_template_yaml | 13 ++ lm_eval/tasks/arabicmmlu/_generate_configs.py | 116 ++++++++++++++++++ lm_eval/tasks/arabicmmlu/arabicmmlu.yaml | 7 ++ .../arabicmmlu_arabic_language_general.yaml | 6 + .../arabicmmlu_arabic_language_grammar.yaml | 6 + .../arabicmmlu/arabicmmlu_driving_test.yaml | 6 + .../arabicmmlu_general_knowledge.yaml | 6 + .../arabicmmlu_high_arabic_language.yaml | 6 + .../arabicmmlu/arabicmmlu_high_biology.yaml | 6 + .../arabicmmlu/arabicmmlu_high_civics.yaml | 6 + .../arabicmmlu_high_computer_science.yaml | 6 + .../arabicmmlu/arabicmmlu_high_economics.yaml | 6 + .../arabicmmlu/arabicmmlu_high_geography.yaml | 6 + .../arabicmmlu/arabicmmlu_high_history.yaml | 6 + .../arabicmmlu_high_islamic_studies.yaml | 6 + .../arabicmmlu_high_philosophy.yaml | 6 + .../arabicmmlu/arabicmmlu_high_physics.yaml | 6 + .../arabicmmlu_islamic_studies.yaml | 6 + .../arabicmmlu_middle_arabic_language.yaml | 6 + .../arabicmmlu/arabicmmlu_middle_civics.yaml | 6 + .../arabicmmlu_middle_computer_science.yaml | 6 + .../arabicmmlu_middle_economics.yaml | 6 + .../arabicmmlu_middle_general_knowledge.yaml | 6 + .../arabicmmlu_middle_geography.yaml | 6 + .../arabicmmlu/arabicmmlu_middle_history.yaml | 6 + .../arabicmmlu_middle_islamic_studies.yaml | 6 + .../arabicmmlu_middle_natural_science.yaml | 6 + .../arabicmmlu_middle_social_science.yaml | 6 + .../arabicmmlu_primary_arabic_language.yaml | 6 + .../arabicmmlu_primary_computer_science.yaml | 6 + .../arabicmmlu_primary_general_knowledge.yaml | 6 + .../arabicmmlu_primary_geography.yaml | 6 + .../arabicmmlu_primary_history.yaml | 6 + .../arabicmmlu_primary_islamic_studies.yaml | 6 + .../arabicmmlu/arabicmmlu_primary_math.yaml | 6 + .../arabicmmlu_primary_natural_science.yaml | 6 + .../arabicmmlu_primary_social_science.yaml | 6 + .../tasks/arabicmmlu/arabicmmlu_prof_law.yaml | 6 + .../arabicmmlu_univ_accounting.yaml | 6 + .../arabicmmlu_univ_computer_science.yaml | 6 + .../arabicmmlu/arabicmmlu_univ_economics.yaml | 6 + .../arabicmmlu_univ_management.yaml | 6 + .../arabicmmlu_univ_political_science.yaml | 6 + lm_eval/tasks/arabicmmlu/utils.py | 38 ++++++ 46 files changed, 455 insertions(+) create mode 100644 lm_eval/tasks/arabicmmlu/README.md create mode 100644 lm_eval/tasks/arabicmmlu/_default_template_yaml create mode 100644 lm_eval/tasks/arabicmmlu/_generate_configs.py create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_arabic_language_general.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_arabic_language_grammar.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_driving_test.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_general_knowledge.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_high_arabic_language.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_high_biology.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_high_civics.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_high_computer_science.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_high_economics.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_high_geography.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_high_history.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_high_islamic_studies.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_high_philosophy.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_high_physics.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_islamic_studies.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_middle_arabic_language.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_middle_civics.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_middle_computer_science.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_middle_economics.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_middle_general_knowledge.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_middle_geography.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_middle_history.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_middle_islamic_studies.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_middle_natural_science.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_middle_social_science.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_primary_arabic_language.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_primary_computer_science.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_primary_general_knowledge.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_primary_geography.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_primary_history.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_primary_islamic_studies.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_primary_math.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_primary_natural_science.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_primary_social_science.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_prof_law.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_univ_accounting.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_univ_computer_science.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_univ_economics.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_univ_management.yaml create mode 100644 lm_eval/tasks/arabicmmlu/arabicmmlu_univ_political_science.yaml create mode 100644 lm_eval/tasks/arabicmmlu/utils.py diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 9d99e42f..b8dbe9db 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -11,6 +11,7 @@ | [aexams](aexams/README.md) | Tasks in Arabic related to various academic exams covering a range of subjects. | Arabic | | [agieval](agieval/README.md) | Tasks involving historical data or questions related to history and historical texts. | English, Chinese | | [anli](anli/README.md) | Adversarial natural language inference tasks designed to test model robustness. | English | +| [arabicmmlu](arabicmmlu/README.md) | Localized Arabic version of MMLU with multiple-choice questions from 40 subjects. | Arabic | | [arc](arc/README.md) | Tasks involving complex reasoning over a diverse set of questions. | English | | [arithmetic](arithmetic/README.md) | Tasks involving numerical computations and arithmetic reasoning. | English | | [asdiv](asdiv/README.md) | Tasks involving arithmetic and mathematical reasoning challenges. | English | diff --git a/lm_eval/tasks/arabicmmlu/README.md b/lm_eval/tasks/arabicmmlu/README.md new file mode 100644 index 00000000..12fd1a97 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/README.md @@ -0,0 +1,40 @@ +# ArabicMMLU + +### Paper + +Title: ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic + +Abstract: https://arxiv.org/abs/2402.12840 + +The focus of language model evaluation has +transitioned towards reasoning and knowledge intensive tasks, driven by advancements in pretraining large models. While state-of-the-art models are partially trained on large Arabic texts, evaluating their performance in Arabic remains challenging due to the limited availability of relevant datasets. To bridge this gap, we present ArabicMMLU, the first multi-task language understanding benchmark for Arabic language, sourced from school exams across diverse educational levels in different countries spanning North Africa, the Levant, and the Gulf regions. Our data comprises 40 tasks and 14,575 multiple-choice questions in Modern Standard Arabic (MSA), and is carefully constructed by collaborating with native speakers in the region. Our comprehensive evaluations of 35 models reveal substantial room for improvement, particularly among the best open-source models. Notably, BLOOMZ, mT0, LLama2, and Falcon struggle to achieve a score of 50%, while even the top-performing Arabic centric model only achieves a score of 62.3%. + +The authors of the paper conducted studies by varying the language of the initial prompt and answer keys between English and Arabic. However, they set English initial prompts and answer keys as the standard, which is the version implemented in this task. + +Homepage: https://github.com/mbzuai-nlp/ArabicMMLU + + +### Citation + +``` +@misc{koto2024arabicmmlu, + title={ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic}, + author={Fajri Koto and Haonan Li and Sara Shatnawi and Jad Doughman and Abdelrahman Boda Sadallah and Aisha Alraeesi and Khalid Almubarak and Zaid Alyafeai and Neha Sengupta and Shady Shehata and Nizar Habash and Preslav Nakov and Timothy Baldwin}, + year={2024}, + eprint={2402.12840}, + archivePrefix={arXiv}, + primaryClass={id='cs.CL' full_name='Computation and Language' is_active=True alt_name='cmp-lg' in_archive='cs' is_general=False description='Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.'} +} +``` + +### Groups and Tasks + +#### Groups + +* `arabicmmlu`: evaluates all ArabicMMLU tasks. + +* `arabicmmlu_stem`: evaluates STEM ArabicMMLU tasks. +* `arabicmmlu_stem_social_science`: evaluates social science ArabicMMLU tasks. +* `arabicmmlu_stem_humanities`: evaluates humanities ArabicMMLU tasks. +* `arabicmmlu_stem_language`: evaluates Arabic language ArabicMMLU tasks. +* `arabicmmlu_stem_other`: evaluates other ArabicMMLU tasks. \ No newline at end of file diff --git a/lm_eval/tasks/arabicmmlu/_default_template_yaml b/lm_eval/tasks/arabicmmlu/_default_template_yaml new file mode 100644 index 00000000..9af55ba7 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/_default_template_yaml @@ -0,0 +1,13 @@ +dataset_path: yazeed7/ArabicMMLU +test_split: test +fewshot_split: dev +fewshot_config: + sampler: first_n +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_choice: !function utils.doc_to_choice +doc_to_target: "Answer Key" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true diff --git a/lm_eval/tasks/arabicmmlu/_generate_configs.py b/lm_eval/tasks/arabicmmlu/_generate_configs.py new file mode 100644 index 00000000..6b45495a --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/_generate_configs.py @@ -0,0 +1,116 @@ +""" +Take in a YAML, and output all "other" splits with this YAML +""" +import argparse +import logging +import os + +import yaml +from tqdm import tqdm + + +eval_logger = logging.getLogger("lm-eval") + + +SUBJECTS = { + "Driving Test": "other", + "High Geography": "social_science", + "High History": "humanities", + "Islamic Studies": "humanities", + "Univ Accounting": "social_science", + "Primary General Knowledge": "other", + "Univ Political Science": "social_science", + "Primary Math": "stem", + "Middle General Knowledge": "other", + "High Biology": "stem", + "Primary Natural Science": "stem", + "High Economics": "social_science", + "Middle Natural Science": "stem", + "Middle Geography": "social_science", + "Primary Social Science": "social_science", + "Middle Computer Science": "stem", + "Middle Islamic Studies": "humanities", + "Primary Computer Science": "stem", + "High Physics": "stem", + "Middle Social Science": "social_science", + "Middle Civics": "social_science", + "High Computer Science": "stem", + "General Knowledge": "other", + "High Civics": "social_science", + "Prof Law": "humanities", + "High Islamic Studies": "humanities", + "Primary Arabic Language": "language", + "High Arabic Language": "language", + "Arabic Language (Grammar)": "language", + "Primary History": "humanities", + "Middle History": "humanities", + "Univ Economics": "social_science", + "Arabic Language (General)": "language", + "Univ Computer Science": "stem", + "Primary Islamic Studies": "humanities", + "Primary Geography": "social_science", + "High Philosophy": "humanities", + "Middle Arabic Language": "language", + "Middle Economics": "social_science", + "Univ Management": "other", +} + + +def parse_args(): + parser = argparse.ArgumentParser() + parser.add_argument("--base_yaml_path", default="_default_template_yaml") + parser.add_argument("--save_prefix_path", default="arabicmmlu") + return parser.parse_args() + + +if __name__ == "__main__": + args = parse_args() + + # get filename of base_yaml so we can `"include": ` it in our "other" YAMLs. + base_yaml_name = os.path.split(args.base_yaml_path)[-1] + with open(args.base_yaml_path, encoding="utf-8") as f: + base_yaml = yaml.full_load(f) + + ALL_CATEGORIES = [] + for subject, category in tqdm(SUBJECTS.items()): + if category not in ALL_CATEGORIES: + ALL_CATEGORIES.append(category) + + + # description = f"The following are multiple choice questions (with answers) about {' '.join(subject.split('_'))}.\n\n" + + yaml_dict = { + "include": base_yaml_name, + "group": f"arabicmmlu_{category}", + "group_alias": category.replace("_", " "), + "task": f"arabicmmlu_{subject.lower().replace(' ', '_')}", + "task_alias": subject, + "dataset_name": subject, + # "description": description, + } + + file_save_path = args.save_prefix_path + f"_{subject.lower().replace(' ', '_').replace('(', '').replace(')', '')}.yaml" + eval_logger.info(f"Saving yaml for subset {subject} to {file_save_path}") + with open(file_save_path, "w", encoding="utf-8") as yaml_file: + yaml.dump( + yaml_dict, + yaml_file, + allow_unicode=True, + default_style='"', + ) + + arabicmmlu_subcategories = [f"arabicmmlu_{category}" for category in ALL_CATEGORIES] + + file_save_path = args.save_prefix_path + ".yaml" + + eval_logger.info(f"Saving benchmark config to {file_save_path}") + with open(file_save_path, "w", encoding="utf-8") as yaml_file: + yaml.dump( + { + "group": "arabicmmlu", + "task": arabicmmlu_subcategories, + }, + yaml_file, + indent=4, + default_flow_style=False, + ) diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu.yaml new file mode 100644 index 00000000..89e9b3d5 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu.yaml @@ -0,0 +1,7 @@ +group: arabicmmlu +task: +- arabicmmlu_other +- arabicmmlu_social_science +- arabicmmlu_humanities +- arabicmmlu_stem +- arabicmmlu_language diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_arabic_language_general.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_arabic_language_general.yaml new file mode 100644 index 00000000..393109aa --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_arabic_language_general.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Arabic Language (General)" +"group": "arabicmmlu_language" +"group_alias": "language" +"include": "_default_template_yaml" +"task": "arabicmmlu_arabic_language_(general)" +"task_alias": "Arabic Language (General)" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_arabic_language_grammar.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_arabic_language_grammar.yaml new file mode 100644 index 00000000..b077a398 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_arabic_language_grammar.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Arabic Language (Grammar)" +"group": "arabicmmlu_language" +"group_alias": "language" +"include": "_default_template_yaml" +"task": "arabicmmlu_arabic_language_(grammar)" +"task_alias": "Arabic Language (Grammar)" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_driving_test.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_driving_test.yaml new file mode 100644 index 00000000..488633fd --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_driving_test.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Driving Test" +"group": "arabicmmlu_other" +"group_alias": "other" +"include": "_default_template_yaml" +"task": "arabicmmlu_driving_test" +"task_alias": "Driving Test" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_general_knowledge.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_general_knowledge.yaml new file mode 100644 index 00000000..b328b4f9 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_general_knowledge.yaml @@ -0,0 +1,6 @@ +"dataset_name": "General Knowledge" +"group": "arabicmmlu_other" +"group_alias": "other" +"include": "_default_template_yaml" +"task": "arabicmmlu_general_knowledge" +"task_alias": "General Knowledge" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_high_arabic_language.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_arabic_language.yaml new file mode 100644 index 00000000..3d0005a2 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_arabic_language.yaml @@ -0,0 +1,6 @@ +"dataset_name": "High Arabic Language" +"group": "arabicmmlu_language" +"group_alias": "language" +"include": "_default_template_yaml" +"task": "arabicmmlu_high_arabic_language" +"task_alias": "High Arabic Language" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_high_biology.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_biology.yaml new file mode 100644 index 00000000..1fc0b6a5 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_biology.yaml @@ -0,0 +1,6 @@ +"dataset_name": "High Biology" +"group": "arabicmmlu_stem" +"group_alias": "stem" +"include": "_default_template_yaml" +"task": "arabicmmlu_high_biology" +"task_alias": "High Biology" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_high_civics.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_civics.yaml new file mode 100644 index 00000000..c3bb13d5 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_civics.yaml @@ -0,0 +1,6 @@ +"dataset_name": "High Civics" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_high_civics" +"task_alias": "High Civics" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_high_computer_science.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_computer_science.yaml new file mode 100644 index 00000000..d85f2f8a --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_computer_science.yaml @@ -0,0 +1,6 @@ +"dataset_name": "High Computer Science" +"group": "arabicmmlu_stem" +"group_alias": "stem" +"include": "_default_template_yaml" +"task": "arabicmmlu_high_computer_science" +"task_alias": "High Computer Science" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_high_economics.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_economics.yaml new file mode 100644 index 00000000..da2519d9 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_economics.yaml @@ -0,0 +1,6 @@ +"dataset_name": "High Economics" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_high_economics" +"task_alias": "High Economics" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_high_geography.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_geography.yaml new file mode 100644 index 00000000..88ec5a02 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_geography.yaml @@ -0,0 +1,6 @@ +"dataset_name": "High Geography" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_high_geography" +"task_alias": "High Geography" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_high_history.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_history.yaml new file mode 100644 index 00000000..6cdfdefe --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_history.yaml @@ -0,0 +1,6 @@ +"dataset_name": "High History" +"group": "arabicmmlu_humanities" +"group_alias": "humanities" +"include": "_default_template_yaml" +"task": "arabicmmlu_high_history" +"task_alias": "High History" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_high_islamic_studies.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_islamic_studies.yaml new file mode 100644 index 00000000..23a7834f --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_islamic_studies.yaml @@ -0,0 +1,6 @@ +"dataset_name": "High Islamic Studies" +"group": "arabicmmlu_humanities" +"group_alias": "humanities" +"include": "_default_template_yaml" +"task": "arabicmmlu_high_islamic_studies" +"task_alias": "High Islamic Studies" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_high_philosophy.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_philosophy.yaml new file mode 100644 index 00000000..0f61e3c7 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_philosophy.yaml @@ -0,0 +1,6 @@ +"dataset_name": "High Philosophy" +"group": "arabicmmlu_humanities" +"group_alias": "humanities" +"include": "_default_template_yaml" +"task": "arabicmmlu_high_philosophy" +"task_alias": "High Philosophy" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_high_physics.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_physics.yaml new file mode 100644 index 00000000..2e510b0d --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_high_physics.yaml @@ -0,0 +1,6 @@ +"dataset_name": "High Physics" +"group": "arabicmmlu_stem" +"group_alias": "stem" +"include": "_default_template_yaml" +"task": "arabicmmlu_high_physics" +"task_alias": "High Physics" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_islamic_studies.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_islamic_studies.yaml new file mode 100644 index 00000000..d97bbdcc --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_islamic_studies.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Islamic Studies" +"group": "arabicmmlu_humanities" +"group_alias": "humanities" +"include": "_default_template_yaml" +"task": "arabicmmlu_islamic_studies" +"task_alias": "Islamic Studies" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_arabic_language.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_arabic_language.yaml new file mode 100644 index 00000000..efb6dd42 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_arabic_language.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Middle Arabic Language" +"group": "arabicmmlu_language" +"group_alias": "language" +"include": "_default_template_yaml" +"task": "arabicmmlu_middle_arabic_language" +"task_alias": "Middle Arabic Language" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_civics.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_civics.yaml new file mode 100644 index 00000000..9de4060b --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_civics.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Middle Civics" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_middle_civics" +"task_alias": "Middle Civics" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_computer_science.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_computer_science.yaml new file mode 100644 index 00000000..635d09f6 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_computer_science.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Middle Computer Science" +"group": "arabicmmlu_stem" +"group_alias": "stem" +"include": "_default_template_yaml" +"task": "arabicmmlu_middle_computer_science" +"task_alias": "Middle Computer Science" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_economics.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_economics.yaml new file mode 100644 index 00000000..ef55891e --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_economics.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Middle Economics" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_middle_economics" +"task_alias": "Middle Economics" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_general_knowledge.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_general_knowledge.yaml new file mode 100644 index 00000000..993fd832 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_general_knowledge.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Middle General Knowledge" +"group": "arabicmmlu_other" +"group_alias": "other" +"include": "_default_template_yaml" +"task": "arabicmmlu_middle_general_knowledge" +"task_alias": "Middle General Knowledge" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_geography.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_geography.yaml new file mode 100644 index 00000000..2c84a47b --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_geography.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Middle Geography" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_middle_geography" +"task_alias": "Middle Geography" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_history.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_history.yaml new file mode 100644 index 00000000..dcb84cb0 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_history.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Middle History" +"group": "arabicmmlu_humanities" +"group_alias": "humanities" +"include": "_default_template_yaml" +"task": "arabicmmlu_middle_history" +"task_alias": "Middle History" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_islamic_studies.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_islamic_studies.yaml new file mode 100644 index 00000000..273b044f --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_islamic_studies.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Middle Islamic Studies" +"group": "arabicmmlu_humanities" +"group_alias": "humanities" +"include": "_default_template_yaml" +"task": "arabicmmlu_middle_islamic_studies" +"task_alias": "Middle Islamic Studies" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_natural_science.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_natural_science.yaml new file mode 100644 index 00000000..6c7b8109 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_natural_science.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Middle Natural Science" +"group": "arabicmmlu_stem" +"group_alias": "stem" +"include": "_default_template_yaml" +"task": "arabicmmlu_middle_natural_science" +"task_alias": "Middle Natural Science" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_social_science.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_social_science.yaml new file mode 100644 index 00000000..1b71ad5f --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_middle_social_science.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Middle Social Science" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_middle_social_science" +"task_alias": "Middle Social Science" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_arabic_language.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_arabic_language.yaml new file mode 100644 index 00000000..3f13179b --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_arabic_language.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Primary Arabic Language" +"group": "arabicmmlu_language" +"group_alias": "language" +"include": "_default_template_yaml" +"task": "arabicmmlu_primary_arabic_language" +"task_alias": "Primary Arabic Language" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_computer_science.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_computer_science.yaml new file mode 100644 index 00000000..d8d92318 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_computer_science.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Primary Computer Science" +"group": "arabicmmlu_stem" +"group_alias": "stem" +"include": "_default_template_yaml" +"task": "arabicmmlu_primary_computer_science" +"task_alias": "Primary Computer Science" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_general_knowledge.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_general_knowledge.yaml new file mode 100644 index 00000000..57472db3 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_general_knowledge.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Primary General Knowledge" +"group": "arabicmmlu_other" +"group_alias": "other" +"include": "_default_template_yaml" +"task": "arabicmmlu_primary_general_knowledge" +"task_alias": "Primary General Knowledge" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_geography.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_geography.yaml new file mode 100644 index 00000000..66c01fe8 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_geography.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Primary Geography" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_primary_geography" +"task_alias": "Primary Geography" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_history.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_history.yaml new file mode 100644 index 00000000..b8c913a4 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_history.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Primary History" +"group": "arabicmmlu_humanities" +"group_alias": "humanities" +"include": "_default_template_yaml" +"task": "arabicmmlu_primary_history" +"task_alias": "Primary History" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_islamic_studies.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_islamic_studies.yaml new file mode 100644 index 00000000..a1c12653 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_islamic_studies.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Primary Islamic Studies" +"group": "arabicmmlu_humanities" +"group_alias": "humanities" +"include": "_default_template_yaml" +"task": "arabicmmlu_primary_islamic_studies" +"task_alias": "Primary Islamic Studies" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_math.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_math.yaml new file mode 100644 index 00000000..d908d580 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_math.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Primary Math" +"group": "arabicmmlu_stem" +"group_alias": "stem" +"include": "_default_template_yaml" +"task": "arabicmmlu_primary_math" +"task_alias": "Primary Math" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_natural_science.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_natural_science.yaml new file mode 100644 index 00000000..d5a513cf --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_natural_science.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Primary Natural Science" +"group": "arabicmmlu_stem" +"group_alias": "stem" +"include": "_default_template_yaml" +"task": "arabicmmlu_primary_natural_science" +"task_alias": "Primary Natural Science" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_social_science.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_social_science.yaml new file mode 100644 index 00000000..bd4cfc29 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_primary_social_science.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Primary Social Science" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_primary_social_science" +"task_alias": "Primary Social Science" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_prof_law.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_prof_law.yaml new file mode 100644 index 00000000..bd1252d0 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_prof_law.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Prof Law" +"group": "arabicmmlu_humanities" +"group_alias": "humanities" +"include": "_default_template_yaml" +"task": "arabicmmlu_prof_law" +"task_alias": "Prof Law" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_accounting.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_accounting.yaml new file mode 100644 index 00000000..2d1f3928 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_accounting.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Univ Accounting" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_univ_accounting" +"task_alias": "Univ Accounting" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_computer_science.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_computer_science.yaml new file mode 100644 index 00000000..bf1725ef --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_computer_science.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Univ Computer Science" +"group": "arabicmmlu_stem" +"group_alias": "stem" +"include": "_default_template_yaml" +"task": "arabicmmlu_univ_computer_science" +"task_alias": "Univ Computer Science" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_economics.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_economics.yaml new file mode 100644 index 00000000..ed1494e5 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_economics.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Univ Economics" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_univ_economics" +"task_alias": "Univ Economics" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_management.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_management.yaml new file mode 100644 index 00000000..d72e3532 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_management.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Univ Management" +"group": "arabicmmlu_other" +"group_alias": "other" +"include": "_default_template_yaml" +"task": "arabicmmlu_univ_management" +"task_alias": "Univ Management" diff --git a/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_political_science.yaml b/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_political_science.yaml new file mode 100644 index 00000000..fe32b63b --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/arabicmmlu_univ_political_science.yaml @@ -0,0 +1,6 @@ +"dataset_name": "Univ Political Science" +"group": "arabicmmlu_social_science" +"group_alias": "social science" +"include": "_default_template_yaml" +"task": "arabicmmlu_univ_political_science" +"task_alias": "Univ Political Science" diff --git a/lm_eval/tasks/arabicmmlu/utils.py b/lm_eval/tasks/arabicmmlu/utils.py new file mode 100644 index 00000000..c8976b49 --- /dev/null +++ b/lm_eval/tasks/arabicmmlu/utils.py @@ -0,0 +1,38 @@ +PROMPT = 'This is a {}. Select the correct answer!\n\nQuestion: {}\n{}\n\nAnswer:' + +level_en = { + 'Primary': 'primary school', + 'Middle': 'middle school', + 'High': 'high school', + 'Univ': 'university', + 'Prof': 'professional', +} + +alpa = ['A.', 'B.', 'C.', 'D.', 'E.'] + + +def doc_to_text(doc): + """ + Refactoring `prepare_data_en` to fit with the lm harness framework. + https://github.com/mbzuai-nlp/ArabicMMLU/blob/main/util_prompt.py + """ + + level = "" if not doc['Level'] else " for " + level_en[doc['Level']] + country = "" if not doc['Country'] else " in " + doc['Country'] + main_meta_data = f"{doc['Subject']} question{level}{country}" + + question = doc['Question'] if doc['Context']=="" else f"{doc['Context']}\n\n{doc['Question']}" + + options = [] + for i, opt in enumerate(['Option 1', 'Option 2', 'Option 3', 'Option 4', 'Option 5']): + if not doc[opt]: + break + options.append(f"{alpa[i]} {doc[opt]}") + + doc_text = PROMPT.format(main_meta_data, question, '\n'.join(options)) + + return doc_text + + +def doc_to_choice(doc): + return [alpa[i][0] for i in range(5) if doc[f'Option {i+1}']] \ No newline at end of file -- GitLab From d14b36e81aea4cef4defae8e64f0078e9c45dcf6 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Wed, 19 Jun 2024 12:17:15 -0400 Subject: [PATCH 005/194] Fix Datasets `--trust_remote_code` (#1998) --- lm_eval/__main__.py | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/lm_eval/__main__.py b/lm_eval/__main__.py index dd7b0396..711df07a 100644 --- a/lm_eval/__main__.py +++ b/lm_eval/__main__.py @@ -354,11 +354,17 @@ def cli_evaluate(args: Union[argparse.Namespace, None] = None) -> None: # Respect user's value passed in via CLI, otherwise default to True and add to comma-separated model args if args.trust_remote_code: - os.environ["HF_DATASETS_TRUST_REMOTE_CODE"] = str(args.trust_remote_code) - args.model_args = ( - args.model_args - + f",trust_remote_code={os.environ['HF_DATASETS_TRUST_REMOTE_CODE']}" + eval_logger.info( + "Passed `--trust_remote_code`, setting environment variable `HF_DATASETS_TRUST_REMOTE_CODE=true`" ) + # HACK: import datasets and override its HF_DATASETS_TRUST_REMOTE_CODE value internally, + # because it's already been determined based on the prior env var before launching our + # script--`datasets` gets imported by lm_eval internally before these lines can update the env. + import datasets + + datasets.config.HF_DATASETS_TRUST_REMOTE_CODE = True + + args.model_args = args.model_args + ",trust_remote_code=True" eval_logger.info(f"Selected Tasks: {task_names}") -- GitLab From 6f7b4a0588bc2217b4a3c25aa1f2ffdb02daa3b9 Mon Sep 17 00:00:00 2001 From: Julen Etxaniz Date: Thu, 20 Jun 2024 06:53:18 -0600 Subject: [PATCH 006/194] Add BertaQA dataset tasks (#1964) * add bertaqa tasks * rename basquetrivia-->bertaqa ; make template stub not .yaml * add bertaqa entry to lm_eval/tasks/README.md --------- Co-authored-by: haileyschoelkopf --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/bertaqa/README.md | 50 +++++++++++++++++++ lm_eval/tasks/bertaqa/_bertaqa_template | 15 ++++++ lm_eval/tasks/bertaqa/bertaqa_en.yaml | 4 ++ .../tasks/bertaqa/bertaqa_en_mt_gemma-7b.yaml | 4 ++ lm_eval/tasks/bertaqa/bertaqa_en_mt_hitz.yaml | 4 ++ .../tasks/bertaqa/bertaqa_en_mt_itzuli.yaml | 4 ++ .../bertaqa/bertaqa_en_mt_latxa-13b-v1.1.yaml | 4 ++ .../bertaqa/bertaqa_en_mt_latxa-13b-v1.yaml | 4 ++ .../bertaqa/bertaqa_en_mt_latxa-70b-v1.1.yaml | 4 ++ .../bertaqa/bertaqa_en_mt_latxa-70b-v1.yaml | 4 ++ .../bertaqa/bertaqa_en_mt_latxa-7b-v1.1.yaml | 4 ++ .../bertaqa/bertaqa_en_mt_latxa-7b-v1.yaml | 4 ++ .../bertaqa/bertaqa_en_mt_llama-2-13b.yaml | 4 ++ .../bertaqa/bertaqa_en_mt_llama-2-70b.yaml | 4 ++ .../bertaqa/bertaqa_en_mt_llama-2-7b.yaml | 4 ++ .../tasks/bertaqa/bertaqa_en_mt_madlad.yaml | 4 ++ lm_eval/tasks/bertaqa/bertaqa_en_mt_nllb.yaml | 4 ++ lm_eval/tasks/bertaqa/bertaqa_eu.yaml | 4 ++ 19 files changed, 130 insertions(+) create mode 100644 lm_eval/tasks/bertaqa/README.md create mode 100644 lm_eval/tasks/bertaqa/_bertaqa_template create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_gemma-7b.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_hitz.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_itzuli.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-13b-v1.1.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-13b-v1.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-70b-v1.1.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-70b-v1.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-7b-v1.1.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-7b-v1.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-13b.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-70b.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-7b.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_madlad.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_en_mt_nllb.yaml create mode 100644 lm_eval/tasks/bertaqa/bertaqa_eu.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index b8dbe9db..6a7847b1 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -20,6 +20,7 @@ | [bbh](bbh/README.md) | Tasks focused on deep semantic understanding through hypothesization and reasoning. | English, German | | [belebele](belebele/README.md) | Language understanding tasks in a variety of languages and scripts. | Multiple (122 languages) | | benchmarks | General benchmarking tasks that test a wide range of language understanding capabilities. | | +| [bertaqa](bertaqa/README.md) | Local Basque cultural trivia QA tests in English and Basque languages. | English, Basque, Basque (MT) | | [bigbench](bigbench/README.md) | Broad tasks from the BIG-bench benchmark designed to push the boundaries of large models. | Multiple | | [blimp](blimp/README.md) | Tasks testing grammatical phenomena to evaluate language model's linguistic capabilities. | English | | [ceval](ceval/README.md) | Tasks that evaluate language understanding and reasoning in an educational context. | Chinese | diff --git a/lm_eval/tasks/bertaqa/README.md b/lm_eval/tasks/bertaqa/README.md new file mode 100644 index 00000000..86aa386d --- /dev/null +++ b/lm_eval/tasks/bertaqa/README.md @@ -0,0 +1,50 @@ +# BertaQA + +### Paper + +Title: BertaQA: How Much Do Language Models Know About Local Culture? + +Abstract: https://arxiv.org/abs/2406.07302 + +Large Language Models (LLMs) exhibit extensive knowledge about the world, but most evaluations have been limited to global or anglocentric subjects. This raises the question of how well these models perform on topics relevant to other cultures, whose presence on the web is not that prominent. To address this gap, we introduce BertaQA, a multiple-choice trivia dataset that is parallel in English and Basque. The dataset consists of a local subset with questions pertinent to the Basque culture, and a global subset with questions of broader interest. We find that state-of-the-art LLMs struggle with local cultural knowledge, even as they excel on global topics. However, we show that continued pre-training in Basque significantly improves the models' performance on Basque culture, even when queried in English. To our knowledge, this is the first solid evidence of knowledge transfer from a low-resource to a high-resource language. Our analysis sheds light on the complex interplay between language and knowledge, and reveals that some prior findings do not fully hold when reassessed on local topics. Our dataset and evaluation code are available under open licenses at https://github.com/juletx/BertaQA. + +Homepage: https://github.com/juletx/BertaQA + +### Citation + +``` +@misc{etxaniz2024bertaqa, + title={BertaQA: How Much Do Language Models Know About Local Culture?}, + author={Julen Etxaniz and Gorka Azkune and Aitor Soroa and Oier Lopez de Lacalle and Mikel Artetxe}, + year={2024}, + eprint={2406.07302}, + archivePrefix={arXiv}, + primaryClass={cs.CL} +} +``` + +### Groups and Tasks + +#### Groups + +- `bertaqa`: Group of BertaQA tasks. + +#### Tasks + +- `bertaqa_eu`: Trivia questions in Basque. +- `bertaqa_en`: Trivia questions in English, human-translated from Basque. +- `bertaqa_en_mt_*`: Trivia questions in English, machine-translated from Basque with different models. + +### Checklist + +For adding novel benchmarks/datasets to the library: + +- [ ] Is the task an existing benchmark in the literature? + - [ ] Have you referenced the original paper that introduced the task? + - [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + +If other tasks on this dataset are already supported: + +- [ ] Is the "Main" variant of this task clearly denoted? +- [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +- [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/bertaqa/_bertaqa_template b/lm_eval/tasks/bertaqa/_bertaqa_template new file mode 100644 index 00000000..80cb3935 --- /dev/null +++ b/lm_eval/tasks/bertaqa/_bertaqa_template @@ -0,0 +1,15 @@ +group: bertaqa +dataset_path: HiTZ/BertaQA +dataset_name: null +validation_split: null +test_split: test +fewshot_split: test +output_type: multiple_choice +doc_to_choice: ["A", "B", "C"] +doc_to_target: answer +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/bertaqa/bertaqa_en.yaml b/lm_eval/tasks/bertaqa/bertaqa_en.yaml new file mode 100644 index 00000000..e39fb119 --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en +include: _bertaqa_template +dataset_name: en +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_gemma-7b.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_gemma-7b.yaml new file mode 100644 index 00000000..6d269225 --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_gemma-7b.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_gemma-7b +include: _bertaqa_template +dataset_name: en_mt_gemma-7b +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_hitz.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_hitz.yaml new file mode 100644 index 00000000..5ed8fa78 --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_hitz.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_hitz +include: _bertaqa_template +dataset_name: en_mt_hitz +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_itzuli.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_itzuli.yaml new file mode 100644 index 00000000..ed908266 --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_itzuli.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_itzuli +include: _bertaqa_template +dataset_name: en_mt_itzuli +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-13b-v1.1.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-13b-v1.1.yaml new file mode 100644 index 00000000..5565ab7e --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-13b-v1.1.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_latxa-13b-v1.1 +include: _bertaqa_template +dataset_name: en_mt_latxa-13b-v1.1 +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-13b-v1.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-13b-v1.yaml new file mode 100644 index 00000000..39960c1c --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-13b-v1.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_latxa-13b-v1 +include: _bertaqa_template +dataset_name: en_mt_latxa-13b-v1 +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-70b-v1.1.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-70b-v1.1.yaml new file mode 100644 index 00000000..f5ff03d5 --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-70b-v1.1.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_latxa-70b-v1.1 +include: _bertaqa_template +dataset_name: en_mt_latxa-70b-v1.1 +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-70b-v1.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-70b-v1.yaml new file mode 100644 index 00000000..51a5001a --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-70b-v1.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_latxa-70b-v1 +include: _bertaqa_template +dataset_name: en_mt_latxa-70b-v1 +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-7b-v1.1.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-7b-v1.1.yaml new file mode 100644 index 00000000..633f3a9f --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-7b-v1.1.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_latxa-7b-v1.1 +include: _bertaqa_template +dataset_name: en_mt_latxa-7b-v1.1 +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-7b-v1.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-7b-v1.yaml new file mode 100644 index 00000000..d15170c5 --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_latxa-7b-v1.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_latxa-7b-v1 +include: _bertaqa_template +dataset_name: en_mt_latxa-7b-v1 +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-13b.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-13b.yaml new file mode 100644 index 00000000..959f4397 --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-13b.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_llama-2-13b +include: _bertaqa_template +dataset_name: en_mt_llama-2-13b +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-70b.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-70b.yaml new file mode 100644 index 00000000..59d0cbb7 --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-70b.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_llama-2-70b +include: _bertaqa_template +dataset_name: en_mt_llama-2-70b +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-7b.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-7b.yaml new file mode 100644 index 00000000..f10f258a --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_llama-2-7b.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_llama-2-7b +include: _bertaqa_template +dataset_name: en_mt_llama-2-7b +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_madlad.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_madlad.yaml new file mode 100644 index 00000000..67a44a8b --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_madlad.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_madlad +include: _bertaqa_template +dataset_name: en_mt_madlad +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_en_mt_nllb.yaml b/lm_eval/tasks/bertaqa/bertaqa_en_mt_nllb.yaml new file mode 100644 index 00000000..9913f6ff --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_en_mt_nllb.yaml @@ -0,0 +1,4 @@ +task: bertaqa_en_mt_nllb +include: _bertaqa_template +dataset_name: en_mt_nllb +doc_to_text: "Question: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nAnswer:" diff --git a/lm_eval/tasks/bertaqa/bertaqa_eu.yaml b/lm_eval/tasks/bertaqa/bertaqa_eu.yaml new file mode 100644 index 00000000..51e9eae6 --- /dev/null +++ b/lm_eval/tasks/bertaqa/bertaqa_eu.yaml @@ -0,0 +1,4 @@ +task: bertaqa_eu +include: _bertaqa_template +dataset_name: eu +doc_to_text: "Galdera: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nErantzuna:" -- GitLab From 536691da2444bd35b76d3f9c9527126273a63251 Mon Sep 17 00:00:00 2001 From: achervyakov <77295913+artemorloff@users.noreply.github.com> Date: Mon, 24 Jun 2024 17:08:54 +0300 Subject: [PATCH 007/194] add tokenizer logs info (#1731) * add tokenizer logs info * add no tokenizer case * Update lm_eval/logging_utils.py Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * Update lm_eval/logging_utils.py Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * add updates * fix conflict --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- lm_eval/evaluator.py | 3 ++- lm_eval/loggers/utils.py | 17 +++++++++++++++++ 2 files changed, 19 insertions(+), 1 deletion(-) diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index 2378b3ea..d3b15c8c 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -22,7 +22,7 @@ from lm_eval.evaluator_utils import ( run_task_tests, ) from lm_eval.loggers import EvaluationTracker -from lm_eval.loggers.utils import add_env_info, get_git_commit_hash +from lm_eval.logging.utils import add_env_info, add_tokenizer_info, get_git_commit_hash from lm_eval.tasks import TaskManager, get_task_dict from lm_eval.utils import ( eval_logger, @@ -326,6 +326,7 @@ def simple_evaluate( results["git_hash"] = get_git_commit_hash() results["date"] = start_date add_env_info(results) # additional environment info to results + add_tokenizer_info(results, lm) # additional info about tokenizer return results else: return None diff --git a/lm_eval/loggers/utils.py b/lm_eval/loggers/utils.py index fd47c9ab..670cdbff 100644 --- a/lm_eval/loggers/utils.py +++ b/lm_eval/loggers/utils.py @@ -110,3 +110,20 @@ def add_env_info(storage: Dict[str, Any]): "upper_git_hash": upper_dir_commit, # in case this repo is submodule } storage.update(added_info) + + +def add_tokenizer_info(storage: Dict[str, Any], lm): + if getattr(lm, "tokenizer", False): + tokenizer_info = { + "tokenizer_pad_token": [lm.tokenizer.pad_token, lm.tokenizer.pad_token_id], + "tokenizer_eos_token": [lm.tokenizer.eos_token, lm.tokenizer.eos_token_id], + "tokenizer_bos_token": [lm.tokenizer.bos_token, lm.tokenizer.bos_token_id], + "eot_token_id": getattr(lm, "eot_token_id", None), + "max_length": getattr(lm, "max_length", None), + } + storage.update(tokenizer_info) + # seems gguf and textsynth do not have tokenizer + else: + logger.debug( + "LM does not have a 'tokenizer' attribute, not logging tokenizer metadata to results." + ) -- GitLab From 0ae3d3eb5c5bdd73fa1f3bfd979866b5110324dd Mon Sep 17 00:00:00 2001 From: Stella Biderman Date: Mon, 24 Jun 2024 11:13:47 -0400 Subject: [PATCH 008/194] Hotfix breaking import (#2015) --- lm_eval/evaluator.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index d3b15c8c..76ae5d15 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -22,7 +22,7 @@ from lm_eval.evaluator_utils import ( run_task_tests, ) from lm_eval.loggers import EvaluationTracker -from lm_eval.logging.utils import add_env_info, add_tokenizer_info, get_git_commit_hash +from lm_eval.loggers.utils import add_env_info, add_tokenizer_info, get_git_commit_hash from lm_eval.tasks import TaskManager, get_task_dict from lm_eval.utils import ( eval_logger, -- GitLab From 9b6b0f5e0b309563705376abe526887f65db7dd3 Mon Sep 17 00:00:00 2001 From: jonabur <135807120+jonabur@users.noreply.github.com> Date: Tue, 25 Jun 2024 17:52:25 +0300 Subject: [PATCH 009/194] add arc_challenge_mt (#1900) * add arc_challenge_mt * add README * add icelandic --- lm_eval/tasks/arc_mt/README.md | 12 ++++++++++ lm_eval/tasks/arc_mt/arc_challenge_mt_da.yaml | 3 +++ lm_eval/tasks/arc_mt/arc_challenge_mt_de.yaml | 3 +++ lm_eval/tasks/arc_mt/arc_challenge_mt_el.yaml | 3 +++ lm_eval/tasks/arc_mt/arc_challenge_mt_es.yaml | 3 +++ lm_eval/tasks/arc_mt/arc_challenge_mt_fi.yaml | 23 +++++++++++++++++++ lm_eval/tasks/arc_mt/arc_challenge_mt_hu.yaml | 3 +++ lm_eval/tasks/arc_mt/arc_challenge_mt_is.yaml | 22 ++++++++++++++++++ lm_eval/tasks/arc_mt/arc_challenge_mt_it.yaml | 3 +++ lm_eval/tasks/arc_mt/arc_challenge_mt_nb.yaml | 3 +++ lm_eval/tasks/arc_mt/arc_challenge_mt_pl.yaml | 3 +++ lm_eval/tasks/arc_mt/arc_challenge_mt_pt.yaml | 3 +++ lm_eval/tasks/arc_mt/arc_challenge_mt_sv.yaml | 3 +++ 13 files changed, 87 insertions(+) create mode 100644 lm_eval/tasks/arc_mt/README.md create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_da.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_de.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_el.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_es.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_fi.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_hu.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_is.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_it.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_nb.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_pl.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_pt.yaml create mode 100644 lm_eval/tasks/arc_mt/arc_challenge_mt_sv.yaml diff --git a/lm_eval/tasks/arc_mt/README.md b/lm_eval/tasks/arc_mt/README.md new file mode 100644 index 00000000..5e1c6e40 --- /dev/null +++ b/lm_eval/tasks/arc_mt/README.md @@ -0,0 +1,12 @@ +# arc mt + +arc mt is an implementation of tasks to support machine translated arc +challenge evals, to improve eval support across a number of additional +languages. + +The main page for the effort is +[here](https://huggingface.co/datasets/LumiOpen/arc_challenge_mt) and we will +include more data and analysis there. + +Initial datasets include a number of European languages, and we plan to expand +more in the future. diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_da.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_da.yaml new file mode 100644 index 00000000..f3efdc4c --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_da.yaml @@ -0,0 +1,3 @@ +include: arc_challenge_mt_fi.yaml +task: arc_challenge_mt_da +dataset_name: da diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_de.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_de.yaml new file mode 100644 index 00000000..36fdf7be --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_de.yaml @@ -0,0 +1,3 @@ +include: arc_challenge_mt_fi.yaml +task: arc_challenge_mt_de +dataset_name: de diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_el.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_el.yaml new file mode 100644 index 00000000..d97580b0 --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_el.yaml @@ -0,0 +1,3 @@ +include: arc_challenge_mt_fi.yaml +task: arc_challenge_mt_el +dataset_name: el diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_es.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_es.yaml new file mode 100644 index 00000000..7dffc6c7 --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_es.yaml @@ -0,0 +1,3 @@ +include: arc_challenge_mt_fi.yaml +task: arc_challenge_mt_es +dataset_name: es diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_fi.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_fi.yaml new file mode 100644 index 00000000..d2032e34 --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_fi.yaml @@ -0,0 +1,23 @@ +group: + - arc_challenge_mt +task: arc_challenge_mt_fi +dataset_path: LumiOpen/arc_challenge_mt +dataset_name: fi +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: test +doc_to_text: "Question: {{question}}\nAnswer:" +doc_to_target: "{{choices.label.index(answerKey)}}" +doc_to_choice: "{{choices.text}}" +should_decontaminate: true +doc_to_decontamination_query: "Question: {{question}}\nAnswer:" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_hu.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_hu.yaml new file mode 100644 index 00000000..03d5ac17 --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_hu.yaml @@ -0,0 +1,3 @@ +include: arc_challenge_mt_fi.yaml +task: arc_challenge_mt_hu +dataset_name: hu diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_is.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_is.yaml new file mode 100644 index 00000000..1591d7eb --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_is.yaml @@ -0,0 +1,22 @@ +group: + - arc_challenge_mt +task: arc_challenge_mt_is +dataset_path: mideind/icelandic-arc-challenge +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: test +doc_to_text: "Question: {{question}}\nAnswer:" +doc_to_target: "{{choices.label.index(answerKey)}}" +doc_to_choice: "{{choices.text}}" +should_decontaminate: true +doc_to_decontamination_query: "Question: {{question}}\nAnswer:" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_it.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_it.yaml new file mode 100644 index 00000000..995f7a3d --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_it.yaml @@ -0,0 +1,3 @@ +include: arc_challenge_mt_fi.yaml +task: arc_challenge_mt_it +dataset_name: it diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_nb.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_nb.yaml new file mode 100644 index 00000000..aceaa14b --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_nb.yaml @@ -0,0 +1,3 @@ +include: arc_challenge_mt_fi.yaml +task: arc_challenge_mt_nb +dataset_name: nb diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_pl.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_pl.yaml new file mode 100644 index 00000000..3b9a332f --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_pl.yaml @@ -0,0 +1,3 @@ +include: arc_challenge_mt_fi.yaml +task: arc_challenge_mt_pl +dataset_name: pl diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_pt.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_pt.yaml new file mode 100644 index 00000000..748743fc --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_pt.yaml @@ -0,0 +1,3 @@ +include: arc_challenge_mt_fi.yaml +task: arc_challenge_mt_pt +dataset_name: pt diff --git a/lm_eval/tasks/arc_mt/arc_challenge_mt_sv.yaml b/lm_eval/tasks/arc_mt/arc_challenge_mt_sv.yaml new file mode 100644 index 00000000..09d97c51 --- /dev/null +++ b/lm_eval/tasks/arc_mt/arc_challenge_mt_sv.yaml @@ -0,0 +1,3 @@ +include: arc_challenge_mt_fi.yaml +task: arc_challenge_mt_sv +dataset_name: sv -- GitLab From 9b6179b2941d42e2540dbffc9c76fb56e596f644 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Tue, 25 Jun 2024 20:36:10 +0500 Subject: [PATCH 010/194] Remove `LM` dependency from `build_all_requests` (#2011) * refactored `lm.apply_chat_template` * nit * fix weird type error * fixed! * skip failing test * pre-commit run all * add type hints * nit * nit * fixup --- lm_eval/api/task.py | 35 ++++++++++--------- lm_eval/evaluator.py | 19 ++++++---- lm_eval/evaluator_utils.py | 6 ++-- lm_eval/tasks/arabicmmlu/README.md | 4 +-- lm_eval/tasks/arabicmmlu/_generate_configs.py | 7 ++-- lm_eval/tasks/arabicmmlu/utils.py | 34 ++++++++++-------- tests/models/test_neuralmagic.py | 1 + 7 files changed, 61 insertions(+), 45 deletions(-) diff --git a/lm_eval/api/task.py b/lm_eval/api/task.py index b5cc1a85..ccfda509 100644 --- a/lm_eval/api/task.py +++ b/lm_eval/api/task.py @@ -368,15 +368,16 @@ class Task(abc.ABC): def build_all_requests( self, *, - limit=None, - rank=None, - world_size=None, - cache_requests=False, - rewrite_requests_cache=False, - system_instruction=None, - apply_chat_template=False, - fewshot_as_multiturn=False, - lm=None, + limit: Union[int, None] = None, + rank: int = 0, + world_size: int = 1, + cache_requests: bool = False, + rewrite_requests_cache: bool = False, + system_instruction: Optional[str] = None, + apply_chat_template: bool = False, + fewshot_as_multiturn: bool = False, + chat_template: Optional[Callable] = None, + tokenizer_name: str = "", ) -> None: """Build a set of Instances for a task, and store them in task.instances""" @@ -391,7 +392,7 @@ class Task(abc.ABC): if system_instruction is not None else "" ) - cache_key += f"-tokenizer{lm.tokenizer_name}" if apply_chat_template else "" + cache_key += f"-tokenizer{tokenizer_name}" cached_instances = load_from_cache(file_name=cache_key) @@ -436,7 +437,7 @@ class Task(abc.ABC): system_instruction, apply_chat_template, fewshot_as_multiturn, - lm, + chat_template, ) # TODO: we should override self.config.repeats if doing greedy gen so users don't waste time+compute @@ -1014,7 +1015,7 @@ class ConfigurableTask(Task): system_instruction: Optional[str] = None, apply_chat_template: bool = False, fewshot_as_multiturn: bool = False, - lm=None, + chat_template: Optional[Callable] = None, ) -> str: """Returns a fewshot context string that is made up of a prepended description (if provided), the `num_fewshot` number of examples, and an appended prompt example. @@ -1029,8 +1030,8 @@ class ConfigurableTask(Task): Whether to apply the chat template to the fewshot context. :param fewshot_as_multiturn: bool Whether to provide the fewshot examples as a multiturn conversation or a single user turn. - :param lm: - Language model with definition of the tokenizer/function to use for applying the chat template. + :param chat_template: Callable + Chat template to be applied to the fewshot context. :returns: str The fewshot context. """ @@ -1077,7 +1078,7 @@ class ConfigurableTask(Task): example = self.doc_to_text(doc) if apply_chat_template: if self.multiple_input: - return lm.apply_chat_template(labeled_examples) + return chat_template(labeled_examples) if isinstance(example, str): self.append_target_question( labeled_examples, example, fewshot_as_multiturn @@ -1089,7 +1090,7 @@ class ConfigurableTask(Task): for ex in example: chat = deepcopy(labeled_examples) self.append_target_question(chat, ex, fewshot_as_multiturn) - labeled_examples_list.append(lm.apply_chat_template(chat)) + labeled_examples_list.append(chat_template(chat)) return labeled_examples_list # if example is an integer, append the choice or convert to string elif isinstance(example, int): @@ -1103,7 +1104,7 @@ class ConfigurableTask(Task): labeled_examples, str(example), fewshot_as_multiturn ) # return lm.apply_chat_template(labeled_examples) - return lm.apply_chat_template(labeled_examples) + return chat_template(labeled_examples) else: if self.multiple_input: return labeled_examples diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index 76ae5d15..73226b05 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -399,7 +399,12 @@ def evaluate( system_instruction=system_instruction, apply_chat_template=apply_chat_template, fewshot_as_multiturn=fewshot_as_multiturn, - lm=lm, + chat_template=getattr(lm, "apply_chat_template") + if apply_chat_template + else None, + tokenizer_name=getattr(lm, "tokenizer_name", "") + if apply_chat_template + else "", ) eval_logger.debug( f"Task: {task_output.task_name}; number of requests on this rank: {len(task.instances)}" @@ -609,16 +614,16 @@ def evaluate( ] # compute group's pooled metric and stderr - results[group][ - metric - ] = lm_eval.api.metrics.aggregate_subtask_metrics(metrics, sizes) + results[group][metric] = ( + lm_eval.api.metrics.aggregate_subtask_metrics(metrics, sizes) + ) # TODO: calculate grouped metric using aggregation fn if "N/A" in stderrs: results[group][stderr] = "N/A" else: - results[group][ - stderr - ] = lm_eval.api.metrics.pooled_sample_stderr(stderrs, sizes) + results[group][stderr] = ( + lm_eval.api.metrics.pooled_sample_stderr(stderrs, sizes) + ) # TODO: allow GroupConfigs to choose which variance formula is used, for back-compatibility # To use the old (likely incorrect) variance formula, comment out the above and uncomment this line: # results[group][stderr] = lm_eval.api.metrics.combined_sample_stderr(stderrs, sizes, metrics=metrics) diff --git a/lm_eval/evaluator_utils.py b/lm_eval/evaluator_utils.py index ad6eb53a..a773c92e 100644 --- a/lm_eval/evaluator_utils.py +++ b/lm_eval/evaluator_utils.py @@ -275,9 +275,9 @@ def consolidate_results( metric_key ] results[task_output.task_name]["samples"] = task_output.sample_len - results[task_output.task_name][ - f"{metric}_stderr,{filter_key}" - ] = task_output.agg_metrics[f"{metric}_stderr,{filter_key}"] + results[task_output.task_name][f"{metric}_stderr,{filter_key}"] = ( + task_output.agg_metrics[f"{metric}_stderr,{filter_key}"] + ) return results, samples, configs, versions, num_fewshot, higher_is_better diff --git a/lm_eval/tasks/arabicmmlu/README.md b/lm_eval/tasks/arabicmmlu/README.md index 12fd1a97..90de14b7 100644 --- a/lm_eval/tasks/arabicmmlu/README.md +++ b/lm_eval/tasks/arabicmmlu/README.md @@ -18,7 +18,7 @@ Homepage: https://github.com/mbzuai-nlp/ArabicMMLU ``` @misc{koto2024arabicmmlu, - title={ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic}, + title={ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic}, author={Fajri Koto and Haonan Li and Sara Shatnawi and Jad Doughman and Abdelrahman Boda Sadallah and Aisha Alraeesi and Khalid Almubarak and Zaid Alyafeai and Neha Sengupta and Shady Shehata and Nizar Habash and Preslav Nakov and Timothy Baldwin}, year={2024}, eprint={2402.12840}, @@ -37,4 +37,4 @@ Homepage: https://github.com/mbzuai-nlp/ArabicMMLU * `arabicmmlu_stem_social_science`: evaluates social science ArabicMMLU tasks. * `arabicmmlu_stem_humanities`: evaluates humanities ArabicMMLU tasks. * `arabicmmlu_stem_language`: evaluates Arabic language ArabicMMLU tasks. -* `arabicmmlu_stem_other`: evaluates other ArabicMMLU tasks. \ No newline at end of file +* `arabicmmlu_stem_other`: evaluates other ArabicMMLU tasks. diff --git a/lm_eval/tasks/arabicmmlu/_generate_configs.py b/lm_eval/tasks/arabicmmlu/_generate_configs.py index 6b45495a..83e6594e 100644 --- a/lm_eval/tasks/arabicmmlu/_generate_configs.py +++ b/lm_eval/tasks/arabicmmlu/_generate_configs.py @@ -1,6 +1,7 @@ """ Take in a YAML, and output all "other" splits with this YAML """ + import argparse import logging import os @@ -76,7 +77,6 @@ if __name__ == "__main__": if category not in ALL_CATEGORIES: ALL_CATEGORIES.append(category) - # description = f"The following are multiple choice questions (with answers) about {' '.join(subject.split('_'))}.\n\n" yaml_dict = { @@ -89,7 +89,10 @@ if __name__ == "__main__": # "description": description, } - file_save_path = args.save_prefix_path + f"_{subject.lower().replace(' ', '_').replace('(', '').replace(')', '')}.yaml" + file_save_path = ( + args.save_prefix_path + + f"_{subject.lower().replace(' ', '_').replace('(', '').replace(')', '')}.yaml" + ) eval_logger.info(f"Saving yaml for subset {subject} to {file_save_path}") with open(file_save_path, "w", encoding="utf-8") as yaml_file: yaml.dump( diff --git a/lm_eval/tasks/arabicmmlu/utils.py b/lm_eval/tasks/arabicmmlu/utils.py index c8976b49..e1ed4b99 100644 --- a/lm_eval/tasks/arabicmmlu/utils.py +++ b/lm_eval/tasks/arabicmmlu/utils.py @@ -1,14 +1,14 @@ -PROMPT = 'This is a {}. Select the correct answer!\n\nQuestion: {}\n{}\n\nAnswer:' +PROMPT = "This is a {}. Select the correct answer!\n\nQuestion: {}\n{}\n\nAnswer:" level_en = { - 'Primary': 'primary school', - 'Middle': 'middle school', - 'High': 'high school', - 'Univ': 'university', - 'Prof': 'professional', + "Primary": "primary school", + "Middle": "middle school", + "High": "high school", + "Univ": "university", + "Prof": "professional", } -alpa = ['A.', 'B.', 'C.', 'D.', 'E.'] +alpa = ["A.", "B.", "C.", "D.", "E."] def doc_to_text(doc): @@ -17,22 +17,28 @@ def doc_to_text(doc): https://github.com/mbzuai-nlp/ArabicMMLU/blob/main/util_prompt.py """ - level = "" if not doc['Level'] else " for " + level_en[doc['Level']] - country = "" if not doc['Country'] else " in " + doc['Country'] + level = "" if not doc["Level"] else " for " + level_en[doc["Level"]] + country = "" if not doc["Country"] else " in " + doc["Country"] main_meta_data = f"{doc['Subject']} question{level}{country}" - question = doc['Question'] if doc['Context']=="" else f"{doc['Context']}\n\n{doc['Question']}" + question = ( + doc["Question"] + if doc["Context"] == "" + else f"{doc['Context']}\n\n{doc['Question']}" + ) options = [] - for i, opt in enumerate(['Option 1', 'Option 2', 'Option 3', 'Option 4', 'Option 5']): + for i, opt in enumerate( + ["Option 1", "Option 2", "Option 3", "Option 4", "Option 5"] + ): if not doc[opt]: break options.append(f"{alpa[i]} {doc[opt]}") - doc_text = PROMPT.format(main_meta_data, question, '\n'.join(options)) - + doc_text = PROMPT.format(main_meta_data, question, "\n".join(options)) + return doc_text def doc_to_choice(doc): - return [alpa[i][0] for i in range(5) if doc[f'Option {i+1}']] \ No newline at end of file + return [alpa[i][0] for i in range(5) if doc[f"Option {i+1}"]] diff --git a/tests/models/test_neuralmagic.py b/tests/models/test_neuralmagic.py index 5cc48ea9..e0a36cee 100644 --- a/tests/models/test_neuralmagic.py +++ b/tests/models/test_neuralmagic.py @@ -23,6 +23,7 @@ DEEPSPARSE_MODELS_TASKS = [ ] +@pytest.mark.skip(reason="test failing") @pytest.mark.parametrize("model_id,task", SPARSEML_MODELS_TASKS) def test_sparseml_eval(model_id, task): lm = get_model("sparseml").create_from_arg_string( -- GitLab From b62b9bd06db3049ef10827d3177cd9fa0c843bff Mon Sep 17 00:00:00 2001 From: Brendan Murphy Date: Tue, 25 Jun 2024 11:55:08 -0400 Subject: [PATCH 011/194] Added CommonsenseQA task (#1721) * Initial configuration * Using the validation set for the test set, because the test set on HF doesn't have labels * Probably just makes more sense to have validation be validation * fix format ; add docs to tasks/README.md * fix format --------- Co-authored-by: haileyschoelkopf --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/commonsense_qa/README.md | 60 +++++++++++++++++++++++ lm_eval/tasks/commonsense_qa/default.yaml | 12 +++++ 3 files changed, 73 insertions(+) create mode 100644 lm_eval/tasks/commonsense_qa/README.md create mode 100644 lm_eval/tasks/commonsense_qa/default.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 6a7847b1..bb04d4f2 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -26,6 +26,7 @@ | [ceval](ceval/README.md) | Tasks that evaluate language understanding and reasoning in an educational context. | Chinese | | [cmmlu](cmmlu/README.md) | Multi-subject multiple choice question tasks for comprehensive academic assessment. | Chinese | | code_x_glue | Tasks that involve understanding and generating code across multiple programming languages. | Go, Java, JS, PHP, Python, Ruby | +| [commonsense_qa](commmonsense_qa/README.md) | CommonsenseQA, a multiple-choice QA dataset for measuring commonsense knowledge. | English | | [copal_id](copal_id/README.md) | Indonesian causal commonsense reasoning dataset that captures local nuances. | Indonesian | | [coqa](coqa/README.md) | Conversational question answering tasks to test dialog understanding. | English | | [crows_pairs](crows_pairs/README.md) | Tasks designed to test model biases in various sociodemographic groups. | English, French | diff --git a/lm_eval/tasks/commonsense_qa/README.md b/lm_eval/tasks/commonsense_qa/README.md new file mode 100644 index 00000000..94ef87a5 --- /dev/null +++ b/lm_eval/tasks/commonsense_qa/README.md @@ -0,0 +1,60 @@ +# Task-name + +### Paper + +Title: `COMMONSENSEQA: A Question Answering Challenge Targeting +Commonsense Knowledge` + +Abstract: https://arxiv.org/pdf/1811.00937.pdf + +CommonsenseQA is a multiple-choice question answering dataset that requires different types of commonsense knowledge to predict the correct answers. +It contains 12,102 questions with one correct answer and four distractor answers. + +Homepage: https://www.tau-nlp.org/commonsenseqa + + +### Citation + +``` +@inproceedings{talmor-etal-2019-commonsenseqa, + title = "{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge", + author = "Talmor, Alon and + Herzig, Jonathan and + Lourie, Nicholas and + Berant, Jonathan", + booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)", + month = jun, + year = "2019", + address = "Minneapolis, Minnesota", + publisher = "Association for Computational Linguistics", + url = "https://aclanthology.org/N19-1421", + doi = "10.18653/v1/N19-1421", + pages = "4149--4158", + archivePrefix = "arXiv", + eprint = "1811.00937", + primaryClass = "cs", +} +``` + +### Groups and Tasks + +#### Groups + +* Not part of a group yet. + +#### Tasks + +* `commonsense_qa`: Represents the "random" split from the paper. Uses an MMLU-style prompt, as (presumably) used by Llama evaluations. + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [x] Is the task an existing benchmark in the literature? + * [x] Have you referenced the original paper that introduced the task? + * [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/commonsense_qa/default.yaml b/lm_eval/tasks/commonsense_qa/default.yaml new file mode 100644 index 00000000..31d31b01 --- /dev/null +++ b/lm_eval/tasks/commonsense_qa/default.yaml @@ -0,0 +1,12 @@ +task: commonsense_qa +dataset_path: tau/commonsense_qa +training_split: train +validation_split: validation +output_type: multiple_choice +doc_to_text: "Question: {{ question.strip() }}\nA. {{choices['text'][0]}}\nB. {{choices['text'][1]}}\nC. {{choices['text'][2]}}\nD. {{choices['text'][3]}}\nE. {{choices['text'][4]}}\nAnswer:" +doc_to_target: answerKey +doc_to_choice: ['A', 'B', 'C', 'D', 'E'] +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true -- GitLab From 0366c74f0db70640c307c3d9447710af5c3f5d35 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Tue, 25 Jun 2024 12:45:06 -0400 Subject: [PATCH 012/194] Factor out LM-specific tests (#1859) * separate out optimum/neuralmagic tests to separate job * fix vllm tests * fix bug in --trust_remote_code * use datasets.config instead intentionally * fix remote code issue? --- .github/workflows/unit_tests.yml | 30 ++++++++++++++++++++++++++++-- tests/models/test_vllm.py | 5 ++--- 2 files changed, 30 insertions(+), 5 deletions(-) diff --git a/.github/workflows/unit_tests.yml b/.github/workflows/unit_tests.yml index a3e25429..11570e1d 100644 --- a/.github/workflows/unit_tests.yml +++ b/.github/workflows/unit_tests.yml @@ -55,13 +55,39 @@ jobs: cache-dependency-path: pyproject.toml - name: Install dependencies run: | + export HF_DATASETS_TRUST_REMOTE_CODE=1 python -m pip install --upgrade pip - pip install -e '.[dev,anthropic,sentencepiece,optimum,deepsparse,sparseml]' --extra-index-url https://download.pytorch.org/whl/cpu + pip install -e '.[dev,anthropic,sentencepiece]' --extra-index-url https://download.pytorch.org/whl/cpu # Install optional git dependencies # pip install bleurt@https://github.com/google-research/bleurt/archive/b610120347ef22b494b6d69b4316e303f5932516.zip#egg=bleurt # if [ -f requirements.txt ]; then pip install -r requirements.txt; fi - name: Test with pytest - run: python -m pytest --showlocals -s -vv -n=auto + run: python -m pytest --showlocals -s -vv -n=auto --ignore=tests/models/test_neuralmagic.py --ignore=tests/models/test_openvino.py + - name: Archive artifacts + uses: actions/upload-artifact@v3 + with: + name: output_results + path: | + test_logs/* + testmodels: + name: External LM Tests + runs-on: ubuntu-latest + timeout-minutes: 30 + steps: + - name: Checkout Code + uses: actions/checkout@v4 + - name: Set up Python 3.8 + uses: actions/setup-python@v5 + with: + python-version: 3.8 + cache: pip + cache-dependency-path: pyproject.toml + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install -e '.[dev,optimum,deepsparse,sparseml]' --extra-index-url https://download.pytorch.org/whl/cpu + - name: Test with pytest + run: python -m pytest tests/models --showlocals -s -vv - name: Archive artifacts uses: actions/upload-artifact@v3 with: diff --git a/tests/models/test_vllm.py b/tests/models/test_vllm.py index b0440759..01363bc8 100644 --- a/tests/models/test_vllm.py +++ b/tests/models/test_vllm.py @@ -1,7 +1,6 @@ from typing import List import pytest -import torch from lm_eval import tasks from lm_eval.api.instance import Instance @@ -11,7 +10,7 @@ task_manager = tasks.TaskManager() @pytest.mark.skip(reason="requires CUDA") -class TEST_VLLM: +class Test_VLLM: vllm = pytest.importorskip("vllm") try: from lm_eval.models.vllm_causallms import VLLM @@ -19,7 +18,7 @@ class TEST_VLLM: LM = VLLM(pretrained="EleutherAI/pythia-70m") except ModuleNotFoundError: pass - torch.use_deterministic_algorithms(True) + # torch.use_deterministic_algorithms(True) task_list = task_manager.load_task_or_group(["arc_easy", "gsm8k", "wikitext"]) multiple_choice_task = task_list["arc_easy"] # type: ignore multiple_choice_task.build_all_requests(limit=10, rank=0, world_size=1) -- GitLab From 6e49b1f6910931882a4b3b105794c6faf96b74e5 Mon Sep 17 00:00:00 2001 From: johnwee1 <91670254+johnwee1@users.noreply.github.com> Date: Wed, 26 Jun 2024 01:49:08 +0800 Subject: [PATCH 013/194] Update interface.md (#1982) * Update interface.md update interface to remove link to really outdated commit of evaluator.py * switch to relative referencing? * Update interface.md --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- docs/interface.md | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/docs/interface.md b/docs/interface.md index 2add18f8..89e0397b 100644 --- a/docs/interface.md +++ b/docs/interface.md @@ -102,12 +102,10 @@ results = lm_eval.simple_evaluate( # call simple_evaluate ) ``` -See https://github.com/EleutherAI/lm-evaluation-harness/blob/365fcda9b85bbb6e0572d91976b8daf409164500/lm_eval/evaluator.py#L35 for a full description of all arguments available. All keyword arguments to simple_evaluate share the same role as the command-line flags described previously. +See the `simple_evaluate()` and `evaluate()` functions in [lm_eval/evaluator.py](../lm_eval/evaluator.py#:~:text=simple_evaluate) for a full description of all arguments available. All keyword arguments to simple_evaluate share the same role as the command-line flags described previously. Additionally, the `evaluate()` function offers the core evaluation functionality provided by the library, but without some of the special handling and simplification + abstraction provided by `simple_evaluate()`. -See https://github.com/EleutherAI/lm-evaluation-harness/blob/365fcda9b85bbb6e0572d91976b8daf409164500/lm_eval/evaluator.py#L173 for more details. - As a brief example usage of `evaluate()`: ```python -- GitLab From e5e5ee0cb629c9c88165292d1b4bf34623392d33 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Wed, 26 Jun 2024 12:40:47 -0400 Subject: [PATCH 014/194] Fix `trust_remote_code`-related test failures (#2024) * make MMLU trust remote code to fix tests * remove trust remote code --- .github/workflows/unit_tests.yml | 1 - lm_eval/tasks/mmlu/continuation/_continuation_template_yaml | 2 ++ lm_eval/tasks/mmlu/default/_default_template_yaml | 2 ++ .../mmlu/flan_cot_fewshot/_mmlu_flan_cot_fewshot_template_yaml | 2 ++ .../flan_cot_zeroshot/_mmlu_flan_cot_zeroshot_template_yaml | 2 ++ .../flan_n_shot/generative/_mmlu_flan_generative_template_yaml | 2 ++ .../loglikelihood/_mmlu_flan_loglikelihood_template_yaml | 2 ++ lm_eval/tasks/mmlu/generative/_default_template_yaml | 2 ++ 8 files changed, 14 insertions(+), 1 deletion(-) diff --git a/.github/workflows/unit_tests.yml b/.github/workflows/unit_tests.yml index 11570e1d..f9dcaf4c 100644 --- a/.github/workflows/unit_tests.yml +++ b/.github/workflows/unit_tests.yml @@ -55,7 +55,6 @@ jobs: cache-dependency-path: pyproject.toml - name: Install dependencies run: | - export HF_DATASETS_TRUST_REMOTE_CODE=1 python -m pip install --upgrade pip pip install -e '.[dev,anthropic,sentencepiece]' --extra-index-url https://download.pytorch.org/whl/cpu # Install optional git dependencies diff --git a/lm_eval/tasks/mmlu/continuation/_continuation_template_yaml b/lm_eval/tasks/mmlu/continuation/_continuation_template_yaml index b7d75e98..45e8928a 100644 --- a/lm_eval/tasks/mmlu/continuation/_continuation_template_yaml +++ b/lm_eval/tasks/mmlu/continuation/_continuation_template_yaml @@ -9,3 +9,5 @@ doc_to_choice: "{{choices}}" doc_to_target: "{{answer}}" metadata: version: 0.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/mmlu/default/_default_template_yaml b/lm_eval/tasks/mmlu/default/_default_template_yaml index 37e8bb16..0f22d02c 100644 --- a/lm_eval/tasks/mmlu/default/_default_template_yaml +++ b/lm_eval/tasks/mmlu/default/_default_template_yaml @@ -13,3 +13,5 @@ metric_list: higher_is_better: true metadata: version: 0.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu_flan_cot_fewshot_template_yaml b/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu_flan_cot_fewshot_template_yaml index ae5d41be..11850950 100644 --- a/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu_flan_cot_fewshot_template_yaml +++ b/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu_flan_cot_fewshot_template_yaml @@ -27,3 +27,5 @@ metric_list: ignore_punctuation: true metadata: version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/mmlu/flan_cot_zeroshot/_mmlu_flan_cot_zeroshot_template_yaml b/lm_eval/tasks/mmlu/flan_cot_zeroshot/_mmlu_flan_cot_zeroshot_template_yaml index ebee3b65..113d20b7 100644 --- a/lm_eval/tasks/mmlu/flan_cot_zeroshot/_mmlu_flan_cot_zeroshot_template_yaml +++ b/lm_eval/tasks/mmlu/flan_cot_zeroshot/_mmlu_flan_cot_zeroshot_template_yaml @@ -34,3 +34,5 @@ metric_list: ignore_punctuation: true metadata: version: 2.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/mmlu/flan_n_shot/generative/_mmlu_flan_generative_template_yaml b/lm_eval/tasks/mmlu/flan_n_shot/generative/_mmlu_flan_generative_template_yaml index d866b1d7..28be9cfc 100644 --- a/lm_eval/tasks/mmlu/flan_n_shot/generative/_mmlu_flan_generative_template_yaml +++ b/lm_eval/tasks/mmlu/flan_n_shot/generative/_mmlu_flan_generative_template_yaml @@ -31,3 +31,5 @@ metric_list: higher_is_better: true metadata: version: 2.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/mmlu/flan_n_shot/loglikelihood/_mmlu_flan_loglikelihood_template_yaml b/lm_eval/tasks/mmlu/flan_n_shot/loglikelihood/_mmlu_flan_loglikelihood_template_yaml index d26c69d4..8f223281 100644 --- a/lm_eval/tasks/mmlu/flan_n_shot/loglikelihood/_mmlu_flan_loglikelihood_template_yaml +++ b/lm_eval/tasks/mmlu/flan_n_shot/loglikelihood/_mmlu_flan_loglikelihood_template_yaml @@ -13,3 +13,5 @@ metric_list: higher_is_better: true metadata: version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/mmlu/generative/_default_template_yaml b/lm_eval/tasks/mmlu/generative/_default_template_yaml index aa503942..bc1ad0db 100644 --- a/lm_eval/tasks/mmlu/generative/_default_template_yaml +++ b/lm_eval/tasks/mmlu/generative/_default_template_yaml @@ -16,3 +16,5 @@ metric_list: higher_is_better: true metadata: version: 1.0 +dataset_kwargs: + trust_remote_code: true -- GitLab From 801322e0515e44eef8b555020650fc0dd2ff9112 Mon Sep 17 00:00:00 2001 From: Steven Basart Date: Fri, 28 Jun 2024 09:14:48 -0400 Subject: [PATCH 015/194] Fixes scrolls task bug with few_shot examples (#2003) Bug: ``` python -m scripts.write_out --task scrolls_quality --output_base_path ~/workspace/ Traceback (most recent call last): File "", line 198, in _run_module_as_main File "", line 88, in _run_code File "/lm-evaluation-harness/scripts/write_out.py", line 92, in main() File "/lm-evaluation-harness/scripts/write_out.py", line 51, in main task_dict = tasks.get_task_dict(task_names, task_manager) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/lm-evaluation-harness/lm_eval/tasks/__init__.py", line 423, in get_task_dict task_name_from_string_dict = task_manager.load_task_or_group( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/lm-evaluation-harness/lm_eval/tasks/__init__.py", line 271, in load_task_or_group collections.ChainMap(*map(self._load_individual_task_or_group, task_list)) File "/lm-evaluation-harness/lm_eval/tasks/__init__.py", line 162, in _load_individual_task_or_group return load_task(task_config, task=name_or_config, group=parent_name) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/lm-evaluation-harness/lm_eval/tasks/__init__.py", line 148, in load_task task_object = config["class"]() ^^^^^^^^^^^^^^^^^ File "/lm-evaluation-harness/lm_eval/tasks/scrolls/task.py", line 120, in __init__ super().__init__() File "/lm-evaluation-harness/lm_eval/api/task.py", line 703, in __init__ self._config = TaskConfig(**config) ^^^^^^^^^^^^^^^^^^^^ TypeError: lm_eval.api.task.TaskConfig() argument after ** must be a mapping, not NoneType ``` --- lm_eval/tasks/scrolls/task.py | 30 ++++++++++++++++++++++-------- 1 file changed, 22 insertions(+), 8 deletions(-) diff --git a/lm_eval/tasks/scrolls/task.py b/lm_eval/tasks/scrolls/task.py index 5b604e15..bbf1a3c3 100644 --- a/lm_eval/tasks/scrolls/task.py +++ b/lm_eval/tasks/scrolls/task.py @@ -4,12 +4,12 @@ from functools import reduce import numpy as np import transformers.data.metrics.squad_metrics as squad_metrics -from datasets import load_metric +from datasets import Dataset, load_metric from transformers import AutoTokenizer from lm_eval.api.instance import Instance from lm_eval.api.metrics import mean -from lm_eval.api.task import Task +from lm_eval.api.task import ConfigurableTask _CITATION = """ @@ -108,7 +108,7 @@ def _num_cpu_cores(): return len(os.sched_getaffinity(0)) -class _SCROLLSTask(Task): +class _SCROLLSTask(ConfigurableTask): VERSION = 2 DATASET_PATH = "tau/scrolls" DATASET_NAME = None @@ -117,7 +117,7 @@ class _SCROLLSTask(Task): PRUNE_NUM_PROC = None def __init__(self): - super().__init__() + super().__init__(config={"metadata": {"version": self.VERSION}}) if self.DATASET_NAME is not None: self.metric = load_metric(_download_metric(), config_name=self.DATASET_NAME) @@ -131,12 +131,26 @@ class _SCROLLSTask(Task): return False def training_docs(self): - for doc in self.dataset["train"]: - yield from self._process_doc(doc) + processed_docs = list(map(self._process_doc, self.dataset["train"])) + + # Flatten the list of lists since _process_doc returns a list of one element. + processed_docs = [item for sublist in processed_docs for item in sublist] + processed_dict = { + key: [d[key] for d in processed_docs] for key in processed_docs[0] + } + + return Dataset.from_dict(processed_dict) def validation_docs(self): - for doc in self.dataset["validation"]: - yield from self._process_doc(doc) + processed_docs = list(map(self._process_doc, self.dataset["validation"])) + + # Flatten the list of lists since _process_doc returns a list of one element. + processed_docs = [item for sublist in processed_docs for item in sublist] + processed_dict = { + key: [d[key] for d in processed_docs] for key in processed_docs[0] + } + + return Dataset.from_dict(processed_dict) def should_decontaminate(self): return True -- GitLab From e922cceb58bdcad6c2426ba237f8fcc3a8fc293d Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Fri, 28 Jun 2024 22:15:39 +0500 Subject: [PATCH 016/194] fix cache (#2037) --- lm_eval/api/model.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/lm_eval/api/model.py b/lm_eval/api/model.py index 7152441b..5eecc617 100644 --- a/lm_eval/api/model.py +++ b/lm_eval/api/model.py @@ -246,9 +246,10 @@ class CachingLM: # add hook to lm lm.set_cache_hook(self.get_cache_hook()) - def __getattr__(self, attr): + def __getattr__(self, attr: str): lm_attr = getattr(self.lm, attr) - if not callable(lm_attr): + if attr not in ["loglikelihood", "loglikelihood_rolling", "generate_until"]: + eval_logger.debug(f"Passing through attribute '{attr}' to underlying LM") return lm_attr def fn(requests): -- GitLab From cc2d3463c2d5aa28f2b26c40d0ff20c878cc56b8 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Fri, 28 Jun 2024 22:21:49 +0500 Subject: [PATCH 017/194] Add chat template to `vllm` (#2034) * add chat template * refactor token padding * nit * nit * check on failing test * check transformers version * remove transformers pin * add ids to test * nit * fixup * fix bos bug * nit * fixup! fix bos bug * increase tolerance for table test * don't detokenize vllm logprobs * Update lm_eval/models/utils.py Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * pre-commit run --all-files --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- lm_eval/models/huggingface.py | 24 ++------------ lm_eval/models/utils.py | 51 +++++++++++++++++++++++++++++ lm_eval/models/vllm_causallms.py | 56 ++++++++++++++++++++++++-------- lm_eval/tasks/scrolls/task.py | 6 ++-- tests/test_evaluator.py | 4 ++- 5 files changed, 101 insertions(+), 40 deletions(-) diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 46418d9a..8c125f71 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -30,6 +30,7 @@ from lm_eval.api.registry import register_model from lm_eval.models.utils import ( Collator, clear_torch_cache, + configure_pad_token, get_dtype, pad_and_concat, stop_sequences_criteria, @@ -253,28 +254,7 @@ class HFLM(TemplateLM): self.logits_cache = logits_cache self.vocab_size = self.tokenizer.vocab_size # select (or create) a pad token to use - if self.tokenizer.pad_token: - pass - elif self.tokenizer.unk_token: - self.tokenizer.pad_token_id = self.tokenizer.unk_token_id - elif self.tokenizer.eos_token: - self.tokenizer.pad_token_id = self.tokenizer.eos_token_id - else: - if getattr(self.config, "model_type", None) == "qwen": - # Qwen's trust_remote_code tokenizer does not allow for adding special tokens - self.tokenizer.pad_token = "<|endoftext|>" - elif ( - self.tokenizer.__class__.__name__ == "RWKVWorldTokenizer" - or self.tokenizer.__class__.__name__ == "Rwkv5Tokenizer" - ): - # The RWKV world tokenizer, does not allow for adding special tokens / setting the pad token (which is set as 0) - # The additional tokenizer name check is needed, as there exists rwkv4 models with neox tokenizer - # --- - # Note that the world tokenizer class name, might change in the future for the final huggingface merge - # https://github.com/huggingface/transformers/pull/26963 - assert self.tokenizer.pad_token_id == 0 - else: - self.tokenizer.add_special_tokens({"pad_token": "<|pad|>"}) + self.tokenizer = configure_pad_token(self.tokenizer, model_config=self.config) # TODO: override this for Gemma self.add_bos_token = add_bos_token diff --git a/lm_eval/models/utils.py b/lm_eval/models/utils.py index 09818f4e..8a81e5de 100644 --- a/lm_eval/models/utils.py +++ b/lm_eval/models/utils.py @@ -5,6 +5,7 @@ import itertools import time from functools import wraps from typing import ( + TYPE_CHECKING, Any, Callable, Dict, @@ -24,6 +25,11 @@ import transformers from lm_eval.utils import eval_logger +if TYPE_CHECKING: + from transformers import PreTrainedTokenizerBase + from transformers.configuration_utils import PretrainedConfig + + def chunks(iter, n: int = 0, fn=None): """ Divides an iterable into chunks of specified size or based on a given function. @@ -613,3 +619,48 @@ class Collator: if arr: yield arr + + +def configure_pad_token( + tokenizer: "PreTrainedTokenizerBase", + model_config: Optional["PretrainedConfig"] = None, +) -> "PreTrainedTokenizerBase": + """ + This function checks if the (Hugging Face) tokenizer has a padding token and sets it if not present. + Some tokenizers require special handling. + + Args: + tokenizer: The tokenizer for which the padding token is to be handled. + model_config: The configuration of the model. Default is None. + + Returns: + The tokenizer after the padding token has been handled. + + Raises: + AssertionError: If the tokenizer is of type RWKVWorldTokenizer or Rwkv5Tokenizer and the padding token id is not 0. + """ + if tokenizer.pad_token: + pass + elif tokenizer.unk_token: + tokenizer.pad_token_id = tokenizer.unk_token_id + elif tokenizer.eos_token: + tokenizer.pad_token_id = tokenizer.eos_token_id + else: + # handle special cases + if model_config and getattr(model_config, "model_type", None) == "qwen": + # Qwen's trust_remote_code tokenizer does not allow for adding special tokens + tokenizer.pad_token = "<|endoftext|>" + elif ( + tokenizer.__class__.__name__ == "RWKVWorldTokenizer" + or tokenizer.__class__.__name__ == "Rwkv5Tokenizer" + ): + # The RWKV world tokenizer, does not allow for adding special tokens / setting the pad token (which is set as 0) + # The additional tokenizer name check is needed, as there exists rwkv4 models with neox tokenizer + # --- + # Note that the world tokenizer class name, might change in the future for the final huggingface merge + # https://github.com/huggingface/transformers/pull/26963 + assert tokenizer.pad_token_id == 0 + else: + tokenizer.add_special_tokens({"pad_token": "<|pad|>"}) + + return tokenizer diff --git a/lm_eval/models/vllm_causallms.py b/lm_eval/models/vllm_causallms.py index 34a63bf2..c8819d7f 100644 --- a/lm_eval/models/vllm_causallms.py +++ b/lm_eval/models/vllm_causallms.py @@ -1,7 +1,7 @@ import copy from importlib.metadata import version from importlib.util import find_spec -from typing import List, Literal, Optional, Tuple, Union +from typing import TYPE_CHECKING, Dict, List, Literal, Optional, Tuple, Union from more_itertools import distribute from packaging.version import parse as parse_version @@ -10,7 +10,7 @@ from tqdm import tqdm from lm_eval.api.instance import Instance from lm_eval.api.model import TemplateLM from lm_eval.api.registry import register_model -from lm_eval.models.utils import Collator, undistribute +from lm_eval.models.utils import Collator, configure_pad_token, undistribute from lm_eval.utils import ( eval_logger, get_rolling_token_windows, @@ -26,6 +26,8 @@ try: except ModuleNotFoundError: pass +if TYPE_CHECKING: + pass eval_logger = eval_logger @@ -118,6 +120,7 @@ class VLLM(TemplateLM): trust_remote_code=trust_remote_code, tokenizer_revision=tokenizer_revision, ) + self.tokenizer = configure_pad_token(self.tokenizer) self.add_bos_token = add_bos_token if "gemma" in pretrained.lower(): self.add_bos_token = True @@ -176,23 +179,46 @@ class VLLM(TemplateLM): def max_gen_toks(self): return self._max_gen_toks + def apply_chat_template(self, chat_history: List[Dict[str, str]]) -> str: + """ + Method to apply a chat template to a list of chat history between user and model. + """ + return self.tokenizer.apply_chat_template( + chat_history, tokenize=False, add_generation_prompt=True + ) + + @property + def chat_template(self) -> str: + if self.tokenizer.chat_template is not None: + return self.tokenizer.chat_template + return self.tokenizer.default_chat_template + + @property + def tokenizer_name(self) -> str: + return self.tokenizer.name_or_path.replace("/", "__") + def tok_encode( self, - string: str, - left_truncate_len=None, - add_special_tokens=None, - truncation=False, - ): - """ """ + string: Union[str, List[str]], + left_truncate_len: int = None, + add_special_tokens: bool = False, + truncation: bool = False, + ) -> Union[List[int], List[List[int]]]: if not add_special_tokens: add_special_tokens = False or self.add_bos_token - encoding = self.tokenizer.encode( - string, add_special_tokens=add_special_tokens, truncation=truncation - ) + encoding: Union[List[List[int]], List[int]] = self.tokenizer( + string, + add_special_tokens=add_special_tokens, + truncation=truncation, + return_attention_mask=False, + ).input_ids # left-truncate the encoded context to be at most `left_truncate_len` tokens long if left_truncate_len: - encoding = encoding[-left_truncate_len:] + if not isinstance(string, str): + encoding = [enc[-left_truncate_len:] for enc in encoding] + else: + encoding = encoding[-left_truncate_len:] return encoding @@ -209,7 +235,7 @@ class VLLM(TemplateLM): sampling_params = SamplingParams(max_tokens=max_tokens, stop=stop, **kwargs) else: sampling_params = SamplingParams( - temperature=0, prompt_logprobs=1, max_tokens=1 + temperature=0, prompt_logprobs=1, max_tokens=1, detokenize=False ) if self.data_parallel_size > 1: # vLLM hangs if tensor_parallel > 1 and resources are set in ray.remote @@ -290,7 +316,9 @@ class VLLM(TemplateLM): # batch tokenize contexts context, all_gen_kwargs = zip(*(req.args for req in requests)) - context_encoding = self.tokenizer(context, add_special_tokens=False).input_ids + context_encoding: List[List[int]] = self.tok_encode( + context, add_special_tokens=self.add_bos_token + ) requests = [ ((a, b), c) for a, b, c in zip(context, context_encoding, all_gen_kwargs) ] diff --git a/lm_eval/tasks/scrolls/task.py b/lm_eval/tasks/scrolls/task.py index bbf1a3c3..2940eb2e 100644 --- a/lm_eval/tasks/scrolls/task.py +++ b/lm_eval/tasks/scrolls/task.py @@ -132,7 +132,7 @@ class _SCROLLSTask(ConfigurableTask): def training_docs(self): processed_docs = list(map(self._process_doc, self.dataset["train"])) - + # Flatten the list of lists since _process_doc returns a list of one element. processed_docs = [item for sublist in processed_docs for item in sublist] processed_dict = { @@ -143,13 +143,13 @@ class _SCROLLSTask(ConfigurableTask): def validation_docs(self): processed_docs = list(map(self._process_doc, self.dataset["validation"])) - + # Flatten the list of lists since _process_doc returns a list of one element. processed_docs = [item for sublist in processed_docs for item in sublist] processed_dict = { key: [d[key] for d in processed_docs] for key in processed_docs[0] } - + return Dataset.from_dict(processed_dict) def should_decontaminate(self): diff --git a/tests/test_evaluator.py b/tests/test_evaluator.py index d5edf9ae..71e25555 100644 --- a/tests/test_evaluator.py +++ b/tests/test_evaluator.py @@ -33,6 +33,7 @@ os.environ["TOKENIZERS_PARALLELISM"] = "false" 10000, ), ], + ids=lambda d: f"{d}", ) def test_evaluator( task_name: List[str], limit: int, model: str, model_args: str, bootstrap_iters: int @@ -107,6 +108,7 @@ def test_evaluator( "pretrained=EleutherAI/pythia-14m,dtype=float32,device=cpu", ), ], + ids=lambda d: f"{d}", ) def test_printed_results(task_name: List[str], limit: int, model: str, model_args: str): results = evaluator.simple_evaluate( @@ -144,6 +146,6 @@ def test_printed_results(task_name: List[str], limit: int, model: str, model_arg try: t1_item = float(t1_item) t2_item = float(t2_item) - assert abs(t1_item - t2_item) < 0.1 + assert abs(t1_item - t2_item) < 0.3 except ValueError: assert t1_item == t2_item -- GitLab From 2a6acc88a0c31be7734aec85b17555323b70c049 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Sat, 29 Jun 2024 08:53:58 -0400 Subject: [PATCH 018/194] fail gracefully upon tokenizer logging failure (#2038) --- lm_eval/loggers/utils.py | 32 +++++++++++++++++++++++--------- 1 file changed, 23 insertions(+), 9 deletions(-) diff --git a/lm_eval/loggers/utils.py b/lm_eval/loggers/utils.py index 670cdbff..348175a9 100644 --- a/lm_eval/loggers/utils.py +++ b/lm_eval/loggers/utils.py @@ -114,15 +114,29 @@ def add_env_info(storage: Dict[str, Any]): def add_tokenizer_info(storage: Dict[str, Any], lm): if getattr(lm, "tokenizer", False): - tokenizer_info = { - "tokenizer_pad_token": [lm.tokenizer.pad_token, lm.tokenizer.pad_token_id], - "tokenizer_eos_token": [lm.tokenizer.eos_token, lm.tokenizer.eos_token_id], - "tokenizer_bos_token": [lm.tokenizer.bos_token, lm.tokenizer.bos_token_id], - "eot_token_id": getattr(lm, "eot_token_id", None), - "max_length": getattr(lm, "max_length", None), - } - storage.update(tokenizer_info) - # seems gguf and textsynth do not have tokenizer + try: + tokenizer_info = { + "tokenizer_pad_token": [ + lm.tokenizer.pad_token, + lm.tokenizer.pad_token_id, + ], + "tokenizer_eos_token": [ + lm.tokenizer.eos_token, + lm.tokenizer.eos_token_id, + ], + "tokenizer_bos_token": [ + lm.tokenizer.bos_token, + lm.tokenizer.bos_token_id, + ], + "eot_token_id": getattr(lm, "eot_token_id", None), + "max_length": getattr(lm, "max_length", None), + } + storage.update(tokenizer_info) + except Exception as err: + logger.debug( + f"Logging detailed tokenizer info failed with {err}, skipping..." + ) + # seems gguf and textsynth do not have tokenizer else: logger.debug( "LM does not have a 'tokenizer' attribute, not logging tokenizer metadata to results." -- GitLab From a8ac0446b854970d7eca5e5c2b612e59c0af707a Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Mon, 1 Jul 2024 09:36:15 -0400 Subject: [PATCH 019/194] ship with exact_match function already used ; don't call evaluate.load() on import (#2045) --- lm_eval/api/metrics.py | 60 +++++++++++++++++++++++++++++++++++++++--- 1 file changed, 57 insertions(+), 3 deletions(-) diff --git a/lm_eval/api/metrics.py b/lm_eval/api/metrics.py index 27b60ed1..1daf3847 100644 --- a/lm_eval/api/metrics.py +++ b/lm_eval/api/metrics.py @@ -1,10 +1,11 @@ import logging import math import random +import re +import string from collections.abc import Iterable from typing import List -import evaluate as hf_evaluate import numpy as np import sacrebleu import sklearn.metrics @@ -166,7 +167,60 @@ def acc_mutual_info_fn(items): # This is a passthrough function return items -exact_match = hf_evaluate.load("exact_match") +### the code used in the `exact_match_hf_evaluate` function is ported from +### https://github.com/huggingface/evaluate/blob/main/metrics/exact_match/exact_match.py +### which is under the apache license. + +# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +def exact_match_hf_evaluate( + predictions, + references, + regexes_to_ignore=None, + ignore_case=False, + ignore_punctuation=False, + ignore_numbers=False, +): + if regexes_to_ignore is not None: + for s in regexes_to_ignore: + predictions = np.array([re.sub(s, "", x) for x in predictions]) + references = np.array([re.sub(s, "", x) for x in references]) + else: + predictions = np.asarray(predictions) + references = np.asarray(references) + + if ignore_case: + predictions = np.char.lower(predictions) + references = np.char.lower(references) + + if ignore_punctuation: + repl_table = string.punctuation.maketrans("", "", string.punctuation) + predictions = np.char.translate(predictions, table=repl_table) + references = np.char.translate(references, table=repl_table) + + if ignore_numbers: + repl_table = string.digits.maketrans("", "", string.digits) + predictions = np.char.translate(predictions, table=repl_table) + references = np.char.translate(references, table=repl_table) + + score_list = predictions == references + + return {"exact_match": np.mean(score_list)} + + +### @register_metric( @@ -176,7 +230,7 @@ exact_match = hf_evaluate.load("exact_match") aggregation="mean", ) def exact_match_fn(**kwargs): - return exact_match.compute(**kwargs) + return exact_match_hf_evaluate(**kwargs) @register_metric( -- GitLab From 3fa4fd725c8a428710109f1d6c14eda37e95baea Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Mon, 1 Jul 2024 09:50:22 -0400 Subject: [PATCH 020/194] update to v0.4.3 (#2046) --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 3818a1a8..040a9b7c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "lm_eval" -version = "0.4.2" +version = "0.4.3" authors = [ {name="EleutherAI", email="contact@eleuther.ai"} ] -- GitLab From e83e891d186f0797640c656501b023104852831d Mon Sep 17 00:00:00 2001 From: Ogundepo Odunayo Date: Mon, 1 Jul 2024 13:16:09 -0400 Subject: [PATCH 021/194] fix wandb logger module import in example (#2041) --- examples/visualize-wandb.ipynb | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/examples/visualize-wandb.ipynb b/examples/visualize-wandb.ipynb index b6ac47ce..d0113d55 100644 --- a/examples/visualize-wandb.ipynb +++ b/examples/visualize-wandb.ipynb @@ -110,13 +110,15 @@ "cell_type": "markdown", "id": "e974cabdbe70b667", "metadata": {}, - "source": "" + "source": [] }, { "cell_type": "markdown", "id": "5178ca9445b844e4", "metadata": {}, - "source": "W&B can also be initialized programmatically for use outside the CLI to parse and log the results." + "source": [ + "W&B can also be initialized programmatically for use outside the CLI to parse and log the results." + ] }, { "cell_type": "code", @@ -126,7 +128,7 @@ "outputs": [], "source": [ "import lm_eval\n", - "from lm_eval.logging_utils import WandbLogger\n", + "from lm_eval.loggers import WandbLogger\n", "\n", "results = lm_eval.simple_evaluate(\n", " model=\"hf\",\n", -- GitLab From 9088a68fac0d94ab028a23de47f9d499db70cc62 Mon Sep 17 00:00:00 2001 From: Nathan Habib <30601243+NathanHB@users.noreply.github.com> Date: Mon, 1 Jul 2024 19:50:26 +0200 Subject: [PATCH 022/194] Fix strip whitespace filter (#2048) * batch commit * :Revert "batch commit" This reverts commit d859d1ca3bc2d6e45979ec51379df119f2a9633d. * batch commit * checkout from main * checkout from main * checkout from main * checkout from main * checkout from main * cleanup * cleanup * cleanup * cleanup * cleanup * cleanup --- lm_eval/filters/extraction.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/lm_eval/filters/extraction.py b/lm_eval/filters/extraction.py index 9230808a..41dc6208 100644 --- a/lm_eval/filters/extraction.py +++ b/lm_eval/filters/extraction.py @@ -62,11 +62,8 @@ class WhitespaceFilter(Filter): def filter_set(inst): filtered_resp = [] for resp in inst: - if resp.startswith(" "): - resp = resp[1:] - + resp = resp.lstrip() filtered_resp.append(resp) - return filtered_resp filtered_resps = [filter_set(resp) for resp in resps] -- GitLab From 67a990e7345d4ba940e8281ac7c9113ccef2a446 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Mon, 1 Jul 2024 22:26:25 -0400 Subject: [PATCH 023/194] update gemma-2 default BOS behavior (#2049) --- lm_eval/models/huggingface.py | 3 +-- lm_eval/models/vllm_causallms.py | 2 +- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 8c125f71..331684f5 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -256,9 +256,8 @@ class HFLM(TemplateLM): # select (or create) a pad token to use self.tokenizer = configure_pad_token(self.tokenizer, model_config=self.config) - # TODO: override this for Gemma self.add_bos_token = add_bos_token - if getattr(self.config, "model_type", None) == "gemma": + if getattr(self.config, "model_type", None) in ["gemma", "gemma2"]: self.add_bos_token = True eval_logger.info( f"Model type is '{self.config.model_type}', a BOS token will be used as Gemma underperforms without it." diff --git a/lm_eval/models/vllm_causallms.py b/lm_eval/models/vllm_causallms.py index c8819d7f..1a1067cc 100644 --- a/lm_eval/models/vllm_causallms.py +++ b/lm_eval/models/vllm_causallms.py @@ -125,7 +125,7 @@ class VLLM(TemplateLM): if "gemma" in pretrained.lower(): self.add_bos_token = True eval_logger.info( - "Found 'gemma' in model name, a BOS token will be used as Gemma underperforms without it." + "Found 'gemma' in model name, a BOS token will be used as Gemma series models underperform without it." ) self.custom_prefix_token_id = prefix_token_id -- GitLab From 1870ee4e5352ce4c29de23469c2932c356a1b87f Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Wed, 3 Jul 2024 04:54:03 -0400 Subject: [PATCH 024/194] Update hellaswag.yaml (#2029) --- lm_eval/tasks/hellaswag/hellaswag.yaml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/lm_eval/tasks/hellaswag/hellaswag.yaml b/lm_eval/tasks/hellaswag/hellaswag.yaml index ec627da7..577ca69e 100644 --- a/lm_eval/tasks/hellaswag/hellaswag.yaml +++ b/lm_eval/tasks/hellaswag/hellaswag.yaml @@ -20,3 +20,5 @@ metric_list: higher_is_better: true metadata: version: 1.0 +dataset_kwargs: + trust_remote_code: true -- GitLab From 3c8db1bb7be5662e4fd5b48a26b6214f758e483f Mon Sep 17 00:00:00 2001 From: Nathan Habib <30601243+NathanHB@users.noreply.github.com> Date: Wed, 3 Jul 2024 14:15:49 +0200 Subject: [PATCH 025/194] Adds Open LLM Leaderboard Taks (#2047) * adds leaderboard tasks * Delete lm_eval/tasks/leaderboard/leaderboard_chat_template.yaml * add readme * Delete lm_eval/tasks/leaderboard/mmlu_pro/mmlu_pro_chat_template.yaml * modify readme * fix bbh task * fix bbh salient task * modify the readme * Delete lm_eval/tasks/leaderboard/ifeval/README.md * Delete lm_eval/tasks/leaderboard/math/README.md * add leaderboard to the tasks repertory * add anouncment about new leaderbaord tasks * linting * Update README.md Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * installs ifeval dependency in new_task github workflow --------- Co-authored-by: Nathan Habib Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- .github/workflows/new_tasks.yml | 2 +- README.md | 1 + lm_eval/tasks/README.md | 1 + lm_eval/tasks/leaderboard/README.md | 319 ++++ .../leaderboard/bbh_mc/_fewshot_template_yaml | 17 + .../bbh_mc/boolean_expressions.yaml | 16 + .../leaderboard/bbh_mc/causal_judgement.yaml | 64 + .../bbh_mc/date_understanding.yaml | 57 + .../leaderboard/bbh_mc/disambiguation_qa.yaml | 50 + .../leaderboard/bbh_mc/formal_fallacies.yaml | 57 + .../leaderboard/bbh_mc/geometric_shapes.yaml | 86 + .../tasks/leaderboard/bbh_mc/hyperbaton.yaml | 34 + .../logical_deduction_five_objects.yaml | 52 + .../logical_deduction_seven_objects.yaml | 52 + .../logical_deduction_three_objects.yaml | 52 + .../bbh_mc/movie_recommendation.yaml | 54 + .../tasks/leaderboard/bbh_mc/navigate.yaml | 40 + .../leaderboard/bbh_mc/object_counting.yaml | 20 + .../bbh_mc/penguins_in_a_table.yaml | 68 + .../reasoning_about_colored_objects.yaml | 116 ++ .../tasks/leaderboard/bbh_mc/ruin_names.yaml | 50 + .../salient_translation_error_detection.yaml | 103 + lm_eval/tasks/leaderboard/bbh_mc/snarks.yaml | 45 + .../bbh_mc/sports_understanding.yaml | 19 + .../bbh_mc/temporal_sequences.yaml | 101 + ...racking_shuffled_objects_five_objects.yaml | 59 + ...acking_shuffled_objects_seven_objects.yaml | 59 + ...acking_shuffled_objects_three_objects.yaml | 59 + .../tasks/leaderboard/bbh_mc/web_of_lies.yaml | 22 + lm_eval/tasks/leaderboard/gpqa/_template_yaml | 20 + .../gpqa/gpqa_diamond_zeroshot.yaml | 4 + .../gpqa/gpqa_extended_zeroshot.yaml | 4 + .../leaderboard/gpqa/gpqa_main_zeroshot.yaml | 4 + lm_eval/tasks/leaderboard/gpqa/utils.py | 38 + lm_eval/tasks/leaderboard/ifeval/ifeval.yaml | 32 + .../tasks/leaderboard/ifeval/instructions.py | 1612 ++++++++++++++++ .../ifeval/instructions_registry.py | 168 ++ .../leaderboard/ifeval/instructions_util.py | 1682 +++++++++++++++++ lm_eval/tasks/leaderboard/ifeval/utils.py | 134 ++ lm_eval/tasks/leaderboard/leaderboard.yaml | 8 + lm_eval/tasks/leaderboard/math/_template_yaml | 28 + .../tasks/leaderboard/math/math_algebra.yaml | 3 + .../math/math_counting_and_prob.yaml | 3 + .../tasks/leaderboard/math/math_geometry.yaml | 3 + .../math/math_intermediate_algebra.yaml | 3 + .../leaderboard/math/math_num_theory.yaml | 3 + .../leaderboard/math/math_prealgebra.yaml | 3 + .../leaderboard/math/math_precalculus.yaml | 3 + lm_eval/tasks/leaderboard/math/utils.py | 294 +++ .../tasks/leaderboard/mmlu_pro/mmlu_pro.yaml | 17 + lm_eval/tasks/leaderboard/mmlu_pro/utils.py | 15 + lm_eval/tasks/leaderboard/musr/_template_yaml | 13 + .../musr/musr_murder_mysteries.yaml | 3 + .../musr/musr_object_placements.yaml | 3 + .../musr/musr_team_allocation.yaml | 3 + lm_eval/tasks/leaderboard/musr/utils.py | 26 + 56 files changed, 5803 insertions(+), 1 deletion(-) create mode 100644 lm_eval/tasks/leaderboard/README.md create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/_fewshot_template_yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/boolean_expressions.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/causal_judgement.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/date_understanding.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/disambiguation_qa.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/formal_fallacies.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/geometric_shapes.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/hyperbaton.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_five_objects.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_seven_objects.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_three_objects.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/movie_recommendation.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/navigate.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/object_counting.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/penguins_in_a_table.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/reasoning_about_colored_objects.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/ruin_names.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/salient_translation_error_detection.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/snarks.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/sports_understanding.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/temporal_sequences.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_five_objects.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_seven_objects.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_three_objects.yaml create mode 100644 lm_eval/tasks/leaderboard/bbh_mc/web_of_lies.yaml create mode 100644 lm_eval/tasks/leaderboard/gpqa/_template_yaml create mode 100644 lm_eval/tasks/leaderboard/gpqa/gpqa_diamond_zeroshot.yaml create mode 100644 lm_eval/tasks/leaderboard/gpqa/gpqa_extended_zeroshot.yaml create mode 100644 lm_eval/tasks/leaderboard/gpqa/gpqa_main_zeroshot.yaml create mode 100644 lm_eval/tasks/leaderboard/gpqa/utils.py create mode 100644 lm_eval/tasks/leaderboard/ifeval/ifeval.yaml create mode 100644 lm_eval/tasks/leaderboard/ifeval/instructions.py create mode 100644 lm_eval/tasks/leaderboard/ifeval/instructions_registry.py create mode 100644 lm_eval/tasks/leaderboard/ifeval/instructions_util.py create mode 100644 lm_eval/tasks/leaderboard/ifeval/utils.py create mode 100644 lm_eval/tasks/leaderboard/leaderboard.yaml create mode 100644 lm_eval/tasks/leaderboard/math/_template_yaml create mode 100644 lm_eval/tasks/leaderboard/math/math_algebra.yaml create mode 100644 lm_eval/tasks/leaderboard/math/math_counting_and_prob.yaml create mode 100644 lm_eval/tasks/leaderboard/math/math_geometry.yaml create mode 100644 lm_eval/tasks/leaderboard/math/math_intermediate_algebra.yaml create mode 100644 lm_eval/tasks/leaderboard/math/math_num_theory.yaml create mode 100644 lm_eval/tasks/leaderboard/math/math_prealgebra.yaml create mode 100644 lm_eval/tasks/leaderboard/math/math_precalculus.yaml create mode 100644 lm_eval/tasks/leaderboard/math/utils.py create mode 100644 lm_eval/tasks/leaderboard/mmlu_pro/mmlu_pro.yaml create mode 100644 lm_eval/tasks/leaderboard/mmlu_pro/utils.py create mode 100644 lm_eval/tasks/leaderboard/musr/_template_yaml create mode 100644 lm_eval/tasks/leaderboard/musr/musr_murder_mysteries.yaml create mode 100644 lm_eval/tasks/leaderboard/musr/musr_object_placements.yaml create mode 100644 lm_eval/tasks/leaderboard/musr/musr_team_allocation.yaml create mode 100644 lm_eval/tasks/leaderboard/musr/utils.py diff --git a/.github/workflows/new_tasks.yml b/.github/workflows/new_tasks.yml index 0df7111c..b748aab5 100644 --- a/.github/workflows/new_tasks.yml +++ b/.github/workflows/new_tasks.yml @@ -56,7 +56,7 @@ jobs: if: steps.changed-tasks.outputs.tasks_any_modified == 'true' || steps.changed-tasks.outputs.api_any_modified == 'true' run: | python -m pip install --upgrade pip - pip install -e '.[dev]' --extra-index-url https://download.pytorch.org/whl/cpu + pip install -e '.[dev,ifeval]' --extra-index-url https://download.pytorch.org/whl/cpu # Install optional git dependencies # pip install bleurt@https://github.com/google-research/bleurt/archive/b610120347ef22b494b6d69b4316e303f5932516.zip#egg=bleurt # if [ -f requirements.txt ]; then pip install -r requirements.txt; fi diff --git a/README.md b/README.md index ef00b8a6..ed50e5e5 100644 --- a/README.md +++ b/README.md @@ -7,6 +7,7 @@ New updates and features include: +- **New Open LLM Leaderboard tasks have been added ! You can find them under the [leaderboard](lm_eval/tasks/leaderboard/README.md) task group.** - Internal refactoring - Config-based task creation and configuration - Easier import and sharing of externally-defined task config YAMLs diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index bb04d4f2..5d6393bb 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -56,6 +56,7 @@ | [lambada_cloze](lambada_cloze/README.md) | Cloze-style LAMBADA dataset. | English | | [lambada_multilingual](lambada_multilingual/README.md) | Multilingual LAMBADA dataset. This is a legacy version of the multilingual dataset, and users should instead use `lambada_multilingual_stablelm`. | German, English, Spanish, French, Italian | | [lambada_multilingual_stablelm](lambada_multilingual_stablelm/README.md) | Multilingual LAMBADA dataset. Users should prefer evaluating on this version of the multilingual dataset instead of on `lambada_multilingual`. | German, English, Spanish, French, Italian, Dutch, Portuguese | +| [leaderboard](leaderboard/README.md) | Task group used by Hugging Face's [Open LLM Leaderboard v2](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard). Those tasks are static and will not change through time | English | | [logiqa](logiqa/README.md) | Logical reasoning tasks requiring advanced inference and deduction. | English, Chinese | | [logiqa2](logiqa2/README.md) | Large-scale logical reasoning dataset adapted from the Chinese Civil Service Examination. | English, Chinese | | [mathqa](mathqa/README.md) | Question answering tasks involving mathematical reasoning and problem-solving. | English | diff --git a/lm_eval/tasks/leaderboard/README.md b/lm_eval/tasks/leaderboard/README.md new file mode 100644 index 00000000..70c8a3a1 --- /dev/null +++ b/lm_eval/tasks/leaderboard/README.md @@ -0,0 +1,319 @@ +# Leaderboard evaluations +Our goal with this group is to create an unchanging through time version of +evaluations that will power the Open LLM Leaderboard on HuggingFace. + +As we want to evaluate models across capabilities, the list currently contains: +- BBH (3-shots, multichoice) +- GPQA (0-shot, multichoice) +- mmlu-pro (5-shots, multichoice) +- Musr (0-shot, multichoice) +- ifeval (0-shot, generative) +- Math-lvl-5 (4-shots, generative, minerva version) + + +Details on the choice of those evals can be found [here](https://huggingface.co/spaces/open-llm-leaderboard/blog) ! + +## BigBenchHard (BBH) + +A suite of 23 challenging BIG-Bench tasks which we call BIG-Bench Hard (BBH). +These are the task for which prior language model evaluations did not +outperform the average human-rater. + +### Paper + +Title: Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them + +BIG-Bench (Srivastava et al., 2022) is a diverse evaluation suite that focuses on tasks believed to be beyond the capabilities of current language models. Language models have already made good progress on this benchmark, with the best model in the BIG-Bench paper outperforming average reported human-rater results on 65% of the BIG-Bench tasks via few-shot prompting. But on what tasks do language models fall short of average human-rater performance, and are those tasks actually unsolvable by current language models? +In this work, we focus on a suite of 23 challenging BIG-Bench tasks which we call BIG-Bench Hard (BBH). These are the task for which prior language model evaluations did not outperform the average human-rater. We find that applying chain-of-thought (CoT) prompting to BBH tasks enables PaLM to surpass the average human-rater performance on 10 of the 23 tasks, and Codex (code-davinci-002) to surpass the average human-rater performance on 17 of the 23 tasks. Since many tasks in BBH require multi-step reasoning, few-shot prompting without CoT, as done in the BIG-Bench evaluations (Srivastava et al., 2022), substantially underestimates the best performance and capabilities of language models, which is better captured via CoT prompting. As further analysis, we explore the interaction between CoT and model scale on BBH, finding that CoT enables emergent task performance on several BBH tasks with otherwise flat scaling curves. + + +- paper: https://huggingface.co/papers/2210.09261 +- Homepage: https://github.com/suzgunmirac/BIG-Bench-Hard + +### Citation + +``` +@article{suzgun2022challenging, + title={Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them}, + author={Suzgun, Mirac and Scales, Nathan and Sch{\"a}rli, Nathanael and Gehrmann, Sebastian and Tay, Yi and Chung, Hyung Won and Chowdhery, Aakanksha and Le, Quoc V and Chi, Ed H and Zhou, Denny and and Wei, Jason}, + journal={arXiv preprint arXiv:2210.09261}, + year={2022} +} +``` + +### Groups + +- `leaderboard_bbh` + +### Tasks + +- `leaderboard_bbh_boolean_expressions` +- `leaderboard_bbh_causal_judgement` +- `leaderboard_bbh_date_understanding` +- `leaderboard_bbh_disambiguation_qa` +- `leaderboard_bbh_dyck_languages` +- `leaderboard_bbh_formal_fallacies` +- `leaderboard_bbh_geometric_shapes` +- `leaderboard_bbh_hyperbaton` +- `leaderboard_bbh_logical_deduction_five_objects` +- `leaderboard_bbh_logical_deduction_seven_objects` +- `leaderboard_bbh_logical_deduction_three_objects` +- `leaderboard_bbh_movie_recommendation` +- `leaderboard_bbh_multistep_arithmetic_two` +- `leaderboard_bbh_navigate` +- `leaderboard_bbh_object_counting` +- `leaderboard_bbh_penguins_in_a_table` +- `leaderboard_bbh_reasoning_about_colored_objects` +- `leaderboard_bbh_ruin_names` +- `leaderboard_bbh_salient_translation_error_detection` +- `leaderboard_bbh_snarks` +- `leaderboard_bbh_sports_understanding` +- `leaderboard_bbh_temporal_sequences` +- `leaderboard_bbh_tracking_shuffled_objects_five_objects` +- `leaderboard_bbh_tracking_shuffled_objects_seven_objects` +- `leaderboard_bbh_tracking_shuffled_objects_three_objects` +- `leaderboard_bbh_web_of_lies` +- `leaderboard_bbh_word_sorting` + +## GPQA + +### Paper + +Title: GPQA: A Graduate-Level Google-Proof Q&A Benchmark + +We present GPQA, a challenging dataset of 448 multiple-choice questions written +by domain experts in biology, physics, and chemistry. We ensure that the +questions are high-quality and extremely difficult: experts who have or are +pursuing PhDs in the corresponding domains reach 65% accuracy (74% when +discounting clear mistakes the experts identified in retrospect), while highly +skilled non-expert validators only reach 34% accuracy, despite spending on +average over 30 minutes with unrestricted access to the web (i.e., the +questions are “Google-proof”). The questions are also difficult for +state-of-the-art AI systems, with our strongest GPT-4–based baseline achieving +39% accuracy. If we are to use future AI systems to help us answer very hard +questions—for example, when developing new scientific knowledge—we need to +develop scalable oversight methods that enable humans to supervise their +outputs, which may be difficult even if the supervisors are themselves skilled +and knowledgeable. The difficulty of GPQA both for skilled non-experts and +frontier AI systems should enable realistic scalable oversight experiments, +which we hope can help devise ways for human experts to reliably get truthful +information from AI systems that surpass human capabilities. + +- Paper: https://huggingface.co/papers/2311.12022 +- Homepage: https://github.com/idavidrein/gpqa/tree/main + +### Citation + +``` +@misc{rein2023gpqa, + title={GPQA: A Graduate-Level Google-Proof Q&A Benchmark}, + author={David Rein and Betty Li Hou and Asa Cooper Stickland and Jackson Petty and Richard Yuanzhe Pang and Julien Dirani and Julian Michael and Samuel R. Bowman}, + year={2023}, + eprint={2311.12022}, + archivePrefix={arXiv}, + primaryClass={cs.AI} +} +``` + +### Groups + +- `leaderboard_gpqa` + +### Tasks + +- `leaderboard_gpqa_extended` +- `leaderboard_gpqa_diamond` +- `leaderboard_gpqa_main` + +## IFEval + +### Paper + +Title: Instruction-Following Evaluation for Large Language Models + +One core capability of Large Language Models (LLMs) is to follow natural +language instructions. However, the evaluation of such abilities is not +standardized: Human evaluations are expensive, slow, and not objectively +reproducible, while LLM-based auto-evaluation is potentially biased or limited +by the ability of the evaluator LLM. To overcome these issues, we introduce +Instruction-Following Eval (IFEval) for large language models. IFEval is a +straightforward and easy-to-reproduce evaluation benchmark. It focuses on a set +of "verifiable instructions" such as "write in more than 400 words" and +"mention the keyword of AI at least 3 times". We identified 25 types of those +verifiable instructions and constructed around 500 prompts, with each prompt +containing one or more verifiable instructions. We show evaluation results of +two widely available LLMs on the market. + +- Paper: https://huggingface.co/papers/2210.09261 +- Homepage: https://github.com/google-research/google-research/tree/master/instruction_following_eval + +### Citation + +``` +@article{zhou2023instructionfollowing, + title={Instruction-Following Evaluation for Large Language Models}, + author={Jeffrey Zhou and Tianjian Lu and Swaroop Mishra and Siddhartha Brahma and Sujoy Basu and Yi Luan and Denny Zhou and Le Hou}, + journal={arXiv preprint arXiv:2311.07911}, + year={2023}, +} +``` + +### Tasks + +- `leaderboard_ifeval` + +## MATH-hard + +This is the 4 shots variant of minerva math but only keeping the level 5 questions. + +### Paper + +Title: Measuring Mathematical Problem Solving With the MATH Dataset + +Many intellectual endeavors require mathematical problem solving, but this +skill remains beyond the capabilities of computers. To measure this ability in +machine learning models, we introduce MATH, a new dataset of 12,500 challenging +competition mathematics problems. Each problem in MATH has a full step-by-step +solution which can be used to teach models to generate answer derivations and +explanations. + +NOTE: The few-shot and the generated answer extraction is based on the +[Minerva](https://arxiv.org/abs/2206.14858) and exact match equivalence is +calculated using the `sympy` library. This requires additional dependencies, +which can be installed via the `lm-eval[math]` extra. + +- Paper: https://huggingface.co/papers/2103.03874 +- Homepage: https://github.com/hendrycks/math + + +### Citation + +``` +@article{hendrycksmath2021, + title={Measuring Mathematical Problem Solving With the MATH Dataset}, + author={Dan Hendrycks and Collin Burns and Saurav Kadavath and Akul Arora and Steven Basart and Eric Tang and Dawn Song and Jacob Steinhardt}, + journal={NeurIPS}, + year={2021} +} +@misc{2206.14858, +Author = {Aitor Lewkowycz and Anders Andreassen and David Dohan and Ethan Dye and Henryk Michalewski and Vinay Ramasesh and Ambrose Slone and Cem Anil and Imanol Schlag and Theo Gutman-Solo and Yuhuai Wu and Behnam Neyshabur and Guy Gur-Ari and Vedant Misra}, +Title = {Solving Quantitative Reasoning Problems with Language Models}, +Year = {2022}, +Eprint = {arXiv:2206.14858}, +} +``` + +### Groups + +- `leaderboard_math_hard` + +### Tasks + +- `leaderboard_math_algebra_hard` +- `leaderboard_math_counting_and_prob_hard` +- `leaderboard_math_geometry_hard` +- `leaderboard_math_intermediate_algebra_hard` +- `leaderboard_math_num_theory_hard` +- `leaderboard_math_prealgebra_hard` +- `leaderboard_math_precalc_hard` + + +## MMLU-Pro + +### Paper + +Title: MMLU-Pro: A More Robust and Challenging Multi-Task Language +Understanding Benchmark + +In the age of large-scale language models, benchmarks like the Massive +Multitask Language Understanding (MMLU) have been pivotal in pushing the +boundaries of what AI can achieve in language comprehension and reasoning +across diverse domains. However, as models continue to improve, their +performance on these benchmarks has begun to plateau, making it increasingly +difficult to discern differences in model capabilities. This paper introduces +MMLU-Pro, an enhanced dataset designed to extend the mostly knowledge-driven +MMLU benchmark by integrating more challenging, reasoning-focused questions and +expanding the choice set from four to ten options. Additionally, MMLU-Pro +eliminates the trivial and noisy questions in MMLU. Our experimental results +show that MMLU-Pro not only raises the challenge, causing a significant drop in +accuracy by 16% to 33% compared to MMLU but also demonstrates greater stability +under varying prompts. With 24 different prompt styles tested, the sensitivity +of model scores to prompt variations decreased from 4-5% in MMLU to just 2% in +MMLU-Pro. Additionally, we found that models utilizing Chain of Thought (CoT) +reasoning achieved better performance on MMLU-Pro compared to direct answering, +which is in stark contrast to the findings on the original MMLU, indicating +that MMLU-Pro includes more complex reasoning questions. Our assessments +confirm that MMLU-Pro is a more discriminative benchmark to better track +progress in the field. + +- Paper: https://huggingface.co/papers/2406.01574 +- Homepage: https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro + +### Citation + +``` +@misc{wang2024mmluprorobustchallengingmultitask, + title={MMLU-Pro: A More Robust and Challenging Multi-Task Language + Understanding Benchmark}, + author={Yubo Wang and Xueguang Ma and Ge Zhang and Yuansheng Ni and Abhranil Chandra and Shiguang Guo and Weiming Ren and Aaran Arulraj and Xuan He and Ziyan Jiang and Tianle Li and Max Ku and Kai Wang and Alex Zhuang and Rongqi Fan and Xiang Yue and Wenhu Chen}, + year={2024}, + eprint={2406.01574}, + archivePrefix={arXiv}, + primaryClass={cs.CL}, + url={https://arxiv.org/abs/2406.01574}, +} +``` + +## Musr + +### Paper + +Title: MuSR: Testing the Limits of Chain-of-thought with Multistep Soft +Reasoning + +While large language models (LLMs) equipped with techniques like +chain-of-thought prompting have demonstrated impressive capabilities, they +still fall short in their ability to reason robustly in complex settings. +However, evaluating LLM reasoning is challenging because system capabilities +continue to grow while benchmark datasets for tasks like logical deduction have +remained static. We introduce MuSR, a dataset for evaluating language models on +multistep soft reasoning tasks specified in a natural language narrative. This +dataset has two crucial features. First, it is created through a novel +neurosymbolic synthetic-to-natural generation algorithm, enabling the +construction of complex reasoning instances that challenge GPT-4 (e.g., murder +mysteries roughly 1000 words in length) and which can be scaled further as more +capable LLMs are released. Second, our dataset instances are free text +narratives corresponding to real-world domains of reasoning; this makes it +simultaneously much more challenging than other synthetically-crafted +benchmarks while remaining realistic and tractable for human annotators to +solve with high accuracy. We evaluate a range of LLMs and prompting techniques +on this dataset and characterize the gaps that remain for techniques like +chain-of-thought to perform robust reasoning. + +- Paper: https://huggingface.co/papers/2310.16049 +- Homepage: https://zayne-sprague.github.io/MuSR/ + +### Citation + +``` +@misc{sprague2024musrtestinglimitschainofthought, + title={MuSR: Testing the Limits of Chain-of-thought with Multistep Soft + Reasoning}, + author={Zayne Sprague and Xi Ye and Kaj Bostrom and Swarat Chaudhuri and Greg Durrett}, + year={2024}, + eprint={2310.16049}, + archivePrefix={arXiv}, + primaryClass={cs.CL}, + url={https://arxiv.org/abs/2310.16049}, +} +``` + +### Groups + +- `leaderboard_musr` + +### Tasks + +- `leaderboard_musr_murder_mysteries` +- `leaderboard_musr_object_placements` +- `leaderboard_musr_team_allocation` diff --git a/lm_eval/tasks/leaderboard/bbh_mc/_fewshot_template_yaml b/lm_eval/tasks/leaderboard/bbh_mc/_fewshot_template_yaml new file mode 100644 index 00000000..c461f75f --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/_fewshot_template_yaml @@ -0,0 +1,17 @@ +group: leaderboard_bbh +dataset_path: SaylorTwift/bbh +output_type: multiple_choice +test_split: test +doc_to_text: 'Q: {{input}} + + A:' +doc_to_target: "{{target}}" +metric_list: + - metric: acc_norm + aggregation: mean + higher_is_better: true +num_fewshot: 3 +fewshot_config: + sampler: first_n +metadata: + version: 0.0 diff --git a/lm_eval/tasks/leaderboard/bbh_mc/boolean_expressions.yaml b/lm_eval/tasks/leaderboard/bbh_mc/boolean_expressions.yaml new file mode 100644 index 00000000..970aa6c1 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/boolean_expressions.yaml @@ -0,0 +1,16 @@ +dataset_name: boolean_expressions +description: 'Evaluate the result of a random Boolean expression. + + ' +doc_to_choice: ["False", "True"] +fewshot_config: + sampler: first_n + samples: + - input: not ( ( not not True ) ) is + target: 'False' + - input: True and False and not True and True is + target: 'False' + - input: not not ( not ( False ) ) is + target: 'True' +include: _fewshot_template_yaml +task: leaderboard_bbh_boolean_expressions diff --git a/lm_eval/tasks/leaderboard/bbh_mc/causal_judgement.yaml b/lm_eval/tasks/leaderboard/bbh_mc/causal_judgement.yaml new file mode 100644 index 00000000..236bc568 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/causal_judgement.yaml @@ -0,0 +1,64 @@ +dataset_name: causal_judgement +description: 'Answer questions about causal attribution. + + ' +doc_to_choice: ["Yes", "No"] +fewshot_config: + sampler: first_n + samples: + - input: 'How would a typical person answer each of the following questions about + causation? + + Frank T., had an ongoing dispute with his neighbor over a stretch of land and + one day decided to shoot his neighbor in the body. Frank T. had no experience + with guns, his hand slipped on the barrel of the gun, and the shot went wild. + Nonetheless, the bullet bounced off a large boulder several feet away and hit + the neighbor''s body, causing significant injury. Did Frank T. intentionally + shoot his neighbor in the body? + + Options: + + - Yes + + - No' + target: 'No' + - input: 'How would a typical person answer each of the following questions about + causation? + + Suzy and Billy are working on a project that is very important for our nation''s + security. The boss tells them both: "Be sure that you are here at exactly 9 + am. It is absolutely essential that you arrive at that time." Both Billy and + Suzy arrive at 9 am. As it happens, there was a motion detector installed in + the room where they arrived. The motion detector was set up to be triggered + if at least one person appeared in the room at the same time. So the motion + detector went off. Did Billy cause the motion detector to go off? + + Options: + + - Yes + + - No' + target: 'Yes' + - input: 'How would a typical person answer each of the following questions about + causation? + + George and his sister Lena reunite at their parents'' house for Thanksgiving. + Whereas George just got into medical school, Lena is unhappy in her marriage + and recently lost her job. Over the course of the day, George and Lena get into + a number of heated arguments. Later in the afternoon they play a game of darts. + They split the first two games, and the third game is close until the end. Who + will win comes down to George''s last shot. If he hits a high point region, + he wins; if he hits a low point region, Lena wins. George thinks of the difficult + time Lena is having, and he really wants to let her win. He aims the dart at + the low point region. He sets up his shot and the dart lands in the low point + region. After his shot, Lena wins the game and is very happy. Did George hit + the low point region intentionally? + + Options: + + - Yes + + - No' + target: 'Yes' +include: _fewshot_template_yaml +task: leaderboard_bbh_causal_judgement diff --git a/lm_eval/tasks/leaderboard/bbh_mc/date_understanding.yaml b/lm_eval/tasks/leaderboard/bbh_mc/date_understanding.yaml new file mode 100644 index 00000000..bbdf8df6 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/date_understanding.yaml @@ -0,0 +1,57 @@ +dataset_name: date_understanding +description: 'Infer the date from context. + + ' +doc_to_choice: ["(A)", "(B)", "(C)", "(D)", "(E)", "(F)"] +fewshot_config: + sampler: first_n + samples: + - input: 'Today is Christmas Eve of 1937. What is the date 10 days ago in MM/DD/YYYY? + + Options: + + (A) 12/14/2026 + + (B) 12/14/1950 + + (C) 12/14/2007 + + (D) 12/14/1937 + + (E) 07/14/1938 + + (F) 12/14/1988' + target: (D) + - input: 'Tomorrow is 11/12/2019. What is the date one year ago from today in MM/DD/YYYY? + + Options: + + (A) 09/04/2018 + + (B) 11/11/2018 + + (C) 08/25/2018 + + (D) 11/02/2018 + + (E) 11/04/2018' + target: (B) + - input: 'Jane and John married on Jan 2, 1958. It is their 5-year anniversary today. + What is the date tomorrow in MM/DD/YYYY? + + Options: + + (A) 01/11/1961 + + (B) 01/03/1963 + + (C) 01/18/1961 + + (D) 10/14/1960 + + (E) 01/03/1982 + + (F) 12/03/1960' + target: (B) +include: _fewshot_template_yaml +task: leaderboard_bbh_date_understanding diff --git a/lm_eval/tasks/leaderboard/bbh_mc/disambiguation_qa.yaml b/lm_eval/tasks/leaderboard/bbh_mc/disambiguation_qa.yaml new file mode 100644 index 00000000..34efa6f6 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/disambiguation_qa.yaml @@ -0,0 +1,50 @@ +dataset_name: disambiguation_qa +description: 'Clarify the meaning of sentences with ambiguous pronouns. + + ' +doc_to_choice: ["(A)", "(B)", "(C)"] +fewshot_config: + sampler: first_n + samples: + - input: 'In the following sentences, explain the antecedent of the pronoun (which + thing the pronoun refers to), or state that it is ambiguous. + + Sentence: The chief told the counselor that they took the day off. + + Options: + + (A) The chief took the day off + + (B) The counselor took the day off + + (C) Ambiguous' + target: (A) + - input: 'In the following sentences, explain the antecedent of the pronoun (which + thing the pronoun refers to), or state that it is ambiguous. + + Sentence: The manager sent a message to the secretary, but he didn''t reply + yet. + + Options: + + (A) The secretary didn''t reply yet + + (B) The manager didn''t reply yet + + (C) Ambiguous' + target: (A) + - input: 'In the following sentences, explain the antecedent of the pronoun (which + thing the pronoun refers to), or state that it is ambiguous. + + Sentence: Bailey will plan to meet the director at his office + + Options: + + (A) It will be Bailey''s office + + (B) It will be the director''s office + + (C) Ambiguous' + target: (C) +include: _fewshot_template_yaml +task: leaderboard_bbh_disambiguation_qa diff --git a/lm_eval/tasks/leaderboard/bbh_mc/formal_fallacies.yaml b/lm_eval/tasks/leaderboard/bbh_mc/formal_fallacies.yaml new file mode 100644 index 00000000..7fb642e5 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/formal_fallacies.yaml @@ -0,0 +1,57 @@ +dataset_name: formal_fallacies +description: 'Distinguish deductively valid arguments from formal fallacies. + + ' +doc_to_choice: ["valid", "invalid"] +fewshot_config: + sampler: first_n + samples: + - input: '"It is not always easy to see who is related to whom -- and in which ways. + The following argument pertains to this question: To begin with, Lesley is a + close friend of Fernando. Moreover, being a close friend of Fernando or a schoolmate + of Lowell is sufficient for being a great-grandfather of Leroy. It follows that + Lesley is a great-grandfather of Leroy." + + Is the argument, given the explicitly stated premises, deductively valid or + invalid? + + Options: + + - valid + + - invalid' + target: valid + - input: '"It is not always easy to see who is related to whom -- and in which ways. + The following argument pertains to this question: Whoever is not a great-grandfather + of Clyde is a stepbrother of Brian. Being an ancestor of Dana is sufficient + for not being a great-grandfather of Clyde. We may conclude: Everyone who is + an ancestor of Dana is a stepbrother of Brian, too." + + Is the argument, given the explicitly stated premises, deductively valid or + invalid? + + Options: + + - valid + + - invalid' + target: valid + - input: '"It is not always easy to grasp who is consuming which products. The following + argument pertains to this question: Every infrequent user of Paul Mitchell shampoo + is either a rare consumer of Nioxin shampoo or a loyal buyer of Caress soap, + or both. No regular consumer of Lush soap is a rare consumer of Nioxin shampoo + and, in the same time, a loyal buyer of Caress soap. It follows that whoever + is an infrequent user of Paul Mitchell shampoo is not a regular consumer of + Lush soap." + + Is the argument, given the explicitly stated premises, deductively valid or + invalid? + + Options: + + - valid + + - invalid' + target: invalid +include: _fewshot_template_yaml +task: leaderboard_bbh_formal_fallacies diff --git a/lm_eval/tasks/leaderboard/bbh_mc/geometric_shapes.yaml b/lm_eval/tasks/leaderboard/bbh_mc/geometric_shapes.yaml new file mode 100644 index 00000000..936caece --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/geometric_shapes.yaml @@ -0,0 +1,86 @@ +dataset_name: geometric_shapes +description: 'Name geometric shapes from their SVG paths. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)","(G)","(H)","(I)","(J)","(K)"] +fewshot_config: + sampler: first_n + samples: + - input: 'This SVG path element + draws a + + Options: + + (A) circle + + (B) heptagon + + (C) hexagon + + (D) kite + + (E) line + + (F) octagon + + (G) pentagon + + (H) rectangle + + (I) sector + + (J) triangle' + target: (F) + - input: 'This SVG path element draws a + + Options: + + (A) circle + + (B) heptagon + + (C) hexagon + + (D) kite + + (E) line + + (F) octagon + + (G) pentagon + + (H) rectangle + + (I) sector + + (J) triangle' + target: (G) + - input: 'This SVG path element draws a + + Options: + + (A) circle + + (B) heptagon + + (C) hexagon + + (D) kite + + (E) line + + (F) octagon + + (G) pentagon + + (H) rectangle + + (I) sector + + (J) triangle' + target: (D) +include: _fewshot_template_yaml +task: leaderboard_bbh_geometric_shapes diff --git a/lm_eval/tasks/leaderboard/bbh_mc/hyperbaton.yaml b/lm_eval/tasks/leaderboard/bbh_mc/hyperbaton.yaml new file mode 100644 index 00000000..24ddaa73 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/hyperbaton.yaml @@ -0,0 +1,34 @@ +dataset_name: hyperbaton +description: 'Order adjectives correctly in English sentences. + + ' +doc_to_choice: ["(A)", "(B)"] +fewshot_config: + sampler: first_n + samples: + - input: 'Which sentence has the correct adjective order: + + Options: + + (A) rubber terrible ship + + (B) terrible rubber ship' + target: (B) + - input: 'Which sentence has the correct adjective order: + + Options: + + (A) repulsive small Brazilian exercise ship + + (B) Brazilian repulsive exercise small ship' + target: (A) + - input: 'Which sentence has the correct adjective order: + + Options: + + (A) blue gold wonderful square shoe + + (B) wonderful square blue gold shoe' + target: (B) +include: _fewshot_template_yaml +task: leaderboard_bbh_hyperbaton diff --git a/lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_five_objects.yaml b/lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_five_objects.yaml new file mode 100644 index 00000000..21280253 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_five_objects.yaml @@ -0,0 +1,52 @@ +dataset_name: logical_deduction_five_objects +description: 'A logical deduction task which requires deducing the order of a sequence + of objects. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)","(E)"] +fewshot_config: + sampler: first_n + samples: + - input: 'The following paragraphs each describe a set of three objects arranged + in a fixed order. The statements are logically consistent within each paragraph. + In a golf tournament, there were three golfers: Amy, Eli, and Eve. Eve finished + above Amy. Eli finished below Amy. + + Options: + + (A) Amy finished last + + (B) Eli finished last + + (C) Eve finished last' + target: (B) + - input: 'The following paragraphs each describe a set of three objects arranged + in a fixed order. The statements are logically consistent within each paragraph. + On a shelf, there are three books: a white book, a green book, and an orange + book. The green book is to the right of the white book. The orange book is the + rightmost. + + Options: + + (A) The white book is the leftmost + + (B) The green book is the leftmost + + (C) The orange book is the leftmost' + target: (A) + - input: 'The following paragraphs each describe a set of three objects arranged + in a fixed order. The statements are logically consistent within each paragraph. + On a shelf, there are three books: a red book, a gray book, and a white book. + The white book is to the left of the gray book. The red book is the second from + the left. + + Options: + + (A) The red book is the leftmost + + (B) The gray book is the leftmost + + (C) The white book is the leftmost' + target: (C) +include: _fewshot_template_yaml +task: leaderboard_bbh_logical_deduction_five_objects diff --git a/lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_seven_objects.yaml b/lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_seven_objects.yaml new file mode 100644 index 00000000..11198d6f --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_seven_objects.yaml @@ -0,0 +1,52 @@ +dataset_name: logical_deduction_seven_objects +description: 'A logical deduction task which requires deducing the order of a sequence + of objects. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)","(G)"] +fewshot_config: + sampler: first_n + samples: + - input: 'The following paragraphs each describe a set of three objects arranged + in a fixed order. The statements are logically consistent within each paragraph. + In a golf tournament, there were three golfers: Amy, Eli, and Eve. Eve finished + above Amy. Eli finished below Amy. + + Options: + + (A) Amy finished last + + (B) Eli finished last + + (C) Eve finished last' + target: (B) + - input: 'The following paragraphs each describe a set of three objects arranged + in a fixed order. The statements are logically consistent within each paragraph. + On a shelf, there are three books: a white book, a green book, and an orange + book. The green book is to the right of the white book. The orange book is the + rightmost. + + Options: + + (A) The white book is the leftmost + + (B) The green book is the leftmost + + (C) The orange book is the leftmost' + target: (A) + - input: 'The following paragraphs each describe a set of three objects arranged + in a fixed order. The statements are logically consistent within each paragraph. + On a shelf, there are three books: a red book, a gray book, and a white book. + The white book is to the left of the gray book. The red book is the second from + the left. + + Options: + + (A) The red book is the leftmost + + (B) The gray book is the leftmost + + (C) The white book is the leftmost' + target: (C) +include: _fewshot_template_yaml +task: leaderboard_bbh_logical_deduction_seven_objects diff --git a/lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_three_objects.yaml b/lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_three_objects.yaml new file mode 100644 index 00000000..f2522f3c --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/logical_deduction_three_objects.yaml @@ -0,0 +1,52 @@ +dataset_name: logical_deduction_three_objects +description: 'A logical deduction task which requires deducing the order of a sequence + of objects. + + ' +doc_to_choice: ["(A)","(B)","(C)"] +fewshot_config: + sampler: first_n + samples: + - input: 'The following paragraphs each describe a set of three objects arranged + in a fixed order. The statements are logically consistent within each paragraph. + In a golf tournament, there were three golfers: Amy, Eli, and Eve. Eve finished + above Amy. Eli finished below Amy. + + Options: + + (A) Amy finished last + + (B) Eli finished last + + (C) Eve finished last' + target: (B) + - input: 'The following paragraphs each describe a set of three objects arranged + in a fixed order. The statements are logically consistent within each paragraph. + On a shelf, there are three books: a white book, a green book, and an orange + book. The green book is to the right of the white book. The orange book is the + rightmost. + + Options: + + (A) The white book is the leftmost + + (B) The green book is the leftmost + + (C) The orange book is the leftmost' + target: (A) + - input: 'The following paragraphs each describe a set of three objects arranged + in a fixed order. The statements are logically consistent within each paragraph. + On a shelf, there are three books: a red book, a gray book, and a white book. + The white book is to the left of the gray book. The red book is the second from + the left. + + Options: + + (A) The red book is the leftmost + + (B) The gray book is the leftmost + + (C) The white book is the leftmost' + target: (C) +include: _fewshot_template_yaml +task: leaderboard_bbh_logical_deduction_three_objects diff --git a/lm_eval/tasks/leaderboard/bbh_mc/movie_recommendation.yaml b/lm_eval/tasks/leaderboard/bbh_mc/movie_recommendation.yaml new file mode 100644 index 00000000..908272af --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/movie_recommendation.yaml @@ -0,0 +1,54 @@ +dataset_name: movie_recommendation +description: 'Recommend movies similar to the given list of movies. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)"] +fewshot_config: + sampler: first_n + samples: + - input: 'Find a movie similar to Star Wars Episode IV - A New Hope, Indiana Jones + and the Last Crusade, Star Wars Episode V - The Empire Strikes Back, The Big + Lebowski: + + Options: + + (A) Tetsuo + + (B) the Ironman + + (C) The Princess Bride + + (D) The Barkley Marathons The Race That Eats Its Young + + (E) Bug' + target: (C) + - input: 'Find a movie similar to Twister, The Silence of the Lambs, Independence + Day, Braveheart: + + Options: + + (A) They Shoot Horses + + (B) Don''t They + + (C) Forrest Gump + + (D) The Salton Sea + + (E) Extreme Days' + target: (C) + - input: 'Find a movie similar to Minority Report, Total Recall, Inside Out, Forrest + Gump: + + Options: + + (A) Phenomena + + (B) Lilting + + (C) Catwoman + + (D) Edge of Tomorrow' + target: (D) +include: _fewshot_template_yaml +task: leaderboard_bbh_movie_recommendation diff --git a/lm_eval/tasks/leaderboard/bbh_mc/navigate.yaml b/lm_eval/tasks/leaderboard/bbh_mc/navigate.yaml new file mode 100644 index 00000000..22d0ddf3 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/navigate.yaml @@ -0,0 +1,40 @@ +dataset_name: navigate +description: 'Given a series of navigation instructions, determine whether one would + end up back at the starting point. + + ' +doc_to_choice: ["Yes","No"] +fewshot_config: + sampler: first_n + samples: + - input: 'If you follow these instructions, do you return to the starting point? + Turn left. Turn around. Turn left. Take 7 steps. Take 2 steps. Take 4 steps. + Take 8 steps. + + Options: + + - Yes + + - No' + target: 'No' + - input: 'If you follow these instructions, do you return to the starting point? + Turn around. Take 1 step. Take 6 steps. Turn around. Take 6 steps. Take 9 steps. + Take 1 step. + + Options: + + - Yes + + - No' + target: 'No' + - input: 'If you follow these instructions, do you return to the starting point? + Always face forward. Take 2 steps right. Take 9 steps left. Take 7 steps right. + + Options: + + - Yes + + - No' + target: 'Yes' +include: _fewshot_template_yaml +task: leaderboard_bbh_navigate diff --git a/lm_eval/tasks/leaderboard/bbh_mc/object_counting.yaml b/lm_eval/tasks/leaderboard/bbh_mc/object_counting.yaml new file mode 100644 index 00000000..9a98c508 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/object_counting.yaml @@ -0,0 +1,20 @@ +dataset_name: object_counting +description: 'Questions that involve enumerating objects and asking the model to count + them. + + ' +doc_to_choice: ["0","1","2","3","4","5","6","7","8","9","10", "11", "12", "13", "14", "15", "16", "17", "18"] +fewshot_config: + sampler: first_n + samples: + - input: I have a blackberry, a clarinet, a nectarine, a plum, a strawberry, a banana, + a flute, an orange, and a violin. How many fruits do I have? + target: '6' + - input: I have an orange, a raspberry, two peaches, a blackberry, an apple, a grape, + a nectarine, and three plums. How many fruits do I have? + target: '11' + - input: I have a lettuce head, a head of broccoli, an onion, a stalk of celery, + two carrots, a garlic, and a yam. How many vegetables do I have? + target: '8' +include: _fewshot_template_yaml +task: leaderboard_bbh_object_counting diff --git a/lm_eval/tasks/leaderboard/bbh_mc/penguins_in_a_table.yaml b/lm_eval/tasks/leaderboard/bbh_mc/penguins_in_a_table.yaml new file mode 100644 index 00000000..27687867 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/penguins_in_a_table.yaml @@ -0,0 +1,68 @@ +dataset_name: penguins_in_a_table +description: 'Answer questions about a table of penguins and their attributes. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)","(E)"] +fewshot_config: + sampler: first_n + samples: + - input: 'Here is a table where the first line is a header and each subsequent line + is a penguin: name, age, height (cm), weight (kg) Louis, 7, 50, 11 Bernard, + 5, 80, 13 Vincent, 9, 60, 11 Gwen, 8, 70, 15 For example: the age of Louis + is 7, the weight of Gwen is 15 kg, the height of Bernard is 80 cm. We now add + a penguin to the table: + + James, 12, 90, 12 + + How many penguins are less than 8 years old? + + Options: + + (A) 1 + + (B) 2 + + (C) 3 + + (D) 4 + + (E) 5' + target: (B) + - input: 'Here is a table where the first line is a header and each subsequent line + is a penguin: name, age, height (cm), weight (kg) Louis, 7, 50, 11 Bernard, + 5, 80, 13 Vincent, 9, 60, 11 Gwen, 8, 70, 15 For example: the age of Louis + is 7, the weight of Gwen is 15 kg, the height of Bernard is 80 cm. Which is + the youngest penguin? + + Options: + + (A) Louis + + (B) Bernard + + (C) Vincent + + (D) Gwen + + (E) James' + target: (B) + - input: 'Here is a table where the first line is a header and each subsequent line + is a penguin: name, age, height (cm), weight (kg) Louis, 7, 50, 11 Bernard, + 5, 80, 13 Vincent, 9, 60, 11 Gwen, 8, 70, 15 For example: the age of Louis + is 7, the weight of Gwen is 15 kg, the height of Bernard is 80 cm. What is + the name of the second penguin sorted by alphabetic order? + + Options: + + (A) Louis + + (B) Bernard + + (C) Vincent + + (D) Gwen + + (E) James' + target: (D) +include: _fewshot_template_yaml +task: leaderboard_bbh_penguins_in_a_table diff --git a/lm_eval/tasks/leaderboard/bbh_mc/reasoning_about_colored_objects.yaml b/lm_eval/tasks/leaderboard/bbh_mc/reasoning_about_colored_objects.yaml new file mode 100644 index 00000000..d4bb5c38 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/reasoning_about_colored_objects.yaml @@ -0,0 +1,116 @@ +dataset_name: reasoning_about_colored_objects +description: 'Answer extremely simple questions about the colors of objects on a surface. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)","(G)","(H)","(I)","(J)","(K)","(L)","(M)","(N)","(O)","(P)","(Q)","(R)"] +fewshot_config: + sampler: first_n + samples: + - input: 'On the nightstand, there is a red pencil, a purple mug, a burgundy keychain, + a fuchsia teddy bear, a black plate, and a blue stress ball. What color is the + stress ball? + + Options: + + (A) red + + (B) orange + + (C) yellow + + (D) green + + (E) blue + + (F) brown + + (G) magenta + + (H) fuchsia + + (I) mauve + + (J) teal + + (K) turquoise + + (L) burgundy + + (M) silver + + (N) gold + + (O) black + + (P) grey + + (Q) purple + + (R) pink' + target: (E) + - input: 'On the table, you see a bunch of objects arranged in a row: a purple paperclip, + a pink stress ball, a brown keychain, a green scrunchiephone charger, a mauve + fidget spinner, and a burgundy pen. What is the color of the object directly + to the right of the stress ball? + + Options: + + (A) red + + (B) orange + + (C) yellow + + (D) green + + (E) blue + + (F) brown + + (G) magenta + + (H) fuchsia + + (I) mauve + + (J) teal + + (K) turquoise + + (L) burgundy + + (M) silver + + (N) gold + + (O) black + + (P) grey + + (Q) purple + + (R) pink' + target: (F) + - input: 'On the nightstand, you see the following items arranged in a row: a teal + plate, a burgundy keychain, a yellow scrunchiephone charger, an orange mug, + a pink notebook, and a grey cup. How many non-orange items do you see to the + left of the teal item? + + Options: + + (A) zero + + (B) one + + (C) two + + (D) three + + (E) four + + (F) five + + (G) six' + target: (A) +include: _fewshot_template_yaml +task: leaderboard_bbh_reasoning_about_colored_objects diff --git a/lm_eval/tasks/leaderboard/bbh_mc/ruin_names.yaml b/lm_eval/tasks/leaderboard/bbh_mc/ruin_names.yaml new file mode 100644 index 00000000..1d865267 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/ruin_names.yaml @@ -0,0 +1,50 @@ +dataset_name: ruin_names +description: 'Select the humorous edit that ''ruins'' the input movie or musical artist + name. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)"] +fewshot_config: + sampler: first_n + samples: + - input: 'Which of the following is a humorous edit of this artist or movie name: + ''whitesnake''? + + Options: + + (A) whitesnape + + (B) whitesnapke + + (C) whitesnuake + + (D) mwhitesnake' + target: (A) + - input: 'Which of the following is a humorous edit of this artist or movie name: + ''one of our dinosaurs is missing''? + + Options: + + (A) ofne of our dinosaurs is missing + + (B) one af our dinosaurs is missing + + (C) one of our dinosaurs is pissing + + (D) one of our dinosaur is missing' + target: (C) + - input: 'Which of the following is a humorous edit of this artist or movie name: + ''counting crows''? + + Options: + + (A) countingy crows + + (B) counting cows + + (C) courting crows + + (D) coutnting crows' + target: (B) +include: _fewshot_template_yaml +task: leaderboard_bbh_ruin_names diff --git a/lm_eval/tasks/leaderboard/bbh_mc/salient_translation_error_detection.yaml b/lm_eval/tasks/leaderboard/bbh_mc/salient_translation_error_detection.yaml new file mode 100644 index 00000000..dd9c9142 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/salient_translation_error_detection.yaml @@ -0,0 +1,103 @@ +dataset_name: salient_translation_error_detection +description: 'Detect the type of error in an English translation of a German source + sentence. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)"] +fewshot_config: + sampler: first_n + samples: + - input: "The following translations from German to English contain a particular + error. That error will be one of the following types: Named Entities: An entity + (names, places, locations, etc.) is changed to a different entity. Numerical + Values: Numerical values (ordinals or cardinals), dates, and/or units are changed. + Modifiers or Adjectives: The modifiers and adjectives pertaining to a noun are + changed. Negation or Antonyms: Introduce or remove a negation or change comparatives + to their antonyms. Facts: Trivial factual errors not pertaining to the above + classes are introduced in the translations. Dropped Content: A significant clause + in the translation is removed. Please identify that error. Source: In der Liste + der Baudenkmale in Lenzen (Elbe) sind alle Baudenkmale der brandenburgischen + Stadt Lenzen (Elbe) und ihrer Ortsteile aufgelistet. + + Translation: In the list of architectural monuments in Lenzen all architectural + monuments of the Brandenburg city of Lenzen and its districts are listed. + + The translation contains an error pertaining to + + Options: + + (A) Modifiers or Adjectives + + (B) Numerical Values + + (C) Negation or Antonyms + + (D) Named Entities + + (E) Dropped Content + + (F) Facts" + target: (D) + - input: "The following translations from German to English contain a particular + error. That error will be one of the following types: Named Entities: An entity + (names, places, locations, etc.) is changed to a different entity. Numerical + Values: Numerical values (ordinals or cardinals), dates, and/or units are changed. + Modifiers or Adjectives: The modifiers and adjectives pertaining to a noun are + changed. Negation or Antonyms: Introduce or remove a negation or change comparatives + to their antonyms. Facts: Trivial factual errors not pertaining to the above + classes are introduced in the translations. Dropped Content: A significant clause + in the translation is removed. Please identify that error. Source: Auf dieser + Seite sind die Baudenkm\xE4ler der oberbayerischen Gro\xDFen Kreisstadt Landsberg + am Lech zusammengestellt. + + Translation: On this page are compiled the architectural monuments of the town of + Landsberg am Lech. + + The translation contains an error pertaining to + + Options: + + (A) Modifiers or Adjectives + + (B) Numerical Values + + (C) Negation or Antonyms + + (D) Named Entities + + (E) Dropped Content + + (F) Facts" + target: (E) + - input: "The following translations from German to English contain a particular + error. That error will be one of the following types: Named Entities: An entity + (names, places, locations, etc.) is changed to a different entity. Numerical + Values: Numerical values (ordinals or cardinals), dates, and/or units are changed. + Modifiers or Adjectives: The modifiers and adjectives pertaining to a noun are + changed. Negation or Antonyms: Introduce or remove a negation or change comparatives + to their antonyms. Facts: Trivial factual errors not pertaining to the above + classes are introduced in the translations. Dropped Content: A significant clause + in the translation is removed. Please identify that error. Source: \u0141eba ist + eine Kleinstadt und ein Badeort im Powiat L\u0119borski der polnischen Woiwodschaft + Pommern. + + Translation: Eba is not a small town and seaside resort in the Powiat L\xE9borski + county of the Pomeranian Voivodeship of Poland.\nThe translation contains an error + pertaining to + + Options: + + (A) Modifiers or Adjectives + + (B) Numerical Values + + (C) Negation or Antonyms + + (D) Named Entities + + (E) Dropped Content + + (F) Facts" + target: (C) +include: _fewshot_template_yaml +task: leaderboard_bbh_salient_translation_error_detection diff --git a/lm_eval/tasks/leaderboard/bbh_mc/snarks.yaml b/lm_eval/tasks/leaderboard/bbh_mc/snarks.yaml new file mode 100644 index 00000000..465e39b1 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/snarks.yaml @@ -0,0 +1,45 @@ +dataset_name: snarks +description: 'Determine which of two sentences is sarcastic. + + + According to Cambridge University Dictionary, sarcasm is "the use of remarks that + clearly mean the opposite of what they say, made in order to hurt someone''s feelings + or to criticize something in a humorous way." Sarcastic sentences often contain + satirical or ironic utterances, hyperboles, ambivalent or witty remarks. + + + ' +doc_to_choice: ["(A)","(B)"] +fewshot_config: + sampler: first_n + samples: + - input: 'Which statement is sarcastic? + + Options: + + (A) Yes, because having interests and actively researching them is a huge waste + + (B) Yes, because having interests and actively researching them is a huge deal' + target: (A) + - input: 'Which statement is sarcastic? + + Options: + + (A) No one is going to disagree with you on this. Avoiding ad hominem attacks + really help your case + + (B) No one is going to disagree with you on this. Ad hominem attacks really + help your case' + target: (B) + - input: 'Which statement is sarcastic? + + Options: + + (A) Consistency in the league''s punishments? What do you think this is supposed + to be, politics? + + (B) Consistency in the league''s punishments? What do you think this is supposed + to be, moral?' + target: (A) +include: _fewshot_template_yaml +task: leaderboard_bbh_snarks diff --git a/lm_eval/tasks/leaderboard/bbh_mc/sports_understanding.yaml b/lm_eval/tasks/leaderboard/bbh_mc/sports_understanding.yaml new file mode 100644 index 00000000..f8c1c626 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/sports_understanding.yaml @@ -0,0 +1,19 @@ +dataset_name: sports_understanding +description: 'Determine whether an artificially constructed sentence relating to sports + is plausible or not. + + ' +doc_to_choice: ["yes","no"] +fewshot_config: + sampler: first_n + samples: + - input: Is the following sentence plausible? "Bam Adebayo scored a reverse layup + in the Western Conference Finals." + target: 'yes' + - input: Is the following sentence plausible? "Santi Cazorla scored a touchdown." + target: 'no' + - input: Is the following sentence plausible? "DeMar DeRozan was called for the + goal tend." + target: 'yes' +include: _fewshot_template_yaml +task: leaderboard_bbh_sports_understanding diff --git a/lm_eval/tasks/leaderboard/bbh_mc/temporal_sequences.yaml b/lm_eval/tasks/leaderboard/bbh_mc/temporal_sequences.yaml new file mode 100644 index 00000000..bafedd9c --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/temporal_sequences.yaml @@ -0,0 +1,101 @@ +dataset_name: temporal_sequences +description: 'Task description: Answer questions about which times certain events + could have occurred. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)"] +fewshot_config: + sampler: first_n + samples: + - input: 'Today, Emily went to the museum. Between what times could they have gone? + + We know that: + + Emily woke up at 1pm. + + Elizabeth saw Emily reading at the library from 2pm to 4pm. + + Jessica saw Emily watching a movie at the theater from 4pm to 5pm. + + Leslie saw Emily waiting at the airport from 5pm to 6pm. + + William saw Emily buying clothes at the mall from 6pm to 7pm. + + The museum was closed after 7pm. + + Between what times could Emily have gone to the museum? + + Options: + + (A) 1pm to 2pm + + (B) 6pm to 7pm + + (C) 5pm to 6pm + + (D) 2pm to 4pm' + target: (A) + - input: 'Today, Elizabeth went to the amusement park. Between what times could + they have gone? + + We know that: + + Elizabeth woke up at 7am. + + David saw Elizabeth fixing their computer at the electronic store from 1pm to + 2pm. + + Sarah saw Elizabeth playing tennis at the tennis court from 2pm to 3pm. + + Susan saw Elizabeth walking towards the Statue of Liberty from 3pm to 6pm. + + Andrew saw Elizabeth taking photos near the Eiffel Tower from 6pm to 9pm. + + Emily saw Elizabeth getting a coffee at the cafe from 9pm to 10pm. + + The amusement park was closed after 10pm. + + Between what times could Elizabeth have gone to the amusement park? + + Options: + + (A) 7am to 1pm + + (B) 9pm to 10pm + + (C) 1pm to 2pm + + (D) 3pm to 6pm' + target: (A) + - input: 'Today, Tiffany went to the beach. Between what times could they have gone? + + We know that: + + Tiffany woke up at 5am. + + Betty saw Tiffany getting a coffee at the cafe from 5am to 6am. + + Jessica saw Tiffany working at the office from 6am to 9am. + + John saw Tiffany stretching at a yoga studio from 9am to 12pm. + + Sean saw Tiffany sitting on a rooftop from 12pm to 2pm. + + Sarah saw Tiffany playing tennis at the tennis court from 2pm to 3pm. + + The beach was closed after 4pm. + + Between what times could Tiffany have gone to the beach? + + Options: + + (A) 9am to 12pm + + (B) 12pm to 2pm + + (C) 5am to 6am + + (D) 3pm to 4pm' + target: (D) +include: _fewshot_template_yaml +task: leaderboard_bbh_temporal_sequences diff --git a/lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_five_objects.yaml b/lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_five_objects.yaml new file mode 100644 index 00000000..59667929 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_five_objects.yaml @@ -0,0 +1,59 @@ +dataset_name: tracking_shuffled_objects_five_objects +description: 'A task requiring determining the final positions of a set of objects + given their initial positions and a description of a sequence of swaps. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)","(E)"] +fewshot_config: + sampler: first_n + samples: + - input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they + are each holding a ball: Alice has a yellow ball, Bob has a blue ball, and Claire + has a pink ball. + + As the game progresses, pairs of players trade balls. First, Claire and Alice + swap balls. Then, Alice and Bob swap balls. Finally, Claire and Bob swap balls. + At the end of the game, Bob has the + + Options: + + (A) yellow ball + + (B) blue ball + + (C) pink ball' + target: (A) + - input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they + are each holding a ball: Alice has a white ball, Bob has a purple ball, and + Claire has a pink ball. + + As the game progresses, pairs of players trade balls. First, Bob and Alice swap + balls. Then, Bob and Claire swap balls. Finally, Bob and Alice swap balls. At + the end of the game, Alice has the + + Options: + + (A) white ball + + (B) purple ball + + (C) pink ball' + target: (C) + - input: 'Alice, Bob, and Claire are dancers at a square dance. At the start of + a song, they each have a partner: Alice is dancing with Lola, Bob is dancing + with Rodrigo, and Claire is dancing with Patrick. + + Throughout the song, the dancers often trade partners. First, Alice and Bob + switch partners. Then, Claire and Bob switch partners. Finally, Bob and Alice + switch partners. At the end of the dance, Alice is dancing with + + Options: + + (A) Lola + + (B) Rodrigo + + (C) Patrick' + target: (C) +include: _fewshot_template_yaml +task: leaderboard_bbh_tracking_shuffled_objects_five_objects diff --git a/lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_seven_objects.yaml b/lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_seven_objects.yaml new file mode 100644 index 00000000..1492eb61 --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_seven_objects.yaml @@ -0,0 +1,59 @@ +dataset_name: tracking_shuffled_objects_seven_objects +description: 'A task requiring determining the final positions of a set of objects + given their initial positions and a description of a sequence of swaps. + + ' +doc_to_choice: ["(A)","(B)","(C)","(D)","(E)","(F)","(G)"] +fewshot_config: + sampler: first_n + samples: + - input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they + are each holding a ball: Alice has a yellow ball, Bob has a blue ball, and Claire + has a pink ball. + + As the game progresses, pairs of players trade balls. First, Claire and Alice + swap balls. Then, Alice and Bob swap balls. Finally, Claire and Bob swap balls. + At the end of the game, Bob has the + + Options: + + (A) yellow ball + + (B) blue ball + + (C) pink ball' + target: (A) + - input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they + are each holding a ball: Alice has a white ball, Bob has a purple ball, and + Claire has a pink ball. + + As the game progresses, pairs of players trade balls. First, Bob and Alice swap + balls. Then, Bob and Claire swap balls. Finally, Bob and Alice swap balls. At + the end of the game, Alice has the + + Options: + + (A) white ball + + (B) purple ball + + (C) pink ball' + target: (C) + - input: 'Alice, Bob, and Claire are dancers at a square dance. At the start of + a song, they each have a partner: Alice is dancing with Lola, Bob is dancing + with Rodrigo, and Claire is dancing with Patrick. + + Throughout the song, the dancers often trade partners. First, Alice and Bob + switch partners. Then, Claire and Bob switch partners. Finally, Bob and Alice + switch partners. At the end of the dance, Alice is dancing with + + Options: + + (A) Lola + + (B) Rodrigo + + (C) Patrick' + target: (C) +include: _fewshot_template_yaml +task: leaderboard_bbh_tracking_shuffled_objects_seven_objects diff --git a/lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_three_objects.yaml b/lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_three_objects.yaml new file mode 100644 index 00000000..134a991b --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/tracking_shuffled_objects_three_objects.yaml @@ -0,0 +1,59 @@ +dataset_name: tracking_shuffled_objects_three_objects +description: 'A task requiring determining the final positions of a set of objects + given their initial positions and a description of a sequence of swaps. + + ' +doc_to_choice: ["(A)","(B)","(C)"] +fewshot_config: + sampler: first_n + samples: + - input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they + are each holding a ball: Alice has a yellow ball, Bob has a blue ball, and Claire + has a pink ball. + + As the game progresses, pairs of players trade balls. First, Claire and Alice + swap balls. Then, Alice and Bob swap balls. Finally, Claire and Bob swap balls. + At the end of the game, Bob has the + + Options: + + (A) yellow ball + + (B) blue ball + + (C) pink ball' + target: (A) + - input: 'Alice, Bob, and Claire are playing a game. At the start of the game, they + are each holding a ball: Alice has a white ball, Bob has a purple ball, and + Claire has a pink ball. + + As the game progresses, pairs of players trade balls. First, Bob and Alice swap + balls. Then, Bob and Claire swap balls. Finally, Bob and Alice swap balls. At + the end of the game, Alice has the + + Options: + + (A) white ball + + (B) purple ball + + (C) pink ball' + target: (C) + - input: 'Alice, Bob, and Claire are dancers at a square dance. At the start of + a song, they each have a partner: Alice is dancing with Lola, Bob is dancing + with Rodrigo, and Claire is dancing with Patrick. + + Throughout the song, the dancers often trade partners. First, Alice and Bob + switch partners. Then, Claire and Bob switch partners. Finally, Bob and Alice + switch partners. At the end of the dance, Alice is dancing with + + Options: + + (A) Lola + + (B) Rodrigo + + (C) Patrick' + target: (C) +include: _fewshot_template_yaml +task: leaderboard_bbh_tracking_shuffled_objects_three_objects diff --git a/lm_eval/tasks/leaderboard/bbh_mc/web_of_lies.yaml b/lm_eval/tasks/leaderboard/bbh_mc/web_of_lies.yaml new file mode 100644 index 00000000..a201d8ff --- /dev/null +++ b/lm_eval/tasks/leaderboard/bbh_mc/web_of_lies.yaml @@ -0,0 +1,22 @@ +dataset_name: web_of_lies +description: 'Evaluate a random boolean function expressed as a word problem. + + ' +doc_to_choice: ["Yes","No"] +fewshot_config: + sampler: first_n + samples: + - input: 'Question: Fidel tells the truth. Jerry says Fidel tells the truth. Vina + says Jerry tells the truth. Millicent says Vina lies. Raymond says Millicent + lies. Does Raymond tell the truth?' + target: 'Yes' + - input: 'Question: Kristian lies. Millie says Kristian lies. Maybelle says Millie + tells the truth. Fidel says Maybelle lies. Leda says Fidel lies. Does Leda tell + the truth?' + target: 'Yes' + - input: 'Question: Kristian tells the truth. Michaela says Kristian lies. Raymond + says Michaela tells the truth. Osvaldo says Raymond tells the truth. Jamey says + Osvaldo tells the truth. Does Jamey tell the truth?' + target: 'No' +include: _fewshot_template_yaml +task: leaderboard_bbh_web_of_lies diff --git a/lm_eval/tasks/leaderboard/gpqa/_template_yaml b/lm_eval/tasks/leaderboard/gpqa/_template_yaml new file mode 100644 index 00000000..83cb1872 --- /dev/null +++ b/lm_eval/tasks/leaderboard/gpqa/_template_yaml @@ -0,0 +1,20 @@ +dataset_path: Idavidrein/gpqa +group: leaderboard_gpqa +output_type: multiple_choice +process_docs: !function utils.process_docs +training_split: train +# Because huggingface dataset only has train split +validation_split: train +test_split: null +doc_to_text: "What is the correct answer to this question:{{Question}}\nChoices:\n(A) {{choice1}}\n(B) {{choice2}}\n(C) {{choice3}}\n(D) {{choice4}}\nAnswer: " +doc_to_target: answer +doc_to_choice: ["(A)", "(B)", "(C)", "(D)"] +num_fewshot: 0 +metric_list: + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 +fewshot_config: + sampler: first_n diff --git a/lm_eval/tasks/leaderboard/gpqa/gpqa_diamond_zeroshot.yaml b/lm_eval/tasks/leaderboard/gpqa/gpqa_diamond_zeroshot.yaml new file mode 100644 index 00000000..a3892165 --- /dev/null +++ b/lm_eval/tasks/leaderboard/gpqa/gpqa_diamond_zeroshot.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: gpqa_diamond +include: _template_yaml +task: leaderboard_gpqa_diamond diff --git a/lm_eval/tasks/leaderboard/gpqa/gpqa_extended_zeroshot.yaml b/lm_eval/tasks/leaderboard/gpqa/gpqa_extended_zeroshot.yaml new file mode 100644 index 00000000..b481d960 --- /dev/null +++ b/lm_eval/tasks/leaderboard/gpqa/gpqa_extended_zeroshot.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: gpqa_extended +include: _template_yaml +task: leaderboard_gpqa_extended diff --git a/lm_eval/tasks/leaderboard/gpqa/gpqa_main_zeroshot.yaml b/lm_eval/tasks/leaderboard/gpqa/gpqa_main_zeroshot.yaml new file mode 100644 index 00000000..a15e45b6 --- /dev/null +++ b/lm_eval/tasks/leaderboard/gpqa/gpqa_main_zeroshot.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: gpqa_main +include: _template_yaml +task: leaderboard_gpqa_main diff --git a/lm_eval/tasks/leaderboard/gpqa/utils.py b/lm_eval/tasks/leaderboard/gpqa/utils.py new file mode 100644 index 00000000..c2317e02 --- /dev/null +++ b/lm_eval/tasks/leaderboard/gpqa/utils.py @@ -0,0 +1,38 @@ +import random +import re + +import datasets + + +def preprocess(text): + if text is None: + return " " + text = text.strip() + text = text.replace(" [title]", ". ") + text = re.sub("\\[.*?\\]", "", text) + text = text.replace(" ", " ") + return text + + +def process_docs(dataset: datasets.Dataset) -> datasets.Dataset: + def _process_doc(doc): + choices = [ + preprocess(doc["Incorrect Answer 1"]), + preprocess(doc["Incorrect Answer 2"]), + preprocess(doc["Incorrect Answer 3"]), + preprocess(doc["Correct Answer"]), + ] + + random.shuffle(choices) + correct_answer_index = choices.index(preprocess(doc["Correct Answer"])) + + out_doc = { + "choice1": choices[0], + "choice2": choices[1], + "choice3": choices[2], + "choice4": choices[3], + "answer": f"({chr(65 + correct_answer_index)})", + } + return out_doc + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/leaderboard/ifeval/ifeval.yaml b/lm_eval/tasks/leaderboard/ifeval/ifeval.yaml new file mode 100644 index 00000000..da394d9c --- /dev/null +++ b/lm_eval/tasks/leaderboard/ifeval/ifeval.yaml @@ -0,0 +1,32 @@ +task: leaderboard_ifeval +group: leaderboard_instruction_following +dataset_path: wis-k/instruction-following-eval +dataset_name: null +output_type: generate_until +test_split: train +num_fewshot: 0 +doc_to_text: prompt +doc_to_target: 0 +generation_kwargs: + until: [] + do_sample: false + temperature: 0.0 + max_gen_toks: 1280 +process_results: !function utils.process_results +metric_list: + - metric: prompt_level_strict_acc + aggregation: mean + higher_is_better: true + - metric: inst_level_strict_acc + aggregation: !function utils.agg_inst_level_acc + higher_is_better: true + - metric: prompt_level_loose_acc + aggregation: mean + higher_is_better: true + - metric: inst_level_loose_acc + aggregation: !function utils.agg_inst_level_acc + higher_is_better: true +metadata: + version: 2.0 +fewshot_config: + sampler: first_n diff --git a/lm_eval/tasks/leaderboard/ifeval/instructions.py b/lm_eval/tasks/leaderboard/ifeval/instructions.py new file mode 100644 index 00000000..5c352af3 --- /dev/null +++ b/lm_eval/tasks/leaderboard/ifeval/instructions.py @@ -0,0 +1,1612 @@ +# Copyright 2023 The Google Research Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Library of instructions.""" + +import collections +import json +import logging +import random +import re +import string +from typing import Dict, Optional, Sequence, Union + +import langdetect + +from lm_eval.tasks.ifeval import instructions_util + + +logger = logging.getLogger(__name__) + +_InstructionArgsDtype = Optional[Dict[str, Union[int, str, Sequence[str]]]] + +_LANGUAGES = instructions_util.LANGUAGE_CODES + +# The relational operation for comparison. +_COMPARISON_RELATION = ("less than", "at least") + +# The maximum number of sentences. +_MAX_NUM_SENTENCES = 20 + +# The number of placeholders. +_NUM_PLACEHOLDERS = 4 + +# The number of bullet lists. +_NUM_BULLETS = 5 + +# The options of constrained response. +_CONSTRAINED_RESPONSE_OPTIONS = ( + "My answer is yes.", + "My answer is no.", + "My answer is maybe.", +) + +# The options of starter keywords. +_STARTER_OPTIONS = ( + "I would say", + "My answer is", + "I believe", + "In my opinion", + "I think", + "I reckon", + "I feel", + "From my perspective", + "As I see it", + "According to me", + "As far as I'm concerned", + "To my understanding", + "In my view", + "My take on it is", + "As per my perception", +) + +# The options of ending keywords. +# TODO(jeffreyzhou) add more ending options +_ENDING_OPTIONS = ("Any other questions?", "Is there anything else I can help with?") + +# The number of highlighted sections. +_NUM_HIGHLIGHTED_SECTIONS = 4 + +# The section spliter. +_SECTION_SPLITER = ("Section", "SECTION") + +# The number of sections. +_NUM_SECTIONS = 5 + +# The number of paragraphs. +_NUM_PARAGRAPHS = 5 + +# The postscript marker. +_POSTSCRIPT_MARKER = ("P.S.", "P.P.S") + +# The number of keywords. +_NUM_KEYWORDS = 2 + +# The occurrences of a single keyword. +_KEYWORD_FREQUENCY = 3 + +# The occurrences of a single letter. +_LETTER_FREQUENCY = 10 + +# The occurrences of words with all capital letters. +_ALL_CAPITAL_WORD_FREQUENCY = 20 + +# The number of words in the response. +_NUM_WORDS_LOWER_LIMIT = 100 +_NUM_WORDS_UPPER_LIMIT = 500 + + +class Instruction: + """An instruction template.""" + + def __init__(self, instruction_id): + self.id = instruction_id + + def build_description(self, **kwargs): + raise NotImplementedError("`build_description` not implemented.") + + def get_instruction_args(self): + raise NotImplementedError("`get_instruction_args` not implemented.") + + def get_instruction_args_keys(self): + raise NotImplementedError("`get_instruction_args_keys` not implemented.") + + def check_following(self, value): + raise NotImplementedError("`check_following` not implemented.") + + +class ResponseLanguageChecker(Instruction): + """Check the language of the entire response.""" + + def build_description(self, *, language=None): + """Build the instruction description. + + Args: + language: A string representing the expected language of the response. The + language has to comply to the 97 types defined in + `langid.py` (https://pypi.org/project/langid/1.1.5/), which follows + ISO 639-1 codes (https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes); + for example, `en` for English, `zh` for Chinese, `fr` for French. + + Returns: + A string representing the instruction description. + """ + self._language = language + if self._language is None: + self._language = random.choice(list(_LANGUAGES.keys())) + # TODO(tianjianlu): opens the description generation to more choices. + self._description_pattern = ( + "Your ENTIRE response should be in {language} language, no other " + + "language is allowed." + ) + return self._description_pattern.format(language=_LANGUAGES[self._language]) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"language": self._language} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["language"] + + def check_following(self, value): + """Check if the language of the entire response follows the instruction. + + Args: + value: A string representing the response. + + Returns: + True if the language of `value` follows instruction; otherwise False. + """ + assert isinstance(value, str) + + try: + return langdetect.detect(value) == self._language + except langdetect.LangDetectException as e: + # Count as instruction is followed. + logging.error( + "Unable to detect language for text %s due to %s", value, e + ) # refex: disable=pytotw.037 + return True + + +class NumberOfSentences(Instruction): + """Check the number of sentences.""" + + def build_description(self, *, num_sentences=None, relation=None): + """Build the instruction description. + + Args: + num_sentences: An integer specifying the number of sentences as a + threshold. + relation: A string in (`less than`, `at least`), defining the relational + operator for comparison. + Two relational comparisons are supported for now: + if 'less than', the actual number of sentences < the threshold; + if 'at least', the actual number of sentences >= the threshold. + + Returns: + A string representing the instruction description. + """ + # The number of sentences as a threshold for comparison. + self._num_sentences_threshold = num_sentences + if self._num_sentences_threshold is None or self._num_sentences_threshold < 0: + self._num_sentences_threshold = random.randint(1, _MAX_NUM_SENTENCES) + + if relation is None: + self._comparison_relation = random.choice(_COMPARISON_RELATION) + elif relation not in _COMPARISON_RELATION: + raise ValueError( + "The supported relation for comparison must be in " + f"{_COMPARISON_RELATION}, but {relation} is given." + ) + else: + self._comparison_relation = relation + + self._description_pattern = ( + "Your response should contain {relation} {num_sentences} sentences." + ) + return self._description_pattern.format( + relation=self._comparison_relation, + num_sentences=self._num_sentences_threshold, + ) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return { + "num_sentences": self._num_sentences_threshold, + "relation": self._comparison_relation, + } + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["num_sentences", "relation"] + + def check_following(self, value): + """Check if the number of sentences follows the instruction. + + Args: + value: A string representing the response. + + Returns: + True if the response follows the instruction. + + Raise: + ValueError if the string in `instruction_args` is not in + [`less_than`, `at_least`]. + """ + num_sentences = instructions_util.count_sentences(value) + if self._comparison_relation == _COMPARISON_RELATION[0]: + return num_sentences < self._num_sentences_threshold + elif self._comparison_relation == _COMPARISON_RELATION[1]: + return num_sentences >= self._num_sentences_threshold + + +class PlaceholderChecker(Instruction): + """Check the placeholders in template writing.""" + + def build_description(self, *, num_placeholders=None): + """Build the instruction description. + + Args: + num_placeholders: An integer denoting the minimum number of + placeholders required in the response. + + Returns: + A string representing the instruction description. + """ + self._num_placeholders = num_placeholders + if self._num_placeholders is None or self._num_placeholders < 0: + self._num_placeholders = random.randint(1, _NUM_PLACEHOLDERS) + self._description_pattern = ( + "The response must contain at least {num_placeholders} placeholders " + + "represented by square brackets, such as [address]." + ) + return self._description_pattern.format(num_placeholders=self._num_placeholders) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"num_placeholders": self._num_placeholders} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["num_placeholders"] + + def check_following(self, value): + """Check if the number of placeholders follows the instruction. + + Args: + value: A string representing the response. + + Returns: + True if the actual number of placeholders in the response is greater than + or equal to `num_placeholders`; otherwise, False. + """ + placeholders = re.findall(r"\[.*?\]", value) + num_placeholders = len(placeholders) + return num_placeholders >= self._num_placeholders + + +class BulletListChecker(Instruction): + """Checks the bullet list in the prompt.""" + + def build_description(self, *, num_bullets=None): + """Build the instruction description. + + Args: + num_bullets: An integer specifying the exact number of bullet lists + that is required to appear in the response. + + Returns: + A string representing the instruction description. + """ + self._num_bullets = num_bullets + if self._num_bullets is None or self._num_bullets < 0: + self._num_bullets = random.randint(1, _NUM_BULLETS) + self._description_pattern = ( + "Your answer must contain exactly {num_bullets} bullet points. " + + "Use the markdown bullet points such as:\n" + + "* This is point 1. \n" + + "* This is point 2" + ) + return self._description_pattern.format(num_bullets=self._num_bullets) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"num_bullets": self._num_bullets} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["num_bullets"] + + def check_following(self, value): + r"""Check if the number of bullet lists meets the requirement. + + Args: + value: A string representing the response. The response is expected to + contain some bullet lists that start with `\*`. + + Returns: + True if the actual number of bullet lists in the response meets the + requirement. + """ + bullet_lists = re.findall(r"^\s*\*[^\*].*$", value, flags=re.MULTILINE) + bullet_lists_2 = re.findall(r"^\s*-.*$", value, flags=re.MULTILINE) + num_bullet_lists = len(bullet_lists) + len(bullet_lists_2) + return num_bullet_lists == self._num_bullets + + +class ConstrainedResponseChecker(Instruction): + """Checks the constrained response.""" + + def build_description(self): + """Build the instruction description.""" + # A sequence of string(s) representing the options of the expected response. + self._constrained_responses = _CONSTRAINED_RESPONSE_OPTIONS + self._description_pattern = ( + "Answer with one of the following options: {response_options}" + ) + return self._description_pattern.format( + response_options=self._constrained_responses + ) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return None + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return [] + + def check_following(self, value): + """Checks if the response matches the constrained options. + + Args: + value: A string representing the response. + + Returns: + True if the actual response contains one of the options in the constrained + responses; otherwise False. + """ + value = value.strip() + for constrained_response in self._constrained_responses: + if constrained_response in value: + return True + return False + + +class ConstrainedStartChecker(Instruction): + """Checks the response start.""" + + def build_description(self, *, starter=None): + """Build the instruction description. + + Args: + starter: A string representing the keyward that the response should start + with. + + Returns: + A string representing the instruction description. + """ + self._starter = starter.strip() if isinstance(starter, str) else starter + if self._starter is None: + self._starter = random.choice(_STARTER_OPTIONS) + self._description_pattern = ( + "During the conversation, when it is your turn, " + + "please always start with {starter}" + ) + return self._description_pattern.format(starter=self._starter) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"starter": self._starter} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["starter"] + + def check_following(self, value): + """Checks if the response starts with the constrained keyword or phrase. + + Args: + value: A string representing the response. + + Returns: + True if the response starts with the given phrase or keyword that is + contained in `instruction_args`; otherwise, False. + """ + response_pattern = r"^\s*" + self._starter + r".*$" + response_with_constrained_start = re.search( + response_pattern, value, flags=re.MULTILINE + ) + return True if response_with_constrained_start else False + + +class HighlightSectionChecker(Instruction): + """Checks the highlighted section.""" + + def build_description(self, *, num_highlights=None): + """Build the instruction description. + + Args: + num_highlights: An integer specifying the minimum number of highlighted + sections. + + Returns: + A string representing the instruction description. + """ + self._num_highlights = num_highlights + if self._num_highlights is None or self._num_highlights < 0: + self._num_highlights = random.randint(1, _NUM_HIGHLIGHTED_SECTIONS) + + self._description_pattern = ( + "Highlight at least {num_highlights} sections in your answer with " + + "markdown, i.e. *highlighted section*." + ) + + return self._description_pattern.format(num_highlights=self._num_highlights) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"num_highlights": self._num_highlights} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["num_highlights"] + + def check_following(self, value): + """Checks if the number of highlighted sections meets the requirement. + + Args: + value: a string repesenting the response. The response is expected to + contain highlighted sections in the format of *highlighted*. + + Returns: + True if the actual number of highlighted sections in the format of + *highlighed sections* meets the minimum requirement; otherwise False. + """ + num_highlights = 0 + highlights = re.findall(r"\*[^\n\*]*\*", value) + double_highlights = re.findall(r"\*\*[^\n\*]*\*\*", value) + for highlight in highlights: + if highlight.strip("*").strip(): + num_highlights += 1 + for highlight in double_highlights: + if highlight.removeprefix("**").removesuffix("**").strip(): + num_highlights += 1 + + return num_highlights >= self._num_highlights + + +class SectionChecker(Instruction): + """Checks the sections.""" + + def build_description(self, *, section_spliter=None, num_sections=None): + """Build the instruction description. + + Args: + section_spliter: A string represents the section spliter keyword that + marks a new section, i.e., `Section` or `SECTION`. + num_sections: An integer specifying the number of sections. + + Returns: + A string representing the instruction description. + """ + self._section_spliter = ( + section_spliter.strip() + if isinstance(section_spliter, str) + else section_spliter + ) + if self._section_spliter is None: + self._section_spliter = random.choice(_SECTION_SPLITER) + + self._num_sections = num_sections + if self._num_sections is None or self._num_sections < 0: + self._num_sections = random.randint(1, _NUM_SECTIONS) + + self._description_pattern = ( + "Your response must have {num_sections} sections. Mark the beginning " + + "of each section with {section_spliter} X, such as:\n" + + "{section_spliter} 1\n" + + "[content of section 1]\n" + + "{section_spliter} 2\n" + + "[content of section 2]" + ) + + return self._description_pattern.format( + num_sections=self._num_sections, section_spliter=self._section_spliter + ) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return { + "section_spliter": self._section_spliter, + "num_sections": self._num_sections, + } + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["section_spliter", "num_sections"] + + def check_following(self, value): + """Checks the response contains multiple sections. + + Args: + value: A string representing the response. The response is expected + to contain multiple sections (number of sections is greater than 1). + A new section starts with `Section 1`, where the number denotes the + section index. + + Returns: + True if the number of sections in the response is greater than or equal to + the minimum number of sections; otherwise, False. + """ + section_splitter_patten = r"\s?" + self._section_spliter + r"\s?\d+\s?" + sections = re.split(section_splitter_patten, value) + num_sections = len(sections) - 1 + return num_sections >= self._num_sections + + +class ParagraphChecker(Instruction): + """Checks the paragraphs.""" + + def build_description(self, *, num_paragraphs=None): + """Build the instruction description. + + Args: + num_paragraphs: An integer specifying the number of paragraphs. + + Returns: + A string representing the instruction description. + """ + self._num_paragraphs = num_paragraphs + if self._num_paragraphs is None or self._num_paragraphs < 0: + self._num_paragraphs = random.randint(1, _NUM_PARAGRAPHS) + + self._description_pattern = ( + "There should be {num_paragraphs} paragraphs. " + + "Paragraphs are separated with the markdown divider: ***" + ) + + return self._description_pattern.format(num_paragraphs=self._num_paragraphs) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"num_paragraphs": self._num_paragraphs} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["num_paragraphs"] + + def check_following(self, value): + """Checks the response contains required number of paragraphs. + + Args: + value: A string representing the response. The response may contain + paragraphs that are separated by the markdown divider: `***`. + + Returns: + True if the actual number of paragraphs is the same as required; + otherwise, False. + """ + paragraphs = re.split(r"\s?\*\*\*\s?", value) + num_paragraphs = len(paragraphs) + + for index, paragraph in enumerate(paragraphs): + if not paragraph.strip(): + if index == 0 or index == len(paragraphs) - 1: + num_paragraphs -= 1 + else: + return False + + return num_paragraphs == self._num_paragraphs + + +class PostscriptChecker(Instruction): + """Checks the postscript.""" + + def build_description(self, *, postscript_marker=None): + """Build the instruction description. + + Args: + postscript_marker: A string containing the keyword that marks the start + of the postscript section. + + Returns: + A string representing the instruction description. + """ + self._postscript_marker = ( + postscript_marker.strip() + if isinstance(postscript_marker, str) + else postscript_marker + ) + if self._postscript_marker is None: + self._postscript_marker = random.choice(_POSTSCRIPT_MARKER) + + self._description_pattern = ( + "At the end of your response, please explicitly add a postscript " + + "starting with {postscript}" + ) + + return self._description_pattern.format(postscript=self._postscript_marker) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"postscript_marker": self._postscript_marker} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["postscript_marker"] + + def check_following(self, value): + """Checks if the response follows the postscript format. + + Args: + value: a string representing the response. The response is expected to + contain a postscript section. + + Returns: + True if the response contains a postscript section starting with + the keyword containing in the `instruction_args`; otherwise False. + """ + value = value.lower() + if self._postscript_marker == "P.P.S": + postscript_pattern = r"\s*p\.\s?p\.\s?s.*$" + elif self._postscript_marker == "P.S.": + postscript_pattern = r"\s*p\.\s?s\..*$" + else: + postscript_pattern = r"\s*" + self._postscript_marker.lower() + r".*$" + postscript = re.findall(postscript_pattern, value, flags=re.MULTILINE) + return True if postscript else False + + +class RephraseChecker(Instruction): + """Checks the repharse.""" + + def build_description(self, *, original_message): + """Build the instruction description. + + Args: + original_message: A string representing the original message. The + rephrased response should only change its words/sentences in between + its two asterisks, for example, *change me*. Both original and rephrased + messages should contain the changes in the form of *change me*. + + Returns: + A string representing the instruction description. + """ + if not self.is_change(original_message): + raise ValueError( + f"Message {original_message} does not contain changes " + "in the form of *change me*." + ) + + self._reference_without_change = original_message + self._description = ( + "Rephrasing: Your rephrased response should only" + + "change the words/sentences in between two asterisks" + + "such as *change me*." + ) + return self._description + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"original_message": self._reference_without_change} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["original_message"] + + def check_following(self, value): + r"""Checks if the rephrasing follows the instruction. + + Args: + value: A string representing the response, which is expected to rephras + the string of `instruction_args`. + + Returns: + True if `value` and `instruction_args` only differ by the words/sentences + in between two asterisks such as *change me*; otherwise, False. + """ + + if not self.is_change(value): + raise ValueError( + f"value {value} does not contain " "changes in the form of *change me*." + ) + + response_without_changes = self.strip_changes(value) + reference_without_changes = self.strip_changes(self._reference_without_change) + + return response_without_changes == reference_without_changes + + def is_change(self, response): + """Check if there is change in the response in the form of *change me*.""" + return re.search(r"\*.*\*", response) + + def strip_changes(self, response): + """Strips off the changes.""" + return re.sub(r"\*.*\*", "", response) + + +class KeywordChecker(Instruction): + """Check the exisitence of certain keywords.""" + + def build_description(self, *, keywords=None): + """Build the instruction description. + + Args: + keywords: A sequence of strings representing the keywords that are + expected in the response. + + Returns: + A string representing the instruction description. + """ + + if not keywords: + self._keywords = instructions_util.generate_keywords( + num_keywords=_NUM_KEYWORDS + ) + else: + self._keywords = keywords + self._keywords = sorted(self._keywords) + + self._description_pattern = "Include keywords {keywords} in the response." + + return self._description_pattern.format(keywords=self._keywords) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"keywords": self._keywords} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["keywords"] + + def check_following(self, value): + """Check if the response contain the expected keywords.""" + for keyword in self._keywords: + if not re.search(keyword, value, flags=re.IGNORECASE): + return False + return True + + +class KeywordFrequencyChecker(Instruction): + """Check the keyword frequency.""" + + def build_description(self, *, keyword=None, frequency=None, relation=None): + """Build the instruction description. + + Args: + keyword: A string representing a keyword that is expected in the response. + frequency: An integer specifying the number of times `keyword` is expected + to appear in the response. + relation: A string in (`less than`, `at least`), defining the relational + operator for comparison. + Two relational comparisons are supported for now: + if 'less than', the actual number of occurrences < frequency; + if 'at least', the actual number of occurrences >= frequency. + + Returns: + A string representing the instruction description. + """ + if not keyword: + self._keyword = instructions_util.generate_keywords(num_keywords=1)[0] + else: + self._keyword = keyword.strip() + + self._frequency = frequency + if self._frequency is None or self._frequency < 0: + self._frequency = random.randint(1, _KEYWORD_FREQUENCY) + + if relation is None: + self._comparison_relation = random.choice(_COMPARISON_RELATION) + elif relation not in _COMPARISON_RELATION: + raise ValueError( + "The supported relation for comparison must be in " + f"{_COMPARISON_RELATION}, but {relation} is given." + ) + else: + self._comparison_relation = relation + + self._description_pattern = ( + "In your response, the word {keyword} should appear {relation} " + + "{frequency} times." + ) + + return self._description_pattern.format( + keyword=self._keyword, + relation=self._comparison_relation, + frequency=self._frequency, + ) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return { + "keyword": self._keyword, + "frequency": self._frequency, + "relation": self._comparison_relation, + } + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["keyword", "frequency", "relation"] + + def check_following(self, value): + """Checks if the response contain the keyword with required frequency.""" + actual_occurrences = len(re.findall(self._keyword, value, flags=re.IGNORECASE)) + + if self._comparison_relation == _COMPARISON_RELATION[0]: + return actual_occurrences < self._frequency + elif self._comparison_relation == _COMPARISON_RELATION[1]: + return actual_occurrences >= self._frequency + + +class NumberOfWords(Instruction): + """Checks the number of words.""" + + def build_description(self, *, num_words=None, relation=None): + """Build the instruction description. + + Args: + num_words: An integer specifying the number of words contained in the + response. + relation: A string in (`less than`, `at least`), defining the relational + operator for comparison. + Two relational comparisons are supported for now: + if 'less than', the actual number of words < num_words; + if 'at least', the actual number of words >= num_words. + + Returns: + A string representing the instruction description. + """ + + self._num_words = num_words + if self._num_words is None or self._num_words < 0: + self._num_words = random.randint( + _NUM_WORDS_LOWER_LIMIT, _NUM_WORDS_UPPER_LIMIT + ) + + if relation is None: + self._comparison_relation = random.choice(_COMPARISON_RELATION) + elif relation not in _COMPARISON_RELATION: + raise ValueError( + "The supported relation for comparison must be in " + f"{_COMPARISON_RELATION}, but {relation} is given." + ) + else: + self._comparison_relation = relation + + self._description_pattern = "Answer with {relation} {num_words} words." + + return self._description_pattern.format( + relation=self._comparison_relation, num_words=self._num_words + ) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"num_words": self._num_words, "relation": self._comparison_relation} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["num_words", "relation"] + + def check_following(self, value): + """Checks if the response contains the expected number of words.""" + num_words = instructions_util.count_words(value) + + if self._comparison_relation == _COMPARISON_RELATION[0]: + return num_words < self._num_words + elif self._comparison_relation == _COMPARISON_RELATION[1]: + return num_words >= self._num_words + + +class JsonFormat(Instruction): + """Check the Json format.""" + + def build_description(self): + self._description_pattern = ( + "Entire output should be wrapped in JSON format. You can use markdown" + " ticks such as ```." + ) + return self._description_pattern + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return None + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return [] + + def check_following(self, value): + value = ( + value.strip() + .removeprefix("```json") + .removeprefix("```Json") + .removeprefix("```JSON") + .removeprefix("```") + .removesuffix("```") + .strip() + ) + try: + json.loads(value) + except ValueError: + return False + return True + + +class ParagraphFirstWordCheck(Instruction): + """Check the paragraph and the first word of the nth paragraph.""" + + def build_description( + self, num_paragraphs=None, nth_paragraph=None, first_word=None + ): + r"""Build the instruction description. + + Args: + num_paragraphs: An integer indicating the number of paragraphs expected + in the response. A paragraph is a subset of the string that is + expected to be separated by '\n\n'. + nth_paragraph: An integer indicating the paragraph number that we look at. + Note that n starts from 1. + first_word: A string that represent the first word of the bth paragraph. + + Returns: + A string representing the instruction description. + """ + self._num_paragraphs = num_paragraphs + if self._num_paragraphs is None or self._num_paragraphs < 0: + self._num_paragraphs = random.randint(1, _NUM_PARAGRAPHS) + + self._nth_paragraph = nth_paragraph + if ( + self._nth_paragraph is None + or self._nth_paragraph <= 0 + or self._nth_paragraph > self._num_paragraphs + ): + self._nth_paragraph = random.randint(1, self._num_paragraphs + 1) + + self._first_word = first_word + if self._first_word is None: + self._first_word = instructions_util.generate_keywords(num_keywords=1)[0] + self._first_word = self._first_word.lower() + + self._description_pattern = ( + "There should be {num_paragraphs} paragraphs. " + + "Paragraphs and only paragraphs are separated with each other by two " + + "new lines as if it was '\\n\\n' in python. " + + "Paragraph {nth_paragraph} must start with word {first_word}." + ) + + return self._description_pattern.format( + num_paragraphs=self._num_paragraphs, + nth_paragraph=self._nth_paragraph, + first_word=self._first_word, + ) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return { + "num_paragraphs": self._num_paragraphs, + "nth_paragraph": self._nth_paragraph, + "first_word": self._first_word, + } + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["num_paragraphs", "nth_paragraph", "first_word"] + + def check_following(self, value): + """Checks for required number of paragraphs and correct first word. + + Args: + value: a string representing the response. The response may contain + paragraphs that are separated by two new lines and the first word of + the nth paragraph will have to match a specified word. + + Returns: + True if the number of paragraphs is the same as required and the first + word of the specified paragraph is the same as required. Otherwise, false. + """ + + paragraphs = re.split(r"\n\n", value) + num_paragraphs = len(paragraphs) + + for paragraph in paragraphs: + if not paragraph.strip(): + num_paragraphs -= 1 + + # check that index doesn't go out of bounds + if self._nth_paragraph <= num_paragraphs: + paragraph = paragraphs[self._nth_paragraph - 1].strip() + if not paragraph: + return False + else: + return False + + first_word = "" + punctuation = {".", ",", "?", "!", "'", '"'} + + # get first word and remove punctuation + word = paragraph.split()[0].strip() + # TODO(jeffrey): make more complex? + word = word.lstrip("'") + word = word.lstrip('"') + + for letter in word: + if letter in punctuation: + break + first_word += letter.lower() + + return num_paragraphs == self._num_paragraphs and first_word == self._first_word + + +# TODO(jeffrey) add relation - at least/at most? +class KeySentenceChecker(Instruction): + """Check the existence of certain key sentences.""" + + def build_description(self, key_sentences=None, num_sentences=None): + """Build the instruction description. + + Args: + key_sentences: A sequences of strings representing the key sentences that + are expected in the response. + num_sentences: The number of key sentences that are expected to be seen in + the response. + + Returns: + A string representing the instruction description. + """ + + if not key_sentences: + # TODO(jeffrey) make a generate sentences function? wonderwords package + self._key_sentences = set(["For now, this is fine."]) + else: + self._key_sentences = key_sentences + + if not num_sentences: + self._num_sentences = random.randint(1, len(self._key_sentences)) + else: + self._num_sentences = num_sentences + + self._description_pattern = ( + "Include {num_sentences} of the following sentences {key_sentences}" + ) + + return self._description_pattern.format( + num_sentences=self._num_sentences, key_sentences=self._key_sentences + ) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return { + "num_sentences": self._num_sentences, + "key_sentences": list(self._key_sentences), + } + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["num_sentences", "key_sentences"] + + def check_following(self, value): + """Checks if the response contains the expected key sentences.""" + count = 0 + sentences = instructions_util.split_into_sentences(value) + for sentence in self._key_sentences: + if sentence in sentences: + count += 1 + + return count == self._num_sentences + + +class ForbiddenWords(Instruction): + """Checks that specified words are not used in response.""" + + def build_description(self, forbidden_words=None): + """Build the instruction description. + + Args: + forbidden_words: A sequences of strings respresenting words that are not + allowed in the response. + + Returns: + A string representing the instruction description. + """ + + if not forbidden_words: + self._forbidden_words = instructions_util.generate_keywords( + num_keywords=_NUM_KEYWORDS + ) + else: + self._forbidden_words = list(set(forbidden_words)) + self._forbidden_words = sorted(self._forbidden_words) + self._description_pattern = ( + "Do not include keywords {forbidden_words} in the response." + ) + + return self._description_pattern.format(forbidden_words=self._forbidden_words) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return {"forbidden_words": self._forbidden_words} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["forbidden_words"] + + def check_following(self, value): + """Check if the response does not contain the expected keywords.""" + for word in self._forbidden_words: + if re.search(r"\b" + word + r"\b", value, flags=re.IGNORECASE): + return False + return True + + +class RephraseParagraph(Instruction): + """Checks that the paragraph is rephrased.""" + + def build_description(self, *, original_paragraph, low, high): + """Builds the instruction description. + + Args: + original_paragraph: A string presenting the original paragraph. The + rephrases response should have betweeb low-high words in common. + low: An integer presenting the lower bound of similar words. + high: An integer representing the upper bound of similar words. + + Returns: + A string representing the instruction description. + """ + # TODO(jeffrey) make more encompassing + self._original_paragraph = original_paragraph + self._low = low + self._high = high + + self._description = ( + "Rephrase the following paragraph: " + + "{original_paragraph}\nYour response should have " + + "between {low} and {high} of the same words. " + + "Words are the same if and only if all of the " + + "letters, ignoring cases, are the same. For " + + "example, 'run' is the same as 'Run' but different " + + "to 'ran'." + ) + + return self._description.format( + original_paragraph=original_paragraph, low=self._low, high=self._high + ) + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return { + "original_paragraph": self._original_paragraph, + "low": self._low, + "high": self._high, + } + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["original_paragraph", "low", "high"] + + def check_following(self, value): + val_words = re.findall(r"\w+", value.lower()) + original_words = re.findall(r"\w+", self._original_paragraph.lower()) + similar_words = 0 + + dict_val = collections.Counter(val_words) + dict_original = collections.Counter(original_words) + + for word in dict_original: + similar_words += min(dict_original[word], dict_val[word]) + + return similar_words >= self._low and similar_words <= self._high + + +class TwoResponsesChecker(Instruction): + """Check that two responses were given.""" + + def build_description(self): + """Build the instruction description.""" + self._description_pattern = ( + "Give two different responses. Responses and only responses should" + " be separated by 6 asterisk symbols: ******." + ) + return self._description_pattern + + def get_instruction_args(self): + """Returns the keyward args of `build_description`.""" + return None + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return [] + + def check_following(self, value): + """Checks if the response has two different answers. + + Args: + value: A string representing the response. + + Returns: + True if two responses are detected and false otherwise. + """ + valid_responses = list() + responses = value.split("******") + for index, response in enumerate(responses): + if not response.strip(): + if index != 0 and index != len(responses) - 1: + return False + else: + valid_responses.append(response) + return ( + len(valid_responses) == 2 + and valid_responses[0].strip() != valid_responses[1].strip() + ) + + +class RepeatPromptThenAnswer(Instruction): + """Checks that Prompt is first repeated then answered.""" + + def build_description(self, *, prompt_to_repeat=None): + """Build the instruction description. + + Args: + prompt_to_repeat: The prompt that is meant to be repeated. + + Returns: + A string representing the instruction description. + """ + if not prompt_to_repeat: + raise ValueError("prompt_to_repeat must be set.") + else: + self._prompt_to_repeat = prompt_to_repeat + self._description_pattern = ( + "First repeat the request word for word without change," + " then give your answer (1. do not say any words or characters" + " before repeating the request; 2. the request you need to repeat" + " does not include this sentence)" + ) + return self._description_pattern + + def get_instruction_args(self): + return {"prompt_to_repeat": self._prompt_to_repeat} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["prompt_to_repeat"] + + def check_following(self, value): + if value.strip().lower().startswith(self._prompt_to_repeat.strip().lower()): + return True + return False + + +class EndChecker(Instruction): + """Checks that the prompt ends with a given phrase.""" + + def build_description(self, *, end_phrase=None): + """Build the instruction description. + + Args: + end_phrase: A string representing the phrase the response should end with. + + Returns: + A string representing the instruction description. + """ + self._end_phrase = ( + end_phrase.strip() if isinstance(end_phrase, str) else end_phrase + ) + if self._end_phrase is None: + self._end_phrase = random.choice(_ENDING_OPTIONS) + self._description_pattern = ( + "Finish your response with this exact phrase {ender}. " + "No other words should follow this phrase." + ) + return self._description_pattern.format(ender=self._end_phrase) + + def get_instruction_args(self): + return {"end_phrase": self._end_phrase} + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["end_phrase"] + + def check_following(self, value): + """Checks if the response ends with the expected phrase.""" + value = value.strip().strip('"').lower() + self._end_phrase = self._end_phrase.strip().lower() + return value.endswith(self._end_phrase) + + +class TitleChecker(Instruction): + """Checks the response for a title.""" + + def build_description(self): + """Build the instruction description.""" + self._description_pattern = ( + "Your answer must contain a title, wrapped in double angular brackets," + " such as <>." + ) + return self._description_pattern + + def get_instruction_args(self): + return None + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return [] + + def check_following(self, value): + """Checks if the response contains a title.""" + pattern = r"<<[^\n]+>>" + re_pattern = re.compile(pattern) + titles = re.findall(re_pattern, value) + + for title in titles: + if title.lstrip("<").rstrip(">").strip(): + return True + return False + + +class LetterFrequencyChecker(Instruction): + """Checks letter frequency.""" + + def build_description(self, *, letter=None, let_frequency=None, let_relation=None): + """Build the instruction description. + + Args: + letter: A string representing a letter that is expected in the response. + let_frequency: An integer specifying the number of times `keyword` is + expected to appear in the response. + let_relation: A string in (`less than`, `at least`), defining the + relational operator for comparison. Two relational comparisons are + supported for now; if 'less than', the actual number of + occurrences < frequency; if 'at least', the actual number of + occurrences >= frequency. + + Returns: + A string representing the instruction description. + """ + if ( + not letter + or len(letter) > 1 + or ord(letter.lower()) < 97 + or ord(letter.lower()) > 122 + ): + self._letter = random.choice(list(string.ascii_letters)) + else: + self._letter = letter.strip() + self._letter = self._letter.lower() + + self._frequency = let_frequency + if self._frequency is None or self._frequency < 0: + self._frequency = random.randint(1, _LETTER_FREQUENCY) + + if let_relation is None: + self._comparison_relation = random.choice(_COMPARISON_RELATION) + elif let_relation not in _COMPARISON_RELATION: + raise ValueError( + "The supported relation for comparison must be in " + f"{_COMPARISON_RELATION}, but {let_relation} is given." + ) + else: + self._comparison_relation = let_relation + + self._description_pattern = ( + "In your response, the letter {letter} should appear {let_relation}" + " {let_frequency} times." + ) + + return self._description_pattern.format( + letter=self._letter, + let_frequency=self._frequency, + let_relation=self._comparison_relation, + ) + + def get_instruction_args(self): + """Returns the keyword args of build description.""" + return { + "letter": self._letter, + "let_frequency": self._frequency, + "let_relation": self._comparison_relation, + } + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["letter", "let_frequency", "let_relation"] + + def check_following(self, value): + """Checks that the response contains the letter at the right frequency.""" + value = value.lower() + letters = collections.Counter(value) + + if self._comparison_relation == _COMPARISON_RELATION[0]: + return letters[self._letter] < self._frequency + else: + return letters[self._letter] >= self._frequency + + +class CapitalLettersEnglishChecker(Instruction): + """Checks that the response is in english and is in all capital letters.""" + + def build_description(self): + """Build the instruction description.""" + self._description_pattern = ( + "Your entire response should be in English, and in all capital letters." + ) + return self._description_pattern + + def get_instruction_args(self): + return None + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return [] + + def check_following(self, value): + """Checks that the response is in English and in all capital letters.""" + assert isinstance(value, str) + + try: + return value.isupper() and langdetect.detect(value) == "en" + except langdetect.LangDetectException as e: + # Count as instruction is followed. + logging.error( + "Unable to detect language for text %s due to %s", value, e + ) # refex: disable=pytotw.037 + return True + + +class LowercaseLettersEnglishChecker(Instruction): + """Checks that the response is in english and is in all lowercase letters.""" + + def build_description(self): + """Build the instruction description.""" + self._description_pattern = ( + "Your entire response should be in English, and in all lowercase" + " letters. No capital letters are allowed." + ) + return self._description_pattern + + def get_instruction_args(self): + return None + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return [] + + def check_following(self, value): + """Checks that the response is in English and in all lowercase letters.""" + assert isinstance(value, str) + + try: + return value.islower() and langdetect.detect(value) == "en" + except langdetect.LangDetectException as e: + # Count as instruction is followed. + logging.error( + "Unable to detect language for text %s due to %s", value, e + ) # refex: disable=pytotw.037 + return True + + +class CommaChecker(Instruction): + """Checks the response for no commas.""" + + def build_description(self): + """Build the instruction description.""" + self._description_pattern = ( + "In your entire response, refrain from the use of any commas." + ) + return self._description_pattern + + def get_instruction_args(self): + return None + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return [] + + def check_following(self, value): + """Checks that the response does not contain commas.""" + return not re.search(r"\,", value) + + +class CapitalWordFrequencyChecker(Instruction): + """Checks frequency of words with all capital letters.""" + + def build_description( + self, + capital_frequency=None, + capital_relation=None, + ): + """Build the instruction description. + + Args: + capital_frequency: An integer that represents the number of words that + should be in all capital letters. + capital_relation: A string that is 'at least' or 'at most' that refers to + the frequency. + + Returns: + A string representing the instruction description. + """ + self._frequency = capital_frequency + if self._frequency is None: + self._frequency = random.randint(1, _ALL_CAPITAL_WORD_FREQUENCY) + + self._comparison_relation = capital_relation + if capital_relation is None: + self._comparison_relation = random.choice(_COMPARISON_RELATION) + elif capital_relation not in _COMPARISON_RELATION: + raise ValueError( + "The supported relation for comparison must be in " + f"{_COMPARISON_RELATION}, but {capital_relation} is given." + ) + + self._description_pattern = ( + "In your response, words with all capital letters should appear" + " {relation} {frequency} times." + ) + + return self._description_pattern.format( + frequency=self._frequency, relation=self._comparison_relation + ) + + def get_instruction_args(self): + """Returns the keyword args of build description.""" + return { + "capital_frequency": self._frequency, + "capital_relation": self._comparison_relation, + } + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return ["capital_frequency", "capital_relation"] + + def check_following(self, value): + """Checks the frequency of words with all capital letters.""" + # Hyphenated words will count as one word + words = instructions_util.nltk.word_tokenize(value) + capital_words = [word for word in words if word.isupper()] + + capital_words = len(capital_words) + + if self._comparison_relation == _COMPARISON_RELATION[0]: + return capital_words < self._frequency + else: + return capital_words >= self._frequency + + +class QuotationChecker(Instruction): + """Checks response is wrapped with double quotation marks.""" + + def build_description(self): + """Build the instruction description.""" + self._description_pattern = ( + "Wrap your entire response with double quotation marks." + ) + return self._description_pattern + + def get_instruction_args(self): + """Returns the keyword args of build description.""" + return None + + def get_instruction_args_keys(self): + """Returns the args keys of `build_description`.""" + return [] + + def check_following(self, value): + """Checks if the response is wrapped with double quotation marks.""" + value = value.strip() + return len(value) > 1 and value[0] == '"' and value[-1] == '"' diff --git a/lm_eval/tasks/leaderboard/ifeval/instructions_registry.py b/lm_eval/tasks/leaderboard/ifeval/instructions_registry.py new file mode 100644 index 00000000..00d9a1de --- /dev/null +++ b/lm_eval/tasks/leaderboard/ifeval/instructions_registry.py @@ -0,0 +1,168 @@ +# Copyright 2023 The Google Research Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Registry of all instructions.""" + +from lm_eval.tasks.ifeval import instructions + + +_KEYWORD = "keywords:" + +_LANGUAGE = "language:" + +_LENGTH = "length_constraints:" + +_CONTENT = "detectable_content:" + +_FORMAT = "detectable_format:" + +_MULTITURN = "multi-turn:" + +_COMBINATION = "combination:" + +_STARTEND = "startend:" + +_CHANGE_CASES = "change_case:" + +_PUNCTUATION = "punctuation:" + +INSTRUCTION_DICT = { + _KEYWORD + "existence": instructions.KeywordChecker, + _KEYWORD + "frequency": instructions.KeywordFrequencyChecker, + # TODO(jeffreyzhou): make a proper set of sentences to choose from + # _KEYWORD + "key_sentences": instructions.KeySentenceChecker, + _KEYWORD + "forbidden_words": instructions.ForbiddenWords, + _KEYWORD + "letter_frequency": instructions.LetterFrequencyChecker, + _LANGUAGE + "response_language": instructions.ResponseLanguageChecker, + _LENGTH + "number_sentences": instructions.NumberOfSentences, + _LENGTH + "number_paragraphs": instructions.ParagraphChecker, + _LENGTH + "number_words": instructions.NumberOfWords, + _LENGTH + "nth_paragraph_first_word": instructions.ParagraphFirstWordCheck, + _CONTENT + "number_placeholders": instructions.PlaceholderChecker, + _CONTENT + "postscript": instructions.PostscriptChecker, + _FORMAT + "number_bullet_lists": instructions.BulletListChecker, + # TODO(jeffreyzhou): Pre-create paragraph or use prompt to replace + # _CONTENT + "rephrase_paragraph": instructions.RephraseParagraph, + _FORMAT + "constrained_response": instructions.ConstrainedResponseChecker, + _FORMAT + "number_highlighted_sections": (instructions.HighlightSectionChecker), + _FORMAT + "multiple_sections": instructions.SectionChecker, + # TODO(tianjianlu): Re-enable rephrasing with preprocessing the message. + # _FORMAT + "rephrase": instructions.RephraseChecker, + _FORMAT + "json_format": instructions.JsonFormat, + _FORMAT + "title": instructions.TitleChecker, + # TODO(tianjianlu): Re-enable with specific prompts. + # _MULTITURN + "constrained_start": instructions.ConstrainedStartChecker, + _COMBINATION + "two_responses": instructions.TwoResponsesChecker, + _COMBINATION + "repeat_prompt": instructions.RepeatPromptThenAnswer, + _STARTEND + "end_checker": instructions.EndChecker, + _CHANGE_CASES + "capital_word_frequency": instructions.CapitalWordFrequencyChecker, + _CHANGE_CASES + "english_capital": instructions.CapitalLettersEnglishChecker, + _CHANGE_CASES + "english_lowercase": instructions.LowercaseLettersEnglishChecker, + _PUNCTUATION + "no_comma": instructions.CommaChecker, + _STARTEND + "quotation": instructions.QuotationChecker, +} + +INSTRUCTION_CONFLICTS = { + _KEYWORD + "existence": {_KEYWORD + "existence"}, + _KEYWORD + "frequency": {_KEYWORD + "frequency"}, + # TODO(jeffreyzhou): make a proper set of sentences to choose from + # _KEYWORD + "key_sentences": instructions.KeySentenceChecker, + _KEYWORD + "forbidden_words": {_KEYWORD + "forbidden_words"}, + _KEYWORD + "letter_frequency": {_KEYWORD + "letter_frequency"}, + _LANGUAGE + "response_language": { + _LANGUAGE + "response_language", + _FORMAT + "multiple_sections", + _KEYWORD + "existence", + _KEYWORD + "frequency", + _KEYWORD + "forbidden_words", + _STARTEND + "end_checker", + _CHANGE_CASES + "english_capital", + _CHANGE_CASES + "english_lowercase", + }, + _LENGTH + "number_sentences": {_LENGTH + "number_sentences"}, + _LENGTH + "number_paragraphs": { + _LENGTH + "number_paragraphs", + _LENGTH + "nth_paragraph_first_word", + _LENGTH + "number_sentences", + _LENGTH + "nth_paragraph_first_word", + }, + _LENGTH + "number_words": {_LENGTH + "number_words"}, + _LENGTH + "nth_paragraph_first_word": { + _LENGTH + "nth_paragraph_first_word", + _LENGTH + "number_paragraphs", + }, + _CONTENT + "number_placeholders": {_CONTENT + "number_placeholders"}, + _CONTENT + "postscript": {_CONTENT + "postscript"}, + _FORMAT + "number_bullet_lists": {_FORMAT + "number_bullet_lists"}, + # TODO(jeffreyzhou): Pre-create paragraph or use prompt to replace + # _CONTENT + "rephrase_paragraph": instructions.RephraseParagraph, + _FORMAT + "constrained_response": set(INSTRUCTION_DICT.keys()), + _FORMAT + "number_highlighted_sections": {_FORMAT + "number_highlighted_sections"}, + _FORMAT + "multiple_sections": { + _FORMAT + "multiple_sections", + _LANGUAGE + "response_language", + _FORMAT + "number_highlighted_sections", + }, + # TODO(tianjianlu): Re-enable rephrasing with preprocessing the message. + # _FORMAT + "rephrase": instructions.RephraseChecker, + _FORMAT + "json_format": set(INSTRUCTION_DICT.keys()).difference( + {_KEYWORD + "forbidden_words", _KEYWORD + "existence"} + ), + _FORMAT + "title": {_FORMAT + "title"}, + # TODO(tianjianlu): Re-enable with specific prompts. + # _MULTITURN + "constrained_start": instructions.ConstrainedStartChecker, + _COMBINATION + "two_responses": set(INSTRUCTION_DICT.keys()).difference( + { + _KEYWORD + "forbidden_words", + _KEYWORD + "existence", + _LANGUAGE + "response_language", + _FORMAT + "title", + _PUNCTUATION + "no_comma", + } + ), + _COMBINATION + "repeat_prompt": set(INSTRUCTION_DICT.keys()).difference( + {_KEYWORD + "existence", _FORMAT + "title", _PUNCTUATION + "no_comma"} + ), + _STARTEND + "end_checker": {_STARTEND + "end_checker"}, + _CHANGE_CASES + "capital_word_frequency": { + _CHANGE_CASES + "capital_word_frequency", + _CHANGE_CASES + "english_lowercase", + _CHANGE_CASES + "english_capital", + }, + _CHANGE_CASES + "english_capital": {_CHANGE_CASES + "english_capital"}, + _CHANGE_CASES + "english_lowercase": { + _CHANGE_CASES + "english_lowercase", + _CHANGE_CASES + "english_capital", + }, + _PUNCTUATION + "no_comma": {_PUNCTUATION + "no_comma"}, + _STARTEND + "quotation": {_STARTEND + "quotation", _FORMAT + "title"}, +} + + +def conflict_make(conflicts): + """Makes sure if A conflicts with B, B will conflict with A. + + Args: + conflicts: Dictionary of potential conflicts where key is instruction id + and value is set of instruction ids that it conflicts with. + + Returns: + Revised version of the dictionary. All instructions conflict with + themselves. If A conflicts with B, B will conflict with A. + """ + for key in conflicts: + for k in conflicts[key]: + conflicts[k].add(key) + conflicts[key].add(key) + return conflicts diff --git a/lm_eval/tasks/leaderboard/ifeval/instructions_util.py b/lm_eval/tasks/leaderboard/ifeval/instructions_util.py new file mode 100644 index 00000000..ccb531f9 --- /dev/null +++ b/lm_eval/tasks/leaderboard/ifeval/instructions_util.py @@ -0,0 +1,1682 @@ +# Copyright 2023 The Google Research Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Utility library of instructions.""" + +import functools +import random +import re + +import immutabledict +import nltk + + +def download_nltk_resources(): + """Download 'punkt' if not already installed""" + try: + nltk.data.find("tokenizers/punkt") + except LookupError: + nltk.download("punkt") + + +download_nltk_resources() + +WORD_LIST = [ + "western", + "sentence", + "signal", + "dump", + "spot", + "opposite", + "bottom", + "potato", + "administration", + "working", + "welcome", + "morning", + "good", + "agency", + "primary", + "wish", + "responsibility", + "press", + "problem", + "president", + "steal", + "brush", + "read", + "type", + "beat", + "trainer", + "growth", + "lock", + "bone", + "case", + "equal", + "comfortable", + "region", + "replacement", + "performance", + "mate", + "walk", + "medicine", + "film", + "thing", + "rock", + "tap", + "total", + "competition", + "ease", + "south", + "establishment", + "gather", + "parking", + "world", + "plenty", + "breath", + "claim", + "alcohol", + "trade", + "dear", + "highlight", + "street", + "matter", + "decision", + "mess", + "agreement", + "studio", + "coach", + "assist", + "brain", + "wing", + "style", + "private", + "top", + "brown", + "leg", + "buy", + "procedure", + "method", + "speed", + "high", + "company", + "valuable", + "pie", + "analyst", + "session", + "pattern", + "district", + "pleasure", + "dinner", + "swimming", + "joke", + "order", + "plate", + "department", + "motor", + "cell", + "spend", + "cabinet", + "difference", + "power", + "examination", + "engine", + "horse", + "dimension", + "pay", + "toe", + "curve", + "literature", + "bother", + "fire", + "possibility", + "debate", + "activity", + "passage", + "hello", + "cycle", + "background", + "quiet", + "author", + "effect", + "actor", + "page", + "bicycle", + "error", + "throat", + "attack", + "character", + "phone", + "tea", + "increase", + "outcome", + "file", + "specific", + "inspector", + "internal", + "potential", + "staff", + "building", + "employer", + "shoe", + "hand", + "direction", + "garden", + "purchase", + "interview", + "study", + "recognition", + "member", + "spiritual", + "oven", + "sandwich", + "weird", + "passenger", + "particular", + "response", + "reaction", + "size", + "variation", + "a", + "cancel", + "candy", + "exit", + "guest", + "condition", + "fly", + "price", + "weakness", + "convert", + "hotel", + "great", + "mouth", + "mind", + "song", + "sugar", + "suspect", + "telephone", + "ear", + "roof", + "paint", + "refrigerator", + "organization", + "jury", + "reward", + "engineering", + "day", + "possession", + "crew", + "bar", + "road", + "description", + "celebration", + "score", + "mark", + "letter", + "shower", + "suggestion", + "sir", + "luck", + "national", + "progress", + "hall", + "stroke", + "theory", + "offer", + "story", + "tax", + "definition", + "history", + "ride", + "medium", + "opening", + "glass", + "elevator", + "stomach", + "question", + "ability", + "leading", + "village", + "computer", + "city", + "grand", + "confidence", + "candle", + "priest", + "recommendation", + "point", + "necessary", + "body", + "desk", + "secret", + "horror", + "noise", + "culture", + "warning", + "water", + "round", + "diet", + "flower", + "bus", + "tough", + "permission", + "week", + "prompt", + "connection", + "abuse", + "height", + "save", + "corner", + "border", + "stress", + "drive", + "stop", + "rip", + "meal", + "listen", + "confusion", + "girlfriend", + "living", + "relation", + "significance", + "plan", + "creative", + "atmosphere", + "blame", + "invite", + "housing", + "paper", + "drink", + "roll", + "silver", + "drunk", + "age", + "damage", + "smoke", + "environment", + "pack", + "savings", + "influence", + "tourist", + "rain", + "post", + "sign", + "grandmother", + "run", + "profit", + "push", + "clerk", + "final", + "wine", + "swim", + "pause", + "stuff", + "singer", + "funeral", + "average", + "source", + "scene", + "tradition", + "personal", + "snow", + "nobody", + "distance", + "sort", + "sensitive", + "animal", + "major", + "negotiation", + "click", + "mood", + "period", + "arrival", + "expression", + "holiday", + "repeat", + "dust", + "closet", + "gold", + "bad", + "sail", + "combination", + "clothes", + "emphasis", + "duty", + "black", + "step", + "school", + "jump", + "document", + "professional", + "lip", + "chemical", + "front", + "wake", + "while", + "inside", + "watch", + "row", + "subject", + "penalty", + "balance", + "possible", + "adult", + "aside", + "sample", + "appeal", + "wedding", + "depth", + "king", + "award", + "wife", + "blow", + "site", + "camp", + "music", + "safe", + "gift", + "fault", + "guess", + "act", + "shame", + "drama", + "capital", + "exam", + "stupid", + "record", + "sound", + "swing", + "novel", + "minimum", + "ratio", + "machine", + "shape", + "lead", + "operation", + "salary", + "cloud", + "affair", + "hit", + "chapter", + "stage", + "quantity", + "access", + "army", + "chain", + "traffic", + "kick", + "analysis", + "airport", + "time", + "vacation", + "philosophy", + "ball", + "chest", + "thanks", + "place", + "mountain", + "advertising", + "red", + "past", + "rent", + "return", + "tour", + "house", + "construction", + "net", + "native", + "war", + "figure", + "fee", + "spray", + "user", + "dirt", + "shot", + "task", + "stick", + "friend", + "software", + "promotion", + "interaction", + "surround", + "block", + "purpose", + "practice", + "conflict", + "routine", + "requirement", + "bonus", + "hole", + "state", + "junior", + "sweet", + "catch", + "tear", + "fold", + "wall", + "editor", + "life", + "position", + "pound", + "respect", + "bathroom", + "coat", + "script", + "job", + "teach", + "birth", + "view", + "resolve", + "theme", + "employee", + "doubt", + "market", + "education", + "serve", + "recover", + "tone", + "harm", + "miss", + "union", + "understanding", + "cow", + "river", + "association", + "concept", + "training", + "recipe", + "relationship", + "reserve", + "depression", + "proof", + "hair", + "revenue", + "independent", + "lift", + "assignment", + "temporary", + "amount", + "loss", + "edge", + "track", + "check", + "rope", + "estimate", + "pollution", + "stable", + "message", + "delivery", + "perspective", + "mirror", + "assistant", + "representative", + "witness", + "nature", + "judge", + "fruit", + "tip", + "devil", + "town", + "emergency", + "upper", + "drop", + "stay", + "human", + "neck", + "speaker", + "network", + "sing", + "resist", + "league", + "trip", + "signature", + "lawyer", + "importance", + "gas", + "choice", + "engineer", + "success", + "part", + "external", + "worker", + "simple", + "quarter", + "student", + "heart", + "pass", + "spite", + "shift", + "rough", + "lady", + "grass", + "community", + "garage", + "youth", + "standard", + "skirt", + "promise", + "blind", + "television", + "disease", + "commission", + "positive", + "energy", + "calm", + "presence", + "tune", + "basis", + "preference", + "head", + "common", + "cut", + "somewhere", + "presentation", + "current", + "thought", + "revolution", + "effort", + "master", + "implement", + "republic", + "floor", + "principle", + "stranger", + "shoulder", + "grade", + "button", + "tennis", + "police", + "collection", + "account", + "register", + "glove", + "divide", + "professor", + "chair", + "priority", + "combine", + "peace", + "extension", + "maybe", + "evening", + "frame", + "sister", + "wave", + "code", + "application", + "mouse", + "match", + "counter", + "bottle", + "half", + "cheek", + "resolution", + "back", + "knowledge", + "make", + "discussion", + "screw", + "length", + "accident", + "battle", + "dress", + "knee", + "log", + "package", + "it", + "turn", + "hearing", + "newspaper", + "layer", + "wealth", + "profile", + "imagination", + "answer", + "weekend", + "teacher", + "appearance", + "meet", + "bike", + "rise", + "belt", + "crash", + "bowl", + "equivalent", + "support", + "image", + "poem", + "risk", + "excitement", + "remote", + "secretary", + "public", + "produce", + "plane", + "display", + "money", + "sand", + "situation", + "punch", + "customer", + "title", + "shake", + "mortgage", + "option", + "number", + "pop", + "window", + "extent", + "nothing", + "experience", + "opinion", + "departure", + "dance", + "indication", + "boy", + "material", + "band", + "leader", + "sun", + "beautiful", + "muscle", + "farmer", + "variety", + "fat", + "handle", + "director", + "opportunity", + "calendar", + "outside", + "pace", + "bath", + "fish", + "consequence", + "put", + "owner", + "go", + "doctor", + "information", + "share", + "hurt", + "protection", + "career", + "finance", + "force", + "golf", + "garbage", + "aspect", + "kid", + "food", + "boot", + "milk", + "respond", + "objective", + "reality", + "raw", + "ring", + "mall", + "one", + "impact", + "area", + "news", + "international", + "series", + "impress", + "mother", + "shelter", + "strike", + "loan", + "month", + "seat", + "anything", + "entertainment", + "familiar", + "clue", + "year", + "glad", + "supermarket", + "natural", + "god", + "cost", + "conversation", + "tie", + "ruin", + "comfort", + "earth", + "storm", + "percentage", + "assistance", + "budget", + "strength", + "beginning", + "sleep", + "other", + "young", + "unit", + "fill", + "store", + "desire", + "hide", + "value", + "cup", + "maintenance", + "nurse", + "function", + "tower", + "role", + "class", + "camera", + "database", + "panic", + "nation", + "basket", + "ice", + "art", + "spirit", + "chart", + "exchange", + "feedback", + "statement", + "reputation", + "search", + "hunt", + "exercise", + "nasty", + "notice", + "male", + "yard", + "annual", + "collar", + "date", + "platform", + "plant", + "fortune", + "passion", + "friendship", + "spread", + "cancer", + "ticket", + "attitude", + "island", + "active", + "object", + "service", + "buyer", + "bite", + "card", + "face", + "steak", + "proposal", + "patient", + "heat", + "rule", + "resident", + "broad", + "politics", + "west", + "knife", + "expert", + "girl", + "design", + "salt", + "baseball", + "grab", + "inspection", + "cousin", + "couple", + "magazine", + "cook", + "dependent", + "security", + "chicken", + "version", + "currency", + "ladder", + "scheme", + "kitchen", + "employment", + "local", + "attention", + "manager", + "fact", + "cover", + "sad", + "guard", + "relative", + "county", + "rate", + "lunch", + "program", + "initiative", + "gear", + "bridge", + "breast", + "talk", + "dish", + "guarantee", + "beer", + "vehicle", + "reception", + "woman", + "substance", + "copy", + "lecture", + "advantage", + "park", + "cold", + "death", + "mix", + "hold", + "scale", + "tomorrow", + "blood", + "request", + "green", + "cookie", + "church", + "strip", + "forever", + "beyond", + "debt", + "tackle", + "wash", + "following", + "feel", + "maximum", + "sector", + "sea", + "property", + "economics", + "menu", + "bench", + "try", + "language", + "start", + "call", + "solid", + "address", + "income", + "foot", + "senior", + "honey", + "few", + "mixture", + "cash", + "grocery", + "link", + "map", + "form", + "factor", + "pot", + "model", + "writer", + "farm", + "winter", + "skill", + "anywhere", + "birthday", + "policy", + "release", + "husband", + "lab", + "hurry", + "mail", + "equipment", + "sink", + "pair", + "driver", + "consideration", + "leather", + "skin", + "blue", + "boat", + "sale", + "brick", + "two", + "feed", + "square", + "dot", + "rush", + "dream", + "location", + "afternoon", + "manufacturer", + "control", + "occasion", + "trouble", + "introduction", + "advice", + "bet", + "eat", + "kill", + "category", + "manner", + "office", + "estate", + "pride", + "awareness", + "slip", + "crack", + "client", + "nail", + "shoot", + "membership", + "soft", + "anybody", + "web", + "official", + "individual", + "pizza", + "interest", + "bag", + "spell", + "profession", + "queen", + "deal", + "resource", + "ship", + "guy", + "chocolate", + "joint", + "formal", + "upstairs", + "car", + "resort", + "abroad", + "dealer", + "associate", + "finger", + "surgery", + "comment", + "team", + "detail", + "crazy", + "path", + "tale", + "initial", + "arm", + "radio", + "demand", + "single", + "draw", + "yellow", + "contest", + "piece", + "quote", + "pull", + "commercial", + "shirt", + "contribution", + "cream", + "channel", + "suit", + "discipline", + "instruction", + "concert", + "speech", + "low", + "effective", + "hang", + "scratch", + "industry", + "breakfast", + "lay", + "join", + "metal", + "bedroom", + "minute", + "product", + "rest", + "temperature", + "many", + "give", + "argument", + "print", + "purple", + "laugh", + "health", + "credit", + "investment", + "sell", + "setting", + "lesson", + "egg", + "middle", + "marriage", + "level", + "evidence", + "phrase", + "love", + "self", + "benefit", + "guidance", + "affect", + "you", + "dad", + "anxiety", + "special", + "boyfriend", + "test", + "blank", + "payment", + "soup", + "obligation", + "reply", + "smile", + "deep", + "complaint", + "addition", + "review", + "box", + "towel", + "minor", + "fun", + "soil", + "issue", + "cigarette", + "internet", + "gain", + "tell", + "entry", + "spare", + "incident", + "family", + "refuse", + "branch", + "can", + "pen", + "grandfather", + "constant", + "tank", + "uncle", + "climate", + "ground", + "volume", + "communication", + "kind", + "poet", + "child", + "screen", + "mine", + "quit", + "gene", + "lack", + "charity", + "memory", + "tooth", + "fear", + "mention", + "marketing", + "reveal", + "reason", + "court", + "season", + "freedom", + "land", + "sport", + "audience", + "classroom", + "law", + "hook", + "win", + "carry", + "eye", + "smell", + "distribution", + "research", + "country", + "dare", + "hope", + "whereas", + "stretch", + "library", + "if", + "delay", + "college", + "plastic", + "book", + "present", + "use", + "worry", + "champion", + "goal", + "economy", + "march", + "election", + "reflection", + "midnight", + "slide", + "inflation", + "action", + "challenge", + "guitar", + "coast", + "apple", + "campaign", + "field", + "jacket", + "sense", + "way", + "visual", + "remove", + "weather", + "trash", + "cable", + "regret", + "buddy", + "beach", + "historian", + "courage", + "sympathy", + "truck", + "tension", + "permit", + "nose", + "bed", + "son", + "person", + "base", + "meat", + "usual", + "air", + "meeting", + "worth", + "game", + "independence", + "physical", + "brief", + "play", + "raise", + "board", + "she", + "key", + "writing", + "pick", + "command", + "party", + "yesterday", + "spring", + "candidate", + "physics", + "university", + "concern", + "development", + "change", + "string", + "target", + "instance", + "room", + "bitter", + "bird", + "football", + "normal", + "split", + "impression", + "wood", + "long", + "meaning", + "stock", + "cap", + "leadership", + "media", + "ambition", + "fishing", + "essay", + "salad", + "repair", + "today", + "designer", + "night", + "bank", + "drawing", + "inevitable", + "phase", + "vast", + "chip", + "anger", + "switch", + "cry", + "twist", + "personality", + "attempt", + "storage", + "being", + "preparation", + "bat", + "selection", + "white", + "technology", + "contract", + "side", + "section", + "station", + "till", + "structure", + "tongue", + "taste", + "truth", + "difficulty", + "group", + "limit", + "main", + "move", + "feeling", + "light", + "example", + "mission", + "might", + "wait", + "wheel", + "shop", + "host", + "classic", + "alternative", + "cause", + "agent", + "consist", + "table", + "airline", + "text", + "pool", + "craft", + "range", + "fuel", + "tool", + "partner", + "load", + "entrance", + "deposit", + "hate", + "article", + "video", + "summer", + "feature", + "extreme", + "mobile", + "hospital", + "flight", + "fall", + "pension", + "piano", + "fail", + "result", + "rub", + "gap", + "system", + "report", + "suck", + "ordinary", + "wind", + "nerve", + "ask", + "shine", + "note", + "line", + "mom", + "perception", + "brother", + "reference", + "bend", + "charge", + "treat", + "trick", + "term", + "homework", + "bake", + "bid", + "status", + "project", + "strategy", + "orange", + "let", + "enthusiasm", + "parent", + "concentrate", + "device", + "travel", + "poetry", + "business", + "society", + "kiss", + "end", + "vegetable", + "employ", + "schedule", + "hour", + "brave", + "focus", + "process", + "movie", + "illegal", + "general", + "coffee", + "ad", + "highway", + "chemistry", + "psychology", + "hire", + "bell", + "conference", + "relief", + "show", + "neat", + "funny", + "weight", + "quality", + "club", + "daughter", + "zone", + "touch", + "tonight", + "shock", + "burn", + "excuse", + "name", + "survey", + "landscape", + "advance", + "satisfaction", + "bread", + "disaster", + "item", + "hat", + "prior", + "shopping", + "visit", + "east", + "photo", + "home", + "idea", + "father", + "comparison", + "cat", + "pipe", + "winner", + "count", + "lake", + "fight", + "prize", + "foundation", + "dog", + "keep", + "ideal", + "fan", + "struggle", + "peak", + "safety", + "solution", + "hell", + "conclusion", + "population", + "strain", + "alarm", + "measurement", + "second", + "train", + "race", + "due", + "insurance", + "boss", + "tree", + "monitor", + "sick", + "course", + "drag", + "appointment", + "slice", + "still", + "care", + "patience", + "rich", + "escape", + "emotion", + "royal", + "female", + "childhood", + "government", + "picture", + "will", + "sock", + "big", + "gate", + "oil", + "cross", + "pin", + "improvement", + "championship", + "silly", + "help", + "sky", + "pitch", + "man", + "diamond", + "most", + "transition", + "work", + "science", + "committee", + "moment", + "fix", + "teaching", + "dig", + "specialist", + "complex", + "guide", + "people", + "dead", + "voice", + "original", + "break", + "topic", + "data", + "degree", + "reading", + "recording", + "bunch", + "reach", + "judgment", + "lie", + "regular", + "set", + "painting", + "mode", + "list", + "player", + "bear", + "north", + "wonder", + "carpet", + "heavy", + "officer", + "negative", + "clock", + "unique", + "baby", + "pain", + "assumption", + "disk", + "iron", + "bill", + "drawer", + "look", + "double", + "mistake", + "finish", + "future", + "brilliant", + "contact", + "math", + "rice", + "leave", + "restaurant", + "discount", + "sex", + "virus", + "bit", + "trust", + "event", + "wear", + "juice", + "failure", + "bug", + "context", + "mud", + "whole", + "wrap", + "intention", + "draft", + "pressure", + "cake", + "dark", + "explanation", + "space", + "angle", + "word", + "efficiency", + "management", + "habit", + "star", + "chance", + "finding", + "transportation", + "stand", + "criticism", + "flow", + "door", + "injury", + "insect", + "surprise", + "apartment", +] # pylint: disable=line-too-long + +# ISO 639-1 codes to language names. +LANGUAGE_CODES = immutabledict.immutabledict( + { + "en": "English", + "es": "Spanish", + "pt": "Portuguese", + "ar": "Arabic", + "hi": "Hindi", + "fr": "French", + "ru": "Russian", + "de": "German", + "ja": "Japanese", + "it": "Italian", + "bn": "Bengali", + "uk": "Ukrainian", + "th": "Thai", + "ur": "Urdu", + "ta": "Tamil", + "te": "Telugu", + "bg": "Bulgarian", + "ko": "Korean", + "pl": "Polish", + "he": "Hebrew", + "fa": "Persian", + "vi": "Vietnamese", + "ne": "Nepali", + "sw": "Swahili", + "kn": "Kannada", + "mr": "Marathi", + "gu": "Gujarati", + "pa": "Punjabi", + "ml": "Malayalam", + "fi": "Finnish", + } +) + +_ALPHABETS = "([A-Za-z])" +_PREFIXES = "(Mr|St|Mrs|Ms|Dr)[.]" +_SUFFIXES = "(Inc|Ltd|Jr|Sr|Co)" +_STARTERS = r"(Mr|Mrs|Ms|Dr|Prof|Capt|Cpt|Lt|He\s|She\s|It\s|They\s|Their\s|Our\s|We\s|But\s|However\s|That\s|This\s|Wherever)" +_ACRONYMS = "([A-Z][.][A-Z][.](?:[A-Z][.])?)" +_WEBSITES = "[.](com|net|org|io|gov|edu|me)" +_DIGITS = "([0-9])" +_MULTIPLE_DOTS = r"\.{2,}" + + +def split_into_sentences(text): + """Split the text into sentences. + + Args: + text: A string that consists of more than or equal to one sentences. + + Returns: + A list of strings where each string is a sentence. + """ + text = " " + text + " " + text = text.replace("\n", " ") + text = re.sub(_PREFIXES, "\\1", text) + text = re.sub(_WEBSITES, "\\1", text) + text = re.sub(_DIGITS + "[.]" + _DIGITS, "\\1\\2", text) + text = re.sub( + _MULTIPLE_DOTS, + lambda match: "" * len(match.group(0)) + "", + text, + ) + if "Ph.D" in text: + text = text.replace("Ph.D.", "PhD") + text = re.sub(r"\s" + _ALPHABETS + "[.] ", " \\1 ", text) + text = re.sub(_ACRONYMS + " " + _STARTERS, "\\1 \\2", text) + text = re.sub( + _ALPHABETS + "[.]" + _ALPHABETS + "[.]" + _ALPHABETS + "[.]", + "\\1\\2\\3", + text, + ) + text = re.sub(_ALPHABETS + "[.]" + _ALPHABETS + "[.]", "\\1\\2", text) + text = re.sub(" " + _SUFFIXES + "[.] " + _STARTERS, " \\1 \\2", text) + text = re.sub(" " + _SUFFIXES + "[.]", " \\1", text) + text = re.sub(" " + _ALPHABETS + "[.]", " \\1", text) + if "”" in text: + text = text.replace(".”", "”.") + if '"' in text: + text = text.replace('."', '".') + if "!" in text: + text = text.replace('!"', '"!') + if "?" in text: + text = text.replace('?"', '"?') + text = text.replace(".", ".") + text = text.replace("?", "?") + text = text.replace("!", "!") + text = text.replace("", ".") + sentences = text.split("") + sentences = [s.strip() for s in sentences] + if sentences and not sentences[-1]: + sentences = sentences[:-1] + return sentences + + +def count_words(text): + """Counts the number of words.""" + tokenizer = nltk.tokenize.RegexpTokenizer(r"\w+") + tokens = tokenizer.tokenize(text) + num_words = len(tokens) + return num_words + + +@functools.lru_cache(maxsize=None) +def _get_sentence_tokenizer(): + return nltk.data.load("nltk:tokenizers/punkt/english.pickle") + + +def count_sentences(text): + """Count the number of sentences.""" + tokenizer = _get_sentence_tokenizer() + tokenized_sentences = tokenizer.tokenize(text) + return len(tokenized_sentences) + + +def generate_keywords(num_keywords): + """Randomly generates a few keywords.""" + return random.sample(WORD_LIST, k=num_keywords) diff --git a/lm_eval/tasks/leaderboard/ifeval/utils.py b/lm_eval/tasks/leaderboard/ifeval/utils.py new file mode 100644 index 00000000..985e8d5a --- /dev/null +++ b/lm_eval/tasks/leaderboard/ifeval/utils.py @@ -0,0 +1,134 @@ +import dataclasses +from typing import Dict, Optional, Union + +from lm_eval.tasks.ifeval import instructions_registry + + +@dataclasses.dataclass +class InputExample: + key: int + instruction_id_list: list[str] + prompt: str + kwargs: list[Dict[str, Optional[Union[str, int]]]] + + +@dataclasses.dataclass +class OutputExample: + instruction_id_list: list[str] + prompt: str + response: str + follow_all_instructions: bool + follow_instruction_list: list[bool] + + +def test_instruction_following_strict( + inp, + response, +): + """Tests response to see if instructions are followed.""" + instruction_list = inp.instruction_id_list + is_following_list = [] + + for index, instruction_id in enumerate(instruction_list): + instruction_cls = instructions_registry.INSTRUCTION_DICT[instruction_id] + instruction = instruction_cls(instruction_id) + + # Remove None values from kwargs to avoid unexpected keyword argument errors in build_description method. + kwargs = {k: v for k, v in inp.kwargs[index].items() if v} + instruction.build_description(**kwargs) + args = instruction.get_instruction_args() + if args and "prompt" in args: + instruction.build_description(prompt=inp.prompt) + + if response.strip() and instruction.check_following(response): + is_following_list.append(True) + else: + is_following_list.append(False) + + return OutputExample( + instruction_id_list=inp.instruction_id_list, + prompt=inp.prompt, + response=response, + follow_all_instructions=all(is_following_list), + follow_instruction_list=is_following_list, + ) + + +def test_instruction_following_loose( + inp, + response, +): + """Tests response for an upper bound for following instructions.""" + r = response.split("\n") + response_remove_first = "\n".join(r[1:]).strip() + response_remove_last = "\n".join(r[:-1]).strip() + response_remove_both = "\n".join(r[1:-1]).strip() + revised_response = response.replace("*", "") + revised_response_remove_first = response_remove_first.replace("*", "") + revised_response_remove_last = response_remove_last.replace("*", "") + revised_response_remove_both = response_remove_both.replace("*", "") + all_responses = [ + response, + revised_response, + response_remove_first, + response_remove_last, + response_remove_both, + revised_response_remove_first, + revised_response_remove_last, + revised_response_remove_both, + ] + instruction_list = inp.instruction_id_list + is_following_list = [] + + for index, instruction_id in enumerate(instruction_list): + instruction_cls = instructions_registry.INSTRUCTION_DICT[instruction_id] + instruction = instruction_cls(instruction_id) + + # Remove None values from kwargs to avoid unexpected keyword argument errors in build_description method. + kwargs = {k: v for k, v in inp.kwargs[index].items() if v} + instruction.build_description(**kwargs) + args = instruction.get_instruction_args() + if args and "prompt" in args: + instruction.build_description(prompt=inp.prompt) + + is_following = False + for r in all_responses: + if r.strip() and instruction.check_following(r): + is_following = True + break + + is_following_list.append(is_following) + + return OutputExample( + instruction_id_list=inp.instruction_id_list, + prompt=inp.prompt, + response=response, + follow_all_instructions=all(is_following_list), + follow_instruction_list=is_following_list, + ) + + +def process_results(doc, results): + inp = InputExample( + key=doc["key"], + instruction_id_list=doc["instruction_id_list"], + prompt=doc["prompt"], + kwargs=doc["kwargs"], + ) + response = results[0] + + out_strict = test_instruction_following_strict(inp, response) + out_loose = test_instruction_following_loose(inp, response) + + return { + "prompt_level_strict_acc": out_strict.follow_all_instructions, + "inst_level_strict_acc": out_strict.follow_instruction_list, + "prompt_level_loose_acc": out_loose.follow_all_instructions, + "inst_level_loose_acc": out_loose.follow_instruction_list, + } + + +def agg_inst_level_acc(items): + flat_items = [item for sublist in items for item in sublist] + inst_level_acc = sum(flat_items) / len(flat_items) + return inst_level_acc diff --git a/lm_eval/tasks/leaderboard/leaderboard.yaml b/lm_eval/tasks/leaderboard/leaderboard.yaml new file mode 100644 index 00000000..d9c5aaac --- /dev/null +++ b/lm_eval/tasks/leaderboard/leaderboard.yaml @@ -0,0 +1,8 @@ +group: leaderboard +task: + - leaderboard_mmlu_pro + - leaderboard_bbh + - leaderboard_gpqa + - leaderboard_math_hard + - leaderboard_ifeval + - leaderboard_musr diff --git a/lm_eval/tasks/leaderboard/math/_template_yaml b/lm_eval/tasks/leaderboard/math/_template_yaml new file mode 100644 index 00000000..a121074b --- /dev/null +++ b/lm_eval/tasks/leaderboard/math/_template_yaml @@ -0,0 +1,28 @@ +group: + - leaderboard_math_hard +dataset_path: lighteval/MATH-Hard +process_docs: !function utils.process_docs +output_type: generate_until +training_split: train +test_split: test +doc_to_text: !function utils.doc_to_text +process_results: !function utils.process_results +doc_to_target: "{{answer if few_shot is undefined else solution}}" +generation_kwargs: + until: + - "Problem:" + do_sample: false + temperature: 0 + max_gen_toks: 1024 +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true +num_fewshot: 4 +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true +fewshot_config: + sampler: first_n + samples: !function utils.list_fewshot_samples diff --git a/lm_eval/tasks/leaderboard/math/math_algebra.yaml b/lm_eval/tasks/leaderboard/math/math_algebra.yaml new file mode 100644 index 00000000..9e1d4753 --- /dev/null +++ b/lm_eval/tasks/leaderboard/math/math_algebra.yaml @@ -0,0 +1,3 @@ +include: _template_yaml +dataset_name: algebra +task: leaderboard_math_algebra_hard diff --git a/lm_eval/tasks/leaderboard/math/math_counting_and_prob.yaml b/lm_eval/tasks/leaderboard/math/math_counting_and_prob.yaml new file mode 100644 index 00000000..41767099 --- /dev/null +++ b/lm_eval/tasks/leaderboard/math/math_counting_and_prob.yaml @@ -0,0 +1,3 @@ +include: _template_yaml +dataset_name: counting_and_probability +task: leaderboard_math_counting_and_prob_hard diff --git a/lm_eval/tasks/leaderboard/math/math_geometry.yaml b/lm_eval/tasks/leaderboard/math/math_geometry.yaml new file mode 100644 index 00000000..189633c3 --- /dev/null +++ b/lm_eval/tasks/leaderboard/math/math_geometry.yaml @@ -0,0 +1,3 @@ +include: _template_yaml +dataset_name: geometry +task: leaderboard_math_geometry_hard diff --git a/lm_eval/tasks/leaderboard/math/math_intermediate_algebra.yaml b/lm_eval/tasks/leaderboard/math/math_intermediate_algebra.yaml new file mode 100644 index 00000000..9959bd18 --- /dev/null +++ b/lm_eval/tasks/leaderboard/math/math_intermediate_algebra.yaml @@ -0,0 +1,3 @@ +include: _template_yaml +dataset_name: intermediate_algebra +task: leaderboard_math_intermediate_algebra_hard diff --git a/lm_eval/tasks/leaderboard/math/math_num_theory.yaml b/lm_eval/tasks/leaderboard/math/math_num_theory.yaml new file mode 100644 index 00000000..a055d94d --- /dev/null +++ b/lm_eval/tasks/leaderboard/math/math_num_theory.yaml @@ -0,0 +1,3 @@ +include: _template_yaml +dataset_name: number_theory +task: leaderboard_math_num_theory_hard diff --git a/lm_eval/tasks/leaderboard/math/math_prealgebra.yaml b/lm_eval/tasks/leaderboard/math/math_prealgebra.yaml new file mode 100644 index 00000000..474d7258 --- /dev/null +++ b/lm_eval/tasks/leaderboard/math/math_prealgebra.yaml @@ -0,0 +1,3 @@ +include: _template_yaml +dataset_name: prealgebra +task: leaderboard_math_prealgebra_hard diff --git a/lm_eval/tasks/leaderboard/math/math_precalculus.yaml b/lm_eval/tasks/leaderboard/math/math_precalculus.yaml new file mode 100644 index 00000000..4d63541e --- /dev/null +++ b/lm_eval/tasks/leaderboard/math/math_precalculus.yaml @@ -0,0 +1,3 @@ +include: _template_yaml +dataset_name: precalculus +task: leaderboard_math_precalculus_hard diff --git a/lm_eval/tasks/leaderboard/math/utils.py b/lm_eval/tasks/leaderboard/math/utils.py new file mode 100644 index 00000000..e3ebcf99 --- /dev/null +++ b/lm_eval/tasks/leaderboard/math/utils.py @@ -0,0 +1,294 @@ +import re +import signal +from typing import Dict, List, Optional + +import datasets + +from lm_eval.utils import eval_logger + + +try: + import sympy + from sympy.parsing.latex import parse_latex +except ModuleNotFoundError: + raise ModuleNotFoundError( + "`sympy` is required for generating translation task prompt templates. \ +please install sympy via pip install lm-eval[math] or pip install -e .[math]", + ) + + +# taken from +# https://github.com/wellecks/lm-evaluation-harness/blob/master/lm_eval/tasks/minerva_math.py +def doc_to_text(doc: dict) -> str: + return "Problem:" + "\n" + doc["problem"] + "\n\n" + "Solution:" + + +def process_docs(dataset: datasets.Dataset) -> datasets.Dataset: + def _process_doc(doc: dict) -> dict: + out_doc = { + "problem": doc["problem"], + "solution": doc["solution"], + "answer": normalize_final_answer( + remove_boxed(last_boxed_only_string(doc["solution"])) + ), + } + if getattr(doc, "few_shot", None) is not None: + out_doc["few_shot"] = True + return out_doc + + return dataset.map(_process_doc) + + +def list_fewshot_samples() -> list[dict]: + return [ + { + "problem": "Find the domain of the expression $\\frac{\\sqrt{x-2}}{\\sqrt{5-x}}$.}", + "solution": "The expressions inside each square root must be non-negative. Therefore, $x-2 \\ge 0$, so $x\\ge2$, and $5 - x \\ge 0$, so $x \\le 5$. Also, the denominator cannot be equal to zero, so $5-x>0$, which gives $x<5$. Therefore, the domain of the expression is $\\boxed{[2,5)}$.\nFinal Answer: The final answer is $[2,5)$. I hope it is correct.", + "few_shot": "1", + }, + { + "problem": "If $\\det \\mathbf{A} = 2$ and $\\det \\mathbf{B} = 12,$ then find $\\det (\\mathbf{A} \\mathbf{B}).$", + "solution": "We have that $\\det (\\mathbf{A} \\mathbf{B}) = (\\det \\mathbf{A})(\\det \\mathbf{B}) = (2)(12) = \\boxed{24}.$\nFinal Answer: The final answer is $24$. I hope it is correct.", + "few_shot": "1", + }, + { + "problem": "Terrell usually lifts two 20-pound weights 12 times. If he uses two 15-pound weights instead, how many times must Terrell lift them in order to lift the same total weight?", + "solution": "If Terrell lifts two 20-pound weights 12 times, he lifts a total of $2\\cdot 12\\cdot20=480$ pounds of weight. If he lifts two 15-pound weights instead for $n$ times, he will lift a total of $2\\cdot15\\cdot n=30n$ pounds of weight. Equating this to 480 pounds, we can solve for $n$:\n\\begin{align*}\n30n&=480\\\n\\Rightarrow\\qquad n&=480/30=\\boxed{16}\n\\end{align*}\nFinal Answer: The final answer is $16$. I hope it is correct.", + "few_shot": "1", + }, + { + "problem": "If the system of equations\n\n\\begin{align*}\n6x-4y&=a,\\\n6y-9x &=b.\n\\end{align*}has a solution $(x, y)$ where $x$ and $y$ are both nonzero,\nfind $\\frac{a}{b},$ assuming $b$ is nonzero.", + "solution": "If we multiply the first equation by $-\\frac{3}{2}$, we obtain\n\n$$6y-9x=-\\frac{3}{2}a.$$Since we also know that $6y-9x=b$, we have\n\n$$-\\frac{3}{2}a=b\\Rightarrow\\frac{a}{b}=\\boxed{-\\frac{2}{3}}.$$\nFinal Answer: The final answer is $-\\frac{2}{3}$. I hope it is correct.", + "few_shot": "1", + }, + ] + + +def process_results(doc: dict, results: List[str]) -> Dict[str, int]: + candidates = results[0] + + unnormalized_answer = get_unnormalized_answer(candidates) + answer = normalize_final_answer(unnormalized_answer) + + if is_equiv(answer, doc["answer"]): + retval = 1 + else: + retval = 0 + + results = { + "exact_match": retval, + } + return results + + +def last_boxed_only_string(string: str) -> Optional[str]: + idx = string.rfind("\\boxed") + if "\\boxed " in string: + return "\\boxed " + string.split("\\boxed ")[-1].split("$")[0] + if idx < 0: + idx = string.rfind("\\fbox") + if idx < 0: + return None + + i = idx + right_brace_idx = None + num_left_braces_open = 0 + while i < len(string): + if string[i] == "{": + num_left_braces_open += 1 + if string[i] == "}": + num_left_braces_open -= 1 + if num_left_braces_open == 0: + right_brace_idx = i + break + i += 1 + + if right_brace_idx is None: + retval = None + else: + retval = string[idx : right_brace_idx + 1] + + return retval + + +def remove_boxed(s: str) -> str: + if "\\boxed " in s: + left = "\\boxed " + assert s[: len(left)] == left + return s[len(left) :] + + left = "\\boxed{" + + assert s[: len(left)] == left + assert s[-1] == "}" + + return s[len(left) : -1] + + +class timeout: + def __init__(self, seconds=1, error_message="Timeout"): + self.seconds = seconds + self.error_message = error_message + + def handle_timeout(self, signum, frame): + raise TimeoutError(self.error_message) + + def __enter__(self): + signal.signal(signal.SIGALRM, self.handle_timeout) + signal.alarm(self.seconds) + + def __exit__(self, type, value, traceback): + signal.alarm(0) + + +def is_equiv(x1: str, x2: str) -> bool: + """ + x1 and x2 are normalized latex string + """ + try: + with timeout(seconds=5): + try: + parsed_x1 = parse_latex(x1) + parsed_x2 = parse_latex(x2) + except ( + sympy.parsing.latex.errors.LaTeXParsingError, + sympy.SympifyError, + TypeError, + ): + eval_logger.debug(f"couldn't parse one of {x1} or {x2}") + return False + + try: + diff = parsed_x1 - parsed_x2 + except TypeError: + eval_logger.debug(f"couldn't subtract {x1} and {x2}") + return False + + try: + if sympy.simplify(diff) == 0: + return True + else: + return False + except ValueError: + eval_logger.debug( + f"Had some trouble simplifying when comparing {x1} and {x2}" + ) + except TimeoutError: + eval_logger.debug(f"Timed out comparing {x1} and {x2}") + return False + except ImportError as e: + eval_logger.error(e) + raise + except Exception as e: + eval_logger.debug(f"Failed comparing {x1} and {x2} with {e}") + return False + + +def get_unnormalized_answer(text: str) -> str: + INVALID_ANSWER = "[invalidanswer]" + end_seq = "I hope it is correct." + text += end_seq + match = re.search( + r"Final Answer: The final answer is(.*?). I hope it is correct.", + text, + ) + if match: + return match.group(1).strip() + else: + return INVALID_ANSWER + + +SUBSTITUTIONS = [ + ("an ", ""), + ("a ", ""), + (".$", "$"), + ("\\$", ""), + (r"\ ", ""), + (" ", ""), + ("mbox", "text"), + (",\\text{and}", ","), + ("\\text{and}", ","), + ("\\text{m}", "\\text{}"), +] +REMOVED_EXPRESSIONS = [ + "square", + "ways", + "integers", + "dollars", + "mph", + "inches", + "ft", + "hours", + "km", + "units", + "\\ldots", + "sue", + "points", + "feet", + "minutes", + "digits", + "cents", + "degrees", + "cm", + "gm", + "pounds", + "meters", + "meals", + "edges", + "students", + "childrentickets", + "multiples", + "\\text{s}", + "\\text{.}", + "\\text{\ns}", + "\\text{}^2", + "\\text{}^3", + "\\text{\n}", + "\\text{}", + r"\mathrm{th}", + r"^\circ", + r"^{\circ}", + r"\;", + r",\!", + "{,}", + '"', + "\\dots", +] + + +def normalize_final_answer(final_answer: str) -> str: + """ + Normalize a final answer to a quantitative reasoning question. + + Copied character for character from appendix D of Lewkowycz et al. (2022) + """ + final_answer = final_answer.split("=")[-1] + + for before, after in SUBSTITUTIONS: + final_answer = final_answer.replace(before, after) + for expr in REMOVED_EXPRESSIONS: + final_answer = final_answer.replace(expr, "") + + # Extract answer that is in LaTeX math, is bold, + # is surrounded by a box, etc. + final_answer = re.sub(r"(.*?)(\$)(.*?)(\$)(.*)", "$\\3$", final_answer) + final_answer = re.sub(r"(\\text\{)(.*?)(\})", "\\2", final_answer) + final_answer = re.sub(r"(\\textbf\{)(.*?)(\})", "\\2", final_answer) + final_answer = re.sub(r"(\\overline\{)(.*?)(\})", "\\2", final_answer) + final_answer = re.sub(r"(\\boxed\{)(.*)(\})", "\\2", final_answer) + + # Normalize shorthand TeX: + # \fracab -> \frac{a}{b} + # \frac{abc}{bef} -> \frac{abc}{bef} + # \fracabc -> \frac{a}{b}c + # \sqrta -> \sqrt{a} + # \sqrtab -> sqrt{a}b + final_answer = re.sub(r"(frac)([^{])(.)", "frac{\\2}{\\3}", final_answer) + final_answer = re.sub(r"(sqrt)([^{])", "sqrt{\\2}", final_answer) + final_answer = final_answer.replace("$", "") + + # Normalize 100,000 -> 100000 + if final_answer.replace(",", "").isdigit(): + final_answer = final_answer.replace(",", "") + + return final_answer diff --git a/lm_eval/tasks/leaderboard/mmlu_pro/mmlu_pro.yaml b/lm_eval/tasks/leaderboard/mmlu_pro/mmlu_pro.yaml new file mode 100644 index 00000000..8ddabf14 --- /dev/null +++ b/lm_eval/tasks/leaderboard/mmlu_pro/mmlu_pro.yaml @@ -0,0 +1,17 @@ +dataset_path: TIGER-Lab/MMLU-Pro # a copy of `cais/leaderboard_mmlu` with no auxiliary_train split +task: leaderboard_mmlu_pro +test_split: test +fewshot_split: validation +fewshot_config: + sampler: first_n +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_choice: !function utils.doc_to_choice +doc_to_target: answer +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +num_fewshot: 5 +metadata: + version: 0.1 diff --git a/lm_eval/tasks/leaderboard/mmlu_pro/utils.py b/lm_eval/tasks/leaderboard/mmlu_pro/utils.py new file mode 100644 index 00000000..bb398262 --- /dev/null +++ b/lm_eval/tasks/leaderboard/mmlu_pro/utils.py @@ -0,0 +1,15 @@ +import string + + +def doc_to_text(doc): + doc_to_text = f"{doc['question']}\n" + + for i in range(len(doc["options"])): + doc_to_text += f"{string.ascii_uppercase[i]}. {doc['options'][i]}\n" + + doc_to_text += "Answer:" + return doc_to_text + + +def doc_to_choice(doc): + return [string.ascii_uppercase[i] for i in range(len(doc["options"]))] diff --git a/lm_eval/tasks/leaderboard/musr/_template_yaml b/lm_eval/tasks/leaderboard/musr/_template_yaml new file mode 100644 index 00000000..2076cb9f --- /dev/null +++ b/lm_eval/tasks/leaderboard/musr/_template_yaml @@ -0,0 +1,13 @@ +group: + - leaderboard_musr +dataset_path: TAUR-Lab/MuSR +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_target: "{{answer_choice}}" +doc_to_choice: "{{choices}}" +metric_list: + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/leaderboard/musr/musr_murder_mysteries.yaml b/lm_eval/tasks/leaderboard/musr/musr_murder_mysteries.yaml new file mode 100644 index 00000000..88aac33e --- /dev/null +++ b/lm_eval/tasks/leaderboard/musr/musr_murder_mysteries.yaml @@ -0,0 +1,3 @@ +include: "_template_yaml" +task: leaderboard_musr_murder_mysteries +test_split: murder_mysteries diff --git a/lm_eval/tasks/leaderboard/musr/musr_object_placements.yaml b/lm_eval/tasks/leaderboard/musr/musr_object_placements.yaml new file mode 100644 index 00000000..89b29fb7 --- /dev/null +++ b/lm_eval/tasks/leaderboard/musr/musr_object_placements.yaml @@ -0,0 +1,3 @@ +include: "_template_yaml" +task: leaderboard_musr_object_placements +test_split: object_placements diff --git a/lm_eval/tasks/leaderboard/musr/musr_team_allocation.yaml b/lm_eval/tasks/leaderboard/musr/musr_team_allocation.yaml new file mode 100644 index 00000000..8ede2ba9 --- /dev/null +++ b/lm_eval/tasks/leaderboard/musr/musr_team_allocation.yaml @@ -0,0 +1,3 @@ +include: "_template_yaml" +task: leaderboard_musr_team_allocation +test_split: team_allocation diff --git a/lm_eval/tasks/leaderboard/musr/utils.py b/lm_eval/tasks/leaderboard/musr/utils.py new file mode 100644 index 00000000..1d0a7d1c --- /dev/null +++ b/lm_eval/tasks/leaderboard/musr/utils.py @@ -0,0 +1,26 @@ +import ast + + +def doc_to_choice(doc): + """ + Convert a doc to a choice. + """ + return ast.literal_eval(doc["choices"]) + + +DOC_TO_TEXT = "{narrative}\n\n" "{question}\n\n" "{choices}\n" "Answer:" + + +def doc_to_text(doc): + """ + Convert a doc to text. + """ + choices = "" + for i, choice in enumerate(ast.literal_eval(doc["choices"])): + choices += f"{i+1} - {choice}\n" + + text = DOC_TO_TEXT.format( + narrative=doc["narrative"], question=doc["question"], choices=choices + ) + + return text -- GitLab From d855d0baf8576296e790d0c9477b40a710d28e67 Mon Sep 17 00:00:00 2001 From: Hanwool Albert Lee <88315152+h-albert-lee@users.noreply.github.com> Date: Wed, 3 Jul 2024 21:17:15 +0900 Subject: [PATCH 026/194] #1442 inverse scaling tasks implementation (#1589) * initial_implementation (test has to be proceeded) * minor fix * revised task name and implemented new task * minor fixes * new tasks implement * minor fix * added 'prompt injection' task * delete prompt injection task (will be implemented at next PR) * trust remote code * Update lm_eval/tasks/inverse_scaling/README.md Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * added readme * Update lm_eval/tasks/README.md * Update lm_eval/tasks/inverse_scaling/_inverse_scaling_mc_yaml * Update lm_eval/tasks/inverse_scaling/README.md Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * Update lm_eval/tasks/inverse_scaling/_inverse_scaling_mc_yaml Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * Update README.md * precommit? * run precommit on readme --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Co-authored-by: haileyschoelkopf --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/inverse_scaling/README.md | 55 +++++++++++++++++++ .../inverse_scaling/_inverse_scaling_mc_yaml | 17 ++++++ .../inverse_scaling_hindsight_neglect.yaml | 3 + .../inverse_scaling_into_the_unknown.yaml | 3 + .../inverse_scaling_memo_trap.yaml | 3 + .../inverse_scaling_modus_tollens.yaml | 3 + .../inverse_scaling/inverse_scaling_neqa.yaml | 3 + ..._scaling_pattern_matching_suppression.yaml | 3 + .../inverse_scaling_quote_repetition.yaml | 3 + .../inverse_scaling_redefine_math.yaml | 3 + .../inverse_scaling_repetitive_algebra.yaml | 3 + .../inverse_scaling_sig_figs.yaml | 3 + ...verse_scaling_winobias_antistereotype.yaml | 20 +++++++ 14 files changed, 123 insertions(+) create mode 100644 lm_eval/tasks/inverse_scaling/README.md create mode 100644 lm_eval/tasks/inverse_scaling/_inverse_scaling_mc_yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_hindsight_neglect.yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_into_the_unknown.yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_memo_trap.yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_modus_tollens.yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_neqa.yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_pattern_matching_suppression.yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_quote_repetition.yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_redefine_math.yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_repetitive_algebra.yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_sig_figs.yaml create mode 100644 lm_eval/tasks/inverse_scaling/inverse_scaling_winobias_antistereotype.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 5d6393bb..1eb7fdc5 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -49,6 +49,7 @@ | [hendrycks_ethics](hendrycks_ethics/README.md) | Tasks designed to evaluate the ethical reasoning capabilities of models. | English | | [hendrycks_math](hendrycks_math/README.md) | Mathematical problem-solving tasks to test numerical reasoning and problem-solving. | English | | [ifeval](ifeval/README.md) | Interactive fiction evaluation tasks for narrative understanding and reasoning. | English | +| [inverse_scaling](inverse_scaling/README.md) | Multiple-choice tasks from the Inverse Scaling Prize, designed to find settings where larger language models perform worse. | English | | [kmmlu](kmmlu/README.md) | Knowledge-based multi-subject multiple choice questions for academic evaluation. | Korean | | [kobest](kobest/README.md) | A collection of tasks designed to evaluate understanding in Korean language. | Korean | | [kormedmcqa](kormedmcqa/README.md) | Medical question answering tasks in Korean to test specialized domain knowledge. | Korean | diff --git a/lm_eval/tasks/inverse_scaling/README.md b/lm_eval/tasks/inverse_scaling/README.md new file mode 100644 index 00000000..10364d8e --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/README.md @@ -0,0 +1,55 @@ +# inverse_scaling + +### Paper + +Title: `Inverse Scaling: When Bigger Isn't Better` + +Abstract: `Work on scaling laws has found that large language models (LMs) show predictable improvements to overall loss with increased scale (model size, training data, and compute). Here, we present evidence for the claim that LMs may show inverse scaling, or worse task performance with increased scale, e.g., due to flaws in the training objective and data. We present empirical evidence of inverse scaling on 11 datasets collected by running a public contest, the Inverse Scaling Prize, with a substantial prize pool. Through analysis of the datasets, along with other examples found in the literature, we identify four potential causes of inverse scaling: (i) preference to repeat memorized sequences over following in-context instructions, (ii) imitation of undesirable patterns in the training data, (iii) tasks containing an easy distractor task which LMs could focus on, rather than the harder real task, and (iv) correct but misleading few-shot demonstrations of the task. We release the winning datasets at this https URL to allow for further investigation of inverse scaling. Our tasks have helped drive the discovery of U-shaped and inverted-U scaling trends, where an initial trend reverses, suggesting that scaling trends are less reliable at predicting the behavior of larger-scale models than previously understood. Overall, our results suggest that there are tasks for which increased model scale alone may not lead to progress, and that more careful thought needs to go into the data and objectives for training language models.` + +Note: This is not official implementation of inverse scaling prize. Implemented by h-albert-lee with permission from the authors of the paper. + +Homepage: https://github.com/inverse-scaling/prize + +### Citation + +@article{mckenzie2023inverse, + title={Inverse Scaling: When Bigger Isn't Better}, + author={Ian R. McKenzie and Alexander Lyzhov and Michael Pieler and Alicia Parrish and Aaron Mueller and Ameya Prabhu and Euan McLean and Aaron Kirtland and Alexis Ross and Alisa Liu and Andrew Gritsevskiy and Daniel Wurgaft and Derik Kauffman and Gabriel Recchia and Jiacheng Liu and Joe Cavanagh and Max Weiss and Sicong Huang and The Floating Droid and Tom Tseng and Tomasz Korbak and Xudong Shen and Yuhui Zhang and Zhengping Zhou and Najoung Kim and Samuel R. Bowman and Ethan Perez}, + journal={arXiv preprint arXiv:2306.09479}, + year={2023} +} + +### Groups and Tasks + +#### Groups + +* `inverse_scaling_mc`: all tasks of Inverse Scaling Prize (currently aside from Prompt Injection), matching their implementations on OPT for multiple-choice type classification tasks. **These match the published dataset versions from the prize, which may slightly differ from numbers in the paper (but have been tested for equivalence to the OPT numbers reported at https://huggingface.co/inverse-scaling/opt-1.3b_eval for multiple sizes.** + + +#### Tasks + +- `inverse_scaling_hindsight_neglect_10shot` +- `inverse_scaling_redefine_math` +- `inverse_scaling_quote_repetition` +- `inverse_scaling_neqa` +- `inverse_scaling_winobias_antistereotype`: not an official Inverse Scaling prize winner, but eval results reported on it at https://huggingface.co/inverse-scaling/opt-1.3b_eval . +- `inverse_scaling_into_the_unknown` +- `inverse_scaling_memo_trap` +- `inverse_scaling_modus_tollens` +- `inverse_scaling_pattern_matching_suppression` +- `inverse_scaling_repetitive_algebra` +- `inverse_scaling_sig_figs` + + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [x] Is the task an existing benchmark in the literature? + * [x] Have you referenced the original paper that introduced the task? + * [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/inverse_scaling/_inverse_scaling_mc_yaml b/lm_eval/tasks/inverse_scaling/_inverse_scaling_mc_yaml new file mode 100644 index 00000000..4dc3df7a --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/_inverse_scaling_mc_yaml @@ -0,0 +1,17 @@ +group: + - inverse_scaling_mc +output_type: multiple_choice +test_split: train +doc_to_text: prompt +doc_to_choice: classes +doc_to_target: answer_index +target_delimiter: "" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 0 diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_hindsight_neglect.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_hindsight_neglect.yaml new file mode 100644 index 00000000..b21baee2 --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_hindsight_neglect.yaml @@ -0,0 +1,3 @@ +include: _inverse_scaling_mc_yaml +task: inverse_scaling_hindsight_neglect_10shot +dataset_path: inverse-scaling/hindsight-neglect-10shot diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_into_the_unknown.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_into_the_unknown.yaml new file mode 100644 index 00000000..0c7ccd3b --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_into_the_unknown.yaml @@ -0,0 +1,3 @@ +include: _inverse_scaling_mc_yaml +task: inverse_scaling_into_the_unknown +dataset_path: Albertmade/into-the-unknown diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_memo_trap.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_memo_trap.yaml new file mode 100644 index 00000000..5c77ffc2 --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_memo_trap.yaml @@ -0,0 +1,3 @@ +include: _inverse_scaling_mc_yaml +task: inverse_scaling_memo_trap +dataset_path: Albertmade/memo-trap diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_modus_tollens.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_modus_tollens.yaml new file mode 100644 index 00000000..89e1ebbc --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_modus_tollens.yaml @@ -0,0 +1,3 @@ +include: _inverse_scaling_mc_yaml +task: inverse_scaling_modus_tollens +dataset_path: Albertmade/modus-tollens diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_neqa.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_neqa.yaml new file mode 100644 index 00000000..11a057d8 --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_neqa.yaml @@ -0,0 +1,3 @@ +include: _inverse_scaling_mc_yaml +task: inverse_scaling_neqa +dataset_path: inverse-scaling/NeQA diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_pattern_matching_suppression.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_pattern_matching_suppression.yaml new file mode 100644 index 00000000..b415bba1 --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_pattern_matching_suppression.yaml @@ -0,0 +1,3 @@ +include: _inverse_scaling_mc_yaml +task: inverse_scaling_pattern_matching_suppression +dataset_path: Albertmade/pattern-matching-suppression diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_quote_repetition.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_quote_repetition.yaml new file mode 100644 index 00000000..6750953c --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_quote_repetition.yaml @@ -0,0 +1,3 @@ +include: _inverse_scaling_mc_yaml +task: inverse_scaling_quote_repetition +dataset_path: inverse-scaling/quote-repetition diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_redefine_math.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_redefine_math.yaml new file mode 100644 index 00000000..2f14ba28 --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_redefine_math.yaml @@ -0,0 +1,3 @@ +include: _inverse_scaling_mc_yaml +task: inverse_scaling_redefine_math +dataset_path: inverse-scaling/redefine-math diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_repetitive_algebra.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_repetitive_algebra.yaml new file mode 100644 index 00000000..048ea271 --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_repetitive_algebra.yaml @@ -0,0 +1,3 @@ +include: _inverse_scaling_mc_yaml +task: inverse_scaling_repetitive_algebra +dataset_path: Albertmade/repetitive-algebra diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_sig_figs.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_sig_figs.yaml new file mode 100644 index 00000000..25d86e33 --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_sig_figs.yaml @@ -0,0 +1,3 @@ +include: _inverse_scaling_mc_yaml +task: inverse_scaling_sig_figs +dataset_path: Albertmade/sig-figs diff --git a/lm_eval/tasks/inverse_scaling/inverse_scaling_winobias_antistereotype.yaml b/lm_eval/tasks/inverse_scaling/inverse_scaling_winobias_antistereotype.yaml new file mode 100644 index 00000000..4c5ff300 --- /dev/null +++ b/lm_eval/tasks/inverse_scaling/inverse_scaling_winobias_antistereotype.yaml @@ -0,0 +1,20 @@ +group: + - inverse_scaling_mc +task: inverse_scaling_winobias_antistereotype +dataset_path: mathemakitten/winobias_antistereotype_test_v5 +output_type: multiple_choice +test_split: test +doc_to_text: text +doc_to_choice: classes +doc_to_target: target +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +dataset_kwargs: + trust_remote_code: true +metadata: + version: 0 -- GitLab From 5a7ed3eee00eca378f157abbe9baf4d406f063f2 Mon Sep 17 00:00:00 2001 From: Choyunhui Date: Mon, 8 Jul 2024 16:34:01 +0900 Subject: [PATCH 027/194] Fix TypeError in samplers.py by converting int to str (#2074) Co-authored-by: yhjo --- lm_eval/api/samplers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/api/samplers.py b/lm_eval/api/samplers.py index 74513bbc..ac75c722 100644 --- a/lm_eval/api/samplers.py +++ b/lm_eval/api/samplers.py @@ -55,7 +55,7 @@ class ContextSampler: labeled_examples += ( str(doc_target[0]) if isinstance(doc_target, list) - else doc_target + else str(doc_target) if self.config.doc_to_choice is None or isinstance(doc_target, str) else str(self.doc_to_choice(doc)[doc_target]) ) -- GitLab From 517aadc4d05507e2fea7b7753e91e6ad7dd76847 Mon Sep 17 00:00:00 2001 From: Lintang Sutawika Date: Mon, 8 Jul 2024 22:12:35 +0700 Subject: [PATCH 028/194] Group agg rework (#1741) * add greoup_config arg * add a group config that allows disabling table for group score and group aggregate in general * fixed size configuration * adjust config * add group config * adjust mmlu to use group_config * fixed args input in aggregate_subtask_metrics * fixed issues related to printing alias of group and updated yaml * update all mmlu variants to include group_config * edit format * modify mmlu tasks * adjust group to also be a configurable group * add configurable group * simplify get_task_list * adjust group scoring with using ConfigurableGroup * adjust args * update mmlu * update mmlu * update to work with new group and task configuration * readd group_agg * readd files * move prepare_print_tasks to evaluator_utils * sort set to False by default, fix predict_only arg * add version for groups * reversed task list * update additional condition when loading a group in a group yaml * update truthfulqa * add description regarding tags replacing group * replace group to tag * fixed conditional statement * remove warning * update loading of task group and newly added tags * reformat with pre-commit * fixed info log * update * fix bug * fix bug * use task id to differentiate tasks * convert all groups to configurable groups * use task_id * reformat * add task_id for python tasks as well * add task_id for python tasks as well * add task_id for python tasks as well * revert truthfulqa * revert mmlu tasks * new mmlu config * new group config parameter `tag_to_task` * Update truthfulqa_mc2.yaml * reformate * add _process_group_config * adjust task_id * add get_subtask_list function to get proper subtask list * group config to_dict update * remove tag check * update mmlu * fix config passing issues * add test yaml * format fix * add documentation * corner case for single tag being called * fix indentation * formatting * update all mmlu variants * Update docs/task_guide.md Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * remove group_alias * Update docs/task_guide.md Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * remove version for metadata * Update docs/task_guide.md Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * update mmlu/ * removed " " in make_table * change how aggregate_metric is loaded * change how aggregate_metric is loaded * update aggregate_metric arg * update format * update format * some docs fixes * add groups for agieval, aexams, aclue * add more explicit aggregation groups * add more groupings / tags distinctions * add more groupings * more groupings * add many explicit group configs * add many explicit group configs * add more explicit group configs * add more explicit group configs * add more error msgs, agg_metric -> agg_metric_list * some docs updates * update task_id to be updateable and uses group:task format * make KMMLU a tag for now * update docs * don't duplicate task names * fix merge conflicts? * giving this a try * clean up diff * switch mmlu variants over to using * don't use to-be-deprecated group: config field in overview notebook * Python tasks which subclass ConfigurableTask now run * update mmlu * pre-commit format * fixed sorting for multi-level printing * move group api to separate file * fix bbh aggregation filter usage * track api/group.py * adjust group and tags loading * make explicit group configs for leaderboard and other newer tasks * fix arabicmmlu * update * change arabicmmlu template name??? * update group alias * fix printing bugs * check table printing is correct ; update tests * use mmlu_stem to have a group included in print tests --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Co-authored-by: haileyschoelkopf --- docs/new_task_guide.md | 92 +++-- docs/task_guide.md | 114 +----- examples/lm-eval-overview.ipynb | 5 +- lm_eval/api/group.py | 117 ++++++ lm_eval/api/task.py | 21 +- lm_eval/evaluator.py | 226 +++++------ lm_eval/evaluator_utils.py | 350 ++++++++++++++---- lm_eval/tasks/__init__.py | 245 ++++++++---- lm_eval/tasks/aclue/README.md | 2 +- lm_eval/tasks/aclue/_aclue.yaml | 26 ++ lm_eval/tasks/aclue/_default_template_yaml | 1 - lm_eval/tasks/aexams/README.md | 4 +- lm_eval/tasks/aexams/_aexams.yaml | 16 + lm_eval/tasks/aexams/_default_template_yaml | 1 - lm_eval/tasks/agieval/README.md | 6 +- lm_eval/tasks/agieval/agieval.yaml | 29 ++ lm_eval/tasks/agieval/agieval_cn.yaml | 19 + lm_eval/tasks/agieval/agieval_en.yaml | 18 + lm_eval/tasks/agieval/agieval_nous.yaml | 16 + lm_eval/tasks/agieval/aqua-rat.yaml | 4 - lm_eval/tasks/agieval/gaokao-biology.yaml | 3 - lm_eval/tasks/agieval/gaokao-chemistry.yaml | 3 - lm_eval/tasks/agieval/gaokao-chinese.yaml | 3 - lm_eval/tasks/agieval/gaokao-english.yaml | 3 - lm_eval/tasks/agieval/gaokao-geography.yaml | 3 - lm_eval/tasks/agieval/gaokao-history.yaml | 3 - lm_eval/tasks/agieval/gaokao-mathcloze.yaml | 3 - lm_eval/tasks/agieval/gaokao-mathqa.yaml | 3 - lm_eval/tasks/agieval/gaokao-physics.yaml | 3 - lm_eval/tasks/agieval/jec-qa-ca.yaml | 3 - lm_eval/tasks/agieval/jec-qa-kd.yaml | 3 - lm_eval/tasks/agieval/logiqa-en.yaml | 4 - lm_eval/tasks/agieval/logiqa-zh.yaml | 3 - lm_eval/tasks/agieval/lsat-ar.yaml | 4 - lm_eval/tasks/agieval/lsat-lr.yaml | 4 - lm_eval/tasks/agieval/lsat-rc.yaml | 4 - lm_eval/tasks/agieval/math.yaml | 3 - .../tasks/agieval/sat-en-without-passage.yaml | 4 - lm_eval/tasks/agieval/sat-en.yaml | 4 - lm_eval/tasks/agieval/sat-math.yaml | 4 - lm_eval/tasks/anli/anli_r1.yaml | 2 +- .../{arabicmmlu.yaml => _arabicmmlu.yaml} | 5 + .../arabicmmlu/_arabicmmlu_humanities.yaml | 9 + .../arabicmmlu/_arabicmmlu_language.yaml | 9 + .../tasks/arabicmmlu/_arabicmmlu_other.yaml | 9 + .../_arabicmmlu_social_science.yaml | 9 + .../tasks/arabicmmlu/_arabicmmlu_stem.yaml | 9 + ...yaml => _default_arabicmmlu_template_yaml} | 2 + lm_eval/tasks/arabicmmlu/_generate_configs.py | 5 +- .../arabicmmlu_arabic_language_general.yaml | 5 +- .../arabicmmlu_arabic_language_grammar.yaml | 5 +- .../arabicmmlu/arabicmmlu_driving_test.yaml | 5 +- .../arabicmmlu_general_knowledge.yaml | 5 +- .../arabicmmlu_high_arabic_language.yaml | 5 +- .../arabicmmlu/arabicmmlu_high_biology.yaml | 5 +- .../arabicmmlu/arabicmmlu_high_civics.yaml | 5 +- .../arabicmmlu_high_computer_science.yaml | 5 +- .../arabicmmlu/arabicmmlu_high_economics.yaml | 5 +- .../arabicmmlu/arabicmmlu_high_geography.yaml | 5 +- .../arabicmmlu/arabicmmlu_high_history.yaml | 5 +- .../arabicmmlu_high_islamic_studies.yaml | 5 +- .../arabicmmlu_high_philosophy.yaml | 5 +- .../arabicmmlu/arabicmmlu_high_physics.yaml | 5 +- .../arabicmmlu_islamic_studies.yaml | 5 +- .../arabicmmlu_middle_arabic_language.yaml | 5 +- .../arabicmmlu/arabicmmlu_middle_civics.yaml | 5 +- .../arabicmmlu_middle_computer_science.yaml | 5 +- .../arabicmmlu_middle_economics.yaml | 5 +- .../arabicmmlu_middle_general_knowledge.yaml | 5 +- .../arabicmmlu_middle_geography.yaml | 5 +- .../arabicmmlu/arabicmmlu_middle_history.yaml | 5 +- .../arabicmmlu_middle_islamic_studies.yaml | 5 +- .../arabicmmlu_middle_natural_science.yaml | 5 +- .../arabicmmlu_middle_social_science.yaml | 5 +- .../arabicmmlu_primary_arabic_language.yaml | 5 +- .../arabicmmlu_primary_computer_science.yaml | 5 +- .../arabicmmlu_primary_general_knowledge.yaml | 5 +- .../arabicmmlu_primary_geography.yaml | 5 +- .../arabicmmlu_primary_history.yaml | 5 +- .../arabicmmlu_primary_islamic_studies.yaml | 5 +- .../arabicmmlu/arabicmmlu_primary_math.yaml | 5 +- .../arabicmmlu_primary_natural_science.yaml | 5 +- .../arabicmmlu_primary_social_science.yaml | 5 +- .../tasks/arabicmmlu/arabicmmlu_prof_law.yaml | 5 +- .../arabicmmlu_univ_accounting.yaml | 5 +- .../arabicmmlu_univ_computer_science.yaml | 5 +- .../arabicmmlu/arabicmmlu_univ_economics.yaml | 5 +- .../arabicmmlu_univ_management.yaml | 5 +- .../arabicmmlu_univ_political_science.yaml | 5 +- lm_eval/tasks/arc/README.md | 6 +- lm_eval/tasks/arc/arc_easy.yaml | 2 +- lm_eval/tasks/arc_mt/arc_challenge_mt_fi.yaml | 2 +- lm_eval/tasks/arithmetic/README.md | 4 +- lm_eval/tasks/arithmetic/arithmetic_1dc.yaml | 2 +- lm_eval/tasks/asdiv/README.md | 2 +- lm_eval/tasks/babi/README.md | 6 +- lm_eval/tasks/basqueglue/README.md | 8 +- lm_eval/tasks/basqueglue/bec.yaml | 2 +- lm_eval/tasks/basqueglue/bhtc.yaml | 2 +- lm_eval/tasks/basqueglue/coref.yaml | 2 +- lm_eval/tasks/basqueglue/qnli.yaml | 2 +- lm_eval/tasks/basqueglue/vaxx.yaml | 2 +- lm_eval/tasks/basqueglue/wic.yaml | 2 +- lm_eval/tasks/bbh/README.md | 6 +- lm_eval/tasks/bbh/cot_fewshot/_bbh.yaml | 36 ++ .../bbh/cot_fewshot/_bbh_cot_fewshot.yaml | 36 ++ .../cot_fewshot/_cot_fewshot_template_yaml | 3 - .../bbh/cot_zeroshot/_bbh_cot_zeroshot.yaml | 36 ++ .../cot_zeroshot/_cot_zeroshot_template_yaml | 1 - lm_eval/tasks/bbh/fewshot/_bbh_fewshot.yaml | 35 ++ .../tasks/bbh/fewshot/_fewshot_template_yaml | 1 - lm_eval/tasks/bbh/zeroshot/_bbh_zeroshot.yaml | 36 ++ .../bbh/zeroshot/_zeroshot_template_yaml | 1 - lm_eval/tasks/belebele/_belebele.yaml | 133 +++++++ lm_eval/tasks/belebele/_default_template_yaml | 1 - lm_eval/tasks/belebele/_generate_configs.py | 33 ++ .../tasks/benchmarks/flan/flan_held_in.yaml | 141 ++++--- lm_eval/tasks/benchmarks/minerva_math.yaml | 6 + .../benchmarks/multimedqa/multimedqa.yaml | 4 + lm_eval/tasks/bertaqa/_bertaqa_template | 2 +- lm_eval/tasks/blimp/_blimp.yaml | 75 ++++ lm_eval/tasks/blimp/_template_yaml | 1 - lm_eval/tasks/ceval/_ceval-valid.yaml | 63 ++++ lm_eval/tasks/ceval/_default_ceval_yaml | 1 - lm_eval/tasks/ceval/_generate_configs.py | 25 +- lm_eval/tasks/cmmlu/_cmmlu.yaml | 78 ++++ lm_eval/tasks/cmmlu/_default_template_yaml | 1 - lm_eval/tasks/cmmlu/_generate_configs.py | 30 ++ lm_eval/tasks/cmmlu/cmmlu_agronomy.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_anatomy.yaml | 4 + .../tasks/cmmlu/cmmlu_ancient_chinese.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_arts.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_astronomy.yaml | 4 + .../tasks/cmmlu/cmmlu_business_ethics.yaml | 4 + .../cmmlu_chinese_civil_service_exam.yaml | 4 + .../cmmlu/cmmlu_chinese_driving_rule.yaml | 4 + .../cmmlu/cmmlu_chinese_food_culture.yaml | 4 + .../cmmlu/cmmlu_chinese_foreign_policy.yaml | 4 + .../tasks/cmmlu/cmmlu_chinese_history.yaml | 4 + .../tasks/cmmlu/cmmlu_chinese_literature.yaml | 4 + .../cmmlu_chinese_teacher_qualification.yaml | 4 + .../tasks/cmmlu/cmmlu_clinical_knowledge.yaml | 4 + .../cmmlu_college_actuarial_science.yaml | 4 + .../tasks/cmmlu/cmmlu_college_education.yaml | 4 + .../cmmlu_college_engineering_hydrology.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_college_law.yaml | 4 + .../cmmlu/cmmlu_college_mathematics.yaml | 4 + .../cmmlu_college_medical_statistics.yaml | 4 + .../tasks/cmmlu/cmmlu_college_medicine.yaml | 4 + .../tasks/cmmlu/cmmlu_computer_science.yaml | 4 + .../tasks/cmmlu/cmmlu_computer_security.yaml | 4 + .../tasks/cmmlu/cmmlu_conceptual_physics.yaml | 4 + ...cmmlu_construction_project_management.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_economics.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_education.yaml | 4 + .../cmmlu/cmmlu_electrical_engineering.yaml | 4 + .../tasks/cmmlu/cmmlu_elementary_chinese.yaml | 4 + .../cmmlu/cmmlu_elementary_commonsense.yaml | 4 + ...elementary_information_and_technology.yaml | 4 + .../cmmlu/cmmlu_elementary_mathematics.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_ethnology.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_food_science.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_genetics.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_global_facts.yaml | 4 + .../cmmlu/cmmlu_high_school_biology.yaml | 4 + .../cmmlu/cmmlu_high_school_chemistry.yaml | 4 + .../cmmlu/cmmlu_high_school_geography.yaml | 4 + .../cmmlu/cmmlu_high_school_mathematics.yaml | 4 + .../cmmlu/cmmlu_high_school_physics.yaml | 4 + .../cmmlu/cmmlu_high_school_politics.yaml | 4 + .../tasks/cmmlu/cmmlu_human_sexuality.yaml | 4 + .../tasks/cmmlu/cmmlu_international_law.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_journalism.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_jurisprudence.yaml | 4 + .../cmmlu/cmmlu_legal_and_moral_basis.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_logical.yaml | 4 + .../tasks/cmmlu/cmmlu_machine_learning.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_management.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_marketing.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_marxist_theory.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_modern_chinese.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_nutrition.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_philosophy.yaml | 4 + .../cmmlu/cmmlu_professional_accounting.yaml | 4 + .../tasks/cmmlu/cmmlu_professional_law.yaml | 4 + .../cmmlu/cmmlu_professional_medicine.yaml | 4 + .../cmmlu/cmmlu_professional_psychology.yaml | 4 + .../tasks/cmmlu/cmmlu_public_relations.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_security_study.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_sociology.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_sports_science.yaml | 4 + .../cmmlu_traditional_chinese_medicine.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_virology.yaml | 4 + lm_eval/tasks/cmmlu/cmmlu_world_history.yaml | 4 + .../tasks/cmmlu/cmmlu_world_religions.yaml | 4 + lm_eval/tasks/copal_id/standard.yaml | 2 +- .../crows_pairs/crows_pairs_english.yaml | 4 +- lm_eval/tasks/csatqa/_csatqa.yaml | 17 + lm_eval/tasks/csatqa/_default_csatqa_yaml | 1 - lm_eval/tasks/fda/task.py | 2 +- lm_eval/tasks/fld/fld_default.yaml | 2 - lm_eval/tasks/french_bench/README.md | 4 +- .../french_bench_arc_challenge.yaml | 2 +- .../french_bench/french_bench_boolqa.yaml | 2 +- .../french_bench/french_bench_fquadv2.yaml | 2 +- .../french_bench_fquadv2_bool.yaml | 2 +- .../french_bench_fquadv2_genq.yaml | 2 +- .../french_bench_fquadv2_hasAns.yaml | 2 +- .../french_bench/french_bench_grammar.yaml | 2 +- .../french_bench/french_bench_hellaswag.yaml | 2 +- .../french_bench/french_bench_multifquad.yaml | 2 +- .../french_bench_opus_perplexity.yaml | 2 +- .../french_bench_orangesum_abstract.yaml | 2 +- .../french_bench_orangesum_title.yaml | 2 +- .../french_bench_reading_comp.yaml | 2 +- .../french_bench_topic_based_nli.yaml | 2 +- .../french_bench/french_bench_trivia.yaml | 2 +- .../french_bench/french_bench_vocab.yaml | 2 +- .../french_bench_wikitext_fr.yaml | 2 +- .../tasks/french_bench/french_bench_xnli.yaml | 2 +- lm_eval/tasks/glue/README.md | 6 +- lm_eval/tasks/glue/cola/default.yaml | 2 +- lm_eval/tasks/glue/mnli/default.yaml | 2 +- lm_eval/tasks/glue/mrpc/default.yaml | 2 +- lm_eval/tasks/glue/qnli/default.yaml | 2 +- lm_eval/tasks/glue/qqp/default.yaml | 2 +- lm_eval/tasks/glue/rte/default.yaml | 2 +- lm_eval/tasks/glue/sst2/default.yaml | 2 +- lm_eval/tasks/glue/wnli/default.yaml | 2 +- lm_eval/tasks/gpqa/README.md | 8 +- .../gpqa/cot_n_shot/_gpqa_cot_n_shot_yaml | 2 +- .../gpqa/cot_zeroshot/_gpqa_cot_zeroshot_yaml | 2 +- .../generative/_gpqa_generative_n_shot_yaml | 2 +- lm_eval/tasks/gpqa/n_shot/_gpqa_n_shot_yaml | 2 +- .../tasks/gpqa/zeroshot/_gpqa_zeroshot_yaml | 2 +- .../gsm8k/gsm8k-cot-self-consistency.yaml | 2 +- lm_eval/tasks/gsm8k/gsm8k-cot-zeroshot.yaml | 2 +- lm_eval/tasks/gsm8k/gsm8k-cot.yaml | 2 +- lm_eval/tasks/gsm8k/gsm8k.yaml | 2 +- lm_eval/tasks/haerae/_default_haerae_yaml | 1 - lm_eval/tasks/haerae/_haerae.yaml | 16 + lm_eval/tasks/headqa/headqa_en.yaml | 3 +- lm_eval/tasks/hellaswag/hellaswag.yaml | 2 +- .../tasks/hendrycks_ethics/commonsense.yaml | 2 +- lm_eval/tasks/hendrycks_ethics/justice.yaml | 2 +- .../hendrycks_ethics/utilitarianism.yaml | 2 +- lm_eval/tasks/hendrycks_ethics/virtue.yaml | 2 +- .../tasks/hendrycks_math/hendrycks_math.yaml | 6 + .../hendrycks_math_algebra.yaml | 2 +- .../inverse_scaling/_inverse_scaling_mc_yaml | 2 +- lm_eval/tasks/inverse_scaling/_some_results | 39 ++ lm_eval/tasks/kmmlu/cot_hard/_cot_kmmlu_yaml | 2 +- lm_eval/tasks/kmmlu/direct/_direct_kmmlu_yaml | 2 +- .../kmmlu/direct_hard/_direct_hard_kmmlu_yaml | 2 +- lm_eval/tasks/kmmlu/hard/_hard_kmmlu_yaml | 2 +- lm_eval/tasks/kobest/kobest_boolq.yaml | 2 +- lm_eval/tasks/kobest/kobest_copa.yaml | 2 +- lm_eval/tasks/kobest/kobest_hellaswag.yaml | 2 +- lm_eval/tasks/kobest/kobest_sentineg.yaml | 2 +- lm_eval/tasks/kobest/kobest_wic.yaml | 2 +- lm_eval/tasks/kormedmcqa/_kormedmcqa.yaml | 11 + .../tasks/kormedmcqa/kormedmcqa_doctor.yaml | 1 - .../tasks/kormedmcqa/kormedmcqa_nurse.yaml | 1 - .../tasks/kormedmcqa/kormedmcqa_pharm.yaml | 1 - lm_eval/tasks/lambada/lambada_openai.yaml | 2 +- lm_eval/tasks/lambada/lambada_standard.yaml | 2 +- .../lambada_cloze/lambada_openai_cloze.yaml | 2 +- .../lambada_cloze/lambada_standard_cloze.yaml | 2 +- .../lambada_multilingual/lambada_mt_en.yaml | 2 +- .../leaderboard/bbh_mc/_fewshot_template_yaml | 1 - .../leaderboard/bbh_mc/_leaderboard_bbh.yaml | 26 ++ .../leaderboard/gpqa/_leaderboard_gpqa.yaml | 5 + lm_eval/tasks/leaderboard/gpqa/_template_yaml | 1 - .../_leaderboard_instruction_following.yaml | 3 + lm_eval/tasks/leaderboard/ifeval/ifeval.yaml | 1 - .../leaderboard/math/_leaderboard_math.yaml | 9 + lm_eval/tasks/leaderboard/math/_template_yaml | 2 - lm_eval/tasks/leaderboard/musr/_musr.yaml | 5 + lm_eval/tasks/leaderboard/musr/_template_yaml | 2 - lm_eval/tasks/mathqa/mathqa.yaml | 2 +- lm_eval/tasks/mmlu/_generate_configs.py | 3 +- lm_eval/tasks/mmlu/continuation/_mmlu.yaml | 34 +- .../continuation/mmlu_abstract_algebra.yaml | 2 +- .../tasks/mmlu/continuation/mmlu_anatomy.yaml | 2 +- .../mmlu/continuation/mmlu_astronomy.yaml | 2 +- .../continuation/mmlu_business_ethics.yaml | 2 +- .../continuation/mmlu_clinical_knowledge.yaml | 2 +- .../continuation/mmlu_college_biology.yaml | 2 +- .../continuation/mmlu_college_chemistry.yaml | 2 +- .../mmlu_college_computer_science.yaml | 2 +- .../mmlu_college_mathematics.yaml | 2 +- .../continuation/mmlu_college_medicine.yaml | 2 +- .../continuation/mmlu_college_physics.yaml | 2 +- .../continuation/mmlu_computer_security.yaml | 2 +- .../continuation/mmlu_conceptual_physics.yaml | 2 +- .../mmlu/continuation/mmlu_econometrics.yaml | 2 +- .../mmlu_electrical_engineering.yaml | 2 +- .../mmlu_elementary_mathematics.yaml | 2 +- .../mmlu/continuation/mmlu_formal_logic.yaml | 2 +- .../mmlu/continuation/mmlu_global_facts.yaml | 2 +- .../mmlu_high_school_biology.yaml | 2 +- .../mmlu_high_school_chemistry.yaml | 2 +- .../mmlu_high_school_computer_science.yaml | 2 +- .../mmlu_high_school_european_history.yaml | 2 +- .../mmlu_high_school_geography.yaml | 2 +- ...u_high_school_government_and_politics.yaml | 2 +- .../mmlu_high_school_macroeconomics.yaml | 2 +- .../mmlu_high_school_mathematics.yaml | 2 +- .../mmlu_high_school_microeconomics.yaml | 2 +- .../mmlu_high_school_physics.yaml | 2 +- .../mmlu_high_school_psychology.yaml | 2 +- .../mmlu_high_school_statistics.yaml | 2 +- .../mmlu_high_school_us_history.yaml | 2 +- .../mmlu_high_school_world_history.yaml | 2 +- .../mmlu/continuation/mmlu_human_aging.yaml | 2 +- .../continuation/mmlu_human_sexuality.yaml | 2 +- .../continuation/mmlu_international_law.yaml | 2 +- .../mmlu/continuation/mmlu_jurisprudence.yaml | 2 +- .../continuation/mmlu_logical_fallacies.yaml | 2 +- .../continuation/mmlu_machine_learning.yaml | 2 +- .../mmlu/continuation/mmlu_management.yaml | 2 +- .../mmlu/continuation/mmlu_marketing.yaml | 2 +- .../continuation/mmlu_medical_genetics.yaml | 2 +- .../mmlu/continuation/mmlu_miscellaneous.yaml | 2 +- .../continuation/mmlu_moral_disputes.yaml | 2 +- .../continuation/mmlu_moral_scenarios.yaml | 2 +- .../mmlu/continuation/mmlu_nutrition.yaml | 2 +- .../mmlu/continuation/mmlu_philosophy.yaml | 2 +- .../mmlu/continuation/mmlu_prehistory.yaml | 2 +- .../mmlu_professional_accounting.yaml | 2 +- .../continuation/mmlu_professional_law.yaml | 2 +- .../mmlu_professional_medicine.yaml | 2 +- .../mmlu_professional_psychology.yaml | 2 +- .../continuation/mmlu_public_relations.yaml | 2 +- .../continuation/mmlu_security_studies.yaml | 2 +- .../mmlu/continuation/mmlu_sociology.yaml | 2 +- .../continuation/mmlu_us_foreign_policy.yaml | 2 +- .../mmlu/continuation/mmlu_virology.yaml | 2 +- .../continuation/mmlu_world_religions.yaml | 2 +- lm_eval/tasks/mmlu/default/_mmlu.yaml | 5 + .../tasks/mmlu/default/_mmlu_humanities.yaml | 9 + lm_eval/tasks/mmlu/default/_mmlu_other.yaml | 9 + .../mmlu/default/_mmlu_social_sciences.yaml | 9 + lm_eval/tasks/mmlu/default/_mmlu_stem.yaml | 9 + .../mmlu/default/mmlu_abstract_algebra.yaml | 3 +- lm_eval/tasks/mmlu/default/mmlu_anatomy.yaml | 3 +- .../tasks/mmlu/default/mmlu_astronomy.yaml | 3 +- .../mmlu/default/mmlu_business_ethics.yaml | 3 +- .../mmlu/default/mmlu_clinical_knowledge.yaml | 3 +- .../mmlu/default/mmlu_college_biology.yaml | 3 +- .../mmlu/default/mmlu_college_chemistry.yaml | 3 +- .../mmlu_college_computer_science.yaml | 3 +- .../default/mmlu_college_mathematics.yaml | 3 +- .../mmlu/default/mmlu_college_medicine.yaml | 3 +- .../mmlu/default/mmlu_college_physics.yaml | 3 +- .../mmlu/default/mmlu_computer_security.yaml | 3 +- .../mmlu/default/mmlu_conceptual_physics.yaml | 3 +- .../tasks/mmlu/default/mmlu_econometrics.yaml | 3 +- .../default/mmlu_electrical_engineering.yaml | 3 +- .../default/mmlu_elementary_mathematics.yaml | 3 +- .../tasks/mmlu/default/mmlu_formal_logic.yaml | 3 +- .../tasks/mmlu/default/mmlu_global_facts.yaml | 3 +- .../default/mmlu_high_school_biology.yaml | 3 +- .../default/mmlu_high_school_chemistry.yaml | 3 +- .../mmlu_high_school_computer_science.yaml | 3 +- .../mmlu_high_school_european_history.yaml | 3 +- .../default/mmlu_high_school_geography.yaml | 3 +- ...u_high_school_government_and_politics.yaml | 3 +- .../mmlu_high_school_macroeconomics.yaml | 3 +- .../default/mmlu_high_school_mathematics.yaml | 3 +- .../mmlu_high_school_microeconomics.yaml | 3 +- .../default/mmlu_high_school_physics.yaml | 3 +- .../default/mmlu_high_school_psychology.yaml | 3 +- .../default/mmlu_high_school_statistics.yaml | 3 +- .../default/mmlu_high_school_us_history.yaml | 3 +- .../mmlu_high_school_world_history.yaml | 3 +- .../tasks/mmlu/default/mmlu_human_aging.yaml | 3 +- .../mmlu/default/mmlu_human_sexuality.yaml | 3 +- .../mmlu/default/mmlu_international_law.yaml | 3 +- .../mmlu/default/mmlu_jurisprudence.yaml | 3 +- .../mmlu/default/mmlu_logical_fallacies.yaml | 3 +- .../mmlu/default/mmlu_machine_learning.yaml | 3 +- .../tasks/mmlu/default/mmlu_management.yaml | 3 +- .../tasks/mmlu/default/mmlu_marketing.yaml | 3 +- .../mmlu/default/mmlu_medical_genetics.yaml | 3 +- .../mmlu/default/mmlu_miscellaneous.yaml | 3 +- .../mmlu/default/mmlu_moral_disputes.yaml | 3 +- .../mmlu/default/mmlu_moral_scenarios.yaml | 3 +- .../tasks/mmlu/default/mmlu_nutrition.yaml | 3 +- .../tasks/mmlu/default/mmlu_philosophy.yaml | 3 +- .../tasks/mmlu/default/mmlu_prehistory.yaml | 3 +- .../default/mmlu_professional_accounting.yaml | 3 +- .../mmlu/default/mmlu_professional_law.yaml | 3 +- .../default/mmlu_professional_medicine.yaml | 3 +- .../default/mmlu_professional_psychology.yaml | 3 +- .../mmlu/default/mmlu_public_relations.yaml | 3 +- .../mmlu/default/mmlu_security_studies.yaml | 3 +- .../tasks/mmlu/default/mmlu_sociology.yaml | 3 +- .../mmlu/default/mmlu_us_foreign_policy.yaml | 3 +- lm_eval/tasks/mmlu/default/mmlu_virology.yaml | 3 +- .../mmlu/default/mmlu_world_religions.yaml | 3 +- .../tasks/mmlu/flan_cot_fewshot/_mmlu.yaml | 34 +- .../mmlu_abstract_algebra.yaml | 2 +- .../mmlu/flan_cot_fewshot/mmlu_anatomy.yaml | 2 +- .../mmlu/flan_cot_fewshot/mmlu_astronomy.yaml | 2 +- .../mmlu_business_ethics.yaml | 2 +- .../mmlu_clinical_knowledge.yaml | 2 +- .../mmlu_college_biology.yaml | 2 +- .../mmlu_college_chemistry.yaml | 2 +- .../mmlu_college_computer_science.yaml | 2 +- .../mmlu_college_mathematics.yaml | 2 +- .../mmlu_college_medicine.yaml | 2 +- .../mmlu_college_physics.yaml | 2 +- .../mmlu_computer_security.yaml | 2 +- .../mmlu_conceptual_physics.yaml | 2 +- .../flan_cot_fewshot/mmlu_econometrics.yaml | 2 +- .../mmlu_electrical_engineering.yaml | 2 +- .../mmlu_elementary_mathematics.yaml | 2 +- .../flan_cot_fewshot/mmlu_formal_logic.yaml | 2 +- .../flan_cot_fewshot/mmlu_global_facts.yaml | 2 +- .../mmlu_high_school_biology.yaml | 2 +- .../mmlu_high_school_chemistry.yaml | 2 +- .../mmlu_high_school_computer_science.yaml | 2 +- .../mmlu_high_school_european_history.yaml | 2 +- .../mmlu_high_school_geography.yaml | 2 +- ...u_high_school_government_and_politics.yaml | 2 +- .../mmlu_high_school_macroeconomics.yaml | 2 +- .../mmlu_high_school_mathematics.yaml | 2 +- .../mmlu_high_school_microeconomics.yaml | 2 +- .../mmlu_high_school_physics.yaml | 2 +- .../mmlu_high_school_psychology.yaml | 2 +- .../mmlu_high_school_statistics.yaml | 2 +- .../mmlu_high_school_us_history.yaml | 2 +- .../mmlu_high_school_world_history.yaml | 2 +- .../flan_cot_fewshot/mmlu_human_aging.yaml | 2 +- .../mmlu_human_sexuality.yaml | 2 +- .../mmlu_international_law.yaml | 2 +- .../flan_cot_fewshot/mmlu_jurisprudence.yaml | 2 +- .../mmlu_logical_fallacies.yaml | 2 +- .../mmlu_machine_learning.yaml | 2 +- .../flan_cot_fewshot/mmlu_management.yaml | 2 +- .../mmlu/flan_cot_fewshot/mmlu_marketing.yaml | 2 +- .../mmlu_medical_genetics.yaml | 2 +- .../flan_cot_fewshot/mmlu_miscellaneous.yaml | 2 +- .../flan_cot_fewshot/mmlu_moral_disputes.yaml | 2 +- .../mmlu_moral_scenarios.yaml | 2 +- .../mmlu/flan_cot_fewshot/mmlu_nutrition.yaml | 2 +- .../flan_cot_fewshot/mmlu_philosophy.yaml | 2 +- .../flan_cot_fewshot/mmlu_prehistory.yaml | 2 +- .../mmlu_professional_accounting.yaml | 2 +- .../mmlu_professional_law.yaml | 2 +- .../mmlu_professional_medicine.yaml | 2 +- .../mmlu_professional_psychology.yaml | 2 +- .../mmlu_public_relations.yaml | 2 +- .../mmlu_security_studies.yaml | 2 +- .../mmlu/flan_cot_fewshot/mmlu_sociology.yaml | 2 +- .../mmlu_us_foreign_policy.yaml | 2 +- .../mmlu/flan_cot_fewshot/mmlu_virology.yaml | 2 +- .../mmlu_world_religions.yaml | 2 +- .../tasks/mmlu/flan_cot_zeroshot/_mmlu.yaml | 34 +- .../mmlu_abstract_algebra.yaml | 2 +- .../mmlu/flan_cot_zeroshot/mmlu_anatomy.yaml | 2 +- .../flan_cot_zeroshot/mmlu_astronomy.yaml | 2 +- .../mmlu_business_ethics.yaml | 2 +- .../mmlu_clinical_knowledge.yaml | 2 +- .../mmlu_college_biology.yaml | 2 +- .../mmlu_college_chemistry.yaml | 2 +- .../mmlu_college_computer_science.yaml | 2 +- .../mmlu_college_mathematics.yaml | 2 +- .../mmlu_college_medicine.yaml | 2 +- .../mmlu_college_physics.yaml | 2 +- .../mmlu_computer_security.yaml | 2 +- .../mmlu_conceptual_physics.yaml | 2 +- .../flan_cot_zeroshot/mmlu_econometrics.yaml | 2 +- .../mmlu_electrical_engineering.yaml | 2 +- .../mmlu_elementary_mathematics.yaml | 2 +- .../flan_cot_zeroshot/mmlu_formal_logic.yaml | 2 +- .../flan_cot_zeroshot/mmlu_global_facts.yaml | 2 +- .../mmlu_high_school_biology.yaml | 2 +- .../mmlu_high_school_chemistry.yaml | 2 +- .../mmlu_high_school_computer_science.yaml | 2 +- .../mmlu_high_school_european_history.yaml | 2 +- .../mmlu_high_school_geography.yaml | 2 +- ...u_high_school_government_and_politics.yaml | 2 +- .../mmlu_high_school_macroeconomics.yaml | 2 +- .../mmlu_high_school_mathematics.yaml | 2 +- .../mmlu_high_school_microeconomics.yaml | 2 +- .../mmlu_high_school_physics.yaml | 2 +- .../mmlu_high_school_psychology.yaml | 2 +- .../mmlu_high_school_statistics.yaml | 2 +- .../mmlu_high_school_us_history.yaml | 2 +- .../mmlu_high_school_world_history.yaml | 2 +- .../flan_cot_zeroshot/mmlu_human_aging.yaml | 2 +- .../mmlu_human_sexuality.yaml | 2 +- .../mmlu_international_law.yaml | 2 +- .../flan_cot_zeroshot/mmlu_jurisprudence.yaml | 2 +- .../mmlu_logical_fallacies.yaml | 2 +- .../mmlu_machine_learning.yaml | 2 +- .../flan_cot_zeroshot/mmlu_management.yaml | 2 +- .../flan_cot_zeroshot/mmlu_marketing.yaml | 2 +- .../mmlu_medical_genetics.yaml | 2 +- .../flan_cot_zeroshot/mmlu_miscellaneous.yaml | 2 +- .../mmlu_moral_disputes.yaml | 2 +- .../mmlu_moral_scenarios.yaml | 2 +- .../flan_cot_zeroshot/mmlu_nutrition.yaml | 2 +- .../flan_cot_zeroshot/mmlu_philosophy.yaml | 2 +- .../flan_cot_zeroshot/mmlu_prehistory.yaml | 2 +- .../mmlu_professional_accounting.yaml | 2 +- .../mmlu_professional_law.yaml | 2 +- .../mmlu_professional_medicine.yaml | 2 +- .../mmlu_professional_psychology.yaml | 2 +- .../mmlu_public_relations.yaml | 2 +- .../mmlu_security_studies.yaml | 2 +- .../flan_cot_zeroshot/mmlu_sociology.yaml | 2 +- .../mmlu_us_foreign_policy.yaml | 2 +- .../mmlu/flan_cot_zeroshot/mmlu_virology.yaml | 2 +- .../mmlu_world_religions.yaml | 2 +- .../mmlu/flan_n_shot/generative/_mmlu.yaml | 34 +- .../_mmlu_flan_generative_template_yaml | 1 - .../generative/mmlu_abstract_algebra.yaml | 2 +- .../flan_n_shot/generative/mmlu_anatomy.yaml | 2 +- .../generative/mmlu_astronomy.yaml | 2 +- .../generative/mmlu_business_ethics.yaml | 2 +- .../generative/mmlu_clinical_knowledge.yaml | 2 +- .../generative/mmlu_college_biology.yaml | 2 +- .../generative/mmlu_college_chemistry.yaml | 2 +- .../mmlu_college_computer_science.yaml | 2 +- .../generative/mmlu_college_mathematics.yaml | 2 +- .../generative/mmlu_college_medicine.yaml | 2 +- .../generative/mmlu_college_physics.yaml | 2 +- .../generative/mmlu_computer_security.yaml | 2 +- .../generative/mmlu_conceptual_physics.yaml | 2 +- .../generative/mmlu_econometrics.yaml | 2 +- .../mmlu_electrical_engineering.yaml | 2 +- .../mmlu_elementary_mathematics.yaml | 2 +- .../generative/mmlu_formal_logic.yaml | 2 +- .../generative/mmlu_global_facts.yaml | 2 +- .../generative/mmlu_high_school_biology.yaml | 2 +- .../mmlu_high_school_chemistry.yaml | 2 +- .../mmlu_high_school_computer_science.yaml | 2 +- .../mmlu_high_school_european_history.yaml | 2 +- .../mmlu_high_school_geography.yaml | 2 +- ...u_high_school_government_and_politics.yaml | 2 +- .../mmlu_high_school_macroeconomics.yaml | 2 +- .../mmlu_high_school_mathematics.yaml | 2 +- .../mmlu_high_school_microeconomics.yaml | 2 +- .../generative/mmlu_high_school_physics.yaml | 2 +- .../mmlu_high_school_psychology.yaml | 2 +- .../mmlu_high_school_statistics.yaml | 2 +- .../mmlu_high_school_us_history.yaml | 2 +- .../mmlu_high_school_world_history.yaml | 2 +- .../generative/mmlu_human_aging.yaml | 2 +- .../generative/mmlu_human_sexuality.yaml | 2 +- .../generative/mmlu_international_law.yaml | 2 +- .../generative/mmlu_jurisprudence.yaml | 2 +- .../generative/mmlu_logical_fallacies.yaml | 2 +- .../generative/mmlu_machine_learning.yaml | 2 +- .../generative/mmlu_management.yaml | 2 +- .../generative/mmlu_marketing.yaml | 2 +- .../generative/mmlu_medical_genetics.yaml | 2 +- .../generative/mmlu_miscellaneous.yaml | 2 +- .../generative/mmlu_moral_disputes.yaml | 2 +- .../generative/mmlu_moral_scenarios.yaml | 2 +- .../generative/mmlu_nutrition.yaml | 2 +- .../generative/mmlu_philosophy.yaml | 2 +- .../generative/mmlu_prehistory.yaml | 2 +- .../mmlu_professional_accounting.yaml | 2 +- .../generative/mmlu_professional_law.yaml | 2 +- .../mmlu_professional_medicine.yaml | 2 +- .../mmlu_professional_psychology.yaml | 2 +- .../generative/mmlu_public_relations.yaml | 2 +- .../generative/mmlu_security_studies.yaml | 2 +- .../generative/mmlu_sociology.yaml | 2 +- .../generative/mmlu_us_foreign_policy.yaml | 2 +- .../flan_n_shot/generative/mmlu_virology.yaml | 2 +- .../generative/mmlu_world_religions.yaml | 2 +- .../mmlu/flan_n_shot/loglikelihood/_mmlu.yaml | 34 +- .../loglikelihood/mmlu_abstract_algebra.yaml | 2 +- .../loglikelihood/mmlu_anatomy.yaml | 2 +- .../loglikelihood/mmlu_astronomy.yaml | 2 +- .../loglikelihood/mmlu_business_ethics.yaml | 2 +- .../mmlu_clinical_knowledge.yaml | 2 +- .../loglikelihood/mmlu_college_biology.yaml | 2 +- .../loglikelihood/mmlu_college_chemistry.yaml | 2 +- .../mmlu_college_computer_science.yaml | 2 +- .../mmlu_college_mathematics.yaml | 2 +- .../loglikelihood/mmlu_college_medicine.yaml | 2 +- .../loglikelihood/mmlu_college_physics.yaml | 2 +- .../loglikelihood/mmlu_computer_security.yaml | 2 +- .../mmlu_conceptual_physics.yaml | 2 +- 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.../loglikelihood/mmlu_us_foreign_policy.yaml | 2 +- .../loglikelihood/mmlu_virology.yaml | 2 +- .../loglikelihood/mmlu_world_religions.yaml | 2 +- lm_eval/tasks/mmlu/generative/_mmlu.yaml | 34 +- .../generative/mmlu_abstract_algebra.yaml | 3 +- .../tasks/mmlu/generative/mmlu_anatomy.yaml | 3 +- .../tasks/mmlu/generative/mmlu_astronomy.yaml | 3 +- .../mmlu/generative/mmlu_business_ethics.yaml | 3 +- .../generative/mmlu_clinical_knowledge.yaml | 3 +- .../mmlu/generative/mmlu_college_biology.yaml | 3 +- .../generative/mmlu_college_chemistry.yaml | 3 +- .../mmlu_college_computer_science.yaml | 3 +- .../generative/mmlu_college_mathematics.yaml | 3 +- .../generative/mmlu_college_medicine.yaml | 3 +- .../mmlu/generative/mmlu_college_physics.yaml | 3 +- .../generative/mmlu_computer_security.yaml | 3 +- .../generative/mmlu_conceptual_physics.yaml | 3 +- .../mmlu/generative/mmlu_econometrics.yaml | 3 +- .../mmlu_electrical_engineering.yaml | 3 +- .../mmlu_elementary_mathematics.yaml | 3 +- 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.../mmlu/generative/mmlu_world_religions.yaml | 3 +- .../advanced_ai_risk/_template_yaml | 2 +- .../persona/_template_yaml | 2 +- .../sycophancy/sycophancy_on_nlp_survey.yaml | 2 +- .../sycophancy_on_philpapers2020.yaml | 2 +- ...sycophancy_on_political_typology_quiz.yaml | 2 +- .../{_template_yaml => winogenerated.yaml} | 2 +- .../tasks/okapi/arc_multilingual/_arc_yaml | 2 +- .../hellaswag_multilingual/_hellaswag_yaml | 2 +- .../okapi/mmlu_multilingual/_default_yaml | 2 +- .../_truthfulqa_mc1_yaml | 2 +- lm_eval/tasks/paloma/_paloma_template | 2 +- lm_eval/tasks/paws-x/_pawsx.yaml | 15 + lm_eval/tasks/paws-x/pawsx_template_yaml | 1 - lm_eval/tasks/pile/pile_arxiv.yaml | 2 - lm_eval/tasks/polemo2/polemo2_in.yaml | 2 +- lm_eval/tasks/qa4mre/qa4mre_2011.yaml | 2 +- lm_eval/tasks/qasper/bool.yaml | 2 +- lm_eval/tasks/qasper/freeform.yaml | 2 +- lm_eval/tasks/squad_completion/task.py | 2 +- lm_eval/tasks/storycloze/storycloze_2016.yaml | 2 +- lm_eval/tasks/storycloze/storycloze_2018.yaml | 2 +- lm_eval/tasks/super_glue/README.md | 6 +- lm_eval/tasks/super_glue/boolq/default.yaml | 2 +- lm_eval/tasks/super_glue/boolq/seq2seq.yaml | 2 +- lm_eval/tasks/super_glue/boolq/t5-prompt.yaml | 2 +- lm_eval/tasks/super_glue/cb/default.yaml | 2 +- lm_eval/tasks/super_glue/cb/t5-prompt.yaml | 2 +- lm_eval/tasks/super_glue/copa/default.yaml | 2 +- lm_eval/tasks/super_glue/copa/t5-prompt.yaml | 2 +- lm_eval/tasks/super_glue/multirc/default.yaml | 2 +- .../tasks/super_glue/multirc/t5-prompt.yaml | 2 +- lm_eval/tasks/super_glue/record/default.yaml | 2 +- .../tasks/super_glue/record/t5-prompt.yaml | 2 +- lm_eval/tasks/super_glue/rte/default.yaml | 2 +- lm_eval/tasks/super_glue/rte/t5-prompt.yaml | 2 +- lm_eval/tasks/super_glue/wic/default.yaml | 2 +- lm_eval/tasks/super_glue/wic/t5-prompt.yaml | 2 +- lm_eval/tasks/super_glue/wsc/default.yaml | 2 +- lm_eval/tasks/super_glue/wsc/t5-prompt.yaml | 2 +- lm_eval/tasks/swde/task.py | 2 +- .../tasks/translation/iwslt2017_ar-en.yaml | 3 +- 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create mode 100644 lm_eval/tasks/aclue/_aclue.yaml create mode 100644 lm_eval/tasks/aexams/_aexams.yaml create mode 100644 lm_eval/tasks/agieval/agieval.yaml create mode 100644 lm_eval/tasks/agieval/agieval_cn.yaml create mode 100644 lm_eval/tasks/agieval/agieval_en.yaml create mode 100644 lm_eval/tasks/agieval/agieval_nous.yaml rename lm_eval/tasks/arabicmmlu/{arabicmmlu.yaml => _arabicmmlu.yaml} (60%) create mode 100644 lm_eval/tasks/arabicmmlu/_arabicmmlu_humanities.yaml create mode 100644 lm_eval/tasks/arabicmmlu/_arabicmmlu_language.yaml create mode 100644 lm_eval/tasks/arabicmmlu/_arabicmmlu_other.yaml create mode 100644 lm_eval/tasks/arabicmmlu/_arabicmmlu_social_science.yaml create mode 100644 lm_eval/tasks/arabicmmlu/_arabicmmlu_stem.yaml rename lm_eval/tasks/arabicmmlu/{_default_template_yaml => _default_arabicmmlu_template_yaml} (92%) create mode 100644 lm_eval/tasks/bbh/cot_fewshot/_bbh.yaml create mode 100644 lm_eval/tasks/bbh/cot_fewshot/_bbh_cot_fewshot.yaml create mode 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lm_eval/tasks/paws-x/_pawsx.yaml create mode 100644 lm_eval/tasks/wmdp/_wmdp.yaml create mode 100644 lm_eval/tasks/xcopa/_xcopa.yaml create mode 100644 lm_eval/tasks/xnli/_xnli.yaml create mode 100644 lm_eval/tasks/xstorycloze/_xstorycloze.yaml create mode 100644 lm_eval/tasks/xwinograd/_xwinograd.yaml delete mode 100644 tests/testdata/mmlu_abstract_algebra-mmlu_global_facts-mmlu_public_relations_10_hf_pretrained-EleutherAI-pythia-14m-dtype-float32-device-cpu.txt create mode 100644 tests/testdata/mmlu_stem_10_hf_pretrained-EleutherAI-pythia-14m-dtype-float32-device-cpu.txt create mode 100644 tests/testyamls/test-01.yaml diff --git a/docs/new_task_guide.md b/docs/new_task_guide.md index 2f6d3217..23f8dd81 100644 --- a/docs/new_task_guide.md +++ b/docs/new_task_guide.md @@ -285,7 +285,7 @@ As a heuristic check: For more detail on the task system and advanced features, see [`docs/task_guide.md`](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/task_guide.md) . If none of the above sound like they apply to your task, it's time to continue onto checking your task performance! -### Task name + groups (registering a task) +### Task name + tags (registering a task) To test a task conveniently, it helps to *register* the task--that is, to give it a name and make the `lm-eval` library aware it exists! @@ -296,14 +296,14 @@ task: ``` Including a task name is mandatory. -It is often also convenient to label your task with several `groups`, or tags, though this field is optional: +It is often also convenient to label your task with several `tag` values, though this field is optional: ```yaml -group: - - group1 - - group2 +tag: + - tag1 + - tag2 ``` -This will add your task to the `group1` and `group2` groups, enabling people to know how to categorize your task, and if desired run all tasks in one of these groups at once, your task along with them. +This will add your task to the `tag1` and `tag2` tags, enabling people to know how to categorize your task, and if desired run all tasks in one of these groups at once, your task along with them. If your task is not in the `lm_eval/tasks` folder, you'll need to tell the Eval Harness where to look for YAML files. @@ -319,7 +319,48 @@ Passing `--tasks /path/to/yaml/file` is also accepted. ### Advanced Group Configs -You can make more complete group config while also tailoring parameters for individual tasks. +While `tag` values are helpful when you want to be able to quickly and conveniently run a set of related tasks via `--tasks my_tag_name`, often, we wish to implement more complex logic. For example, the MMLU benchmark contains 57 *subtasks* that must all be *averaged* together in order to report a final 'MMLU score'. + +Groupings of tasks might also use particular variants of a task--for example, we might want to default to evaluating a task as 5-shot when called as part of a given grouping, but not have a preference for number of shots when evaluating it as a standalone. + +We implement this via **groups**, which are distinct from tags. Groups can be implemented via *group config* YAML files, which are laid out similarly but slightly differently to tasks' YAML configs. + +The most basic form of group can be defined via a YAML config similar to the following: + +```yaml +group: nli_tasks +task: + - cb + - anli_r1 + - rte +metadata: + version: 1.0 +``` + +This will behave almost identically to a `tag` that includes these 3 tasks, but with one key distinction: we'll print the `nli_tasks` group as a row (with no associated metrics) in our table of outputs, and visually show that these 3 tasks appear under its subheader. + + +Now, let's assume we actually want to report an aggregate score for `nli_tasks`. We would instead use a YAML config like the following: + +```yaml +group: nli_tasks +task: + - cb + - anli_r1 + - rte +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true # defaults to `true`. Set this to `false` to do a "macro" average (taking each subtask's average accuracy, and summing those accuracies and dividing by 3)--by default we do a "micro" average (retain all subtasks' per-document accuracies, and take the mean over all documents' accuracies to get our aggregate mean). +metadata: + version: 1.0 +``` + +Similar to our `metric_list` for listing out the metrics we want to calculate for a given task, we use an `aggregate_metric_list` field to specify which metric name to aggregate across subtasks, what aggregation function to use, and whether we should micro- or macro- average these metrics. See [./task_guide.md](./task_guide.md) for a full list of related sub-keys. + +**[!Tip]: currently, we predominantly only support the aggregation of group metrics that use `mean` (either micro- or macro- averaged) over their subtasks. If you require even more complex aggregation rules, you may want to perform aggregation offline.** + +Group configs can be fairly complex! We can do various operations, such as defining new subtask(s) inline in our group YAML, overriding an existing task's specific config value, or nesting existing groups within our For example, let's build a config for evaluating MMLU and a few natural language inference tasks. For MMLU, we can write the name for the benchmark as a subtask written under `task`. You can configure the parameters such as `num_fewshot`. If the task being configured is a group such as `mmlu` or `super_glue`, the parameter set will be applied to all of the subtasks. @@ -331,33 +372,13 @@ task: - cb - anli_r1 - rte + aggregate_metric_list: + - metric: acc + aggregation: mean + higher_is_better: true - task: mmlu num_fewshot: 2 ``` -It's also important to note how you can basically insert a group config as a task. Here, to make a group of natural language inference tasks, you simply write like how you would normally write a group config but this time place that as part of a task list under the main group being built. - -### Duplicate Tasks in Group Configs - -There might be cases where you might want to evaluate prompts and how models perform over prompt variations. You can list an existing task (In the example below, `anli_r1`) which varying `doc_to_text` implementation. To differentiate from each variation, we can utilize `task_alias`. LM-Eval will recognize that there are multiple variations of the same tasks and differentiate them. -```yaml -group: flan_held_in -group_alias: Flan (Held-In) -task: - # ANLI R1 - - group: anli_r1_flan - group_alias: ANLI R1 - task: - - task: anli_r1 - task_alias: prompt-0 - include: _held_in_template_yaml - doc_to_text: "{{premise}}\n\nChoose your answer ..." - ... - - task: anli_r1 - task_alias: prompt-1 - include: _held_in_template_yaml - doc_to_text: "{{premise}}\n\nBased on ..." - ... -``` ### Configuring python classes @@ -384,19 +405,16 @@ task: ## Beautifying Table Display -To avoid conflict, each task needs to be registered with a unique name. Because of this, slight variations of task are still counted as unique tasks and need to be named uniquely. This could be done by appending an additional naming that may refer to the variation such as in MMLU where the template used to evaluated for flan are differentiated from the default by the prefix `mmlu_flan_*`. Printing the full task names can easily clutter the results table at the end of the evaluation especially when you have a long list of tasks or are using a benchmark that comprises of many tasks. To make it more legible, you can use `task_alias` and `group_alias` to provide an alternative task name and group name that will be printed. For example in `mmlu_abstract_algebra.yaml` we set `group_alias` to `stem` and `task_alias` to `abstract_algebra`. +To avoid conflict, each task needs to be registered with a unique name. Because of this, slight variations of task are still counted as unique tasks and need to be named uniquely. This could be done by appending an additional naming that may refer to the variation such as in MMLU where the template used to evaluated for flan are differentiated from the default by the prefix `mmlu_flan_*`. Printing the full task names can easily clutter the results table at the end of the evaluation especially when you have a long list of tasks or are using a benchmark that comprises of many tasks. To make it more legible, you can use `task_alias` and `group_alias` to provide an alternative task name and group name that will be printed. For example in `mmlu_abstract_algebra.yaml` we set `task_alias` to `abstract_algebra`. In group configs, a `group_alias` for a group can also be set. ``` "dataset_name": "abstract_algebra" "description": "The following are multiple choice questions (with answers) about abstract\ \ algebra.\n\n" -"group": "mmlu_stem" -"group_alias": "stem" "include": "_default_template_yaml" "task": "mmlu_abstract_algebra" "task_alias": "abstract_algebra" ``` -Note: Even though `group` can be a list, for now, `group_alias` can only be a single string. ## Checking validity @@ -416,9 +434,9 @@ a simple eye test. ## Versioning -One key feature in LM Evaluation Harness is the ability to version tasks--that is, mark them with a specific version number that can be bumped whenever a breaking change is made. +One key feature in LM Evaluation Harness is the ability to version tasks and groups--that is, mark them with a specific version number that can be bumped whenever a breaking change is made. -This version info can be provided by adding the following to your new task config file: +This version info can be provided by adding the following to your new task or group config file: ``` metadata: diff --git a/docs/task_guide.md b/docs/task_guide.md index b10ca7d9..34e47c41 100644 --- a/docs/task_guide.md +++ b/docs/task_guide.md @@ -16,7 +16,8 @@ Tasks are configured via the `TaskConfig` object. Below, we describe all fields Task naming + registration: - **task** (`str`, defaults to None) — name of the task. -- **group** (`str`, *optional*) — name of the task group(s) a task belongs to. Enables one to run all tasks with a specified tag or group name at once. +- **task_alias** (`str`, defaults to None) - Alias of the task name that will be printed in the final table results. +- **tag** (`str`, *optional*) — name of the task tags(s) a task belongs to. Enables one to run all tasks with a specified tag name at once. Dataset configuration options: - **dataset_path** (`str`) — The name of the dataset as listed by HF in the datasets Hub. @@ -55,8 +56,6 @@ Other: ## Filters -Explain: What are filters? What is their place in the pipeline? - A key component of the `lm-evaluation-harness` library is the `Filter` object. In a typical evaluation run of the harness, we take the formatted inputs and run them through our LM, with the appropriate output type (greedy or free-form generation, or loglikelihood-based comparative scoring). After getting scores or output text from our LM on each `Instance` or document in the dataset, we then need to feed these responses into a metric or scoring function to return scores to a user. @@ -295,105 +294,24 @@ Generative tasks: Tasks using complex filtering: - GSM8k with CoT (+ with Self-Consistency): (`lm_eval/tasks/gsm8k/gsm8k-cot.yaml` ; `lm_eval/tasks/gsm8k/gsm8k-cot-self-consistency.yaml`) - -## Benchmarks +# Group Configuration When evaluating a language model, it's is not unusual to test across a number of tasks that may not be related to one another in order to assess a variety of capabilities. To this end, it may be combursome to have to list the set of tasks or add a new group name to each yaml of each individual task. -To solve this, we can create a benchmark yaml config. This is a config that contains the names of the tasks that should be included in a particular benchmark. The config consists of two main keys `group` which denotes the name of the benchmark and `task` which is where we can list the tasks. The tasks listed in `task` are the task names that have been registered. A good example would be the list of tasks used to evaluate the Pythia Suite. - -```yaml -group: pythia -task: - - lambada_openai - - wikitext - - piqa - - sciq - - wsc - - winogrande - - arc - - logiqa - - blimp - - hendrycksTest* -``` - -It is also possible to list an existing task in your benchmark configuration with some adjustments. For example, a few tasks from mmlu is included `multimedqa`. There, the `task_alias` and `group_alias` (See [here](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/new_task_guide.md#beautifying-table-display) for more details) are modified to suit the benchmark. - -```yaml -group: multimedqa -task: - - pubmedqa - - medmcqa - - medqa_4options - - task: mmlu_anatomy - task_alias: "anatomy (mmlu)" - group_alias: null - - task: mmlu_clinical_knowledge - task_alias: "clinical_knowledge (mmlu)" - group_alias: null - ... -``` +To solve this, we can create a **group** yaml config. This is a config that contains the names of the tasks that should be included in a particular group. The config consists of two main keys: a `group` key which denotes the name of the group (as it would be called from the command line, e.g. `mmlu`) and a `task` key which is where we can list the tasks. The tasks listed in `task` are the task names that have been registered. A good example of a group yaml config can be found at [../lm_eval/tasks/mmlu/default/_mmlu.yaml]. See also the [New Task Guide](./new_task_guide.md) for a more in-depth and tutorial-esque explanation of how to write complex GroupConfigs. -Alternatively, benchmarks can have tasks that are customizable for each task. They can be defined like how a yaml task is usually set. +## Configurations -```yaml -group: t0_eval -task: - # Coreference Resolution - - dataset_path: super_glue - dataset_name: wsc.fixed - use_prompt: promptsource:* - training_split: train - validation_split: validation - metric_list: - - metric: exact_match - aggregation: mean - higher_is_better: true - ignore_case: true - ignore_punctuation: true - # Coreference Resolution - - dataset_path: winogrande - dataset_name: winogrande_xl - use_prompt: promptsource:* - training_split: train - validation_split: validation - metric_list: - - metric: exact_match - aggregation: mean - higher_is_better: true - ignore_case: true - ignore_punctuation: true - ... -``` +Groups are configured via the `GroupConfig` object. Below, we describe all fields usable within the object, and their role in defining a task. -If the benchmark contains the same dataset but with different configurations, use `task` to differentiate between them. For example, T0-Eval evaluates on 3 versions of ANLI but the huggingface dataset collects them in one dataset. - -```YAML -group: t0_eval -task: - ... - - task: anli_r1 - dataset_path: anli - use_prompt: promptsource:* - training_split: train_r1 - validation_split: dev_r1 - metric_list: - - metric: exact_match - aggregation: mean - higher_is_better: true - ignore_case: true - ignore_punctuation: true - - task: anli_r2 - dataset_path: anli - use_prompt: promptsource:* - training_split: train_r2 - validation_split: dev_r2 - metric_list: - - metric: exact_match - aggregation: mean - higher_is_better: true - ignore_case: true - ignore_punctuation: true -``` +### Parameters -Calling the benchmark is done the same way we would call any task with `--tasks`. Benchmarks can be added in `lm_eval/tasks/benchmarks/` +- **group** (`str`, defaults to `None`) — name of the group. Used to invoke it from the command line. +- **group_alias** (`str`, defaults to `None`) - Alternative name for the group that will be printed in the table output. +- **task** (`Union[str, list]`, defaults to `None`) - List of tasks that constitute the group. +- **aggregate_metric_list** (`list`, defaults to `None`) - similar to `metric_list` in TaskConfigs, provide a list of configurations for metrics that should be aggregated across subtasks. Leaving empty will result in no aggregation being performed for this group. Keys for each list entry are: + - `metric: str` - the name of the metric to aggregate over (all subtasks must report a metric holding this name.) + - `aggregation: str` - what aggregation function to apply to aggregate these per-subtask metrics. **currently, only `mean` is supported.** + - `weight_by_size: bool = True` whether to perform micro- averaging (`True`) or macro- (`False`) averaging of subtasks' accuracy scores when reporting the group's metric. MMLU, for example, averages over per-document accuracies (the *micro average*), resulting in the same accuracy as if one simply concatenated all 57 subjects into a single dataset and evaluated accuracy on that dataset. + - `filter_list: Union[str, List[str]] = "none"` - what filter keys one should match on to aggregate results. For example, if trying to aggregate over the `exact_match` metric using `strict-match` filter for `bbh_cot_zeroshot`, then set this to be `filter_list: "strict-match"`. +- **metadata** (`dict`, *optional*) - As with TaskConfigs, a field where extra config metadata can be passed. set the `num_fewshot` key within this to override the printed n_shot value in a results table for your group, for example. diff --git a/examples/lm-eval-overview.ipynb b/examples/lm-eval-overview.ipynb index 898192ce..6ba5cdf2 100644 --- a/examples/lm-eval-overview.ipynb +++ b/examples/lm-eval-overview.ipynb @@ -377,7 +377,7 @@ "id": "LOUHK7PtQfq4" }, "source": [ - "Often, tasks are part of a larger group used to measure different capabilities. The dynamism of the field today means new dimensions of evaluation can come about which would mix and match new and older tasks alike. In LM-Eval, We can also group tasks and call that the group name to evaluate on a set of tasks easily. In this instance, let's evaluate the group `yes_or_no_tasks` which comprise of the tasks `demo_boolq` and `demo_cola`; tasks which are multiple choice tasks with options `yes` and `no` as the name suggests.\n", + "Often, tasks are part of a larger group used to measure different capabilities. The dynamism of the field today means new dimensions of evaluation can come about which would mix and match new and older tasks alike. In LM-Eval, We can also group tasks and call that the group name to evaluate on a set of tasks easily. In this instance, let's evaluate the tag `yes_or_no_tasks` which comprise of the tasks `demo_boolq` and `demo_cola`; tasks which are multiple choice tasks with options `yes` and `no` as the name suggests.\n", "\n", " "computer science" (#2241) --- lm_eval/tasks/mmlu_pro/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/tasks/mmlu_pro/utils.py b/lm_eval/tasks/mmlu_pro/utils.py index 15c8b39b..03117be5 100644 --- a/lm_eval/tasks/mmlu_pro/utils.py +++ b/lm_eval/tasks/mmlu_pro/utils.py @@ -50,7 +50,7 @@ def process_docs(dataset, subject): process_biology = partial(process_docs, subject="biology") process_business = partial(process_docs, subject="business") process_chemistry = partial(process_docs, subject="chemistry") -process_computer_science = partial(process_docs, subject="computer_science") +process_computer_science = partial(process_docs, subject="computer science") process_economics = partial(process_docs, subject="economics") process_engineering = partial(process_docs, subject="engineering") process_health = partial(process_docs, subject="health") -- GitLab From fa837646bdc01a22e611c3fd3fe5b528a58f309e Mon Sep 17 00:00:00 2001 From: LSinev Date: Fri, 23 Aug 2024 12:15:12 +0300 Subject: [PATCH 084/194] Fix typos in multiple places (#2244) ACLUE bibtex typo reported to ACL Anthology and fixed here as title in pdf is correct. --- lm_eval/tasks/README.md | 2 +- lm_eval/tasks/__init__.py | 2 +- lm_eval/tasks/aclue/README.md | 2 +- lm_eval/tasks/eq_bench/README.md | 4 +- lm_eval/tasks/ifeval/instructions.py | 52 +++++++++---------- .../tasks/leaderboard/ifeval/instructions.py | 52 +++++++++---------- lm_eval/tasks/scrolls/README.md | 2 +- lm_eval/tasks/scrolls/task.py | 2 +- .../tmmluplus/default/_generate_configs.py | 2 +- 9 files changed, 60 insertions(+), 60 deletions(-) diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 518975a9..6c500ee5 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -69,7 +69,7 @@ | [mgsm](mgsm/README.md) | Benchmark of multilingual grade-school math problems. | Spanish, French, German, Russian, Chinese, Japanese, Thai, Swahili, Bengali, Telugu | | [minerva_math](minerva_math/README.md) | Mathematics-focused tasks requiring numerical reasoning and problem-solving skills. | English | | mmlu | Massive Multitask Language Understanding benchmark for broad domain language evaluation. Several variants are supported. | English | -| [mmlusr](mmlusr/README.md) | Variation of MMLU designed to be more rigourous. | English | +| [mmlusr](mmlusr/README.md) | Variation of MMLU designed to be more rigorous. | English | | model_written_evals | Evaluation tasks auto-generated for evaluating a collection of AI Safety concerns. | | | [mutual](mutual/README.md) | A retrieval-based dataset for multi-turn dialogue reasoning. | English | | [nq_open](nq_open/README.md) | Open domain question answering tasks based on the Natural Questions dataset. | English | diff --git a/lm_eval/tasks/__init__.py b/lm_eval/tasks/__init__.py index b8927179..4cae6852 100644 --- a/lm_eval/tasks/__init__.py +++ b/lm_eval/tasks/__init__.py @@ -492,7 +492,7 @@ class TaskManager: "`group` and `group_alias` keys in tasks' configs will no longer be used in the next release of lm-eval. " "`tag` will be used to allow to call a collection of tasks just like `group`. " "`group` will be removed in order to not cause confusion with the new ConfigurableGroup " - "which will be the offical way to create groups with addition of group-wide configuations." + "which will be the official way to create groups with addition of group-wide configurations." ) print_info = False # attr = "tag" diff --git a/lm_eval/tasks/aclue/README.md b/lm_eval/tasks/aclue/README.md index 5e218e59..6323ef7e 100644 --- a/lm_eval/tasks/aclue/README.md +++ b/lm_eval/tasks/aclue/README.md @@ -14,7 +14,7 @@ Homepage: https://github.com/isen-zhang/ACLUE ```bibtex @inproceedings{zhang-li-2023-large, - title = "Can Large Langauge Model Comprehend {A}ncient {C}hinese? A Preliminary Test on {ACLUE}", + title = "Can Large Language Model Comprehend {A}ncient {C}hinese? A Preliminary Test on {ACLUE}", author = "Zhang, Yixuan and Li, Haonan", booktitle = "Proceedings of the Ancient Language Processing Workshop", month = sep, diff --git a/lm_eval/tasks/eq_bench/README.md b/lm_eval/tasks/eq_bench/README.md index 472890bd..df11108e 100644 --- a/lm_eval/tasks/eq_bench/README.md +++ b/lm_eval/tasks/eq_bench/README.md @@ -16,8 +16,8 @@ Homepage: https://eqbench.com/ NOTE: There are some key differences between the lm-evaluation-harness version and the implementation described in the EQ-Bench paper (These have been OK'd by the author): - The lm-eval version uses the EQ-Bench v2 test set (171 questions) and score calculation. It does not incorporate the revision part of the prompt, as per v2.1 (https://github.com/EQ-bench/EQ-Bench) -- No retries in lm-eval version (EQ-Bench pipeline retries with successively higher temps if it encounters unparseable answers) -- In the original implementation, unparseable answers are excluded from the final score, and 83% of answers have to be parseable or a fail is returned. The lm-eval version instead assigns 0 to unparsable answers and has no fail criteria. So for lower performing models, there may be differences with the EQ-Bench leaderboard. +- No retries in lm-eval version (EQ-Bench pipeline retries with successively higher temps if it encounters unparsable answers) +- In the original implementation, unparsable answers are excluded from the final score, and 83% of answers have to be parseable or a fail is returned. The lm-eval version instead assigns 0 to unparsable answers and has no fail criteria. So for lower performing models, there may be differences with the EQ-Bench leaderboard. ### Citation diff --git a/lm_eval/tasks/ifeval/instructions.py b/lm_eval/tasks/ifeval/instructions.py index 5c352af3..a79cbba4 100644 --- a/lm_eval/tasks/ifeval/instructions.py +++ b/lm_eval/tasks/ifeval/instructions.py @@ -78,7 +78,7 @@ _ENDING_OPTIONS = ("Any other questions?", "Is there anything else I can help wi # The number of highlighted sections. _NUM_HIGHLIGHTED_SECTIONS = 4 -# The section spliter. +# The section splitter. _SECTION_SPLITER = ("Section", "SECTION") # The number of sections. @@ -153,7 +153,7 @@ class ResponseLanguageChecker(Instruction): return self._description_pattern.format(language=_LANGUAGES[self._language]) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"language": self._language} def get_instruction_args_keys(self): @@ -223,7 +223,7 @@ class NumberOfSentences(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "num_sentences": self._num_sentences_threshold, "relation": self._comparison_relation, @@ -276,7 +276,7 @@ class PlaceholderChecker(Instruction): return self._description_pattern.format(num_placeholders=self._num_placeholders) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"num_placeholders": self._num_placeholders} def get_instruction_args_keys(self): @@ -323,7 +323,7 @@ class BulletListChecker(Instruction): return self._description_pattern.format(num_bullets=self._num_bullets) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"num_bullets": self._num_bullets} def get_instruction_args_keys(self): @@ -362,7 +362,7 @@ class ConstrainedResponseChecker(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return None def get_instruction_args_keys(self): @@ -393,7 +393,7 @@ class ConstrainedStartChecker(Instruction): """Build the instruction description. Args: - starter: A string representing the keyward that the response should start + starter: A string representing the keyword that the response should start with. Returns: @@ -409,7 +409,7 @@ class ConstrainedStartChecker(Instruction): return self._description_pattern.format(starter=self._starter) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"starter": self._starter} def get_instruction_args_keys(self): @@ -458,7 +458,7 @@ class HighlightSectionChecker(Instruction): return self._description_pattern.format(num_highlights=self._num_highlights) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"num_highlights": self._num_highlights} def get_instruction_args_keys(self): @@ -469,12 +469,12 @@ class HighlightSectionChecker(Instruction): """Checks if the number of highlighted sections meets the requirement. Args: - value: a string repesenting the response. The response is expected to + value: a string representing the response. The response is expected to contain highlighted sections in the format of *highlighted*. Returns: True if the actual number of highlighted sections in the format of - *highlighed sections* meets the minimum requirement; otherwise False. + *highlighted sections* meets the minimum requirement; otherwise False. """ num_highlights = 0 highlights = re.findall(r"\*[^\n\*]*\*", value) @@ -529,7 +529,7 @@ class SectionChecker(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "section_spliter": self._section_spliter, "num_sections": self._num_sections, @@ -582,7 +582,7 @@ class ParagraphChecker(Instruction): return self._description_pattern.format(num_paragraphs=self._num_paragraphs) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"num_paragraphs": self._num_paragraphs} def get_instruction_args_keys(self): @@ -642,7 +642,7 @@ class PostscriptChecker(Instruction): return self._description_pattern.format(postscript=self._postscript_marker) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"postscript_marker": self._postscript_marker} def get_instruction_args_keys(self): @@ -672,7 +672,7 @@ class PostscriptChecker(Instruction): class RephraseChecker(Instruction): - """Checks the repharse.""" + """Checks the rephrase.""" def build_description(self, *, original_message): """Build the instruction description. @@ -701,7 +701,7 @@ class RephraseChecker(Instruction): return self._description def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"original_message": self._reference_without_change} def get_instruction_args_keys(self): @@ -766,7 +766,7 @@ class KeywordChecker(Instruction): return self._description_pattern.format(keywords=self._keywords) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"keywords": self._keywords} def get_instruction_args_keys(self): @@ -831,7 +831,7 @@ class KeywordFrequencyChecker(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "keyword": self._keyword, "frequency": self._frequency, @@ -894,7 +894,7 @@ class NumberOfWords(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"num_words": self._num_words, "relation": self._comparison_relation} def get_instruction_args_keys(self): @@ -922,7 +922,7 @@ class JsonFormat(Instruction): return self._description_pattern def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return None def get_instruction_args_keys(self): @@ -996,7 +996,7 @@ class ParagraphFirstWordCheck(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "num_paragraphs": self._num_paragraphs, "nth_paragraph": self._nth_paragraph, @@ -1089,7 +1089,7 @@ class KeySentenceChecker(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "num_sentences": self._num_sentences, "key_sentences": list(self._key_sentences), @@ -1117,7 +1117,7 @@ class ForbiddenWords(Instruction): """Build the instruction description. Args: - forbidden_words: A sequences of strings respresenting words that are not + forbidden_words: A sequences of strings representing words that are not allowed in the response. Returns: @@ -1138,7 +1138,7 @@ class ForbiddenWords(Instruction): return self._description_pattern.format(forbidden_words=self._forbidden_words) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"forbidden_words": self._forbidden_words} def get_instruction_args_keys(self): @@ -1188,7 +1188,7 @@ class RephraseParagraph(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "original_paragraph": self._original_paragraph, "low": self._low, @@ -1225,7 +1225,7 @@ class TwoResponsesChecker(Instruction): return self._description_pattern def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return None def get_instruction_args_keys(self): diff --git a/lm_eval/tasks/leaderboard/ifeval/instructions.py b/lm_eval/tasks/leaderboard/ifeval/instructions.py index 5c352af3..a79cbba4 100644 --- a/lm_eval/tasks/leaderboard/ifeval/instructions.py +++ b/lm_eval/tasks/leaderboard/ifeval/instructions.py @@ -78,7 +78,7 @@ _ENDING_OPTIONS = ("Any other questions?", "Is there anything else I can help wi # The number of highlighted sections. _NUM_HIGHLIGHTED_SECTIONS = 4 -# The section spliter. +# The section splitter. _SECTION_SPLITER = ("Section", "SECTION") # The number of sections. @@ -153,7 +153,7 @@ class ResponseLanguageChecker(Instruction): return self._description_pattern.format(language=_LANGUAGES[self._language]) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"language": self._language} def get_instruction_args_keys(self): @@ -223,7 +223,7 @@ class NumberOfSentences(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "num_sentences": self._num_sentences_threshold, "relation": self._comparison_relation, @@ -276,7 +276,7 @@ class PlaceholderChecker(Instruction): return self._description_pattern.format(num_placeholders=self._num_placeholders) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"num_placeholders": self._num_placeholders} def get_instruction_args_keys(self): @@ -323,7 +323,7 @@ class BulletListChecker(Instruction): return self._description_pattern.format(num_bullets=self._num_bullets) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"num_bullets": self._num_bullets} def get_instruction_args_keys(self): @@ -362,7 +362,7 @@ class ConstrainedResponseChecker(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return None def get_instruction_args_keys(self): @@ -393,7 +393,7 @@ class ConstrainedStartChecker(Instruction): """Build the instruction description. Args: - starter: A string representing the keyward that the response should start + starter: A string representing the keyword that the response should start with. Returns: @@ -409,7 +409,7 @@ class ConstrainedStartChecker(Instruction): return self._description_pattern.format(starter=self._starter) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"starter": self._starter} def get_instruction_args_keys(self): @@ -458,7 +458,7 @@ class HighlightSectionChecker(Instruction): return self._description_pattern.format(num_highlights=self._num_highlights) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"num_highlights": self._num_highlights} def get_instruction_args_keys(self): @@ -469,12 +469,12 @@ class HighlightSectionChecker(Instruction): """Checks if the number of highlighted sections meets the requirement. Args: - value: a string repesenting the response. The response is expected to + value: a string representing the response. The response is expected to contain highlighted sections in the format of *highlighted*. Returns: True if the actual number of highlighted sections in the format of - *highlighed sections* meets the minimum requirement; otherwise False. + *highlighted sections* meets the minimum requirement; otherwise False. """ num_highlights = 0 highlights = re.findall(r"\*[^\n\*]*\*", value) @@ -529,7 +529,7 @@ class SectionChecker(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "section_spliter": self._section_spliter, "num_sections": self._num_sections, @@ -582,7 +582,7 @@ class ParagraphChecker(Instruction): return self._description_pattern.format(num_paragraphs=self._num_paragraphs) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"num_paragraphs": self._num_paragraphs} def get_instruction_args_keys(self): @@ -642,7 +642,7 @@ class PostscriptChecker(Instruction): return self._description_pattern.format(postscript=self._postscript_marker) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"postscript_marker": self._postscript_marker} def get_instruction_args_keys(self): @@ -672,7 +672,7 @@ class PostscriptChecker(Instruction): class RephraseChecker(Instruction): - """Checks the repharse.""" + """Checks the rephrase.""" def build_description(self, *, original_message): """Build the instruction description. @@ -701,7 +701,7 @@ class RephraseChecker(Instruction): return self._description def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"original_message": self._reference_without_change} def get_instruction_args_keys(self): @@ -766,7 +766,7 @@ class KeywordChecker(Instruction): return self._description_pattern.format(keywords=self._keywords) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"keywords": self._keywords} def get_instruction_args_keys(self): @@ -831,7 +831,7 @@ class KeywordFrequencyChecker(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "keyword": self._keyword, "frequency": self._frequency, @@ -894,7 +894,7 @@ class NumberOfWords(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"num_words": self._num_words, "relation": self._comparison_relation} def get_instruction_args_keys(self): @@ -922,7 +922,7 @@ class JsonFormat(Instruction): return self._description_pattern def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return None def get_instruction_args_keys(self): @@ -996,7 +996,7 @@ class ParagraphFirstWordCheck(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "num_paragraphs": self._num_paragraphs, "nth_paragraph": self._nth_paragraph, @@ -1089,7 +1089,7 @@ class KeySentenceChecker(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "num_sentences": self._num_sentences, "key_sentences": list(self._key_sentences), @@ -1117,7 +1117,7 @@ class ForbiddenWords(Instruction): """Build the instruction description. Args: - forbidden_words: A sequences of strings respresenting words that are not + forbidden_words: A sequences of strings representing words that are not allowed in the response. Returns: @@ -1138,7 +1138,7 @@ class ForbiddenWords(Instruction): return self._description_pattern.format(forbidden_words=self._forbidden_words) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return {"forbidden_words": self._forbidden_words} def get_instruction_args_keys(self): @@ -1188,7 +1188,7 @@ class RephraseParagraph(Instruction): ) def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return { "original_paragraph": self._original_paragraph, "low": self._low, @@ -1225,7 +1225,7 @@ class TwoResponsesChecker(Instruction): return self._description_pattern def get_instruction_args(self): - """Returns the keyward args of `build_description`.""" + """Returns the keyword args of `build_description`.""" return None def get_instruction_args_keys(self): diff --git a/lm_eval/tasks/scrolls/README.md b/lm_eval/tasks/scrolls/README.md index a90e00f4..b1245926 100644 --- a/lm_eval/tasks/scrolls/README.md +++ b/lm_eval/tasks/scrolls/README.md @@ -11,7 +11,7 @@ Homepage: https://www.scrolls-benchmark.com/ Since SCROLLS tasks are generally longer than the maximum sequence length of many models, it is possible to create "subset" tasks that contain only those samples whose tokenized length is less than some pre-defined limit. For example, to create a subset of "Qasper" that would -be suitable for a model using the GPTNeoX tokenizer and a 4K maximium sequence length: +be suitable for a model using the GPTNeoX tokenizer and a 4K maximum sequence length: ``` class QasperGPTNeoX4K(Qasper): diff --git a/lm_eval/tasks/scrolls/task.py b/lm_eval/tasks/scrolls/task.py index 45656be3..ac2fed25 100644 --- a/lm_eval/tasks/scrolls/task.py +++ b/lm_eval/tasks/scrolls/task.py @@ -439,7 +439,7 @@ class GovReport(_SCROLLSSummaryTask): Note: The average length of the reference summaries is ~3,000 characters, or ~600 tokens as tokenized by GPT-NeoX. For causal models, - it is recommended to set `max_gen_toks` sufficently large (e.g. 1024) + it is recommended to set `max_gen_toks` sufficiently large (e.g. 1024) to allow a full summary to be generated. """ diff --git a/lm_eval/tasks/tmmluplus/default/_generate_configs.py b/lm_eval/tasks/tmmluplus/default/_generate_configs.py index a3b1271a..06ef7a71 100644 --- a/lm_eval/tasks/tmmluplus/default/_generate_configs.py +++ b/lm_eval/tasks/tmmluplus/default/_generate_configs.py @@ -11,7 +11,7 @@ from tqdm import tqdm # Copy from https://github.com/iKala/ievals/blob/main/ievals/settings.py -# from TMMLU+ offical example +# from TMMLU+ official example categories = { "STEM": [ "physics", -- GitLab From 5ad23ec22ca63193ef6ace0fded1142c6c34eb21 Mon Sep 17 00:00:00 2001 From: eyuansu62 <30862458+eyuansu62@users.noreply.github.com> Date: Fri, 23 Aug 2024 19:55:20 +0800 Subject: [PATCH 085/194] fix group args of mmlu and mmlu_pro (#2245) --- lm_eval/tasks/mmlu/generative/_mmlu.yaml | 3 ++- lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml | 23 +++++++++++++++++++++++ 2 files changed, 25 insertions(+), 1 deletion(-) create mode 100644 lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml diff --git a/lm_eval/tasks/mmlu/generative/_mmlu.yaml b/lm_eval/tasks/mmlu/generative/_mmlu.yaml index 3cff0f12..1a63611b 100644 --- a/lm_eval/tasks/mmlu/generative/_mmlu.yaml +++ b/lm_eval/tasks/mmlu/generative/_mmlu.yaml @@ -26,7 +26,8 @@ task: - metric: acc weight_by_size: True aggregate_metric_list: - - metric: acc + - aggregation: mean + metric: exact_match weight_by_size: True metadata: version: 2 diff --git a/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml b/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml new file mode 100644 index 00000000..84ae47e7 --- /dev/null +++ b/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml @@ -0,0 +1,23 @@ +group: mmlu_pro +task: + - mmlu_pro_biology + - mmlu_pro_business + - mmlu_pro_chemistry + - mmlu_pro_computer_science + - mmlu_pro_economics + - mmlu_pro_engineering + - mmlu_pro_health + - mmlu_pro_history + - mmlu_pro_law + - mmlu_pro_math + - mmlu_pro_other + - mmlu_pro_philosophy + - mmlu_pro_physics + - mmlu_pro_psychology +aggregate_metric_list: + - aggregation: mean + metric: exact_match + weight_by_size: true + filter_list: custom-extract +metadata: + version: 1.0 \ No newline at end of file -- GitLab From aab42ba836b4af28cc1c5c1e697ea334c6ea7ced Mon Sep 17 00:00:00 2001 From: Cameron Witkowski Date: Fri, 23 Aug 2024 14:47:54 -0400 Subject: [PATCH 086/194] Created new task for testing Llama on Asdiv (#2236) * Created DUP eval code for gsm8k * asdiv * Fixed fewshot=8 issue * added results to .gitignore * reverted unnecessary changes and moved results + gsm8k_dup out of repo to prepare for pull req * fixed whitespace and unintentional hardcoded version change information * created mbpp task * Reverted changes re. mbpp to save for a future Pull req * reverted metrics.py to previous commit * updated asdiv readme to include informaiton about new asdiv_cot_llama task * Apply suggestions from code review --------- Co-authored-by: Alexander Detkov Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- lm_eval/tasks/asdiv/README.md | 5 ++ lm_eval/tasks/asdiv/asdiv-cot-llama.yaml | 88 ++++++++++++++++++++++++ 2 files changed, 93 insertions(+) create mode 100644 lm_eval/tasks/asdiv/asdiv-cot-llama.yaml diff --git a/lm_eval/tasks/asdiv/README.md b/lm_eval/tasks/asdiv/README.md index 46ca56c0..11ffaf81 100644 --- a/lm_eval/tasks/asdiv/README.md +++ b/lm_eval/tasks/asdiv/README.md @@ -41,6 +41,11 @@ Homepage: https://github.com/chaochun/nlu-asdiv-dataset #### Tasks * `asdiv` +* `asdiv_cot_llama`: ASDIV with prompt formatting modified to conform to the evaluation settings described by Meta here: https://huggingface.co/datasets/meta-llama/Meta-Llama-3.1-8B-Instruct-evals/viewer/Meta-Llama-3.1-8B-Instruct-evals__gsm8k__details?row=0 + - Note that the CoT prompt from (https://arxiv.org/pdf/2201.11903) is used exactly as in GSM8k-CoT + - This file is setup to run identically to the task `gsm8k_cot_llama` but for asdiv. + - Use this task with --fewshot_as_multiturn and --apply_chat_template to run correctly with Llama Instruct models. + ### Checklist diff --git a/lm_eval/tasks/asdiv/asdiv-cot-llama.yaml b/lm_eval/tasks/asdiv/asdiv-cot-llama.yaml new file mode 100644 index 00000000..344ba223 --- /dev/null +++ b/lm_eval/tasks/asdiv/asdiv-cot-llama.yaml @@ -0,0 +1,88 @@ +dataset_path: EleutherAI/asdiv +doc_to_target: "{{answer.split(' (')[0] if answer is defined else target}}" +doc_to_text: "Given the following problem, reason and give a final answer to the problem.\nProblem: {{body if body is defined}} {{question}}\nYour response should end with \"The final answer is [answer]\" where [answer] is the response to the problem.\n" +fewshot_config: + sampler: first_n + samples: + - question: There are 15 trees in the grove. Grove workers will plant trees in the + grove today. After they are done, there will be 21 trees. How many trees did + the grove workers plant today? + target: There are 15 trees originally. Then there were 21 trees after some more + were planted. So there must have been 21 - 15 = 6. The final answer is 6 + - question: If there are 3 cars in the parking lot and 2 more cars arrive, how many + cars are in the parking lot? + target: There are originally 3 cars. 2 more cars arrive. 3 + 2 = 5. The final answer + is 5 + - question: Leah had 32 chocolates and her sister had 42. If they ate 35, how many + pieces do they have left in total? + target: Originally, Leah had 32 chocolates. Her sister had 42. So in total they + had 32 + 42 = 74. After eating 35, they had 74 - 35 = 39. The final answer is 39 + - question: Jason had 20 lollipops. He gave Denny some lollipops. Now Jason has 12 + lollipops. How many lollipops did Jason give to Denny? + target: Jason started with 20 lollipops. Then he had 12 after giving some to Denny. + So he gave Denny 20 - 12 = 8. The final answer is 8 + - question: Shawn has five toys. For Christmas, he got two toys each from his mom and + dad. How many toys does he have now? + target: Shawn started with 5 toys. If he got 2 toys each from his mom and dad, + then that is 4 more toys. 5 + 4 = 9. The final answer is 9 + - question: There were nine computers in the server room. Five more computers were + installed each day, from monday to thursday. How many computers are now in the + server room? + target: There were originally 9 computers. For each of 4 days, 5 more computers + were added. So 5 * 4 = 20 computers were added. 9 + 20 is 29. The final answer is + 29 + - question: Michael had 58 golf balls. On tuesday, he lost 23 golf balls. On wednesday, + he lost 2 more. How many golf balls did he have at the end of wednesday? + target: Michael started with 58 golf balls. After losing 23 on tuesday, he had + 58 - 23 = 35. After losing 2 more, he had 35 - 2 = 33 golf balls. The final answer + is 33 + - question: Olivia has $23. She bought five bagels for $3 each. How much money does + she have left? + target: Olivia had 23 dollars. 5 bagels for 3 dollars each will be 5 x 3 = 15 + dollars. So she has 23 - 15 dollars left. 23 - 15 is 8. The final answer is 8 +filter_list: +- filter: + - function: regex + group_select: -1 + regex_pattern: The final answer is ((-?[$0-9.,]{2,})|(-?[0-9]+)) + - function: take_first + name: strict-match +- filter: + - function: regex + group_select: -1 + regex_pattern: (-?[$0-9.,]{2,})|(-?[0-9]+) + - function: take_first + name: flexible-extract +generation_kwargs: + do_sample: false + until: + - '<|eot_id|>' + - '<|start_header_id|>user<|end_header_id|>' + - 'Q:' + - + - <|im_end|> +tag: +- chain_of_thought +metadata: + version: 1.0 +metric_list: +- aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: false + metric: exact_match + regexes_to_ignore: + - ',' + - \$ + - '(?s).*#### ' + - \.$ +num_fewshot: 8 +output_type: generate_until +repeats: 1 +task: asdiv_cot_llama +validation_split: validation +test_split: validation +should_decontaminate: true +doc_to_decontamination_query: "{{body}} {{question}}" +dataset_kwargs: + trust_remote_code: true -- GitLab From ebe7226ebfb8d11a9fb8d6b53eb65891f895c633 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 26 Aug 2024 00:55:24 +0500 Subject: [PATCH 087/194] chat template hotfix (#2250) * chat template hotfix * pre-commit --- lm_eval/evaluator.py | 8 +++++++- lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml | 2 +- 2 files changed, 8 insertions(+), 2 deletions(-) diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index 4ffed157..f42965ce 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -287,12 +287,18 @@ def simple_evaluate( if check_integrity: run_task_tests(task_list=tasks) + # hotfix: delete when chat_template fixed + try: + chat = lm.chat_template(apply_chat_template) + except: # noqa: E722 + chat = None + if evaluation_tracker is not None: evaluation_tracker.general_config_tracker.log_experiment_args( model_source=model, model_args=model_args, system_instruction=system_instruction, - chat_template=lm.chat_template(apply_chat_template), + chat_template=chat, fewshot_as_multiturn=fewshot_as_multiturn, ) diff --git a/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml b/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml index 84ae47e7..6d13175e 100644 --- a/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml +++ b/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml @@ -20,4 +20,4 @@ aggregate_metric_list: weight_by_size: true filter_list: custom-extract metadata: - version: 1.0 \ No newline at end of file + version: 1.0 -- GitLab From 40010ec1d8e8ac00e1e075cba01902bf09561edf Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Wed, 28 Aug 2024 11:43:47 -0400 Subject: [PATCH 088/194] [Draft] More descriptive `simple_evaluate()` LM TypeError (#2258) * Update evaluator.py * update error msg --- lm_eval/evaluator.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index f42965ce..9bd82888 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -208,7 +208,9 @@ def simple_evaluate( ) else: if not isinstance(model, lm_eval.api.model.LM): - raise TypeError + raise TypeError( + f"The value of `model` passed to simple_evaluate() was of type {type(model)}, but is required to be a subclass of lm_eval.api.model.LM . This may be because you are passing an initialized Hugging Face PreTrainedModel without having wrapped it in `lm_eval.models.huggingface.HFLM(pretrained=my_model)` first." + ) eval_logger.info("Using pre-initialized model") lm = model -- GitLab From 2de3688fd82b782a6c114662afc4ffa66edbd6a7 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Wed, 28 Aug 2024 13:17:30 -0400 Subject: [PATCH 089/194] update nltk version to require 3.9.1 (#2259) --- lm_eval/tasks/ifeval/ifeval.yaml | 2 +- lm_eval/tasks/ifeval/instructions_util.py | 18 ++++++++++++++++-- lm_eval/tasks/ifeval/utils.py | 4 ---- lm_eval/tasks/leaderboard/ifeval/ifeval.yaml | 2 +- .../leaderboard/ifeval/instructions_util.py | 18 ++++++++++++++++-- pyproject.toml | 2 +- 6 files changed, 35 insertions(+), 11 deletions(-) diff --git a/lm_eval/tasks/ifeval/ifeval.yaml b/lm_eval/tasks/ifeval/ifeval.yaml index 381e98a1..508a63a9 100644 --- a/lm_eval/tasks/ifeval/ifeval.yaml +++ b/lm_eval/tasks/ifeval/ifeval.yaml @@ -26,4 +26,4 @@ metric_list: aggregation: !function utils.agg_inst_level_acc higher_is_better: true metadata: - version: 3.0 + version: 4.0 diff --git a/lm_eval/tasks/ifeval/instructions_util.py b/lm_eval/tasks/ifeval/instructions_util.py index ccb531f9..9ca2d4de 100644 --- a/lm_eval/tasks/ifeval/instructions_util.py +++ b/lm_eval/tasks/ifeval/instructions_util.py @@ -20,14 +20,28 @@ import re import immutabledict import nltk +import pkg_resources +from packaging import version + + +# Downloading 'punkt' with nltk<3.9 has a remote code vuln. +# see https://github.com/EleutherAI/lm-evaluation-harness/issues/2210 +# and https://github.com/nltk/nltk/issues/3266 +# for more information. +NLTK_MIN_VERSION = "3.9.1" def download_nltk_resources(): """Download 'punkt' if not already installed""" + nltk_version = pkg_resources.get_distribution("nltk").version + assert ( + version.parse(nltk_version) >= version.parse(NLTK_MIN_VERSION) + ), f"`nltk` version {nltk_version} is not >= {NLTK_MIN_VERSION}. Please update `nltk` before proceeding--older versions are vulnerable to a remote code execution vulnerability." + try: - nltk.data.find("tokenizers/punkt") + nltk.data.find("tokenizers/punkt_tab") except LookupError: - nltk.download("punkt") + nltk.download("punkt_tab") download_nltk_resources() diff --git a/lm_eval/tasks/ifeval/utils.py b/lm_eval/tasks/ifeval/utils.py index 31dcb01e..c1e91e33 100644 --- a/lm_eval/tasks/ifeval/utils.py +++ b/lm_eval/tasks/ifeval/utils.py @@ -110,10 +110,6 @@ def test_instruction_following_loose( def process_results(doc, results): - eval_logger.warning( - "This task is meant for chat-finetuned models, and may not give meaningful results for models other than `openai` or `anthropic` if `doc_to_text` in its YAML is not wrapped in the appropriate chat template string. This warning will be removed when chat templating support is added natively to local models" - ) - inp = InputExample( key=doc["key"], instruction_id_list=doc["instruction_id_list"], diff --git a/lm_eval/tasks/leaderboard/ifeval/ifeval.yaml b/lm_eval/tasks/leaderboard/ifeval/ifeval.yaml index cab7498b..72c3ba02 100644 --- a/lm_eval/tasks/leaderboard/ifeval/ifeval.yaml +++ b/lm_eval/tasks/leaderboard/ifeval/ifeval.yaml @@ -26,6 +26,6 @@ metric_list: aggregation: !function utils.agg_inst_level_acc higher_is_better: true metadata: - version: 2.0 + version: 3.0 fewshot_config: sampler: first_n diff --git a/lm_eval/tasks/leaderboard/ifeval/instructions_util.py b/lm_eval/tasks/leaderboard/ifeval/instructions_util.py index ccb531f9..9ca2d4de 100644 --- a/lm_eval/tasks/leaderboard/ifeval/instructions_util.py +++ b/lm_eval/tasks/leaderboard/ifeval/instructions_util.py @@ -20,14 +20,28 @@ import re import immutabledict import nltk +import pkg_resources +from packaging import version + + +# Downloading 'punkt' with nltk<3.9 has a remote code vuln. +# see https://github.com/EleutherAI/lm-evaluation-harness/issues/2210 +# and https://github.com/nltk/nltk/issues/3266 +# for more information. +NLTK_MIN_VERSION = "3.9.1" def download_nltk_resources(): """Download 'punkt' if not already installed""" + nltk_version = pkg_resources.get_distribution("nltk").version + assert ( + version.parse(nltk_version) >= version.parse(NLTK_MIN_VERSION) + ), f"`nltk` version {nltk_version} is not >= {NLTK_MIN_VERSION}. Please update `nltk` before proceeding--older versions are vulnerable to a remote code execution vulnerability." + try: - nltk.data.find("tokenizers/punkt") + nltk.data.find("tokenizers/punkt_tab") except LookupError: - nltk.download("punkt") + nltk.download("punkt_tab") download_nltk_resources() diff --git a/pyproject.toml b/pyproject.toml index 5249819f..00319775 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -62,7 +62,7 @@ dev = ["pytest", "pytest-cov", "pytest-xdist", "pre-commit", "mypy"] deepsparse = ["deepsparse-nightly[llm]>=1.8.0.20240404"] gptq = ["auto-gptq[triton]>=0.6.0"] hf_transfer = ["hf_transfer"] -ifeval = ["langdetect", "immutabledict"] +ifeval = ["langdetect", "immutabledict", "nltk>=3.9.1"] neuronx = ["optimum[neuronx]"] mamba = ["mamba_ssm", "causal-conv1d==1.0.2"] math = ["sympy>=1.12", "antlr4-python3-runtime==4.11"] -- GitLab From 8138fd52437dcd8c76ac87bdc9d684840e794c42 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Wed, 28 Aug 2024 14:51:33 -0400 Subject: [PATCH 090/194] Fix `loglikelihood_rolling` caching ( #1821 ) (#2187) * fix revision type * allow for None-input loglikelihood reqs to be cached * handle no remaining cache items * pre-commit * change cache_hook.add_partial(loglikelihood_rolling...) convention --------- Co-authored-by: Baber Abbasi --- lm_eval/api/model.py | 7 +++++-- lm_eval/models/api_models.py | 5 ++++- lm_eval/models/huggingface.py | 11 ++++++++++- lm_eval/models/nemo_lm.py | 6 ++++++ lm_eval/models/neuralmagic.py | 3 +++ lm_eval/models/neuron_optimum.py | 9 +++++++-- lm_eval/models/vllm_causallms.py | 8 +++++++- 7 files changed, 42 insertions(+), 7 deletions(-) diff --git a/lm_eval/api/model.py b/lm_eval/api/model.py index a3602736..1cf8aedb 100644 --- a/lm_eval/api/model.py +++ b/lm_eval/api/model.py @@ -283,8 +283,11 @@ class CachingLM: eval_logger.info( f"Cached requests: {len(requests) - len(remaining_reqs)}, Requests remaining: {len(remaining_reqs)}" ) - # actually run the LM on the requests that do not have cached results - rem_res = getattr(self.lm, attr)(remaining_reqs) + if remaining_reqs: + # actually run the LM on the requests that do not have cached results + rem_res = getattr(self.lm, attr)(remaining_reqs) + else: + rem_res = [] # stick the new ones back into the list and also cache any of the new ones resptr = 0 diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index ff72925c..c6aa6608 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -510,7 +510,7 @@ class TemplateAPI(TemplateLM): ): if answer_ is not None: res.append(answer_) - # partial caching + # cache requests that aren't from a loglikelihood_rolling request if cache_key is not None: self.cache_hook.add_partial( "loglikelihood", cache_key, answer_ @@ -638,4 +638,7 @@ class TemplateAPI(TemplateLM): string_nll = sum(string_nll) loglikelihoods.append(string_nll) + + # cache this loglikelihood_rolling request + self.cache_hook.add_partial("loglikelihood_rolling", (string,), string_nll) return loglikelihoods diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 938bddde..80f65ca5 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -1018,6 +1018,9 @@ class HFLM(TemplateLM): string_nll = sum(string_nll) loglikelihoods.append(string_nll) + # cache this loglikelihood_rolling request + self.cache_hook.add_partial("loglikelihood_rolling", (string,), string_nll) + return loglikelihoods def _batch_scheduler(self, pos, n_reordered_requests): @@ -1246,7 +1249,13 @@ class HFLM(TemplateLM): res.append(answer) - self.cache_hook.add_partial("loglikelihood", request_str, answer) + if request_str is not None: + # special case: loglikelihood_rolling produces a number of loglikelihood requests + # all with cache key None. instead do add_partial on the per-example level + # in the loglikelihood_rolling() function for those. + self.cache_hook.add_partial( + "loglikelihood", request_str, answer + ) pbar.update(1) pbar.close() diff --git a/lm_eval/models/nemo_lm.py b/lm_eval/models/nemo_lm.py index cb1aca1e..b3ab5f52 100644 --- a/lm_eval/models/nemo_lm.py +++ b/lm_eval/models/nemo_lm.py @@ -386,6 +386,9 @@ class NeMoLM(LM): string_nll = sum(string_nll) loglikelihoods.append(string_nll) + + # cache this loglikelihood_rolling request + self.cache_hook.add_partial("loglikelihood_rolling", (string,), string_nll) return loglikelihoods def _loglikelihood_tokens(self, requests, disable_tqdm=False): @@ -468,6 +471,9 @@ class NeMoLM(LM): answer = (logprob, is_greedy) if cache_key is not None: + # special case: loglikelihood_rolling produces a number of loglikelihood requests + # all with cache key None. instead do add_partial on the per-example level + # in the loglikelihood_rolling() function for those. self.cache_hook.add_partial("loglikelihood", cache_key, answer) res.append(answer) diff --git a/lm_eval/models/neuralmagic.py b/lm_eval/models/neuralmagic.py index 7c16b06d..8cb61d6f 100644 --- a/lm_eval/models/neuralmagic.py +++ b/lm_eval/models/neuralmagic.py @@ -321,6 +321,9 @@ class DeepSparseLM(LM): res.append(answer) if cache_key is not None: + # special case: loglikelihood_rolling produces a number of loglikelihood requests + # all with cache key None. instead do add_partial on the per-example level + # in the loglikelihood_rolling() function for those. self.cache_hook.add_partial("loglikelihood", cache_key, answer) return re_ord.get_original(res) diff --git a/lm_eval/models/neuron_optimum.py b/lm_eval/models/neuron_optimum.py index 38307d27..f3ee42ef 100644 --- a/lm_eval/models/neuron_optimum.py +++ b/lm_eval/models/neuron_optimum.py @@ -502,7 +502,8 @@ class NEURON_HF(TemplateLM): string_nll = sum(string_nll) loglikelihoods.append(string_nll) - + # cache this loglikelihood_rolling request + self.cache_hook.add_partial("loglikelihood_rolling", (string,), string_nll) return loglikelihoods def _loglikelihood_tokens( @@ -620,7 +621,11 @@ class NEURON_HF(TemplateLM): res.append(answer) - self.cache_hook.add_partial("loglikelihood", cache_key, answer) + if cache_key is not None: + # special case: loglikelihood_rolling produces a number of loglikelihood requests + # all with cache key None. instead do add_partial on the per-example level + # in the loglikelihood_rolling() function for those. + self.cache_hook.add_partial("loglikelihood", cache_key, answer) return re_ord.get_original(res) diff --git a/lm_eval/models/vllm_causallms.py b/lm_eval/models/vllm_causallms.py index 1a1067cc..c79ae548 100644 --- a/lm_eval/models/vllm_causallms.py +++ b/lm_eval/models/vllm_causallms.py @@ -307,6 +307,10 @@ class VLLM(TemplateLM): string_nll = sum(string_nll) loglikelihoods.append(string_nll) + + # cache this loglikelihood_rolling request + self.cache_hook.add_partial("loglikelihood_rolling", (string,), string_nll) + return loglikelihoods def generate_until( @@ -453,8 +457,10 @@ class VLLM(TemplateLM): res.append(answer) - # partial caching if cache_key is not None: + # special case: loglikelihood_rolling produces a number of loglikelihood requests + # all with cache key None. instead do add_partial on the per-example level + # in the loglikelihood_rolling() function for those. self.cache_hook.add_partial("loglikelihood", cache_key, answer) pbar.update(1) pbar.close() -- GitLab From b31f92e8bec4c40e5c75f9b4ffb9c42cb10a725f Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Fri, 30 Aug 2024 06:25:06 +0500 Subject: [PATCH 091/194] API: fix maxlen; vllm: prefix_token_id bug (#2262) * max_length - 1 (generation always >= 1) * vllm: fix rolling prefix_token * nit: add comment * fixup! max_length should be handled for logliklihoods --- lm_eval/models/api_models.py | 9 ++++++--- lm_eval/models/vllm_causallms.py | 3 ++- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index c6aa6608..25223e90 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -104,6 +104,7 @@ class TemplateAPI(TemplateLM): self._truncate = truncate self._max_gen_toks = int(max_gen_toks) self._seed = int(seed) + eval_logger.info(f"Using max length {max_length}") self.max_length = max_length if int(num_concurrent) <= 1: eval_logger.info( @@ -417,9 +418,10 @@ class TemplateAPI(TemplateLM): cache_keys = [] for chunk in chunks: for cache_key, context_enc, continuation_enc in chunk: - inp = (context_enc + continuation_enc)[-(self.max_length) :] + # max_length - 1 as we always have 1 token for generation + inp = (context_enc + continuation_enc)[-(self.max_length - 1) :] ctxlen = len(context_enc) - max( - 0, len(context_enc) + len(continuation_enc) - (self.max_length) + 0, len(context_enc) + len(continuation_enc) - (self.max_length - 1) ) inputs.append(inp) @@ -619,7 +621,8 @@ class TemplateAPI(TemplateLM): utils.get_rolling_token_windows( token_list=self.tok_encode(string), prefix_token=self.prefix_token_id, - max_seq_len=self.max_length, + # max_seq_len - (1 for context) + max_seq_len=self.max_length - 1, context_len=1, ), ) diff --git a/lm_eval/models/vllm_causallms.py b/lm_eval/models/vllm_causallms.py index c79ae548..d6a8dc18 100644 --- a/lm_eval/models/vllm_causallms.py +++ b/lm_eval/models/vllm_causallms.py @@ -289,7 +289,8 @@ class VLLM(TemplateLM): make_disjoint_window, get_rolling_token_windows( token_list=self.tok_encode(string), - prefix_token=self.eot_token_id, + prefix_token=self.prefix_token_id, + # max_seq_len - (1 for context) max_seq_len=self.max_length - 1, context_len=1, ), -- GitLab From 928e8bb6f50d1e93ef5d0bcaa81f8c5fd9a6f4d8 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Fri, 30 Aug 2024 06:40:41 +0500 Subject: [PATCH 092/194] hotfix #2262 (#2264) * max_length - 1 (generation always >= 1) * vllm: fix rolling prefix_token * nit: add comment * fixup! max_length should be handled for logliklihoods * Revert "fixup! max_length should be handled for logliklihoods" This reverts commit 432d1a3b754c117c3a54ea2fe792ab3a1bd09ed3. --- lm_eval/models/api_models.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index 25223e90..9d217055 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -104,8 +104,9 @@ class TemplateAPI(TemplateLM): self._truncate = truncate self._max_gen_toks = int(max_gen_toks) self._seed = int(seed) - eval_logger.info(f"Using max length {max_length}") - self.max_length = max_length + # max_length - 1 as we always have 1 token for generation + eval_logger.info(f"Using max length {max_length} - 1") + self.max_length = max_length - 1 if int(num_concurrent) <= 1: eval_logger.info( "Concurrent requests are disabled. To enable concurrent requests, set `num_concurrent` > 1." @@ -419,9 +420,9 @@ class TemplateAPI(TemplateLM): for chunk in chunks: for cache_key, context_enc, continuation_enc in chunk: # max_length - 1 as we always have 1 token for generation - inp = (context_enc + continuation_enc)[-(self.max_length - 1) :] + inp = (context_enc + continuation_enc)[-(self.max_length) :] ctxlen = len(context_enc) - max( - 0, len(context_enc) + len(continuation_enc) - (self.max_length - 1) + 0, len(context_enc) + len(continuation_enc) - (self.max_length) ) inputs.append(inp) -- GitLab From 7a1614eb90d29b2983ffa027a7974b7ef53fba19 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Wed, 4 Sep 2024 19:09:57 +0500 Subject: [PATCH 093/194] Chat Template fix (cont. #2235) (#2269) * default chat template method fix * move chat_template to TemplateLM * remove hotfix * handle openai `chat_template` * Update lm_eval/api/model.py Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * add 'max_tokens' to gen_kwargs * pre-commit --------- Co-authored-by: KonradSzafer Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- lm_eval/api/model.py | 114 ++++++++++++++++++++++++--- lm_eval/evaluator.py | 8 +- lm_eval/models/api_models.py | 8 -- lm_eval/models/huggingface.py | 92 --------------------- lm_eval/models/openai_completions.py | 13 ++- lm_eval/models/vllm_causallms.py | 6 -- 6 files changed, 117 insertions(+), 124 deletions(-) diff --git a/lm_eval/api/model.py b/lm_eval/api/model.py index 1cf8aedb..765fc012 100644 --- a/lm_eval/api/model.py +++ b/lm_eval/api/model.py @@ -3,7 +3,7 @@ import hashlib import json import logging import os -from typing import Dict, List, Optional, Tuple, Type, TypeVar +from typing import Dict, List, Optional, Tuple, Type, TypeVar, Union import transformers from sqlitedict import SqliteDict @@ -192,15 +192,13 @@ class LM(abc.ABC): "To use this model with chat templates, please implement the 'tokenizer_name' property." ) - @property - def chat_template(self) -> str: - """Must be defined for LM subclasses that implement Chat Templating. - Should return the structure of the chat template applied to user/assistant messages. - This is used only to save in the experiment results for reproducibility. + def chat_template(self, chat_template: Union[bool, str] = False) -> Optional[str]: + """Returns the chat template structure for user/assistant messages if a template is provided. + This method is intended to be overridden in a subclass to define a specific chat template format. + For models that do not support chat templates, this method returns None by default. """ - raise NotImplementedError( - "To use this model with chat templates, please implement the 'chat_template' property." - ) + + return "" def set_cache_hook(self, cache_hook) -> None: self.cache_hook = cache_hook @@ -316,6 +314,8 @@ class TemplateLM(LM): and boilerplate often included in other LM subclasses. """ + tokenizer = None + @property @abc.abstractmethod def eot_token_id(self): @@ -386,3 +386,99 @@ class TemplateLM(LM): @abc.abstractmethod def generate_until(self, requests, disable_tqdm: bool = False) -> List[str]: pass + + def chat_template(self, chat_template: Union[bool, str] = False) -> Optional[str]: + """ + Set and get the appropriate chat template for the model. + This method sets the tokenizer's chat_template and returns the template string for reproducibility. + + The template selection logic is adapted from the Transformers library's `apply_chat_template` + method in the Tokenizer class. The original implementation can be found at: + https://github.com/huggingface/transformers/blob/fc35907f95459d7a6c5281dfadd680b6f7b620e3/src/transformers/tokenization_utils_base.py#L1687 + + This method ensures that the right template is chosen based on the following: + 0. If the model has no 'tokenizer' attribute: assumes that there is only a single possible chat template, handled on the model provider side internally. Returns the empty string. + 1. If the model's tokenizer has multiple templates: + a. Use the specified template if it exists in the dictionary. + b. Use the default template from the list if no specific template is provided. + c. Raise an error if no default template exists and no specific template is provided. + 2. If the model's tokenizer has a single template or no template: + a. Use the tokenizer's chat template if available. + b. Fall back to the default chat template if no tokenizer chat template exists. + + Args: + chat_template (Union[bool, str]): Specifies the chat template to use. + - If False or None, no template is applied. + - If True, the default or only available template is used. + - If a string, the template with the matching name is used. + + Returns: + Optional[str]: The selected chat template, or None if no template is applied. + """ + if self.tokenizer is None: + return "" + + if chat_template is False or chat_template is None: + eval_logger.warning( + "model.chat_template was called with the chat_template set to False or None. " + "Therefore no chat template will be applied. Make sure this is an intended behavior." + ) + return None + + # Convert boolean chat_template to None to ensure compatibility with the adapted logic + if isinstance(chat_template, bool): + chat_template = None + using_default_template = False + + # First, handle the cases when the model has a dict of multiple templates + template = self.tokenizer.chat_template or self.tokenizer.default_chat_template + + if isinstance(template, dict): + using_default_dict = self.tokenizer.chat_template is None + + if chat_template is not None: + if chat_template in template: + selected_template = template[chat_template] + if using_default_dict: + using_default_template = True + else: + raise ValueError( + f"The specified chat template '{chat_template}' is not available. " + f"Available template names are {sorted(template.keys())}." + ) + else: + # If user didn't pass a chat template, use the default template from the dict + if "default" in template: + selected_template = template["default"] + using_default_template = True + else: + raise ValueError( + "This model has multiple chat templates with no default specified! Please either pass a chat " + "template or the name of the template you wish to use to the `chat_template` argument. Available " + f"template names are {sorted(template.keys())}." + ) + + # Cases when the model has a single template or no template + else: + # priority: `chat_template` argument > `tokenizer.chat_template` > `tokenizer.default_chat_template + if isinstance(chat_template, str): + eval_logger.warning( + "Chat template name provided, but the tokenizer's chat template is not a dictionary. " + "Using the tokenizer's chat template or the default template instead." + ) + if self.tokenizer.chat_template is not None: + selected_template = self.tokenizer.chat_template + else: + selected_template = self.tokenizer.default_chat_template + using_default_template = True + + if using_default_template: + eval_logger.warning( + "No chat template is set for this tokenizer, falling back to a default class-level template. This is " + "very error-prone, because models are often trained with templates different from the class default! " + "Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which " + "point any code depending on them will stop working. We recommend setting a valid chat template before " + "then to ensure that this model continues working without issues." + ) + + return selected_template diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index 9bd82888..52a8d00d 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -289,18 +289,12 @@ def simple_evaluate( if check_integrity: run_task_tests(task_list=tasks) - # hotfix: delete when chat_template fixed - try: - chat = lm.chat_template(apply_chat_template) - except: # noqa: E722 - chat = None - if evaluation_tracker is not None: evaluation_tracker.general_config_tracker.log_experiment_args( model_source=model, model_args=model_args, system_instruction=system_instruction, - chat_template=chat, + chat_template=lm.chat_template(apply_chat_template), fewshot_as_multiturn=fewshot_as_multiturn, ) diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index 9d217055..70988939 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -225,14 +225,6 @@ class TemplateAPI(TemplateLM): """Override this property to return the headers for the API request.""" return {"Authorization": f"Bearer {self.api_key}"} - @property - def chat_template(self) -> str: - """Must be defined for LM subclasses that implement Chat Templating. - Should return the structure of the chat template applied to user/assistant messages. - Only used for logging and reproducibility. - """ - return "" - @property def tokenizer_name(self) -> str: """Must be defined for LM subclasses which implement Chat Templating. diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 80f65ca5..01a8cf67 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -438,98 +438,6 @@ class HFLM(TemplateLM): def tokenizer_name(self) -> str: return self.tokenizer.name_or_path.replace("/", "__") - def chat_template(self, chat_template: Union[bool, str] = False) -> Optional[str]: - """ - Get the appropriate chat template for the model based on configuration and input. - This method determines, and returns the correct chat template, ensuring reproducibility. - - The template selection logic is adapted from the Transformers library's `apply_chat_template` - method in the Tokenizer class. The original implementation can be found at: - https://github.com/huggingface/transformers/blob/fc35907f95459d7a6c5281dfadd680b6f7b620e3/src/transformers/tokenization_utils_base.py#L1687 - - This method ensures that the right template is chosen based on the following: - 1. If the model's tokenizer has multiple templates: - a. Use the specified template if it exists in the dictionary. - b. Use the default template from the list if no specific template is provided. - c. Raise an error if no default template exists and no specific template is provided. - 2. If the model's tokenizer has a single template or no template: - a. Use the tokenizer's chat template if available. - b. Fall back to the default chat template if no tokenizer chat template exists. - - Args: - chat_template (Union[bool, str]): Specifies the chat template to use. - - If False or None, no template is applied. - - If True, the default or only available template is used. - - If a string, the template with the matching name is used. - - Returns: - Optional[str]: The selected chat template, or None if no template is applied. - """ - if chat_template is False or chat_template is None: - eval_logger.warning( - "model.chat_template was called with the chat_template set to False or None. " - "Therefore no chat template will be applied. Make sure this is an intended behavior." - ) - return None - - # Convert boolean chat_template to None to ensure compatibility with the adapted logic - if isinstance(chat_template, bool): - chat_template = None - using_default_template = False - - # First, handle the cases when the model has a dict of multiple templates - template = self.tokenizer.chat_template or self.tokenizer.default_chat_template - - if isinstance(template, dict): - using_default_dict = self.tokenizer.chat_template is None - - if chat_template is not None: - if chat_template in template: - selected_template = template[chat_template] - if using_default_dict: - using_default_template = True - else: - raise ValueError( - f"The specified chat template '{chat_template}' is not available. " - f"Available template names are {sorted(template.keys())}." - ) - else: - # If user didn't pass a chat template, use the default template from the dict - if "default" in template: - selected_template = template["default"] - using_default_template = True - else: - raise ValueError( - "This model has multiple chat templates with no default specified! Please either pass a chat " - "template or the name of the template you wish to use to the `chat_template` argument. Available " - f"template names are {sorted(template.keys())}." - ) - - # Cases when the model has a single template or no template - else: - # priority: `chat_template` argument > `tokenizer.chat_template` > `tokenizer.default_chat_template - if isinstance(chat_template, str): - eval_logger.warning( - "Chat template name provided, but the tokenizer's chat template is not a dictionary. " - "Using the tokenizer's chat template or the default template instead." - ) - if self.tokenizer.chat_template is not None: - selected_template = self.tokenizer.chat_template - else: - selected_template = self.tokenizer.default_chat_template - using_default_template = True - - if using_default_template: - eval_logger.warning( - "No chat template is set for this tokenizer, falling back to a default class-level template. This is " - "very error-prone, because models are often trained with templates different from the class default! " - "Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which " - "point any code depending on them will stop working. We recommend setting a valid chat template before " - "then to ensure that this model continues working without issues." - ) - - return selected_template - def _get_backend( self, config: Union[transformers.PretrainedConfig, transformers.AutoConfig], diff --git a/lm_eval/models/openai_completions.py b/lm_eval/models/openai_completions.py index 26dc93d6..4bf2c42b 100644 --- a/lm_eval/models/openai_completions.py +++ b/lm_eval/models/openai_completions.py @@ -29,7 +29,10 @@ class LocalCompletionsAPI(TemplateAPI): ) -> dict: if generate: gen_kwargs.pop("do_sample", False) - max_tokens = gen_kwargs.pop("max_gen_toks", self._max_gen_toks) + if "max_tokens" in gen_kwargs: + max_tokens = gen_kwargs.pop("max_tokens") + else: + max_tokens = gen_kwargs.pop("max_gen_toks", self._max_gen_toks) temperature = gen_kwargs.pop("temperature", 0) stop = gen_kwargs.pop("until", ["<|endoftext|>"]) return { @@ -124,7 +127,10 @@ class LocalChatCompletion(LocalCompletionsAPI): **kwargs, ) -> dict: gen_kwargs.pop("do_sample", False) - max_tokens = gen_kwargs.pop("max_gen_toks", self._max_gen_toks) + if "max_tokens" in gen_kwargs: + max_tokens = gen_kwargs.pop("max_tokens") + else: + max_tokens = gen_kwargs.pop("max_gen_toks", self._max_gen_toks) temperature = gen_kwargs.pop("temperature", 0) stop = gen_kwargs.pop("until", ["<|endoftext|>"]) if not isinstance(stop, (list, tuple)): @@ -194,6 +200,9 @@ class OpenAICompletionsAPI(LocalCompletionsAPI): ), "Loglikelihood is not supported for gpt-3.5-turbo" return super().loglikelihood(requests, **kwargs) + def chat_template(self, chat_template: Union[bool, str] = False) -> Optional[str]: + return "" + @register_model("openai-chat-completions") class OpenAIChatCompletion(LocalChatCompletion): diff --git a/lm_eval/models/vllm_causallms.py b/lm_eval/models/vllm_causallms.py index d6a8dc18..168f490a 100644 --- a/lm_eval/models/vllm_causallms.py +++ b/lm_eval/models/vllm_causallms.py @@ -187,12 +187,6 @@ class VLLM(TemplateLM): chat_history, tokenize=False, add_generation_prompt=True ) - @property - def chat_template(self) -> str: - if self.tokenizer.chat_template is not None: - return self.tokenizer.chat_template - return self.tokenizer.default_chat_template - @property def tokenizer_name(self) -> str: return self.tokenizer.name_or_path.replace("/", "__") -- GitLab From 543617fef9ba885e87f8db8930fbbff1d4e2ca49 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Thu, 5 Sep 2024 11:01:48 -0400 Subject: [PATCH 094/194] Bump version to v0.4.4 ; Fixes to TMMLUplus (#2280) --- lm_eval/__main__.py | 7 ------- lm_eval/tasks/__init__.py | 10 ++++++---- lm_eval/tasks/tmmluplus/default/_tmmluplus.yaml | 13 +++++++++++++ .../tasks/tmmluplus/default/_tmmluplus_STEM.yaml | 10 ++++++++++ .../tmmluplus/default/_tmmluplus_humanities.yaml | 10 ++++++++++ .../tasks/tmmluplus/default/_tmmluplus_other.yaml | 10 ++++++++++ .../default/_tmmluplus_social_sciences.yaml | 10 ++++++++++ ...fault_template_yaml => _tmmluplus_template_yaml} | 2 +- lm_eval/tasks/tmmluplus/default/tmmluplus.yaml | 6 ------ .../tmmluplus/default/tmmluplus_accounting.yaml | 5 ++--- .../default/tmmluplus_administrative_law.yaml | 5 ++--- .../default/tmmluplus_advance_chemistry.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_agriculture.yaml | 5 ++--- .../default/tmmluplus_anti_money_laundering.yaml | 5 ++--- .../tasks/tmmluplus/default/tmmluplus_auditing.yaml | 5 ++--- .../default/tmmluplus_basic_medical_science.yaml | 5 ++--- .../default/tmmluplus_business_management.yaml | 5 ++--- .../tmmluplus_chinese_language_and_literature.yaml | 5 ++--- .../default/tmmluplus_clinical_psychology.yaml | 5 ++--- .../default/tmmluplus_computer_science.yaml | 5 ++--- .../default/tmmluplus_culinary_skills.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_dentistry.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_economics.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_education.yaml | 5 ++--- .../tmmluplus_education_(profession_level).yaml | 5 ++--- .../default/tmmluplus_educational_psychology.yaml | 5 ++--- .../default/tmmluplus_engineering_math.yaml | 5 ++--- .../default/tmmluplus_finance_banking.yaml | 5 ++--- .../default/tmmluplus_financial_analysis.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_fire_science.yaml | 5 ++--- .../tmmluplus_general_principles_of_law.yaml | 5 ++--- .../default/tmmluplus_geography_of_taiwan.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_human_behavior.yaml | 5 ++--- .../default/tmmluplus_insurance_studies.yaml | 5 ++--- .../default/tmmluplus_introduction_to_law.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_jce_humanities.yaml | 5 ++--- .../default/tmmluplus_junior_chemistry.yaml | 5 ++--- .../default/tmmluplus_junior_chinese_exam.yaml | 5 ++--- .../default/tmmluplus_junior_math_exam.yaml | 5 ++--- .../default/tmmluplus_junior_science_exam.yaml | 5 ++--- .../default/tmmluplus_junior_social_studies.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_linear_algebra.yaml | 5 ++--- .../default/tmmluplus_logic_reasoning.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_macroeconomics.yaml | 5 ++--- .../default/tmmluplus_management_accounting.yaml | 5 ++--- .../default/tmmluplus_marketing_management.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_mechanical.yaml | 5 ++--- .../tasks/tmmluplus/default/tmmluplus_music.yaml | 5 ++--- .../default/tmmluplus_national_protection.yaml | 5 ++--- .../default/tmmluplus_nautical_science.yaml | 5 ++--- ...ational_therapy_for_psychological_disorders.yaml | 5 ++--- .../tmmluplus_official_document_management.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_optometry.yaml | 5 ++--- .../default/tmmluplus_organic_chemistry.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_pharmacology.yaml | 5 ++--- .../tasks/tmmluplus/default/tmmluplus_pharmacy.yaml | 5 ++--- .../default/tmmluplus_physical_education.yaml | 5 ++--- .../tasks/tmmluplus/default/tmmluplus_physics.yaml | 5 ++--- .../default/tmmluplus_politic_science.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_real_estate.yaml | 5 ++--- .../default/tmmluplus_secondary_physics.yaml | 5 ++--- .../tmmluplus_statistics_and_machine_learning.yaml | 5 ++--- .../default/tmmluplus_taiwanese_hokkien.yaml | 5 ++--- .../tasks/tmmluplus/default/tmmluplus_taxation.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_technical.yaml | 5 ++--- .../tmmluplus_three_principles_of_people.yaml | 5 ++--- .../tasks/tmmluplus/default/tmmluplus_trade.yaml | 5 ++--- ...ditional_chinese_medicine_clinical_medicine.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_trust_practice.yaml | 5 ++--- .../tasks/tmmluplus/default/tmmluplus_ttqav2.yaml | 5 ++--- .../default/tmmluplus_tve_chinese_language.yaml | 5 ++--- .../tmmluplus/default/tmmluplus_tve_design.yaml | 5 ++--- .../default/tmmluplus_tve_mathematics.yaml | 5 ++--- .../default/tmmluplus_tve_natural_sciences.yaml | 5 ++--- .../default/tmmluplus_veterinary_pathology.yaml | 5 ++--- .../default/tmmluplus_veterinary_pharmacology.yaml | 5 ++--- pyproject.toml | 2 +- 77 files changed, 195 insertions(+), 220 deletions(-) create mode 100644 lm_eval/tasks/tmmluplus/default/_tmmluplus.yaml create mode 100644 lm_eval/tasks/tmmluplus/default/_tmmluplus_STEM.yaml create mode 100644 lm_eval/tasks/tmmluplus/default/_tmmluplus_humanities.yaml create mode 100644 lm_eval/tasks/tmmluplus/default/_tmmluplus_other.yaml create mode 100644 lm_eval/tasks/tmmluplus/default/_tmmluplus_social_sciences.yaml rename lm_eval/tasks/tmmluplus/default/{_default_template_yaml => _tmmluplus_template_yaml} (97%) delete mode 100644 lm_eval/tasks/tmmluplus/default/tmmluplus.yaml diff --git a/lm_eval/__main__.py b/lm_eval/__main__.py index f10c9b85..ab687819 100644 --- a/lm_eval/__main__.py +++ b/lm_eval/__main__.py @@ -299,13 +299,6 @@ def cli_evaluate(args: Union[argparse.Namespace, None] = None) -> None: "When `fewshot_as_multiturn` is selected, `apply_chat_template` must be set (either to `True` or to the chosen template name)." ) - if ( - args.num_fewshot is None or args.num_fewshot == 0 - ) and args.fewshot_as_multiturn: - raise ValueError( - "If fewshot_as_multiturn is set, num_fewshot must be greater than 0." - ) - if args.include_path is not None: eval_logger.info(f"Including path: {args.include_path}") task_manager = TaskManager(args.verbosity, include_path=args.include_path) diff --git a/lm_eval/tasks/__init__.py b/lm_eval/tasks/__init__.py index 4cae6852..7eeec8bb 100644 --- a/lm_eval/tasks/__init__.py +++ b/lm_eval/tasks/__init__.py @@ -489,10 +489,12 @@ class TaskManager: if attr in config: if attr == "group" and print_info: self.logger.info( - "`group` and `group_alias` keys in tasks' configs will no longer be used in the next release of lm-eval. " - "`tag` will be used to allow to call a collection of tasks just like `group`. " - "`group` will be removed in order to not cause confusion with the new ConfigurableGroup " - "which will be the official way to create groups with addition of group-wide configurations." + "`group` and `group_alias` keys in TaskConfigs are deprecated and will be removed in v0.4.5 of lm_eval. " + "The new `tag` field will be used to allow for a shortcut to a group of tasks one does not wish to aggregate metrics across. " + "`group`s which aggregate across subtasks must be only defined in a separate group config file, " + "which will be the official way to create groups that support cross-task aggregation as in `mmlu`. " + "Please see the v0.4.4 patch notes and our documentation: https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/new_task_guide.md#advanced-group-configs " + "for more information." ) print_info = False # attr = "tag" diff --git a/lm_eval/tasks/tmmluplus/default/_tmmluplus.yaml b/lm_eval/tasks/tmmluplus/default/_tmmluplus.yaml new file mode 100644 index 00000000..45208d4d --- /dev/null +++ b/lm_eval/tasks/tmmluplus/default/_tmmluplus.yaml @@ -0,0 +1,13 @@ +group: tmmluplus +task: +- tmmluplus_other +- tmmluplus_social_sciences +- tmmluplus_humanities +- tmmluplus_STEM +aggregate_metric_list: + - metric: acc + weight_by_size: True + - metric: acc_norm + weight_by_size: True +metadata: + version: 2.0 diff --git a/lm_eval/tasks/tmmluplus/default/_tmmluplus_STEM.yaml b/lm_eval/tasks/tmmluplus/default/_tmmluplus_STEM.yaml new file mode 100644 index 00000000..47f81f50 --- /dev/null +++ b/lm_eval/tasks/tmmluplus/default/_tmmluplus_STEM.yaml @@ -0,0 +1,10 @@ +group: tmmluplus_STEM +task: +- tmmluplus_STEM_tasks +aggregate_metric_list: + - metric: acc + weight_by_size: True + - metric: acc_norm + weight_by_size: True +metadata: + version: 2.0 diff --git a/lm_eval/tasks/tmmluplus/default/_tmmluplus_humanities.yaml b/lm_eval/tasks/tmmluplus/default/_tmmluplus_humanities.yaml new file mode 100644 index 00000000..1cd42f88 --- /dev/null +++ b/lm_eval/tasks/tmmluplus/default/_tmmluplus_humanities.yaml @@ -0,0 +1,10 @@ +group: tmmluplus_humanities +task: +- tmmluplus_humanities_tasks +aggregate_metric_list: + - metric: acc + weight_by_size: True + - metric: acc_norm + weight_by_size: True +metadata: + version: 2.0 diff --git a/lm_eval/tasks/tmmluplus/default/_tmmluplus_other.yaml b/lm_eval/tasks/tmmluplus/default/_tmmluplus_other.yaml new file mode 100644 index 00000000..2b679ef4 --- /dev/null +++ b/lm_eval/tasks/tmmluplus/default/_tmmluplus_other.yaml @@ -0,0 +1,10 @@ +group: tmmluplus_other +task: +- tmmluplus_other_tasks +aggregate_metric_list: + - metric: acc + weight_by_size: True + - metric: acc_norm + weight_by_size: True +metadata: + version: 2.0 diff --git a/lm_eval/tasks/tmmluplus/default/_tmmluplus_social_sciences.yaml b/lm_eval/tasks/tmmluplus/default/_tmmluplus_social_sciences.yaml new file mode 100644 index 00000000..a219550b --- /dev/null +++ b/lm_eval/tasks/tmmluplus/default/_tmmluplus_social_sciences.yaml @@ -0,0 +1,10 @@ +group: tmmluplus_social_sciences +task: +- tmmluplus_social_sciences_tasks +aggregate_metric_list: + - metric: acc + weight_by_size: True + - metric: acc_norm + weight_by_size: True +metadata: + version: 2.0 diff --git a/lm_eval/tasks/tmmluplus/default/_default_template_yaml b/lm_eval/tasks/tmmluplus/default/_tmmluplus_template_yaml similarity index 97% rename from lm_eval/tasks/tmmluplus/default/_default_template_yaml rename to lm_eval/tasks/tmmluplus/default/_tmmluplus_template_yaml index 98d3c133..c03cfb1b 100644 --- a/lm_eval/tasks/tmmluplus/default/_default_template_yaml +++ b/lm_eval/tasks/tmmluplus/default/_tmmluplus_template_yaml @@ -16,4 +16,4 @@ metric_list: aggregation: mean higher_is_better: true metadata: - version: 1.0 + version: 2.0 diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus.yaml deleted file mode 100644 index 105cf98a..00000000 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus.yaml +++ /dev/null @@ -1,6 +0,0 @@ -group: tmmluplus -task: -- tmmluplus_other -- tmmluplus_social_sciences -- tmmluplus_humanities -- tmmluplus_STEM diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_accounting.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_accounting.yaml index 9e27c919..c6ee4a50 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_accounting.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_accounting.yaml @@ -1,7 +1,6 @@ "dataset_name": "accounting" "description": "以下為會計學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_accounting" "task_alias": "accounting" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_administrative_law.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_administrative_law.yaml index 454efec6..36957836 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_administrative_law.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_administrative_law.yaml @@ -1,7 +1,6 @@ "dataset_name": "administrative_law" "description": "以下為行政法的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_humanities" -"group_alias": "humanities" -"include": "_default_template_yaml" +"tag": "tmmluplus_humanities_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_administrative_law" "task_alias": "administrative law" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_advance_chemistry.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_advance_chemistry.yaml index d5baa64b..549b3cc8 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_advance_chemistry.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_advance_chemistry.yaml @@ -1,7 +1,6 @@ "dataset_name": "advance_chemistry" "description": "以下為化學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_advance_chemistry" "task_alias": "advance chemistry" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_agriculture.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_agriculture.yaml index 340369c8..8ef29126 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_agriculture.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_agriculture.yaml @@ -1,7 +1,6 @@ "dataset_name": "agriculture" "description": "以下為農業的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_agriculture" "task_alias": "agriculture" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_anti_money_laundering.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_anti_money_laundering.yaml index 95bb0e47..7f8d873f 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_anti_money_laundering.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_anti_money_laundering.yaml @@ -1,7 +1,6 @@ "dataset_name": "anti_money_laundering" "description": "以下為洗錢防制的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_humanities" -"group_alias": "humanities" -"include": "_default_template_yaml" +"tag": "tmmluplus_humanities_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_anti_money_laundering" "task_alias": "anti money laundering" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_auditing.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_auditing.yaml index a8168029..e5c598b7 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_auditing.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_auditing.yaml @@ -1,7 +1,6 @@ "dataset_name": "auditing" "description": "以下為審計學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_auditing" "task_alias": "auditing" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_basic_medical_science.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_basic_medical_science.yaml index d329b78a..6c6db6aa 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_basic_medical_science.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_basic_medical_science.yaml @@ -1,7 +1,6 @@ "dataset_name": "basic_medical_science" "description": "以下為基礎醫學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_basic_medical_science" "task_alias": "basic medical science" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_business_management.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_business_management.yaml index 9cacf048..e8377ee3 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_business_management.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_business_management.yaml @@ -1,7 +1,6 @@ "dataset_name": "business_management" "description": "以下為企業管理的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_business_management" "task_alias": "business management" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_chinese_language_and_literature.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_chinese_language_and_literature.yaml index 73eba768..53a8d652 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_chinese_language_and_literature.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_chinese_language_and_literature.yaml @@ -1,7 +1,6 @@ "dataset_name": "chinese_language_and_literature" "description": "以下為國文的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_chinese_language_and_literature" "task_alias": "chinese language and literature" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_clinical_psychology.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_clinical_psychology.yaml index f8194feb..7753e2a0 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_clinical_psychology.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_clinical_psychology.yaml @@ -1,7 +1,6 @@ "dataset_name": "clinical_psychology" "description": "以下為臨床心理學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_clinical_psychology" "task_alias": "clinical psychology" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_computer_science.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_computer_science.yaml index c55f6a4a..00949ddc 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_computer_science.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_computer_science.yaml @@ -1,7 +1,6 @@ "dataset_name": "computer_science" "description": "以下為資訊工程的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_computer_science" "task_alias": "computer science" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_culinary_skills.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_culinary_skills.yaml index 457eac1d..92f11098 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_culinary_skills.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_culinary_skills.yaml @@ -1,7 +1,6 @@ "dataset_name": "culinary_skills" "description": "以下為餐旅的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_culinary_skills" "task_alias": "culinary skills" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_dentistry.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_dentistry.yaml index d6295240..836a9c12 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_dentistry.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_dentistry.yaml @@ -1,7 +1,6 @@ "dataset_name": "dentistry" "description": "以下為牙醫學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_dentistry" "task_alias": "dentistry" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_economics.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_economics.yaml index 2ed100fb..8665c62f 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_economics.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_economics.yaml @@ -1,7 +1,6 @@ "dataset_name": "economics" "description": "以下為經濟學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_economics" "task_alias": "economics" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_education.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_education.yaml index cc601810..46f230cd 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_education.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_education.yaml @@ -1,7 +1,6 @@ "dataset_name": "education" "description": "以下為教育常識的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_education" "task_alias": "education" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_education_(profession_level).yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_education_(profession_level).yaml index f986517b..281654c5 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_education_(profession_level).yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_education_(profession_level).yaml @@ -1,7 +1,6 @@ "dataset_name": "education_(profession_level)" "description": "以下為教育專業的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_education_(profession_level)" "task_alias": "education (profession level)" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_educational_psychology.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_educational_psychology.yaml index bed8f2d4..be1c2c8a 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_educational_psychology.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_educational_psychology.yaml @@ -1,7 +1,6 @@ "dataset_name": "educational_psychology" "description": "以下為教育心理的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_educational_psychology" "task_alias": "educational psychology" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_engineering_math.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_engineering_math.yaml index cf681cd5..a8a35e1c 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_engineering_math.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_engineering_math.yaml @@ -1,7 +1,6 @@ "dataset_name": "engineering_math" "description": "以下為工程數學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_engineering_math" "task_alias": "engineering math" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_finance_banking.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_finance_banking.yaml index e60086e1..465c1d74 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_finance_banking.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_finance_banking.yaml @@ -1,7 +1,6 @@ "dataset_name": "finance_banking" "description": "以下為金融與法規的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_finance_banking" "task_alias": "finance banking" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_financial_analysis.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_financial_analysis.yaml index 9990ab5d..647189c6 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_financial_analysis.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_financial_analysis.yaml @@ -1,7 +1,6 @@ "dataset_name": "financial_analysis" "description": "以下為財務分析的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_financial_analysis" "task_alias": "financial analysis" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_fire_science.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_fire_science.yaml index 807f6f5f..9b78539c 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_fire_science.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_fire_science.yaml @@ -1,7 +1,6 @@ "dataset_name": "fire_science" "description": "以下為火災學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_fire_science" "task_alias": "fire science" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_general_principles_of_law.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_general_principles_of_law.yaml index 30b21cae..8213106b 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_general_principles_of_law.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_general_principles_of_law.yaml @@ -1,7 +1,6 @@ "dataset_name": "general_principles_of_law" "description": "以下為法學大意的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_humanities" -"group_alias": "humanities" -"include": "_default_template_yaml" +"tag": "tmmluplus_humanities_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_general_principles_of_law" "task_alias": "general principles of law" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_geography_of_taiwan.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_geography_of_taiwan.yaml index 80ab36b7..ae24c2e1 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_geography_of_taiwan.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_geography_of_taiwan.yaml @@ -1,7 +1,6 @@ "dataset_name": "geography_of_taiwan" "description": "以下為台灣地理的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_geography_of_taiwan" "task_alias": "geography of taiwan" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_human_behavior.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_human_behavior.yaml index 54aaa80f..bb2fa723 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_human_behavior.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_human_behavior.yaml @@ -1,7 +1,6 @@ "dataset_name": "human_behavior" "description": "以下為人類行為與社會的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_human_behavior" "task_alias": "human behavior" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_insurance_studies.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_insurance_studies.yaml index fa23be46..5d1abf78 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_insurance_studies.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_insurance_studies.yaml @@ -1,7 +1,6 @@ "dataset_name": "insurance_studies" "description": "以下為保險學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_insurance_studies" "task_alias": "insurance studies" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_introduction_to_law.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_introduction_to_law.yaml index 6434d3ea..ddbd4889 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_introduction_to_law.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_introduction_to_law.yaml @@ -1,7 +1,6 @@ "dataset_name": "introduction_to_law" "description": "以下為法律概論的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_humanities" -"group_alias": "humanities" -"include": "_default_template_yaml" +"tag": "tmmluplus_humanities_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_introduction_to_law" "task_alias": "introduction to law" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_jce_humanities.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_jce_humanities.yaml index 2ff3bed0..b70bcdd3 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_jce_humanities.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_jce_humanities.yaml @@ -1,7 +1,6 @@ "dataset_name": "jce_humanities" "description": "以下為指考人文科目的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_humanities" -"group_alias": "humanities" -"include": "_default_template_yaml" +"tag": "tmmluplus_humanities_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_jce_humanities" "task_alias": "jce humanities" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_chemistry.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_chemistry.yaml index de9c0691..3c43b6b6 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_chemistry.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_chemistry.yaml @@ -1,7 +1,6 @@ "dataset_name": "junior_chemistry" "description": "以下為國中理化的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_junior_chemistry" "task_alias": "junior chemistry" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_chinese_exam.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_chinese_exam.yaml index 93709052..ac68698b 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_chinese_exam.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_chinese_exam.yaml @@ -1,7 +1,6 @@ "dataset_name": "junior_chinese_exam" "description": "以下為國中會考基測國文的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_junior_chinese_exam" "task_alias": "junior chinese exam" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_math_exam.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_math_exam.yaml index a869a55f..bc72e5e0 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_math_exam.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_math_exam.yaml @@ -1,7 +1,6 @@ "dataset_name": "junior_math_exam" "description": "以下為國中會考基測數學科的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_junior_math_exam" "task_alias": "junior math exam" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_science_exam.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_science_exam.yaml index ed4b8d27..740e674e 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_science_exam.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_science_exam.yaml @@ -1,7 +1,6 @@ "dataset_name": "junior_science_exam" "description": "以下為國中會考基測自然科的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_junior_science_exam" "task_alias": "junior science exam" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_social_studies.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_social_studies.yaml index 760ff0e7..54472b09 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_social_studies.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_junior_social_studies.yaml @@ -1,7 +1,6 @@ "dataset_name": "junior_social_studies" "description": "以下為國中會考基測社會科的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_junior_social_studies" "task_alias": "junior social studies" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_linear_algebra.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_linear_algebra.yaml index c2286dbc..762bdfc0 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_linear_algebra.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_linear_algebra.yaml @@ -1,7 +1,6 @@ "dataset_name": "linear_algebra" "description": "以下為線代的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_linear_algebra" "task_alias": "linear algebra" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_logic_reasoning.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_logic_reasoning.yaml index 059bef3d..58fdc83f 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_logic_reasoning.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_logic_reasoning.yaml @@ -1,7 +1,6 @@ "dataset_name": "logic_reasoning" "description": "以下為邏輯思維的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_logic_reasoning" "task_alias": "logic reasoning" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_macroeconomics.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_macroeconomics.yaml index 91009abe..81984475 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_macroeconomics.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_macroeconomics.yaml @@ -1,7 +1,6 @@ "dataset_name": "macroeconomics" "description": "以下為總經的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_macroeconomics" "task_alias": "macroeconomics" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_management_accounting.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_management_accounting.yaml index 2d071f86..fd77179d 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_management_accounting.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_management_accounting.yaml @@ -1,7 +1,6 @@ "dataset_name": "management_accounting" "description": "以下為管理會計的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_management_accounting" "task_alias": "management accounting" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_marketing_management.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_marketing_management.yaml index da39f0a8..f903c4b6 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_marketing_management.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_marketing_management.yaml @@ -1,7 +1,6 @@ "dataset_name": "marketing_management" "description": "以下為行銷管理的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_marketing_management" "task_alias": "marketing management" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_mechanical.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_mechanical.yaml index 81ea0dce..5300cc1d 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_mechanical.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_mechanical.yaml @@ -1,7 +1,6 @@ "dataset_name": "mechanical" "description": "以下為機械與機電概論的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_mechanical" "task_alias": "mechanical" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_music.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_music.yaml index 72864c00..b0e62bad 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_music.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_music.yaml @@ -1,7 +1,6 @@ "dataset_name": "music" "description": "以下為音樂科的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_music" "task_alias": "music" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_national_protection.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_national_protection.yaml index 62e98266..4ae2953b 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_national_protection.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_national_protection.yaml @@ -1,7 +1,6 @@ "dataset_name": "national_protection" "description": "以下為軍事的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_national_protection" "task_alias": "national protection" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_nautical_science.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_nautical_science.yaml index e02c1dbc..1be4cf1d 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_nautical_science.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_nautical_science.yaml @@ -1,7 +1,6 @@ "dataset_name": "nautical_science" "description": "以下為航海的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_nautical_science" "task_alias": "nautical science" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_occupational_therapy_for_psychological_disorders.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_occupational_therapy_for_psychological_disorders.yaml index ba2bfa82..5f6f3395 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_occupational_therapy_for_psychological_disorders.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_occupational_therapy_for_psychological_disorders.yaml @@ -1,7 +1,6 @@ "dataset_name": "occupational_therapy_for_psychological_disorders" "description": "以下為心理障礙職能治療學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_occupational_therapy_for_psychological_disorders" "task_alias": "occupational therapy for psychological disorders" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_official_document_management.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_official_document_management.yaml index 77dce1d6..16617d2f 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_official_document_management.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_official_document_management.yaml @@ -1,7 +1,6 @@ "dataset_name": "official_document_management" "description": "以下為機關文書的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_official_document_management" "task_alias": "official document management" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_optometry.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_optometry.yaml index 7e3b78b7..ccec8708 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_optometry.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_optometry.yaml @@ -1,7 +1,6 @@ "dataset_name": "optometry" "description": "以下為視光學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_optometry" "task_alias": "optometry" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_organic_chemistry.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_organic_chemistry.yaml index 75a096f9..8f1a8cce 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_organic_chemistry.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_organic_chemistry.yaml @@ -1,7 +1,6 @@ "dataset_name": "organic_chemistry" "description": "以下為有機化學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_organic_chemistry" "task_alias": "organic chemistry" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_pharmacology.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_pharmacology.yaml index 0da7ec98..f42435e5 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_pharmacology.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_pharmacology.yaml @@ -1,7 +1,6 @@ "dataset_name": "pharmacology" "description": "以下為藥理學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_pharmacology" "task_alias": "pharmacology" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_pharmacy.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_pharmacy.yaml index a87aa4be..4cb8e83f 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_pharmacy.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_pharmacy.yaml @@ -1,7 +1,6 @@ "dataset_name": "pharmacy" "description": "以下為藥劑學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_pharmacy" "task_alias": "pharmacy" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_physical_education.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_physical_education.yaml index fb3558e9..af762327 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_physical_education.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_physical_education.yaml @@ -1,7 +1,6 @@ "dataset_name": "physical_education" "description": "以下為體育的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_physical_education" "task_alias": "physical education" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_physics.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_physics.yaml index 3a8443fe..c9d4e16b 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_physics.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_physics.yaml @@ -1,7 +1,6 @@ "dataset_name": "physics" "description": "以下為物理的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_physics" "task_alias": "physics" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_politic_science.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_politic_science.yaml index 67d2068c..9ebbdb24 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_politic_science.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_politic_science.yaml @@ -1,7 +1,6 @@ "dataset_name": "politic_science" "description": "以下為政治的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_politic_science" "task_alias": "politic science" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_real_estate.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_real_estate.yaml index ba90b7aa..971557b5 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_real_estate.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_real_estate.yaml @@ -1,7 +1,6 @@ "dataset_name": "real_estate" "description": "以下為房地產的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_real_estate" "task_alias": "real estate" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_secondary_physics.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_secondary_physics.yaml index 6865167c..1660fc6d 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_secondary_physics.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_secondary_physics.yaml @@ -1,7 +1,6 @@ "dataset_name": "secondary_physics" "description": "以下為高中物理的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_secondary_physics" "task_alias": "secondary physics" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_statistics_and_machine_learning.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_statistics_and_machine_learning.yaml index 9a6e68ba..252496cf 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_statistics_and_machine_learning.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_statistics_and_machine_learning.yaml @@ -1,7 +1,6 @@ "dataset_name": "statistics_and_machine_learning" "description": "以下為統計與機器學習的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_statistics_and_machine_learning" "task_alias": "statistics and machine learning" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_taiwanese_hokkien.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_taiwanese_hokkien.yaml index 89297df3..2977a167 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_taiwanese_hokkien.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_taiwanese_hokkien.yaml @@ -1,7 +1,6 @@ "dataset_name": "taiwanese_hokkien" "description": "以下為閩南語的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_taiwanese_hokkien" "task_alias": "taiwanese hokkien" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_taxation.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_taxation.yaml index f5452027..c382b8c8 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_taxation.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_taxation.yaml @@ -1,7 +1,6 @@ "dataset_name": "taxation" "description": "以下為稅務的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_humanities" -"group_alias": "humanities" -"include": "_default_template_yaml" +"tag": "tmmluplus_humanities_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_taxation" "task_alias": "taxation" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_technical.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_technical.yaml index 6167a8fe..b4621a4e 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_technical.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_technical.yaml @@ -1,7 +1,6 @@ "dataset_name": "technical" "description": "以下為技術工相關的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_technical" "task_alias": "technical" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_three_principles_of_people.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_three_principles_of_people.yaml index de50db70..83a3628d 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_three_principles_of_people.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_three_principles_of_people.yaml @@ -1,7 +1,6 @@ "dataset_name": "three_principles_of_people" "description": "以下為三民主義的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_three_principles_of_people" "task_alias": "three principles of people" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_trade.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_trade.yaml index 1c42e22e..7eacf4dc 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_trade.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_trade.yaml @@ -1,7 +1,6 @@ "dataset_name": "trade" "description": "以下為貿易的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_trade" "task_alias": "trade" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_traditional_chinese_medicine_clinical_medicine.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_traditional_chinese_medicine_clinical_medicine.yaml index b5a3fdf1..7d626dd2 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_traditional_chinese_medicine_clinical_medicine.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_traditional_chinese_medicine_clinical_medicine.yaml @@ -1,7 +1,6 @@ "dataset_name": "traditional_chinese_medicine_clinical_medicine" "description": "以下為中醫臨床醫學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_traditional_chinese_medicine_clinical_medicine" "task_alias": "traditional chinese medicine clinical medicine" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_trust_practice.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_trust_practice.yaml index 0c1e7ae3..f4b3a010 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_trust_practice.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_trust_practice.yaml @@ -1,7 +1,6 @@ "dataset_name": "trust_practice" "description": "以下為信託實務的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_humanities" -"group_alias": "humanities" -"include": "_default_template_yaml" +"tag": "tmmluplus_humanities_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_trust_practice" "task_alias": "trust practice" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_ttqav2.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_ttqav2.yaml index 2216d4d4..95a10411 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_ttqav2.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_ttqav2.yaml @@ -1,7 +1,6 @@ "dataset_name": "ttqav2" "description": "以下為台灣在地用語的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_ttqav2" "task_alias": "ttqav2" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_chinese_language.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_chinese_language.yaml index 0c98fedd..a8660088 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_chinese_language.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_chinese_language.yaml @@ -1,7 +1,6 @@ "dataset_name": "tve_chinese_language" "description": "以下為統測國文的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_social_sciences" -"group_alias": "social sciences" -"include": "_default_template_yaml" +"tag": "tmmluplus_social_sciences_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_tve_chinese_language" "task_alias": "tve chinese language" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_design.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_design.yaml index e36b1548..01a27149 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_design.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_design.yaml @@ -1,7 +1,6 @@ "dataset_name": "tve_design" "description": "以下為統測 設計的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_tve_design" "task_alias": "tve design" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_mathematics.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_mathematics.yaml index b4158f17..6240db29 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_mathematics.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_mathematics.yaml @@ -1,7 +1,6 @@ "dataset_name": "tve_mathematics" "description": "以下為統測數學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_tve_mathematics" "task_alias": "tve mathematics" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_natural_sciences.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_natural_sciences.yaml index c2ecf4ad..833c47fc 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_natural_sciences.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_tve_natural_sciences.yaml @@ -1,7 +1,6 @@ "dataset_name": "tve_natural_sciences" "description": "以下為統測自然科的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_STEM" -"group_alias": "STEM" -"include": "_default_template_yaml" +"tag": "tmmluplus_STEM_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_tve_natural_sciences" "task_alias": "tve natural sciences" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_veterinary_pathology.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_veterinary_pathology.yaml index c1fcb438..c5a8edcb 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_veterinary_pathology.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_veterinary_pathology.yaml @@ -1,7 +1,6 @@ "dataset_name": "veterinary_pathology" "description": "以下為獸醫病理學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_veterinary_pathology" "task_alias": "veterinary pathology" diff --git a/lm_eval/tasks/tmmluplus/default/tmmluplus_veterinary_pharmacology.yaml b/lm_eval/tasks/tmmluplus/default/tmmluplus_veterinary_pharmacology.yaml index 45c6553b..b75b1f00 100644 --- a/lm_eval/tasks/tmmluplus/default/tmmluplus_veterinary_pharmacology.yaml +++ b/lm_eval/tasks/tmmluplus/default/tmmluplus_veterinary_pharmacology.yaml @@ -1,7 +1,6 @@ "dataset_name": "veterinary_pharmacology" "description": "以下為獸醫藥理學的單選題，請提供正確答案的選項。\n\n" -"group": "tmmluplus_other" -"group_alias": "other" -"include": "_default_template_yaml" +"tag": "tmmluplus_other_tasks" +"include": "_tmmluplus_template_yaml" "task": "tmmluplus_veterinary_pharmacology" "task_alias": "veterinary pharmacology" diff --git a/pyproject.toml b/pyproject.toml index 00319775..1bc0944e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "lm_eval" -version = "0.4.3" +version = "0.4.4" authors = [ {name="EleutherAI", email="contact@eleuther.ai"} ] -- GitLab From decc533d02222f3b866d9a89263277fe0cc2fcb2 Mon Sep 17 00:00:00 2001 From: Malikeh Ehghaghi <35193114+Malikeh97@users.noreply.github.com> Date: Tue, 10 Sep 2024 17:28:47 -0400 Subject: [PATCH 095/194] Add Open Arabic LLM Leaderboard Benchmarks (Full and Light Version) (#2232) * arabic leaferboard yaml file is added * arabic toxigen is implemented * Dataset library is imported * arabic sciq is added * util file of arabic toxigen is updated * arabic race is added * arabic piqa is implemented * arabic open qa is added * arabic copa is implemented * arabic boolq ia added * arabic arc easy is added * arabic arc challenge is added * arabic exams benchmark is implemented * arabic hellaswag is added * arabic leaderboard yaml file metrics are updated * arabic mmlu benchmarks are added * arabic mmlu group yaml file is updated * alghafa benchmarks are added * acva benchmarks are added * acva utils.py is updated * light version of arabic leaderboard benchmarks are added * bugs fixed * bug fixed * bug fixed * bug fixed * bug fixed * bug fixed * library import bug is fixed * doc to target updated * bash file is deleted * results folder is deleted * leaderboard groups are added * full arabic leaderboard groups are added, plus some bug fixes to the light version * Create README.md README.md for arabic_leaderboard_complete * Create README.md README.md for arabic_leaderboard_light * Delete lm_eval/tasks/arabic_leaderboard directory * Update README.md * Update README.md adding the Arabic leaderboards to the library * Update README.md 10% of the training set * Update README.md 10% of the training set * revert .gitignore to prev version * Update lm_eval/tasks/README.md Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * updated main README.md * Update lm_eval/tasks/README.md * specify machine translated benchmarks (complete) * specify machine translated benchmarks (light version) * add alghafa to the related task names (complete and light) * add 'acva' to the related task names (complete and light) * add 'arabic_leaderboard' to all the groups (complete and light) * all dataset - not a random sample * added more accurate details to the readme file * added mt_mmlu from okapi * Update lm_eval/tasks/README.md Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * Update lm_eval/tasks/README.md Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * updated mt_mmlu readme * renaming 'alghafa' full and light * renaming 'arabic_mmlu' light and full * renaming 'acva' full and light * update readme and standardize dir/file names * running pre-commit --------- Co-authored-by: shahrzads Co-authored-by: shahrzads <56282669+shahrzads@users.noreply.github.com> Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- lm_eval/tasks/README.md | 2 + .../arabic_leaderboard_complete/README.md | 254 ++++++++++++++++++ .../arabic_leaderboard_alghafa.yaml | 23 ++ ...leaderboard_alghafa_mcq_exams_test_ar.yaml | 23 ++ ..._leaderboard_alghafa_meta_ar_dialects.yaml | 23 ++ ...rabic_leaderboard_alghafa_meta_ar_msa.yaml | 23 ++ ..._choice_facts_truefalse_balanced_task.yaml | 23 ++ ..._choice_grounded_statement_soqal_task.yaml | 23 ++ ...ce_grounded_statement_xglue_mlqa_task.yaml | 23 ++ ...oice_rating_sentiment_no_neutral_task.yaml | 23 ++ ...multiple_choice_rating_sentiment_task.yaml | 23 ++ ...lghafa_multiple_choice_sentiment_task.yaml | 23 ++ .../arabic_leaderboard_alghafa/utils.py | 23 ++ .../arabic_exams.yaml | 23 ++ .../arabic_leaderboard_arabic_exams.yaml | 13 + .../arabic_leaderboard_arabic_exams/utils.py | 33 +++ .../arabic_leaderboard_arabic_mmlu.yaml | 68 +++++ ...derboard_arabic_mmlu_abstract_algebra.yaml | 23 ++ ...rabic_leaderboard_arabic_mmlu_anatomy.yaml | 23 ++ ...bic_leaderboard_arabic_mmlu_astronomy.yaml | 23 ++ ...aderboard_arabic_mmlu_business_ethics.yaml | 23 ++ ...rboard_arabic_mmlu_clinical_knowledge.yaml | 23 ++ ...aderboard_arabic_mmlu_college_biology.yaml | 23 ++ ...erboard_arabic_mmlu_college_chemistry.yaml | 23 ++ ..._arabic_mmlu_college_computer_science.yaml | 23 ++ ...board_arabic_mmlu_college_mathematics.yaml | 23 ++ ...derboard_arabic_mmlu_college_medicine.yaml | 23 ++ ...aderboard_arabic_mmlu_college_physics.yaml | 23 ++ ...erboard_arabic_mmlu_computer_security.yaml | 23 ++ ...rboard_arabic_mmlu_conceptual_physics.yaml | 23 ++ ..._leaderboard_arabic_mmlu_econometrics.yaml | 23 ++ ...rd_arabic_mmlu_electrical_engineering.yaml | 23 ++ ...rd_arabic_mmlu_elementary_mathematics.yaml | 23 ++ ..._leaderboard_arabic_mmlu_formal_logic.yaml | 23 ++ ..._leaderboard_arabic_mmlu_global_facts.yaml | 23 ++ ...board_arabic_mmlu_high_school_biology.yaml | 23 ++ ...ard_arabic_mmlu_high_school_chemistry.yaml | 23 ++ ...bic_mmlu_high_school_computer_science.yaml | 23 ++ ...bic_mmlu_high_school_european_history.yaml | 23 ++ ...ard_arabic_mmlu_high_school_geography.yaml | 23 ++ ...u_high_school_government_and_politics.yaml | 23 ++ ...rabic_mmlu_high_school_macroeconomics.yaml | 23 ++ ...d_arabic_mmlu_high_school_mathematics.yaml | 23 ++ ...rabic_mmlu_high_school_microeconomics.yaml | 23 ++ ...board_arabic_mmlu_high_school_physics.yaml | 23 ++ ...rd_arabic_mmlu_high_school_psychology.yaml | 23 ++ ...rd_arabic_mmlu_high_school_statistics.yaml | 23 ++ ...rd_arabic_mmlu_high_school_us_history.yaml | 23 ++ ...arabic_mmlu_high_school_world_history.yaml | 23 ++ ...c_leaderboard_arabic_mmlu_human_aging.yaml | 23 ++ ...aderboard_arabic_mmlu_human_sexuality.yaml | 23 ++ ...erboard_arabic_mmlu_international_law.yaml | 23 ++ ...leaderboard_arabic_mmlu_jurisprudence.yaml | 23 ++ ...erboard_arabic_mmlu_logical_fallacies.yaml | 23 ++ ...derboard_arabic_mmlu_machine_learning.yaml | 23 ++ ...ic_leaderboard_arabic_mmlu_management.yaml | 23 ++ ...bic_leaderboard_arabic_mmlu_marketing.yaml | 23 ++ ...derboard_arabic_mmlu_medical_genetics.yaml | 23 ++ ...leaderboard_arabic_mmlu_miscellaneous.yaml | 23 ++ ...eaderboard_arabic_mmlu_moral_disputes.yaml | 23 ++ ...aderboard_arabic_mmlu_moral_scenarios.yaml | 23 ++ ...bic_leaderboard_arabic_mmlu_nutrition.yaml | 23 ++ ...ic_leaderboard_arabic_mmlu_philosophy.yaml | 23 ++ ...ic_leaderboard_arabic_mmlu_prehistory.yaml | 23 ++ ...d_arabic_mmlu_professional_accounting.yaml | 23 ++ ...derboard_arabic_mmlu_professional_law.yaml | 23 ++ ...ard_arabic_mmlu_professional_medicine.yaml | 23 ++ ...d_arabic_mmlu_professional_psychology.yaml | 23 ++ ...derboard_arabic_mmlu_public_relations.yaml | 23 ++ ...derboard_arabic_mmlu_security_studies.yaml | 23 ++ ...bic_leaderboard_arabic_mmlu_sociology.yaml | 23 ++ ...erboard_arabic_mmlu_us_foreign_policy.yaml | 23 ++ ...abic_leaderboard_arabic_mmlu_virology.yaml | 23 ++ ...aderboard_arabic_mmlu_world_religions.yaml | 23 ++ .../arabic_leaderboard_arabic_mmlu/utils.py | 35 +++ ...c_leaderboard_arabic_mt_arc_challenge.yaml | 13 + .../arabic_mt_arc_challenge.yaml | 23 ++ .../utils.py | 23 ++ ...arabic_leaderboard_arabic_mt_arc_easy.yaml | 13 + .../arabic_mt_arc_easy.yaml | 23 ++ .../utils.py | 23 ++ .../arabic_leaderboard_arabic_mt_boolq.yaml | 13 + .../arabic_mt_boolq.yaml | 23 ++ .../utils.py | 24 ++ .../arabic_leaderboard_arabic_mt_copa.yaml | 13 + .../arabic_mt_copa.yaml | 23 ++ .../utils.py | 19 ++ ...rabic_leaderboard_arabic_mt_hellaswag.yaml | 13 + .../arabic_mt_hellaswag.yaml | 23 ++ .../utils.py | 30 +++ .../arabic_leaderboard_arabic_mt_mmlu.yaml | 13 + .../arabic_mt_mmlu.yaml | 23 ++ .../utils.py | 23 ++ ...bic_leaderboard_arabic_mt_openbook_qa.yaml | 13 + .../arabic_mt_openbook_qa.yaml | 23 ++ .../utils.py | 23 ++ .../arabic_leaderboard_arabic_mt_piqa.yaml | 13 + .../arabic_mt_piqa.yaml | 23 ++ .../utils.py | 23 ++ .../arabic_leaderboard_arabic_mt_race.yaml | 13 + .../arabic_mt_race.yaml | 23 ++ .../utils.py | 23 ++ .../arabic_leaderboard_arabic_mt_sciq.yaml | 13 + .../arabic_mt_sciq.yaml | 23 ++ .../utils.py | 41 +++ .../arabic_leaderboard_arabic_mt_toxigen.yaml | 13 + .../arabic_mt_toxigen.yaml | 23 ++ .../utils.py | 23 ++ .../arabic_leaderboard_acva.yaml | 70 +++++ .../arabic_leaderboard_acva_Algeria.yaml | 23 ++ ...arabic_leaderboard_acva_Ancient_Egypt.yaml | 23 ++ .../arabic_leaderboard_acva_Arab_Empire.yaml | 23 ++ ..._leaderboard_acva_Arabic_Architecture.yaml | 23 ++ .../arabic_leaderboard_acva_Arabic_Art.yaml | 23 ++ ...bic_leaderboard_acva_Arabic_Astronomy.yaml | 23 ++ ...c_leaderboard_acva_Arabic_Calligraphy.yaml | 23 ++ ...abic_leaderboard_acva_Arabic_Ceremony.yaml | 23 ++ ...abic_leaderboard_acva_Arabic_Clothing.yaml | 23 ++ ...rabic_leaderboard_acva_Arabic_Culture.yaml | 23 ++ .../arabic_leaderboard_acva_Arabic_Food.yaml | 23 ++ ...rabic_leaderboard_acva_Arabic_Funeral.yaml | 23 ++ ...bic_leaderboard_acva_Arabic_Geography.yaml | 23 ++ ...rabic_leaderboard_acva_Arabic_History.yaml | 23 ++ ...aderboard_acva_Arabic_Language_Origin.yaml | 23 ++ ...ic_leaderboard_acva_Arabic_Literature.yaml | 23 ++ .../arabic_leaderboard_acva_Arabic_Math.yaml | 23 ++ ...abic_leaderboard_acva_Arabic_Medicine.yaml | 23 ++ .../arabic_leaderboard_acva_Arabic_Music.yaml | 23 ++ ...abic_leaderboard_acva_Arabic_Ornament.yaml | 23 ++ ...ic_leaderboard_acva_Arabic_Philosophy.yaml | 23 ++ ...ard_acva_Arabic_Physics_and_Chemistry.yaml | 23 ++ ...rabic_leaderboard_acva_Arabic_Wedding.yaml | 23 ++ .../arabic_leaderboard_acva_Bahrain.yaml | 23 ++ .../arabic_leaderboard_acva_Comoros.yaml | 23 ++ .../arabic_leaderboard_acva_Egypt_modern.yaml | 23 ++ ...rboard_acva_InfluenceFromAncientEgypt.yaml | 23 ++ ...aderboard_acva_InfluenceFromByzantium.yaml | 23 ++ ...c_leaderboard_acva_InfluenceFromChina.yaml | 23 ++ ..._leaderboard_acva_InfluenceFromGreece.yaml | 23 ++ ...c_leaderboard_acva_InfluenceFromIslam.yaml | 23 ++ ..._leaderboard_acva_InfluenceFromPersia.yaml | 23 ++ ...ic_leaderboard_acva_InfluenceFromRome.yaml | 23 ++ .../arabic_leaderboard_acva_Iraq.yaml | 23 ++ ...abic_leaderboard_acva_Islam_Education.yaml | 23 ++ ...board_acva_Islam_branches_and_schools.yaml | 23 ++ ...c_leaderboard_acva_Islamic_law_system.yaml | 23 ++ .../arabic_leaderboard_acva_Jordan.yaml | 23 ++ .../arabic_leaderboard_acva_Kuwait.yaml | 23 ++ .../arabic_leaderboard_acva_Lebanon.yaml | 23 ++ .../arabic_leaderboard_acva_Libya.yaml | 23 ++ .../arabic_leaderboard_acva_Mauritania.yaml | 23 ++ ...erboard_acva_Mesopotamia_civilization.yaml | 23 ++ .../arabic_leaderboard_acva_Morocco.yaml | 23 ++ .../arabic_leaderboard_acva_Oman.yaml | 23 ++ .../arabic_leaderboard_acva_Palestine.yaml | 23 ++ .../arabic_leaderboard_acva_Qatar.yaml | 23 ++ .../arabic_leaderboard_acva_Saudi_Arabia.yaml | 23 ++ .../arabic_leaderboard_acva_Somalia.yaml | 23 ++ .../arabic_leaderboard_acva_Sudan.yaml | 23 ++ .../arabic_leaderboard_acva_Syria.yaml | 23 ++ .../arabic_leaderboard_acva_Tunisia.yaml | 23 ++ ...leaderboard_acva_United_Arab_Emirates.yaml | 23 ++ .../arabic_leaderboard_acva_Yemen.yaml | 23 ++ ...arabic_leaderboard_acva_communication.yaml | 23 ++ ...c_leaderboard_acva_computer_and_phone.yaml | 23 ++ .../arabic_leaderboard_acva_daily_life.yaml | 23 ++ ...arabic_leaderboard_acva_entertainment.yaml | 23 ++ .../arabic_leaderboard_avca/utils.py | 16 ++ .../arabic_leaderboard_complete.yaml | 25 ++ .../tasks/arabic_leaderboard_light/README.md | 20 ++ .../arabic_leaderboard_alghafa_light.yaml | 23 ++ ...board_alghafa_mcq_exams_test_ar_light.yaml | 23 ++ ...rboard_alghafa_meta_ar_dialects_light.yaml | 23 ++ ...leaderboard_alghafa_meta_ar_msa_light.yaml | 23 ++ ...e_facts_truefalse_balanced_task_light.yaml | 23 ++ ...e_grounded_statement_soqal_task_light.yaml | 23 ++ ...unded_statement_xglue_mlqa_task_light.yaml | 23 ++ ...ating_sentiment_no_neutral_task_light.yaml | 23 ++ ...le_choice_rating_sentiment_task_light.yaml | 23 ++ ..._multiple_choice_sentiment_task_light.yaml | 23 ++ .../arabic_leaderboard_alghafa_light/utils.py | 23 ++ .../arabic_exams_light.yaml | 23 ++ ...arabic_leaderboard_arabic_exams_light.yaml | 13 + .../utils.py | 33 +++ ...rd_arabic_mmlu_abstract_algebra_light.yaml | 23 ++ ...leaderboard_arabic_mmlu_anatomy_light.yaml | 23 ++ ...aderboard_arabic_mmlu_astronomy_light.yaml | 23 ++ ...ard_arabic_mmlu_business_ethics_light.yaml | 23 ++ ..._arabic_mmlu_clinical_knowledge_light.yaml | 23 ++ ...ard_arabic_mmlu_college_biology_light.yaml | 23 ++ ...d_arabic_mmlu_college_chemistry_light.yaml | 23 ++ ...c_mmlu_college_computer_science_light.yaml | 23 ++ ...arabic_mmlu_college_mathematics_light.yaml | 23 ++ ...rd_arabic_mmlu_college_medicine_light.yaml | 23 ++ ...ard_arabic_mmlu_college_physics_light.yaml | 23 ++ ...d_arabic_mmlu_computer_security_light.yaml | 23 ++ ..._arabic_mmlu_conceptual_physics_light.yaml | 23 ++ ...rboard_arabic_mmlu_econometrics_light.yaml | 23 ++ ...bic_mmlu_electrical_engineering_light.yaml | 23 ++ ...bic_mmlu_elementary_mathematics_light.yaml | 23 ++ ...rboard_arabic_mmlu_formal_logic_light.yaml | 23 ++ ...rboard_arabic_mmlu_global_facts_light.yaml | 23 ++ ...arabic_mmlu_high_school_biology_light.yaml | 23 ++ ...abic_mmlu_high_school_chemistry_light.yaml | 23 ++ ...lu_high_school_computer_science_light.yaml | 23 ++ ...lu_high_school_european_history_light.yaml | 23 ++ ...abic_mmlu_high_school_geography_light.yaml | 23 ++ ..._school_government_and_politics_light.yaml | 23 ++ ...mmlu_high_school_macroeconomics_light.yaml | 23 ++ ...ic_mmlu_high_school_mathematics_light.yaml | 23 ++ ...mmlu_high_school_microeconomics_light.yaml | 23 ++ ...arabic_mmlu_high_school_physics_light.yaml | 23 ++ ...bic_mmlu_high_school_psychology_light.yaml | 23 ++ ...bic_mmlu_high_school_statistics_light.yaml | 23 ++ ...bic_mmlu_high_school_us_history_light.yaml | 23 ++ ..._mmlu_high_school_world_history_light.yaml | 23 ++ ...erboard_arabic_mmlu_human_aging_light.yaml | 23 ++ ...ard_arabic_mmlu_human_sexuality_light.yaml | 23 ++ ...d_arabic_mmlu_international_law_light.yaml | 23 ++ ...board_arabic_mmlu_jurisprudence_light.yaml | 23 ++ .../arabic_leaderboard_arabic_mmlu_light.yaml | 68 +++++ ...d_arabic_mmlu_logical_fallacies_light.yaml | 23 ++ ...rd_arabic_mmlu_machine_learning_light.yaml | 23 ++ ...derboard_arabic_mmlu_management_light.yaml | 23 ++ ...aderboard_arabic_mmlu_marketing_light.yaml | 23 ++ ...rd_arabic_mmlu_medical_genetics_light.yaml | 23 ++ ...board_arabic_mmlu_miscellaneous_light.yaml | 23 ++ ...oard_arabic_mmlu_moral_disputes_light.yaml | 23 ++ ...ard_arabic_mmlu_moral_scenarios_light.yaml | 23 ++ ...aderboard_arabic_mmlu_nutrition_light.yaml | 23 ++ ...derboard_arabic_mmlu_philosophy_light.yaml | 23 ++ ...derboard_arabic_mmlu_prehistory_light.yaml | 23 ++ ...ic_mmlu_professional_accounting_light.yaml | 23 ++ ...rd_arabic_mmlu_professional_law_light.yaml | 23 ++ ...abic_mmlu_professional_medicine_light.yaml | 23 ++ ...ic_mmlu_professional_psychology_light.yaml | 23 ++ ...rd_arabic_mmlu_public_relations_light.yaml | 23 ++ ...rd_arabic_mmlu_security_studies_light.yaml | 23 ++ ...aderboard_arabic_mmlu_sociology_light.yaml | 23 ++ ...d_arabic_mmlu_us_foreign_policy_light.yaml | 23 ++ ...eaderboard_arabic_mmlu_virology_light.yaml | 23 ++ ...ard_arabic_mmlu_world_religions_light.yaml | 23 ++ .../utils.py | 35 +++ ...erboard_arabic_mt_arc_challenge_light.yaml | 13 + .../arabic_mt_arc_challenge_light.yaml | 23 ++ .../utils.py | 23 ++ ..._leaderboard_arabic_mt_arc_easy_light.yaml | 13 + .../arabic_mt_arc_easy_light.yaml | 23 ++ .../utils.py | 23 ++ ...bic_leaderboard_arabic_mt_boolq_light.yaml | 13 + .../arabic_mt_boolq_light.yaml | 23 ++ .../utils.py | 24 ++ .../arabic_mt_copa_light.yaml | 23 ++ ...rbic_leaderboard_arabic_mt_copa_light.yaml | 13 + .../utils.py | 19 ++ ...leaderboard_arabic_mt_hellaswag_light.yaml | 13 + .../arabic_mt_hellaswag_light.yaml | 23 ++ .../utils.py | 30 +++ ...abic_leaderboard_arabic_mt_mmlu_light.yaml | 13 + .../arabic_mt_mmlu_light.yaml | 23 ++ .../utils.py | 23 ++ ...aderboard_arabic_mt_openbook_qa_light.yaml | 13 + .../arabic_mt_openbook_qa_light.yaml | 23 ++ .../utils.py | 23 ++ ...abic_leaderboard_arabic_mt_piqa_light.yaml | 13 + .../arabic_mt_piqa_light.yaml | 23 ++ .../utils.py | 23 ++ ...abic_leaderboard_arabic_mt_race_light.yaml | 13 + .../arabic_mt_race_light.yaml | 23 ++ .../utils.py | 23 ++ ...abic_leaderboard_arabic_mt_sciq_light.yaml | 13 + .../arabic_mt_sciq_light.yaml | 23 ++ .../utils.py | 41 +++ ...c_leaderboard_arabic_mt_toxigen_light.yaml | 13 + .../arabic_mt_toxigen_light.yaml | 23 ++ .../utils.py | 23 ++ ...arabic_leaderboard_acva_Algeria_light.yaml | 23 ++ ..._leaderboard_acva_Ancient_Egypt_light.yaml | 23 ++ ...ic_leaderboard_acva_Arab_Empire_light.yaml | 23 ++ ...rboard_acva_Arabic_Architecture_light.yaml | 23 ++ ...bic_leaderboard_acva_Arabic_Art_light.yaml | 23 ++ ...aderboard_acva_Arabic_Astronomy_light.yaml | 23 ++ ...erboard_acva_Arabic_Calligraphy_light.yaml | 23 ++ ...eaderboard_acva_Arabic_Ceremony_light.yaml | 23 ++ ...eaderboard_acva_Arabic_Clothing_light.yaml | 23 ++ ...leaderboard_acva_Arabic_Culture_light.yaml | 23 ++ ...ic_leaderboard_acva_Arabic_Food_light.yaml | 23 ++ ...leaderboard_acva_Arabic_Funeral_light.yaml | 23 ++ ...aderboard_acva_Arabic_Geography_light.yaml | 23 ++ ...leaderboard_acva_Arabic_History_light.yaml | 23 ++ ...ard_acva_Arabic_Language_Origin_light.yaml | 23 ++ ...derboard_acva_Arabic_Literature_light.yaml | 23 ++ ...ic_leaderboard_acva_Arabic_Math_light.yaml | 23 ++ ...eaderboard_acva_Arabic_Medicine_light.yaml | 23 ++ ...c_leaderboard_acva_Arabic_Music_light.yaml | 23 ++ ...eaderboard_acva_Arabic_Ornament_light.yaml | 23 ++ ...derboard_acva_Arabic_Philosophy_light.yaml | 23 ++ ...va_Arabic_Physics_and_Chemistry_light.yaml | 23 ++ ...leaderboard_acva_Arabic_Wedding_light.yaml | 23 ++ ...arabic_leaderboard_acva_Bahrain_light.yaml | 23 ++ ...arabic_leaderboard_acva_Comoros_light.yaml | 23 ++ ...c_leaderboard_acva_Egypt_modern_light.yaml | 23 ++ ..._acva_InfluenceFromAncientEgypt_light.yaml | 23 ++ ...ard_acva_InfluenceFromByzantium_light.yaml | 23 ++ ...erboard_acva_InfluenceFromChina_light.yaml | 23 ++ ...rboard_acva_InfluenceFromGreece_light.yaml | 23 ++ ...erboard_acva_InfluenceFromIslam_light.yaml | 23 ++ ...rboard_acva_InfluenceFromPersia_light.yaml | 23 ++ ...derboard_acva_InfluenceFromRome_light.yaml | 23 ++ .../arabic_leaderboard_acva_Iraq_light.yaml | 23 ++ ...eaderboard_acva_Islam_Education_light.yaml | 23 ++ ...acva_Islam_branches_and_schools_light.yaml | 23 ++ ...erboard_acva_Islamic_law_system_light.yaml | 23 ++ .../arabic_leaderboard_acva_Jordan_light.yaml | 23 ++ .../arabic_leaderboard_acva_Kuwait_light.yaml | 23 ++ ...arabic_leaderboard_acva_Lebanon_light.yaml | 23 ++ .../arabic_leaderboard_acva_Libya_light.yaml | 23 ++ ...bic_leaderboard_acva_Mauritania_light.yaml | 23 ++ ...d_acva_Mesopotamia_civilization_light.yaml | 23 ++ ...arabic_leaderboard_acva_Morocco_light.yaml | 23 ++ .../arabic_leaderboard_acva_Oman_light.yaml | 23 ++ ...abic_leaderboard_acva_Palestine_light.yaml | 23 ++ .../arabic_leaderboard_acva_Qatar_light.yaml | 23 ++ ...c_leaderboard_acva_Saudi_Arabia_light.yaml | 23 ++ ...arabic_leaderboard_acva_Somalia_light.yaml | 23 ++ .../arabic_leaderboard_acva_Sudan_light.yaml | 23 ++ .../arabic_leaderboard_acva_Syria_light.yaml | 23 ++ ...arabic_leaderboard_acva_Tunisia_light.yaml | 23 ++ ...board_acva_United_Arab_Emirates_light.yaml | 23 ++ .../arabic_leaderboard_acva_Yemen_light.yaml | 23 ++ ..._leaderboard_acva_communication_light.yaml | 23 ++ ...erboard_acva_computer_and_phone_light.yaml | 23 ++ ...bic_leaderboard_acva_daily_life_light.yaml | 23 ++ ..._leaderboard_acva_entertainment_light.yaml | 23 ++ .../arabic_leaderboard_acva_light.yaml | 70 +++++ .../arabic_leaderboard_avca_light/utils.py | 16 ++ .../arabic_leaderboard_light.yaml | 25 ++ 337 files changed, 7980 insertions(+) create mode 100644 lm_eval/tasks/arabic_leaderboard_complete/README.md create mode 100644 lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa.yaml create mode 100644 lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_mcq_exams_test_ar.yaml create mode 100644 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lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_entertainment_light.yaml create mode 100644 lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_light.yaml create mode 100644 lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/utils.py create mode 100644 lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_light.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 6c500ee5..09a6dd79 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -11,6 +11,8 @@ | [aexams](aexams/README.md) | Tasks in Arabic related to various academic exams covering a range of subjects. | Arabic | | [agieval](agieval/README.md) | Tasks involving historical data or questions related to history and historical texts. | English, Chinese | | [anli](anli/README.md) | Adversarial natural language inference tasks designed to test model robustness. | English | +| [arabic_leaderboard_complete](arabic_leaderboard_complete/README.md) | A full version of the tasks in the Open Arabic LLM Leaderboard, focusing on the evaluation of models that reflect the characteristics of Arabic language understanding and comprehension, culture, and heritage. Note that some of these tasks are machine-translated. | Arabic (Some MT) | +| [arabic_leaderboard_light](arabic_leaderboard_light/README.md) | A light version of the tasks in the Open Arabic LLM Leaderboard (i.e., 10% samples of the test set in the original benchmarks), focusing on the evaluation of models that reflect the characteristics of Arabic language understanding and comprehension, culture, and heritage. Note that some of these tasks are machine-translated. | Arabic (Some MT) | | [arabicmmlu](arabicmmlu/README.md) | Localized Arabic version of MMLU with multiple-choice questions from 40 subjects. | Arabic | | [arc](arc/README.md) | Tasks involving complex reasoning over a diverse set of questions. | English | | [arithmetic](arithmetic/README.md) | Tasks involving numerical computations and arithmetic reasoning. | English | diff --git a/lm_eval/tasks/arabic_leaderboard_complete/README.md b/lm_eval/tasks/arabic_leaderboard_complete/README.md new file mode 100644 index 00000000..8052abcb --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/README.md @@ -0,0 +1,254 @@ +# Arabic Leaderboard + + +Title: Open Arabic LLM Leaderboard + +The Open Arabic LLM Leaderboard evaluates language models on a large number of different evaluation tasks that reflect the characteristics of the Arabic language and culture. +The benchmark uses several datasets, most of them translated to Arabic, and validated by native Arabic speakers. They also used benchmarks from other papers or prepared benchmarks from scratch natively for Arabic. + +Homepage: https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard + +### Citation + +``` + +@misc{OALL, + author = {Elfilali, Ali and Alobeidli, Hamza and Fourrier, Clémentine and Boussaha, Basma El Amel and Cojocaru, Ruxandra and Habib, Nathan and Hacid, Hakim}, + title = {Open Arabic LLM Leaderboard}, + year = {2024}, + publisher = {OALL}, + howpublished = "\url{https://huggingface.co/spaces/OALL/Open-Arabic-LLM-Leaderboard}" +} + +@inproceedings{almazrouei-etal-2023-alghafa, + title = "{A}l{G}hafa Evaluation Benchmark for {A}rabic Language Models", + author = "Almazrouei, Ebtesam and + Cojocaru, Ruxandra and + Baldo, Michele and + Malartic, Quentin and + Alobeidli, Hamza and + Mazzotta, Daniele and + Penedo, Guilherme and + Campesan, Giulia and + Farooq, Mugariya and + Alhammadi, Maitha and + Launay, Julien and + Noune, Badreddine", + editor = "Sawaf, Hassan and + El-Beltagy, Samhaa and + Zaghouani, Wajdi and + Magdy, Walid and + Abdelali, Ahmed and + Tomeh, Nadi and + Abu Farha, Ibrahim and + Habash, Nizar and + Khalifa, Salam and + Keleg, Amr and + Haddad, Hatem and + Zitouni, Imed and + Mrini, Khalil and + Almatham, Rawan", + booktitle = "Proceedings of ArabicNLP 2023", + month = dec, + year = "2023", + address = "Singapore (Hybrid)", + publisher = "Association for Computational Linguistics", + url = "https://aclanthology.org/2023.arabicnlp-1.21", + doi = "10.18653/v1/2023.arabicnlp-1.21", + pages = "244--275", + abstract = "Recent advances in the space of Arabic large language models have opened up a wealth of potential practical applications. From optimal training strategies, large scale data acquisition and continuously increasing NLP resources, the Arabic LLM landscape has improved in a very short span of time, despite being plagued by training data scarcity and limited evaluation resources compared to English. In line with contributing towards this ever-growing field, we introduce AlGhafa, a new multiple-choice evaluation benchmark for Arabic LLMs. For showcasing purposes, we train a new suite of models, including a 14 billion parameter model, the largest monolingual Arabic decoder-only model to date. We use a collection of publicly available datasets, as well as a newly introduced HandMade dataset consisting of 8 billion tokens. Finally, we explore the quantitative and qualitative toxicity of several Arabic models, comparing our models to existing public Arabic LLMs.", +} +@misc{huang2023acegpt, + title={AceGPT, Localizing Large Language Models in Arabic}, + author={Huang Huang and Fei Yu and Jianqing Zhu and Xuening Sun and Hao Cheng and Dingjie Song and Zhihong Chen and Abdulmohsen Alharthi and Bang An and Ziche Liu and Zhiyi Zhang and Junying Chen and Jianquan Li and Benyou Wang and Lian Zhang and Ruoyu Sun and Xiang Wan and Haizhou Li and Jinchao Xu}, + year={2023}, + eprint={2309.12053}, + archivePrefix={arXiv}, + primaryClass={cs.CL} +} +@misc{lighteval, + author = {Fourrier, Clémentine and Habib, Nathan and Wolf, Thomas and Tunstall, Lewis}, + title = {LightEval: A lightweight framework for LLM evaluation}, + year = {2023}, + version = {0.3.0}, + url = {https://github.com/huggingface/lighteval} +} +``` + +### Groups and Tasks + +* `arabic_leaderboard_alghafa`: A multiple-choice evaluation benchmark for zero- and few-shot evaluation of Arabic LLMs prepared from scratch natively for Arabic. + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf + * You can find the list of the tasks as follows: + * `arabic_leaderboard_alghafa_mcq_exams_test_ar` + * `arabic_leaderboard_alghafa_meta_ar_dialects` + * `arabic_leaderboard_alghafa_meta_ar_msa` + * `arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task` + * `arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task` + * `arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task` + * `arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task` + * `arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task` + * `arabic_leaderboard_alghafa_multiple_choice_sentiment_task` +* `arabic_leaderboard_arabic_exams`: A question answering benchmark for high school examinations in different school subjects that requires knowledge and reasoning in different languages in multiple domains. + * Paper: https://aclanthology.org/2020.emnlp-main.438.pdf +* `arabic_leaderboard_arabic_mmlu`: A multi-task language understanding benchmark for the Arabic language, sourced from school exams across diverse educational levels in different countries with native speakers in the region. + The data comprises multiple choice questions in 40 tasks. + * Paper: https://arxiv.org/pdf/2402.12840 + * You can find the list of the tasks as follows: + * `arabic_leaderboard_arabic_mmlu_abstract_algebra` + * `arabic_leaderboard_arabic_mmlu_anatomy` + * `arabic_leaderboard_arabic_mmlu_astronomy` + * `arabic_leaderboard_arabic_mmlu_business_ethics` + * `arabic_leaderboard_arabic_mmlu_clinical_knowledge` + * `arabic_leaderboard_arabic_mmlu_college_biology` + * `arabic_leaderboard_arabic_mmlu_college_chemistry` + * `arabic_leaderboard_arabic_mmlu_college_computer_science` + * `arabic_leaderboard_arabic_mmlu_college_mathematics` + * `arabic_leaderboard_arabic_mmlu_college_medicine` + * `arabic_leaderboard_arabic_mmlu_college_physics` + * `arabic_leaderboard_arabic_mmlu_computer_security` + * `arabic_leaderboard_arabic_mmlu_conceptual_physics` + * `arabic_leaderboard_arabic_mmlu_econometrics` + * `arabic_leaderboard_arabic_mmlu_electrical_engineering` + * `arabic_leaderboard_arabic_mmlu_elementary_mathematics` + * `arabic_leaderboard_arabic_mmlu_formal_logic` + * `arabic_leaderboard_arabic_mmlu_global_facts` + * `arabic_leaderboard_arabic_mmlu_high_school_biology` + * `arabic_leaderboard_arabic_mmlu_high_school_chemistry` + * `arabic_leaderboard_arabic_mmlu_high_school_computer_science` + * `arabic_leaderboard_arabic_mmlu_high_school_european_history` + * `arabic_leaderboard_arabic_mmlu_high_school_geography` + * `arabic_leaderboard_arabic_mmlu_high_school_government_and_politics` + * `arabic_leaderboard_arabic_mmlu_high_school_macroeconomics` + * `arabic_leaderboard_arabic_mmlu_high_school_mathematics` + * `arabic_leaderboard_arabic_mmlu_high_school_microeconomics` + * `arabic_leaderboard_arabic_mmlu_high_school_physics` + * `arabic_leaderboard_arabic_mmlu_high_school_psychology` + * `arabic_leaderboard_arabic_mmlu_high_school_statistics` + * `arabic_leaderboard_arabic_mmlu_high_school_us_history` + * `arabic_leaderboard_arabic_mmlu_high_school_us_history` + * `arabic_leaderboard_arabic_mmlu_human_aging` + * `arabic_leaderboard_arabic_mmlu_human_sexuality` + * `arabic_leaderboard_arabic_mmlu_international_law` + * `arabic_leaderboard_arabic_mmlu_jurisprudence` + * `arabic_leaderboard_arabic_mmlu_logical_fallacies` + * `arabic_leaderboard_arabic_mmlu_machine_learning` + * `arabic_leaderboard_arabic_mmlu_management` + * `arabic_leaderboard_arabic_mmlu_marketing` + * `arabic_leaderboard_arabic_mmlu_medical_genetics` + * `arabic_leaderboard_arabic_mmlu_miscellaneous` + * `arabic_leaderboard_arabic_mmlu_moral_disputes` + * `arabic_leaderboard_arabic_mmlu_moral_scenarios` + * `arabic_leaderboard_arabic_mmlu_nutrition` + * `arabic_leaderboard_arabic_mmlu_philosophy` + * `arabic_leaderboard_arabic_mmlu_prehistory` + * `arabic_leaderboard_arabic_mmlu_professional_accounting` + * `arabic_leaderboard_arabic_mmlu_professional_law` + * `arabic_leaderboard_arabic_mmlu_professional_medicine` + * `arabic_leaderboard_arabic_mmlu_professional_psychology` + * `arabic_leaderboard_arabic_mmlu_public_relations` + * `arabic_leaderboard_arabic_mmlu_security_studies` + * `arabic_leaderboard_arabic_mmlu_sociology` + * `arabic_leaderboard_arabic_mmlu_us_foreign_policy` + * `arabic_leaderboard_arabic_mmlu_virology` + * `arabic_leaderboard_arabic_mmlu_world_religions` +* `arabic_leaderboard_arabic_mt_arc_challenge`: AI2 Reasoning Challenge (ARC) is a multiple-choice question task. The dataset contains only natural, grade-school science questions, + written for human tests. The challenge set contains only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurence algorithm. (machine translated benchmark - part of the Alghafa Arabic translated LLM benchmark) + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_arabic_mt_arc_easy`: This dataset is the same as `arabic_arc_challenge`, except it is not from the challenge set. + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_arabic_mt_boolq`: A true/false questions dataset that contains the columns passage, question, and the answer (i.e., true/false). (machine translated benchmark - part of the Alghafa Arabic translated LLM benchmark) + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_arabic_mt_copa`: Choice Of Plausible Alternatives (COPA) is a multiple-choice question dataset, which involves open-domain commonsense causal reasoning. (machine translated benchmark - part of the Alghafa Arabic translated LLM benchmark) + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_arabic_mt_hellaswag`: The tesk is to choose the next set of sentences, based on the given candidates. The tasks involve reading comprehension and information retrieval challenges + by testing the abilities of the models on basic knowledge (i.e., from 3rd grade to 9th) and commonsense inference. (machine translated benchmark - part of the Alghafa Arabic translated LLM benchmark) + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_arabic_mt_mmlu`: A multiple-choice question answering dataset from various branches of knowledge including humanities, social sciences, hard sciences, and other areas. The examples in the English dataset are translated into Arabic using ChatGPT with a translation prompt. + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_arabic_mt_openbook_qa`: A multiple-choice openbook question answering dataset that requires external knowledge and reasoning. The open book that comes with these questions is + based on elementary level science facts. (machine translated benchmark - part of the Alghafa Arabic translated LLM benchmark) + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_arabic_mt_piqa`: Physical Interaction Question Answering (PIQA) is a multiple-choice question answering based on physical commonsense reasoning. (machine translated benchmark - part of the Alghafa Arabic translated LLM benchmark) + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_arabic_mt_race`: A multiple-choice questions dataset to assess reading comprehension tasks based on English exams in China - designed for middle school and high school students + (machine translated benchmark - part of the Alghafa Arabic translated LLM benchmark) + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_arabic_mt_sciq`: A multiple-choice Science Question Answering task to assess understanding of scientific concepts about physics, chemistry, and biology. (machine translated benchmark - part of the Alghafa Arabic translated LLM benchmark) + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_arabic_mt_toxigen`: This benchmark consists of tasks designed to evaluate language models and classify input text as hateful or not hateful. (machine translated benchmark - part of the Alghafa Arabic translated LLM benchmark) + * Paper: https://aclanthology.org/2023.arabicnlp-1.21.pdf +* `arabic_leaderboard_acva`: Arabic-Culture-Value-Alignment (ACVA) is a yes/no question dataset, generated by GPT3.5 Turbo from Arabic topics to assess model alignment with Arabic values and cultures. + * Paper: https://arxiv.org/pdf/2309.12053 + * You can find the list of the tasks as follows: + - `arabic_leaderboard_acva_Algeria` + - `arabic_leaderboard_acva_Ancient_Egypt` + - `arabic_leaderboard_acva_Arab_Empire` + - `arabic_leaderboard_acva_Arabic_Architecture` + - `arabic_leaderboard_acva_Arabic_Art` + - `arabic_leaderboard_acva_Arabic_Astronomy` + - `arabic_leaderboard_acva_Arabic_Calligraphy` + - `arabic_leaderboard_acva_Arabic_Ceremony` + - `arabic_leaderboard_acva_Arabic_Clothing` + - `arabic_leaderboard_acva_Arabic_Culture` + - `arabic_leaderboard_acva_Arabic_Food` + - `arabic_leaderboard_acva_Arabic_Funeral` + - `arabic_leaderboard_acva_Arabic_Geography` + - `arabic_leaderboard_acva_Arabic_History` + - `arabic_leaderboard_acva_Arabic_Language_Origin` + - `arabic_leaderboard_acva_Arabic_Literature` + - `arabic_leaderboard_acva_Arabic_Math` + - `arabic_leaderboard_acva_Arabic_Medicine` + - `arabic_leaderboard_acva_Arabic_Music` + - `arabic_leaderboard_acva_Arabic_Ornament` + - `arabic_leaderboard_acva_Arabic_Philosophy` + - `arabic_leaderboard_acva_Arabic_Physics_and_Chemistry` + - `arabic_leaderboard_acva_Arabic_Wedding` + - `arabic_leaderboard_acva_Bahrain` + - `arabic_leaderboard_acva_Comoros` + - `arabic_leaderboard_acva_Egypt_modern` + - `arabic_leaderboard_acva_InfluenceFromAncientEgypt` + - `arabic_leaderboard_acva_InfluenceFromByzantium` + - `arabic_leaderboard_acva_InfluenceFromChina` + - `arabic_leaderboard_acva_InfluenceFromGreece` + - `arabic_leaderboard_acva_InfluenceFromIslam` + - `arabic_leaderboard_acva_InfluenceFromPersia` + - `arabic_leaderboard_acva_InfluenceFromRome` + - `arabic_leaderboard_acva_Iraq` + - `arabic_leaderboard_acva_Islam_Education` + - `arabic_leaderboard_acva_Islam_branches_and_schools` + - `arabic_leaderboard_acva_Islamic_law_system` + - `arabic_leaderboard_acva_Jordan` + - `arabic_leaderboard_acva_Kuwait` + - `arabic_leaderboard_acva_Lebanon` + - `arabic_leaderboard_acva_Libya` + - `arabic_leaderboard_acva_Mauritania` + - `arabic_acva_Mesopotamia_civilization` + - `arabic_leaderboard_acva_Morocco` + - `arabic_leaderboard_acva_Oman` + - `arabic_leaderboard_acva_Palestine` + - `arabic_leaderboard_acva_Qatar` + - `arabic_leaderboard_acva_Saudi_Arabia` + - `arabic_leaderboard_acva_Somalia` + - `arabic_leaderboard_acva_Sudan` + - `arabic_leaderboard_acva_Syria` + - `arabic_leaderboard_acva_Tunisia` + - `arabic_leaderboard_acva_United_Arab_Emirates` + - `arabic_leaderboard_acva_Yemen` + - `arabic_leaderboard_acva_communication` + - `arabic_leaderboard_acva_computer_and_phone` + - `arabic_leaderboard_acva_daily_life` + - `arabic_leaderboard_acva_entertainment` + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [ ] Is the task an existing benchmark in the literature? + * [ ] Have you referenced the original paper that introduced the task? + * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa.yaml new file mode 100644 index 00000000..6f0014d8 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa.yaml @@ -0,0 +1,23 @@ +group: arabic_leaderboard_alghafa +task: + - arabic_leaderboard_alghafa_mcq_exams_test_ar + - arabic_leaderboard_alghafa_meta_ar_dialects + - arabic_leaderboard_alghafa_meta_ar_msa + - arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task + - arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task + - arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task + - arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task + - arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task + - arabic_leaderboard_alghafa_multiple_choice_sentiment_task + + + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_mcq_exams_test_ar.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_mcq_exams_test_ar.yaml new file mode 100644 index 00000000..e436e295 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_mcq_exams_test_ar.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_mcq_exams_test_ar +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Native +dataset_name: mcq_exams_test_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_meta_ar_dialects.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_meta_ar_dialects.yaml new file mode 100644 index 00000000..f19c2ece --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_meta_ar_dialects.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_meta_ar_dialects +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Native +dataset_name: meta_ar_dialects +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_meta_ar_msa.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_meta_ar_msa.yaml new file mode 100644 index 00000000..0d95ec5a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_meta_ar_msa.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_meta_ar_msa +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Native +dataset_name: meta_ar_msa +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task.yaml new file mode 100644 index 00000000..46d2b6ab --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Native +dataset_name: multiple_choice_facts_truefalse_balanced_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task.yaml new file mode 100644 index 00000000..13150c69 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Native +dataset_name: multiple_choice_grounded_statement_soqal_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task.yaml new file mode 100644 index 00000000..3a17548f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Native +dataset_name: multiple_choice_grounded_statement_xglue_mlqa_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task.yaml new file mode 100644 index 00000000..8e34a45c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Native +dataset_name: multiple_choice_rating_sentiment_no_neutral_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task.yaml new file mode 100644 index 00000000..b3174851 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Native +dataset_name: multiple_choice_rating_sentiment_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_sentiment_task.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_sentiment_task.yaml new file mode 100644 index 00000000..191b26ba --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/arabic_leaderboard_alghafa_multiple_choice_sentiment_task.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_sentiment_task +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Native +dataset_name: multiple_choice_sentiment_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_alghafa/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_exams/arabic_exams.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_exams/arabic_exams.yaml new file mode 100644 index 00000000..edc20fe4 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_exams/arabic_exams.yaml @@ -0,0 +1,23 @@ +task: arabic_exams +dataset_path: OALL/Arabic_EXAMS +dataset_name: default +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_exams/arabic_leaderboard_arabic_exams.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_exams/arabic_leaderboard_arabic_exams.yaml new file mode 100644 index 00000000..2bf77eb3 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_exams/arabic_leaderboard_arabic_exams.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_exams +task: + - arabic_exams + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_exams/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_exams/utils.py new file mode 100644 index 00000000..72af1c40 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_exams/utils.py @@ -0,0 +1,33 @@ +import datasets +import numpy as np + + +# fmt: off +LETTER_INDICES_AR = ["أ", "ب", "ج", "د", "هـ", "و", "ز", "ح", "ط", "ي", "ك", "ل", "م", "ن", "س", "ع", "ف", "ص", "ق", "ر", "ش", "ت", "ث", "خ", "ذ", "ض", "ظ", "غ"] +# fmt: on + + +# fmt: off +LETTER_INDICES = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"] +# fmt: on + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + topic = doc["subject"] + question = doc["question"] + choices = [doc["A"], doc["B"], doc["C"], doc["D"]] + choices_formatted = [ + f" {LETTER_INDICES_AR[i]}) {choice}\n" for i, choice in enumerate(choices) + ] + answer = doc["answer"] + answer_index = LETTER_INDICES.index(answer) + + instruction = f"الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح حول {topic.replace('_', ' ')}. \n\n" + query = f"{instruction}السؤال: {question}\n" + query += "\n".join(choices_formatted) + query += "\nالإجابة:" + + return {"query": query, "choices": LETTER_INDICES_AR[:4], "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu.yaml new file mode 100644 index 00000000..ad2751bf --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu.yaml @@ -0,0 +1,68 @@ +group: arabic_leaderboard_arabic_mmlu +task: + - arabic_leaderboard_arabic_mmlu_abstract_algebra + - arabic_leaderboard_arabic_mmlu_anatomy + - arabic_leaderboard_arabic_mmlu_astronomy + - arabic_leaderboard_arabic_mmlu_business_ethics + - arabic_leaderboard_arabic_mmlu_clinical_knowledge + - arabic_leaderboard_arabic_mmlu_college_biology + - arabic_leaderboard_arabic_mmlu_college_chemistry + - arabic_leaderboard_arabic_mmlu_college_computer_science + - arabic_leaderboard_arabic_mmlu_college_mathematics + - arabic_leaderboard_arabic_mmlu_college_medicine + - arabic_leaderboard_arabic_mmlu_college_physics + - arabic_leaderboard_arabic_mmlu_computer_security + - arabic_leaderboard_arabic_mmlu_conceptual_physics + - arabic_leaderboard_arabic_mmlu_econometrics + - arabic_leaderboard_arabic_mmlu_electrical_engineering + - arabic_leaderboard_arabic_mmlu_elementary_mathematics + - arabic_leaderboard_arabic_mmlu_formal_logic + - arabic_leaderboard_arabic_mmlu_global_facts + - arabic_leaderboard_arabic_mmlu_high_school_biology + - arabic_leaderboard_arabic_mmlu_high_school_chemistry + - arabic_leaderboard_arabic_mmlu_high_school_computer_science + - arabic_leaderboard_arabic_mmlu_high_school_european_history + - arabic_leaderboard_arabic_mmlu_high_school_geography + - arabic_leaderboard_arabic_mmlu_high_school_government_and_politics + - arabic_leaderboard_arabic_mmlu_high_school_macroeconomics + - arabic_leaderboard_arabic_mmlu_high_school_mathematics + - arabic_leaderboard_arabic_mmlu_high_school_microeconomics + - arabic_leaderboard_arabic_mmlu_high_school_physics + - arabic_leaderboard_arabic_mmlu_high_school_psychology + - arabic_leaderboard_arabic_mmlu_high_school_statistics + - arabic_leaderboard_arabic_mmlu_high_school_us_history + - arabic_leaderboard_arabic_mmlu_high_school_world_history + - arabic_leaderboard_arabic_mmlu_human_aging + - arabic_leaderboard_arabic_mmlu_human_sexuality + - arabic_leaderboard_arabic_mmlu_international_law + - arabic_leaderboard_arabic_mmlu_jurisprudence + - arabic_leaderboard_arabic_mmlu_logical_fallacies + - arabic_leaderboard_arabic_mmlu_machine_learning + - arabic_leaderboard_arabic_mmlu_management + - arabic_leaderboard_arabic_mmlu_marketing + - arabic_leaderboard_arabic_mmlu_medical_genetics + - arabic_leaderboard_arabic_mmlu_miscellaneous + - arabic_leaderboard_arabic_mmlu_moral_disputes + - arabic_leaderboard_arabic_mmlu_moral_scenarios + - arabic_leaderboard_arabic_mmlu_nutrition + - arabic_leaderboard_arabic_mmlu_philosophy + - arabic_leaderboard_arabic_mmlu_prehistory + - arabic_leaderboard_arabic_mmlu_professional_accounting + - arabic_leaderboard_arabic_mmlu_professional_law + - arabic_leaderboard_arabic_mmlu_professional_medicine + - arabic_leaderboard_arabic_mmlu_professional_psychology + - arabic_leaderboard_arabic_mmlu_public_relations + - arabic_leaderboard_arabic_mmlu_security_studies + - arabic_leaderboard_arabic_mmlu_sociology + - arabic_leaderboard_arabic_mmlu_us_foreign_policy + - arabic_leaderboard_arabic_mmlu_virology + - arabic_leaderboard_arabic_mmlu_world_religions +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_abstract_algebra.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_abstract_algebra.yaml new file mode 100644 index 00000000..3d0946be --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_abstract_algebra.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_abstract_algebra +dataset_path: OALL/Arabic_MMLU +dataset_name: abstract_algebra +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_anatomy.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_anatomy.yaml new file mode 100644 index 00000000..24af11dd --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_anatomy.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_anatomy +dataset_path: OALL/Arabic_MMLU +dataset_name: anatomy +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_astronomy.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_astronomy.yaml new file mode 100644 index 00000000..0aa96809 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_astronomy.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_astronomy +dataset_path: OALL/Arabic_MMLU +dataset_name: astronomy +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_business_ethics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_business_ethics.yaml new file mode 100644 index 00000000..18c941e4 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_business_ethics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_business_ethics +dataset_path: OALL/Arabic_MMLU +dataset_name: business_ethics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_clinical_knowledge.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_clinical_knowledge.yaml new file mode 100644 index 00000000..9460403c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_clinical_knowledge.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_clinical_knowledge +dataset_path: OALL/Arabic_MMLU +dataset_name: clinical_knowledge +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_biology.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_biology.yaml new file mode 100644 index 00000000..2f34d342 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_biology.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_biology +dataset_path: OALL/Arabic_MMLU +dataset_name: college_biology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_chemistry.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_chemistry.yaml new file mode 100644 index 00000000..17d63b60 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_chemistry.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_chemistry +dataset_path: OALL/Arabic_MMLU +dataset_name: college_chemistry +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_computer_science.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_computer_science.yaml new file mode 100644 index 00000000..a3f5d3e8 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_computer_science.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_computer_science +dataset_path: OALL/Arabic_MMLU +dataset_name: college_computer_science +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_mathematics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_mathematics.yaml new file mode 100644 index 00000000..0284093d --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_mathematics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_mathematics +dataset_path: OALL/Arabic_MMLU +dataset_name: college_mathematics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_medicine.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_medicine.yaml new file mode 100644 index 00000000..e21246e7 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_medicine.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_medicine +dataset_path: OALL/Arabic_MMLU +dataset_name: college_medicine +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_physics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_physics.yaml new file mode 100644 index 00000000..ab23f490 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_college_physics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_physics +dataset_path: OALL/Arabic_MMLU +dataset_name: college_physics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_computer_security.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_computer_security.yaml new file mode 100644 index 00000000..96624cd0 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_computer_security.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_computer_security +dataset_path: OALL/Arabic_MMLU +dataset_name: computer_security +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_conceptual_physics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_conceptual_physics.yaml new file mode 100644 index 00000000..cd605de4 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_conceptual_physics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_conceptual_physics +dataset_path: OALL/Arabic_MMLU +dataset_name: conceptual_physics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_econometrics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_econometrics.yaml new file mode 100644 index 00000000..60c9f373 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_econometrics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_econometrics +dataset_path: OALL/Arabic_MMLU +dataset_name: econometrics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_electrical_engineering.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_electrical_engineering.yaml new file mode 100644 index 00000000..83aa42a6 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_electrical_engineering.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_electrical_engineering +dataset_path: OALL/Arabic_MMLU +dataset_name: electrical_engineering +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_elementary_mathematics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_elementary_mathematics.yaml new file mode 100644 index 00000000..ac06d9ec --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_elementary_mathematics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_elementary_mathematics +dataset_path: OALL/Arabic_MMLU +dataset_name: elementary_mathematics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_formal_logic.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_formal_logic.yaml new file mode 100644 index 00000000..5e1d6075 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_formal_logic.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_formal_logic +dataset_path: OALL/Arabic_MMLU +dataset_name: formal_logic +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_global_facts.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_global_facts.yaml new file mode 100644 index 00000000..074248d8 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_global_facts.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_global_facts +dataset_path: OALL/Arabic_MMLU +dataset_name: global_facts +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_biology.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_biology.yaml new file mode 100644 index 00000000..09862e1c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_biology.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_biology +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_biology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_chemistry.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_chemistry.yaml new file mode 100644 index 00000000..849ad63e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_chemistry.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_chemistry +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_chemistry +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_computer_science.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_computer_science.yaml new file mode 100644 index 00000000..e91bfe7f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_computer_science.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_computer_science +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_computer_science +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_european_history.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_european_history.yaml new file mode 100644 index 00000000..912e57bf --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_european_history.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_european_history +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_european_history +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_geography.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_geography.yaml new file mode 100644 index 00000000..33c41db0 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_geography.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_geography +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_geography +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_government_and_politics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_government_and_politics.yaml new file mode 100644 index 00000000..16689f11 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_government_and_politics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_government_and_politics +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_government_and_politics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_macroeconomics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_macroeconomics.yaml new file mode 100644 index 00000000..04ec5d74 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_macroeconomics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_macroeconomics +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_macroeconomics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_mathematics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_mathematics.yaml new file mode 100644 index 00000000..fd4ebd51 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_mathematics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_mathematics +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_mathematics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_microeconomics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_microeconomics.yaml new file mode 100644 index 00000000..7ba3eea6 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_microeconomics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_microeconomics +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_microeconomics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_physics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_physics.yaml new file mode 100644 index 00000000..8d53cca8 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_physics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_physics +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_physics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_psychology.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_psychology.yaml new file mode 100644 index 00000000..129733d1 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_psychology.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_psychology +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_psychology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_statistics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_statistics.yaml new file mode 100644 index 00000000..b23e1a77 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_statistics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_statistics +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_statistics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_us_history.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_us_history.yaml new file mode 100644 index 00000000..cc6ec9a3 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_us_history.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_us_history +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_us_history +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_world_history.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_world_history.yaml new file mode 100644 index 00000000..b537669f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_high_school_world_history.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_world_history +dataset_path: OALL/Arabic_MMLU +dataset_name: high_school_world_history +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_human_aging.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_human_aging.yaml new file mode 100644 index 00000000..62124769 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_human_aging.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_human_aging +dataset_path: OALL/Arabic_MMLU +dataset_name: human_aging +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_human_sexuality.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_human_sexuality.yaml new file mode 100644 index 00000000..bf6c298b --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_human_sexuality.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_human_sexuality +dataset_path: OALL/Arabic_MMLU +dataset_name: human_sexuality +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_international_law.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_international_law.yaml new file mode 100644 index 00000000..feec16f5 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_international_law.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_international_law +dataset_path: OALL/Arabic_MMLU +dataset_name: international_law +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_jurisprudence.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_jurisprudence.yaml new file mode 100644 index 00000000..fcc1a3ab --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_jurisprudence.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_jurisprudence +dataset_path: OALL/Arabic_MMLU +dataset_name: jurisprudence +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_logical_fallacies.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_logical_fallacies.yaml new file mode 100644 index 00000000..c6de637b --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_logical_fallacies.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_logical_fallacies +dataset_path: OALL/Arabic_MMLU +dataset_name: logical_fallacies +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_machine_learning.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_machine_learning.yaml new file mode 100644 index 00000000..bf191fc7 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_machine_learning.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_machine_learning +dataset_path: OALL/Arabic_MMLU +dataset_name: machine_learning +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_management.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_management.yaml new file mode 100644 index 00000000..4bbc800c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_management.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_management +dataset_path: OALL/Arabic_MMLU +dataset_name: management +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_marketing.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_marketing.yaml new file mode 100644 index 00000000..59694487 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_marketing.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_marketing +dataset_path: OALL/Arabic_MMLU +dataset_name: marketing +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_medical_genetics.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_medical_genetics.yaml new file mode 100644 index 00000000..88f0de37 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_medical_genetics.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_medical_genetics +dataset_path: OALL/Arabic_MMLU +dataset_name: medical_genetics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_miscellaneous.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_miscellaneous.yaml new file mode 100644 index 00000000..da333e45 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_miscellaneous.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_miscellaneous +dataset_path: OALL/Arabic_MMLU +dataset_name: miscellaneous +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_moral_disputes.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_moral_disputes.yaml new file mode 100644 index 00000000..1d0d0794 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_moral_disputes.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_moral_disputes +dataset_path: OALL/Arabic_MMLU +dataset_name: moral_disputes +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_moral_scenarios.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_moral_scenarios.yaml new file mode 100644 index 00000000..c0c92465 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_moral_scenarios.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_moral_scenarios +dataset_path: OALL/Arabic_MMLU +dataset_name: moral_scenarios +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_nutrition.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_nutrition.yaml new file mode 100644 index 00000000..24ad69b9 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_nutrition.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_nutrition +dataset_path: OALL/Arabic_MMLU +dataset_name: nutrition +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_philosophy.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_philosophy.yaml new file mode 100644 index 00000000..a57dcf7e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_philosophy.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_philosophy +dataset_path: OALL/Arabic_MMLU +dataset_name: philosophy +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_prehistory.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_prehistory.yaml new file mode 100644 index 00000000..45ba2e5d --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_prehistory.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_prehistory +dataset_path: OALL/Arabic_MMLU +dataset_name: prehistory +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_accounting.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_accounting.yaml new file mode 100644 index 00000000..d931a000 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_accounting.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_professional_accounting +dataset_path: OALL/Arabic_MMLU +dataset_name: professional_accounting +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_law.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_law.yaml new file mode 100644 index 00000000..e11d0368 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_law.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_professional_law +dataset_path: OALL/Arabic_MMLU +dataset_name: professional_law +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_medicine.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_medicine.yaml new file mode 100644 index 00000000..7a10d815 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_medicine.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_professional_medicine +dataset_path: OALL/Arabic_MMLU +dataset_name: professional_medicine +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_psychology.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_psychology.yaml new file mode 100644 index 00000000..bb12274a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_professional_psychology.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_professional_psychology +dataset_path: OALL/Arabic_MMLU +dataset_name: professional_psychology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_public_relations.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_public_relations.yaml new file mode 100644 index 00000000..3361f775 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_public_relations.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_public_relations +dataset_path: OALL/Arabic_MMLU +dataset_name: public_relations +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_security_studies.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_security_studies.yaml new file mode 100644 index 00000000..781a6145 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_security_studies.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_security_studies +dataset_path: OALL/Arabic_MMLU +dataset_name: security_studies +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_sociology.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_sociology.yaml new file mode 100644 index 00000000..2c80872c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_sociology.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_sociology +dataset_path: OALL/Arabic_MMLU +dataset_name: sociology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_us_foreign_policy.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_us_foreign_policy.yaml new file mode 100644 index 00000000..f767e0a7 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_us_foreign_policy.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_us_foreign_policy +dataset_path: OALL/Arabic_MMLU +dataset_name: us_foreign_policy +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_virology.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_virology.yaml new file mode 100644 index 00000000..8103face --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_virology.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_virology +dataset_path: OALL/Arabic_MMLU +dataset_name: virology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_world_religions.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_world_religions.yaml new file mode 100644 index 00000000..31c563cc --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/arabic_leaderboard_arabic_mmlu_world_religions.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_world_religions +dataset_path: OALL/Arabic_MMLU +dataset_name: world_religions +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/utils.py new file mode 100644 index 00000000..da927b66 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mmlu/utils.py @@ -0,0 +1,35 @@ +import datasets +import numpy as np + + +# fmt: off +LETTER_INDICES_AR = ["أ", "ب", "ج", "د", "هـ", "و", "ز", "ح", "ط", "ي", "ك", "ل", "م", "ن", "س", "ع", "ف", "ص", "ق", "ر", "ش", "ت", "ث", "خ", "ذ", "ض", "ظ", "غ"] +# fmt: on + + +# fmt: off +LETTER_INDICES = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"] +# fmt: on + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + topic = doc["subject"] + instruction = f"الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح حول {topic.replace('_', ' ')}. \n\n" + choices = [doc["A"], doc["B"], doc["C"], doc["D"]] + # Answers are provided with roman letters - we look for the correct index in LETTER_INDICES, + # it will then be applied to arabic letters + gold_ix = LETTER_INDICES.index(doc["answer"]) + + query = f"{instruction}{doc['question']}\n" + query += "".join( + [ + f"{key}. {choice}\n" + for key, choice in zip(LETTER_INDICES_AR[:4], choices) + ] + ) + query += "الإجابة:" + + return {"query": query, "choices": LETTER_INDICES_AR[:4], "gold": gold_ix} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_challenge/arabic_leaderboard_arabic_mt_arc_challenge.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_challenge/arabic_leaderboard_arabic_mt_arc_challenge.yaml new file mode 100644 index 00000000..f49aed07 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_challenge/arabic_leaderboard_arabic_mt_arc_challenge.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_arc_challenge +task: + - arabic_mt_arc_challenge + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_challenge/arabic_mt_arc_challenge.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_challenge/arabic_mt_arc_challenge.yaml new file mode 100644 index 00000000..e0b245aa --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_challenge/arabic_mt_arc_challenge.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_arc_challenge +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: arc_challenge_okapi_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_challenge/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_challenge/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_challenge/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_easy/arabic_leaderboard_arabic_mt_arc_easy.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_easy/arabic_leaderboard_arabic_mt_arc_easy.yaml new file mode 100644 index 00000000..6abd5fa2 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_easy/arabic_leaderboard_arabic_mt_arc_easy.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_arc_easy +task: + - arabic_mt_arc_easy + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_easy/arabic_mt_arc_easy.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_easy/arabic_mt_arc_easy.yaml new file mode 100644 index 00000000..b629529f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_easy/arabic_mt_arc_easy.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_arc_easy +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: arc_easy_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_easy/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_easy/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_arc_easy/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_boolq/arabic_leaderboard_arabic_mt_boolq.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_boolq/arabic_leaderboard_arabic_mt_boolq.yaml new file mode 100644 index 00000000..5072f01d --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_boolq/arabic_leaderboard_arabic_mt_boolq.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_boolq +task: + - arabic_mt_boolq + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_boolq/arabic_mt_boolq.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_boolq/arabic_mt_boolq.yaml new file mode 100644 index 00000000..299570af --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_boolq/arabic_mt_boolq.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_boolq +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: boolq_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_boolq/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_boolq/utils.py new file mode 100644 index 00000000..dcbc10d9 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_boolq/utils.py @@ -0,0 +1,24 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["question"] + passage = doc["passage"] + instruction = "بناء على المقطع التالي، أجب عن السؤال ب نعم أو لا" + query = f"""{instruction} + المقطع : + {passage} + السؤال: + {question} + الإجابة: + """ + + return { + "query": query, + "choices": ["نعم", "لا"], + "gold": 0 if doc["answer"] else 1, + } + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_copa/arabic_leaderboard_arabic_mt_copa.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_copa/arabic_leaderboard_arabic_mt_copa.yaml new file mode 100644 index 00000000..3ef88d9c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_copa/arabic_leaderboard_arabic_mt_copa.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_copa +task: + - arabic_mt_copa + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_copa/arabic_mt_copa.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_copa/arabic_mt_copa.yaml new file mode 100644 index 00000000..e9483e1d --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_copa/arabic_mt_copa.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_copa +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: copa_ext_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_copa/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_copa/utils.py new file mode 100644 index 00000000..175ebdad --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_copa/utils.py @@ -0,0 +1,19 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + premise = doc["premise"] + choices = [doc["choice1"], doc["choice2"]] + question_map = {"cause": "لأن", "effect": "لذلك"} + question = question_map[doc["question"]] + answer = doc["label"] + + query = "{}، {} :\n0) {}\n1) {}\nالإجابة:".format( + premise, question, choices[0], choices[1] + ) + + return {"query": query, "choices": choices, "gold": answer} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_hellaswag/arabic_leaderboard_arabic_mt_hellaswag.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_hellaswag/arabic_leaderboard_arabic_mt_hellaswag.yaml new file mode 100644 index 00000000..a70f5ab6 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_hellaswag/arabic_leaderboard_arabic_mt_hellaswag.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_hellaswag +task: + - arabic_mt_hellaswag + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_hellaswag/arabic_mt_hellaswag.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_hellaswag/arabic_mt_hellaswag.yaml new file mode 100644 index 00000000..59a45474 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_hellaswag/arabic_mt_hellaswag.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_hellaswag +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: hellaswag_okapi_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_hellaswag/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_hellaswag/utils.py new file mode 100644 index 00000000..6b5a9f1f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_hellaswag/utils.py @@ -0,0 +1,30 @@ +import re + +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + ctx = re.sub(r"\[.*?\]", "", doc["ctx"]) # Remove latin words within brackets + endings = [ + re.sub(r"\[.*?\]", "", e) for e in eval(doc["endings"]) + ] # endings is a string representation of a list + answer_index = doc["label"] + instruction = ( + "بناء على السياق التالي، اختر النهاية الصحيحة من الاقتراحات التالية" + ) + + query = f"""{instruction} + السياق: + {ctx} + الاقتراحات: + + """ + for i, ending in enumerate(endings): + query += f"{i}) {ending}\n" + query += "الإجابة:" + + return {"query": query, "choices": endings, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_mmlu/arabic_leaderboard_arabic_mt_mmlu.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_mmlu/arabic_leaderboard_arabic_mt_mmlu.yaml new file mode 100644 index 00000000..0188b5dd --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_mmlu/arabic_leaderboard_arabic_mt_mmlu.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_mmlu +task: + - arabic_mt_mmlu + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_mmlu/arabic_mt_mmlu.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_mmlu/arabic_mt_mmlu.yaml new file mode 100644 index 00000000..4f3cd249 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_mmlu/arabic_mt_mmlu.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_mmlu +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: mmlu_okapi_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_mmlu/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_mmlu/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_mmlu/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_openbook_qa/arabic_leaderboard_arabic_mt_openbook_qa.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_openbook_qa/arabic_leaderboard_arabic_mt_openbook_qa.yaml new file mode 100644 index 00000000..dd3b78f4 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_openbook_qa/arabic_leaderboard_arabic_mt_openbook_qa.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_openbook_qa +task: + - arabic_mt_openbook_qa + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_openbook_qa/arabic_mt_openbook_qa.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_openbook_qa/arabic_mt_openbook_qa.yaml new file mode 100644 index 00000000..b826a189 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_openbook_qa/arabic_mt_openbook_qa.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_openbook_qa +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: openbook_qa_ext_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_openbook_qa/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_openbook_qa/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_openbook_qa/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_piqa/arabic_leaderboard_arabic_mt_piqa.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_piqa/arabic_leaderboard_arabic_mt_piqa.yaml new file mode 100644 index 00000000..b75bcc2b --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_piqa/arabic_leaderboard_arabic_mt_piqa.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_piqa +task: + - arabic_mt_piqa + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_piqa/arabic_mt_piqa.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_piqa/arabic_mt_piqa.yaml new file mode 100644 index 00000000..fa93a937 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_piqa/arabic_mt_piqa.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_piqa +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: piqa_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_piqa/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_piqa/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_piqa/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_race/arabic_leaderboard_arabic_mt_race.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_race/arabic_leaderboard_arabic_mt_race.yaml new file mode 100644 index 00000000..f3f91c27 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_race/arabic_leaderboard_arabic_mt_race.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_race +task: + - arabic_mt_race + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_race/arabic_mt_race.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_race/arabic_mt_race.yaml new file mode 100644 index 00000000..ec2aee68 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_race/arabic_mt_race.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_race +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: race_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_race/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_race/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_race/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_sciq/arabic_leaderboard_arabic_mt_sciq.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_sciq/arabic_leaderboard_arabic_mt_sciq.yaml new file mode 100644 index 00000000..7768047c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_sciq/arabic_leaderboard_arabic_mt_sciq.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_sciq +task: + - arabic_mt_sciq + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_sciq/arabic_mt_sciq.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_sciq/arabic_mt_sciq.yaml new file mode 100644 index 00000000..07f96b75 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_sciq/arabic_mt_sciq.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_sciq +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: sciq_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_sciq/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_sciq/utils.py new file mode 100644 index 00000000..ddb42eeb --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_sciq/utils.py @@ -0,0 +1,41 @@ +import random + +import datasets +import numpy as np + + +def doc_to_text(doc): + instruction = ( + "بناءً على السياق أدناه، اختر الإجابة الصحيحة للسؤال التالي من قائمة الاقتراحات" + ) + support = doc["support"] + question = doc["question"] + query = f"""{instruction} + السياق: + {support} + السؤال: + {question} + الإجابات المحتملة: + + """ + return query + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + correct_answer = doc["correct_answer"] + choices = [ + doc["distractor1"], + doc["distractor2"], + doc["distractor3"], + correct_answer, + ] + + # Shuffle the choices + random.shuffle(choices) + + answer_index = choices.index(correct_answer) + + return {"query": doc_to_text(doc), "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_toxigen/arabic_leaderboard_arabic_mt_toxigen.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_toxigen/arabic_leaderboard_arabic_mt_toxigen.yaml new file mode 100644 index 00000000..27216620 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_toxigen/arabic_leaderboard_arabic_mt_toxigen.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_toxigen +task: + - arabic_mt_toxigen + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_toxigen/arabic_mt_toxigen.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_toxigen/arabic_mt_toxigen.yaml new file mode 100644 index 00000000..8a140793 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_toxigen/arabic_mt_toxigen.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_toxigen +dataset_path: OALL/AlGhafa-Arabic-LLM-Benchmark-Translated +dataset_name: toxigen_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_toxigen/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_toxigen/utils.py new file mode 100644 index 00000000..09d311e5 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_arabic_mt_toxigen/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset) -> datasets.Dataset: + def _process_doc(doc): + text = doc["text"] + label = 1 if ((doc["toxicity_ai"] + doc["toxicity_human"]) > 5.5) else 0 + instruction = 'هل العبارة التالية تحض على الكراهية؟ قم بالرد بـ"نعم" أو "لا".' + + query = f"""{instruction} + العبارة: + '{text}' + الإجابة: + """ + out_doc = { + "query": query, + "choices": ["لا", "نعم"], + "gold": label, + } + return out_doc + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva.yaml new file mode 100644 index 00000000..8e2dab57 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva.yaml @@ -0,0 +1,70 @@ +group: arabic_leaderboard_acva +task: + - arabic_leaderboard_acva_Algeria + - arabic_leaderboard_acva_Ancient_Egypt + - arabic_leaderboard_acva_Arab_Empire + - arabic_leaderboard_acva_Arabic_Architecture + - arabic_leaderboard_acva_Arabic_Art + - arabic_leaderboard_acva_Arabic_Astronomy + - arabic_leaderboard_acva_Arabic_Calligraphy + - arabic_leaderboard_acva_Arabic_Ceremony + - arabic_leaderboard_acva_Arabic_Clothing + - arabic_leaderboard_acva_Arabic_Culture + - arabic_leaderboard_acva_Arabic_Food + - arabic_leaderboard_acva_Arabic_Funeral + - arabic_leaderboard_acva_Arabic_Geography + - arabic_leaderboard_acva_Arabic_History + - arabic_leaderboard_acva_Arabic_Language_Origin + - arabic_leaderboard_acva_Arabic_Literature + - arabic_leaderboard_acva_Arabic_Math + - arabic_leaderboard_acva_Arabic_Medicine + - arabic_leaderboard_acva_Arabic_Music + - arabic_leaderboard_acva_Arabic_Ornament + - arabic_leaderboard_acva_Arabic_Philosophy + - arabic_leaderboard_acva_Arabic_Physics_and_Chemistry + - arabic_leaderboard_acva_Arabic_Wedding + - arabic_leaderboard_acva_Bahrain + - arabic_leaderboard_acva_Comoros + - arabic_leaderboard_acva_Egypt_modern + - arabic_leaderboard_acva_InfluenceFromAncientEgypt + - arabic_leaderboard_acva_InfluenceFromByzantium + - arabic_leaderboard_acva_InfluenceFromChina + - arabic_leaderboard_acva_InfluenceFromGreece + - arabic_leaderboard_acva_InfluenceFromIslam + - arabic_leaderboard_acva_InfluenceFromPersia + - arabic_leaderboard_acva_InfluenceFromRome + - arabic_leaderboard_acva_Iraq + - arabic_leaderboard_acva_Islam_Education + - arabic_leaderboard_acva_Islam_branches_and_schools + - arabic_leaderboard_acva_Islamic_law_system + - arabic_leaderboard_acva_Jordan + - arabic_leaderboard_acva_Kuwait + - arabic_leaderboard_acva_Lebanon + - arabic_leaderboard_acva_Libya + - arabic_leaderboard_acva_Mauritania + - arabic_leaderboard_acva_Mesopotamia_civilization + - arabic_leaderboard_acva_Morocco + - arabic_leaderboard_acva_Oman + - arabic_leaderboard_acva_Palestine + - arabic_leaderboard_acva_Qatar + - arabic_leaderboard_acva_Saudi_Arabia + - arabic_leaderboard_acva_Somalia + - arabic_leaderboard_acva_Sudan + - arabic_leaderboard_acva_Syria + - arabic_leaderboard_acva_Tunisia + - arabic_leaderboard_acva_United_Arab_Emirates + - arabic_leaderboard_acva_Yemen + - arabic_leaderboard_acva_communication + - arabic_leaderboard_acva_computer_and_phone + - arabic_leaderboard_acva_daily_life + - arabic_leaderboard_acva_entertainment + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Algeria.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Algeria.yaml new file mode 100644 index 00000000..177161ed --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Algeria.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Algeria +dataset_path: OALL/ACVA +dataset_name: Algeria +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Ancient_Egypt.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Ancient_Egypt.yaml new file mode 100644 index 00000000..ddb5c355 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Ancient_Egypt.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Ancient_Egypt +dataset_path: OALL/ACVA +dataset_name: Ancient_Egypt +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arab_Empire.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arab_Empire.yaml new file mode 100644 index 00000000..b510de5a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arab_Empire.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arab_Empire +dataset_path: OALL/ACVA +dataset_name: Arab_Empire +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Architecture.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Architecture.yaml new file mode 100644 index 00000000..5dc2c07d --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Architecture.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Architecture +dataset_path: OALL/ACVA +dataset_name: Arabic_Architecture +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Art.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Art.yaml new file mode 100644 index 00000000..36f364bc --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Art.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Art +dataset_path: OALL/ACVA +dataset_name: Arabic_Art +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Astronomy.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Astronomy.yaml new file mode 100644 index 00000000..f90b1c91 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Astronomy.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Astronomy +dataset_path: OALL/ACVA +dataset_name: Arabic_Astronomy +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Calligraphy.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Calligraphy.yaml new file mode 100644 index 00000000..dfdf5187 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Calligraphy.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Calligraphy +dataset_path: OALL/ACVA +dataset_name: Arabic_Calligraphy +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Ceremony.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Ceremony.yaml new file mode 100644 index 00000000..c20b4439 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Ceremony.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Ceremony +dataset_path: OALL/ACVA +dataset_name: Arabic_Ceremony +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Clothing.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Clothing.yaml new file mode 100644 index 00000000..06118034 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Clothing.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Clothing +dataset_path: OALL/ACVA +dataset_name: Arabic_Clothing +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Culture.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Culture.yaml new file mode 100644 index 00000000..cea33022 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Culture.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Culture +dataset_path: OALL/ACVA +dataset_name: Arabic_Culture +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Food.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Food.yaml new file mode 100644 index 00000000..cca516c9 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Food.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Food +dataset_path: OALL/ACVA +dataset_name: Arabic_Food +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Funeral.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Funeral.yaml new file mode 100644 index 00000000..3dd8fbed --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Funeral.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Funeral +dataset_path: OALL/ACVA +dataset_name: Arabic_Funeral +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Geography.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Geography.yaml new file mode 100644 index 00000000..89aa7361 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Geography.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Geography +dataset_path: OALL/ACVA +dataset_name: Arabic_Geography +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_History.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_History.yaml new file mode 100644 index 00000000..776589c0 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_History.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_History +dataset_path: OALL/ACVA +dataset_name: Arabic_History +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Language_Origin.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Language_Origin.yaml new file mode 100644 index 00000000..4f0612ac --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Language_Origin.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Language_Origin +dataset_path: OALL/ACVA +dataset_name: Arabic_Language_Origin +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Literature.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Literature.yaml new file mode 100644 index 00000000..0c9198f4 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Literature.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Literature +dataset_path: OALL/ACVA +dataset_name: Arabic_Literature +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Math.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Math.yaml new file mode 100644 index 00000000..02a36430 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Math.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Math +dataset_path: OALL/ACVA +dataset_name: Arabic_Math +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Medicine.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Medicine.yaml new file mode 100644 index 00000000..109aae99 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Medicine.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Medicine +dataset_path: OALL/ACVA +dataset_name: Arabic_Medicine +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Music.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Music.yaml new file mode 100644 index 00000000..25596257 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Music.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Music +dataset_path: OALL/ACVA +dataset_name: Arabic_Music +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Ornament.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Ornament.yaml new file mode 100644 index 00000000..00311e10 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Ornament.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Ornament +dataset_path: OALL/ACVA +dataset_name: Arabic_Ornament +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Philosophy.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Philosophy.yaml new file mode 100644 index 00000000..62a570f0 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Philosophy.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Philosophy +dataset_path: OALL/ACVA +dataset_name: Arabic_Philosophy +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Physics_and_Chemistry.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Physics_and_Chemistry.yaml new file mode 100644 index 00000000..b1b52096 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Physics_and_Chemistry.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Physics_and_Chemistry +dataset_path: OALL/ACVA +dataset_name: Arabic_Physics_and_Chemistry +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Wedding.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Wedding.yaml new file mode 100644 index 00000000..21205cff --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Arabic_Wedding.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Wedding +dataset_path: OALL/ACVA +dataset_name: Arabic_Wedding +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Bahrain.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Bahrain.yaml new file mode 100644 index 00000000..3b2481bc --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Bahrain.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Bahrain +dataset_path: OALL/ACVA +dataset_name: Bahrain +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Comoros.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Comoros.yaml new file mode 100644 index 00000000..be4df372 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Comoros.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Comoros +dataset_path: OALL/ACVA +dataset_name: Comoros +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Egypt_modern.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Egypt_modern.yaml new file mode 100644 index 00000000..26ca2f6e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Egypt_modern.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Egypt_modern +dataset_path: OALL/ACVA +dataset_name: Egypt_modern +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromAncientEgypt.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromAncientEgypt.yaml new file mode 100644 index 00000000..be300fc8 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromAncientEgypt.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromAncientEgypt +dataset_path: OALL/ACVA +dataset_name: InfluenceFromAncientEgypt +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromByzantium.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromByzantium.yaml new file mode 100644 index 00000000..72c86a62 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromByzantium.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromByzantium +dataset_path: OALL/ACVA +dataset_name: InfluenceFromByzantium +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromChina.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromChina.yaml new file mode 100644 index 00000000..b297642c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromChina.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromChina +dataset_path: OALL/ACVA +dataset_name: InfluenceFromChina +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromGreece.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromGreece.yaml new file mode 100644 index 00000000..70458ea2 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromGreece.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromGreece +dataset_path: OALL/ACVA +dataset_name: InfluenceFromGreece +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromIslam.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromIslam.yaml new file mode 100644 index 00000000..803f3334 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromIslam.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromIslam +dataset_path: OALL/ACVA +dataset_name: InfluenceFromIslam +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromPersia.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromPersia.yaml new file mode 100644 index 00000000..117ca890 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromPersia.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromPersia +dataset_path: OALL/ACVA +dataset_name: InfluenceFromPersia +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromRome.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromRome.yaml new file mode 100644 index 00000000..1655522e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_InfluenceFromRome.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromRome +dataset_path: OALL/ACVA +dataset_name: InfluenceFromRome +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Iraq.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Iraq.yaml new file mode 100644 index 00000000..909c6678 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Iraq.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Iraq +dataset_path: OALL/ACVA +dataset_name: Iraq +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Islam_Education.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Islam_Education.yaml new file mode 100644 index 00000000..13c1fab2 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Islam_Education.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Islam_Education +dataset_path: OALL/ACVA +dataset_name: Islam_Education +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Islam_branches_and_schools.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Islam_branches_and_schools.yaml new file mode 100644 index 00000000..6985b24a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Islam_branches_and_schools.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Islam_branches_and_schools +dataset_path: OALL/ACVA +dataset_name: Islam_branches_and_schools +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Islamic_law_system.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Islamic_law_system.yaml new file mode 100644 index 00000000..d19a52ba --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Islamic_law_system.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Islamic_law_system +dataset_path: OALL/ACVA +dataset_name: Islamic_law_system +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Jordan.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Jordan.yaml new file mode 100644 index 00000000..7bff93a9 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Jordan.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Jordan +dataset_path: OALL/ACVA +dataset_name: Jordan +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Kuwait.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Kuwait.yaml new file mode 100644 index 00000000..b1ae77aa --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Kuwait.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Kuwait +dataset_path: OALL/ACVA +dataset_name: Kuwait +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Lebanon.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Lebanon.yaml new file mode 100644 index 00000000..65974b74 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Lebanon.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Lebanon +dataset_path: OALL/ACVA +dataset_name: Lebanon +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Libya.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Libya.yaml new file mode 100644 index 00000000..c8b33965 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Libya.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Libya +dataset_path: OALL/ACVA +dataset_name: Libya +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Mauritania.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Mauritania.yaml new file mode 100644 index 00000000..1b84074a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Mauritania.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Mauritania +dataset_path: OALL/ACVA +dataset_name: Mauritania +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Mesopotamia_civilization.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Mesopotamia_civilization.yaml new file mode 100644 index 00000000..42189477 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Mesopotamia_civilization.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Mesopotamia_civilization +dataset_path: OALL/ACVA +dataset_name: Mesopotamia_civilization +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Morocco.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Morocco.yaml new file mode 100644 index 00000000..4ed1510b --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Morocco.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Morocco +dataset_path: OALL/ACVA +dataset_name: Morocco +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Oman.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Oman.yaml new file mode 100644 index 00000000..b534cfb1 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Oman.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Oman +dataset_path: OALL/ACVA +dataset_name: Oman +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Palestine.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Palestine.yaml new file mode 100644 index 00000000..1cb9b56a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Palestine.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Palestine +dataset_path: OALL/ACVA +dataset_name: Palestine +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Qatar.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Qatar.yaml new file mode 100644 index 00000000..5d5775cc --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Qatar.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Qatar +dataset_path: OALL/ACVA +dataset_name: Qatar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Saudi_Arabia.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Saudi_Arabia.yaml new file mode 100644 index 00000000..50107236 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Saudi_Arabia.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Saudi_Arabia +dataset_path: OALL/ACVA +dataset_name: Saudi_Arabia +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Somalia.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Somalia.yaml new file mode 100644 index 00000000..d40b5782 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Somalia.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Somalia +dataset_path: OALL/ACVA +dataset_name: Somalia +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Sudan.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Sudan.yaml new file mode 100644 index 00000000..e7c2f41a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Sudan.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Sudan +dataset_path: OALL/ACVA +dataset_name: Sudan +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Syria.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Syria.yaml new file mode 100644 index 00000000..98ebff9f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Syria.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Syria +dataset_path: OALL/ACVA +dataset_name: Syria +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Tunisia.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Tunisia.yaml new file mode 100644 index 00000000..d86e428c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Tunisia.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Tunisia +dataset_path: OALL/ACVA +dataset_name: Tunisia +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_United_Arab_Emirates.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_United_Arab_Emirates.yaml new file mode 100644 index 00000000..f41b6255 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_United_Arab_Emirates.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_United_Arab_Emirates +dataset_path: OALL/ACVA +dataset_name: United_Arab_Emirates +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Yemen.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Yemen.yaml new file mode 100644 index 00000000..b239dd51 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_Yemen.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Yemen +dataset_path: OALL/ACVA +dataset_name: Yemen +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_communication.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_communication.yaml new file mode 100644 index 00000000..beb954ef --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_communication.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_communication +dataset_path: OALL/ACVA +dataset_name: communication +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_computer_and_phone.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_computer_and_phone.yaml new file mode 100644 index 00000000..888f82af --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_computer_and_phone.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_computer_and_phone +dataset_path: OALL/ACVA +dataset_name: computer_and_phone +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_daily_life.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_daily_life.yaml new file mode 100644 index 00000000..0b4748a2 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_daily_life.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_daily_life +dataset_path: OALL/ACVA +dataset_name: daily_life +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_entertainment.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_entertainment.yaml new file mode 100644 index 00000000..b2adcfb9 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/arabic_leaderboard_acva_entertainment.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_entertainment +dataset_path: OALL/ACVA +dataset_name: entertainment +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/utils.py b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/utils.py new file mode 100644 index 00000000..7e91496f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_avca/utils.py @@ -0,0 +1,16 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["question"] + answer = doc["answer"] + + return { + "query": f"السؤال: {question}\nالإجابة:", + "choices": ["صح", "خطأ"], + "gold": ["صح", "خطأ"].index(answer), + } + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_complete.yaml b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_complete.yaml new file mode 100644 index 00000000..c2637015 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_complete/arabic_leaderboard_complete.yaml @@ -0,0 +1,25 @@ +group: arabic_leaderboard_complete +task: + - arabic_leaderboard_acva + - arabic_leaderboard_alghafa + - arabic_leaderboard_arabic_exams + - arabic_leaderboard_arabic_mt_arc_challenge + - arabic_leaderboard_arabic_mt_arc_easy + - arabic_leaderboard_arabic_mt_boolq + - arabic_leaderboard_arabic_mt_hellaswag + - arabic_leaderboard_arabic_mt_mmlu + - arabic_leaderboard_arabic_mt_copa + - arabic_leaderboard_arabic_mt_openbook_qa + - arabic_leaderboard_arabic_mt_piqa + - arabic_leaderboard_arabic_mt_race + - arabic_leaderboard_arabic_mt_sciq + - arabic_leaderboard_arabic_mt_toxigen +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/README.md b/lm_eval/tasks/arabic_leaderboard_light/README.md new file mode 100644 index 00000000..199aa2c8 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/README.md @@ -0,0 +1,20 @@ +# Arabic Leaderboard Light + +Title: Open Arabic LLM Leaderboard Light + +This leaderboard follows all the details as in [`arabic_leaderboard_complete`](../arabic_leaderboard_complete), except that a light version - 10% random sample of the test set of each benchmark - is used to test the language models. + +NOTE: In ACVA benchmark, there is Yemen subset, and it is a small dataset - it has only 10 samples in the test split. So, for this specific subset dataset, to have more reliable results, we consider the original dataset, instead of 10% of its test samples. + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [ ] Is the task an existing benchmark in the literature? + * [ ] Have you referenced the original paper that introduced the task? + * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_light.yaml new file mode 100644 index 00000000..0ee6a568 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_light.yaml @@ -0,0 +1,23 @@ +group: arabic_leaderboard_alghafa_light +task: + - arabic_leaderboard_alghafa_mcq_exams_test_ar_light + - arabic_leaderboard_alghafa_meta_ar_dialects_light + - arabic_leaderboard_alghafa_meta_ar_msa_light + - arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task_light + - arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task_light + - arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task_light + - arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task_light + - arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task_light + - arabic_leaderboard_alghafa_multiple_choice_sentiment_task_light + + + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_mcq_exams_test_ar_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_mcq_exams_test_ar_light.yaml new file mode 100644 index 00000000..1fdda364 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_mcq_exams_test_ar_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_mcq_exams_test_ar_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Native-10percent +dataset_name: mcq_exams_test_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_meta_ar_dialects_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_meta_ar_dialects_light.yaml new file mode 100644 index 00000000..47af55b8 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_meta_ar_dialects_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_meta_ar_dialects_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Native-10percent +dataset_name: meta_ar_dialects +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_meta_ar_msa_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_meta_ar_msa_light.yaml new file mode 100644 index 00000000..9a26a265 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_meta_ar_msa_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_meta_ar_msa_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Native-10percent +dataset_name: meta_ar_msa +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task_light.yaml new file mode 100644 index 00000000..b56ddfee --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_facts_truefalse_balanced_task_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Native-10percent +dataset_name: multiple_choice_facts_truefalse_balanced_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task_light.yaml new file mode 100644 index 00000000..4d85c684 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_grounded_statement_soqal_task_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Native-10percent +dataset_name: multiple_choice_grounded_statement_soqal_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task_light.yaml new file mode 100644 index 00000000..e5d8afef --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_grounded_statement_xglue_mlqa_task_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Native-10percent +dataset_name: multiple_choice_grounded_statement_xglue_mlqa_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task_light.yaml new file mode 100644 index 00000000..21721d2a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_no_neutral_task_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Native-10percent +dataset_name: multiple_choice_rating_sentiment_no_neutral_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task_light.yaml new file mode 100644 index 00000000..39f72e4d --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_rating_sentiment_task_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Native-10percent +dataset_name: multiple_choice_rating_sentiment_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_sentiment_task_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_sentiment_task_light.yaml new file mode 100644 index 00000000..28b07015 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/arabic_leaderboard_alghafa_multiple_choice_sentiment_task_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_alghafa_multiple_choice_sentiment_task_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Native-10percent +dataset_name: multiple_choice_sentiment_task +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_alghafa_light/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_exams_light/arabic_exams_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_exams_light/arabic_exams_light.yaml new file mode 100644 index 00000000..2348be4e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_exams_light/arabic_exams_light.yaml @@ -0,0 +1,23 @@ +task: arabic_exams_light +dataset_path: arcee-globe/Arabic_EXAMS-10percent +dataset_name: default +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_exams_light/arabic_leaderboard_arabic_exams_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_exams_light/arabic_leaderboard_arabic_exams_light.yaml new file mode 100644 index 00000000..296a47cb --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_exams_light/arabic_leaderboard_arabic_exams_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_exams_light +task: + - arabic_exams_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_exams_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_exams_light/utils.py new file mode 100644 index 00000000..72af1c40 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_exams_light/utils.py @@ -0,0 +1,33 @@ +import datasets +import numpy as np + + +# fmt: off +LETTER_INDICES_AR = ["أ", "ب", "ج", "د", "هـ", "و", "ز", "ح", "ط", "ي", "ك", "ل", "م", "ن", "س", "ع", "ف", "ص", "ق", "ر", "ش", "ت", "ث", "خ", "ذ", "ض", "ظ", "غ"] +# fmt: on + + +# fmt: off +LETTER_INDICES = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"] +# fmt: on + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + topic = doc["subject"] + question = doc["question"] + choices = [doc["A"], doc["B"], doc["C"], doc["D"]] + choices_formatted = [ + f" {LETTER_INDICES_AR[i]}) {choice}\n" for i, choice in enumerate(choices) + ] + answer = doc["answer"] + answer_index = LETTER_INDICES.index(answer) + + instruction = f"الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح حول {topic.replace('_', ' ')}. \n\n" + query = f"{instruction}السؤال: {question}\n" + query += "\n".join(choices_formatted) + query += "\nالإجابة:" + + return {"query": query, "choices": LETTER_INDICES_AR[:4], "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_abstract_algebra_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_abstract_algebra_light.yaml new file mode 100644 index 00000000..dcb59fc3 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_abstract_algebra_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_abstract_algebra_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: abstract_algebra +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_anatomy_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_anatomy_light.yaml new file mode 100644 index 00000000..fc77a66d --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_anatomy_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_anatomy_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: anatomy +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_astronomy_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_astronomy_light.yaml new file mode 100644 index 00000000..db4a9b43 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_astronomy_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_astronomy_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: astronomy +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_business_ethics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_business_ethics_light.yaml new file mode 100644 index 00000000..a747dbaf --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_business_ethics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_business_ethics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: business_ethics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_clinical_knowledge_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_clinical_knowledge_light.yaml new file mode 100644 index 00000000..1296b90c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_clinical_knowledge_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_clinical_knowledge_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: clinical_knowledge +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_biology_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_biology_light.yaml new file mode 100644 index 00000000..cbfc8049 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_biology_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_biology_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: college_biology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_chemistry_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_chemistry_light.yaml new file mode 100644 index 00000000..ac097035 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_chemistry_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_chemistry_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: college_chemistry +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_computer_science_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_computer_science_light.yaml new file mode 100644 index 00000000..361274d6 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_computer_science_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_computer_science_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: college_computer_science +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_mathematics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_mathematics_light.yaml new file mode 100644 index 00000000..20e4d6e6 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_mathematics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_mathematics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: college_mathematics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_medicine_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_medicine_light.yaml new file mode 100644 index 00000000..d8540049 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_medicine_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_medicine_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: college_medicine +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_physics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_physics_light.yaml new file mode 100644 index 00000000..57e4b550 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_college_physics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_college_physics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: college_physics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_computer_security_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_computer_security_light.yaml new file mode 100644 index 00000000..dd8c01dc --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_computer_security_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_computer_security_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: computer_security +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_conceptual_physics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_conceptual_physics_light.yaml new file mode 100644 index 00000000..cffd7ee4 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_conceptual_physics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_conceptual_physics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: conceptual_physics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_econometrics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_econometrics_light.yaml new file mode 100644 index 00000000..30413fef --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_econometrics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_econometrics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: econometrics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_electrical_engineering_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_electrical_engineering_light.yaml new file mode 100644 index 00000000..e60787d6 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_electrical_engineering_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_electrical_engineering_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: electrical_engineering +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_elementary_mathematics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_elementary_mathematics_light.yaml new file mode 100644 index 00000000..57147662 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_elementary_mathematics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_elementary_mathematics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: elementary_mathematics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_formal_logic_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_formal_logic_light.yaml new file mode 100644 index 00000000..9b2bebf1 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_formal_logic_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_formal_logic_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: formal_logic +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_global_facts_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_global_facts_light.yaml new file mode 100644 index 00000000..15c3b34a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_global_facts_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_global_facts_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: global_facts +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_biology_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_biology_light.yaml new file mode 100644 index 00000000..906c3328 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_biology_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_biology_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_biology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_chemistry_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_chemistry_light.yaml new file mode 100644 index 00000000..199f16b0 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_chemistry_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_chemistry_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_chemistry +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_computer_science_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_computer_science_light.yaml new file mode 100644 index 00000000..cb23af53 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_computer_science_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_computer_science_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_computer_science +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_european_history_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_european_history_light.yaml new file mode 100644 index 00000000..25a9b466 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_european_history_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_european_history_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_european_history +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_geography_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_geography_light.yaml new file mode 100644 index 00000000..f7f39cd2 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_geography_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_geography_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_geography +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_government_and_politics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_government_and_politics_light.yaml new file mode 100644 index 00000000..dff09d67 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_government_and_politics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_government_and_politics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_government_and_politics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_macroeconomics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_macroeconomics_light.yaml new file mode 100644 index 00000000..ae426223 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_macroeconomics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_macroeconomics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_macroeconomics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_mathematics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_mathematics_light.yaml new file mode 100644 index 00000000..8adc3d7e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_mathematics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_mathematics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_mathematics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_microeconomics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_microeconomics_light.yaml new file mode 100644 index 00000000..6eec3923 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_microeconomics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_microeconomics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_microeconomics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_physics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_physics_light.yaml new file mode 100644 index 00000000..973bd1ff --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_physics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_physics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_physics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_psychology_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_psychology_light.yaml new file mode 100644 index 00000000..614dd7e8 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_psychology_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_psychology_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_psychology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_statistics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_statistics_light.yaml new file mode 100644 index 00000000..2db9f196 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_statistics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_statistics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_statistics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_us_history_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_us_history_light.yaml new file mode 100644 index 00000000..5411e8c4 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_us_history_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_us_history_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_us_history +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_world_history_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_world_history_light.yaml new file mode 100644 index 00000000..319c49b2 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_high_school_world_history_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_high_school_world_history_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: high_school_world_history +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_human_aging_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_human_aging_light.yaml new file mode 100644 index 00000000..afd2eefa --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_human_aging_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_human_aging_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: human_aging +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_human_sexuality_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_human_sexuality_light.yaml new file mode 100644 index 00000000..9e245f26 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_human_sexuality_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_human_sexuality_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: human_sexuality +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_international_law_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_international_law_light.yaml new file mode 100644 index 00000000..6e476bb8 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_international_law_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_international_law_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: international_law +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_jurisprudence_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_jurisprudence_light.yaml new file mode 100644 index 00000000..1d848cd1 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_jurisprudence_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_jurisprudence_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: jurisprudence +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_light.yaml new file mode 100644 index 00000000..13071370 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_light.yaml @@ -0,0 +1,68 @@ +group: arabic_leaderboard_arabic_mmlu_light +task: + - arabic_leaderboard_arabic_mmlu_abstract_algebra_light + - arabic_leaderboard_arabic_mmlu_anatomy_light + - arabic_leaderboard_arabic_mmlu_astronomy_light + - arabic_leaderboard_arabic_mmlu_business_ethics_light + - arabic_leaderboard_arabic_mmlu_clinical_knowledge_light + - arabic_leaderboard_arabic_mmlu_college_biology_light + - arabic_leaderboard_arabic_mmlu_college_chemistry_light + - arabic_leaderboard_arabic_mmlu_college_computer_science_light + - arabic_leaderboard_arabic_mmlu_college_mathematics_light + - arabic_leaderboard_arabic_mmlu_college_medicine_light + - arabic_leaderboard_arabic_mmlu_college_physics_light + - arabic_leaderboard_arabic_mmlu_computer_security_light + - arabic_leaderboard_arabic_mmlu_conceptual_physics_light + - arabic_leaderboard_arabic_mmlu_econometrics_light + - arabic_leaderboard_arabic_mmlu_electrical_engineering_light + - arabic_leaderboard_arabic_mmlu_elementary_mathematics_light + - arabic_leaderboard_arabic_mmlu_formal_logic_light + - arabic_leaderboard_arabic_mmlu_global_facts_light + - arabic_leaderboard_arabic_mmlu_high_school_biology_light + - arabic_leaderboard_arabic_mmlu_high_school_chemistry_light + - arabic_leaderboard_arabic_mmlu_high_school_computer_science_light + - arabic_leaderboard_arabic_mmlu_high_school_european_history_light + - arabic_leaderboard_arabic_mmlu_high_school_geography_light + - arabic_leaderboard_arabic_mmlu_high_school_government_and_politics_light + - arabic_leaderboard_arabic_mmlu_high_school_macroeconomics_light + - arabic_leaderboard_arabic_mmlu_high_school_mathematics_light + - arabic_leaderboard_arabic_mmlu_high_school_microeconomics_light + - arabic_leaderboard_arabic_mmlu_high_school_physics_light + - arabic_leaderboard_arabic_mmlu_high_school_psychology_light + - arabic_leaderboard_arabic_mmlu_high_school_statistics_light + - arabic_leaderboard_arabic_mmlu_high_school_us_history_light + - arabic_leaderboard_arabic_mmlu_high_school_world_history_light + - arabic_leaderboard_arabic_mmlu_human_aging_light + - arabic_leaderboard_arabic_mmlu_human_sexuality_light + - arabic_leaderboard_arabic_mmlu_international_law_light + - arabic_leaderboard_arabic_mmlu_jurisprudence_light + - arabic_leaderboard_arabic_mmlu_logical_fallacies_light + - arabic_leaderboard_arabic_mmlu_machine_learning_light + - arabic_leaderboard_arabic_mmlu_management_light + - arabic_leaderboard_arabic_mmlu_marketing_light + - arabic_leaderboard_arabic_mmlu_medical_genetics_light + - arabic_leaderboard_arabic_mmlu_miscellaneous_light + - arabic_leaderboard_arabic_mmlu_moral_disputes_light + - arabic_leaderboard_arabic_mmlu_moral_scenarios_light + - arabic_leaderboard_arabic_mmlu_nutrition_light + - arabic_leaderboard_arabic_mmlu_philosophy_light + - arabic_leaderboard_arabic_mmlu_prehistory_light + - arabic_leaderboard_arabic_mmlu_professional_accounting_light + - arabic_leaderboard_arabic_mmlu_professional_law_light + - arabic_leaderboard_arabic_mmlu_professional_medicine_light + - arabic_leaderboard_arabic_mmlu_professional_psychology_light + - arabic_leaderboard_arabic_mmlu_public_relations_light + - arabic_leaderboard_arabic_mmlu_security_studies_light + - arabic_leaderboard_arabic_mmlu_sociology_light + - arabic_leaderboard_arabic_mmlu_us_foreign_policy_light + - arabic_leaderboard_arabic_mmlu_virology_light + - arabic_leaderboard_arabic_mmlu_world_religions_light +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_logical_fallacies_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_logical_fallacies_light.yaml new file mode 100644 index 00000000..866420ba --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_logical_fallacies_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_logical_fallacies_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: logical_fallacies +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_machine_learning_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_machine_learning_light.yaml new file mode 100644 index 00000000..01ed181e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_machine_learning_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_machine_learning_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: machine_learning +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_management_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_management_light.yaml new file mode 100644 index 00000000..62d7e32a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_management_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_management_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: management +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_marketing_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_marketing_light.yaml new file mode 100644 index 00000000..c42f7a17 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_marketing_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_marketing_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: marketing +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_medical_genetics_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_medical_genetics_light.yaml new file mode 100644 index 00000000..40d0d883 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_medical_genetics_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_medical_genetics_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: medical_genetics +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_miscellaneous_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_miscellaneous_light.yaml new file mode 100644 index 00000000..06bc6a47 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_miscellaneous_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_miscellaneous_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: miscellaneous +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_moral_disputes_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_moral_disputes_light.yaml new file mode 100644 index 00000000..be0c60e6 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_moral_disputes_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_moral_disputes_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: moral_disputes +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_moral_scenarios_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_moral_scenarios_light.yaml new file mode 100644 index 00000000..08e71366 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_moral_scenarios_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_moral_scenarios_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: moral_scenarios +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_nutrition_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_nutrition_light.yaml new file mode 100644 index 00000000..7987f5f3 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_nutrition_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_nutrition_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: nutrition +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_philosophy_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_philosophy_light.yaml new file mode 100644 index 00000000..85ebdd7a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_philosophy_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_philosophy_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: philosophy +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_prehistory_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_prehistory_light.yaml new file mode 100644 index 00000000..24aa8e22 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_prehistory_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_prehistory_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: prehistory +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_accounting_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_accounting_light.yaml new file mode 100644 index 00000000..1dc00966 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_accounting_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_professional_accounting_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: professional_accounting +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_law_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_law_light.yaml new file mode 100644 index 00000000..6e8c3617 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_law_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_professional_law_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: professional_law +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_medicine_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_medicine_light.yaml new file mode 100644 index 00000000..b90cdb38 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_medicine_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_professional_medicine_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: professional_medicine +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_psychology_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_psychology_light.yaml new file mode 100644 index 00000000..420a5362 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_professional_psychology_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_professional_psychology_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: professional_psychology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_public_relations_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_public_relations_light.yaml new file mode 100644 index 00000000..83d267bc --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_public_relations_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_public_relations_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: public_relations +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_security_studies_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_security_studies_light.yaml new file mode 100644 index 00000000..03e05d66 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_security_studies_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_security_studies_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: security_studies +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_sociology_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_sociology_light.yaml new file mode 100644 index 00000000..7deb0883 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_sociology_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_sociology_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: sociology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_us_foreign_policy_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_us_foreign_policy_light.yaml new file mode 100644 index 00000000..6c5f40a5 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_us_foreign_policy_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_us_foreign_policy_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: us_foreign_policy +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_virology_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_virology_light.yaml new file mode 100644 index 00000000..5ee4a7c9 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_virology_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_virology_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: virology +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_world_religions_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_world_religions_light.yaml new file mode 100644 index 00000000..57b13f05 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/arabic_leaderboard_arabic_mmlu_world_religions_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_arabic_mmlu_world_religions_light +dataset_path: arcee-globe/Arabic_MMLU-10percent +dataset_name: world_religions +output_type: multiple_choice +training_split: null +validation_split: dev +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: dev +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/utils.py new file mode 100644 index 00000000..da927b66 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mmlu_light/utils.py @@ -0,0 +1,35 @@ +import datasets +import numpy as np + + +# fmt: off +LETTER_INDICES_AR = ["أ", "ب", "ج", "د", "هـ", "و", "ز", "ح", "ط", "ي", "ك", "ل", "م", "ن", "س", "ع", "ف", "ص", "ق", "ر", "ش", "ت", "ث", "خ", "ذ", "ض", "ظ", "غ"] +# fmt: on + + +# fmt: off +LETTER_INDICES = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"] +# fmt: on + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + topic = doc["subject"] + instruction = f"الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح حول {topic.replace('_', ' ')}. \n\n" + choices = [doc["A"], doc["B"], doc["C"], doc["D"]] + # Answers are provided with roman letters - we look for the correct index in LETTER_INDICES, + # it will then be applied to arabic letters + gold_ix = LETTER_INDICES.index(doc["answer"]) + + query = f"{instruction}{doc['question']}\n" + query += "".join( + [ + f"{key}. {choice}\n" + for key, choice in zip(LETTER_INDICES_AR[:4], choices) + ] + ) + query += "الإجابة:" + + return {"query": query, "choices": LETTER_INDICES_AR[:4], "gold": gold_ix} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_challenge_light/arabic_leaderboard_arabic_mt_arc_challenge_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_challenge_light/arabic_leaderboard_arabic_mt_arc_challenge_light.yaml new file mode 100644 index 00000000..a88bd6bd --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_challenge_light/arabic_leaderboard_arabic_mt_arc_challenge_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_arc_challenge_light +task: + - arabic_mt_arc_challenge_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_challenge_light/arabic_mt_arc_challenge_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_challenge_light/arabic_mt_arc_challenge_light.yaml new file mode 100644 index 00000000..e6b299e8 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_challenge_light/arabic_mt_arc_challenge_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_arc_challenge_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: arc_challenge_okapi_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_challenge_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_challenge_light/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_challenge_light/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_easy_light/arabic_leaderboard_arabic_mt_arc_easy_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_easy_light/arabic_leaderboard_arabic_mt_arc_easy_light.yaml new file mode 100644 index 00000000..618b5429 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_easy_light/arabic_leaderboard_arabic_mt_arc_easy_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_arc_easy_light +task: + - arabic_mt_arc_easy_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_easy_light/arabic_mt_arc_easy_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_easy_light/arabic_mt_arc_easy_light.yaml new file mode 100644 index 00000000..90252fb3 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_easy_light/arabic_mt_arc_easy_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_arc_easy_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: arc_easy_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_easy_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_easy_light/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_arc_easy_light/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_boolq_light/arabic_leaderboard_arabic_mt_boolq_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_boolq_light/arabic_leaderboard_arabic_mt_boolq_light.yaml new file mode 100644 index 00000000..ee02f9cb --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_boolq_light/arabic_leaderboard_arabic_mt_boolq_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_boolq_light +task: + - arabic_mt_boolq_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_boolq_light/arabic_mt_boolq_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_boolq_light/arabic_mt_boolq_light.yaml new file mode 100644 index 00000000..4bdd145c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_boolq_light/arabic_mt_boolq_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_boolq_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: boolq_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_boolq_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_boolq_light/utils.py new file mode 100644 index 00000000..dcbc10d9 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_boolq_light/utils.py @@ -0,0 +1,24 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["question"] + passage = doc["passage"] + instruction = "بناء على المقطع التالي، أجب عن السؤال ب نعم أو لا" + query = f"""{instruction} + المقطع : + {passage} + السؤال: + {question} + الإجابة: + """ + + return { + "query": query, + "choices": ["نعم", "لا"], + "gold": 0 if doc["answer"] else 1, + } + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_copa_light/arabic_mt_copa_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_copa_light/arabic_mt_copa_light.yaml new file mode 100644 index 00000000..0ca475e7 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_copa_light/arabic_mt_copa_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_copa_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: copa_ext_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_copa_light/arbic_leaderboard_arabic_mt_copa_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_copa_light/arbic_leaderboard_arabic_mt_copa_light.yaml new file mode 100644 index 00000000..f3ea35bc --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_copa_light/arbic_leaderboard_arabic_mt_copa_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_copa_light +task: + - arabic_mt_copa_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_copa_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_copa_light/utils.py new file mode 100644 index 00000000..175ebdad --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_copa_light/utils.py @@ -0,0 +1,19 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + premise = doc["premise"] + choices = [doc["choice1"], doc["choice2"]] + question_map = {"cause": "لأن", "effect": "لذلك"} + question = question_map[doc["question"]] + answer = doc["label"] + + query = "{}، {} :\n0) {}\n1) {}\nالإجابة:".format( + premise, question, choices[0], choices[1] + ) + + return {"query": query, "choices": choices, "gold": answer} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_hellaswag_light/arabic_leaderboard_arabic_mt_hellaswag_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_hellaswag_light/arabic_leaderboard_arabic_mt_hellaswag_light.yaml new file mode 100644 index 00000000..0f44bbbc --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_hellaswag_light/arabic_leaderboard_arabic_mt_hellaswag_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_hellaswag_light +task: + - arabic_mt_hellaswag_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_hellaswag_light/arabic_mt_hellaswag_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_hellaswag_light/arabic_mt_hellaswag_light.yaml new file mode 100644 index 00000000..56ea04f2 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_hellaswag_light/arabic_mt_hellaswag_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_hellaswag_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: hellaswag_okapi_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_hellaswag_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_hellaswag_light/utils.py new file mode 100644 index 00000000..6b5a9f1f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_hellaswag_light/utils.py @@ -0,0 +1,30 @@ +import re + +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + ctx = re.sub(r"\[.*?\]", "", doc["ctx"]) # Remove latin words within brackets + endings = [ + re.sub(r"\[.*?\]", "", e) for e in eval(doc["endings"]) + ] # endings is a string representation of a list + answer_index = doc["label"] + instruction = ( + "بناء على السياق التالي، اختر النهاية الصحيحة من الاقتراحات التالية" + ) + + query = f"""{instruction} + السياق: + {ctx} + الاقتراحات: + + """ + for i, ending in enumerate(endings): + query += f"{i}) {ending}\n" + query += "الإجابة:" + + return {"query": query, "choices": endings, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_mmlu_light/arabic_leaderboard_arabic_mt_mmlu_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_mmlu_light/arabic_leaderboard_arabic_mt_mmlu_light.yaml new file mode 100644 index 00000000..b95ca1b5 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_mmlu_light/arabic_leaderboard_arabic_mt_mmlu_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_mmlu_light +task: + - arabic_mt_mmlu_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_mmlu_light/arabic_mt_mmlu_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_mmlu_light/arabic_mt_mmlu_light.yaml new file mode 100644 index 00000000..43084db3 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_mmlu_light/arabic_mt_mmlu_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_mmlu_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: mmlu_okapi_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_mmlu_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_mmlu_light/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_mmlu_light/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_openbook_qa_light/arabic_leaderboard_arabic_mt_openbook_qa_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_openbook_qa_light/arabic_leaderboard_arabic_mt_openbook_qa_light.yaml new file mode 100644 index 00000000..3737f621 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_openbook_qa_light/arabic_leaderboard_arabic_mt_openbook_qa_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_openbook_qa_light +task: + - arabic_mt_openbook_qa_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_openbook_qa_light/arabic_mt_openbook_qa_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_openbook_qa_light/arabic_mt_openbook_qa_light.yaml new file mode 100644 index 00000000..5e914fbd --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_openbook_qa_light/arabic_mt_openbook_qa_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_openbook_qa_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: openbook_qa_ext_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_openbook_qa_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_openbook_qa_light/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_openbook_qa_light/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_piqa_light/arabic_leaderboard_arabic_mt_piqa_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_piqa_light/arabic_leaderboard_arabic_mt_piqa_light.yaml new file mode 100644 index 00000000..642b2e0a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_piqa_light/arabic_leaderboard_arabic_mt_piqa_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_piqa_light +task: + - arabic_mt_piqa_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_piqa_light/arabic_mt_piqa_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_piqa_light/arabic_mt_piqa_light.yaml new file mode 100644 index 00000000..4dd9e005 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_piqa_light/arabic_mt_piqa_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_piqa_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: piqa_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_piqa_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_piqa_light/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_piqa_light/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_race_light/arabic_leaderboard_arabic_mt_race_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_race_light/arabic_leaderboard_arabic_mt_race_light.yaml new file mode 100644 index 00000000..8f427484 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_race_light/arabic_leaderboard_arabic_mt_race_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_race_light +task: + - arabic_mt_race_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_race_light/arabic_mt_race_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_race_light/arabic_mt_race_light.yaml new file mode 100644 index 00000000..fed452cc --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_race_light/arabic_mt_race_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_race_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: race_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_race_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_race_light/utils.py new file mode 100644 index 00000000..62f9874e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_race_light/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["query"] + answer_index = int(doc["label"]) + # Dynamically determining the choices by excluding '__few_shots', 'query' and 'label' + choices_keys = [ + key for key in doc.keys() if key not in ["query", "label", "__few_shots"] + ] + choices = [doc[key] for key in choices_keys] + + instruction = "الأسئلة التالية هي أسئلة متعددة الإختيارات مع الجواب الصحيح\n\n" + query = f"{instruction}السؤال: {question}\n" + for index, choice in enumerate(choices): + query += f"{index}) {choice}\n" + query += "الإجابة:" + + return {"query": query, "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_sciq_light/arabic_leaderboard_arabic_mt_sciq_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_sciq_light/arabic_leaderboard_arabic_mt_sciq_light.yaml new file mode 100644 index 00000000..13127e99 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_sciq_light/arabic_leaderboard_arabic_mt_sciq_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_sciq_light +task: + - arabic_mt_sciq_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_sciq_light/arabic_mt_sciq_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_sciq_light/arabic_mt_sciq_light.yaml new file mode 100644 index 00000000..95976cbb --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_sciq_light/arabic_mt_sciq_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_sciq_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: sciq_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_sciq_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_sciq_light/utils.py new file mode 100644 index 00000000..ddb42eeb --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_sciq_light/utils.py @@ -0,0 +1,41 @@ +import random + +import datasets +import numpy as np + + +def doc_to_text(doc): + instruction = ( + "بناءً على السياق أدناه، اختر الإجابة الصحيحة للسؤال التالي من قائمة الاقتراحات" + ) + support = doc["support"] + question = doc["question"] + query = f"""{instruction} + السياق: + {support} + السؤال: + {question} + الإجابات المحتملة: + + """ + return query + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + correct_answer = doc["correct_answer"] + choices = [ + doc["distractor1"], + doc["distractor2"], + doc["distractor3"], + correct_answer, + ] + + # Shuffle the choices + random.shuffle(choices) + + answer_index = choices.index(correct_answer) + + return {"query": doc_to_text(doc), "choices": choices, "gold": answer_index} + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_toxigen_light/arabic_leaderboard_arabic_mt_toxigen_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_toxigen_light/arabic_leaderboard_arabic_mt_toxigen_light.yaml new file mode 100644 index 00000000..7e305d54 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_toxigen_light/arabic_leaderboard_arabic_mt_toxigen_light.yaml @@ -0,0 +1,13 @@ +group: arabic_leaderboard_arabic_mt_toxigen_light +task: + - arabic_mt_toxigen_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_toxigen_light/arabic_mt_toxigen_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_toxigen_light/arabic_mt_toxigen_light.yaml new file mode 100644 index 00000000..b2bef8ab --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_toxigen_light/arabic_mt_toxigen_light.yaml @@ -0,0 +1,23 @@ +task: arabic_mt_toxigen_light +dataset_path: arcee-globe/AlGhafa-Arabic-LLM-Benchmark-Translated-10percent +dataset_name: toxigen_ar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_toxigen_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_toxigen_light/utils.py new file mode 100644 index 00000000..09d311e5 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_arabic_mt_toxigen_light/utils.py @@ -0,0 +1,23 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset) -> datasets.Dataset: + def _process_doc(doc): + text = doc["text"] + label = 1 if ((doc["toxicity_ai"] + doc["toxicity_human"]) > 5.5) else 0 + instruction = 'هل العبارة التالية تحض على الكراهية؟ قم بالرد بـ"نعم" أو "لا".' + + query = f"""{instruction} + العبارة: + '{text}' + الإجابة: + """ + out_doc = { + "query": query, + "choices": ["لا", "نعم"], + "gold": label, + } + return out_doc + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Algeria_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Algeria_light.yaml new file mode 100644 index 00000000..4ab4634f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Algeria_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Algeria_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Algeria +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Ancient_Egypt_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Ancient_Egypt_light.yaml new file mode 100644 index 00000000..ab6fffed --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Ancient_Egypt_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Ancient_Egypt_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Ancient_Egypt +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arab_Empire_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arab_Empire_light.yaml new file mode 100644 index 00000000..886574eb --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arab_Empire_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arab_Empire_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arab_Empire +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Architecture_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Architecture_light.yaml new file mode 100644 index 00000000..e57472ad --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Architecture_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Architecture_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Architecture +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Art_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Art_light.yaml new file mode 100644 index 00000000..e94340e7 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Art_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Art_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Art +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Astronomy_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Astronomy_light.yaml new file mode 100644 index 00000000..e8ed990d --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Astronomy_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Astronomy_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Astronomy +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Calligraphy_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Calligraphy_light.yaml new file mode 100644 index 00000000..cd41bdde --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Calligraphy_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Calligraphy_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Calligraphy +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Ceremony_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Ceremony_light.yaml new file mode 100644 index 00000000..72c67054 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Ceremony_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Ceremony_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Ceremony +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Clothing_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Clothing_light.yaml new file mode 100644 index 00000000..9348de07 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Clothing_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Clothing_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Clothing +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Culture_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Culture_light.yaml new file mode 100644 index 00000000..4f211064 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Culture_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Culture_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Culture +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Food_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Food_light.yaml new file mode 100644 index 00000000..7ccef674 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Food_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Food_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Food +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Funeral_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Funeral_light.yaml new file mode 100644 index 00000000..94115478 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Funeral_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Funeral_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Funeral +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Geography_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Geography_light.yaml new file mode 100644 index 00000000..36221d88 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Geography_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Geography_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Geography +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_History_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_History_light.yaml new file mode 100644 index 00000000..2e128318 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_History_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_History_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_History +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Language_Origin_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Language_Origin_light.yaml new file mode 100644 index 00000000..80606043 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Language_Origin_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Language_Origin_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Language_Origin +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Literature_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Literature_light.yaml new file mode 100644 index 00000000..3122e395 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Literature_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Literature_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Literature +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Math_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Math_light.yaml new file mode 100644 index 00000000..0182aeda --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Math_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Math_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Math +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Medicine_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Medicine_light.yaml new file mode 100644 index 00000000..aec88feb --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Medicine_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Medicine_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Medicine +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Music_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Music_light.yaml new file mode 100644 index 00000000..35a77189 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Music_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Music_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Music +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Ornament_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Ornament_light.yaml new file mode 100644 index 00000000..6b31186c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Ornament_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Ornament_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Ornament +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Philosophy_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Philosophy_light.yaml new file mode 100644 index 00000000..f6b5fa71 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Philosophy_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Philosophy_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Philosophy +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Physics_and_Chemistry_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Physics_and_Chemistry_light.yaml new file mode 100644 index 00000000..559d729c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Physics_and_Chemistry_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Physics_and_Chemistry_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Physics_and_Chemistry +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Wedding_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Wedding_light.yaml new file mode 100644 index 00000000..9241709c --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Arabic_Wedding_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Arabic_Wedding_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Arabic_Wedding +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Bahrain_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Bahrain_light.yaml new file mode 100644 index 00000000..b9c7cef5 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Bahrain_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Bahrain_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Bahrain +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Comoros_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Comoros_light.yaml new file mode 100644 index 00000000..1f74bd46 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Comoros_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Comoros_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Comoros +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Egypt_modern_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Egypt_modern_light.yaml new file mode 100644 index 00000000..e0b19cff --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Egypt_modern_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Egypt_modern_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Egypt_modern +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromAncientEgypt_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromAncientEgypt_light.yaml new file mode 100644 index 00000000..6cf755a2 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromAncientEgypt_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromAncientEgypt_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: InfluenceFromAncientEgypt +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromByzantium_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromByzantium_light.yaml new file mode 100644 index 00000000..8fe285eb --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromByzantium_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromByzantium_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: InfluenceFromByzantium +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromChina_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromChina_light.yaml new file mode 100644 index 00000000..bb028b08 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromChina_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromChina_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: InfluenceFromChina +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromGreece_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromGreece_light.yaml new file mode 100644 index 00000000..25060acc --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromGreece_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromGreece_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: InfluenceFromGreece +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromIslam_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromIslam_light.yaml new file mode 100644 index 00000000..0a60a2f3 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromIslam_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromIslam_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: InfluenceFromIslam +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromPersia_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromPersia_light.yaml new file mode 100644 index 00000000..7081bec2 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromPersia_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromPersia_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: InfluenceFromPersia +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromRome_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromRome_light.yaml new file mode 100644 index 00000000..8c64cf3b --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_InfluenceFromRome_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_InfluenceFromRome_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: InfluenceFromRome +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Iraq_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Iraq_light.yaml new file mode 100644 index 00000000..a056a9cf --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Iraq_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Iraq_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Iraq +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Islam_Education_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Islam_Education_light.yaml new file mode 100644 index 00000000..e8f6ad45 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Islam_Education_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Islam_Education_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Islam_Education +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Islam_branches_and_schools_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Islam_branches_and_schools_light.yaml new file mode 100644 index 00000000..98137e9a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Islam_branches_and_schools_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Islam_branches_and_schools_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Islam_branches_and_schools +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Islamic_law_system_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Islamic_law_system_light.yaml new file mode 100644 index 00000000..d9aff345 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Islamic_law_system_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Islamic_law_system_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Islamic_law_system +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Jordan_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Jordan_light.yaml new file mode 100644 index 00000000..674a998e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Jordan_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Jordan_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Jordan +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Kuwait_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Kuwait_light.yaml new file mode 100644 index 00000000..0c3d372d --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Kuwait_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Kuwait_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Kuwait +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Lebanon_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Lebanon_light.yaml new file mode 100644 index 00000000..9c3856d6 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Lebanon_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Lebanon_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Lebanon +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Libya_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Libya_light.yaml new file mode 100644 index 00000000..6070ccbf --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Libya_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Libya_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Libya +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Mauritania_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Mauritania_light.yaml new file mode 100644 index 00000000..0b1deda6 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Mauritania_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Mauritania_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Mauritania +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Mesopotamia_civilization_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Mesopotamia_civilization_light.yaml new file mode 100644 index 00000000..65474b72 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Mesopotamia_civilization_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Mesopotamia_civilization_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Mesopotamia_civilization +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Morocco_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Morocco_light.yaml new file mode 100644 index 00000000..d752434a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Morocco_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Morocco_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Morocco +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Oman_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Oman_light.yaml new file mode 100644 index 00000000..448498f4 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Oman_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Oman_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Oman +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Palestine_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Palestine_light.yaml new file mode 100644 index 00000000..a619c460 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Palestine_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Palestine_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Palestine +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Qatar_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Qatar_light.yaml new file mode 100644 index 00000000..967dbc57 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Qatar_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Qatar_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Qatar +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Saudi_Arabia_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Saudi_Arabia_light.yaml new file mode 100644 index 00000000..d45558b9 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Saudi_Arabia_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Saudi_Arabia_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Saudi_Arabia +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Somalia_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Somalia_light.yaml new file mode 100644 index 00000000..558ea176 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Somalia_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Somalia_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Somalia +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Sudan_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Sudan_light.yaml new file mode 100644 index 00000000..ce599733 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Sudan_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Sudan_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Sudan +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Syria_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Syria_light.yaml new file mode 100644 index 00000000..8b0bd7ae --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Syria_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Syria_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Syria +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Tunisia_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Tunisia_light.yaml new file mode 100644 index 00000000..a53c5e0b --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Tunisia_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Tunisia_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: Tunisia +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_United_Arab_Emirates_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_United_Arab_Emirates_light.yaml new file mode 100644 index 00000000..1ce5993a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_United_Arab_Emirates_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_United_Arab_Emirates_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: United_Arab_Emirates +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Yemen_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Yemen_light.yaml new file mode 100644 index 00000000..e480b19d --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_Yemen_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_Yemen_light +dataset_path: OALL/ACVA +dataset_name: Yemen +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_communication_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_communication_light.yaml new file mode 100644 index 00000000..2814278a --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_communication_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_communication_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: communication +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_computer_and_phone_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_computer_and_phone_light.yaml new file mode 100644 index 00000000..ddd07e3f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_computer_and_phone_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_computer_and_phone_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: computer_and_phone +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_daily_life_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_daily_life_light.yaml new file mode 100644 index 00000000..2d975e4e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_daily_life_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_daily_life_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: daily_life +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_entertainment_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_entertainment_light.yaml new file mode 100644 index 00000000..721e6cdd --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_entertainment_light.yaml @@ -0,0 +1,23 @@ +task: arabic_leaderboard_acva_entertainment_light +dataset_path: arcee-globe/ACVA-10percent +dataset_name: entertainment +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{query}}" +doc_to_target: "{{gold}}" +doc_to_choice: "choices" +fewshot_split: validation +fewshot_config: + sampler: first_n +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_light.yaml new file mode 100644 index 00000000..ea4a8977 --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/arabic_leaderboard_acva_light.yaml @@ -0,0 +1,70 @@ +group: arabic_leaderboard_acva_light +task: + - arabic_leaderboard_acva_Algeria_light + - arabic_leaderboard_acva_Ancient_Egypt_light + - arabic_leaderboard_acva_Arab_Empire_light + - arabic_leaderboard_acva_Arabic_Architecture_light + - arabic_leaderboard_acva_Arabic_Art_light + - arabic_leaderboard_acva_Arabic_Astronomy_light + - arabic_leaderboard_acva_Arabic_Calligraphy_light + - arabic_leaderboard_acva_Arabic_Ceremony_light + - arabic_leaderboard_acva_Arabic_Clothing_light + - arabic_leaderboard_acva_Arabic_Culture_light + - arabic_leaderboard_acva_Arabic_Food_light + - arabic_leaderboard_acva_Arabic_Funeral_light + - arabic_leaderboard_acva_Arabic_Geography_light + - arabic_leaderboard_acva_Arabic_History_light + - arabic_leaderboard_acva_Arabic_Language_Origin_light + - arabic_leaderboard_acva_Arabic_Literature_light + - arabic_leaderboard_acva_Arabic_Math_light + - arabic_leaderboard_acva_Arabic_Medicine_light + - arabic_leaderboard_acva_Arabic_Music_light + - arabic_leaderboard_acva_Arabic_Ornament_light + - arabic_leaderboard_acva_Arabic_Philosophy_light + - arabic_leaderboard_acva_Arabic_Physics_and_Chemistry_light + - arabic_leaderboard_acva_Arabic_Wedding_light + - arabic_leaderboard_acva_Bahrain_light + - arabic_leaderboard_acva_Comoros_light + - arabic_leaderboard_acva_Egypt_modern_light + - arabic_leaderboard_acva_InfluenceFromAncientEgypt_light + - arabic_leaderboard_acva_InfluenceFromByzantium_light + - arabic_leaderboard_acva_InfluenceFromChina_light + - arabic_leaderboard_acva_InfluenceFromGreece_light + - arabic_leaderboard_acva_InfluenceFromIslam_light + - arabic_leaderboard_acva_InfluenceFromPersia_light + - arabic_leaderboard_acva_InfluenceFromRome_light + - arabic_leaderboard_acva_Iraq_light + - arabic_leaderboard_acva_Islam_Education_light + - arabic_leaderboard_acva_Islam_branches_and_schools_light + - arabic_leaderboard_acva_Islamic_law_system_light + - arabic_leaderboard_acva_Jordan_light + - arabic_leaderboard_acva_Kuwait_light + - arabic_leaderboard_acva_Lebanon_light + - arabic_leaderboard_acva_Libya_light + - arabic_leaderboard_acva_Mauritania_light + - arabic_leaderboard_acva_Mesopotamia_civilization_light + - arabic_leaderboard_acva_Morocco_light + - arabic_leaderboard_acva_Oman_light + - arabic_leaderboard_acva_Palestine_light + - arabic_leaderboard_acva_Qatar_light + - arabic_leaderboard_acva_Saudi_Arabia_light + - arabic_leaderboard_acva_Somalia_light + - arabic_leaderboard_acva_Sudan_light + - arabic_leaderboard_acva_Syria_light + - arabic_leaderboard_acva_Tunisia_light + - arabic_leaderboard_acva_United_Arab_Emirates_light + - arabic_leaderboard_acva_Yemen_light + - arabic_leaderboard_acva_communication_light + - arabic_leaderboard_acva_computer_and_phone_light + - arabic_leaderboard_acva_daily_life_light + - arabic_leaderboard_acva_entertainment_light + +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/utils.py b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/utils.py new file mode 100644 index 00000000..7e91496f --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_avca_light/utils.py @@ -0,0 +1,16 @@ +import datasets +import numpy as np + + +def process_docs(dataset: datasets.Dataset): + def _process_doc(doc): + question = doc["question"] + answer = doc["answer"] + + return { + "query": f"السؤال: {question}\nالإجابة:", + "choices": ["صح", "خطأ"], + "gold": ["صح", "خطأ"].index(answer), + } + + return dataset.map(_process_doc) diff --git a/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_light.yaml b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_light.yaml new file mode 100644 index 00000000..d77ebd1e --- /dev/null +++ b/lm_eval/tasks/arabic_leaderboard_light/arabic_leaderboard_light.yaml @@ -0,0 +1,25 @@ +group: arabic_leaderboard_light +task: + - arabic_leaderboard_acva_light + - arabic_leaderboard_alghafa_light + - arabic_leaderboard_arabic_exams_light + - arabic_leaderboard_arabic_mt_arc_challenge_light + - arabic_leaderboard_arabic_mt_arc_easy_light + - arabic_leaderboard_arabic_mt_boolq_light + - arabic_leaderboard_arabic_mt_hellaswag_light + - arabic_leaderboard_arabic_mt_mmlu_light + - arabic_leaderboard_arabic_mt_copa_light + - arabic_leaderboard_arabic_mt_openbook_qa_light + - arabic_leaderboard_arabic_mt_piqa_light + - arabic_leaderboard_arabic_mt_race_light + - arabic_leaderboard_arabic_mt_sciq_light + - arabic_leaderboard_arabic_mt_toxigen_light +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true + - metric: acc_norm + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 -- GitLab From fb963f0f0a5b28b69763590bb59676072cf43a01 Mon Sep 17 00:00:00 2001 From: Lintang Sutawika Date: Fri, 13 Sep 2024 13:47:02 -0400 Subject: [PATCH 096/194] Multimodal prototyping (#2243) * add WIP hf vlm class * add doc_to_image * add mmmu tasks * fix merge conflicts * add lintang's changes to hf_vlms.py * fix doc_to_image * added yaml_path for config-loading * revert * add line to process str type v * update * modeling cleanup * add aggregation for mmmu * rewrite MMMU processing code based on only MMMU authors' repo (doc_to_image still WIP) * implemented doc_to_image * update doc_to_image to accept list of features * update functions * readd image processed * update args process * bugfix for repeated images fed to model * push WIP loglikelihood code * commit most recent code (generative ; qwen2-vl testing) * preliminary image_token_id handling * small mmmu update: some qs have >4 mcqa options * push updated modeling code * use processor.apply_chat_template * add mathvista draft * nit * nit * ensure no footguns in text<>multimodal LM<>task incompatibility * add notification to readme regarding launch of prototype! * fix compatibility check * reorganize mmmu configs * chat_template=None * add interleave chat_template * add condition * add max_images; interleave=true * nit * testmini_mcq * nit * pass image string; convert img * add vllm * add init * vlm add multi attr * fixup * pass max images to vllm model init * nit * encoding to device * fix HFMultimodalLM.chat_template ? * add mmmu readme * remove erroneous prints * use HFMultimodalLM.chat_template ; restore tasks/__init__.py * add docstring for replace_placeholders in utils * fix `replace_placeholders`; set image_string=None * fix typo * cleanup + fix merge conflicts * update MMMU readme * del mathvista * add some sample scores * Update README.md * add log msg for image_string value --------- Co-authored-by: haileyschoelkopf Co-authored-by: Baber Abbasi Co-authored-by: Baber Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- README.md | 1 + lm_eval/api/task.py | 99 ++- lm_eval/evaluator.py | 20 + lm_eval/models/__init__.py | 2 + lm_eval/models/hf_vlms.py | 719 ++++++++++++++++++ lm_eval/models/huggingface.py | 9 + lm_eval/models/utils.py | 34 + lm_eval/models/vllm_vlms.py | 279 +++++++ lm_eval/tasks/mmmu/README.md | 150 ++++ lm_eval/tasks/mmmu/_art_and_design.yaml | 13 + lm_eval/tasks/mmmu/_business.yaml | 14 + lm_eval/tasks/mmmu/_health_and_medicine.yaml | 14 + .../mmmu/_humanities_and_social_sciences.yaml | 13 + lm_eval/tasks/mmmu/_mmmu.yaml | 14 + lm_eval/tasks/mmmu/_science.yaml | 14 + lm_eval/tasks/mmmu/_tech_and_engineering.yaml | 16 + lm_eval/tasks/mmmu/_template_yaml | 19 + lm_eval/tasks/mmmu/mmmu_accounting.yaml | 4 + lm_eval/tasks/mmmu/mmmu_agriculture.yaml | 4 + .../mmmu_architecture_and_engineering.yaml | 4 + lm_eval/tasks/mmmu/mmmu_art.yaml | 4 + lm_eval/tasks/mmmu/mmmu_art_theory.yaml | 4 + .../mmmu/mmmu_basic_medical_science.yaml | 4 + lm_eval/tasks/mmmu/mmmu_biology.yaml | 4 + lm_eval/tasks/mmmu/mmmu_chemistry.yaml | 4 + .../tasks/mmmu/mmmu_clinical_medicine.yaml | 4 + lm_eval/tasks/mmmu/mmmu_computer_science.yaml | 4 + lm_eval/tasks/mmmu/mmmu_design.yaml | 4 + ...u_diagnostics_and_laboratory_medicine.yaml | 4 + lm_eval/tasks/mmmu/mmmu_economics.yaml | 4 + lm_eval/tasks/mmmu/mmmu_electronics.yaml | 4 + lm_eval/tasks/mmmu/mmmu_energy_and_power.yaml | 4 + lm_eval/tasks/mmmu/mmmu_finance.yaml | 4 + lm_eval/tasks/mmmu/mmmu_geography.yaml | 4 + lm_eval/tasks/mmmu/mmmu_history.yaml | 4 + lm_eval/tasks/mmmu/mmmu_literature.yaml | 4 + lm_eval/tasks/mmmu/mmmu_manage.yaml | 4 + lm_eval/tasks/mmmu/mmmu_marketing.yaml | 4 + lm_eval/tasks/mmmu/mmmu_materials.yaml | 4 + lm_eval/tasks/mmmu/mmmu_math.yaml | 4 + .../mmmu/mmmu_mechanical_engineering.yaml | 4 + lm_eval/tasks/mmmu/mmmu_music.yaml | 4 + lm_eval/tasks/mmmu/mmmu_pharmacy.yaml | 4 + lm_eval/tasks/mmmu/mmmu_physics.yaml | 4 + lm_eval/tasks/mmmu/mmmu_psychology.yaml | 4 + lm_eval/tasks/mmmu/mmmu_public_health.yaml | 4 + lm_eval/tasks/mmmu/mmmu_sociology.yaml | 4 + lm_eval/tasks/mmmu/utils.py | 341 +++++++++ 48 files changed, 1865 insertions(+), 26 deletions(-) create mode 100644 lm_eval/models/hf_vlms.py create mode 100644 lm_eval/models/vllm_vlms.py create mode 100644 lm_eval/tasks/mmmu/README.md create mode 100644 lm_eval/tasks/mmmu/_art_and_design.yaml create mode 100644 lm_eval/tasks/mmmu/_business.yaml create mode 100644 lm_eval/tasks/mmmu/_health_and_medicine.yaml create mode 100644 lm_eval/tasks/mmmu/_humanities_and_social_sciences.yaml create mode 100644 lm_eval/tasks/mmmu/_mmmu.yaml create mode 100644 lm_eval/tasks/mmmu/_science.yaml create mode 100644 lm_eval/tasks/mmmu/_tech_and_engineering.yaml create mode 100644 lm_eval/tasks/mmmu/_template_yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_accounting.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_agriculture.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_architecture_and_engineering.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_art.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_art_theory.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_basic_medical_science.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_biology.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_chemistry.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_clinical_medicine.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_computer_science.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_design.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_diagnostics_and_laboratory_medicine.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_economics.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_electronics.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_energy_and_power.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_finance.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_geography.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_history.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_literature.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_manage.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_marketing.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_materials.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_math.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_mechanical_engineering.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_music.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_pharmacy.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_physics.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_psychology.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_public_health.yaml create mode 100644 lm_eval/tasks/mmmu/mmmu_sociology.yaml create mode 100644 lm_eval/tasks/mmmu/utils.py diff --git a/README.md b/README.md index e973cdb7..9f26c811 100644 --- a/README.md +++ b/README.md @@ -6,6 +6,7 @@ *Latest News 📣* +- [2024/09] We are prototyping allowing users of LM Evaluation Harness to create and evaluate on text+image multimodal input, text output tasks, and have just added the `hf-multimodal` and `vllm-vlm` model types and `mmmu` task as a prototype feature. We welcome users to try out this in-progress feature and stress-test it for themselves, and suggest they check out [`lmms-eval`](https://github.com/EvolvingLMMs-Lab/lmms-eval), a wonderful project originally forking off of the lm-evaluation-harness, for a broader range of multimodal tasks, models, and features. - [2024/07] [API model](docs/API_guide.md) support has been updated and refactored, introducing support for batched and async requests, and making it significantly easier to customize and use for your own purposes. **To run Llama 405B, we recommend using VLLM's OpenAI-compliant API to host the model, and use the `local-completions` model type to evaluate the model.** - [2024/07] New Open LLM Leaderboard tasks have been added ! You can find them under the [leaderboard](lm_eval/tasks/leaderboard/README.md) task group. diff --git a/lm_eval/api/task.py b/lm_eval/api/task.py index 8a1a3bdb..8dadf948 100644 --- a/lm_eval/api/task.py +++ b/lm_eval/api/task.py @@ -75,6 +75,7 @@ class TaskConfig(dict): process_docs: Optional[Callable] = None doc_to_text: Optional[Union[Callable, str]] = None doc_to_target: Optional[Union[Callable, str]] = None + doc_to_image: Union[Callable, str] = None doc_to_choice: Optional[Union[Callable, str, dict, list]] = None process_results: Optional[Union[Callable, str]] = None use_prompt: Optional[str] = None @@ -377,6 +378,10 @@ class Task(abc.ABC): def doc_to_target(self, doc): pass + # not an abstractmethod because not every language-only task has to implement this + def doc_to_image(self, doc): + raise NotImplementedError + def build_all_requests( self, *, @@ -735,6 +740,10 @@ class ConfigurableTask(Task): ) self.OUTPUT_TYPE = self.config.output_type + if self.config.doc_to_image is not None: + # mark the task as requiring multimodality. + self.MULTIMODAL = True + if self.config.dataset_path is not None: self.DATASET_PATH = self.config.dataset_path @@ -1042,8 +1051,8 @@ class ConfigurableTask(Task): Whether to apply the chat template to the fewshot context. :param fewshot_as_multiturn: bool Whether to provide the fewshot examples as a multiturn conversation or a single user turn. - :param chat_template: Callable - Chat template to be applied to the fewshot context. + :param chat_template: + callable (from lm.apply_chat_template) that takes in a list[Dict] chat transcript and renders it into a string. :returns: str The fewshot context. """ @@ -1279,9 +1288,34 @@ class ConfigurableTask(Task): else: raise TypeError + def doc_to_image(self, doc: Any, doc_to_image=None) -> Union[int, str, list]: + if doc_to_image is not None: + doc_to_image = doc_to_image + elif self.config.doc_to_image is not None: + doc_to_image = self.config.doc_to_image + else: + return None + + if isinstance(doc_to_image, list): + image_feature = [ + self.doc_to_image(doc, feature) for feature in doc_to_image + ] + return [feature for feature in image_feature if feature is not None] + elif isinstance(doc_to_image, str): + if doc_to_image in self.features: + return doc[doc_to_image] + else: + return ast.literal_eval(utils.apply_template(doc_to_image, doc)) + elif callable(doc_to_image): + return doc_to_image(doc) + else: + return None + def construct_requests( self, doc: dict, ctx: str, **kwargs ) -> Union[List[Instance], Instance]: + aux_arguments = None + if self.OUTPUT_TYPE == "loglikelihood": arguments = (ctx, self.doc_to_target(doc)) elif self.OUTPUT_TYPE == "loglikelihood_rolling": @@ -1299,6 +1333,37 @@ class ConfigurableTask(Task): # Otherwise they are placed in the continuation arguments = [(ctx, f"{target_delimiter}{cont}") for cont in choices] + # TODO: we should raise a warning telling users this will at most ~2x runtime. + if "acc_mutual_info" in self._metric_fn_list.keys(): + # if we are calculating multiple choice accuracy + # using mutual information instead of raw loglikelihood as metric, need unconditional lls. + + # here mutual info refers to calculating + # log(P(choice|ctx) / P(choice)) = log(P(choice|ctx)) - log(P(choice)) + # in other words normalizing by subtracting the unconditional logprob of each choice. + aux_arguments = [("", f"{choice}") for choice in choices] + + arguments.extend(aux_arguments) + + elif self.OUTPUT_TYPE == "generate_until": + arguments = (ctx, deepcopy(self.config.generation_kwargs)) + + multimodal_arg = {} + if ( + self.config.doc_to_image + ): # TODO: ensure that non-multimodal tasks aren't getting visual args + multimodal_arg = { + **multimodal_arg, + **{"visual": self.doc_to_image(doc)}, + } + + if bool(multimodal_arg): + if isinstance(arguments, list): + arguments = [arg + (multimodal_arg,) for arg in arguments] + else: + arguments = arguments + (multimodal_arg,) + + if self.OUTPUT_TYPE == "multiple_choice": request_list = [ Instance( request_type="loglikelihood", @@ -1309,33 +1374,15 @@ class ConfigurableTask(Task): ) for i, arg in enumerate(arguments) ] - # TODO: we should raise a warning telling users this will at most ~2x runtime. - if "acc_mutual_info" in self._metric_fn_list.keys(): - # if we are calculating multiple choice accuracy - # using mutual information instead of raw loglikelihood as metric, need unconditional lls. - # here mutual info refers to calculating - # log(P(choice|ctx) / P(choice)) = log(P(choice|ctx)) - log(P(choice)) - # in other words normalizing by subtracting the unconditional logprob of each choice. - request_list.extend( - [ - Instance( - request_type="loglikelihood", - doc=doc, - arguments=("", "{}".format(choice)), - idx=i, - **kwargs, - ) - for i, choice in enumerate(choices) - ] - ) return request_list - elif self.OUTPUT_TYPE == "generate_until": - arguments = (ctx, deepcopy(self.config.generation_kwargs)) - return Instance( - request_type=self.OUTPUT_TYPE, doc=doc, arguments=arguments, idx=0, **kwargs + request_type=self.OUTPUT_TYPE, + doc=doc, + arguments=arguments, + idx=0, + **kwargs, ) def process_results(self, doc, results): @@ -1547,7 +1594,7 @@ class ConfigurableTask(Task): f"ConfigurableTask(task_name={getattr(self.config, 'task', None)}," f"output_type={self.OUTPUT_TYPE}," f"num_fewshot={getattr(self.config, 'num_fewshot', None)}," - f"num_samples={len(self.eval_docs)})" + f"num_samples={len(self.eval_docs)})", ) diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index 52a8d00d..4f4c8f7f 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -414,8 +414,28 @@ def evaluate( for task_output in eval_tasks ): raise ValueError("log_samples must be True for 'bypass' metric-only tasks") + + # validation check: are we running multimodal task <-> non-multimodal model class, or vice-versa. + incompatible_tasks = [] for task_output in eval_tasks: task: Task = task_output.task + + if getattr(lm, "MULTIMODAL", False) != getattr(task, "MULTIMODAL", False): + incompatible_tasks.append(task_output.task_name) + if len(incompatible_tasks) > 0: + if not getattr(lm, "MULTIMODAL", False): + raise ValueError( + f"Attempted to run tasks: {incompatible_tasks} which require multimodal input, but the selected model type does not currently implement this. Multimodal support is currently restricted to the ['hf-multimodal', 'vllm-vlm'] model type." + ) + else: + raise ValueError( + f"Attempted to run tasks: {incompatible_tasks} which are text-only, but used a model type which only currently supports multimodal tasks." + ) + # end multimodality validation check + + for task_output in eval_tasks: + task: Task = task_output.task + limit = get_sample_size(task, limit) task.build_all_requests( limit=limit, diff --git a/lm_eval/models/__init__.py b/lm_eval/models/__init__.py index 0b2441eb..553be3a5 100644 --- a/lm_eval/models/__init__.py +++ b/lm_eval/models/__init__.py @@ -3,6 +3,7 @@ from . import ( api_models, dummy, gguf, + hf_vlms, huggingface, mamba_lm, nemo_lm, @@ -12,6 +13,7 @@ from . import ( optimum_lm, textsynth, vllm_causallms, + vllm_vlms, ) diff --git a/lm_eval/models/hf_vlms.py b/lm_eval/models/hf_vlms.py new file mode 100644 index 00000000..c94c76b2 --- /dev/null +++ b/lm_eval/models/hf_vlms.py @@ -0,0 +1,719 @@ +import copy +from typing import Dict, List, Optional, Tuple, Union + +import torch +import torch.nn.functional as F +import transformers +from tqdm import tqdm +from transformers import BatchEncoding + +from lm_eval import utils +from lm_eval.api.instance import Instance +from lm_eval.api.registry import register_model +from lm_eval.models.huggingface import HFLM +from lm_eval.models.utils import ( + Collator, + pad_and_concat, + replace_placeholders, + stop_sequences_criteria, +) + + +DEFAULT_IMAGE_PLACEHOLDER = "" + + +eval_logger = utils.eval_logger + + +@register_model("hf-multimodal") +class HFMultimodalLM(HFLM): + """ + An abstracted Hugging Face model class for multimodal LMs like Llava and Idefics. + """ + + AUTO_MODEL_CLASS = transformers.AutoModelForVision2Seq + MULTIMODAL = True # flag to indicate, for now, that this model type can run multimodal requests + + def __init__( + self, + pretrained: Union[str, transformers.PreTrainedModel], + image_token_id: Optional[int] = None, + image_string: Optional[str] = None, + interleave: bool = True, + # TODO: handle whitespace in image placeholder (replacement) + max_images: Optional[int] = 999, + convert_img_format=False, + **kwargs, + ): + # We initialize using HFLM's init. Sub-methods like _create_model and _create_tokenizer + # modify init behavior. + super().__init__(pretrained, **kwargs) + + assert ( + self.batch_size != "auto" + ), "Batch size 'auto' is not yet supported for hf-multimodal models." + self.chat_applied: bool = False + # TODO: phi-3.5 "image placeholders" are , , ... in order. how to handle this case + + # HF AutoModelForVision2Seq models have an `image_token_id` value in their configs + # denoting the token which indicates a location where an image will be substituted in. + # This can take different string values across models, e.g. for Idefics2 and <|image_pad|> for Qwen2-VL + self.interleave = interleave + self.max_images = max_images + self.rgb = convert_img_format + # WARNING: improperly set image_token_id can lead to ignored image input or other (potentially silent) errors! + if not image_string: + self.image_token_id = ( + int(image_token_id) + if image_token_id + else ( + getattr(self.config, "image_token_id", None) + or getattr(self.config, "image_token_index", None) + ) + ) + assert ( + self.image_token_id is not None + ), "Must have a non-None image_token_id to evaluate a Hugging Face AutoModelForVision2Seq model. Please pass `image_token_id` in `--model_args` if model's config does not already specify one." + # get the string this token ID corresponds to + self.image_token = self.tok_decode( + [self.image_token_id], skip_special_tokens=False + ) + if image_token_id is not None: + eval_logger.info( + f"A non-default image_token_id with image_token_id={self.image_token_id} and string value '{self.image_token}' was specified manually. Note that using an improper image_token placeholder may lead to ignored image input or errors!" + ) + else: + eval_logger.info( + f"A non-default image_token string with string value image_string='{image_string}' was specified manually. Note that using an improper image_token placeholder may lead to ignored image input or errors!" + ) + self.image_token = image_string + + def _create_tokenizer( + self, + pretrained: Union[str, transformers.PreTrainedModel], + tokenizer: Optional[ + Union[ + str, + transformers.ProcessorMixin, + ] + ], + revision: Optional[str] = "main", + trust_remote_code: Optional[bool] = False, + **kwargs, + ) -> None: + """ + Helper method during initialization. + + For the multimodal variant, we initialize not just + `self.tokenizer` but also `self.processor`. + """ + + if tokenizer: + if isinstance(tokenizer, str): + return transformers.AutoProcessor.from_pretrained( + tokenizer, + revision=revision, + trust_remote_code=trust_remote_code, + # use_fast=use_fast_tokenizer, + ) + else: + assert isinstance( + tokenizer, transformers.ProcessorMixin + ) # TODO: check this condition + return tokenizer + + # Get tokenizer based on 'pretrained' + if isinstance(pretrained, str): + model_name = pretrained + else: + # get the HF hub name via accessor on model + model_name = self.model.name_or_path + + self.processor = transformers.AutoProcessor.from_pretrained( + model_name, + revision=revision, + trust_remote_code=trust_remote_code, + # use_fast=use_fast_tokenizer, + ) + + self.tokenizer = self.processor.tokenizer + + def tok_multimodal_encode( + self, string, images, left_truncate_len=None, add_special_tokens=None + ): + """Helper function which encodes an image + string combo using AutoProcessor""" + # We inherit special token kwarg setup from HFLM.tok_encode + # special_tokens_kwargs = {} + + # by default for CausalLM - false or self.add_bos_token is set + # if add_special_tokens is None: + # special_tokens_kwargs = {"add_special_tokens": False or self.add_bos_token} + # otherwise the method explicitly defines the value + # else: + # special_tokens_kwargs = {"add_special_tokens": add_special_tokens} + + # encode text+images + # TODO: why does (Qwen2-VL) processor error when attempting to add special tokens to text? + encoding = self.processor( + text=string, images=images, return_tensors=None + ) # , **special_tokens_kwargs) + + # remove (and store) our tokenized text + text_encoding = encoding.pop("input_ids") + encoding.pop("attention_mask") + + # left-truncate the encoded context to be at most `left_truncate_len` tokens long + if left_truncate_len: + text_encoding = text_encoding[-left_truncate_len:] + + return text_encoding, encoding # image_encoding is a dict + + def _encode_multimodal_pair(self, context, continuation, images): + """Helper function to perform the role of TemplateLM._encode_pair + Except allowing for image input to also be processed alongside `context`. + + This method is a bit messy due to the need to defer conversion of image and text token input + into PyTorch tensors until the main inference loop. + """ + + n_spaces = len(context) - len(context.rstrip()) + if n_spaces > 0: + continuation = context[-n_spaces:] + continuation + context = context[:-n_spaces] + + # TODO: replace default placeholder with self.image_token, for contexts + + whole_enc, image_enc = self.tok_multimodal_encode( + context + continuation, images + ) + context_enc, _ = self.tok_multimodal_encode(context, images) + + # tok_multimodal_encode returns List[List[int]] for tokenized text. Get rid of the batch dim + # since we only are encoding a single string. + # TODO: this is a bit hacky, it'd be nice to make this generally cleaner + whole_enc, context_enc = whole_enc[0], context_enc[0] + + context_enc_len = len(context_enc) + continuation_enc = whole_enc[context_enc_len:] + + return context_enc, continuation_enc, image_enc + + def apply_chat_template(self, chat_history: List[Dict[str, str]]) -> str: + self.chat_applied = True + if not self.interleave: + for content in chat_history: + c = [] + text = content["content"] + + # Count and remove image placeholders + image_count = min( + self.max_images, text.count(DEFAULT_IMAGE_PLACEHOLDER) + ) + text = text.replace(DEFAULT_IMAGE_PLACEHOLDER, "") + + # Add image entries + for _ in range(image_count): + c.append({"type": "image", "image": None}) + + # Add single text entry at the end + c.append({"type": "text", "text": text}) + + content["content"] = c + else: + for content in chat_history: + c = [] + text = content["content"] + expected_image_count = min( + self.max_images, text.count(DEFAULT_IMAGE_PLACEHOLDER) + ) + actual_image_count = 0 + + text_parts = text.split(DEFAULT_IMAGE_PLACEHOLDER) + + for i, part in enumerate(text_parts): + # TODO: concatenate text parts (esp. if skipping images)? + if part: # Add non-empty text parts + c.append({"type": "text", "text": part}) + if ( + (i < len(text_parts) - 1) and i < self.max_images + ): # Add image placeholder after each split except the last + c.append({"type": "image"}) + actual_image_count += 1 + + content["content"] = c + + if actual_image_count != expected_image_count: + raise ValueError( + f"Mismatch in image placeholder count. Expected: {expected_image_count}, Actual: {actual_image_count}" + ) + + return self.processor.apply_chat_template( + chat_history, add_generation_prompt=True + ) + + def chat_template(self, chat_template: Union[bool, str] = False) -> Optional[str]: + if hasattr(self.processor, "apply_chat_template"): + _tokenizer = self.tokenizer + self.tokenizer = self.processor + + selected_template = super().chat_template(chat_template) + + self.tokenizer = _tokenizer + return selected_template + else: + return super().chat_template(chat_template) + + def tok_batch_multimodal_encode( + self, + strings: List[str], # note that input signature of this fn is different + images: List[List], # TODO: images are pil.Image at the moment, update typehint + padding_side: str = "left", + left_truncate_len: int = None, + truncation: bool = False, + ) -> Union[ + BatchEncoding, Dict[str, torch.Tensor] + ]: # note that this return signature differs from HFLM tok_batch_encode. + # NOTE: here, we replace tags with our model's corresponding image_token string value. + if not self.chat_applied: + # TODO: This still keeps the whitespace in the image placeholder, which is not ideal. + strings = [ + replace_placeholders( + string, DEFAULT_IMAGE_PLACEHOLDER, self.image_token, self.max_images + ) + for string in strings + ] + + # encode a batch of strings. converts to tensors and pads automatically, unlike tok_encode. + old_padding_side = self.tokenizer.padding_side + self.tokenizer.padding_side = padding_side + + # add_special_tokens = {"add_special_tokens": False or self.add_bos_token} + + images = [img[: self.max_images] for img in images] + if self.rgb: + images = [[img.convert("RGB") for img in sublist] for sublist in images] + + encoding = self.processor( + images=images, + text=strings, + truncation=truncation, + padding="longest", + return_tensors="pt", + # **add_special_tokens, # TODO: at least some Processors error out when passing this. How do we control whether text gets BOS added? + ) + + encoding.to( # TODO: our other tokenization methods in HFLM don't typically move to device. this breaks convention + self.device, self.model.dtype + ) # TODO: This only casts the pixel values. Should they always be float16? + if left_truncate_len: + encoding["input_ids"] = encoding["input_ids"][:, -left_truncate_len:] + encoding["attention_mask"] = encoding["attention_mask"][ + :, -left_truncate_len: + ] + self.tokenizer.padding_side = old_padding_side + + return encoding + + def _model_multimodal_call(self, inps, imgs, attn_mask=None, labels=None): + """ + TODO: update docstring + """ + # note: imgs is a dict. + with torch.no_grad(): + return self.model(inps, **imgs).logits + + def _model_multimodal_generate(self, inputs, max_length, stop, **generation_kwargs): + generation_kwargs["temperature"] = generation_kwargs.get("temperature", 0.0) + do_sample = generation_kwargs.get("do_sample", None) + + # The temperature has to be a strictly positive float -- if it is 0.0, use greedy decoding strategies + if generation_kwargs.get("temperature") == 0.0 and do_sample is None: + generation_kwargs["do_sample"] = do_sample = False + + if do_sample is False and generation_kwargs.get("temperature") == 0.0: + generation_kwargs.pop("temperature") + + stopping_criteria = stop_sequences_criteria( + self.tokenizer, + stop, + inputs["input_ids"].shape[1], + inputs["input_ids"].shape[0], + ) + return self.model.generate( + **inputs, + max_length=max_length, + stopping_criteria=stopping_criteria, + pad_token_id=self.tokenizer.pad_token_id, + use_cache=True, + **generation_kwargs, + ) + + def _batch_images(self, image_encs): + """ + Helper function: batch together image encodings across examples in a batch. + # TODO: for variable-sized images, this may break down. + """ + batched_imgs = {} + for key in image_encs[0].keys(): + batched_imgs[key] = torch.cat( + [ + torch.tensor( + image_enc[key], device=self.device, dtype=self.model.dtype + ) + for image_enc in image_encs + ], + dim=0, + ) + return batched_imgs + + def loglikelihood_rolling(self, requests: List[Instance]) -> List[float]: + raise NotImplementedError( + "model type `hf-multimodal` does not support loglikelihood_rolling. Use 'hf' model type for text-only loglikelihood_rolling tasks ", + "this is because we do not support measuring the loglikelihood a model assigns to an image.", + ) + + def loglikelihood( + self, requests: List[Instance], disable_tqdm: bool = False + ) -> List[Tuple[float, bool]]: + raise NotImplementedError( + "'loglikelihood' requests for model type `hf-multimodal` are not yet tested. This feature will be enabled when a loglikelihood-based multiple-choice VQA dataset is added!" + ) + + new_reqs = [] + for context, continuation, aux_arguments in [req.args for req in requests]: + if context == "": + raise ValueError( + "Must get non-empty context for multimodal requests! You might be trying to run 'loglikelihood_rolling', which is not supported in the multimodal case." + ) + else: + visuals = aux_arguments["visual"] + + context_enc, continuation_enc, image_enc = self._encode_multimodal_pair( + context, continuation, visuals + ) + # TODO: key to pick for caching images + new_reqs.append( + ( + (context, continuation, visuals), + context_enc, + continuation_enc, + image_enc, + ) + ) + + return self._loglikelihood_tokens(new_reqs, disable_tqdm=disable_tqdm) + + def _loglikelihood_tokens( + self, + requests: List[ + Tuple[Tuple[None, str, str], List[int], List[int], List[int]] + ], # TODO: update typehint to be correct + disable_tqdm: bool = False, + override_bs: int = None, + ) -> List[Tuple[float, bool]]: + res = [] + + # TODO: **improve multimodal collation.** We currently ignore image size when ordering docs. ideally we'd take them into account + def _collate(req: Tuple[Tuple[str, str], List[int], List[int]]): + """Defines the key for the sorted method""" + # the negative sign on len(toks) sorts descending - this has a few advantages: + # - time estimates will always be over not underestimates, which is more useful for planning + # - to know the size of a batch when going through the list, you know the first one is always the batch + # padded context length. this is useful to simplify the batching logic and more importantly to make + # automatic adaptive batches much much easier to implement + # - any OOMs will happen right away rather than near the end + toks = req[1] + req[2] + return -len(toks), tuple(toks) + + def _lookup_one_token_cont(req: Tuple[Tuple[str, str], List[int], List[int]]): + """Defines the key to group and lookup one-token continuations""" + # Use with group_by="contexts" (optional)" + # allows for the creation of a lookup, so we can reuse logits in case of one-token continuations. + # speeds up some multiple-choice tasks proportionally to the number of choices. + # groups requests by context+continuation[:-1] and infer on one request/group. + return req[-1] + req[-3] + req[-2][:-1] + + re_ord = Collator( + requests, + sort_fn=_collate, + group_by="contexts" # TODO: can't group-by just "contexts" any more, need to incorporate imgs + if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM + and self.logits_cache + else None, + group_fn=_lookup_one_token_cont, + ) + + # automatic (variable) batch size detection for vectorization + # pull longest context sample from request + n_reordered_requests = len(re_ord) + batch_size = ( + self.batch_size + if self.batch_size != "auto" + else override_bs + if override_bs is not None + else 0 + ) + batch_fn = ( + self._batch_scheduler + if self.batch_size == "auto" + and n_reordered_requests > 0 + and not override_bs + else None + ) + + chunks = re_ord.get_batched(n=batch_size, batch_fn=batch_fn) + pbar = tqdm( + total=len(requests), + disable=(disable_tqdm or (self.rank != 0)), + desc="Running loglikelihood requests with text+image input", + ) + for chunk in chunks: + imgs = [] + inps = [] + cont_toks_list = [] + inplens = [] + + padding_len_inp = None + # because vectorizing is annoying, we first convert each (context, continuation) pair to padded + # tensors, then we pack them together into a batch, call the model, and then pick it all apart + # again because vectorizing is annoying + + for _, context_enc, continuation_enc, image_enc in chunk: + # sanity check + assert len(image_enc) > 0 + assert len(context_enc) > 0 + assert len(continuation_enc) > 0 + assert len(continuation_enc) <= self.max_length + + # how this all works (illustrated on a causal decoder-only setup): + # CTX CONT + # inp 0 1 2 3|4 5 6 7 8 9 <- last token is deleted by inp[:, :-1] + # model \ \ + # logits 1 2 3|4 5 6 7 8 9 <- the ctx half gets tossed out by the + # cont_toks 4 5 6 7 8 9 [:, -len(continuation_enc):, :self.vocab_size] slice + + # when too long to fit in context, truncate from the left + # TODO: assuming that we won't handle enc-dec Vision2Seq models. Is that a safe assumption? + inp = torch.tensor( + (context_enc + continuation_enc)[-(self.max_length + 1) :][:-1], + dtype=torch.long, + device=self.device, + ) + (inplen,) = inp.shape + + padding_len_inp = ( + max(padding_len_inp, inplen) + if padding_len_inp is not None + else inplen + ) + + inps.append(inp) # [1, inp_length] + cont_toks_list.append(continuation_enc) + inplens.append(inplen) + + imgs.append(image_enc) + + # create encoder attn mask and batched conts, if seq2seq + call_kwargs = {} + batched_inps = pad_and_concat( + padding_len_inp, inps, padding_side="right" + ) # [batch, padding_len_inp] + # batch our examples' image inputs together + batched_imgs = self._batch_images( + imgs + ) # TODO: fix/test for bs>1 case with differently-sized imgs! + + multi_logits = F.log_softmax( + self._model_multimodal_call(batched_inps, batched_imgs, **call_kwargs), + dim=-1, + ) # [batch, padding_length (inp or cont), vocab] + + for ( + request_str, + ctx_tokens, + _, + image_encs, + ), logits, inplen, cont_toks in zip( + chunk, multi_logits, inplens, cont_toks_list + ): + # Slice to original seq length + contlen = len(cont_toks) + # take only logits in the continuation + # (discard context toks if decoder-only ; discard right-padding) + # also discards + checks for "virtual tokens" in the causal LM's input window + # from prompt/prefix tuning tokens, if applicable + ctx_len = ( + inplen + (logits.shape[0] - padding_len_inp) + if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM + else None + ) + logits = self._select_cont_toks(logits, contlen=contlen, inplen=ctx_len) + logits = logits.unsqueeze(0) # [1, seq, vocab] + + # Check if per-token argmax is exactly equal to continuation + greedy_tokens = logits.argmax(dim=-1) + + # check for one-token continuation cache hits. + # noop in case group_by != "contexts" or no cache hit and returns the + # original args. Otherwise, expands the logits batch dimension and yields each + # batch along with matching continuation tokens and prompt strings. + # logits -> [1, seq, vocab] + for request_str, cont_toks, logits in re_ord.get_cache( + req_str=request_str, + cxt_toks=ctx_tokens, + cont_toks=cont_toks, + logits=logits, + ): + cont_toks = torch.tensor( + cont_toks, dtype=torch.long, device=self.device + ).unsqueeze(0) # [1, seq] + max_equal = (greedy_tokens == cont_toks).all() + + # Obtain log-probs at the corresponding continuation token indices + # last_token_slice = logits[:, -1, :].squeeze(0).tolist() + logits = torch.gather(logits, 2, cont_toks.unsqueeze(-1)).squeeze( + -1 + ) # [1, seq] + + # Answer: (log prob, is-exact-match) + answer = (float(logits.sum()), bool(max_equal)) + + res.append(answer) + + self.cache_hook.add_partial( + "loglikelihood", request_str, answer + ) # TODO: choose convention for adding images into the cache key + pbar.update(1) + + pbar.close() + + return re_ord.get_original(res) + + def generate_until( + self, requests: List[Instance], disable_tqdm: bool = False + ) -> List[str]: + # TODO: back out to HFLM.generate_until() for all requests without aux_arguments (text-only reqs) + res = [] + + def _collate(x): + # the negative sign on len(toks) sorts descending - this has a few advantages: + # - time estimates will always be over not underestimates, which is more useful for planning + # - to know the size of a batch when going through the list, you know the first one is always the batch + # padded context length. this is useful to simplify the batching logic and more importantly to make + # automatic adaptive batches much much easier to implement + # - any OOMs will happen right away rather than near the end + toks = self.tok_encode(x[0]) + return -len(toks), x[0] + + pbar = tqdm( + total=len(requests), + disable=(disable_tqdm or (self.rank != 0)), + desc="Running generate_until requests with text+image input", + ) + # TODO: port auto-batch sizing into this. + + # we group requests by their generation_kwargs, + # so that we don't try to execute e.g. greedy sampling and temp=0.8 sampling + # in the same batch. + re_ords = Collator( + [reg.args for reg in requests], + _collate, + group_by="gen_kwargs", + group_fn=lambda x: x[1], + ) + chunks = re_ords.get_batched(n=self.batch_size, batch_fn=None) + + ### Up to here: was identical to non-multimodal HFLM generate_until ### + + for chunk in chunks: + contexts, all_gen_kwargs, aux_arguments = zip(*chunk) + + visuals = [arg["visual"] for arg in aux_arguments] + + if not isinstance(contexts, list): + contexts = list( + contexts + ) # for Qwen2-VL, processor is unhappy accepting a tuple of strings instead of a list. + # TODO: could we upstream this workaround to HF? + ### this part onward: same as HFLM ### + + # we assume all gen kwargs in the batch are the same + # this is safe to assume because the `grouper` object ensures it. + gen_kwargs = all_gen_kwargs[0] + # unpack our keyword arguments. + until = None + if isinstance(gen_kwargs, dict): + kwargs = copy.deepcopy(gen_kwargs) # edge case for repeats > 1 + if "until" in kwargs.keys(): + until = kwargs.pop("until") + if isinstance(until, str): + until = [until] + elif not isinstance(until, list): + raise ValueError( + f"Expected `kwargs['until']` to be of type Union[str,list] but got {until}" + ) + else: + raise ValueError( + f"Expected `kwargs` to be of type `dict` but got {type(gen_kwargs)}" + ) + # add EOS token to stop sequences + eos = self.tok_decode(self.eot_token_id, skip_special_tokens=False) + if not until: + until = [eos] + else: + until.append(eos) + if "max_gen_toks" in kwargs.keys(): + max_gen_toks = kwargs.pop("max_gen_toks") + else: + max_gen_toks = self.max_gen_toks + + ### end stuff that's entirely copied verbatim from HFLM ### + + max_ctx_len = self.max_length - max_gen_toks + + inputs = self.tok_batch_multimodal_encode( + contexts, + visuals, + left_truncate_len=max_ctx_len, + truncation=self.truncation, + ) + + context_enc = inputs["input_ids"] + + if "max_length" not in kwargs: + kwargs["max_length"] = context_enc.shape[1] + max_gen_toks + + cont = self._model_multimodal_generate(inputs, stop=until, **kwargs) + + del inputs + torch.cuda.empty_cache() + import gc + + gc.collect() + + ### essentially same as HFLM beyond this line! + + cont_toks_list = cont.tolist() + for cont_toks, context in zip(cont_toks_list, contexts): + # discard context + left-padding toks if using causal decoder-only VLM + cont_toks = cont_toks[context_enc.shape[1] :] + + s = self.tok_decode(cont_toks) + + # use secondary stop seqs to cut off should-have-been-stopped content post-hoc + for term in until: + if len(term) > 0: + # ignore '' separator, + # for seq2seq case where self.tok_decode(self.eot_token_id) = '' + s = s.split(term)[0] + + res.append(s) + self.cache_hook.add_partial( + "generate_until", (context, gen_kwargs), s + ) # TODO: cache key for multimodal input should be what? + pbar.update(1) + # reorder this group of results back to original unsorted form + res = re_ords.get_original(res) + + pbar.close() + return res diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 01a8cf67..63ad1440 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -448,7 +448,16 @@ class HFLM(TemplateLM): Helper method during initialization. Determines the backend ("causal" (decoder-only) or "seq2seq" (encoder-decoder)) model type to be used. + sets `self.AUTO_MODEL_CLASS` appropriately if not already set. """ + # escape hatch: if we're using a subclass that shouldn't follow + # the default _get_backend logic, + # then skip over the method. + # TODO: this seems very much undesirable in some cases--our code in HFLM + # references AutoModelForCausalLM at times to check for equality + if self.AUTO_MODEL_CLASS is not None: + return + assert backend in ["default", "causal", "seq2seq"] if backend != "default": diff --git a/lm_eval/models/utils.py b/lm_eval/models/utils.py index 8a81e5de..72fac038 100644 --- a/lm_eval/models/utils.py +++ b/lm_eval/models/utils.py @@ -664,3 +664,37 @@ def configure_pad_token( tokenizer.add_special_tokens({"pad_token": "<|pad|>"}) return tokenizer + + +def replace_placeholders( + string: str, default_placeholder: str, image_token: str, max_images: int +): + """ + A utility function used for local multimodal models. It locates all `placeholder` string + occurrences in the given input `string_` and replaces the first `max_count` instances with + `replacement`, and all subsequent occurrences with the empty string. + + This is used to replace placeholder tags by model-specific image tokens like <|image_pad|> + and to allow for only the first `max_count` images to be passed to a model if desired. + + :param string: The original string containing placeholders. + :param default_placeholder: The placeholder text to be replaced. + :param image_token: The token to replace the placeholder with. + :param max_images: The maximum number of replacements to make. + :return: The string with placeholders replaced. + """ + count = 0 + result = [] + + parts = string.split(default_placeholder) + for part in parts[:-1]: # Iterate through all but the last part + result.append(part) + if count < max_images: + result.append(image_token) + count += 1 + elif default_placeholder != image_token: + result.append(default_placeholder) + + # Add the last part of the string + result.append(parts[-1]) + return "".join(result) diff --git a/lm_eval/models/vllm_vlms.py b/lm_eval/models/vllm_vlms.py new file mode 100644 index 00000000..5a126090 --- /dev/null +++ b/lm_eval/models/vllm_vlms.py @@ -0,0 +1,279 @@ +import copy +from typing import Dict, List, Optional + +import transformers +from more_itertools import distribute +from tqdm import tqdm + +from lm_eval.api.instance import Instance +from lm_eval.api.registry import register_model +from lm_eval.models.utils import Collator, undistribute +from lm_eval.models.vllm_causallms import VLLM +from lm_eval.utils import simple_parse_args_string + + +try: + import ray + from vllm import LLM, SamplingParams + from vllm.lora.request import LoRARequest # noqa: F401 + from vllm.transformers_utils.tokenizer import get_tokenizer # noqa: F401 +except ModuleNotFoundError: + pass + + +DEFAULT_IMAGE_PLACEHOLDER = "" + + +@register_model("vllm-vlm") +class VLLM_VLM(VLLM): + MULTIMODAL = True + + def __init__( + self, + pretrained: str, + trust_remote_code: Optional[bool] = False, + revision: Optional[str] = None, + interleave: bool = True, + # TODO: handle max_images and limit_mm_per_prompt better + max_images: int = 999, + limit_mm_per_prompt: str = "image=1", + **kwargs, + ): + kwargs["limit_mm_per_prompt"] = simple_parse_args_string(limit_mm_per_prompt) + super().__init__( + pretrained=pretrained, + trust_remote_code=trust_remote_code, + revision=revision, + **kwargs, + ) + self.interleave = interleave + self.max_images = max_images + self.processor = transformers.AutoProcessor.from_pretrained( + pretrained, + revision=revision, + trust_remote_code=trust_remote_code, + ) + self.chat_applied: bool = False + + def tok_batch_multimodal_encode( + self, + strings: List[str], # note that input signature of this fn is different + images, # TODO: typehint on this + left_truncate_len: int = None, + truncation: bool = False, + ): + images = [img[: self.max_images] for img in images] + + outputs = [] + for x, i in zip(strings, images): + inputs = { + "prompt": x, + "multi_modal_data": {"image": i}, + } + outputs.append(inputs) + return outputs + + def _model_generate( + self, + requests: List[List[dict]] = None, + generate: bool = False, + max_tokens: int = None, + stop: Optional[List[str]] = None, + **kwargs, + ): + if generate: + kwargs = self.modify_gen_kwargs(kwargs) + sampling_params = SamplingParams(max_tokens=max_tokens, stop=stop, **kwargs) + else: + sampling_params = SamplingParams( + temperature=0, prompt_logprobs=1, max_tokens=1, detokenize=False + ) + if self.data_parallel_size > 1: + # vLLM hangs if tensor_parallel > 1 and resources are set in ray.remote + # also seems to only work with decorator and not with ray.remote() fn + # see https://github.com/vllm-project/vllm/issues/973 + # note: this has changed on 0.3.3, and it only works now if num_gpus are set. + # but then tensor_parallel breaks + @ray.remote + def run_inference_one_model( + model_args: dict, sampling_params, requests: List[List[dict]] + ): + llm = LLM(**model_args) + return llm.generate(requests, sampling_params=sampling_params) + + # dispatch requests to all self.data_parallel_size workers, in interleaved fashion + # interleaved important to balance context lengths across workers + requests = [list(x) for x in distribute(self.data_parallel_size, requests)] + inputs = ((self.model_args, sampling_params, req) for req in requests) + object_refs = [run_inference_one_model.remote(*x) for x in inputs] + results = ray.get(object_refs) + # Invoke ray.shutdown() to prevent hang-ups if subsequent calls required. + ray.shutdown() + # flatten results + return undistribute(results) + + if self.lora_request is not None: + outputs = self.model.generate( + requests, + sampling_params=sampling_params, + use_tqdm=True if self.batch_size == "auto" else False, + lora_request=self.lora_request, + ) + else: + outputs = self.model.generate( + requests, + sampling_params=sampling_params, + use_tqdm=True if self.batch_size == "auto" else False, + ) + return outputs + + def apply_chat_template(self, chat_history: List[Dict[str, str]]) -> str: + self.chat_applied = True + if not self.interleave: + for content in chat_history: + c = [] + text = content["content"] + + # Count and remove image placeholders + image_count = min( + self.max_images, text.count(DEFAULT_IMAGE_PLACEHOLDER) + ) + text = text.replace(DEFAULT_IMAGE_PLACEHOLDER, "") + + # Add image entries + for _ in range(image_count): + c.append({"type": "image", "image": None}) + + # Add single text entry at the end + c.append({"type": "text", "text": text}) + + content["content"] = c + else: + for content in chat_history: + c = [] + text = content["content"] + expected_image_count = min( + self.max_images, text.count(DEFAULT_IMAGE_PLACEHOLDER) + ) + actual_image_count = 0 + + text_parts = text.split(DEFAULT_IMAGE_PLACEHOLDER) + + for i, part in enumerate(text_parts): + # TODO: concatenate text parts (esp. if skipping images)? + if part: # Add non-empty text parts + c.append({"type": "text", "text": part}) + if ( + (i < len(text_parts) - 1) and i < self.max_images + ): # Add image placeholder after each split except the last + c.append({"type": "image"}) + actual_image_count += 1 + + content["content"] = c + + if actual_image_count != expected_image_count: + raise ValueError( + f"Mismatch in image placeholder count. Expected: {expected_image_count}, Actual: {actual_image_count}" + ) + + return self.processor.apply_chat_template( + chat_history, add_generation_prompt=True + ) + + def generate_until( + self, requests: List[Instance], disable_tqdm: bool = False + ) -> List[str]: + # TODO: support text-only reqs + res = [] + + def _collate(x): + # the negative sign on len(toks) sorts descending - this has a few advantages: + # - time estimates will always be over not underestimates, which is more useful for planning + # - to know the size of a batch when going through the list, you know the first one is always the batch + # padded context length. this is useful to simplify the batching logic and more importantly to make + # automatic adaptive batches much much easier to implement + # - any OOMs will happen right away rather than near the end + toks = self.tok_encode(x[0]) + return -len(toks), x[0] + + pbar = tqdm( + total=len(requests), + disable=(disable_tqdm or (self.rank != 0)), + desc="Running generate_until requests with text+image input", + ) + # TODO: port auto-batch sizing into this. + + # we group requests by their generation_kwargs, + # so that we don't try to execute e.g. greedy sampling and temp=0.8 sampling + # in the same batch. + re_ords = Collator( + [reg.args for reg in requests], + _collate, + group_by="gen_kwargs", + group_fn=lambda x: x[1], + ) + chunks = re_ords.get_batched(n=self.batch_size, batch_fn=None) + + for chunk in chunks: + contexts, all_gen_kwargs, aux_arguments = zip(*chunk) + + visuals = [arg["visual"] for arg in aux_arguments] + + if not isinstance(contexts, list): + contexts = list( + contexts + ) # for Qwen2-VL, processor is unhappy accepting a tuple of strings instead of a list. + # TODO: could we upstream this workaround to HF? + + # we assume all gen kwargs in the batch are the same + # this is safe to assume because the `grouper` object ensures it. + gen_kwargs = all_gen_kwargs[0] + # unpack our keyword arguments. + until = None + if isinstance(gen_kwargs, dict): + kwargs = copy.deepcopy(gen_kwargs) # edge case for repeats > 1 + if "until" in kwargs.keys(): + until = kwargs.pop("until") + if isinstance(until, str): + until = [until] + elif not isinstance(until, list): + raise ValueError( + f"Expected `kwargs['until']` to be of type Union[str,list] but got {until}" + ) + else: + raise ValueError( + f"Expected `kwargs` to be of type `dict` but got {type(gen_kwargs)}" + ) + # add EOS token to stop sequences + eos = self.tokenizer.decode(self.eot_token_id) + if not until: + until = [eos] + else: + until.append(eos) + if "max_gen_toks" in kwargs.keys(): + max_gen_toks = kwargs.pop("max_gen_toks") + else: + max_gen_toks = self.max_gen_toks + + max_ctx_len = self.max_length - max_gen_toks + + inputs = self.tok_batch_multimodal_encode( + contexts, + visuals, + left_truncate_len=max_ctx_len, + ) + + cont = self._model_generate(inputs, stop=until, generate=True, **kwargs) + + for output, context in zip(cont, contexts): + generated_text = output.outputs[0].text + res.append(generated_text) + self.cache_hook.add_partial( + "generate_until", (context, gen_kwargs), generated_text + ) + pbar.update(1) + # reorder this group of results back to original unsorted form + res = re_ords.get_original(res) + + pbar.close() + return res diff --git a/lm_eval/tasks/mmmu/README.md b/lm_eval/tasks/mmmu/README.md new file mode 100644 index 00000000..e9d0da12 --- /dev/null +++ b/lm_eval/tasks/mmmu/README.md @@ -0,0 +1,150 @@ +# MMMU Benchmark + +### Paper + +Title: `MMMU: A Massive Multi-discipline MultimodalUnderstanding and Reasoning Benchmark for Expert AGI` + +Abstract: `MMMU is a new benchmark designed to evaluate multimodal models on massive multi-discipline tasks demanding college-level subject knowledge and deliberate reasoning.` + +`The benchmark is composed of 30 tasks, for a total of 900 mixed image+text examples (some with multiple images in context)` + +Homepage: `https://github.com/MMMU-Benchmark/MMMU/tree/main/mmmu` + +Note: Some questions have multiple images in context. To control for this use `max_images=N` in model init. + +### Citation + +``` +@inproceedings{yue2023mmmu, + title={MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI}, + author={Xiang Yue and Yuansheng Ni and Kai Zhang and Tianyu Zheng and Ruoqi Liu and Ge Zhang and Samuel Stevens and Dongfu Jiang and Weiming Ren and Yuxuan Sun and Cong Wei and Botao Yu and Ruibin Yuan and Renliang Sun and Ming Yin and Boyuan Zheng and Zhenzhu Yang and Yibo Liu and Wenhao Huang and Huan Sun and Yu Su and Wenhu Chen}, + booktitle={Proceedings of CVPR}, + year={2024}, + } +``` + +### Groups, Tags, and Tasks + +#### Groups + +* `mmmu_val` +* `mmmu_val_art_and_design` +* `mmmu_val_business` +* `mmmu_val_health_and_medicine` +* `mmmu_val_humanities_and_social_science` +* `mmmu_val_science` +* `mmmu_val_tech_and_engineering` + +#### Tags + + +#### Tasks + +* `mmmu_val_accounting` +* `mmmu_val_agriculture` +* `mmmu_val_architecture_and_engineering.yaml` +* `mmmu_val_art` +* `mmmu_val_art_theory` +* `mmmu_val_basic_medical_science` +* `mmmu_val_biology` +* `mmmu_val_chemistry` +* `mmmu_val_computer_science` +* `mmmu_val_clinical_medicine` +* `mmmu_val_design` +* `mmmu_val_diagnostics_and_laboratory_medicine` +* `mmmu_val_electronics` +* `mmmu_val_energy_and_power` +* `mmmu_val_economics` +* `mmmu_val_finance` +* `mmmu_val_geography` +* `mmmu_val_history` +* ... + +### Variants + +The `mmmu_val` group implements MMMU using processing code [from the original MMMU authors](https://github.com/MMMU-Benchmark/MMMU/tree/main/mmmu) and uses the prompt format found in [the MMMU repository for Llava-1.5](https://github.com/MMMU-Benchmark/MMMU/blob/main/mmmu/configs/llava1.5.yaml). This implementation should give scores on par with or slightly higher than those reported by [lmms-eval](https://github.com/EvolvingLMMs-Lab/lmms-eval/tree/main/lmms_eval/tasks/mmmu) for `mmmu_val` and the MMMU repository code. + +Scores on several tested models (**all with `--apply_chat_template`**) are: + +Qwen2-VL-2B: +``` +hf-multimodal (pretrained=Qwen/Qwen2-VL-2B-Instruct,attn_implementation=flash_attention_2,dtype=bfloat16,convert_img_format=True), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 2 +``` +``` +| Groups |Version|Filter|n-shot|Metric| |Value | |Stderr| +|--------------------------------|------:|------|------|------|---|-----:|---|-----:| +|mmmu_val | 0|none | |acc |↑ |0.3778|± |0.0155| +| - Art and Design | 0|none | |acc |↑ |0.5500|± |0.0415| +| - Business | 0|none | |acc |↑ |0.3600|± |0.0389| +| - Health and Medicine | 0|none | |acc |↑ |0.3667|± |0.0394| +| - Humanities and Social Science| 0|none | |acc |↑ |0.5167|± |0.0438| +| - Science | 0|none | |acc |↑ |0.2467|± |0.0352| +| - Tech and Engineering | 0|none | |acc |↑ |0.3143|± |0.0317| +``` +Author-reported score: 41.1% + + +Qwen2-VL-7B: +``` +hf-multimodal (pretrained=Qwen/Qwen2-VL-7B-Instruct,attn_implementation=flash_attention_2,dtype=bfloat16,convert_img_format=True), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 2 +``` +``` +| Groups |Version|Filter|n-shot|Metric| |Value | |Stderr| +|--------------------------------|------:|------|------|------|---|-----:|---|-----:| +|mmmu_val | 0|none | |acc |↑ |0.5056|± |0.0160| +| - Art and Design | 0|none | |acc |↑ |0.6917|± |0.0398| +| - Business | 0|none | |acc |↑ |0.4333|± |0.0406| +| - Health and Medicine | 0|none | |acc |↑ |0.5667|± |0.0401| +| - Humanities and Social Science| 0|none | |acc |↑ |0.6750|± |0.0426| +| - Science | 0|none | |acc |↑ |0.3800|± |0.0392| +| - Tech and Engineering | 0|none | |acc |↑ |0.4000|± |0.0341| +``` +Author-reported score: 54.1% + +Idefics2-8B: +``` +hf-multimodal (pretrained=HuggingFaceM4/idefics2-8b,attn_implementation=flash_attention_2,dtype=bfloat16,convert_img_format=True,max_images=2), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 2 +``` +``` +| Groups |Version|Filter|n-shot|Metric| |Value | |Stderr| +|--------------------------------|------:|------|------|------|---|-----:|---|-----:| +|mmmu_val | 0|none | |acc |↑ |0.4011|± |0.0154| +| - Art and Design | 0|none | |acc |↑ |0.6167|± |0.0436| +| - Business | 0|none | |acc |↑ |0.3200|± |0.0373| +| - Health and Medicine | 0|none | |acc |↑ |0.4000|± |0.0401| +| - Humanities and Social Science| 0|none | |acc |↑ |0.5750|± |0.0424| +| - Science | 0|none | |acc |↑ |0.2600|± |0.0358| +| - Tech and Engineering | 0|none | |acc |↑ |0.3381|± |0.0312| +``` +Author-reported score: ~43% + +Llava-v1.6-Mistral-7B: +``` +hf-multimodal (pretrained=llava-hf/llava-v1.6-mistral-7b-hf,attn_implementation=flash_attention_2,dtype=bfloat16,convert_img_format=True), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 2 +``` +``` +| Groups |Version|Filter|n-shot|Metric| |Value | |Stderr| +|--------------------------------|------:|------|------|------|---|-----:|---|-----:| +|mmmu_val | 0|none | |acc |↑ |0.3522|± |0.0151| +| - Art and Design | 0|none | |acc |↑ |0.5167|± |0.0440| +| - Business | 0|none | |acc |↑ |0.2667|± |0.0362| +| - Health and Medicine | 0|none | |acc |↑ |0.3867|± |0.0397| +| - Humanities and Social Science| 0|none | |acc |↑ |0.5917|± |0.0433| +| - Science | 0|none | |acc |↑ |0.2200|± |0.0342| +| - Tech and Engineering | 0|none | |acc |↑ |0.2524|± |0.0299| +``` +Author-reported score: 35.3% + + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [x] Is the task an existing benchmark in the literature? + * [x] Have you referenced the original paper that introduced the task? + * [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [x] Is the "Main" variant of this task clearly denoted? +* [x] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [x] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/mmmu/_art_and_design.yaml b/lm_eval/tasks/mmmu/_art_and_design.yaml new file mode 100644 index 00000000..b0dda187 --- /dev/null +++ b/lm_eval/tasks/mmmu/_art_and_design.yaml @@ -0,0 +1,13 @@ +group: mmmu_val_art_and_design +group_alias: Art and Design +task: + - mmmu_val_art + - mmmu_val_art_theory + - mmmu_val_design + - mmmu_val_music +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/mmmu/_business.yaml b/lm_eval/tasks/mmmu/_business.yaml new file mode 100644 index 00000000..497948e5 --- /dev/null +++ b/lm_eval/tasks/mmmu/_business.yaml @@ -0,0 +1,14 @@ +group: mmmu_val_business +group_alias: Business +task: + - mmmu_val_accounting + - mmmu_val_economics + - mmmu_val_finance + - mmmu_val_manage + - mmmu_val_marketing +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/mmmu/_health_and_medicine.yaml b/lm_eval/tasks/mmmu/_health_and_medicine.yaml new file mode 100644 index 00000000..04709d3d --- /dev/null +++ b/lm_eval/tasks/mmmu/_health_and_medicine.yaml @@ -0,0 +1,14 @@ +group: mmmu_val_health_and_medicine +group_alias: Health and Medicine +task: + - mmmu_val_basic_medical_science + - mmmu_val_clinical_medicine + - mmmu_val_diagnostics_and_laboratory_medicine + - mmmu_val_pharmacy + - mmmu_val_public_health +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/mmmu/_humanities_and_social_sciences.yaml b/lm_eval/tasks/mmmu/_humanities_and_social_sciences.yaml new file mode 100644 index 00000000..b8d70a9e --- /dev/null +++ b/lm_eval/tasks/mmmu/_humanities_and_social_sciences.yaml @@ -0,0 +1,13 @@ +group: mmmu_val_humanities_and_social_science +group_alias: Humanities and Social Science +task: + - mmmu_val_history + - mmmu_val_literature + - mmmu_val_sociology + - mmmu_val_psychology +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/mmmu/_mmmu.yaml b/lm_eval/tasks/mmmu/_mmmu.yaml new file mode 100644 index 00000000..6bcd234b --- /dev/null +++ b/lm_eval/tasks/mmmu/_mmmu.yaml @@ -0,0 +1,14 @@ +group: mmmu_val +task: + - mmmu_val_art_and_design + - mmmu_val_business + - mmmu_val_health_and_medicine + - mmmu_val_humanities_and_social_science + - mmmu_val_science + - mmmu_val_tech_and_engineering +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/mmmu/_science.yaml b/lm_eval/tasks/mmmu/_science.yaml new file mode 100644 index 00000000..9b41585a --- /dev/null +++ b/lm_eval/tasks/mmmu/_science.yaml @@ -0,0 +1,14 @@ +group: mmmu_val_science +group_alias: Science +task: + - mmmu_val_biology + - mmmu_val_chemistry + - mmmu_val_geography + - mmmu_val_math + - mmmu_val_physics +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/mmmu/_tech_and_engineering.yaml b/lm_eval/tasks/mmmu/_tech_and_engineering.yaml new file mode 100644 index 00000000..956f9906 --- /dev/null +++ b/lm_eval/tasks/mmmu/_tech_and_engineering.yaml @@ -0,0 +1,16 @@ +group: mmmu_val_tech_and_engineering +group_alias: Tech and Engineering +task: + - mmmu_val_agriculture + - mmmu_val_architecture_and_engineering + - mmmu_val_computer_science + - mmmu_val_electronics + - mmmu_val_energy_and_power + - mmmu_val_materials + - mmmu_val_mechanical_engineering +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/mmmu/_template_yaml b/lm_eval/tasks/mmmu/_template_yaml new file mode 100644 index 00000000..f92ce60d --- /dev/null +++ b/lm_eval/tasks/mmmu/_template_yaml @@ -0,0 +1,19 @@ +dataset_path: MMMU/MMMU +validation_split: validation +output_type: generate_until +doc_to_image: !function utils.doc_to_image +doc_to_text: !function utils.doc_to_text +doc_to_target: "answer" +process_results: !function utils.process_results +generation_kwargs: + until: + - "<|endoftext|>" + temperature: 0.0 + do_sample: false + max_gen_toks: 512 +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/mmmu/mmmu_accounting.yaml b/lm_eval/tasks/mmmu/mmmu_accounting.yaml new file mode 100644 index 00000000..3c4aa41d --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_accounting.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_accounting +include: _template_yaml +task_alias: Accounting +dataset_name: Accounting diff --git a/lm_eval/tasks/mmmu/mmmu_agriculture.yaml b/lm_eval/tasks/mmmu/mmmu_agriculture.yaml new file mode 100644 index 00000000..387f33f7 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_agriculture.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_agriculture +include: _template_yaml +task_alias: Agriculture +dataset_name: Agriculture diff --git a/lm_eval/tasks/mmmu/mmmu_architecture_and_engineering.yaml b/lm_eval/tasks/mmmu/mmmu_architecture_and_engineering.yaml new file mode 100644 index 00000000..829ee3a8 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_architecture_and_engineering.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_architecture_and_engineering +include: _template_yaml +task_alias: Architecture and Engineering +dataset_name: Architecture_and_Engineering diff --git a/lm_eval/tasks/mmmu/mmmu_art.yaml b/lm_eval/tasks/mmmu/mmmu_art.yaml new file mode 100644 index 00000000..ff812ab3 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_art.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_art +include: _template_yaml +task_alias: Art +dataset_name: Art diff --git a/lm_eval/tasks/mmmu/mmmu_art_theory.yaml b/lm_eval/tasks/mmmu/mmmu_art_theory.yaml new file mode 100644 index 00000000..d6331871 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_art_theory.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_art_theory +include: _template_yaml +task_alias: Art Theory +dataset_name: Art_Theory diff --git a/lm_eval/tasks/mmmu/mmmu_basic_medical_science.yaml b/lm_eval/tasks/mmmu/mmmu_basic_medical_science.yaml new file mode 100644 index 00000000..d7486f1e --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_basic_medical_science.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_basic_medical_science +include: _template_yaml +task_alias: Basic Medical Science +dataset_name: Basic_Medical_Science diff --git a/lm_eval/tasks/mmmu/mmmu_biology.yaml b/lm_eval/tasks/mmmu/mmmu_biology.yaml new file mode 100644 index 00000000..49d36f38 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_biology.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_biology +include: _template_yaml +task_alias: Biology +dataset_name: Biology diff --git a/lm_eval/tasks/mmmu/mmmu_chemistry.yaml b/lm_eval/tasks/mmmu/mmmu_chemistry.yaml new file mode 100644 index 00000000..cb096531 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_chemistry.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_chemistry +include: _template_yaml +task_alias: Chemistry +dataset_name: Chemistry diff --git a/lm_eval/tasks/mmmu/mmmu_clinical_medicine.yaml b/lm_eval/tasks/mmmu/mmmu_clinical_medicine.yaml new file mode 100644 index 00000000..a0833d16 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_clinical_medicine.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_clinical_medicine +include: _template_yaml +task_alias: Clinical Medicine +dataset_name: Clinical_Medicine diff --git a/lm_eval/tasks/mmmu/mmmu_computer_science.yaml b/lm_eval/tasks/mmmu/mmmu_computer_science.yaml new file mode 100644 index 00000000..53c91a61 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_computer_science.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_computer_science +include: _template_yaml +task_alias: Computer Science +dataset_name: Computer_Science diff --git a/lm_eval/tasks/mmmu/mmmu_design.yaml b/lm_eval/tasks/mmmu/mmmu_design.yaml new file mode 100644 index 00000000..0367dd65 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_design.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_design +include: _template_yaml +task_alias: Design +dataset_name: Design diff --git a/lm_eval/tasks/mmmu/mmmu_diagnostics_and_laboratory_medicine.yaml b/lm_eval/tasks/mmmu/mmmu_diagnostics_and_laboratory_medicine.yaml new file mode 100644 index 00000000..2ec1b7dc --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_diagnostics_and_laboratory_medicine.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_diagnostics_and_laboratory_medicine +include: _template_yaml +task_alias: Diagnostics and Laboratory Medicine +dataset_name: Diagnostics_and_Laboratory_Medicine diff --git a/lm_eval/tasks/mmmu/mmmu_economics.yaml b/lm_eval/tasks/mmmu/mmmu_economics.yaml new file mode 100644 index 00000000..3d6465da --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_economics.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_economics +include: _template_yaml +task_alias: Economics +dataset_name: Economics diff --git a/lm_eval/tasks/mmmu/mmmu_electronics.yaml b/lm_eval/tasks/mmmu/mmmu_electronics.yaml new file mode 100644 index 00000000..02df22f8 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_electronics.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_electronics +include: _template_yaml +task_alias: Electronics +dataset_name: Electronics diff --git a/lm_eval/tasks/mmmu/mmmu_energy_and_power.yaml b/lm_eval/tasks/mmmu/mmmu_energy_and_power.yaml new file mode 100644 index 00000000..add24ebe --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_energy_and_power.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_energy_and_power +include: _template_yaml +task_alias: Energy and Power +dataset_name: Energy_and_Power diff --git a/lm_eval/tasks/mmmu/mmmu_finance.yaml b/lm_eval/tasks/mmmu/mmmu_finance.yaml new file mode 100644 index 00000000..c6b6f042 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_finance.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_finance +include: _template_yaml +task_alias: Finance +dataset_name: Finance diff --git a/lm_eval/tasks/mmmu/mmmu_geography.yaml b/lm_eval/tasks/mmmu/mmmu_geography.yaml new file mode 100644 index 00000000..b5f90221 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_geography.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_geography +include: _template_yaml +task_alias: Geography +dataset_name: Geography diff --git a/lm_eval/tasks/mmmu/mmmu_history.yaml b/lm_eval/tasks/mmmu/mmmu_history.yaml new file mode 100644 index 00000000..435388fd --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_history.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_history +include: _template_yaml +task_alias: History +dataset_name: History diff --git a/lm_eval/tasks/mmmu/mmmu_literature.yaml b/lm_eval/tasks/mmmu/mmmu_literature.yaml new file mode 100644 index 00000000..9e0a1ba5 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_literature.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_literature +include: _template_yaml +task_alias: Literature +dataset_name: Literature diff --git a/lm_eval/tasks/mmmu/mmmu_manage.yaml b/lm_eval/tasks/mmmu/mmmu_manage.yaml new file mode 100644 index 00000000..bd199241 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_manage.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_manage +include: _template_yaml +task_alias: Manage +dataset_name: Manage diff --git a/lm_eval/tasks/mmmu/mmmu_marketing.yaml b/lm_eval/tasks/mmmu/mmmu_marketing.yaml new file mode 100644 index 00000000..53848171 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_marketing.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_marketing +include: _template_yaml +task_alias: Marketing +dataset_name: Marketing diff --git a/lm_eval/tasks/mmmu/mmmu_materials.yaml b/lm_eval/tasks/mmmu/mmmu_materials.yaml new file mode 100644 index 00000000..ee469443 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_materials.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_materials +include: _template_yaml +task_alias: Materials +dataset_name: Materials diff --git a/lm_eval/tasks/mmmu/mmmu_math.yaml b/lm_eval/tasks/mmmu/mmmu_math.yaml new file mode 100644 index 00000000..e6817689 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_math.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_math +include: _template_yaml +task_alias: Math +dataset_name: Math diff --git a/lm_eval/tasks/mmmu/mmmu_mechanical_engineering.yaml b/lm_eval/tasks/mmmu/mmmu_mechanical_engineering.yaml new file mode 100644 index 00000000..4b9d95be --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_mechanical_engineering.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_mechanical_engineering +include: _template_yaml +task_alias: Mechanical Engineering +dataset_name: Mechanical_Engineering diff --git a/lm_eval/tasks/mmmu/mmmu_music.yaml b/lm_eval/tasks/mmmu/mmmu_music.yaml new file mode 100644 index 00000000..cf4032de --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_music.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_music +include: _template_yaml +task_alias: Music +dataset_name: Music diff --git a/lm_eval/tasks/mmmu/mmmu_pharmacy.yaml b/lm_eval/tasks/mmmu/mmmu_pharmacy.yaml new file mode 100644 index 00000000..04a4f1ff --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_pharmacy.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_pharmacy +include: _template_yaml +task_alias: Pharmacy +dataset_name: Pharmacy diff --git a/lm_eval/tasks/mmmu/mmmu_physics.yaml b/lm_eval/tasks/mmmu/mmmu_physics.yaml new file mode 100644 index 00000000..53371cad --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_physics.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_physics +include: _template_yaml +task_alias: Physics +dataset_name: Physics diff --git a/lm_eval/tasks/mmmu/mmmu_psychology.yaml b/lm_eval/tasks/mmmu/mmmu_psychology.yaml new file mode 100644 index 00000000..8471d4a1 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_psychology.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_psychology +include: _template_yaml +task_alias: Psychology +dataset_name: Psychology diff --git a/lm_eval/tasks/mmmu/mmmu_public_health.yaml b/lm_eval/tasks/mmmu/mmmu_public_health.yaml new file mode 100644 index 00000000..aefc0590 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_public_health.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_public_health +include: _template_yaml +task_alias: Public Health +dataset_name: Public_Health diff --git a/lm_eval/tasks/mmmu/mmmu_sociology.yaml b/lm_eval/tasks/mmmu/mmmu_sociology.yaml new file mode 100644 index 00000000..5da664a8 --- /dev/null +++ b/lm_eval/tasks/mmmu/mmmu_sociology.yaml @@ -0,0 +1,4 @@ +task: mmmu_val_sociology +include: _template_yaml +task_alias: Sociology +dataset_name: Sociology diff --git a/lm_eval/tasks/mmmu/utils.py b/lm_eval/tasks/mmmu/utils.py new file mode 100644 index 00000000..87a30220 --- /dev/null +++ b/lm_eval/tasks/mmmu/utils.py @@ -0,0 +1,341 @@ +import ast +import random +import re + +import numpy as np + + +random.seed(42) + + +# source for prompt fstrings: https://github.com/MMMU-Benchmark/MMMU/blob/7787d60648c82a9d40acd656fa541a6c74f58995/eval/configs/llava1.5.yaml#L3 +MULTI_CHOICE_EXAMPLE_FORMAT = """{} + +{} + +Answer with the option's letter from the given choices directly.""" + + +SHORT_ANS_EXAMPLE_FORMAT = """{} + +Answer the question using a single word or phrase.""" + +START_CHR = "A" + + +def doc_to_image(doc): + # get formatted prompt (incl. multi-choice options) pre- reformatting + input_text = _doc_to_text(doc) + # locate instances in input + image_placeholders = [ + img.replace(" ", "_").replace("<", "").replace(">", "") + for img in re.findall("", input_text) + ] + + # collect visuals (can have dupes of a given image or be out of order) + # E.g. validation_Math_19 contains and but seen as [, , , , ] + visuals = [doc[img] for img in image_placeholders] + + return visuals + + +def doc_to_text(doc): + """Get the prompt for a given document.""" + + prompt = _doc_to_text(doc) + + for i in range(1, 8): + # replace with . TODO: check this is always the right decision incl. for non-HF models + prompt = prompt.replace(f"", "") + + return prompt + + +def _doc_to_text(doc): + """Helper--get the prompt for a given document but DO NOT yet replace with .""" + + if doc["question_type"] == "multiple-choice": + choices_str = "" + + for i, choice in enumerate(ast.literal_eval(doc["options"])): + # add (A) {choice1}\n , (B) {choice2}\n , and so on + # to create the list of formatted choices in the prompt + choices_str += f"\n({chr(ord(START_CHR) + i)}) {choice}" + + choices_str = ( + choices_str.lstrip() + ) # remove the extraneous prepended \n that we added + + prompt = MULTI_CHOICE_EXAMPLE_FORMAT.format(doc["question"], choices_str) + else: + prompt = SHORT_ANS_EXAMPLE_FORMAT.format(doc["question"]) + + return prompt + + +def process_results(doc, results): + if doc["question_type"] == "multiple-choice": + # multichoice logic + option_strs = ast.literal_eval(doc["options"]) + option_letters = ["A", "B", "C", "D", "E", "F", "G", "H", "I"] + + all_choices = option_letters[: len(option_strs)] + index2ans = {index: ans for index, ans in zip(option_letters, option_strs)} + + pred = parse_multi_choice_response(results[0], all_choices, index2ans) + # print(pred, all_choices, index2ans) + is_correct = eval_multi_choice(doc["answer"], pred) + else: + # freeform response handling + pred = parse_open_response(results[0]) + is_correct = eval_open(doc["answer"], pred) + + return {"acc": float(is_correct)} + + # TODO: it would be better if we could use a Filter for this logic. + + +### Output parsing and answer selection taken from +### https://github.com/MMMU-Benchmark/MMMU/blob/main/eval/utils/data_utils.py +### and +### https://github.com/MMMU-Benchmark/MMMU/blob/main/eval/utils/eval_utils.py + + +# ----------- Process Multi-choice ------------- +def parse_multi_choice_response(response, all_choices, index2ans): + """ + Parse the prediction from the generated response. + Return the predicted index e.g., A, B, C, D. + """ + for char in [",", ".", "!", "?", ";", ":", "'"]: + response = response.strip(char) + response = " " + response + " " # add space to avoid partial match + + index_ans = True + ans_with_brack = False + candidates = [] + for choice in all_choices: # e.g., (A) (B) (C) (D) + if f"({choice})" in response: + candidates.append(choice) + ans_with_brack = True + + if len(candidates) == 0: + for choice in all_choices: # e.g., A B C D + if f" {choice} " in response: + candidates.append(choice) + + # if all above doesn't get candidates, check if the content is larger than 5 tokens and try to parse the example + if len(candidates) == 0 and len(response.split()) > 5: + for index, ans in index2ans.items(): + if ans.lower() in response.lower(): + candidates.append(index) + index_ans = False # it's content ans. + + if len(candidates) == 0: # still not get answer, randomly choose one. + pred_index = random.choice(all_choices) + elif len(candidates) > 1: + start_indexes = [] + if index_ans: + if ans_with_brack: + for can in candidates: + index = response.rfind(f"({can})") + start_indexes.append(index) # -1 will be ignored anyway + # start_indexes = [generated_response.index(f'({can})') for can in candidates] + else: + for can in candidates: + index = response.rfind(f" {can} ") + start_indexes.append(index) + else: + for can in candidates: + index = response.lower().rfind(index2ans[can].lower()) + start_indexes.append(index) + # get the last one + pred_index = candidates[np.argmax(start_indexes)] + else: # if only one candidate, use it. + pred_index = candidates[0] + + # print(response, all_choices, index2ans, pred_index) + + return pred_index + + +# ----------- Process Open ------------- +def check_is_number(string): + """ + Check if the given string a number. + """ + try: + float(string.replace(",", "")) + return True + except ValueError: + # check if there's comma inside + return False + + +def normalize_str(string): + """ + Normalize the str to lower case and make them float numbers if possible. + """ + # check if characters in the string + + # if number, numerize it. + string = string.strip() + + is_number = check_is_number(string) + + if is_number: + string = string.replace(",", "") + string = float(string) + # leave 2 decimal + string = round(string, 2) + return [string] + else: # it's likely to be a string + # lower it + string = string.lower() + if len(string) == 1: + return [" " + string, string + " "] # avoid trivial matches + return [string] + + +def extract_numbers(string): + """ + Exact all forms of numbers from a string with regex. + """ + # Pattern for numbers with commas + pattern_commas = r"-?\b\d{1,3}(?:,\d{3})+\b" + # Pattern for scientific notation + pattern_scientific = r"-?\d+(?:\.\d+)?[eE][+-]?\d+" + # Pattern for simple numbers without commas + pattern_simple = r"-?(?:\d+\.\d+|\.\d+|\d+\b)(?![eE][+-]?\d+)(?![,\d])" + + # Extract numbers with commas + numbers_with_commas = re.findall(pattern_commas, string) + # Extract numbers in scientific notation + numbers_scientific = re.findall(pattern_scientific, string) + # Extract simple numbers without commas + numbers_simple = re.findall(pattern_simple, string) + + # Combine all extracted numbers + all_numbers = numbers_with_commas + numbers_scientific + numbers_simple + return all_numbers + + +def parse_open_response(response): + """ + Parse the prediction from the generated response. + Return a list of predicted strings or numbers. + """ + + # content = content.strip("\n").strip(".").strip(" ") + def get_key_subresponses(response): + key_responses = [] + response = response.strip().strip(".").lower() + sub_responses = re.split(r"\.\s(?=[A-Z])|\n", response) + indicators_of_keys = [ + "could be ", + "so ", + "is ", + "thus ", + "therefore ", + "final ", + "answer ", + "result ", + ] + key_responses = [] + for index, resp in enumerate(sub_responses): + # if last one, accept it's an equation (the entire response can be just one sentence with equation) + if index == len(sub_responses) - 1: + indicators_of_keys.extend(["="]) + shortest_key_response = None # the shortest response that may contain the answer (tail part of the response) + for indicator in indicators_of_keys: + if indicator in resp: + if not shortest_key_response: + shortest_key_response = resp.split(indicator)[-1].strip() + else: + if len(resp.split(indicator)[-1].strip()) < len( + shortest_key_response + ): + shortest_key_response = resp.split(indicator)[-1].strip() + # key_responses.append(resp.split(indicator)[1].strip()) + + if shortest_key_response: + # and it's not trivial + if shortest_key_response.strip() not in [ + ":", + ",", + ".", + "!", + "?", + ";", + ":", + "'", + ]: + key_responses.append(shortest_key_response) + if len(key_responses) == 0: # did not found any + return [response] + return key_responses + + # pdb.set_trace() + key_responses = get_key_subresponses(response) + + pred_list = key_responses.copy() # keep the original string response + for resp in key_responses: + pred_list.extend(extract_numbers(resp)) + + tmp_pred_list = [] + for i in range(len(pred_list)): + tmp_pred_list.extend(normalize_str(pred_list[i])) + pred_list = tmp_pred_list + + # remove duplicates + pred_list = list(set(pred_list)) + + return pred_list + + +# ----------- Evaluation ------------- + + +def eval_multi_choice(gold_i, pred_i): + """ + Evaluate a multiple choice instance. + """ + correct = False + # only they are exactly the same, we consider it as correct + if isinstance(gold_i, list): + for answer in gold_i: + if answer == pred_i: + correct = True + break + else: # gold_i is a string + if gold_i == pred_i: + correct = True + return correct + + +def eval_open(gold_i, pred_i): + """ + Evaluate an open question instance + """ + correct = False + if isinstance(gold_i, list): + # use float to avoid trivial matches + norm_answers = [] + for answer in gold_i: + norm_answers.extend(normalize_str(answer)) + else: + norm_answers = normalize_str(gold_i) + for pred in pred_i: # pred is already normalized in parse response phase + if isinstance(pred, str): # if it's a string, then find if ans in the pred_i + for norm_ans in norm_answers: + # only see if the string answer in the string pred + if isinstance(norm_ans, str) and norm_ans in pred: + if not correct: + correct = True + break + else: # it's a float number + if pred in norm_answers: + if not correct: + correct = True + break + return correct -- GitLab From a5e0adcb52915788262ac346a023a01eb25b6339 Mon Sep 17 00:00:00 2001 From: SYusupov <36813444+SYusupov@users.noreply.github.com> Date: Tue, 17 Sep 2024 22:17:39 +0200 Subject: [PATCH 097/194] Update README.md (#2297) * Update README.md I encounter some Git buffer size limits when trying to download all commits history of the repository, such as: ```error: RPC failed; curl 18 transfer closed with outstanding read data remaining error: 5815 bytes of body are still expected fetch-pack: unexpected disconnect while reading sideband packet fatal: early EOF``` therefore the installation is faster and there are not errors when I download only the last version of the repository * Fix linting issue --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 9f26c811..078dd43f 100644 --- a/README.md +++ b/README.md @@ -54,7 +54,7 @@ The Language Model Evaluation Harness is the backend for 🤗 Hugging Face's pop To install the `lm-eval` package from the github repository, run: ```bash -git clone https://github.com/EleutherAI/lm-evaluation-harness +git clone --depth 1 https://github.com/EleutherAI/lm-evaluation-harness cd lm-evaluation-harness pip install -e . ``` -- GitLab From 88ea85b4e54d0554e6051da71e30bf955a614954 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Wed, 18 Sep 2024 02:35:28 +0500 Subject: [PATCH 098/194] repr bug (#2315) --- lm_eval/api/task.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/api/task.py b/lm_eval/api/task.py index 8dadf948..1cebbdd2 100644 --- a/lm_eval/api/task.py +++ b/lm_eval/api/task.py @@ -1594,7 +1594,7 @@ class ConfigurableTask(Task): f"ConfigurableTask(task_name={getattr(self.config, 'task', None)}," f"output_type={self.OUTPUT_TYPE}," f"num_fewshot={getattr(self.config, 'num_fewshot', None)}," - f"num_samples={len(self.eval_docs)})", + f"num_samples={len(self.eval_docs)})" ) -- GitLab From 9a092f374bdc6d6032ae2b878b7a49b97801ab69 Mon Sep 17 00:00:00 2001 From: David Corvoysier Date: Wed, 18 Sep 2024 22:15:57 +0200 Subject: [PATCH 099/194] Update neuron backend (#2314) * feat(neuron): align with latest optimum-neuron * feat(neuron): support pre-exported neuron models * fix(neuron): correctly use max_length * fix(neuron): adapt loglikelihood The evaluation of log likelihood was not working for neuron models using continuous batching, such as all cached neuron LLama models. * refactor(neuron): remove dead code --- lm_eval/models/neuron_optimum.py | 241 ++++++++++------------------ tests/models/test_neuron_optimum.py | 26 --- 2 files changed, 88 insertions(+), 179 deletions(-) delete mode 100644 tests/models/test_neuron_optimum.py diff --git a/lm_eval/models/neuron_optimum.py b/lm_eval/models/neuron_optimum.py index f3ee42ef..b276c151 100644 --- a/lm_eval/models/neuron_optimum.py +++ b/lm_eval/models/neuron_optimum.py @@ -1,7 +1,5 @@ import copy -import json import logging -import subprocess from collections import defaultdict from typing import List, Optional, Union @@ -33,54 +31,6 @@ except ImportError: logger = logging.getLogger(__name__) -def get_nc_count() -> Union[int, None]: - """Returns the number of neuron cores on the current instance.""" - try: - cmd = "neuron-ls --json-output" - result = subprocess.run(cmd, shell=True, capture_output=True) - print(f"inferring nc_count from `neuron-ls` {result.stdout}") - json_output = json.loads(result.stdout) - count = sum([x["nc_count"] for x in json_output]) - print(f"nc_count={count}") - return count - except Exception: - return None - - -def wrap_constant_batch_size(func): - def _decorator(self, input_ids): - """input_ids a 2D array with batch_size on dim=0 - - makes sure the func runs with self.batch_size - """ - # access a from TestSample - batch_size = input_ids.shape[0] - - if batch_size < self.batch_size: - # handle the event of input_ids.shape[0] != batch_size - # Neuron cores expect constant batch_size - input_ids = torch.concat( - ( - input_ids, - # add missing_batch_size dummy - torch.zeros( - [self.batch_size - batch_size, *input_ids.size()[1:]], - dtype=input_ids.dtype, - device=input_ids.device, - ), - ), - dim=0, - ) - elif batch_size > self.batch_size: - raise ValueError( - f"The specified batch_size ({batch_size}) exceeds the model static batch size ({self.batch_size})" - ) - # return the forward pass that requires constant batch size - return func(self, input_ids)[:batch_size] - - return _decorator - - class CustomNeuronModelForCausalLM(NeuronModelForCausalLM): """NeuronModelForCausalLM with `stopping_criteria` in `generate`""" @@ -146,7 +96,7 @@ class CustomNeuronModelForCausalLM(NeuronModelForCausalLM): raise ValueError( f"The specified batch_size ({batch_size}) exceeds the model static batch size ({self.batch_size})" ) - elif batch_size < self.batch_size: + elif batch_size < self.batch_size and not self.continuous_batching: logger.warning( "Inputs will be padded to match the model static batch size. This will increase latency." ) @@ -158,8 +108,6 @@ class CustomNeuronModelForCausalLM(NeuronModelForCausalLM): if attention_mask is not None: padding = torch.zeros(padding_shape, dtype=torch.int64) padded_attention_mask = torch.cat([attention_mask, padding]) - # Drop the current generation context and clear the Key/Value cache - self.reset_generation() output_ids = self.generate_tokens( padded_input_ids, @@ -179,8 +127,6 @@ class NEURON_HF(TemplateLM): Tested with neuron 2.17.0 """ - _DEFAULT_MAX_LENGTH = 2048 - def __init__( self, pretrained: Optional[str] = "TinyLlama/TinyLlama-1.1B-Chat-v1.0", @@ -203,7 +149,7 @@ class NEURON_HF(TemplateLM): "please install neuron via pip install transformers-neuron ", "also make sure you are running on an AWS inf2 instance", ) - if version.parse(optimum_neuron_version) != version.parse("0.0.17"): + if version.parse(optimum_neuron_version) != version.parse("0.0.24"): logger.warning( '`optimum-neuron` model requires `pip install "optimum[neuronx]>=0.0.17" ' "preferably using the Hugging Face Neuron Deep Learning AMI (Ubuntu 22.04) " @@ -217,35 +163,16 @@ class NEURON_HF(TemplateLM): self.batch_size_per_gpu = int(batch_size) batch_size = int(batch_size) - if tp_degree is None: - # execute `neuron-ls --json-output | jq '.[0].nc_count'`` - # to get the number of neuron cores on your instance - tp_degree = get_nc_count() - - assert isinstance(tp_degree, int), ( - f"model_args must include tp_degree. tp_degree must be set to an integer," - f" but is tp_degree=`{tp_degree}` with type=`{type(tp_degree)}`." - "Set it to number of neuron cores on your instance." - " For inf2.xlarge and inf2.8xlarge, set it to `2`." - " For inf2.24xlarge, set it to `12`." - " For inf2.48xlarge, set it to `24`." - ) - - revision = str(revision) # cast to string if not already one - # TODO: update this to be less of a hack once subfolder is fixed in HF - revision = revision + ("/" + subfolder if subfolder is not None else "") self._config = transformers.AutoConfig.from_pretrained( pretrained, revision=revision, trust_remote_code=trust_remote_code, ) - torch_dtype = lm_eval.models.utils.get_dtype(dtype) - assert torch_dtype in [ - torch.float16, - torch.bfloat16, - ], "Only float16 and bfloat16 are supported" + revision = str(revision) # cast to string if not already one + # TODO: update this to be less of a hack once subfolder is fixed in HF + revision = revision + ("/" + subfolder if subfolder is not None else "") self.tokenizer = transformers.AutoTokenizer.from_pretrained( pretrained if tokenizer is None else tokenizer, @@ -254,36 +181,58 @@ class NEURON_HF(TemplateLM): use_fast=use_fast_tokenizer, ) - # Neuron specific code - if torch_dtype == torch.float16: - self.amp_dtype = "f16" - elif torch_dtype == torch.bfloat16: - self.amp_dtype = "bf16" - elif torch_dtype == torch.float32: - self.amp_dtype = "f32" - else: - raise NotImplementedError("Only float16 and bfloat16 are implemented.") - - compiler_args = {"num_cores": tp_degree, "auto_cast_type": self.amp_dtype} - input_shapes = { - "batch_size": batch_size, - "sequence_length": self._DEFAULT_MAX_LENGTH, - } + neuron_config = getattr(self._config, "neuron", None) + if neuron_config is None: + # Check export parameters + if tp_degree is not None: + assert isinstance(tp_degree, int), ( + f"tp_degree must be set to an integer," + f" but is tp_degree=`{tp_degree}` with type=`{type(tp_degree)}`." + "Set it to a number lower than the number of neuron cores on your instance." + " For inf2.xlarge and inf2.8xlarge, set it to `2`." + " For inf2.24xlarge, set it <= `12`." + " For inf2.48xlarge, set it <= `24`." + ) + torch_dtype = lm_eval.models.utils.get_dtype(dtype) + + if torch_dtype == torch.float16: + self.amp_dtype = "f16" + elif torch_dtype == torch.bfloat16: + self.amp_dtype = "bf16" + elif torch_dtype == torch.float32: + self.amp_dtype = "f32" + else: + raise NotImplementedError( + "Only float16/bfloat16/float32 are supported." + ) - print( - f"{'='*20} \n loading model to neuron with" - f" {compiler_args}, {input_shapes}..." - ) - self.model = CustomNeuronModelForCausalLM.from_pretrained( - pretrained, - revision=revision, - trust_remote_code=trust_remote_code, - low_cpu_mem_usage=low_cpu_mem_usage, - export=True, - **compiler_args, - **input_shapes, - ) - print(f"SUCCESS: neuron model compiled. \n {'='*20}") + print(f"{'='*20} \n exporting model to neuron") + self.model = CustomNeuronModelForCausalLM.from_pretrained( + pretrained, + revision=revision, + trust_remote_code=trust_remote_code, + low_cpu_mem_usage=low_cpu_mem_usage, + export=True, + batch_size=batch_size, + num_cores=tp_degree, + auto_cast_type=self.amp_dtype, + sequence_length=max_length, + ) + neuron_config = self.model.config.neuron + print( + f"SUCCESS: neuron model exported with config {neuron_config}. \n {'='*20}" + ) + else: + print( + f"{'='*20} \n loading neuron model with config" f" {neuron_config}..." + ) + self.model = CustomNeuronModelForCausalLM.from_pretrained( + pretrained, + revision=revision, + trust_remote_code=trust_remote_code, + low_cpu_mem_usage=low_cpu_mem_usage, + ) + print(f"SUCCESS: neuron model loaded. \n {'='*20}") self.truncation = truncation @@ -291,8 +240,6 @@ class NEURON_HF(TemplateLM): self.tokenizer.pad_token_id = self.tokenizer.eos_token_id self.add_bos_token = add_bos_token - self._max_length = max_length - self.batch_schedule = 1 self.batch_sizes = {} @@ -313,17 +260,7 @@ class NEURON_HF(TemplateLM): @property def max_length(self): - if self._max_length: # if max length manually set, return it - return self._max_length - seqlen_config_attrs = ("n_positions", "max_position_embeddings", "n_ctx") - for attr in seqlen_config_attrs: - if hasattr(self.model.config, attr): - return getattr(self.model.config, attr) - if hasattr(self.tokenizer, "model_max_length"): - if self.tokenizer.model_max_length == 1000000000000000019884624838656: - return self._DEFAULT_MAX_LENGTH - return self.tokenizer.model_max_length - return self._DEFAULT_MAX_LENGTH + return self.model.max_length @property def max_gen_toks(self) -> int: @@ -391,34 +328,6 @@ class NEURON_HF(TemplateLM): def tok_decode(self, tokens): return self.tokenizer.decode(tokens) - @wrap_constant_batch_size - def _model_call(self, input_ids: torch.Tensor): - """ - get logits for the entire sequence - - :param input_ids: torch.Tensor - A torch tensor of shape [batch, sequence_cont] - the size of sequence may vary from call to call - :return - A torch tensor of shape [batch, sequence, vocab] with the - logits returned from the model's decoder-lm head - """ - _, sequence_length = input_ids.shape - - with torch.inference_mode(): - cache_ids = torch.arange(0, sequence_length, dtype=torch.int32).split(1) - input_ids_split = input_ids.split(1, dim=1) - - return torch.concat( - [ - self.model.forward( - input_ids=input_id, cache_ids=cache_id, return_dict=False - )[0] - for input_id, cache_id in zip(input_ids_split, cache_ids) - ], - dim=1, - ) - def _model_generate(self, context, max_length, stop, **generation_kwargs): # we require users to pass do_sample=True explicitly # for non-greedy gen. This should be reevaluated when considering beam search. @@ -580,15 +489,41 @@ class NEURON_HF(TemplateLM): cont_toks_list.append(continuation_enc) inplens.append(inplen) - # create encoder attn mask and batched conts, if seq2seq - call_kwargs = {} + # Add dummy inputs up to the model static batch size + if len(inps) < self.batch_size: + inps = inps + [ + torch.zeros_like(inps[0]), + ] * (self.batch_size - len(inps)) + + masks = [torch.ones_like(inp) for inp in inps] batched_inps = lm_eval.models.utils.pad_and_concat( padding_len_inp, inps, padding_side="right" ) # [batch, padding_len_inp] - multi_logits = F.log_softmax( - self._model_call(batched_inps, **call_kwargs), dim=-1 - ) # [batch, padding_length (inp or cont), vocab] + batched_masks = lm_eval.models.utils.pad_and_concat( + padding_len_inp, masks, padding_side="right" + ) + if self.model.model.neuron_config.output_all_logits: + inputs = self.model.prepare_inputs_for_prefill( + batched_inps, batched_masks + ) + multi_logits = F.log_softmax( + self.model.forward(**inputs).logits, dim=-1 + ) # [batch, padding_length (inp or cont), vocab] + else: + # The model will only return the logits for the last input token, so we need + # to iterate over inputs to accumulate logits. + # To speed things up we use the KV cache as we would do when generating. + inputs = self.model.prepare_inputs_for_prefill( + batched_inps[:, :1], batched_masks[:, :1] + ) + outputs = [self.model.forward(**inputs).logits] + for i in range(1, padding_len_inp): + inputs = self.model.prepare_inputs_for_decode( + batched_inps[:, : i + 1], batched_masks[:, : i + 1] + ) + outputs.append(self.model.forward(**inputs).logits) + multi_logits = F.log_softmax(torch.concat(outputs, dim=1), dim=-1) for (cache_key, _, _), logits, inplen, cont_toks in zip( chunk, multi_logits, inplens, cont_toks_list diff --git a/tests/models/test_neuron_optimum.py b/tests/models/test_neuron_optimum.py deleted file mode 100644 index 564d5230..00000000 --- a/tests/models/test_neuron_optimum.py +++ /dev/null @@ -1,26 +0,0 @@ -import pytest -import torch - -from lm_eval.models.neuron_optimum import wrap_constant_batch_size - - -def test_wrap_constant_batch_size(): - class Tester: - def __init__(self, batch_size): - self.batch_size = batch_size - - @wrap_constant_batch_size - def test_constant_batch_size(self, inputs): - assert len(inputs) == self.batch_size - return inputs - - batch_size_test = 8 - for i in range(1, batch_size_test + 1): - tensor = torch.ones([i, 2, 2]) - out = Tester(batch_size=batch_size_test).test_constant_batch_size(tensor) - torch.testing.assert_allclose(out, tensor) - - with pytest.raises(ValueError): - Tester(batch_size=batch_size_test).test_constant_batch_size( - torch.ones([batch_size_test + 1, 2, 2]) - ) -- GitLab From d7734d1923fe74265045169ca6fd1031046d646d Mon Sep 17 00:00:00 2001 From: Amine Elhattami <35821254+Am1n3e@users.noreply.github.com> Date: Tue, 24 Sep 2024 14:08:44 +0200 Subject: [PATCH 100/194] Fixed dummy model (#2339) --- lm_eval/models/dummy.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/lm_eval/models/dummy.py b/lm_eval/models/dummy.py index 83737739..014ad49e 100644 --- a/lm_eval/models/dummy.py +++ b/lm_eval/models/dummy.py @@ -26,9 +26,9 @@ class DummyLM(LM): def generate_until(self, requests, disable_tqdm: bool = False): res = [] - for ctx, _ in tqdm(requests, disable=disable_tqdm): + for request in tqdm(requests, disable=disable_tqdm): res.append("lol") - assert ctx.strip() != "" + assert request.arguments[0].strip() != "" return res -- GitLab From bc50a9aa6d6149f6702889b4ef341b83d0304f85 Mon Sep 17 00:00:00 2001 From: Eldar Kurtic Date: Tue, 24 Sep 2024 16:12:57 +0200 Subject: [PATCH 101/194] add a note for missing dependencies (#2336) --- lm_eval/tasks/leaderboard/README.md | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/lm_eval/tasks/leaderboard/README.md b/lm_eval/tasks/leaderboard/README.md index d9bc1107..1bd7bd3e 100644 --- a/lm_eval/tasks/leaderboard/README.md +++ b/lm_eval/tasks/leaderboard/README.md @@ -13,6 +13,15 @@ As we want to evaluate models across capabilities, the list currently contains: Details on the choice of those evals can be found [here](https://huggingface.co/spaces/open-llm-leaderboard/blog) ! +## Install +To install the `lm-eval` package with support for leaderboard evaluations, run: + +```bash +git clone --depth 1 https://github.com/EleutherAI/lm-evaluation-harness +cd lm-evaluation-harness +pip install -e ".[math,ifeval,sentencepiece]" +``` + ## BigBenchHard (BBH) A suite of 23 challenging BIG-Bench tasks which we call BIG-Bench Hard (BBH). -- GitLab From f378f30605e0c3afef65d795370d220e6bfc92c4 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Thu, 26 Sep 2024 07:04:06 +0500 Subject: [PATCH 102/194] load metric with `evaluate` (#2351) --- lm_eval/tasks/squadv2/task.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/lm_eval/tasks/squadv2/task.py b/lm_eval/tasks/squadv2/task.py index 32c44c60..184a5978 100644 --- a/lm_eval/tasks/squadv2/task.py +++ b/lm_eval/tasks/squadv2/task.py @@ -37,7 +37,9 @@ _CITATION = """ def _squad_metric(predictions, references): - squad_metric = datasets.load_metric("squad_v2") + import evaluate + + squad_metric = evaluate.load("squad_v2") return squad_metric.compute(predictions=predictions, references=references) -- GitLab From 72d619ffdb075be0261e60d3bcd2d91e155b5580 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Thu, 26 Sep 2024 18:36:02 +0500 Subject: [PATCH 103/194] fix writeout script (#2350) --- scripts/write_out.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/scripts/write_out.py b/scripts/write_out.py index 6ff5a430..a5122df9 100644 --- a/scripts/write_out.py +++ b/scripts/write_out.py @@ -5,6 +5,7 @@ import random import numpy as np from lm_eval import tasks +from lm_eval.evaluator_utils import get_task_list from lm_eval.tasks import TaskManager from lm_eval.utils import eval_logger, join_iters @@ -51,9 +52,8 @@ def main(): task_dict = tasks.get_task_dict(task_names, task_manager) os.makedirs(args.output_base_path, exist_ok=True) - for task_name, task in task_dict.items(): - if isinstance(task, tuple): - _, task = task + for task in [x.task for x in get_task_list(task_dict)]: + task_name = task.config.task rnd = random.Random() rnd.seed(args.seed) -- GitLab From b2bf7bc4a601c643343757c92c1a51eb69caf1d7 Mon Sep 17 00:00:00 2001 From: Giulio Lovisotto Date: Thu, 26 Sep 2024 16:03:33 +0200 Subject: [PATCH 104/194] Treat tags in python tasks the same as yaml tasks (#2288) * Treat python tasks same as yaml tasks. * Add tests. * Re-add fixture decorators. * Fix typing specification error for Python 3.9. --- lm_eval/tasks/__init__.py | 87 ++++++++++++++++++++++---------------- tests/test_task_manager.py | 73 ++++++++++++++++++++++++++++++++ 2 files changed, 123 insertions(+), 37 deletions(-) create mode 100644 tests/test_task_manager.py diff --git a/lm_eval/tasks/__init__.py b/lm_eval/tasks/__init__.py index 7eeec8bb..6669a35b 100644 --- a/lm_eval/tasks/__init__.py +++ b/lm_eval/tasks/__init__.py @@ -40,7 +40,11 @@ class TaskManager: [x for x in self._all_tasks if self._task_index[x]["type"] == "group"] ) self._all_subtasks = sorted( - [x for x in self._all_tasks if self._task_index[x]["type"] == "task"] + [ + x + for x in self._all_tasks + if self._task_index[x]["type"] in ["task", "python_task"] + ] ) self._all_tags = sorted( [x for x in self._all_tasks if self._task_index[x]["type"] == "tag"] @@ -436,6 +440,43 @@ class TaskManager: :return Dictionary of task names as key and task metadata """ + + def _populate_tags_and_groups(config, task, tasks_and_groups, print_info): + # TODO: remove group in next release + for attr in ["tag", "group"]: + if attr in config: + if attr == "group" and print_info: + self.logger.info( + "`group` and `group_alias` keys in TaskConfigs are deprecated and will be removed in v0.4.5 of lm_eval. " + "The new `tag` field will be used to allow for a shortcut to a group of tasks one does not wish to aggregate metrics across. " + "`group`s which aggregate across subtasks must be only defined in a separate group config file, " + "which will be the official way to create groups that support cross-task aggregation as in `mmlu`. " + "Please see the v0.4.4 patch notes and our documentation: https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/new_task_guide.md#advanced-group-configs " + "for more information." + ) + print_info = False + # attr = "tag" + + attr_list = config[attr] + if isinstance(attr_list, str): + attr_list = [attr_list] + + for tag in attr_list: + if tag not in tasks_and_groups: + tasks_and_groups[tag] = { + "type": "tag", + "task": [task], + "yaml_path": -1, + } + elif tasks_and_groups[tag]["type"] != "tag": + self.logger.info( + f"The tag {tag} is already registered as a group, this tag will not be registered. " + "This may affect tasks you want to call." + ) + break + else: + tasks_and_groups[tag]["task"].append(task) + # TODO: remove group in next release print_info = True ignore_dirs = [ @@ -451,10 +492,14 @@ class TaskManager: config = utils.load_yaml_config(yaml_path, mode="simple") if self._config_is_python_task(config): # This is a python class config - tasks_and_groups[config["task"]] = { + task = config["task"] + tasks_and_groups[task] = { "type": "python_task", "yaml_path": yaml_path, } + _populate_tags_and_groups( + config, task, tasks_and_groups, print_info + ) elif self._config_is_group(config): # This is a group config tasks_and_groups[config["group"]] = { @@ -483,41 +528,9 @@ class TaskManager: "type": "task", "yaml_path": yaml_path, } - - # TODO: remove group in next release - for attr in ["tag", "group"]: - if attr in config: - if attr == "group" and print_info: - self.logger.info( - "`group` and `group_alias` keys in TaskConfigs are deprecated and will be removed in v0.4.5 of lm_eval. " - "The new `tag` field will be used to allow for a shortcut to a group of tasks one does not wish to aggregate metrics across. " - "`group`s which aggregate across subtasks must be only defined in a separate group config file, " - "which will be the official way to create groups that support cross-task aggregation as in `mmlu`. " - "Please see the v0.4.4 patch notes and our documentation: https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/new_task_guide.md#advanced-group-configs " - "for more information." - ) - print_info = False - # attr = "tag" - - attr_list = config[attr] - if isinstance(attr_list, str): - attr_list = [attr_list] - - for tag in attr_list: - if tag not in tasks_and_groups: - tasks_and_groups[tag] = { - "type": "tag", - "task": [task], - "yaml_path": -1, - } - elif tasks_and_groups[tag]["type"] != "tag": - self.logger.info( - f"The tag {tag} is already registered as a group, this tag will not be registered. " - "This may affect tasks you want to call." - ) - break - else: - tasks_and_groups[tag]["task"].append(task) + _populate_tags_and_groups( + config, task, tasks_and_groups, print_info + ) else: self.logger.debug(f"File {f} in {root} could not be loaded") diff --git a/tests/test_task_manager.py b/tests/test_task_manager.py new file mode 100644 index 00000000..1b10d329 --- /dev/null +++ b/tests/test_task_manager.py @@ -0,0 +1,73 @@ +import tempfile +from pathlib import Path + +import pytest + +from lm_eval.tasks import TaskManager + + +@pytest.fixture(scope="module") +def custom_task_name(): + return "zzz_my_python_task" + + +@pytest.fixture(scope="module") +def custom_task_tag(): + return "zzz-tag" + + +@pytest.fixture(scope="module") +def task_yaml(pytestconfig, custom_task_name, custom_task_tag): + yield f"""include: {pytestconfig.rootpath}/lm_eval/tasks/hellaswag/hellaswag.yaml +task: {custom_task_name} +class: !function {custom_task_name}.MockPythonTask +tag: + - {custom_task_tag} +""" + + +@pytest.fixture(scope="module") +def task_code(): + return """ +from lm_eval.tasks import ConfigurableTask + +class MockPythonTask(ConfigurableTask): + + def __init__( + self, + data_dir=None, + cache_dir=None, + download_mode=None, + config=None, + ) -> None: + config.pop("class") + super().__init__(data_dir, cache_dir, download_mode, config) +""" + + +@pytest.fixture(scope="module") +def custom_task_files_dir(task_yaml, task_code, custom_task_name): + with tempfile.TemporaryDirectory() as temp_dir: + yaml_path = Path(temp_dir) / f"{custom_task_name}.yaml" + with open(yaml_path, "w") as f: + f.write(task_yaml) + pysource_path = Path(temp_dir) / f"{custom_task_name}.py" + with open(pysource_path, "w") as f: + f.write(task_code) + yield temp_dir + + +def test_python_task_inclusion( + custom_task_files_dir: Path, custom_task_name: str, custom_task_tag: str +): + task_manager = TaskManager( + verbosity="INFO", include_path=str(custom_task_files_dir) + ) + # check if python tasks enters the global task_index + assert custom_task_name in task_manager.task_index + # check if subtask is present + assert custom_task_name in task_manager.all_subtasks + # check if tag is present + assert custom_task_tag in task_manager.all_tags + # check if it can be loaded by tag (custom_task_tag) + assert custom_task_name in task_manager.load_task_or_group(custom_task_tag) -- GitLab From af92448e4e9b763ced7ea1ddce8432b2a174c1e2 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Thu, 26 Sep 2024 23:56:31 +0500 Subject: [PATCH 105/194] change group to tags in task `eus_exams` task configs (#2320) --- lm_eval/tasks/eus_exams/README.md | 2 +- lm_eval/tasks/eus_exams/eus_exams_es | 2 +- lm_eval/tasks/eus_exams/eus_exams_eu | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/lm_eval/tasks/eus_exams/README.md b/lm_eval/tasks/eus_exams/README.md index f44c5f04..3a14f7df 100644 --- a/lm_eval/tasks/eus_exams/README.md +++ b/lm_eval/tasks/eus_exams/README.md @@ -26,7 +26,7 @@ Homepage: https://github.com/hitz-zentroa/latxa ### Groups and Tasks -#### Groups +#### Tags * `eus_exams_eu`: The Basque version of the exams. * `eus_exams_es`: The Spanish version of the exams. diff --git a/lm_eval/tasks/eus_exams/eus_exams_es b/lm_eval/tasks/eus_exams/eus_exams_es index 25886606..5f2325f2 100644 --- a/lm_eval/tasks/eus_exams/eus_exams_es +++ b/lm_eval/tasks/eus_exams/eus_exams_es @@ -1,4 +1,4 @@ include: eus_exams -group: +tag: - eus_exams_es doc_to_text: "Pregunta: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nD: {{candidates[3]}}\nRespuesta:" diff --git a/lm_eval/tasks/eus_exams/eus_exams_eu b/lm_eval/tasks/eus_exams/eus_exams_eu index 95b82388..dfa3df57 100644 --- a/lm_eval/tasks/eus_exams/eus_exams_eu +++ b/lm_eval/tasks/eus_exams/eus_exams_eu @@ -1,4 +1,4 @@ include: eus_exams -group: +tag: - eus_exams_eu doc_to_text: "Galdera: {{question}}\nA: {{candidates[0]}}\nB: {{candidates[1]}}\nC: {{candidates[2]}}\nD: {{candidates[3]}}\nErantzuna:" -- GitLab From 7d242381c0aeca89a2bea94c4c849ddd2a4bec35 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Thu, 26 Sep 2024 23:57:39 +0500 Subject: [PATCH 106/194] change glianorex to test split (#2332) * change glianorex to test set * nit * fix test; doc_to_target can be str for multiple_choice * nit --- lm_eval/tasks/glianorex/README.md | 5 +++++ lm_eval/tasks/glianorex/glianorex.yaml | 4 +++- lm_eval/tasks/glianorex/glianorex_en.yaml | 4 +++- lm_eval/tasks/glianorex/glianorex_fr.yaml | 4 +++- lm_eval/tasks/glianorex/preprocess_glianorex.py | 3 ++- tests/test_tasks.py | 6 +++++- 6 files changed, 21 insertions(+), 5 deletions(-) diff --git a/lm_eval/tasks/glianorex/README.md b/lm_eval/tasks/glianorex/README.md index 3efc9256..cff102a8 100644 --- a/lm_eval/tasks/glianorex/README.md +++ b/lm_eval/tasks/glianorex/README.md @@ -18,3 +18,8 @@ All tasks are multiple choice questions with 4 options, only one correct option. - `glianorex_en`: Evaluates the accuracy on 264 questions in English. - `glianorex_fr`: Evaluates the accuracy on 264 questions in French. + +#### Change Log + +* (all tasks) 2024-09-23 -- 1.0 + * Switched the `test_split` from `train` to `test`. diff --git a/lm_eval/tasks/glianorex/glianorex.yaml b/lm_eval/tasks/glianorex/glianorex.yaml index a7ba4366..b1fdb236 100755 --- a/lm_eval/tasks/glianorex/glianorex.yaml +++ b/lm_eval/tasks/glianorex/glianorex.yaml @@ -1,7 +1,7 @@ task: glianorex dataset_path: maximegmd/glianorex output_type: multiple_choice -test_split: train +test_split: test doc_to_text: !function preprocess_glianorex.doc_to_text doc_to_target: !function preprocess_glianorex.doc_to_target doc_to_choice: [ 'A', 'B', 'C', 'D' ] @@ -12,3 +12,5 @@ metric_list: - metric: acc_norm aggregation: mean higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/glianorex/glianorex_en.yaml b/lm_eval/tasks/glianorex/glianorex_en.yaml index b08c6f81..d1be3d18 100755 --- a/lm_eval/tasks/glianorex/glianorex_en.yaml +++ b/lm_eval/tasks/glianorex/glianorex_en.yaml @@ -1,7 +1,7 @@ task: glianorex_en dataset_path: maximegmd/glianorex output_type: multiple_choice -test_split: train +test_split: test doc_to_text: !function preprocess_glianorex.doc_to_text doc_to_target: !function preprocess_glianorex.doc_to_target process_docs: !function preprocess_glianorex.filter_english @@ -13,3 +13,5 @@ metric_list: - metric: acc_norm aggregation: mean higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/glianorex/glianorex_fr.yaml b/lm_eval/tasks/glianorex/glianorex_fr.yaml index 6d09bc5a..8a289430 100755 --- a/lm_eval/tasks/glianorex/glianorex_fr.yaml +++ b/lm_eval/tasks/glianorex/glianorex_fr.yaml @@ -1,7 +1,7 @@ task: glianorex_fr dataset_path: maximegmd/glianorex output_type: multiple_choice -test_split: train +test_split: test doc_to_text: !function preprocess_glianorex.doc_to_text doc_to_target: !function preprocess_glianorex.doc_to_target process_docs: !function preprocess_glianorex.filter_french @@ -13,3 +13,5 @@ metric_list: - metric: acc_norm aggregation: mean higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/glianorex/preprocess_glianorex.py b/lm_eval/tasks/glianorex/preprocess_glianorex.py index f257df14..9a70dfd5 100755 --- a/lm_eval/tasks/glianorex/preprocess_glianorex.py +++ b/lm_eval/tasks/glianorex/preprocess_glianorex.py @@ -7,7 +7,8 @@ def doc_to_text(doc) -> str: return f"Question: {doc['question']}\n{answers}Answer:" -def doc_to_target(doc) -> int: +def doc_to_target(doc) -> str: + # answer_idx is `A`, `B`, `C`, `D` etc. return doc["answer_idx"] diff --git a/tests/test_tasks.py b/tests/test_tasks.py index c9453d54..0dc514a2 100644 --- a/tests/test_tasks.py +++ b/tests/test_tasks.py @@ -101,7 +101,11 @@ class TestNewTasks: ) _array_target = [task.doc_to_target(doc) for doc in arr] if task._config.output_type == "multiple_choice": - assert all(isinstance(label, int) for label in _array_target) + # TODO: label can be string or int; add better test conditions + assert all( + (isinstance(label, int) or isinstance(label, str)) + for label in _array_target + ) def test_build_all_requests(self, task_class, limit): task_class.build_all_requests(rank=1, limit=limit, world_size=1) -- GitLab From 558d0d71aff9d9d2c72143a3cb96be48ca16c527 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Fri, 27 Sep 2024 00:08:07 +0500 Subject: [PATCH 107/194] mmlu-pro: add newlines to task descriptions (not leaderboard) (#2334) * add newlines to task descriptions; increment versions * fix task tests (with groups) * Apply suggestions from code review --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- lm_eval/tasks/mmlu_pro/README.md | 5 +++++ lm_eval/tasks/mmlu_pro/_default_template_yaml | 2 +- lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_biology.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_business.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_chemistry.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_computer_science.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_economics.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_engineering.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_health.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_history.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_law.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_math.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_other.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_philosophy.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_physics.yaml | 2 +- lm_eval/tasks/mmlu_pro/mmlu_pro_psychology.yaml | 2 +- tests/test_tasks.py | 10 ++++++---- 18 files changed, 27 insertions(+), 20 deletions(-) diff --git a/lm_eval/tasks/mmlu_pro/README.md b/lm_eval/tasks/mmlu_pro/README.md index 53694cdc..8fddbef2 100644 --- a/lm_eval/tasks/mmlu_pro/README.md +++ b/lm_eval/tasks/mmlu_pro/README.md @@ -57,3 +57,8 @@ If other tasks on this dataset are already supported: * [ ] Is the "Main" variant of this task clearly denoted? * [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? * [ ] Have you noted which, if any, published evaluation setups are matched by this variant? + +### Changelog + +* (tasks, group) 2024-09-23 -- (version 1 --> version 2) + * Added one newline to task description(s) as per [reference implementation](https://github.com/TIGER-AI-Lab/MMLU-Pro/blob/47b9891aacb8bd7cda29d5c5ba17b9434dd333bc/evaluate_from_local.py#L93) diff --git a/lm_eval/tasks/mmlu_pro/_default_template_yaml b/lm_eval/tasks/mmlu_pro/_default_template_yaml index e616cef7..9c4f44b5 100644 --- a/lm_eval/tasks/mmlu_pro/_default_template_yaml +++ b/lm_eval/tasks/mmlu_pro/_default_template_yaml @@ -30,4 +30,4 @@ metric_list: ignore_case: true ignore_punctuation: true metadata: - version: 0.0 + version: 1.0 diff --git a/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml b/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml index 6d13175e..fc320412 100644 --- a/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml +++ b/lm_eval/tasks/mmlu_pro/_mmlu_pro.yaml @@ -20,4 +20,4 @@ aggregate_metric_list: weight_by_size: true filter_list: custom-extract metadata: - version: 1.0 + version: 2.0 diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_biology.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_biology.yaml index 825f2ad2..80aee851 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_biology.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_biology.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about biology. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about biology. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_biology" task_alias: "biology" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_business.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_business.yaml index f0e5f86a..daf871f6 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_business.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_business.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about business. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about business. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_business" task_alias: "business" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_chemistry.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_chemistry.yaml index 84510942..5baf354e 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_chemistry.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_chemistry.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about chemistry. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about chemistry. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_chemistry" task_alias: "chemistry" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_computer_science.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_computer_science.yaml index 51ca4c29..7de34737 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_computer_science.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_computer_science.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about computer science. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about computer science. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_computer_science" task_alias: "computer_science" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_economics.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_economics.yaml index 9b058739..27461278 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_economics.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_economics.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about economics. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about economics. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_economics" task_alias: "economics" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_engineering.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_engineering.yaml index dbb265bd..dcf02f50 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_engineering.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_engineering.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about engineering. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about engineering. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_engineering" task_alias: "engineering" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_health.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_health.yaml index ed1a3a53..d161d1d8 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_health.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_health.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about health. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about health. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_health" task_alias: "health" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_history.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_history.yaml index 5ae6fb9c..d28efd3e 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_history.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_history.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about history. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about history. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_history" task_alias: "history" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_law.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_law.yaml index 1197dff3..ba99f16d 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_law.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_law.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about law. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about law. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_law" task_alias: "law" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_math.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_math.yaml index 67b3b46d..0526f11f 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_math.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_math.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about math. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about math. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_math" task_alias: "math" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_other.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_other.yaml index 918608b9..beb2ec9d 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_other.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_other.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about other. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about other. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_other" task_alias: "other" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_philosophy.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_philosophy.yaml index 9eae2b39..99e5d65b 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_philosophy.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_philosophy.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about philosophy. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about philosophy. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_philosophy" task_alias: "philosophy" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_physics.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_physics.yaml index 00c39623..7e7fa740 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_physics.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_physics.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about physics. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about physics. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_physics" task_alias: "physics" diff --git a/lm_eval/tasks/mmlu_pro/mmlu_pro_psychology.yaml b/lm_eval/tasks/mmlu_pro/mmlu_pro_psychology.yaml index 5258bced..b28fb72d 100644 --- a/lm_eval/tasks/mmlu_pro/mmlu_pro_psychology.yaml +++ b/lm_eval/tasks/mmlu_pro/mmlu_pro_psychology.yaml @@ -1,4 +1,4 @@ -description: "The following are multiple choice questions (with answers) about psychology. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice." +description: "The following are multiple choice questions (with answers) about psychology. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n" include: "_default_template_yaml" task: "mmlu_pro_psychology" task_alias: "psychology" diff --git a/tests/test_tasks.py b/tests/test_tasks.py index 0dc514a2..221b533d 100644 --- a/tests/test_tasks.py +++ b/tests/test_tasks.py @@ -5,6 +5,7 @@ import pytest import lm_eval.tasks as tasks from lm_eval.api.task import ConfigurableTask +from lm_eval.evaluator_utils import get_task_list from .utils import new_tasks @@ -20,10 +21,11 @@ def task_class(): # CI: new_tasks checks if any modifications have been made task_classes = new_tasks() # Check if task_classes is empty - if task_classes: - return list(task_manager.load_task_or_group(task_classes).values()) - else: - return list(task_manager.load_task_or_group(TASKS).values()) + task_classes = task_classes if task_classes else TASKS + res = tasks.get_task_dict(task_classes, task_manager) + res = [x.task for x in get_task_list(res)] + + return res @pytest.fixture() -- GitLab From deb4328771e180e086cf9390d527529fadc1d357 Mon Sep 17 00:00:00 2001 From: Arda Date: Thu, 26 Sep 2024 21:27:56 +0200 Subject: [PATCH 108/194] Added TurkishMMLU to LM Evaluation Harness (#2283) * Added TurkishMMLU to LM Evaluation Harness * Fixed COT name * Fixed COT name * Updated Readme * Fixed Test issues * Completed Scan for changed tasks * Updated Readme * Update README.md * fixup task naming casing + ensure yaml template stubs aren't registered --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Co-authored-by: haileyschoelkopf --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/turkishmmlu/README.md | 94 ++++++++++++++++ lm_eval/tasks/turkishmmlu/config/Biology.yaml | 3 + .../tasks/turkishmmlu/config/Chemistry.yaml | 3 + .../tasks/turkishmmlu/config/Geography.yaml | 3 + lm_eval/tasks/turkishmmlu/config/History.yaml | 3 + .../tasks/turkishmmlu/config/Mathematics.yaml | 3 + .../tasks/turkishmmlu/config/Philosophy.yaml | 3 + lm_eval/tasks/turkishmmlu/config/Physics.yaml | 3 + .../config/Religion_and_Ethics.yaml | 3 + .../Turkish_Language_and_Literature.yaml | 3 + .../config/_turkishmmlu_default_yaml | 21 ++++ .../tasks/turkishmmlu/config_cot/Biology.yaml | 54 +++++++++ .../turkishmmlu/config_cot/Chemistry.yaml | 86 ++++++++++++++ .../turkishmmlu/config_cot/Geography.yaml | 52 +++++++++ .../tasks/turkishmmlu/config_cot/History.yaml | 72 ++++++++++++ .../turkishmmlu/config_cot/Mathematics.yaml | 74 ++++++++++++ .../turkishmmlu/config_cot/Philosophy.yaml | 45 ++++++++ .../tasks/turkishmmlu/config_cot/Physics.yaml | 106 ++++++++++++++++++ .../config_cot/Religion_and_Ethics.yaml | 51 +++++++++ .../Turkish_Language_and_Literature.yaml | 59 ++++++++++ .../config_cot/_turkishmmlu_cot_default_yaml | 34 ++++++ 22 files changed, 776 insertions(+) create mode 100644 lm_eval/tasks/turkishmmlu/README.md create mode 100644 lm_eval/tasks/turkishmmlu/config/Biology.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config/Chemistry.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config/Geography.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config/History.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config/Mathematics.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config/Philosophy.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config/Physics.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config/Religion_and_Ethics.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config/Turkish_Language_and_Literature.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config/_turkishmmlu_default_yaml create mode 100644 lm_eval/tasks/turkishmmlu/config_cot/Biology.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config_cot/Chemistry.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config_cot/Geography.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config_cot/History.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config_cot/Mathematics.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config_cot/Philosophy.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config_cot/Physics.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config_cot/Religion_and_Ethics.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config_cot/Turkish_Language_and_Literature.yaml create mode 100644 lm_eval/tasks/turkishmmlu/config_cot/_turkishmmlu_cot_default_yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 09a6dd79..3903db98 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -107,6 +107,7 @@ | [translation](translation/README.md) | Tasks focused on evaluating the language translation capabilities of models. | Arabic, English, Spanish, Basque, Hindi, Indonesian, Burmese, Russian, Swahili, Telugu, Chinese | | [triviaqa](triviaqa/README.md) | A large-scale dataset for trivia question answering to test general knowledge. | English | | [truthfulqa](truthfulqa/README.md) | A QA task aimed at evaluating the truthfulness and factual accuracy of model responses. | English | +| [turkishmmlu](turkishmmlu/README.md) | A multiple-choice QA test modeled after MMLU, written in Turkish based on Turkish high-school level exams. | Turkish | | [unitxt](unitxt/README.md) | A number of tasks implemented using the unitxt library for flexible, shareable, and reusable data preparation and evaluation for generative AI. | English | | [unscramble](unscramble/README.md) | Tasks involving the rearrangement of scrambled sentences to test syntactic understanding. | English | | [webqs](webqs/README.md) | Web-based question answering tasks designed to evaluate internet search and retrieval. | English | diff --git a/lm_eval/tasks/turkishmmlu/README.md b/lm_eval/tasks/turkishmmlu/README.md new file mode 100644 index 00000000..fd7d2e0d --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/README.md @@ -0,0 +1,94 @@ +# TurkishMMLU + +This repository contains configuration files for LM Evaluation Harness for Few-Shot and Chain-of-Thought experiments for TurkishMMLU. Using these configurations with LM Evaluation Harness, the results of this study are obtained. + +TurkishMMLU is a multiple-choice Question-Answering dataset created for the Turkish Natural Language Processing (NLP) community based on Turkish Highschool Curricula across nine subjects. This comprehensive study is conducted to provide Question-Answering benchmark for Turkish language. The questions of the dataset are written by curriculum experts, suitable for the high-school curricula in Turkey, covering subjects ranging from natural sciences and math questions to more culturally representative topics such as Turkish Literature and the history of the Turkish Republic. + +To access this dataset please send an email to: +arda.yueksel@tum.de or akoksal@cis.lmu.de. + +## Abstract + +Multiple choice question answering tasks evaluate the reasoning, comprehension, and mathematical abilities of Large Language Models (LLMs). While existing benchmarks employ automatic translation for multilingual evaluation, this approach is error-prone and potentially introduces culturally biased questions, especially in social sciences. We introduce the first multitask, multiple-choice Turkish QA benchmark, TurkishMMLU, to evaluate LLMs' understanding of the Turkish language. TurkishMMLU includes over 10,000 questions, covering 9 different subjects from Turkish high-school education curricula. These questions are written by curriculum experts, suitable for the high-school curricula in Turkey, covering subjects ranging from natural sciences and math questions to more culturally representative topics such as Turkish Literature and the history of the Turkish Republic. We evaluate over 20 LLMs, including multilingual open-source (e.g., Gemma, Llama, MT5), closed-source (GPT 4o, Claude, Gemini), and Turkish-adapted (e.g., Trendyol) models. We provide an extensive evaluation, including zero-shot and few-shot evaluation of LLMs, chain-of-thought reasoning, and question difficulty analysis along with model performance. We provide an in-depth analysis of the Turkish capabilities and limitations of current LLMs to provide insights for future LLMs for the Turkish language. We publicly release our code for the dataset and evaluation. + +## Dataset + +Dataset is divided into four categories Natural Sciences, Mathematics, Language, and Social Sciences and Humanities with a total of nine subjects in Turkish highschool education. It is available in multiple choice for LLM evaluation. The questions also contain difficulty indicator referred as Correctness ratio. + +## Evaluation + +5-Shot evaluation results from the paper includes open and closed source SOTA LLM with different architectures. For this study, multilingual and Turkish adapted models are tested. + +The evaluation results of this study are obtained using the provided configurations with LM Evaluation Harness. + +| Model | Source | Average | Natural Sciences | Math | Turkish L & L | Social Sciences and Humanities | +| ------------------- | ------ | ------- | ---------------- | ---- | ------------- | ------------------------------ | +| GPT 4o | Closed | 83.1 | 75.3 | 59.0 | 82.0 | 95.3 | +| Claude-3 Opus | Closed | 79.1 | 71.7 | 59.0 | 77.0 | 90.3 | +| GPT 4-turbo | Closed | 75.7 | 70.3 | 57.0 | 67.0 | 86.5 | +| Llama-3 70B-IT | Closed | 67.3 | 56.7 | 42.0 | 57.0 | 84.3 | +| Claude-3 Sonnet | Closed | 67.3 | 67.3 | 44.0 | 58.0 | 75.5 | +| Llama-3 70B | Open | 66.1 | 56.0 | 37.0 | 57.0 | 83.3 | +| Claude-3 Haiku | Closed | 65.4 | 57.0 | 40.0 | 61.0 | 79.3 | +| Gemini 1.0-pro | Closed | 63.2 | 52.7 | 29.0 | 63.0 | 79.8 | +| C4AI Command-r+ | Open | 60.6 | 50.0 | 26.0 | 57.0 | 78.0 | +| Aya-23 35B | Open | 55.6 | 43.3 | 31.0 | 49.0 | 72.5 | +| C4AI Command-r | Open | 54.9 | 44.7 | 29.0 | 49.0 | 70.5 | +| Mixtral 8x22B | Open | 54.8 | 45.3 | 27.0 | 49.0 | 70.3 | +| GPT 3.5-turbo | Closed | 51.0 | 42.7 | 39.0 | 35.0 | 61.8 | +| Llama-3 8B-IT | Open | 46.4 | 36.7 | 29.0 | 39.0 | 60.0 | +| Llama-3 8B | Open | 46.2 | 37.3 | 30.0 | 33.0 | 60.3 | +| Mixtral 8x7B-IT | Open | 45.2 | 41.3 | 28.0 | 39.0 | 54.0 | +| Aya-23 8B | Open | 45.0 | 39.0 | 23.0 | 31.0 | 58.5 | +| Gemma 7B | Open | 43.6 | 34.3 | 22.0 | 47.0 | 55.0 | +| Aya-101 | Open | 40.7 | 31.3 | 24.0 | 38.0 | 55.0 | +| Trendyol-LLM 7B-C-D | Open | 34.1 | 30.3 | 22.0 | 28.0 | 41.5 | +| mT0-xxl | Open | 33.9 | 29.3 | 28.0 | 21.0 | 42.0 | +| Mistral 7B-IT | Open | 32.0 | 34.3 | 26.0 | 38.0 | 30.3 | +| Llama-2 7B | Open | 22.3 | 25.3 | 20.0 | 20.0 | 19.8 | +| mT5-xxl | Open | 18.1 | 19.3 | 24.0 | 14.0 | 16.8 | + +## Citation + +``` +@misc{yüksel2024turkishmmlumeasuringmassivemultitask, +title={TurkishMMLU: Measuring Massive Multitask Language Understanding in Turkish}, +author={Arda Yüksel and Abdullatif Köksal and Lütfi Kerem Şenel and Anna Korhonen and Hinrich Schütze}, +year={2024}, +eprint={2407.12402}, +archivePrefix={arXiv}, +primaryClass={cs.CL}, +url={https://arxiv.org/abs/2407.12402}, +} +``` + +### Groups and Tasks + +#### Groups + +- `turkishmmlu`: 'All 9 Subjects of Turkish MMLU namely: + Biology, Chemistry, Physics, Geography, Philosophy, History, Religion and Ethics, Turkish Language and Literature, and Mathematics + +#### Tasks + +The following tasks evaluate subjects in the TurkishMMLU dataset + +- `turkishmmlu_{subject}` + +The following task evaluate subjects in the TurkishMMLU dataset in Chain-of-Thought (COT) + +- `turkishmmlu_cot_{subject}` + +### Checklist + +For adding novel benchmarks/datasets to the library: + +- [x] Is the task an existing benchmark in the literature? + - [x] Have you referenced the original paper that introduced the task? + - [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + +If other tasks on this dataset are already supported: + +- [ ] Is the "Main" variant of this task clearly denoted? +- [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +- [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/turkishmmlu/config/Biology.yaml b/lm_eval/tasks/turkishmmlu/config/Biology.yaml new file mode 100644 index 00000000..cafd341b --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config/Biology.yaml @@ -0,0 +1,3 @@ +include: _turkishmmlu_default_yaml +task: turkishmmlu_biology +dataset_name: Biology diff --git a/lm_eval/tasks/turkishmmlu/config/Chemistry.yaml b/lm_eval/tasks/turkishmmlu/config/Chemistry.yaml new file mode 100644 index 00000000..42dd1a87 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config/Chemistry.yaml @@ -0,0 +1,3 @@ +include: _turkishmmlu_default_yaml +task: turkishmmlu_chemistry +dataset_name: Chemistry diff --git a/lm_eval/tasks/turkishmmlu/config/Geography.yaml b/lm_eval/tasks/turkishmmlu/config/Geography.yaml new file mode 100644 index 00000000..110f77ca --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config/Geography.yaml @@ -0,0 +1,3 @@ +include: _turkishmmlu_default_yaml +task: turkishmmlu_geography +dataset_name: Geography diff --git a/lm_eval/tasks/turkishmmlu/config/History.yaml b/lm_eval/tasks/turkishmmlu/config/History.yaml new file mode 100644 index 00000000..d8350f5e --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config/History.yaml @@ -0,0 +1,3 @@ +include: _turkishmmlu_default_yaml +task: turkishmmlu_history +dataset_name: History diff --git a/lm_eval/tasks/turkishmmlu/config/Mathematics.yaml b/lm_eval/tasks/turkishmmlu/config/Mathematics.yaml new file mode 100644 index 00000000..4318be85 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config/Mathematics.yaml @@ -0,0 +1,3 @@ +include: _turkishmmlu_default_yaml +task: turkishmmlu_mathematics +dataset_name: Mathematics diff --git a/lm_eval/tasks/turkishmmlu/config/Philosophy.yaml b/lm_eval/tasks/turkishmmlu/config/Philosophy.yaml new file mode 100644 index 00000000..4ced0c33 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config/Philosophy.yaml @@ -0,0 +1,3 @@ +include: _turkishmmlu_default_yaml +task: turkishmmlu_philosophy +dataset_name: Philosophy diff --git a/lm_eval/tasks/turkishmmlu/config/Physics.yaml b/lm_eval/tasks/turkishmmlu/config/Physics.yaml new file mode 100644 index 00000000..9baeb743 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config/Physics.yaml @@ -0,0 +1,3 @@ +include: _turkishmmlu_default_yaml +task: turkishmmlu_physics +dataset_name: Physics diff --git a/lm_eval/tasks/turkishmmlu/config/Religion_and_Ethics.yaml b/lm_eval/tasks/turkishmmlu/config/Religion_and_Ethics.yaml new file mode 100644 index 00000000..7513119d --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config/Religion_and_Ethics.yaml @@ -0,0 +1,3 @@ +include: _turkishmmlu_default_yaml +task: turkishmmlu_religion_and_ethics +dataset_name: Religion_and_Ethics diff --git a/lm_eval/tasks/turkishmmlu/config/Turkish_Language_and_Literature.yaml b/lm_eval/tasks/turkishmmlu/config/Turkish_Language_and_Literature.yaml new file mode 100644 index 00000000..552e08b7 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config/Turkish_Language_and_Literature.yaml @@ -0,0 +1,3 @@ +include: _turkishmmlu_default_yaml +task: turkishmmlu_turkish_language_and_literature +dataset_name: Turkish_Language_and_Literature diff --git a/lm_eval/tasks/turkishmmlu/config/_turkishmmlu_default_yaml b/lm_eval/tasks/turkishmmlu/config/_turkishmmlu_default_yaml new file mode 100644 index 00000000..e1dae1a9 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config/_turkishmmlu_default_yaml @@ -0,0 +1,21 @@ +tag: turkishmmlu +task: null +dataset_path: AYueksel/TurkishMMLU +dataset_name: TurkishMMLU +test_split: test +fewshot_split: dev +fewshot_config: + sampler: first_n +output_type: multiple_choice +doc_to_text: "Soru: {{ question.strip() }}\nA. {{ choices[0] }}\nB. {{ choices[1] }}\nC. {{ choices[2] }}\nD. {{ choices[3] }}\nE. {{ choices[4] }}\nCevap:" +doc_to_choice: ["A", "B", "C", "D", "E"] +doc_to_target: "{{['A', 'B', 'C', 'D', 'E'].index(answer)}}" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/turkishmmlu/config_cot/Biology.yaml b/lm_eval/tasks/turkishmmlu/config_cot/Biology.yaml new file mode 100644 index 00000000..98d61be7 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config_cot/Biology.yaml @@ -0,0 +1,54 @@ +include: _turkishmmlu_cot_default_yaml +task: turkishmmlu_cot_biology +description: + "Soru: AaKkDdEeX$^{R}$X$^{r}$ genotipli bireyde AKD alelleri bağlı olup diğerleri bağımsızdır.\ + \ Bu birey bu karakterler açısından kaç çeşit gamet oluşturabilir? (Krossing over gerçekleşmemiştir.)\nA) 2 \nB)\ + \ 4 \nC) 8 \nD) 16 \nE) 32 \nÇözüm: Adım adım düşünelim.\ + \ Bir bireyde A, K ve D genleri bağımlı olduğunda, bu üç gen birlikte hareket eder ve aynı gamet içinde bulunurlar.\ + \ Diğer lokuslardaki alleller bağımsızdır.\ + \ AKD lokusundaki allel kombinasyonları: AKD veya akd (2 seçenek)\ + \ Diğer lokuslardaki allel kombinasyonları: Ee (2 seçenek), X$^{R}$X$^{r}$ (2 seçenek).\ + \ Şimdi, bağımlı olan AKD lokusundaki kombinasyonu diğer bağımsız lokuslardaki kombinasyonlarla çarpacağız:\ + \ 2 x 2 x 2 = 8\ + \ Bu birey 8 farklı gamet oluşturabilir.\ + \ Doğru cevap C şıkkıdır.\n\nSoru: Aşağıda verilen hormon çiftlerinden hangisi antagonist (zıt) çalışır?\nA) Oksitosin\ + \ - Prolaktin\nB) Kalsitonin - Parathormon\nC) Adrenalin\ + \ - Noradrenalin\nD) Östrojen - Progesteron\nE) FSH - LH\nÇözüm: Adım adım düşünelim.\ + \ Bu soruyu cevaplayabilmek için hormonların görevlerini ve birbirleri ile olan ilişkilerini bilmek gerekir.\ + \ A) Oksitosin ve Prolaktin: Oksitosin doğum sırasında uterus kasılmalarını uyarır ve süt salgılanmasını sağlar. Prolaktin ise süt üretimini uyarır. Bu iki hormon birbirini destekleyici görev yapar, zıt değildir.\ + \ B) Kalsitonin ve Parathormon: Kalsitonin kanda kalsiyum seviyesini düşürür, parathormon ise kalsiyum seviyesini yükseltir. Bu iki hormon birbirine zıt etki gösterir, antagonisttir.\ + \ C) Adrenalin ve Noradrenalin: Her ikisi de stres hormonudur ve benzer görevleri vardır. Zıt etki göstermezler.\ + \ D) Östrojen ve Progesteron: Östrojen kadınlık hormonudur, progesteron ise gebelik sırasında üretilir. Birlikte çalışırlar, zıt etki göstermezler.\ + \ E) FSH ve LH: FSH folikül gelişimini, LH ovulasyonu uyarır. Birlikte çalışırlar, zıt etki göstermezler.\ + \ Dolayısıyla verilen seçenekler arasında antagonist (zıt) çalışan hormon çifti Kalsitonin ve Parathormon'dur.\ + \ Doğru cevap B şıkkıdır.\n\nSoru: I. Besin azalması II. Avcıların artması III. Zehirli madde birikimin artması\ + \ Yukarıdaki faktörlerden hangileri çevre direncini artırır?\nA) Yalnız I\nB) Yalnız II\nC)\ + \ Yalnız III\nD) II ve III\nE) I, II ve III\nÇözüm: Adım adım düşünelim.\ + \ Çevre direnci, bir ekosistemin dışarıdan gelen olumsuz etkilere karşı direncini ifade eder. Yüksek çevre direnci, ekosistemin bu olumsuz etkilere daha iyi direnebileceği anlamına gelir.\ + \ I. Besin azalması, popülasyonların büyümesini ve sağlığını olumsuz etkiler, dolayısıyla çevre direncini artırır.\ + \ II. Avcıların artması, popülasyonların dengesini bozar ve türlerin sayısını azaltır, bu da çevre direncini artırır.\ + \ III. Zehirli madde birikiminin artması, canlıların sağlığını ve üremesini olumsuz etkiler, ekosistemin dengesini bozar, bu şekilde çevre direncini artırır.\ + \ Sorudaki faktörlerin hepsi olumsuz faktörlerdir ve ekosistemin direncini zorlar. Doğru cevap E şıkkıdır.\n\nSoru:\ + \ Gen klonlama çalışmaları sırasında; a. Vektör DNA ve istenen geni taşıyan DNA'nın kesilmesi, b. İstenen geni taşıyan DNA'nın,\ + \ vektör DNA ile birleştirilmesi, c. Bakterinin çoğalmasıyla birlikte istenen genin kopyalanması, uygulamaları yapılmaktadır.\ + \ Bu uygulamalarda; I. DNA polimeraz II. DNA ligaz III. Restriksiyon enzimi yapılarının kullanıldığı çalışma basamakları\ + \ hangi seçenekte doğru olarak verilmiştir?\ + \ I II III \nA) a, b b\ + \ a, c\nB) b a, b c\nC)\ + \ a c a, c\nD) c b, c a\nE)\ + \ b, c a a, b\nÇözüm: Adım Adım düşünelim.\ + \ I. DNA polimeraz: c (Bakterinin çoğalması ile birlikte istenen genin kopyalanması)\ + \ II. DNA ligaz: b, c (İstenen geni taşıyan DNA'nın, vektör DNA ile birleştirilmesi ve sonrasında bakterinin çoğalması ile birlikte kopyalanması)\ + \ III. Restriksiyon enzimi: a (Vektör DNA ve istenen geni taşıyan DNA'nın kesilmesi)\ + \ Doğru cevap D şıkkıdır.\n\nSoru: İnsanlardaki lizozomlar, fagositoz yapmayan hücrelerde de aktif olabilir. Hücreler metabolik faaliyetlerinin sorunsuz geçebilmesi için bazı hücresel yapılarını yıkıp yeniden yapar.\ + \ Hücresel yapıların kontrollü ve programlı şekilde yıkılması lizozomlar tarafından yapılır ve otofaji olarak bilinir.\ + \ Otofaji ile ilgili ifadelerden; I. Otofaji sonucu hücresel yapılar yıkılamadığında lizozomal depolama hastalıkları ortaya çıkar\ + \ II. Otofaji sırasında hidrolitik enzimler hücre dışında etkinlik gösterir\ + \ III. Otofaji olayında hidrolitik enzimler lizozomlarda üretilip sitoplazmaya gönderilir hangileri doğrudur?\nA) Yalnız\ + \ I\nB) I ve II\nC) I ve III\nD) II ve III\nE) I, II ve III\nÇözüm: Adım adım düşünelim.\ + \ I. Otofaji sonucu hücresel yapılar yıkılamadığında lizozomal depolama hastalıkları ortaya çıkar: Doğru\ + \ II. Otofaji sırasında hidrolitik enzimler hücre dışında etkinlik gösterir: Yanlış, hidrolitik enzimler lizozomlarda etkinlik gösterir.\ + \ III. Otofaji olayında hidrolitik enzimler lizozomlarda üretilip sitoplazmaya gönderilir: Yanlış, hidrolitik enzimler lizozomlarda üretilir ve lizozom içinde etkinlik gösterir.\ + \ Doğru cevap A şıkkıdır." +num_fewshot: 0 +dataset_name: Biology diff --git a/lm_eval/tasks/turkishmmlu/config_cot/Chemistry.yaml b/lm_eval/tasks/turkishmmlu/config_cot/Chemistry.yaml new file mode 100644 index 00000000..b002bb91 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config_cot/Chemistry.yaml @@ -0,0 +1,86 @@ +include: _turkishmmlu_cot_default_yaml +task: turkishmmlu_cot_chemistry +description: + "Soru: 16 litre CO ve CO $_{2}$ gaz karışımını yakmak için aynı koşullarda 30 litre hava kullanılmaktadır.\ + \ Buna göre başlangıç karışımındaki VCO\/VCO$_{2}$ oranı aşağıdakilerden hangisidir?(Havanın 1\/5’i oksijen gazıdır.)\nA)\ + \ 3\nB) 3\/8\nC) 2\/3\nD) 1\/5\nE) 1\/3\nÇözüm: Adım adım düşünelim.\ + \ Yakma için kullanılan hava miktarının 1\/5'i oksijen olduğuna göre; 30 litre hava içinde 30*(1\/5) = 6 litre oksijen mevcuttur.\ + \ CO ve CO$_2$ yakmak için gerekli oksijen miktarlarını inceleyelim:CO + 1\/2 O$_2$ → CO$_2$ (Her 1 mol CO için 1\/2 mol O$_2$ gerekir.)\ + \ CO$_2$ yanmaz. Bu durumda, CO'nun yandığını ve tüm 6 litre oksijeni kullandığını varsayalım. 2 mol CO (her biri 22.4 litre/mol standart koşullarda)\ + \ için 1 mol O$_2$ (22.4 litre/mol) gerekiyor. Bu nedenle, 6 litre O$_2$ ile 12 litre CO yakılabilir.\ + \ Bu bilgiyle, başlangıçtaki CO miktarını hesaplayabiliriz. Ancak burada bir yanlış anlama var; zira yakma işlemi\ + \ sonunda sadece CO kullanıldığını farzetmek, CO$_2$'nin başlangıçta orada olmadığını varsayar ki bu doğru değil.\ + \ Soruda CO ve CO$_2$ karışımından bahsedilmektedir, bu nedenle direkt CO kullanımı üzerinden gitmemiz gerek.\ + \ Yakma işlemi CO için geçerli olduğundan ve tüm oksijen CO'nun yanması için kullanıldığından, CO miktarı ve oranı\ + \ direkt olarak hesaplanmalıdır. 6 litre O$_2$, 12 litre CO yakabilir düşüncesi yanlış olmuştur, çünkü her 1 litre CO için 1\/2 litre O$_2$ gerekmektedir.\ + \ Doğru açıklamayla, \\(V_{CO}\\) miktarını \\(x\\) litre ve \\(V_{CO_2}\\) miktarını \\(16 - x\\) litre olarak alalım.\ + \ CO yanmak için 1\/2 oranında O2 kullanır:\ + \ $\\[x \\text{ litre CO} \\times \\frac{1}{2} = \\frac{x}{2} \\text{ litre O}_2\\]$\ + \ Tüm işlemde 6 litre O$_2$ kullanıldığından ve bu O$_2$ yalnızca CO'nun yanması için kullanıldığından,\ + \ $\\(\\frac{x}{2} = 6 \\rightarrow x = 12\\)$. Yani 12 litre CO ve dolayısıyla $\\(16 - 12 = 4\\)$ litre CO$_2$ vardır.\ + \ Bu durumda VCO\/VCO$_2$ oranı $\\(12 / 4 = 3\\)$'tür. Doğru cevap A şıkkıdır.\n\nSoru:\ + \ Aşağıda verilen çözeltilerden hangisinin bileşenlerinin fiziksel halleri doğru verilmiştir?\nÖrnek Çözünen\ + \ Çözücü\nA) Alkollü su Katı Sıvı\nB)\ + \ Tuzlu su Sıvı Katı\nC)\ + \ Gazoz Gaz Sıvı\nD)\ + \ Lehim Gaz Katı\nE)\ + \ Palladyumda hidrojen Katı Gaz\nÇözüm: Adım adım düşünelim.\ + \ Doğru seçenek C şıkkıdır: Gazoz. Gazoz, çözüneni bir gaz (genellikle karbondioksit) ve çözücüsü bir sıvı (su) olan bir çözeltidir. Diğer seçeneklerde çözünen ve çözücü arasındaki fiziksel haller doğru verilmemiştir.\ + \ A şıkkı: Alkollü su; çözünen etanol (alkol) katı değil, sıvı halde ve çözücü su, sıvı halde olmalıdır.\ + \ B şıkkı: Tuzlu su; çözünen tuz (genellikle sodyum klorür) katı, çözücü su ise sıvı halde olmalıdır.\ + \ D şıkkı: Lehim; çözünen katı bir madde (genellikle kalay ve kurşun alaşımı) ve çözücü katı halde olduğunda lehim olarak adlandırılmaz; ısındığında sıvı hale geçer.\ + \ E şıkkı: Palladyumda hidrojen; çözünen hidrojen gazı ve çözücüsü katı bir metal olan palladyum doğru bir açıklamadır fakat soruda istenilen \"çözücü ve çözünenin fiziksel halleri\" açısından en uygun seçenek\ + \ Gazozdur. Doğru cevap C şıkkıdır.\n\nSoru: $_{29}$X$^{2+}$ iyonu ve $_{27}$Y atomu ile ilgili,\ + \ l. s orbitallerindeki elektron sayısı farklıdır. ll. İzoelektronik taneciklerdir. lll. Yarı dolu orbital sayıları eşittir.\ + \ yargılarından hangileri yanlıştır?\nA) l, ll ve lll\nB) ll ve lll\nC) l ve ll\nD) l ve lll\nE) Yalnız lll\nÇözüm: Adım adım düşünelim.\ + \ Bu soruyu çözmek için her iki tanecik $(_{29} \\text{X}^{2+} \\text{ ve } _{27}\\text{Y})$ hakkında bazı bilgileri bilmek gerekmektedir.\ + \ İlk olarak, periyodik cetveldeki yerlerine ve elektron konfigürasyonlarına bakalım.\ + \ - $_{29}$X sembolü ile temsil edilen element Bakır (Cu)’dır ve onun +2 yüklü iyonu $_{29}\\text{Cu}^{2+}$, 29 protona\\ + \ ve 27 elektrona sahip olacaktır. Bakır'ın temel hâli için elektron konfigürasyonu $[Ar] 3d^10 4s^1$ dir,\ + \ ancak 2 elektron kaybettiğinde, 4s orbitalinden ve bir sonraki 3d orbitalinden elektronlar kaybolur ve son konfigürasyon $[Ar] 3d^9$ olur.\ + \ - $_{27}$Y sembolü ile temsil edilen element Kobalt (Co)’dır ve Kobalt'ın nötr atomu, 27 elektrona sahiptir.\ + \ Kobalt'ın elektron konfigürasyonu $[Ar] 3d^7 4s^2$ dir. Şimdi yargılara bakalım:\ + \ l. s orbitallerindeki elektron sayısı farklıdır. Bu doğru, çünkü Cu^{2+} iyonunda 4s orbitali tamamen boşken,\ + \ Co atomunda 4s orbitali 2 elektron içerir.\ + \ ll. İzoelektronik taneciklerdir. Bu yanlış, çünkü izoelektronik tanecikler aynı sayıda elektrona ve\ + \ elektron dizilimine sahiptir. Bu durumda, Cu^{2+} iyonu ve Co atomu izoelektronik değildir.\ + \ lll. Yarı dolu orbital sayıları eşittir. Bu yanlış, çünkü Cu^{2+} yalnızca bir yarı dolu 3d orbitaline (3d^9) sahipken,\ + \ Co atomunda birden fazla yarı dolu 3d orbitali bulunabilir.\ + \ Dolayısıyla, ll ve lll yargıları yanlıştır. Doğru cevap B şıkkıdır.\n\nSoru:\ + \ Elektrolitik metal kaplama, elektrokimyasal metotlar kullanılarak yüzeyde metalik film oluşturulmasıdır.\ + \ Bu işlem malzemenin korozyondan korunması, güzel görünmesi ve yüksek sertlik kazanması gibi amaçlarla uygulanır.\ + \ Aşağıda verilenlerden hangisinde bu yöntem kullanılmamıştır?\nA) Bakır kapların\ + \ kalaylanması.\nB) Araba jantlarının nikel ile kaplanması.\nC) Çeliğin ısıya ve korozyona karşı dayanıklılığını artırmak\ + \ için alüminyum ile kaplanması.\nD) Demir tavanın yüzeyinin teflon ile kaplanması.\nE) Kol saatinin altın\ + \ ile kaplanması.Çözüm: Adım adım düşünelim. Elektrolitik metal kaplama yöntemi, bir metalin başka bir metal ile kaplanmasını içerir.\ + \ Bu yöntem, genellikle elektrokimyasal süreçler kullanılarak yapılır ve metal yüzeyinin korunmasını,\ + \ estetik görünüm kazanmasını veya belirli özellikler elde etmesini amaçlar. Seçenekler arasında bahsedilen\ + \ uygulamalardan Teflon ile kaplama işlemi, elektrolitik bir süreç değildir. Teflon (PTFE),\ + \ metal bir malzeme değil, sıcaklığa ve kimyasallara karşı dirençli bir polimer türüdür. Demir tavanın\ + \ yüzeyinin Teflon ile kaplanması, elektrokimyasal bir yöntem değil, daha ziyade fiziksel veya kimyasal\ + \ buhar biriktirme gibi farklı bir süreç gerektirir.\ + \ Doğru cevap D şıkkıdır.\n\nSoru: Laboratuvarda deney yapan beş arkadaş ile ilgili aşağıdaki bilgiler veriliyor.\ + \ Hasan: Asitler ile çalışılan bir deneyde asitin üzerine su ekliyor.\ + \ İnci: Deney sonrası malzemeleri tezgâhın üzerinde bırakıp deney raporunu yazmaya koyuluyor.\ + \ Nihal: Çözeltinin çökelmesini beklemek için yan masadaki arkadaşlarıyla sohbet ediyor.\ + \ Gülsüm: Kimyasal malzemeler ile çalışırken eldiven giymiyor ve aynı bagetle iki farklı çözeltiyi karıştırıyor.\ + \ Cenk: Sodyum metalinin su ile tepkimesini yaparken gözlerine koruyucu gözlük takıyor.\ + \ Yukarıda verilen bilgilere göre hangi öğrencilerin laboratuvardaki davranışları doğrudur?\nA) Hasan ve Gülsüm\nB) Nihal,\ + \ Gülsüm ve İnci\nC) Hasan ve İnci\nD) Nihal\nE) Cenk\nÇözüm: Adım adım düşünelim.\ + \ Laboratuvarda güvenli çalışmanın bazı kuralları vardır, bu kurallar tehlikeleri azaltmak\ + \ ve güvenli bir çalışma ortamı sağlamak için önemlidir. Öğrencilerin davranışlarını bu kurallar ışığında değerlendirelim:\ + \ - Hasan, asitlerle çalışırken asidin üzerine su ekliyor. Bu işlem çok tehlikelidir çünkü asidin üzerine su eklemek\ + \ yanma ya da patlamaya sebep olabilir. Doğru yöntem, suyun üzerine yavaşça asit eklemektir.\ + \ - İnci, deney sonrası malzemeleri tezgâhın üzerinde bırakıyor ve deney raporuna geçiyor. Laboratuvar güvenliği\ + \ açısından malzemelerin doğru şekilde temizlenmesi ve düzenlenmesi gerekmektedir. Bu yüzden İnci'nin davranışı yanlıştır.\ + \ - Nihal, çözeltinin çökelmesini beklerken yan masadaki arkadaşlarıyla sohbet ediyor. Deney süresince dikkatin\ + \ dağılmaması ve her zaman deney üzerinde kontrolün sağlanması önemli olduğundan, bu davranış doğru olmasa da,\ + \ direkt olarak güvenlikle ilişkili bir hata içermiyor.\ + \ - Gülsüm, kimyasal malzemeler ile çalışırken eldiven giymiyor ve aynı bağetle iki farklı çözeltiyi karıştırıyor.\ + \ Kimyasallarla çalışırken kişisel koruyucu ekipman kullanmak çok önemlidir, bu nedenle eldiven giymemek ve çapraz\ + \ kontaminasyona yol açacak şekilde aynı aracı kullanmak yanlıştır.\ + \ - Cenk, sodyum metalinin su ile tepkimesini yaparken gözlerine koruyucu gözlük takıyor. Bu, doğru bir davranıştır\ + \ çünkü bu tür bir deney sırasında gözleri korumak son derece önemlidir.\ + \ Buna göre, laboratuvardaki doğru davranışları sergileyen öğrenci Cenk'tir. Doğru cevap E şıkkıdır." +num_fewshot: 0 +dataset_name: Chemistry diff --git a/lm_eval/tasks/turkishmmlu/config_cot/Geography.yaml b/lm_eval/tasks/turkishmmlu/config_cot/Geography.yaml new file mode 100644 index 00000000..e940a306 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config_cot/Geography.yaml @@ -0,0 +1,52 @@ +include: _turkishmmlu_cot_default_yaml +task: turkishmmlu_cot_geography +description: + "Soru: Yerkabuğunu oluşturan levha sınırları ile aşağıdakilerden hangisinin dağılışı paralellik göstermez?\nA) Tektonik depremlerin\nB) Volkanik faaliyetlerin\nC) Kaplıcaların\nD)\ + \ Orman alanlarının\nE) Fay hatlarının\nÇözüm: Adım adım düşünelim.\ + \ Bu soruyu cevaplayabilmek için, levha sınırlarının özelliklerini ve levha hareketlerinin yeryüzündeki etkilerini bilmek gerekir.\ + \ A) Tektonik depremlerin dağılışı, levha sınırlarıyla paralellik gösterir. Levhaların birbirinden uzaklaştığı veya birbirine çarptığı yerlerde depremler meydana gelir.\ + \ B) Volkanik faaliyetlerin dağılışı, levha sınırlarıyla paralellik gösterir. Özellikle açılma (divergent) sınırlarında ve çarpışma (konverjan) sınırlarında volkanik faaliyetler görülür.\ + \ C) Kaplıcaların dağılışı, levha sınırlarıyla paralellik gösterir. Yerkabuğu inceldikçe ve magma yeryüzüne yaklaştıkça kaplıcalar oluşur. Bu da genellikle levha sınırlarında gerçekleşir.\ + \ D) Orman alanlarının dağılışı, levha sınırlarıyla paralellik göstermez. Orman alanlarının dağılışı iklim, toprak yapısı, yükselti gibi faktörlere bağlıdır, doğrudan levha sınırlarıyla ilişkili değildir.\ + \ E) Fay hatlarının dağılışı, levha sınırlarıyla paralellik gösterir. Faylar, levha hareketleri sonucu oluşur ve levha sınırlarına paralel uzanırlar.\ + \ Dolayısıyla, verilen seçeneklerden sadece D şıkkı \"Orman alanlarının\" dağılışı, levha sınırlarıyla paralellik göstermez.\ + \ Doğru cevap D şıkkıdır.\n\nSoru: Geçmişten günümüze değişen iklim koşullarına rağmen, kendi yaşam bölgelerinde varlıklarını\ + \ devam ettiren kalıntı bitkilere..........denir. \ + \ Yukarıdaki boşluğa aşağıdakilerden hangisi getirilirse cümle tamamlanmış olur?\nA)\ + \ Endemik\nB) Relikt\nC) Psödomaki\nD) Antropojen Bozkır\nE) Habitat\nÇözüm: Adım adım düşünelim.\ + \ Bu soruyu cevaplayabilmek için \"relikt\" kavramının ne anlama geldiğini bilmemiz gerekir.\ + \ Relikt bitkiler, geçmiş dönemlerdeki iklim koşullarına uyum sağlamış ve günümüze kadar varlıklarını sürdürebilmiş bitki türleridir.\ + \ Bu bitkiler, çevresel koşullar değişmiş olmasına rağmen özel alanlarda hayatta kalabilmişlerdir.\ + \ Seçeneklere baktığımızda, relikt bitkileri en iyi tanımlayan seçenek B şıkkındaki \"Relikt\" seçeneğidir.\ + \ Doğru cevap B şıkkıdır.\n\nSoru: I. Üretim sürecinde doğanın dengesini bozacak ve\ + \ insan sağlığına zararlı olabilecek kimyasal madde kullanmadan yapılan bir tarım şeklidir. II. Yağışın az, sulamanın yetersiz olduğu alanlarda tarlaların bir yıl ekilip, bir yıl dinlendirilmesi şeklinde uygulanan bir tarım yöntemidir. III. Kış sıcaklık ortalamasının 0 °C’nin altına inmediği yerlerde uygulanan tarım yöntemidir.\ + \ Bu yöntem tarım ürünlerinin mevsimi dışında yetiştirilmesine olanak sağlar. Yukarıda anlatılan tarımsal faaliyetler hangisinde doğru verilmiştir?\ + \ I II III \nA) Organik Nadas Seracılık\nB) Entansif Organik Ekstansif\nC) Seracılık Nadas Organik\nD) Ekstansif Nadas Seracılık\nE)\ + \ Organik Ekstansif Seracılık\nÇözüm: Adım adım düşünelim. Bu soruyu cevaplayabilmek için, verilen tarım yöntemlerinin özelliklerini bilmemiz gerekir.\ + \ Organik tarım, üretim sürecinde doğanın dengesini bozacak ve insan sağlığına zararlı olabilecek kimyasal madde kullanmadan yapılan bir tarım şeklidir.\ + \ Nadas, yağışın az, sulamanın yetersiz olduğu alanlarda tarlaların bir yıl ekilip, bir yıl dinlendirilmesi şeklinde uygulanan bir tarım yöntemidir.\ + \ Seracılık, kış sıcaklık ortalamasının 0 °C’nin altına inmediği yerlerde uygulanan tarım yöntemidir. Bu yöntem tarım ürünlerinin mevsimi dışında yetiştirilmesine olanak sağlar.\ + \ Dolayısıyla, verilen tarım yöntemlerinin doğru karşılıkları şu şekildedir: Organik - Nadas - Seracılık\ + \ Doğru cevap A şıkkıdır.\n\nSoru:\ + \ Yeşilırmak Havzası gelişim projesi ile aşağıdakilerden hangisinin gerçekleşmesi beklenmez?\nA)\ + \ Yeşilırmak'ın akım düzensizliğinden kaynaklanan sel, taşkın, erozyon, su ve çevre kirliliği sorunlarının çözülmesi\nB)\ + \ Otlak alanlarının iyileştirilmesi\nC) Düzenli kentleşmenin sağlanması\nD) Sanayileşmenin\ + \ gerçekleşmesi\nE) Bölgeden çıkarılan ham madde kaynaklarının pazarlanması\nÇözüm: Adım adım düşünelim.\ + \ Yeşilırmak Havzası Gelişim Projesi genellikle bölgedeki çevresel sorunların çözümü, tarım alanlarının geliştirilmesi, su kaynaklarının yönetimi gibi hedeflerle yapılan bir projedir.\ + \ A) Doğru: Projede sel, taşkın, erozyon gibi akım düzensizliğinden kaynaklanan sorunların çözülmesi hedeflenir.\ + \ B) Doğru: Projede otlak alanlarının iyileştirilmesi ve tarım alanlarının geliştirilmesi gibi doğal alanların rehabilitasyonu da önemli bir hedeftir.\ + \ C) Doğru: Projede düzenli kentleşme, altyapı geliştirme gibi şehir planlaması da dikkate alınır.\ + \ D) Doğru: Projenin amaçlarından biri sanayileşmede plansızlığın giderilmesi ve sanayinin gelişmesidir.\ + \ E) Yanlış: Projedenin amaçları arasında ham madde kaynaklarının pazarlanması yer almamaktadır.\ + \ Sonuç olarak, E) Bölgeden çıkarılan ham madde kaynaklarının pazarlanması beklenmez, çünkü projenin amaçları arasında yer almamaktadır.\ + \ Doğru cevap E şıkkıdır.\n\nSoru:\ + \ 1\/2.000.000 ölçekli bir haritada 4 cm olarak gösterilen A-B arasındaki uzaklık başka bir haritada 16 cm olarak gösterilmiştir.\ + \ Buna göre ikinci haritanın ölçeği aşağıdakilerden hangisidir?\nA) 1\/100.000\nB) 1\/200.000\nC) 1\/500.000\nD) 1\/1.500.000\nE)\ + \ 1\/8.000.000\nÇözüm: Adım adım düşünelim.\ + \ İlk haritada 4 cm olarak gösterilen A-B arasındaki uzaklık, ikinci haritada 16 cm olarak gösterilmiştir.\ + \ İlk haritada 4 cm olan uzaklık, ikinci haritada 16 cm olarak gösterildiğine göre, ikinci haritanın ölçeği 4 kat büyüktür.\ + \ İlk haritanın ölçeği 1/2.000.000 olduğuna göre, ikinci haritanın ölçeği 4 kat büyük olduğundan 1/500.000 olacaktır.\ + \ Dolayısıyla, ikinci haritanın ölçeği 1/500.000'dir.\ + \ Doğru cevap C şıkkıdır." +num_fewshot: 0 +dataset_name: Geography diff --git a/lm_eval/tasks/turkishmmlu/config_cot/History.yaml b/lm_eval/tasks/turkishmmlu/config_cot/History.yaml new file mode 100644 index 00000000..cbb53a59 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config_cot/History.yaml @@ -0,0 +1,72 @@ +include: _turkishmmlu_cot_default_yaml +task: turkishmmlu_cot_history +description: + "Soru: Denizcilikte öne çıkan ............. Beyliği Balıkesir bölgesinde kuruldu.\ + \ Osmanlı Devleti’ne .............. döneminde katıldı. Bu beyliğin Osmanlı Devletine katılmasıyla Osmanlı\ + \ Devleti’nde donanma gücü oluşturuldu. Yukarıdaki metinde boş bırakılan yerlere aşağıdakilerden hangisi getirilmelidir?\nA)\ + \ Karesioğulları - Orhan Bey\nB) Hamitoğulları - I. Murat (Hüdavendigar)\nC) Ramazanoğluları\ + \ - I. Selim (Yavuz)\nD) Karamanoğulları - II. Mehmet (Fatih)\nE) Candaroğulları - II. Mehmet (Fatih)\nÇözüm: Adım adım düşünelim.\ + \ Denizcilikte öne çıkan Karesi Beyliği Balıkesir bölgesinde kurulmuştur.\ + \ Osmanlı Devleti'ne katılması ise Orhan Bey döneminde gerçekleşmiştir.\ + \ Bu dönemde Karesi Beyliği'nin Osmanlı'ya katılmasıyla Osmanlı Devleti'nde donanma gücü oluşturulmuştur.\ + \ Doğru cevap A şıkkıdır.\n\nSoru: Osmanlı Devleti’nin kuruluşu ile ilgili birçok tez ortaya atılmıştır.\ + \ Bu tezler arasında birbiriyle benzer fikirler\ + \ olmakla beraber birbirinden oldukça farklı bakış açılarını temsil eden görüşler de ortaya atılmıştır.\ + \ Bu doğrultuda Tarihçi Colin İmber’in görüşleri “Osmanlıların kökenleri hakkındaki eski ya da çağdaş kuramların\ + \ hiçbiri kesinlikle kanıtlanamaz. Osman Gazi hakkındaki geleneksel hikâyelerin neredeyse tümü hayal ürünüdür.\ + \ Çağdaş bir tarihçinin yapabileceği en iyi şey, Osmanlı tarihinin başlangıcının bir kara delikten ibaret\ + \ olduğunu kabul etmek olacaktır.” şeklindedir. Ancak 15. yüzyılda Aşıkpaşazade Osmanlı Tarihi eserini nasıl yazdığını\ + \ şu cümlelerle ifade etmiştir: \"Kendimden önce yazılmış eserleri inceledim. Bu inceleme sonucunda\ + \ önceki dönemleri kaleme aldım.\" Buna göre, Tarihçi Colin İmber ve Aşıkpaşazade’nin görüşleri dikkate\ + \ alındığında aşağıdakilerden hangisine ulaşılamaz?\nA)\ + \ Tarihî meselelerde birbirine zıt görüşler ortaya atılmıştır.\nB) Colin İmber, Osmanlı kuruluş kaynaklarını yetersiz\ + \ görmüştür.\nC) Aşıkpaşazade eserini kaynaklara dayandırmıştır.\nD) Colin İmber, Osman Bey hakkındaki görüşleri\ + \ reddetmiştir.\nE) Osmanlı kuruluşu efsanelere dayanılarak yazılmıştır.\nÇözüm: Adım adım düşünelim.\ + \ Seçenekleri gözden geçirelim:\ + \ A) Tarihi meselelerde birbirine zıt görüşler ortaya atılmıştır.\ + \ - Bu doğru, çünkü Colin İmber ve Asıkpaşazade'nin görüşleri birbirine zıt gibi görünmektedir.\ + \ B) Colin İmber, Osmanlı kuruluş kaynaklarını yetersiz görmüştür. \ + \ - Doğru, çünkü İmber'e göre Osmanlı tarihindeki kaynaklar yetersiz ve hikayeler hayal ürünüdür.\ + \ C) Asıkpaşazade eserini kaynaklara dayandırmıştır. - Doğru, çünkü Asıkpaşazade, eserini kaynaklara dayandırdığını belirtmiştir.\ + \ D) Colin İmber, Osman Bey hakkındaki görüşleri reddetmiştir.\ + \ - Doğru, çünkü İmber, Osman Gazi hakkındaki geleneksel hikayelerin çoğunun hayal ürünü olduğunu belirtmiştir.\ + \ E) Osmanlı kuruluşu efsanelere dayanılarak yazılmıştır.\ + \ - Bu yanlıştır, çünkü Asıkpaşazade'nin eserini kaynaklara dayandırdığı\ + \ ve İmber'in görüşüne göre Osmanlı tarihinin başlangıcının kesin olarak bilinmediği belirtilmiştir.\ + \ Doğru cevap E şıkkıdır.\n\nSoru: Aşağıdakilerden hangisi İstanbul İsyanları’nın sonuçlarından biri değildir?\nA) İstanbul’da\ + \ asayiş ve kamu düzeni bozulmuştur.\nB) Yeniçerilerin devlet içindeki otoritesi artmıştır.\nC) Padişah ve devlet adamlarının\ + \ otoriteleri sarsılmıştır.\nD) Tarımsal üretim azalmış, topraklar boş kalmıştır.\nE) Halkın orduya olan güveni\ + \ azalmıştır.\nÇözüm: Adım adım düşünelim.\ + \ İstanbul İsyanları'nın sonuçlarından biri olarak verilen seçeneklerin hepsi olumlu ya da olumsuz sonuçlar içermektedir.\ + \ Ancak, D seçeneği olan \"Tarımsal üretim azalmış, topraklar boş kalmıştır\" \ + \ İstanbul İsyanları'nın sonuçlarından biri olarak kabul edilmemektedir. İstanbul İsyanları genellikle\ + \ askeri, siyasi ve sosyal sonuçlarla ilişkilendirilir, tarımsal üretimdeki azalma ve toprakların boş\ + \ kalması bu isyanlarla doğrudan bağlantılı değildir.\ + \ Doğru cevap D şıkkıdır.\n\nSoru: SSCB'nin 1991'de dağılmasından sonra Rusya'nın girişimiyle kurulan teşkilat\ + \ aşağıdakilerden hangisidir?\nA) Gümrük Birliği\nB) Avrupa Birliği\nC) Bağımsız Devletler Topluluğu\nD) Şhangay\ + \ Teşkilatı\nE) AGİT\nÇözüm: Adım adım düşünelim.\ + \ Seçenekleri gözden geçirelim: A) Gümrük Birliği - SSCB'nin dağılmasından sonra Rusya'nın girişimiyle kurulan bir teşkilat değildir.\ + \ B) Avrupa Birliği - SSCB'nin dağılmasıyla ilgili değildir ve Rusya'nın girişimiyle kurulmamıştır.\ + \ C) Bağımsız Devletler Topluluğu - SSCB'nin dağılmasından sonra Rusya'nın girişimiyle kurulan bir teşkilattır.\ + \ D) Şangay Teşkilatı - SSCB'nin dağılmasıyla ilgili değildir ve Rusya'nın girişimiyle kurulmamıştır.\ + \ E) AGİT (Avrupa Güvenlik ve İşbirliği Teşkilatı) - SSCB'nin dağılmasıyla ilgili değildir ve Rusya'nın girişimiyle kurulmamıştır.\ + \ Doğru cevap C şıkkıdır.\n\nSoru: Cüveynî “Tarih-i Cihangüşa” adlı eserinde Uygur bölgesini gezerken rastladığı garip\ + \ işaretlerle yazılmış taşlardan söz etmektedir.\ + \ Daha sonra Danimarkalı Messerschmidt’in (Mesırşmit) 1721’de bu eseri görerek Avrupa bilim camiasına tanıtması üzerine birçok bilim adamı\ + \ bu yazıların kime ait olduğu hakkında tahminlerde bulunmuştur. Bu bilim insanlarının bazıları bu yazıların; Prusyalılara, İskitlere,\ + \ Yunanlara ve Latinlere ait olduğunu ileri sürmüştür. Bölgeye giden birçok araştırmacı burada kazılar yaparak yeni kalıntılar tespit etmiştir.\ + \ Kitabelerin okunuşunu ilk çözen Danimarkalı W. Thomsen (V. Tomsen) olmuş, Türklerin yaşantılarına, töresine,\ + \ kültürüne ve devlet yönetimine dair bilgilerle birlikte bu abidelerin Türklere ait olduğunu tüm dünyaya duyurmuştur.\ + \ Metne göre, tarih biliminin aşağıdaki hangi bilim dalından yararlandığı söylenemez?\nA) Arkeoloji\nB)\ + \ Nümizmatik\nC) Epigrafi\nD) Paleografya\nE) Etnografya\nÇözüm: Adım adım düşünelim.\ + \ Metinde, Cuveyni'nin \"Tarih-i Cihanguşa\" adlı eserinde Uygur bölgesinde rastladığı garip işaretlerle yazılmış taşlardan bahsedilmektedir.\ + \ Kitabelerin okunuşunu ilk çözen Danimarkalı W. Thomsen, bu abidelerin Türklere ait olduğunu tüm dünyaya duyurmuştur.\ + \ Bu ifadelerde, epigrafi ve paleografi bilim dallarından bahsedilmektedir.\ + \ Yeni kalıntıların tespitiyle ilgili olarak arkeoloji bilim dalından da bahsedilmektedir.\ + \ Türklerin yaşantılarına, töresine, kültürüne ve devlet yönetimine dair bilgilerin elde edilmesi etnografya bilim dalıyla ilgilidir.\ + \ Nümizmatik, madeni paraları ve metal para basımı tarihini inceleyen bir bilim dalıdır.\ + \ Metinde bahsedilen taşlarla ilgili olarak nümizmatik biliminin bir katkısından bahsedilmemektedir.\ + \ Sonuç olarak, verilen metne göre tarih bilimi, nümizmatik bilim dalından yararlanmamıştır.\ + \ Doğru cevap B şıkkıdır." +num_fewshot: 0 +dataset_name: History diff --git a/lm_eval/tasks/turkishmmlu/config_cot/Mathematics.yaml b/lm_eval/tasks/turkishmmlu/config_cot/Mathematics.yaml new file mode 100644 index 00000000..ff08a127 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config_cot/Mathematics.yaml @@ -0,0 +1,74 @@ +include: _turkishmmlu_cot_default_yaml +task: turkishmmlu_cot_mathematics +description: + "Soru: 3 farklı fizik ve 4 farklı kimya kitabı sıra halinde bir rafa dizilecektir. Fizik veya kimya kitaplarının\ + \ birbirinden ayrılmaması koşuluyla bu kitaplar kaç farklı şekilde dizilebilir\nA) 7.3!.4! \nB) 3.3!.4!\nC) 5.3!.4!\nD)\ + \ 6.3!.4!\nE) 2!.3!.4!\nÇözüm: Adım adım düşünelim. + \ Bu tür soruları çözerken, ilgili koşulları adım adım inceleyerek ilerlemek önemlidir. Bu\ + \ problemde iki önemli koşul var: fizik kitaplarının birbirinden ayrılmaması ve kimya\ + \ kitaplarının birbirinden ayrılmaması gerekmektedir. 1. Adım: Fizik ve kimya kitapları kendi arasında ayrılmaması gerektiği için, tüm fizik\ + \ kitaplarını tek bir grup olarak ve tüm kimya kitaplarını da tek bir grup olarak\ + \ düşünebiliriz. Bu durumda, sadece iki grup olduğu için bu iki grubu sıra halinde\ + \ dizmenin 2! farklı yolu vardır. 2. Adım: Fizik kitapları kendi içinde sıralanabilir. 3 farklı fizik kitabı olduğu için, bu\ + \ kitapları sıralamanın 3! farklı yolu vardır. 3. Adım: Kimya kitapları kendi içinde sıralanabilir. 4 farklı kimya kitabı olduğu için, bu\ + \ kitapları sıralamanın 4! farklı yolu vardır. 4. Adım: Bu durumda, tüm durumların toplam sayısını bulmak için bu\ + \ kombinasyonların çarpımını alırız: 2! . 3! . 4!.\ + \ Doğru cevap E şıkkıdır.\n\nSoru: $(p \\land q')' \\Rightarrow p$ koşullu önermesinin\ + \ karşıtı aşağıdakilerden hangisidir?\nA) $p \\Rightarrow (p \\Rightarrow q)$\nB) $p \\Rightarrow (p \\land q')$\nC)\ + \ $p' \\Rightarrow q$\nD) $q' \\lor p$\nE) $p' \\lor (q \\Rightarrow p)$\nÇözüm: Adım adım düşünelim.\ + \ Verilen koşullu önermenin karşıtını bulmak için, öncelikle verilen koşullu önermeyi ve\ + \ karşıtını gözden geçirelim.\ + \ Verilen koşullu önerme: $(p \\land q')' \\Rightarrow p$\ + \ Bir koşullu önermenin karşıtını bulmak için, koşullu önermenin solundaki ifade (hipotez) ile\ + \ sağdaki ifade (sonuç) yer değiştirilmelidir. Buna göre, verilen önermenin karşıtı:\ + \ $p \\Rightarrow (p \\land q')'$\ + \ $(p \\land q')'$ ifadesini açalım:\ + \ $(p \\land q')' = p' \\lor q$\ + \ $(p \\land q')' = $p \\Rightarrow q$\ + \ Bu durumda, verilen koşullu önermenin karşıtı: $p \\Rightarrow (p \\land q')'$\ + \ $p \\Rightarrow (p \\Rightarrow q)$ şeklinde de ifade edilebilir. \ + \ Doğru cevap A şıkkıdır.\n\nSoru: A oto kiralama firması kiralanacak bir araç için sabit 200 TL\ + \ ve her bir kilometre için 20 kuruş almaktadır. B oto kiralama firması ise kiralanacak bir araç için sabit 140 TL ve her bir kilometre için 25 kuruş almaktadır.\ + \ Buna göre kiralanan birer araçla kaç kilometre yol gidilirse iki firmaya da ödenecek ücret birbirine eşit olur\nA) 1150\nB)\ + \ 1200\nC) 1250\nD) 1300\nE) 1350\nÇözüm: Adım adım düşünelim. A ve B firmalarının uyguladığı ücret planını bir denklemle ifade edebiliriz.\ + \ A firması için toplam maliyet: 200 + 0.20k TL ('k' kilometre için)\ + \ B firması için toplam maliyet: 140 + 0.25k TL\ + \ Bu iki firmaya ödenecek ücretin birbirine eşit olduğu durumu bulmak için bu iki ifadeyi birbirine eşitleriz:\ + \ 200 + 0.20k = 140 + 0.25k\ + \ Bu denklemi çözmek için öncelikle her iki tarafından da '140' çıkarırız ve '0.20k' sapmasını bir tarafa alırız:\ + \ 60 = 0.05k\ + \ Buradan 'k' değerini bulmak için:\ + \ k = 60/0.05 = 1200\ + \ Yani, araçlarla 1200 kilometre yol gidildiğinde iki firmaya da ödenecek ücret birbirine eşit olur.\ + \ Bu nedenle doğru seçenek B: 1200 olacaktır. Doğru cevap B şıkkıdır.\n\nSoru:\ + \ Merkezinin koordinatları M(-1,2) ve yarıçap uzunluğu r=3 birim olan çemberin standart denklemi\ + \ aşağıdakilerden hangisidir?\nA) $\\(\\mathrm{\\left( x-1\\right) ^{2}+\\left( y-2\\right) ^{2}=9}\\)$\nB)\ + \ $\\(\\mathrm{\\left( x-1\\right) ^{2}-\\left( y-2\\right) ^{2}=9}\\)$\nC)\ + \ $\\(\\mathrm{\\left( x+1\\right) ^{2}+\\left( y-2\\right) ^{2}=9}\\)$\nD)\ + \ $\\(\\mathrm{\\left( x+1\\right) ^{2}+\\left( y+2\\right) ^{2}=9}\\)$\nE)\ + \ $\\(\\mathrm{\\left( x+1\\right) ^{2}-\\left( y+2\\right) ^{2}=9}\\)$\nÇözüm: Adım adım düşünelim.\ + \ Çemberin standart denklemi $(x - h)^2 + (y - k)^2 = r^2$ şeklinde ifade edilir, burada\ + \ $(h, k)$ çemberin merkezinin koordinatlarıdır ve $r$ çemberin yarıçapıdır.\ + \ Verilen soruda, çemberin merkezi $M(-1,2)$ ve yarıçapının uzunluğu $r=3$ birim\ + \ olarak belirtilmiştir. Bu değerleri standart denklemde yerine koyalım:\ + \ Merkez $(-1, 2)$ olduğu için, $h = -1$ ve $k = 2$ olur. Yarıçap $r = 3$ birimi olduğu\ + \ için denklem $r^2 = 9$ şekline dönüşür.\ + \ Bunu denkleme yerleştirirsek:\ + \ $(x - (-1))^2 + (y - 2)^2 = 3^2$.\ + \ Bu da şu şekilde basitleştirilir:\ + \ $(x + 1)^2 + (y - 2)^2 = 9$.\ + \ Doğru cevap C şıkkıdır.\n\nSoru:\ + \ $\\(\\large| -8-1\\large| +\\large|-1+6\\large| -\\large|4\\large|\\)$ işleminin sonucu kaçtır?\nA) 2\nB)\ + \ 4\nC) 9\nD) 10\nE) 18\nÇözüm: Adım adım düşünelim.\ + \ Mutlak değer ifadesindeki sayı negatif olsa dahi sonuç pozitif olacaktır. Soruda\ + \ verilen ifadeyi adım adım çözeceğiz:\ + \ $\\large| -8 - 1\\large| + \\large| -1 + 6\\large| - \\large| 4\\large|$\ + \ İlk adımda her bir mutlak değer içindeki işlemi yapalım:\ + \ - $\\large| -8 - 1\\large| = \\large| -9\\large| = 9$ (Mutlak değer içindeki sonuç her\ + \ zaman pozitiftir.)\ + \ - $\\large| -1 + 6\\large| = \\large| 5\\large| = 5$.\ + \ - $\\large| 4\\large| = 4$.\ + \ Böylece ifade şu şekle dönüşür: $9 + 5 - 4$. Sonuç: $9 + 5 - 4 = 10$\ + \ Bu nedenle işlemin sonucu 10'dur. Doğru cevap D şıkkıdır.\n\n" +num_fewshot: 0 +dataset_name: Mathematics diff --git a/lm_eval/tasks/turkishmmlu/config_cot/Philosophy.yaml b/lm_eval/tasks/turkishmmlu/config_cot/Philosophy.yaml new file mode 100644 index 00000000..3ef5fd61 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config_cot/Philosophy.yaml @@ -0,0 +1,45 @@ +include: _turkishmmlu_cot_default_yaml +task: turkishmmlu_cot_philosophy +description: + "Soru: Aşağıdaki ifadelerden hangisi Kant'ın epistemolojik görüşünü yansıtan bir yargıdır?\nA)\ + \ Bilginin kaynağı hem akıl hem deneyimdir.\nB) Doğru bilgi mümkün değildir.\nC) Sezgiye\ + \ dayalı bilgi gerçektir.\nD) Akıl tek başına bilgi elde etmek için yeterlidir.\nE)\ + \ Fenomenlerin bilgisi özseldir.\nÇözüm: Adım adım düşünelim.\ + \ Kant'ın epistemolojik görüşü, bilginin kaynağı olarak hem akıl (yani a priori bilgi) hem de deneyim (a posteriori bilgi) olduğunu öne sürer.\ + \ Doğru cevap A şıkkıdır.\n\nSoru: Bir argümanın ya da argümanı oluşturan önermelerin kendi içinde\ + \ veya birbiriyle uygun olması o argümanın ya daönermenin .................. olduğunu gösterir. Parçadaki boşluğa aşağıdaki\ + \ kavramlardan hangisi getirilmelidir?\nA) Çelişik\nB) Gerçek\nC) Doğru\nD)\ + \ Tutarlı\nE) Geçerli\nÇözüm: Adım adım düşünelim.\ + \ Boşluğa getirilmesi gereken kavram, bir argümanın veya argümanı oluşturan önermelerin kendi içinde veya\ + \ birbiriyle uygun olmasını ifade eden bir kavram olmalıdır. Bu durumda, argümanın veya önermenin tutarlı olduğunu gösterir.\ + \ Doğru cevap D şıkkıdır.\n\nSoru: Bir tek teoloji yoktur. Hemen her dinin kendi teolojisi vardır;\ + \ Hristiyan ve İslam teolojisi gibi. Bunlardan hiçbiri açıklamalarında ait oldukları dinin inanç esaslarının dışına çıkmaz.\ + \ Aşağıdakilerden hangisi bu durumun sebebi olamaz?\nA) Teolojilerin ait oldukları dini baştan doğru kabul\ + \ etmeleri\nB) Teolojilerin din felsefesi gibi dine eleştirel olarak yaklaşmaları\nC) Teolojilerin ait oldukları\ + \ dinin doğruluğunu ispat etme çabaları\nD) Teolojilerin belli bir dini görüşü savunmaya çalışmaları\nE)\ + \ Teolojilerin din felsefesi gibi dinlere tarafsız yaklaşmamaları\nÇözüm: Adım adım düşünelim.\ + \ Bu soruda, verilen ifadelerden hangisinin çeşitli dinlerin kendi teolojilerinin ait oldukları dinin inanç esaslarının dışına\ + \ çıkmadığı durumu açıklamada bir sebep olamayacağı sorulmaktadır. Teolojinin temel amacı, bir dinin inanç esaslarını açıklamak ve yorumlamaktır.\ + \ Dolayısıyla, teolojilerin ait oldukları dini baştan doğru kabul etmeleri A), belli bir dinin görüşünü savunmaya çalışmaları, D)\ + \ ait oldukları dinin doğruluğunu ispat etme çabaları C) ve din felsefesi gibi dinlere tarafsız yaklaşmamaları E) bu durumun sebepleri olabilir.\ + \ Ancak, din felsefesi gibi dine eleştirel olarak yaklaşmaları B) ise teolojik çalışmaların temel amaçlarından biri değildir.\ + \ Doğru cevap B şıkkıdır. \n\nSoru: Konfüçyüs’a göre “Zenginlik ve şeref herkesin istediği şeylerdir. Eğer bunlar doğru bir yolda\ + \ kazanılmazsa pek çabuk kaybedilir. Fakirlik ve düşkünlük insanların nefret ettiği şeylerdir. Eğer insanlar dürüst davranmazlarsa\ + \ kendilerini bunlardan sıyırmalarının imkânı yoktur.” Bu açıklama ile Konfüçyüs, felsefenin hangi konusuna vurgu\ + \ yapmıştır?\nA) Bilgi\nB) Spor\nC) Varlık\nD) Siyaset\nE) Ahlak\nÇözüm: Adım adım düşünelim.\ + \ Konfüçyüs'ün bu açıklamasında vurgu yaptığı temel konu, insan davranışlarının doğruluğuyla ilgilidir.\ + \ Konfüçyüs, zenginlik, şeref, fakirlik ve düşkünlük gibi dışsal değerlerin kazanılmasının doğru bir şekilde sağlanmaması durumunda\ + \ hızlıca kaybedilebileceğini, ancak insanların dürüst davranışlar sergilemediği sürece bu tür olumsuzluklardan kaçmanın mümkün olmadığını vurgular.\ + \ Dolayısıyla, Konfüçyüs'ün bu açıklamasıyla vurguladığı konu ahlaktır.\ Doğru cevap E şıkkıdır.\n\nSoru:\ + \ İnancın temele alındığı MS 2- MS 15. yüzyıl felsefesi, kendinden önceki dönem felsefelerinden etkilenmiştir.\ + \ Örneğin Hristiyan filozofları, Hristiyanlığı yaymak için diriliş inancını destekleyen ruhun ölmemesi hatta tekrar dirilmesi\ + \ fikrini savunan Antik Yunan filozofunun görüşlerinden; İslam filozofları ise Tanrı’nın varlığı kanıtlamalarında\ + \ başka bir Antik Yunan filozofunun geliştirdiği mantıktan yararlanmışlardır. Bu parçaya göre, MS 2- 15. yüzyıl\ + \ felsefesini etkileyen filozoflar sırasıyla aşağıdaki seçeneklerden hangisinde verilmiştir?\nA)\ + \ Epiküros, Aristoteles\nB) Epiküros, Platon\nC) Platon, Aristoteles\nD) Platon, Epiküros\nE)\ + \ Aristoteles, Platon\nÇözüm: Adım adım düşünelim.\ + \ Parçada belirtilenler doğrultusunda, Hristiyan filozoflarının diriliş inancını desteklemek için Antik Yunan filozoflarının ruhun ölmemesi\ + \ ve hatta tekrar dirilmesi fikrini savunan görüşlerinden etkilendiği ifade edilmiştir. Bu görüşleri savunan Antik Yunan filozofunun Platon olduğu bilinmektedir.\ + \ İslam filozoflarının ise Tanrı'nın varlığını kanıtlamada başka bir Antik Yunan filozofunun mantığından yararlandığı ifade edilmektedir\ + \ ve bu filozofun da Aristoteles olduğu bilinmektedir. Doğru cevap C şıkkıdır." +dataset_name: Philosophy diff --git a/lm_eval/tasks/turkishmmlu/config_cot/Physics.yaml b/lm_eval/tasks/turkishmmlu/config_cot/Physics.yaml new file mode 100644 index 00000000..25d8eff9 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config_cot/Physics.yaml @@ -0,0 +1,106 @@ +include: _turkishmmlu_cot_default_yaml +task: turkishmmlu_cot_physics +description: + "Soru: 20°C sıcaklığında R direncine sahip silindirik bakır tel eritilerek boyu ilk boyunun iki katı kadar ve yine\ + \ silindirik olacak biçimde yeni bir kalıba dökülüyor. Bu durumda yeni telin direnci kaç R olur?\nA)\ + \ 4\nB) 2\nC) 1\nD) 1/2\nE) 1/4\nÇözüm: Adım adım düşünelim.\ + \ Yeni direncin değerini bulmak için öncelikle direncin nasıl değiştiğini anlamamız gerekiyor.\ + \ Direnç \\(R\\), iletkenin direncinin uzunluğu \\(l\\), kesit alanı \\(A\\) ve\ + \ malzemenin özdirenci (veya direnç katsayısı) \\(\\rho\\) ile doğrudan ilişkilidir ve\ + \ aşağıdaki formülle ifade edilir:\ + \ \\[R = \\rho \\frac{l}{A}\\]\ + \ Bu denklemde görüldüğü üzere, direnç iletkenin uzunluğu ile doğru orantılıyken,\ + \ kesit alanı ile ters orantılıdır. Soruda verilenler doğrultusunda, bakır telin uzunluğu iki\ + \ katına çıkarılıyor, bu durumda yeni uzunluğumuz \\(2l\\) olacaktır. Bakır telin hacmi\ + \ değişmediğinden ve şekli de yine silindirik olduğundan, bu durumda kesit alan da\ + \ değişmek zorundadır; çünkü uzunluk iki katına çıkartıldığında, hacmi korumak için\ + \ kesit alanın yarıya düşürülmesi gerekiyor. Yeni kesit alanımız \\(A/2\\) olacaktır.\ + \ Yeni direnç \\(R'\\) şu şekilde hesaplanır:\ + \ \\[R' = \\rho \\frac{2l}{A/2} = 4 \\times \\rho \\frac{l}{A}\\]\ + \ Bu durumda, yeni direnç \\(R'\\) orijinal direnç \\(R\\) ile karşılaştırıldığında 4 katına\ + \ çıkmış olur. Doğru cevap A şıkkıdır.\n\nSoru: Karayip resif mürekkep balığı suyun üstünde 2 m yüksekliğe çıkmak\ + \ ve vücut uzunluğunun 50 katı kadar bir mesafeye yani toplamda 10 m uçmak için tepkili itme kullanır.\ + \ Bunun için vücuduna düşük hızda aldığı akışkan ile kütlesini arttırıp, sonra bu akışkanı yüksek hızda dışarı atarak kütlesini azaltır. Mürekkep balığının kullandığı\ + \ bu yöntem roketleri fırlatmak için ihtiyaç duyulan itiş gücünün temel mantığını oluşturur. Örneğin yükünü\ + \ kaldırabilecek yeterli itiş kuvvetinin sağlanabilmesi için Atlas V roketinde, saniyede 1000 kg’dan fazla yakıt\ + \ tüketilmesi ve egzoz gazının saniyede 4000 m süratle dışarı atılması gerekmiştir. Yer çekimine karşı yapılan bu\ + \ fırlatma işlemi rokete uçuş süresi boyunca gerekli yakıtın sağlanması ve yer çekiminden kurtulmak için saatte 40000 km gibi bir sürate ulaşması\ + \ ile mümkün olabilmektedir. Aşağıdakilerden hangisinde ya da hangilerinde\ + \ yukarıdaki metinde geçen duruma örnek verilebilir?\nI. Şişirilen balonun serbest bırakılması. II. Ateşlenen top aracının geriye doğru hareket etmesi.\ + \ III. Havada patlayan havai fişeği parçalarının farklı yönlerde ilerlemesi. IV.\ + \ Hareketli bir bilardo topu ile duran bilardo topunun hareket ettirilmesi\nA) Yalnız I\nB)\ + \ Yalnız II\nC) I ve II\nD) II ve IV\nE) I, II ve IV\nÇözüm: Adım adım düşünelim.\ + \ Yukarıdaki metinde anlatılan durum, bir cismin içerisinden hızla dışarı atılan akışkan veya gaz sayesinde\ + \ ters yönde bir itiş gücü üretilmesini ve bu sayede ileri hareket edilmesini içerir. Bu durum, roketlerin fırlatılma\ + \ prensibi ve Karayip resif mürekkep balığının hareket mekanizması ile örneklendirilmiştir. Verilen seçenekler göz önünde\ + \ bulundurulduğunda: \ + \ I. Şişirilen balonun serbest bırakılması - Bu durum, balonun içindeki hava dışarıya hızla atıldığında balonun ters yönde\ + \ hareket etmesi prensibine dayanır, bu nedenle ilgili durumla benzerdir. \ + \ II. Ateşlenen top aracının geriye doğru hareket etmesi - Bu, Newton'un üçüncü yasası (her eyleme karşılık eşit ve zıt\ + \ yönde bir tepki olur) örneğidir ve roketin veya mürekkep balığının hareketine benzer bir durumdur. Ateşlenen top, bir yöne doğru\ + \ kuvvet uyguladığında, top aracı da zıt yönde bir kuvvetle hareket eder.\ + \ III. Havada patlayan havai fişeğin parçalarının farklı yönlere ilerlemesi - Bu, içeriden\ + \ dışarıya bir patlama etkisi ile nesnelerin her yöne dağılmasını içerir ve itme\ + \ kuvvetinin her yöne eşit dağıldığı bir durumu ifade eder. Bu örnek, direkt olarak\ + \ içeriden dışarıya hızlı bir akışkan veya gazın atılması ile ileri hareket etme prensibini\ + \ taşımaz.\ + \ IV. Hareketli bir bilardo topu ile duran bilardo topunun hareket ettirilmesi - Bu, iki katı\ + \ cismin çarpışması durumunu ve momentumun korunumu ilkesini içerir, direkt olarak\ + \ itiş kuvveti prensibi ile ilgili değildir.\ + \ Böylece, açıklanan prensiplere en çok uyan seçenek I. ve II. durumları içeren seçenek doğrudur.\ + \ Doğru cevap C şıkkıdır.\n\nSoru: Yay sabiti k olan yay sarkacı ve ip uzunluğu $\\(\\ell\\)$ olan basit sarkaçtan oluşturulan\ + \ sistemler yerçekimi ivmesinin daha büyük olduğu bir gezegene götürülürse periyotları nasıl değişir?\nYay Sarkacı Basit Sarkaç\nA) Değişmez Artar\nB) Değişmez Değişmez\nC) Azalır\ + \ Değişmez\nD) Artar Azalır\nE) Değişmez Azalır\nÇözüm: Adım adım düşünelim.\ + \ Yay sarkacının periyodu, yay sabiti \\(k\\) ve sarkacın kütlesi \\(m\\) ile ilişkili olup\ + \ \\(T = 2\\pi\\sqrt{\\frac{m}{k}}\\) formülüyle hesaplanır. Yerçekimi ivmesi (\\(g\\)) bu formülde yer almadığından, yay sarkacının\ + \ periyodu yerçekimi ivmesinin değerinden bağımsızdır ve değişmez. \ + \ Basit sarkacın periyodu ise \\(T = 2\\pi\\sqrt{\\frac{\\ell}{g}}\\) formülüyle hesaplanır. Bu formülde \\(\\ell\\) ipin uzunluğunu\ + \ ve \\(g\\) yerçekimi ivmesini temsil eder. Eğer yerçekimi ivmesi \\(g\\) büyükse, denklemin paydası büyüyeceğinden, periyodun\ + \ değeri azalır. Bu durumda, yay sarkacının periyodu değişmezken, basit sarkacın periyodu azalır.\ + \ Doğru cevap E şıkkıdır.\n\nSoru: 100 g kütleli bir kap özkütlesi 1 g/cm $^{3}$ olan su ile dolu iken kütlesi 350 g oluyor.\ + \ Buna göre, kap 0,5 g/cm$^{3 }$özkütleli sıvı ile doldurulursa kütlesi kaç g olur?\nA) 75\nB)\ + \ 125\nC) 175\nD) 225\nE) 250\nÇözüm: Adım adım düşünelim.\ + \ Kap ve suyun birleşik kütlesi 350 g olduğuna göre, sadece suyun kütlesini bulabilmek için kapın kütlesini bu değerden\ + \ çıkarmamız gerekiyor. Kap zaten boşken 100 g olduğuna göre: \ + \ Su + kap = 350 g\ + \ Su = 350 g - kap\ + \ Su = 350 g - 100 g\ + \ Su = 250 g\ + \ Bu, kapın içerisine koyduğumuz suyun kütlesinin 250 g olduğunu gösterir. Su için\ + \ verilen özkütlesi 1 g/cm$^{3}$ olduğuna göre ve kütlesi 250 g ise hacmi de 250\ + \ cm$^{3}$ olmalıdır (çünkü kütlesi özkütlesi ile çarpıldığında hacmini verir).\ + \ Şimdi, 0,5 g/cm$^{3}$ öz kütleli bir sıvı ile aynı kapı doldurursak, aynı hacmi (250\ + \ cm$^{3}$) dolduracağını varsayabiliriz. Bu sıvının kütlesini bulmak için hacmi öz\ + \ kütlesi ile çarpalım:\ + \ Kütle = özkütle * hacim\ + \ Kütle = 0,5 g/cm$^{3}$ * 250 cm$^{3}$\ + \ Kütle = 125 g\ + \ Bu yeni sıvının kütlesi 125 g olacaktır. Ancak bu sadece sıvının kütlesi. Toplam\ + \ kütleyi bulmak için kapın kütlesini (100 g) de eklememiz gerekiyor:\ + \ Toplam kütle = sıvı + kap\ + \ Toplam kütle = 125 g + 100 g\ + \ Toplam kütle = 225 g\ + \ Buna göre, kap 0,5 g/cm$^{3}$ özkütleli sıvı ile doldurulursa toplam kütlesi 225 g olur.\ + \ Doğru cevap D şıkkıdır.\n\nSoru: Sıcaklık için aşağıda verilenlerden hangisi doğrudur?\nA)\ + \ Bir enerji çeşitidir.\nB) Termometre ile ölçülür.\nC) Birimi\ + \ kaloridir.\nD) Madde miktarına bağlıdır.\nE) Birimi joule' dür.\nÇözüm: Adım adım düşünelim.\ + \ Sıcaklığın ne olduğunu ve nasıl ölçüldüğünü ele alarak, verilen seçenekleri inceleyelim:\ + \ A) \"Bir enerji çeşididir.\" - Bu ifade doğru değildir. Sıcaklık, enerjinin bir çeşidi değil,\ + \ malzemenin veya cismin ortalama kinetik enerjisinin bir ölçüsüdür. Dolayısıyla,\ + \ enerjinin bir türü olarak değil, enerjinin belli bir durumunu ifade eder.\ + \ B) \"Termometre ile ölçülür.\" - Bu ifade doğrudur. Sıcaklık termometre gibi özel\ + \ aygıtlar kullanılarak ölçülür. Bu aygıtlar, farklı sıcaklık değerlerinde farklı tepkiler verir\ + \ ve bu sayede sıcaklığın ne olduğunu belirleyebiliriz.\ + \ C) \"Birimi kaloridir.\" - Bu ifade yanlıştır. Kalori, enerji birimidir ve özellikle ısı\ + \ enerjisinin miktarını ölçmek için kullanılır. Sıcaklığın birimi ise derece Celsius (°C), derece\ + \ Fahrenheit (°F), veya Kelvin (K) gibi ölçü birimleridir.\ + \ D) \"Madde miktarına bağlıdır.\" - Bu ifade yanlıştır. Sıcaklık, bir maddenin miktarından\ + \ bağımsız, maddenin ortalama kinetik enerjisinin bir ölçüsüdür. Yani, madde miktarı\ + \ sıcaklığı doğrudan etkilemez; aynı sıcaklıktaki iki farklı miktar madde, biri fazla biri az\ + \ olsa dahi, aynı sıcaklığa sahip olabilir.\ + \ E) \"Birimi joule'dür.\" - Bu ifade de yanlıştır. Joule, enerjinin SI birimidir ve sıcaklığın\ + \ birimi değildir. Daha önce belirtildiği gibi, sıcaklığın birimi derece Celsius, derece\ + \ Fahrenheit veya Kelvin'dir.\ + \ Doğru cevap B şıkkıdır." +num_fewshot: 0 +dataset_name: Physics diff --git a/lm_eval/tasks/turkishmmlu/config_cot/Religion_and_Ethics.yaml b/lm_eval/tasks/turkishmmlu/config_cot/Religion_and_Ethics.yaml new file mode 100644 index 00000000..a81b9b80 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config_cot/Religion_and_Ethics.yaml @@ -0,0 +1,51 @@ +include: _turkishmmlu_cot_default_yaml +task: turkishmmlu_cot_religion_and_ethics +description: + "Soru: (I) Allah’a (c.c.) inanmak insanın hayatında olumlu değişiklikler yapar. (II) Bunun nedeni imanın; duygu, düşünce ve davranışlar üzerinde etkili olmasıdır.\ + \ (III) İnsanın Allah (c.c.) ile irtibatı dua, ibadet, tövbe ve Kur’an okuma gibi yollarla gerçekleşir. (IV) İnsan büyük oranda inancına göre görür, düşünür ve davranışlar sergiler.\ + \ (V) Bu durumu açıklayan birçok ayet ve hadis bulunmaktadır. Bu parçadaki numaralanmış cümlelerden hangisi düşüncenin akışını bozmaktadır?\nA)\ + \ I\nB) II\nC) III\nD) IV\nE) V\nÇözüm: Adım adım düşünelim.\ + \ Metinde düşüncenin akışını bozan cümle C) III'dür. Çünkü diğer cümleler imanın insan üzerindeki etkilerine odaklanırken,\ + \ III numaralı cümle insanın Allah ile irtibatını nasıl gerçekleştirdiğine dair bir açıklama sunar, bu da ana fikrin akışını biraz keser. \ + \ Doğru cevap C şıkkıdır.\n\nSoru: İslam ahlakının kaynağı aşağıdakilerden hangisidir?\nA)\ + \ Kur’an ve sünnet\nB) Birey ve toplum\nC) Terbiye ve deneyim\nD)\ + \ Akıl ve düşünce\nE) Vicdan ve bilgi\nÇözüm: Adım adım düşünelim.\ + \ İslam ahlakının kaynağı \"Kur'an ve Sünnet\"tir. \ + \ Kur'an, İslam'ın kutsal kitabıdır ve peygamberin sözleri, eylemleri ve onayladıkları olan sünnet, İslam ahlakının temelini oluşturur.\ + \ Doğru cevap A şıkkıdır.\n\nSoru: Dinimizin ibadetler konusunda önem verdiği temel ilkelerden biri ihlastır.\ + \ Dolayısıyla İslami açıdan ibadetlerin, sadece Yüce Allah’ın (c.c.) rızasını kazanmak amacıyla yapılması esastır.\ + \ Mümin, her zaman bu bilinçte olmalıdır.\nİbadetlerini bu bilinçle, severek, isteyerek ve samimiyetle yapmalıdır.\ + \ Nitekim bizler her gün namazlarda okuduğumuz Fâtiha suresinde, ---- diyerek bunu ifade ediyoruz.\ + \ Verilen parçada boş bırakılan yere aşağıdaki ayetlerden hangisi getirilmelidir?\nA)\ + \ “Rahmân ve rahîm olan Allah’ın adıyla.” (Fâtiha suresi, 1. ayet.) \nB)\ + \ “Hamd (övme ve övülme), âlemlerin Rabbi Allah’a mahsustur. ” (Fâtiha suresi, 2. ayet.) \nC)\ + \ “O, rahmândır ve rahîmdir. Ceza gününün malikidir. ” (Fâtiha suresi, 3-4. ayetler.) \nD)\ + \ “Yalnız sana ibadet eder ve yalnız senden yardım dileriz.” (Fâtiha suresi, 5. ayet.) \nE)\ + \ “Bize doğru yolu göster. ” (Fâtiha suresi, 6. ayet.)\nÇözüm: Adım adım düşünelim. \ + \ Verilen parçada ifade edildiği gibi, İslami ibadetlerin temel amacı Allah'ın rızasını kazanmaktır ve bu amaçla ibadetlerin ihlas ile yapılması önemlidir. Namazlarda okunan Fatiha suresinde bu bilinci ifade eden bir ayet bulunmaktadır.\ + \ Fatiha suresinin ayetleri şunlardır:\ + \ Rahmân ve Rahîm olan Allah'ın adıyla.\ + \ Hamd (övme ve övülme) âlemlerin Rabbi Allah'a mahsustur.\ + \ O, Rahmân'dır ve Rahîm'dir.\ + \ Ceza gününün malikidir. \ + \ Yalnız sana ibadet eder ve yalnız senden yardım dileriz.\ + \ Bize doğru yolu göster.\ + \ İbadetlerin ihlas ile yapılması ve sadece Allah'ın rızasını gözeterek gerçekleştirilmesi kavramını ifade eden ayet ise D) Yalnız sana ibadet eder ve yalnız senden yardım dileriz. şeklindeki 5. ayettir.\ + \ Doğru cevap D şıkkıdır.\n\nSoru: Müminler ancak kardeştirler. Öyleyse kardeşlerinizin arasını düzeltin.\ + \ Allah’a karşı gelmekten sakının ki size merhamet edilsin.” (Hucurât suresi, 10. ayet.) Ayetin asıl konusu nedir?\nA)\ + \ Adalet\nB) Kardeşlik\nC) İtaat\nD) Bağışlama\nE) Sorumluluk\nÇözüm: Adım adım düşünelim.\ + \ Bu ayetin asıl konusu \"Kardeşlik\"tir. Çünkü ayette müminlerin birbirlerine kardeş oldukları\ + \ ve aralarındaki ilişkilerin düzeltilmesi gerektiği vurgulanır. Doğru cevap B şıkkıdır.\n\nSoru:\ + \ İslam medeniyeti, Emeviler döneminde oluşum sürecine girmiş, Abbasiler döneminde gelişmiş, Selçuklular döneminde bu gelişim devam etmiş, \ + \ Osmanlı döneminde ise kurum ve kuruluşlarıyla en parlak devrini yaşamıştır. İslam medeniyetinin mimari, edebiyat, sanat, matematik, astronomi, tıp vb. \ + \ alanlarda ortaya koyduğu örnekler oldukça fazladır. Farabi, İbn Sina, Biruni, Harezmî, İbn Rüşd, İbn Haldun gibi ilim adamları kendi dönemlerinde, felsefe, mantık, matematik,\ + \ tıp, astronomi gibi alanlarda tüm dünyaya zengin ilmi ürünler sunmuşlardır. Bu parçanın ana konusu aşağıdakilerden hangisidir?\nA)\ + \ Medeniyetin en önemli unsurları\nB) Medeniyete katkı sağlayan İslam âlimleri\nC)\ + \ İslam medeniyetiyle ortaya çıkan kurumlar\nD) İslam medeniyetinin en parlak dönemleri\nE)\ + \ İslam medeniyetinin oluşma süreci\nÇözüm: Adım adım düşünelim.\ + \ Bu parçanın ana konusu, İslam medeniyetinin gelişimini ve etkisini tanımlayan bir açıklamadır.\ + \ Parça, İslam medeniyetinin Emeviler, Abbasiler, Selçuklular ve Osmanlılar dönemlerindeki oluşumunu ve gelişimini kapsamlı bir şekilde ele alırken,\ + \ İslam medeniyetinin farklı alanlardaki önemli katkılarını ve ilim adamlarının rollerini vurgular.\ + \ Doğru cevap E şıkkıdır." +dataset_name: Religion_and_Ethics +num_fewshot: 0 diff --git a/lm_eval/tasks/turkishmmlu/config_cot/Turkish_Language_and_Literature.yaml b/lm_eval/tasks/turkishmmlu/config_cot/Turkish_Language_and_Literature.yaml new file mode 100644 index 00000000..2e1ee51a --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config_cot/Turkish_Language_and_Literature.yaml @@ -0,0 +1,59 @@ +include: _turkishmmlu_cot_default_yaml +task: turkishmmlu_cot_turkish_language_and_literature +description: + "Soru: Aşağıdakilerden hangisi edebiyat tarihinin konuları arasında yer almaz?\nA) Edebî dönemler\nB)\ + \ Şair ve yazarların edebî kişiliği\nC) Şair ve yazarların hayatları\nD) Edebî eserler\nE)\ + \ Arkeolojik eserler\nÇözüm: Adım adım düşünelim.\ + \ Edebiyat tarihinin konularını gözden geçirelim:\ + \ A) Edebî dönemler - Edebiyat tarihi, farklı edebi dönemleri ve bu dönemlerdeki edebi akımları inceler.\ + \ B) Şair ve yazarların edebî kişiliği - Edebiyat tarihi, şair ve yazarların eserlerindeki temaları, tarzları ve edebi kişiliklerini de ele alır.\ + \ C) Şair ve yazarların hayatları - Edebiyat tarihi, şair ve yazarların biyografilerini ve hayat hikayelerini de inceler.\ + \ D) Edebî eserler - Edebiyat tarihi, farklı edebi eserleri, bu eserlerin türlerini, temalarını ve döneminin özelliklerini inceler.\ + \ E) Arkeolojik eserler - Edebiyat tarihi, genellikle arkeolojik eserlerle ilgilenmez. Arkeolojik eserler,\ + \ arkeoloji biliminin konusudur ve genellikle tarih ve kültürel antropoloji alanlarında incelenir.\ + \ Sonuç olarak, edebiyat tarihinin konuları arasında yer almayan (farklı bir alana ait olan) seçenek E) Arkeolojik eserlerdir.\ + \ Doğru cevap E şıkkıdır.\n\nSoru: Osmanlı Devleti'nin son döneminde ortaya çıkan düşünce akımlarının\ + \ temsilcileri hangi seçenekte doğru verilmiştir?\nA) İslamcılık: Sait Halim Paşa, Mehmet Emin Yurdakul\nB)\ + \ Türkçülük: Ziya Gökalp, Ömer Seyfettin\nC) Batıcılık: Tevfik Fikret, Eşref Edip\nD) Osmanlıcılık:\ + \ Mehmet Akif Ersoy, Sait Halim Paşa\nE) Medeniyetçilik: Münif Paşa, Ali Canip Yöntem\nÇözüm: Adım adım düşünelim.\ + \ Osmanlı Devleti'nin son döneminde ortaya çıkan düşünce akımlarının temsilcilerini inceleyelim:\ + \ A) İslamcılık: Sait Halim Paşa, Mehmet Emin Yurdakul - İslamcılık akımının temsilcileri arasında Sait Halim Paşa ve Mehmet Emin Yurdakul yer almamaktadır.\ + \ B) Türkçülük: Ziya Gökalp, Ömer Seyfettin - Türkçülük akımının önde gelen temsilcileri arasında Ziya Gökalp ve Ömer Seyfettin bulunmaktadır. Bu seçenek doğru görünmektedir.\ + \ C) Batıcılık: Tevfik Fikret, Eşref Edip - Batıcılık akımının temsilcileri arasında Tevfik Fikret ve Eşref Edip bulunmamaktadır.\ + \ D) Osmanlıcılık: Mehmet Akif Ersoy, Sait Halim Paşa - Osmanlıcılık akımının temsilcileri arasında Mehmet Akif Ersoy ve Sait Halim Paşa bulunmamaktadır.\ + \ E) Medeniyetçilik: Münif Paşa, Ali Canip Yöntem - Medeniyetçilik akımının temsilcileri arasında Münif Paşa ve Ali Canip Yöntem bulunmamaktadır.\ + \ Doğru cevap B şıkkıdır.\n\nSoru: Birçok edebiyatçı ve eleştirmene göre şairlik yeteneği Tevfik Fikret'ten bile daha ileridedir.\ + \ Fakat siyasi görüşleri daima sanatının önünde yer almıştır.\ + \ Millî Mücadele Dönemi'nde Anadolu hareketini eleştirmiş, saltanat yanlısı görüşler ortaya koymuştur. Cumhuriyet Dönemi'nde de siyasi fikirleri yüzünden çokça eleştirilmiştir.\ + \ Parçada bahsedilen Servetifünun şairi aşağıdakilerden hangisidir?\nA) Süleyman Nazif\nB) Hüseyin Cahit Yalçın\nC) Mehmet Rauf\nD) Cenab\ + \ Şahabettin\nE) Halit Ziya Uşaklıgil\nÇözüm: Adım adım düşünelim.\ + \ Parçada bahsedilen şairin siyasi görüşlerinin sanatından daha önde olduğu ve Milli Mücadele Dönemi'nde Anadolu hareketini eleştirdiği,\ + \ saltanat yanlısı görüşler ortaya koyduğu ve Cumhuriyet Dönemi'nde de siyasi fikirleri nedeniyle eleştirildiği belirtilmektedir.\ + \ Bu özellikler ışığında, Servet-i Fünun döneminin önemli şairlerinden olan Cenab Şahabettin'i işaretlemek gerekir.\ + \ Doğru cevap D şıkkıdır.\n\nSoru: Selime’nin odasında biraz kaldıktan sonra otelden çıktım ( ) kırlara doğru yürüdüm ( )\ + \ Tozlu bir yol ( ) İki yanında fırınlar ( ) kahveler ( ) büyük ambarlar var ( )\ + \ Bu parçada yay ayraçlarla gösterilen yerlere aşağıdaki noktalama işaretlerinden hangisinde\ + \ verilenler getirilmelidir?\nA) (,) (.) (...) (,) (,) (.)\nB) (,) (!) (.) (,) (;) (...)\nC)\ + \ (...) (.) (...) (,) (,) (.)\nD) (,) (.) (.) (,) (,) (.)\nE) (,) (.) (;) (,) (,) (.)\nÇözüm: Adım adım düşünelim.\ + \ Parçada yay ayraçlarla gösterilen yerlere uygun noktalama işaretlerini belirlememiz gerekiyor.\ + \ Parçada yer alan noktalama işaretlerini dikkate alarak, uygun noktalama işaretlerini belirleyelim:\ + \ Selime’nin odasında biraz kaldıktan sonra otelden çıktım (,) kırlara doğru yürüdüm (.)\ + \ Tozlu bir yol (...) İki yanında fırınlar (,) kahveler (,) büyük ambarlar var (.)\ + \ Parçada yer alan noktalama işaretlerine göre, doğru sıralama şu şekildedir: (,) (.) (...) (,) (,) (.)\ + \ Doğru cevap A şıkkıdır.\n\nSoru: HOROZLA İNCİ Bir horoz inci bulur, kuyumcuya gider: “Al, şuna bak, der, pırıl pırıl,\ + \ ne özrü ne kusuru var. Fakat sen bana bir avuç mısır ver, benim işime o yarar.”\ + \ Bir cahile bir kitap miras kalır. Adam kitabı alır, komşusu kitapçıya gider:\ + \ “Bak, ne güzel kitap, der, fakat sen bana beş on kuruş ver, benim işime o yarar.”\ + \ Nâzım Hikmet , La Fontaine’den Masallar Bu fablda; I. Teşhis ve intak sanatlarından yararlanıldığı,\ + \ II. Fablın kahramanlarından birinin hayvan olduğu, III. Fablda zamanın belli olduğu bilgilerinden hangilerine\ + \ ulaşılabilir?\nA) Yalnız I\nB) Yalnız II\nC) I ve II\nD) I ve III\nE) II ve III\nÇözüm: Adım adım düşünelim. + \ Verilen metinde, bir horoz ve bir cahil (insan) arasında bir benzetme yapılmıştır. Bu fabldan hangi bilgilere ulaşılabilir gözden geçirelim:\ + \ I. Teşhis ve intak sanatlarından yararlanıldığı - Metinde, horozun inciyi bulduktan sonra kuyumcuya gidip onun değerini belirlemesi anlatılmaktadır.\ + \ Bu, bir tür değerlendirme ve tanımlama sürecidir. Dolayısıyla, I doğrudur.\ + \ II. Fablın kahramanlarından birinin hayvan olduğu - Metinde, horozun inci bulduğu ve cahilin bir kitap bulduğu anlatılmaktadır.\ + \ Horoz bir hayvandır, dolayısıyla fablın bir hayvan karakterine sahip olduğunu söyleyebiliriz. II doğrudur.\ + \ III. Fablda zamanın belli olduğu - Metinde, zaman belirtilmemiştir. Dolayısıyla, III hakkında bir bilgiye ulaşılamaz.\ + \ Sonuç olarak, I ve II doğru yanıtlardır, ancak III hakkında bir bilgiye ulaşılamaz.\ + \ Doğru cevap D şıkkıdır." +num_fewshot: 0 +dataset_name: Turkish_Language_and_Literature diff --git a/lm_eval/tasks/turkishmmlu/config_cot/_turkishmmlu_cot_default_yaml b/lm_eval/tasks/turkishmmlu/config_cot/_turkishmmlu_cot_default_yaml new file mode 100644 index 00000000..e2f9f9d6 --- /dev/null +++ b/lm_eval/tasks/turkishmmlu/config_cot/_turkishmmlu_cot_default_yaml @@ -0,0 +1,34 @@ +tag: turkishmmlu_cot +task: null +dataset_path: AYueksel/TurkishMMLU +dataset_name: TurkishMMLU +test_split: test +fewshot_split: dev +output_type: generate_until +doc_to_text: "\n\nSoru: {{ question.strip() }}\nA) {{ choices[0] }}\nB) {{ choices[1] }}\nC) {{ choices[2] }}\nD) {{ choices[3] }}\nE) {{ choices[4] }}\nÇözüm: Adım adım düşünelim." +doc_to_target: "{{ answer }}" +filter_list: + - name: "get-answer" + filter: + - function: "regex" + regex_pattern: "([A-E])(?= şıkkıdır| şıkkı)$" + - function: "take_first" + - name: "get-choice" + filter: + - function: "regex" + regex_pattern: "([A-E])" + - function: "take_first" +generation_kwargs: + until: + - "" + do_sample: false + temperature: 0.0 +num_fewshot: 0 +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: true +metadata: + version: 0.0 -- GitLab From 00f5537abc673d63937c44ccd4975ce5e925a44c Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Fri, 27 Sep 2024 00:54:26 +0500 Subject: [PATCH 109/194] add mmlu readme (#2282) --- lm_eval/tasks/mmlu/README.md | 73 ++++++++++++++++++++++++++++++++++++ 1 file changed, 73 insertions(+) create mode 100644 lm_eval/tasks/mmlu/README.md diff --git a/lm_eval/tasks/mmlu/README.md b/lm_eval/tasks/mmlu/README.md new file mode 100644 index 00000000..a3425d51 --- /dev/null +++ b/lm_eval/tasks/mmlu/README.md @@ -0,0 +1,73 @@ +# Task-name + +### Paper + +Title: `Measuring Massive Multitask Language Understanding` + +Abstract: `https://arxiv.org/abs/2009.03300` + +`The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more.` + +Homepage: `https://github.com/hendrycks/test` + +Note: The `Flan` variants are derived from [here](https://github.com/jasonwei20/flan-2), and as described in Appendix D.1 of [Scaling Instruction-Finetuned Language Models](https://arxiv.org/abs/2210.11416). + +### Citation + +``` +@article{hendryckstest2021, + title={Measuring Massive Multitask Language Understanding}, + author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt}, + journal={Proceedings of the International Conference on Learning Representations (ICLR)}, + year={2021} +} + +@article{hendrycks2021ethics, + title={Aligning AI With Shared Human Values}, + author={Dan Hendrycks and Collin Burns and Steven Basart and Andrew Critch and Jerry Li and Dawn Song and Jacob Steinhardt}, + journal={Proceedings of the International Conference on Learning Representations (ICLR)}, + year={2021} +} +``` + +### Groups, Tags, and Tasks + +#### Groups + +* `mmlu`: `Original multiple-choice MMLU benchmark` +* `mmlu_continuation`: `MMLU but with continuation prompts` +* `mmlu_generation`: `MMLU generation` + +MMLU is the original benchmark as implemented by Hendrycks et al. with the choices in context and the answer letters (e.g `A`, `B`, `C`, `D`) in the continuation. +`mmlu_continuation` is a cloze-style variant without the choices in context and the full answer choice in the continuation. +`mmlu_generation` is a generation variant, similar to the original but the LLM is asked to generate the correct answer letter. + + +#### Subgroups + +* `mmlu_stem' +* `mmlu_humanities' +* `mmlu_social_sciences' +* `mmlu_other' + +Subgroup variants are prefixed with the subgroup name, e.g. `mmlu_stem_continuation`. + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [x] Is the task an existing benchmark in the literature? + * [x] Have you referenced the original paper that introduced the task? + * [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [x] Is the "Main" variant of this task clearly denoted? +* [x] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [x] Have you noted which, if any, published evaluation setups are matched by this variant? + +# changelog +ver 1: PR #497 +switch to original implementation + +ver 2: PR #2116 +add missing newline in description. -- GitLab From 1bc6c93394d0a27f1672695e017f84b97427197e Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Fri, 27 Sep 2024 00:58:09 +0500 Subject: [PATCH 110/194] openai: better error messages; fix greedy matching (#2327) * better error message; fix greedy matching * Update lm_eval/models/openai_completions.py Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * Update lm_eval/models/openai_completions.py Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * pre-commit --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- lm_eval/models/openai_completions.py | 23 ++++++++++++++++------- 1 file changed, 16 insertions(+), 7 deletions(-) diff --git a/lm_eval/models/openai_completions.py b/lm_eval/models/openai_completions.py index 4bf2c42b..331a3f6a 100644 --- a/lm_eval/models/openai_completions.py +++ b/lm_eval/models/openai_completions.py @@ -69,11 +69,11 @@ class LocalCompletionsAPI(TemplateAPI): for choice, ctxlen in zip(out["choices"], ctxlens): assert ctxlen > 0, "Context length must be greater than 0" logprobs = sum(choice["logprobs"]["token_logprobs"][ctxlen:-1]) - tokens = choice["logprobs"]["token_logprobs"][ctxlen:-1] + tokens_logprobs = choice["logprobs"]["token_logprobs"][ctxlen:-1] top_logprobs = choice["logprobs"]["top_logprobs"][ctxlen:-1] is_greedy = True - for tok, top in zip(tokens, top_logprobs): - if tok != max(top, key=top.get): + for tok, top in zip(tokens_logprobs, top_logprobs): + if tok != max(top.values()): is_greedy = False break res.append((logprobs, is_greedy)) @@ -190,14 +190,18 @@ class OpenAICompletionsAPI(LocalCompletionsAPI): key = os.environ.get("OPENAI_API_KEY", None) if key is None: raise ValueError( - "API key not found. Please set the OPENAI_API_KEY environment variable." + "API key not found. Please set the `OPENAI_API_KEY` environment variable." ) return key def loglikelihood(self, requests, **kwargs): assert ( - self.model != "gpt-3.5-turbo" - ), "Loglikelihood is not supported for gpt-3.5-turbo" + self.model + in [ + "babbage-002", + "davinci-002", + ] + ), f"Prompt loglikelihoods are only supported by OpenAI's API for {['babbage-002', 'davinci-002']}." return super().loglikelihood(requests, **kwargs) def chat_template(self, chat_template: Union[bool, str] = False) -> Optional[str]: @@ -226,6 +230,11 @@ class OpenAIChatCompletion(LocalChatCompletion): key = os.environ.get("OPENAI_API_KEY", None) if key is None: raise ValueError( - "API key not found. Please set the OPENAI_API_KEY environment variable." + "API key not found. Please set the `OPENAI_API_KEY` environment variable." ) return key + + def loglikelihood(self, requests, **kwargs): + raise NotImplementedError( + "Loglikelihood (and therefore `multiple_choice`-type tasks) is not supported for chat completions as OpenAI does not provide prompt logprobs. See https://github.com/EleutherAI/lm-evaluation-harness/issues/942#issuecomment-1777836312 or https://github.com/EleutherAI/lm-evaluation-harness/issues/1196 for more background on this limitation." + ) -- GitLab From 5a48ca27adfbd15578638cc571240c8c1d4e505e Mon Sep 17 00:00:00 2001 From: eyuansu62 <30862458+eyuansu62@users.noreply.github.com> Date: Sat, 28 Sep 2024 22:49:32 +0800 Subject: [PATCH 111/194] fix some bugs of mmlu (#2299) * fix some bugs of mmlu * Fix end of file newline issue --------- Co-authored-by: eyuansu62 <772468951@qq.com> --- lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu.yaml | 4 +++- .../flan_cot_fewshot/_mmlu_flan_cot_fewshot_template_yaml | 7 +++---- .../generative/_mmlu_flan_generative_template_yaml | 2 +- 3 files changed, 7 insertions(+), 6 deletions(-) diff --git a/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu.yaml b/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu.yaml index 28ed66b2..c6c1c6a1 100644 --- a/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu.yaml +++ b/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu.yaml @@ -26,7 +26,9 @@ task: - metric: acc weight_by_size: True aggregate_metric_list: - - metric: acc + - aggregation: mean + metric: exact_match weight_by_size: True + filter_list: get-answer metadata: version: 2 diff --git a/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu_flan_cot_fewshot_template_yaml b/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu_flan_cot_fewshot_template_yaml index be1ede3f..cfbf222e 100644 --- a/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu_flan_cot_fewshot_template_yaml +++ b/lm_eval/tasks/mmlu/flan_cot_fewshot/_mmlu_flan_cot_fewshot_template_yaml @@ -1,12 +1,11 @@ dataset_path: hails/mmlu_no_train # a copy of `cais/mmlu` with no auxiliary_train split validation_split: validation test_split: test -fewshot_split: dev fewshot_config: sampler: first_n output_type: generate_until -doc_to_text: "Q: {{question.strip()}}\n(A) {{choices[0]}} (B) {{choices[1]}} (C) {{choices[2]}} (D) {{choices[3]}}\nA: Let's think step by step." -doc_to_target: "{{['(A)', '(B)', '(C)', '(D)'][answer]}}" +doc_to_text: "{% if choices is defined%}Q: {{question.strip()}}\n(A) {{choices[0]}} (B) {{choices[1]}} (C) {{choices[2]}} (D) {{choices[3]}}\nA: Let's think step by step.{% else %}Q: {{ question.strip() }}\nA:{% endif %}" +doc_to_target: "{{['(A)', '(B)', '(C)', '(D)'][answer] if answer is defined else target}}" filter_list: - name: "get-answer" filter: @@ -18,7 +17,7 @@ generation_kwargs: - "" do_sample: false temperature: 0.0 -num_fewshot: 0 +num_fewshot: 4 metric_list: - metric: exact_match aggregation: mean diff --git a/lm_eval/tasks/mmlu/flan_n_shot/generative/_mmlu_flan_generative_template_yaml b/lm_eval/tasks/mmlu/flan_n_shot/generative/_mmlu_flan_generative_template_yaml index 76944383..a38a0696 100644 --- a/lm_eval/tasks/mmlu/flan_n_shot/generative/_mmlu_flan_generative_template_yaml +++ b/lm_eval/tasks/mmlu/flan_n_shot/generative/_mmlu_flan_generative_template_yaml @@ -12,7 +12,7 @@ filter_list: - function: "take_first" - name: "flexible-extract" filter: - - function: !function utils.MultiChoiceRegexFilter + - function: "multi_choice_regex" group_select: 0 regex_pattern: "(\\([A-Z]\\))" ignore_case: true -- GitLab From caa7c4096ea339dada889c94a0a7230fb21b2a60 Mon Sep 17 00:00:00 2001 From: zxcvuser Date: Mon, 30 Sep 2024 16:53:21 +0200 Subject: [PATCH 112/194] Add new benchmark: Portuguese bench (#2156) * Add portuguese_bench * Add flores_pt group * Update _flores_common_yaml * Run linters and update flores and readme --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/portuguese_bench/README.md | 64 ++++++++++ .../portuguese_bench/assin_entailment.yaml | 17 +++ .../portuguese_bench/assin_paraphrase.yaml | 17 +++ .../flores_pt/_flores_common_yaml | 28 +++++ .../flores_pt/create_yamls_flores_pt.py | 114 ++++++++++++++++++ .../flores_pt/flores_ca-pt.yaml | 7 ++ .../flores_pt/flores_de-pt.yaml | 7 ++ .../flores_pt/flores_en-pt.yaml | 7 ++ .../flores_pt/flores_es-pt.yaml | 7 ++ .../flores_pt/flores_eu-pt.yaml | 7 ++ .../flores_pt/flores_fr-pt.yaml | 7 ++ .../flores_pt/flores_gl-pt.yaml | 7 ++ .../flores_pt/flores_it-pt.yaml | 7 ++ .../flores_pt/flores_pt-ca.yaml | 7 ++ .../flores_pt/flores_pt-de.yaml | 7 ++ .../flores_pt/flores_pt-en.yaml | 7 ++ .../flores_pt/flores_pt-es.yaml | 7 ++ .../flores_pt/flores_pt-eu.yaml | 7 ++ .../flores_pt/flores_pt-fr.yaml | 7 ++ .../flores_pt/flores_pt-gl.yaml | 7 ++ .../flores_pt/flores_pt-it.yaml | 7 ++ .../portuguese_bench/flores_pt/flores_pt.yaml | 24 ++++ .../portuguese_bench/portuguese_bench.yaml | 8 ++ 24 files changed, 385 insertions(+) create mode 100644 lm_eval/tasks/portuguese_bench/README.md create mode 100644 lm_eval/tasks/portuguese_bench/assin_entailment.yaml create mode 100644 lm_eval/tasks/portuguese_bench/assin_paraphrase.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/_flores_common_yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/create_yamls_flores_pt.py create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_ca-pt.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_de-pt.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_en-pt.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_es-pt.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_eu-pt.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_fr-pt.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_gl-pt.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_it-pt.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-ca.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-de.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-en.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-es.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-eu.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-fr.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-gl.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-it.yaml create mode 100644 lm_eval/tasks/portuguese_bench/flores_pt/flores_pt.yaml create mode 100644 lm_eval/tasks/portuguese_bench/portuguese_bench.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 3903db98..771f1adc 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -121,3 +121,4 @@ | [xnli_eu](xnli_eu/README.md) | Cross-lingual Natural Language Inference tasks in Basque. | Basque | | [xstorycloze](xstorycloze/README.md) | Cross-lingual narrative understanding tasks to predict story endings in multiple languages. | Russian, Simplified Chinese, Spanish, Arabic, Hindi, Indonesian, Telugu, Swahili, Basque, Burmese | | [xwinograd](xwinograd/README.md) | Cross-lingual Winograd schema tasks for coreference resolution in multiple languages. | English, French, Japanese, Portuguese, Russian, Chinese | +| [portuguese_bench](portuguese_bench/README.md) | Collection of tasks in European Portuguese encompassing various evaluation areas. | Portuguese | diff --git a/lm_eval/tasks/portuguese_bench/README.md b/lm_eval/tasks/portuguese_bench/README.md new file mode 100644 index 00000000..cc522cf7 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/README.md @@ -0,0 +1,64 @@ +# PortugueseBench + +### Paper + +PortugueseBench is a benchmark for evaluating language models in Portuguese tasks. This is, it evaluates the ability of a language model to understand and generate Portuguese text. PortugueseBench offers a combination of pre-existing, open datasets. All the details of PortugueseBench will be published in a paper soon. + +The datasets included in PortugueseBench are: + +| Task | Category | Paper title | Homepage | +|:-------------:|:-----:|:-------------:|:-----:| +| Belebele_es | Reading Comprehension | [The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://arxiv.org/abs/2308.16884) | https://huggingface.co/datasets/facebook/belebele | +| FLORES_es | Translation | [The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation](https://arxiv.org/abs/2106.03193) | https://huggingface.co/datasets/facebook/flores | +| ASSIN | Natural Language Inference + Paraphrasing | [Avaliando a similaridade semântica entre frases curtas através de uma abordagem híbrida](https://aclanthology.org/W17-6612/) | https://huggingface.co/datasets/nilc-nlp/assin | + + +### Citation +Paper for PortugueseBench coming soon. + +### Groups and Tasks + +#### Groups + +- `portuguese_bench`: All tasks included in PortugueseBench. +- `flores_pt`: All FLORES translation tasks from or to Portuguese. + +#### Tasks + +The following tasks evaluate tasks on PortugueseBench dataset using various scoring methods. + - `assin_paraphrase` + - `assin_entailment` + - `belebele_por_Latn` + - `flores_pt` + - `flores_pt-ca` + - `flores_pt-de` + - `flores_pt-en` + - `flores_pt-es` + - `flores_pt-eu` + - `flores_pt-fr` + - `flores_pt-gl` + - `flores_pt-it` + - `flores_ca-pt` + - `flores_de-pt` + - `flores_en-pt` + - `flores_es-pt` + - `flores_eu-pt` + - `flores_fr-pt` + - `flores_gl-pt` + - `flores_it-pt` + +Some of these tasks are taken from benchmarks already available in LM Evaluation Harness. These are: +- `belebele_por_Latn`: Belebele Portuguese + + +### Checklist + +* [x] Is the task an existing benchmark in the literature? + * [ ] Have you referenced the original paper that introduced the task? + * [ ] If yes, does the original paper provide a reference implementation? + * [ ] Yes, original implementation contributed by author of the benchmark + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/portuguese_bench/assin_entailment.yaml b/lm_eval/tasks/portuguese_bench/assin_entailment.yaml new file mode 100644 index 00000000..e28f37cb --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/assin_entailment.yaml @@ -0,0 +1,17 @@ +task: assin_entailment +dataset_path: nilc-nlp/assin +dataset_name: null +training_split: train +validation_split: validation +test_split: test +output_type: multiple_choice +doc_to_text: "" +doc_to_target: '{{0 if entailment_judgment == 0 else 1}}' +target_delimiter: "" +doc_to_choice: '{{[premise + ", certo? Também, " + hypothesis, premise + ", certo? Sim, " + hypothesis]}}' +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/portuguese_bench/assin_paraphrase.yaml b/lm_eval/tasks/portuguese_bench/assin_paraphrase.yaml new file mode 100644 index 00000000..41c760b1 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/assin_paraphrase.yaml @@ -0,0 +1,17 @@ +task: assin_paraphrase +dataset_path: nilc-nlp/assin +dataset_name: null +training_split: train +validation_split: validation +test_split: test +output_type: multiple_choice +doc_to_text: "" +doc_to_target: '{{0 if entailment_judgment == 0 else 1}}' +target_delimiter: "" +doc_to_choice: '{{[premise + ", certo? Não, " + hypothesis, premise + ", certo? Sim, " + hypothesis]}}' +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/_flores_common_yaml b/lm_eval/tasks/portuguese_bench/flores_pt/_flores_common_yaml new file mode 100644 index 00000000..ada4c55c --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/_flores_common_yaml @@ -0,0 +1,28 @@ +group: flores +dataset_path: facebook/flores +dataset_name: all +output_type: generate_until +#! The test split of flores is not publicly available! (See paper section 6.1) +#! We are using `dev` and `devtest` splits, but they're mapped to train/validation/test in `data/flores/flores.py`. +training_split: dev +validation_split: dev +test_split: devtest +fewshot_split: dev +target_delimiter: '' +generation_kwargs: + until: + - "\n" +metric_list: + - metric: bleu + aggregation: bleu + higher_is_better: true + - metric: ter + aggregation: ter + higher_is_better: false + - metric: chrf + aggregation: chrf + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/create_yamls_flores_pt.py b/lm_eval/tasks/portuguese_bench/flores_pt/create_yamls_flores_pt.py new file mode 100644 index 00000000..4a1dffcf --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/create_yamls_flores_pt.py @@ -0,0 +1,114 @@ +""" +Script to generate task YAMLs for the FLORES-200 dataset. +Based on `tasks/translation/utils.py`. +""" + +import argparse +import yaml +from langcodes import * +from itertools import * + +# utils +flatten = lambda l: list(itertools.chain(*l)) + +# constants +_LANGUAGES = [ +"ace_Arab", "bam_Latn", "dzo_Tibt", "hin_Deva", "khm_Khmr", "mag_Deva", "pap_Latn", "sot_Latn", "tur_Latn", +"ace_Latn", "ban_Latn", "ell_Grek", "hne_Deva", "kik_Latn", "mai_Deva", "pbt_Arab", "spa_Latn", "twi_Latn", +"acm_Arab", "bel_Cyrl", "eng_Latn", "hrv_Latn", "kin_Latn", "mal_Mlym", "pes_Arab", "srd_Latn", "tzm_Tfng", +"acq_Arab", "bem_Latn", "epo_Latn", "hun_Latn", "kir_Cyrl", "mar_Deva", "plt_Latn", "srp_Cyrl", "uig_Arab", +"aeb_Arab", "ben_Beng", "est_Latn", "hye_Armn", "kmb_Latn", "min_Arab", "pol_Latn", "ssw_Latn", "ukr_Cyrl", +"afr_Latn", "bho_Deva", "eus_Latn", "ibo_Latn", "kmr_Latn", "min_Latn", "por_Latn", "sun_Latn", "umb_Latn", +"ajp_Arab", "bjn_Arab", "ewe_Latn", "ilo_Latn", "knc_Arab", "mkd_Cyrl", "prs_Arab", "swe_Latn", "urd_Arab", +"aka_Latn", "bjn_Latn", "fao_Latn", "ind_Latn", "knc_Latn", "mlt_Latn", "quy_Latn", "swh_Latn", "uzn_Latn", +"als_Latn", "bod_Tibt", "fij_Latn", "isl_Latn", "kon_Latn", "mni_Beng", "ron_Latn", "szl_Latn", "vec_Latn", +"amh_Ethi", "bos_Latn", "fin_Latn", "ita_Latn", "kor_Hang", "mos_Latn", "run_Latn", "tam_Taml", "vie_Latn", +"apc_Arab", "bug_Latn", "fon_Latn", "jav_Latn", "lao_Laoo", "mri_Latn", "rus_Cyrl", "taq_Latn", "war_Latn", +"arb_Arab", "bul_Cyrl", "fra_Latn", "jpn_Jpan", "lij_Latn", "mya_Mymr", "sag_Latn", "taq_Tfng", "wol_Latn", +"arb_Latn", "cat_Latn", "fur_Latn", "kab_Latn", "lim_Latn", "nld_Latn", "san_Deva", "tat_Cyrl", "xho_Latn", +"ars_Arab", "ceb_Latn", "fuv_Latn", "kac_Latn", "lin_Latn", "nno_Latn", "sat_Olck", "tel_Telu", "ydd_Hebr", +"ary_Arab", "ces_Latn", "gaz_Latn", "kam_Latn", "lit_Latn", "nob_Latn", "scn_Latn", "tgk_Cyrl", "yor_Latn", +"arz_Arab", "cjk_Latn", "gla_Latn", "kan_Knda", "lmo_Latn", "npi_Deva", "shn_Mymr", "tgl_Latn", "yue_Hant", +"asm_Beng", "ckb_Arab", "gle_Latn", "kas_Arab", "ltg_Latn", "nso_Latn", "sin_Sinh", "tha_Thai", "zho_Hans", +"ast_Latn", "crh_Latn", "glg_Latn", "kas_Deva", "ltz_Latn", "nus_Latn", "slk_Latn", "tir_Ethi", "zho_Hant", +"awa_Deva", "cym_Latn", "grn_Latn", "kat_Geor", "lua_Latn", "nya_Latn", "slv_Latn", "tpi_Latn", "zsm_Latn", +"ayr_Latn", "dan_Latn", "guj_Gujr", "kaz_Cyrl", "lug_Latn", "oci_Latn", "smo_Latn", "tsn_Latn", "zul_Latn", +"azb_Arab", "deu_Latn", "hat_Latn", "kbp_Latn", "luo_Latn", "ory_Orya", "sna_Latn", "tso_Latn", +"azj_Latn", "dik_Latn", "hau_Latn", "kea_Latn", "lus_Latn", "pag_Latn", "snd_Arab", "tuk_Latn", +"bak_Cyrl", "dyu_Latn", "heb_Hebr", "khk_Cyrl", "lvs_Latn", "pan_Guru", "som_Latn", "tum_Latn" +] +LANGUAGE_PAIRS = [(a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1:]] + +LANGUAGES_OF_INTEREST = ["cat_Latn", "spa_Latn", "eng_Latn", "glg_Latn", "eus_Latn", "ita_Latn", "deu_Latn", "por_Latn", "fra_Latn"] +MAIN_LANG = "por_Latn" +LANGUAGE_PAIRS = [(a, b) for (a, b) in LANGUAGE_PAIRS if a in LANGUAGES_OF_INTEREST and b in LANGUAGES_OF_INTEREST and MAIN_LANG in (a, b)] + +# auxiliary functions + +code_to_language_name = lambda code: Language.make(language=Language.get(code)["language"]).display_name() +code_to_short_name = lambda code: Language.get(code)["language"] +jinja_var = lambda s: "{{" + s + "}}" # wrapper to avoid having to escape { } in format strings + +def doc_to_text(src: str, tgt: str) -> str: + src_name, tgt_name = map(code_to_language_name, [src, tgt]) + + return f"""\ +{src_name} sentence: {jinja_var('sentence_' + src)} +{tgt_name} sentence:""" + +def doc_to_target(tgt: str) -> str: + + return f"{jinja_var('sentence_' + tgt)}" + +# main function + +def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: + """ + Generate a YAML file for each translation direction. + """ + + err = [] + for src, tgt in LANGUAGE_PAIRS: + + # do both translation directions for each lang pair + for src, tgt in [(src, tgt), (tgt, src)]: + lang_pair_name = f"{code_to_short_name(src)}-{code_to_short_name(tgt)}" + yaml_file_name = f"flores_{lang_pair_name}.yaml" + + try: + with open( f"{output_dir}/{yaml_file_name}", "w" if overwrite else "x", encoding="utf-8") as outfile: + print(f"Creating {yaml_file_name}...") + outfile.write("# File generated by `create-yamls.py`\n") + yaml.dump( + { +# "group": "flores_pt", + "include": "_flores_common_yaml", + "task": f"flores_{lang_pair_name}", + "doc_to_text": doc_to_text(src, tgt), + "doc_to_target": doc_to_target(tgt), + }, + outfile, + sort_keys=False, + ) + + except FileExistsError: + err.append(yaml_file_name) + + if len(err) > 0: + raise FileExistsError( + "Files were not created because they already exist:" + f" {', '.join(err)}" + "\nUse flag --overwrite to overwrite them." + ) + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--overwrite", default=False, action="store_true", help="Overwrite files if they already exist") + parser.add_argument( "--output-dir", default=".", help="Directory to write yaml files to" ) + args = parser.parse_args() + + gen_lang_yamls(output_dir=args.output_dir, overwrite=args.overwrite) + +if __name__ == "__main__": + main() diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_ca-pt.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_ca-pt.yaml new file mode 100644 index 00000000..565f6267 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_ca-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-pt +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_de-pt.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_de-pt.yaml new file mode 100644 index 00000000..17e10e9c --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_de-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_de-pt +doc_to_text: 'German sentence: {{sentence_deu_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_en-pt.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_en-pt.yaml new file mode 100644 index 00000000..60668225 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_en-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_en-pt +doc_to_text: 'English sentence: {{sentence_eng_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_es-pt.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_es-pt.yaml new file mode 100644 index 00000000..b218e155 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_es-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-pt +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_eu-pt.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_eu-pt.yaml new file mode 100644 index 00000000..f230a732 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_eu-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-pt +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_fr-pt.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_fr-pt.yaml new file mode 100644 index 00000000..376900a1 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_fr-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_fr-pt +doc_to_text: 'French sentence: {{sentence_fra_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_gl-pt.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_gl-pt.yaml new file mode 100644 index 00000000..e965a347 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_gl-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-pt +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_it-pt.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_it-pt.yaml new file mode 100644 index 00000000..bb6243ad --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_it-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_it-pt +doc_to_text: 'Italian sentence: {{sentence_ita_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-ca.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-ca.yaml new file mode 100644 index 00000000..196295c9 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-ca +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-de.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-de.yaml new file mode 100644 index 00000000..85f7605d --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-de.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-de +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + German sentence:' +doc_to_target: '{{sentence_deu_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-en.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-en.yaml new file mode 100644 index 00000000..638690d9 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-en.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-en +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + English sentence:' +doc_to_target: '{{sentence_eng_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-es.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-es.yaml new file mode 100644 index 00000000..327af21d --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-es +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-eu.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-eu.yaml new file mode 100644 index 00000000..6b0169bc --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-eu +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-fr.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-fr.yaml new file mode 100644 index 00000000..f4ff52e4 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-fr.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-fr +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + French sentence:' +doc_to_target: '{{sentence_fra_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-gl.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-gl.yaml new file mode 100644 index 00000000..5371f510 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-gl +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-it.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-it.yaml new file mode 100644 index 00000000..9757b19f --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt-it.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-it +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + Italian sentence:' +doc_to_target: '{{sentence_ita_Latn}}' diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt.yaml b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt.yaml new file mode 100644 index 00000000..03495904 --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/flores_pt/flores_pt.yaml @@ -0,0 +1,24 @@ +group: flores_pt +task: + - flores_es-pt + - flores_pt-es + - flores_en-pt + - flores_pt-en + - flores_eu-pt + - flores_pt-eu + - flores_pt-it + - flores_it-pt + - flores_pt-fr + - flores_fr-pt + - flores_pt-ca + - flores_ca-pt + - flores_pt-gl + - flores_gl-pt + - flores_pt-de + - flores_de-pt +aggregate_metric_list: + - metric: bleu + aggregation: mean + weight_by_size: false +metadata: + version: 1.0 diff --git a/lm_eval/tasks/portuguese_bench/portuguese_bench.yaml b/lm_eval/tasks/portuguese_bench/portuguese_bench.yaml new file mode 100644 index 00000000..3031a6ff --- /dev/null +++ b/lm_eval/tasks/portuguese_bench/portuguese_bench.yaml @@ -0,0 +1,8 @@ +group: portuguese_bench +task: + - belebele_por_Latn + - flores_pt + - assin_paraphrase + - assin_entailment +metadata: + version: 1.0 -- GitLab From 15ffb0dafa9c869c7436ba9a3cf3067ac4c9d846 Mon Sep 17 00:00:00 2001 From: Giulio Lovisotto Date: Mon, 30 Sep 2024 17:01:26 +0200 Subject: [PATCH 113/194] Fix missing key in custom task loading. (#2304) --- lm_eval/tasks/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/tasks/__init__.py b/lm_eval/tasks/__init__.py index 6669a35b..b3968258 100644 --- a/lm_eval/tasks/__init__.py +++ b/lm_eval/tasks/__init__.py @@ -275,7 +275,7 @@ class TaskManager: task_object = config["class"]() if isinstance(task_object, ConfigurableTask): # very scuffed: set task name here. TODO: fixme? - task_object.config.task = config["task"] + task_object.config.task = task else: task_object = ConfigurableTask(config=config) -- GitLab From ea17b98e3cac7e4e80f8ac2183d1837fcd90f5fc Mon Sep 17 00:00:00 2001 From: zxcvuser Date: Thu, 3 Oct 2024 14:18:41 +0200 Subject: [PATCH 114/194] Add new benchmark: Spanish bench (#2157) * Add spanish_bench * Add flores_es group * Update _flores_common_yaml * Delete lm_eval/tasks/spanish_bench/escola.yaml * Delete escola from spanish_bench.yaml * Delete escola from README.md * pre-commit run --all-files * Updated some task groupings and readme --------- --- lm_eval/tasks/README.md | 4 +- lm_eval/tasks/spanish_bench/README.md | 82 +++++ .../flores_es/_flores_common_yaml | 28 ++ .../flores_es/create_yamls_flores_es.py | 331 ++++++++++++++++++ .../spanish_bench/flores_es/flores_ca-es.yaml | 7 + .../spanish_bench/flores_es/flores_de-es.yaml | 7 + .../spanish_bench/flores_es/flores_en-es.yaml | 7 + .../spanish_bench/flores_es/flores_es-ca.yaml | 7 + .../spanish_bench/flores_es/flores_es-de.yaml | 7 + .../spanish_bench/flores_es/flores_es-en.yaml | 7 + .../spanish_bench/flores_es/flores_es-eu.yaml | 7 + .../spanish_bench/flores_es/flores_es-fr.yaml | 7 + .../spanish_bench/flores_es/flores_es-gl.yaml | 7 + .../spanish_bench/flores_es/flores_es-it.yaml | 7 + .../spanish_bench/flores_es/flores_es-pt.yaml | 7 + .../spanish_bench/flores_es/flores_es.yaml | 24 ++ .../spanish_bench/flores_es/flores_eu-es.yaml | 7 + .../spanish_bench/flores_es/flores_fr-es.yaml | 7 + .../spanish_bench/flores_es/flores_gl-es.yaml | 7 + .../spanish_bench/flores_es/flores_it-es.yaml | 7 + .../spanish_bench/flores_es/flores_pt-es.yaml | 7 + .../mgsm_direct_es_spanish_bench.yaml | 9 + .../spanish_bench/mgsm_direct_es_v2.yaml | 9 + lm_eval/tasks/spanish_bench/paws_es.yaml | 20 ++ .../spanish_bench/paws_es_spanish_bench.yaml | 18 + .../phrases_es/_phrases_es_common.yaml | 24 ++ .../phrases_es/phrases_es-va.yaml | 7 + .../phrases_es/phrases_va-es.yaml | 7 + .../tasks/spanish_bench/spanish_bench.yaml | 14 + lm_eval/tasks/spanish_bench/utils.py | 100 ++++++ lm_eval/tasks/spanish_bench/wnli_es.yaml | 14 + lm_eval/tasks/spanish_bench/xlsum_es.yaml | 22 ++ lm_eval/tasks/spanish_bench/xnli_es.yaml | 19 + .../spanish_bench/xnli_es_spanish_bench.yaml | 19 + lm_eval/tasks/spanish_bench/xquad_es.yaml | 23 ++ 35 files changed, 885 insertions(+), 1 deletion(-) create mode 100644 lm_eval/tasks/spanish_bench/README.md create mode 100644 lm_eval/tasks/spanish_bench/flores_es/_flores_common_yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/create_yamls_flores_es.py create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_ca-es.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_de-es.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_en-es.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_es-ca.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_es-de.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_es-en.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_es-eu.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_es-fr.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_es-gl.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_es-it.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_es-pt.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_es.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_eu-es.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_fr-es.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_gl-es.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_it-es.yaml create mode 100644 lm_eval/tasks/spanish_bench/flores_es/flores_pt-es.yaml create mode 100644 lm_eval/tasks/spanish_bench/mgsm_direct_es_spanish_bench.yaml create mode 100644 lm_eval/tasks/spanish_bench/mgsm_direct_es_v2.yaml create mode 100644 lm_eval/tasks/spanish_bench/paws_es.yaml create mode 100644 lm_eval/tasks/spanish_bench/paws_es_spanish_bench.yaml create mode 100644 lm_eval/tasks/spanish_bench/phrases_es/_phrases_es_common.yaml create mode 100644 lm_eval/tasks/spanish_bench/phrases_es/phrases_es-va.yaml create mode 100644 lm_eval/tasks/spanish_bench/phrases_es/phrases_va-es.yaml create mode 100644 lm_eval/tasks/spanish_bench/spanish_bench.yaml create mode 100644 lm_eval/tasks/spanish_bench/utils.py create mode 100644 lm_eval/tasks/spanish_bench/wnli_es.yaml create mode 100644 lm_eval/tasks/spanish_bench/xlsum_es.yaml create mode 100644 lm_eval/tasks/spanish_bench/xnli_es.yaml create mode 100644 lm_eval/tasks/spanish_bench/xnli_es_spanish_bench.yaml create mode 100644 lm_eval/tasks/spanish_bench/xquad_es.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 771f1adc..075c7d50 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -86,6 +86,7 @@ | [pile_10k](pile_10k/README.md) | The first 10K elements of The Pile, useful for debugging models trained on it. | English | | [piqa](piqa/README.md) | Physical Interaction Question Answering tasks to test physical commonsense reasoning. | English | | [polemo2](polemo2/README.md) | Sentiment analysis and emotion detection tasks based on Polish language data. | Polish | +| [portuguese_bench](portuguese_bench/README.md) | Collection of tasks in European Portuguese encompassing various evaluation areas. | Portuguese | | [prost](prost/README.md) | Tasks requiring understanding of professional standards and ethics in various domains. | English | | [pubmedqa](pubmedqa/README.md) | Question answering tasks based on PubMed research articles for biomedical understanding. | English | | [qa4mre](qa4mre/README.md) | Question Answering for Machine Reading Evaluation, assessing comprehension and reasoning. | English | @@ -95,6 +96,7 @@ | [sciq](sciq/README.md) | Science Question Answering tasks to assess understanding of scientific concepts. | English | | [scrolls](scrolls/README.md) | Tasks that involve long-form reading comprehension across various domains. | English | | [siqa](siqa/README.md) | Social Interaction Question Answering to evaluate common sense and social reasoning. | English | +| [spanish_bench](spanish_bench/README.md) | Collection of tasks in Spanish encompassing various evaluation areas. | Spanish | | [squad_completion](squad_completion/README.md) | A variant of the SQuAD question answering task designed for zero-shot evaluation of small LMs. | English | | [squadv2](squadv2/README.md) | Stanford Question Answering Dataset version 2, a reading comprehension benchmark. | English | | [storycloze](storycloze/README.md) | Tasks to predict story endings, focusing on narrative logic and coherence. | English | @@ -121,4 +123,4 @@ | [xnli_eu](xnli_eu/README.md) | Cross-lingual Natural Language Inference tasks in Basque. | Basque | | [xstorycloze](xstorycloze/README.md) | Cross-lingual narrative understanding tasks to predict story endings in multiple languages. | Russian, Simplified Chinese, Spanish, Arabic, Hindi, Indonesian, Telugu, Swahili, Basque, Burmese | | [xwinograd](xwinograd/README.md) | Cross-lingual Winograd schema tasks for coreference resolution in multiple languages. | English, French, Japanese, Portuguese, Russian, Chinese | -| [portuguese_bench](portuguese_bench/README.md) | Collection of tasks in European Portuguese encompassing various evaluation areas. | Portuguese | + diff --git a/lm_eval/tasks/spanish_bench/README.md b/lm_eval/tasks/spanish_bench/README.md new file mode 100644 index 00000000..ef55d00e --- /dev/null +++ b/lm_eval/tasks/spanish_bench/README.md @@ -0,0 +1,82 @@ +# SpanishBench + +### Paper + +SpanishBench is a benchmark for evaluating language models in Spanish tasks. This is, it evaluates the ability of a language model to understand and generate Spanish text. SpanishBench offers a combination of pre-existing, open datasets. All the details of SpanishBench will be published in a paper soon. + +The datasets included in SpanishBench are: + +| Task | Category | Paper title | Homepage | +|:-------------:|:-----:|:-------------:|:-----:| +| Belebele_es | Reading Comprehension | [The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://arxiv.org/abs/2308.16884) | https://huggingface.co/datasets/facebook/belebele | +| FLORES_es | Translation | [The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation](https://arxiv.org/abs/2106.03193) | https://huggingface.co/datasets/facebook/flores | +| MGSM_es | Math | [Language Models are Multilingual Chain-of-Thought Reasoners](https://arxiv.org/abs/2210.03057) | https://huggingface.co/datasets/juletxara/mgsm | +| PAWS-X_es | Paraphrasing | [PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification](https://aclanthology.org/D19-1382/) | https://huggingface.co/datasets/google-research-datasets/paws-x | +| WNLI-es | Natural Language Inference | No paper. | https://huggingface.co/datasets/PlanTL-GOB-ES/wnli-es | +| XL-Sum_es | Summarization | [XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages](https://aclanthology.org/2021.findings-acl.413/) | https://huggingface.co/datasets/csebuetnlp/xlsum | +| XNLI_es | Natural Language Inference | [XNLI: Evaluating Cross-lingual Sentence Representations](https://aclanthology.org/D18-1269/) | https://huggingface.co/datasets/facebook/xnli | +| XQuAD_es | Question Answering | [On the Cross-lingual Transferability of Monolingual Representations](https://aclanthology.org/2020.acl-main.421/) | https://huggingface.co/datasets/google/xquad | +| XStoryCloze_es | Commonsense Reasoning | [Few-shot Learning with Multilingual Generative Language Models](https://aclanthology.org/2022.emnlp-main.616/) | https://huggingface.co/datasets/juletxara/xstory_cloze | + + +### Citation +Paper for SpanishBench coming soon. + +### Groups and Tasks + +#### Groups + +- `spanish_bench`: All tasks included in SpanishBench. +- `flores_es`: All FLORES translation tasks from or to Spanish. + +#### Tags +- `phrases_es`: Two Phrases_va tasks for language adaptation between Spanish and Valencian. + +#### Tasks + +The following tasks evaluate tasks on SpanishBench dataset using various scoring methods. + - `belebele_spa_Latn` + - `flores_es` + - `flores_es-ca` + - `flores_es-de` + - `flores_es-en` + - `flores_es-eu` + - `flores_es-fr` + - `flores_es-gl` + - `flores_es-it` + - `flores_es-pt` + - `flores_ca-es` + - `flores_de-es` + - `flores_en-es` + - `flores_eu-es` + - `flores_fr-es` + - `flores_gl-es` + - `flores_it-es` + - `flores_pt-es` + - `mgsm_direct_es_v2` (`v2` is due to an existing open issue in the original task) + - `paws_es` + - `phrases_es` + - `wnli_es` + - `xlsum_es` + - `xnli_es` + - `xquad_es` + - `xstorycloze_es` + +Some of these tasks are taken from benchmarks already available in LM Evaluation Harness. These are: +- `belebele_spa_Latn`: Belebele Spanish +- `mgsm_direct_es`: MGSM Spanish (We fix an existing open issue in the original task) +- `paws_es`: PAWS-X Spanish +- `xnli_es`: XNLI Spanish +- `xstorycloze_es`: XStoryCloze Spanish + +### Checklist + +* [x] Is the task an existing benchmark in the literature? + * [ ] Have you referenced the original paper that introduced the task? + * [ ] If yes, does the original paper provide a reference implementation? + * [ ] Yes, original implementation contributed by author of the benchmark + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/spanish_bench/flores_es/_flores_common_yaml b/lm_eval/tasks/spanish_bench/flores_es/_flores_common_yaml new file mode 100644 index 00000000..ada4c55c --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/_flores_common_yaml @@ -0,0 +1,28 @@ +group: flores +dataset_path: facebook/flores +dataset_name: all +output_type: generate_until +#! The test split of flores is not publicly available! (See paper section 6.1) +#! We are using `dev` and `devtest` splits, but they're mapped to train/validation/test in `data/flores/flores.py`. +training_split: dev +validation_split: dev +test_split: devtest +fewshot_split: dev +target_delimiter: '' +generation_kwargs: + until: + - "\n" +metric_list: + - metric: bleu + aggregation: bleu + higher_is_better: true + - metric: ter + aggregation: ter + higher_is_better: false + - metric: chrf + aggregation: chrf + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/spanish_bench/flores_es/create_yamls_flores_es.py b/lm_eval/tasks/spanish_bench/flores_es/create_yamls_flores_es.py new file mode 100644 index 00000000..59571e8d --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/create_yamls_flores_es.py @@ -0,0 +1,331 @@ +""" +Script to generate task YAMLs for the FLORES-200 dataset. +Based on `tasks/translation/utils.py`. +""" + +import argparse +from itertools import * + +import yaml +from langcodes import * + + +# utils +flatten = lambda l: list(itertools.chain(*l)) + +# constants +_LANGUAGES = [ + "ace_Arab", + "bam_Latn", + "dzo_Tibt", + "hin_Deva", + "khm_Khmr", + "mag_Deva", + "pap_Latn", + "sot_Latn", + "tur_Latn", + "ace_Latn", + "ban_Latn", + "ell_Grek", + "hne_Deva", + "kik_Latn", + "mai_Deva", + "pbt_Arab", + "spa_Latn", + "twi_Latn", + "acm_Arab", + "bel_Cyrl", + "eng_Latn", + "hrv_Latn", + "kin_Latn", + "mal_Mlym", + "pes_Arab", + "srd_Latn", + "tzm_Tfng", + "acq_Arab", + "bem_Latn", + "epo_Latn", + "hun_Latn", + "kir_Cyrl", + "mar_Deva", + "plt_Latn", + "srp_Cyrl", + "uig_Arab", + "aeb_Arab", + "ben_Beng", + "est_Latn", + "hye_Armn", + "kmb_Latn", + "min_Arab", + "pol_Latn", + "ssw_Latn", + "ukr_Cyrl", + "afr_Latn", + "bho_Deva", + "eus_Latn", + "ibo_Latn", + "kmr_Latn", + "min_Latn", + "por_Latn", + "sun_Latn", + "umb_Latn", + "ajp_Arab", + "bjn_Arab", + "ewe_Latn", + "ilo_Latn", + "knc_Arab", + "mkd_Cyrl", + "prs_Arab", + "swe_Latn", + "urd_Arab", + "aka_Latn", + "bjn_Latn", + "fao_Latn", + "ind_Latn", + "knc_Latn", + "mlt_Latn", + "quy_Latn", + "swh_Latn", + "uzn_Latn", + "als_Latn", + "bod_Tibt", + "fij_Latn", + "isl_Latn", + "kon_Latn", + "mni_Beng", + "ron_Latn", + "szl_Latn", + "vec_Latn", + "amh_Ethi", + "bos_Latn", + "fin_Latn", + "ita_Latn", + "kor_Hang", + "mos_Latn", + "run_Latn", + "tam_Taml", + "vie_Latn", + "apc_Arab", + "bug_Latn", + "fon_Latn", + "jav_Latn", + "lao_Laoo", + "mri_Latn", + "rus_Cyrl", + "taq_Latn", + "war_Latn", + "arb_Arab", + "bul_Cyrl", + "fra_Latn", + "jpn_Jpan", + "lij_Latn", + "mya_Mymr", + "sag_Latn", + "taq_Tfng", + "wol_Latn", + "arb_Latn", + "cat_Latn", + "fur_Latn", + "kab_Latn", + "lim_Latn", + "nld_Latn", + "san_Deva", + "tat_Cyrl", + "xho_Latn", + "ars_Arab", + "ceb_Latn", + "fuv_Latn", + "kac_Latn", + "lin_Latn", + "nno_Latn", + "sat_Olck", + "tel_Telu", + "ydd_Hebr", + "ary_Arab", + "ces_Latn", + "gaz_Latn", + "kam_Latn", + "lit_Latn", + "nob_Latn", + "scn_Latn", + "tgk_Cyrl", + "yor_Latn", + "arz_Arab", + "cjk_Latn", + "gla_Latn", + "kan_Knda", + "lmo_Latn", + "npi_Deva", + "shn_Mymr", + "tgl_Latn", + "yue_Hant", + "asm_Beng", + "ckb_Arab", + "gle_Latn", + "kas_Arab", + "ltg_Latn", + "nso_Latn", + "sin_Sinh", + "tha_Thai", + "zho_Hans", + "ast_Latn", + "crh_Latn", + "glg_Latn", + "kas_Deva", + "ltz_Latn", + "nus_Latn", + "slk_Latn", + "tir_Ethi", + "zho_Hant", + "awa_Deva", + "cym_Latn", + "grn_Latn", + "kat_Geor", + "lua_Latn", + "nya_Latn", + "slv_Latn", + "tpi_Latn", + "zsm_Latn", + "ayr_Latn", + "dan_Latn", + "guj_Gujr", + "kaz_Cyrl", + "lug_Latn", + "oci_Latn", + "smo_Latn", + "tsn_Latn", + "zul_Latn", + "azb_Arab", + "deu_Latn", + "hat_Latn", + "kbp_Latn", + "luo_Latn", + "ory_Orya", + "sna_Latn", + "tso_Latn", + "azj_Latn", + "dik_Latn", + "hau_Latn", + "kea_Latn", + "lus_Latn", + "pag_Latn", + "snd_Arab", + "tuk_Latn", + "bak_Cyrl", + "dyu_Latn", + "heb_Hebr", + "khk_Cyrl", + "lvs_Latn", + "pan_Guru", + "som_Latn", + "tum_Latn", +] +LANGUAGE_PAIRS = [ + (a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1 :] +] + +LANGUAGES_OF_INTEREST = [ + "cat_Latn", + "spa_Latn", + "eng_Latn", + "glg_Latn", + "eus_Latn", + "ita_Latn", + "deu_Latn", + "por_Latn", + "fra_Latn", +] +MAIN_LANG = "spa_Latn" +LANGUAGE_PAIRS = [ + (a, b) + for (a, b) in LANGUAGE_PAIRS + if a in LANGUAGES_OF_INTEREST and b in LANGUAGES_OF_INTEREST and MAIN_LANG in (a, b) +] + +# auxiliary functions + +code_to_language_name = lambda code: Language.make( + language=Language.get(code)["language"] +).display_name() +code_to_short_name = lambda code: Language.get(code)["language"] +jinja_var = ( + lambda s: "{{" + s + "}}" +) # wrapper to avoid having to escape { } in format strings + + +def doc_to_text(src: str, tgt: str) -> str: + src_name, tgt_name = map(code_to_language_name, [src, tgt]) + + return f"""\ +{src_name} sentence: {jinja_var('sentence_' + src)} +{tgt_name} sentence:""" + + +def doc_to_target(tgt: str) -> str: + return f"{jinja_var('sentence_' + tgt)}" + + +# main function + + +def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: + """ + Generate a YAML file for each translation direction. + """ + + err = [] + for src, tgt in LANGUAGE_PAIRS: + # do both translation directions for each lang pair + for src, tgt in [(src, tgt), (tgt, src)]: + lang_pair_name = f"{code_to_short_name(src)}-{code_to_short_name(tgt)}" + yaml_file_name = f"flores_{lang_pair_name}.yaml" + + try: + with open( + f"{output_dir}/{yaml_file_name}", + "w" if overwrite else "x", + encoding="utf-8", + ) as outfile: + print(f"Creating {yaml_file_name}...") + outfile.write("# File generated by `create-yamls.py`\n") + yaml.dump( + { + # "group": "flores_es", + "include": "_flores_common_yaml", + "task": f"flores_{lang_pair_name}", + "doc_to_text": doc_to_text(src, tgt), + "doc_to_target": doc_to_target(tgt), + }, + outfile, + sort_keys=False, + ) + + except FileExistsError: + err.append(yaml_file_name) + + if len(err) > 0: + raise FileExistsError( + "Files were not created because they already exist:" + f" {', '.join(err)}" + "\nUse flag --overwrite to overwrite them." + ) + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument( + "--overwrite", + default=False, + action="store_true", + help="Overwrite files if they already exist", + ) + parser.add_argument( + "--output-dir", default=".", help="Directory to write yaml files to" + ) + args = parser.parse_args() + + gen_lang_yamls(output_dir=args.output_dir, overwrite=args.overwrite) + + +if __name__ == "__main__": + main() diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_ca-es.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_ca-es.yaml new file mode 100644 index 00000000..9a6aa442 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_ca-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-es +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_de-es.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_de-es.yaml new file mode 100644 index 00000000..9b4c18e7 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_de-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_de-es +doc_to_text: 'German sentence: {{sentence_deu_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_en-es.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_en-es.yaml new file mode 100644 index 00000000..f10872eb --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_en-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_en-es +doc_to_text: 'English sentence: {{sentence_eng_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_es-ca.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_es-ca.yaml new file mode 100644 index 00000000..e35b7152 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_es-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-ca +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_es-de.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_es-de.yaml new file mode 100644 index 00000000..c86e9758 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_es-de.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-de +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + German sentence:' +doc_to_target: '{{sentence_deu_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_es-en.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_es-en.yaml new file mode 100644 index 00000000..d16d9706 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_es-en.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-en +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + English sentence:' +doc_to_target: '{{sentence_eng_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_es-eu.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_es-eu.yaml new file mode 100644 index 00000000..576bb0e2 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_es-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-eu +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_es-fr.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_es-fr.yaml new file mode 100644 index 00000000..ff625654 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_es-fr.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-fr +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + French sentence:' +doc_to_target: '{{sentence_fra_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_es-gl.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_es-gl.yaml new file mode 100644 index 00000000..dd3c6a9e --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_es-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-gl +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_es-it.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_es-it.yaml new file mode 100644 index 00000000..9e3960a2 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_es-it.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-it +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + Italian sentence:' +doc_to_target: '{{sentence_ita_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_es-pt.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_es-pt.yaml new file mode 100644 index 00000000..b218e155 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_es-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-pt +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_es.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_es.yaml new file mode 100644 index 00000000..7d5c7e54 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_es.yaml @@ -0,0 +1,24 @@ +group: flores_es +task: + - flores_es-en + - flores_en-es + - flores_es-eu + - flores_eu-es + - flores_es-pt + - flores_pt-es + - flores_es-it + - flores_it-es + - flores_es-fr + - flores_fr-es + - flores_es-ca + - flores_ca-es + - flores_es-gl + - flores_gl-es + - flores_es-de + - flores_de-es +aggregate_metric_list: + - metric: bleu + aggregation: mean + weight_by_size: false +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_eu-es.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_eu-es.yaml new file mode 100644 index 00000000..efb5200d --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_eu-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-es +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_fr-es.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_fr-es.yaml new file mode 100644 index 00000000..20b44724 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_fr-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_fr-es +doc_to_text: 'French sentence: {{sentence_fra_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_gl-es.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_gl-es.yaml new file mode 100644 index 00000000..c00acf3f --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_gl-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-es +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_it-es.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_it-es.yaml new file mode 100644 index 00000000..3e4fe0d7 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_it-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_it-es +doc_to_text: 'Italian sentence: {{sentence_ita_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/flores_es/flores_pt-es.yaml b/lm_eval/tasks/spanish_bench/flores_es/flores_pt-es.yaml new file mode 100644 index 00000000..327af21d --- /dev/null +++ b/lm_eval/tasks/spanish_bench/flores_es/flores_pt-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-es +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/spanish_bench/mgsm_direct_es_spanish_bench.yaml b/lm_eval/tasks/spanish_bench/mgsm_direct_es_spanish_bench.yaml new file mode 100644 index 00000000..856ea498 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/mgsm_direct_es_spanish_bench.yaml @@ -0,0 +1,9 @@ +include: ../mgsm/direct/mgsm_direct_es.yaml +doc_to_target: '{{answer_number|string}}' +doc_to_text: '{% if answer is not none %}{{question+"\nRespuesta: "}}{% else %}{{"Pregunta: "+question+"\nRespuesta: "}}{% endif %}' +generation_kwargs: + until: + - "\n\n" + - "\n" + +task: mgsm_direct_es_spanish_bench diff --git a/lm_eval/tasks/spanish_bench/mgsm_direct_es_v2.yaml b/lm_eval/tasks/spanish_bench/mgsm_direct_es_v2.yaml new file mode 100644 index 00000000..ed5a4a73 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/mgsm_direct_es_v2.yaml @@ -0,0 +1,9 @@ +include: ../mgsm/direct/mgsm_direct_es.yaml +doc_to_target: '{{answer_number|string}}' +doc_to_text: '{% if answer is not none %}{{question+"\nRespuesta: "}}{% else %}{{"Pregunta: "+question+"\nRespuesta: "}}{% endif %}' +generation_kwargs: + until: + - "\n\n" + - "\n" + +task: mgsm_direct_es_v2 diff --git a/lm_eval/tasks/spanish_bench/paws_es.yaml b/lm_eval/tasks/spanish_bench/paws_es.yaml new file mode 100644 index 00000000..400e9786 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/paws_es.yaml @@ -0,0 +1,20 @@ +group: + - pawsx +task: paws_es +dataset_path: paws-x +dataset_name: es +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: test +process_docs: !function utils.process_docs_paraphrases +doc_to_text: '' +doc_to_target: label +doc_to_choice: '{{[sentence1+", ¿verdad? No, "+sentence2, sentence1+", ¿verdad? Sí, "+sentence2]}}' +target_delimiter: '' +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/paws_es_spanish_bench.yaml b/lm_eval/tasks/spanish_bench/paws_es_spanish_bench.yaml new file mode 100644 index 00000000..ba764273 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/paws_es_spanish_bench.yaml @@ -0,0 +1,18 @@ +task: paws_es_spanish_bench +dataset_path: paws-x +dataset_name: es +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: test +process_docs: !function utils.process_docs_paraphrases +doc_to_text: '' +doc_to_target: label +doc_to_choice: '{{[sentence1+", ¿verdad? No, "+sentence2, sentence1+", ¿verdad? Sí, "+sentence2]}}' +target_delimiter: '' +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/phrases_es/_phrases_es_common.yaml b/lm_eval/tasks/spanish_bench/phrases_es/_phrases_es_common.yaml new file mode 100644 index 00000000..4aacaa4c --- /dev/null +++ b/lm_eval/tasks/spanish_bench/phrases_es/_phrases_es_common.yaml @@ -0,0 +1,24 @@ +tag: phrases_es +dataset_path: gplsi/ES-VA_translation_test +output_type: generate_until +training_split: null +validation_split: null +test_split: test +fewshot_split: test +num_fewshot: 5 +target_delimiter: ' ' +generation_kwargs: + until: + - "\n" +metric_list: + - metric: bleu + aggregation: bleu + higher_is_better: true + - metric: ter + aggregation: ter + higher_is_better: false + - metric: chrf + aggregation: chrf + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/phrases_es/phrases_es-va.yaml b/lm_eval/tasks/spanish_bench/phrases_es/phrases_es-va.yaml new file mode 100644 index 00000000..546f914d --- /dev/null +++ b/lm_eval/tasks/spanish_bench/phrases_es/phrases_es-va.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _phrases_es_common.yaml +task: phrases_es-va +doc_to_text: 'Oració en espanyol: {{es}} + + Oració en valencià:' +doc_to_target: '{{va}}' diff --git a/lm_eval/tasks/spanish_bench/phrases_es/phrases_va-es.yaml b/lm_eval/tasks/spanish_bench/phrases_es/phrases_va-es.yaml new file mode 100644 index 00000000..b0028666 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/phrases_es/phrases_va-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _phrases_es_common.yaml +task: phrases_va-es +doc_to_text: 'Oració en valencià: {{va}} + + Oració en espanyol:' +doc_to_target: '{{es}}' diff --git a/lm_eval/tasks/spanish_bench/spanish_bench.yaml b/lm_eval/tasks/spanish_bench/spanish_bench.yaml new file mode 100644 index 00000000..8ddef58c --- /dev/null +++ b/lm_eval/tasks/spanish_bench/spanish_bench.yaml @@ -0,0 +1,14 @@ +group: spanish_bench +task: + - belebele_spa_Latn + - wnli_es + - xnli_es_spanish_bench + - xstorycloze_es + - xquad_es + - xlsum_es + - paws_es_spanish_bench + - mgsm_direct_es_spanish_bench + - flores_es + - phrases_es +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/utils.py b/lm_eval/tasks/spanish_bench/utils.py new file mode 100644 index 00000000..13793285 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/utils.py @@ -0,0 +1,100 @@ +import re +from itertools import product + +import evaluate +import transformers.data.metrics.squad_metrics as squad_metrics + +from lm_eval.utils import general_detokenize + + +def lowercase_first_letter(text): + return text[0].lower() + text[1:] + + +def process_doc_nli(dataset): + def process_fn(doc): + # Detokenize(remove extra whitespaces) + doc["premise"] = general_detokenize(doc["premise"]).strip() + doc["hypothesis"] = general_detokenize(doc["hypothesis"]).strip() + # Remove last punctuation mark in the premise + doc["premise"] = ( + doc["premise"][:-1] + if doc["premise"].endswith((".", ",", "!", "?")) + else doc["premise"] + ) + # Lowercase the first letter in the hypothesis + doc["hypothesis"] = lowercase_first_letter(doc["hypothesis"]) + # Ensure that the hypothesis ends with a dot + doc["hypothesis"] = ( + (doc["hypothesis"] + ".") + if not doc["hypothesis"].endswith(".") + else doc["hypothesis"] + ) + return doc + + return dataset.map(process_fn) + + +def process_results_qa(doc, results): + preds = results[0] + reference = doc["answers"]["text"][0] + # import code; code.interact(local=dict(globals(), **locals())) + f1_sum = squad_metrics.compute_f1(reference, preds) + exact_match = squad_metrics.compute_exact(reference, preds) + return {"f1": f1_sum, "exact_match": exact_match} + + +def process_xlsum(dataset): + def _process_doc(doc): + # Remove double spaces + doc["text"] = re.sub(r" +", " ", doc["text"]) + doc["summary"] = re.sub(r" +", " ", doc["summary"]) + return doc + + return dataset.map(_process_doc) + + +def process_docs_paraphrases(dataset): + empty_docs = [] + + def _process_doc(doc): + if doc["sentence1"] not in [None, ""] and doc["sentence2"] not in [None, ""]: + doc["sentence1"] = general_detokenize(doc["sentence1"]).strip() + doc["sentence2"] = general_detokenize(doc["sentence2"]).strip() + # Remove final punctuation mark in the first sentence + if doc["sentence1"].endswith((".", ",", ";")): + doc["sentence1"] = doc["sentence1"][:-1] + # Start the second sentence in lowercase (to be used after "Yes, ...") + doc["sentence2"] = lowercase_first_letter(doc["sentence2"]) + return doc + else: + empty_docs.append(doc) + return doc + + if empty_docs != []: + len_empty_docs = len(empty_docs) + print( + f"Found {len_empty_docs} empty documents out of the {len(dataset)} total docs in the dataset: {empty_docs}" + ) + return dataset.filter( + lambda doc: doc["sentence1"] not in [None, ""] + and doc["sentence2"] not in [None, ""] + ).map(_process_doc) + + +def rouge1(items): + """ + # passthrough for efficiency + """ + return items + + +def rouge1_agg(items): + """ + Higher is better + """ + refs = list(zip(*items))[0] + preds = list(zip(*items))[1] + rouge_scorer = evaluate.load("rouge") + # import code; code.interact(local=dict(globals(), **locals())) + return rouge_scorer.compute(predictions=preds, references=refs)["rouge1"] diff --git a/lm_eval/tasks/spanish_bench/wnli_es.yaml b/lm_eval/tasks/spanish_bench/wnli_es.yaml new file mode 100644 index 00000000..7e9c72da --- /dev/null +++ b/lm_eval/tasks/spanish_bench/wnli_es.yaml @@ -0,0 +1,14 @@ +task: wnli_es +dataset_path: PlanTL-GOB-ES/wnli-es +dataset_name: null +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: null +doc_to_text: "{{sentence1}}\nPregunta: {{sentence2}} ¿Verdadero o Falso?\nRespuesta:" +doc_to_target: label +doc_to_choice: ["Falso", "Verdadero"] +metric_list: + - metric: acc +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/xlsum_es.yaml b/lm_eval/tasks/spanish_bench/xlsum_es.yaml new file mode 100644 index 00000000..c9a0354e --- /dev/null +++ b/lm_eval/tasks/spanish_bench/xlsum_es.yaml @@ -0,0 +1,22 @@ +task: xlsum_es +dataset_path: csebuetnlp/xlsum +dataset_name: spanish +doc_to_text: 'Texto: {{text}} + + Resumen:' +doc_to_target: '{{summary}}' +output_type: generate_until +test_split: test +training_split: train +validation_split: validation +fewshot_split: train +process_docs: !function utils.process_xlsum +metric_list: + - metric: bleu + aggregation: bleu + higher_is_better: true + - metric: !function utils.rouge1 + aggregation: !function utils.rouge1_agg + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/xnli_es.yaml b/lm_eval/tasks/spanish_bench/xnli_es.yaml new file mode 100644 index 00000000..e30da630 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/xnli_es.yaml @@ -0,0 +1,19 @@ +# Task configuration derived from Eleuther AI's implementation as of March 22, 2024, supplemented with an additional preprocessing function +task: xnli_es +dataset_path: xnli +dataset_name: es +output_type: multiple_choice +doc_to_choice: '{{[premise+", ¿correcto? Sí, "+hypothesis,premise+", ¿correcto? Así + que, "+hypothesis,premise+", ¿correcto? No, "+hypothesis]}}' +doc_to_text: '' +target_delimiter: '' +process_docs: !function utils.process_doc_nli +training_split: null +validation_split: validation +doc_to_target: label +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/xnli_es_spanish_bench.yaml b/lm_eval/tasks/spanish_bench/xnli_es_spanish_bench.yaml new file mode 100644 index 00000000..beb898bd --- /dev/null +++ b/lm_eval/tasks/spanish_bench/xnli_es_spanish_bench.yaml @@ -0,0 +1,19 @@ +# Task configuration derived from Eleuther AI's implementation as of March 22, 2024, supplemented with an additional preprocessing function +task: xnli_es_spanish_bench +dataset_path: xnli +dataset_name: es +output_type: multiple_choice +doc_to_choice: '{{[premise+", ¿correcto? Sí, "+hypothesis,premise+", ¿correcto? Así + que, "+hypothesis,premise+", ¿correcto? No, "+hypothesis]}}' +doc_to_text: '' +target_delimiter: '' +process_docs: !function utils.process_doc_nli +training_split: null +validation_split: validation +doc_to_target: label +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/xquad_es.yaml b/lm_eval/tasks/spanish_bench/xquad_es.yaml new file mode 100644 index 00000000..10819b69 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/xquad_es.yaml @@ -0,0 +1,23 @@ +task: xquad_es +dataset_path: xquad +dataset_name: xquad.es +output_type: generate_until +doc_to_text: "Contexto: {{context}}\n\nPregunta: {{question}}\n\nRespuesta:" +doc_to_target: '{{answers["text"][0]}}' +validation_split: validation +target_delimiter: ' ' +process_results: !function utils.process_results_qa +generation_kwargs: + until: + - "\n" + do_sample: false + temperature: 0.0 +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + - metric: f1 + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 -- GitLab From 0e76386206771143c25b98de977a47cf6055de66 Mon Sep 17 00:00:00 2001 From: zxcvuser Date: Thu, 3 Oct 2024 14:27:19 +0200 Subject: [PATCH 115/194] Add new benchmark: Galician bench (#2155) * Add galician_bench * Update xnli_gl path * Add flores_gl group * Update _flores_common_yaml * Updated some task groupings and readme --------- --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/galician_bench/README.md | 80 +++++ .../galician_bench/belebele_glg_Latn.yaml | 7 + .../flores_gl/_flores_common_yaml | 28 ++ .../flores_gl/create_yamls_flores_gl.py | 115 +++++++ .../flores_gl/flores_ca-gl.yaml | 7 + .../flores_gl/flores_de-gl.yaml | 7 + .../flores_gl/flores_en-gl.yaml | 7 + .../flores_gl/flores_es-gl.yaml | 7 + .../flores_gl/flores_eu-gl.yaml | 7 + .../flores_gl/flores_fr-gl.yaml | 7 + .../flores_gl/flores_gl-ca.yaml | 7 + .../flores_gl/flores_gl-de.yaml | 7 + .../flores_gl/flores_gl-en.yaml | 7 + .../flores_gl/flores_gl-es.yaml | 7 + .../flores_gl/flores_gl-eu.yaml | 7 + .../flores_gl/flores_gl-fr.yaml | 7 + .../flores_gl/flores_gl-it.yaml | 7 + .../flores_gl/flores_gl-pt.yaml | 7 + .../galician_bench/flores_gl/flores_gl.yaml | 24 ++ .../flores_gl/flores_it-gl.yaml | 7 + .../flores_gl/flores_pt-gl.yaml | 7 + lm_eval/tasks/galician_bench/galcola.yaml | 16 + .../tasks/galician_bench/galician_bench.yaml | 15 + .../tasks/galician_bench/mgsm_direct_gl.yaml | 25 ++ .../tasks/galician_bench/openbookqa_gl.yaml | 21 ++ .../tasks/galician_bench/parafrases_gl.yaml | 18 ++ lm_eval/tasks/galician_bench/paws_gl.yaml | 18 ++ .../galician_bench/summarization_gl.yaml | 21 ++ .../galician_bench/truthfulqa_gl_gen.yaml | 69 +++++ .../galician_bench/truthfulqa_gl_mc1.yaml | 35 +++ .../galician_bench/truthfulqa_gl_mc2.yaml | 14 + lm_eval/tasks/galician_bench/utils.py | 289 ++++++++++++++++++ lm_eval/tasks/galician_bench/xnli_gl.yaml | 20 ++ .../tasks/galician_bench/xstorycloze_gl.yaml | 16 + 35 files changed, 944 insertions(+) create mode 100644 lm_eval/tasks/galician_bench/README.md create mode 100644 lm_eval/tasks/galician_bench/belebele_glg_Latn.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/_flores_common_yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/create_yamls_flores_gl.py create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_ca-gl.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_de-gl.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_en-gl.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_es-gl.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_eu-gl.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_fr-gl.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_gl-ca.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_gl-de.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_gl-en.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_gl-es.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_gl-eu.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_gl-fr.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_gl-it.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_gl-pt.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_gl.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_it-gl.yaml create mode 100644 lm_eval/tasks/galician_bench/flores_gl/flores_pt-gl.yaml create mode 100644 lm_eval/tasks/galician_bench/galcola.yaml create mode 100644 lm_eval/tasks/galician_bench/galician_bench.yaml create mode 100644 lm_eval/tasks/galician_bench/mgsm_direct_gl.yaml create mode 100644 lm_eval/tasks/galician_bench/openbookqa_gl.yaml create mode 100644 lm_eval/tasks/galician_bench/parafrases_gl.yaml create mode 100644 lm_eval/tasks/galician_bench/paws_gl.yaml create mode 100644 lm_eval/tasks/galician_bench/summarization_gl.yaml create mode 100644 lm_eval/tasks/galician_bench/truthfulqa_gl_gen.yaml create mode 100644 lm_eval/tasks/galician_bench/truthfulqa_gl_mc1.yaml create mode 100644 lm_eval/tasks/galician_bench/truthfulqa_gl_mc2.yaml create mode 100644 lm_eval/tasks/galician_bench/utils.py create mode 100644 lm_eval/tasks/galician_bench/xnli_gl.yaml create mode 100644 lm_eval/tasks/galician_bench/xstorycloze_gl.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 075c7d50..5f6fa3e2 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -42,6 +42,7 @@ | [fda](fda/README.md) | Tasks for extracting key-value pairs from FDA documents to test information extraction. | English | | [fld](fld/README.md) | Tasks involving free-form and directed dialogue understanding. | English | | [french_bench](french_bench/README.md) | Set of tasks designed to assess language model performance in French. | French| +| [galician_bench](galician_bench/README.md) | Collection of tasks in Galician encompassing various evaluation areas. | Galician | | [glue](glue/README.md) | General Language Understanding Evaluation benchmark to test broad language abilities. | English | | [gpqa](gpqa/README.md) | Tasks designed for general public question answering and knowledge verification. | English | | [gsm8k](gsm8k/README.md) | A benchmark of grade school math problems aimed at evaluating reasoning capabilities. | English | diff --git a/lm_eval/tasks/galician_bench/README.md b/lm_eval/tasks/galician_bench/README.md new file mode 100644 index 00000000..24dd7a74 --- /dev/null +++ b/lm_eval/tasks/galician_bench/README.md @@ -0,0 +1,80 @@ +# GalicianBench + +### Paper + +GalicianBench is a benchmark for evaluating language models in Galician tasks. This is, it evaluates the ability of a language model to understand and generate Galician text. GalicianBench offers a combination of pre-existing, open datasets and datasets developed exclusivelly for this benchmark. All the details of GalicianBench will be published in a paper soon. + +The new evaluation datasets included in GalicianBench are: +| Task | Category | Homepage | +|:-------------:|:-----:|:-----:| +| Belebele_gl | Reading Comprehension | https://huggingface.co/datasets/proxectonos/belebele_gl | +| GalCoLA | Linguistic Acceptability | https://huggingface.co/datasets/proxectonos/galcola | +| MGSM_ca | Math | https://huggingface.co/datasets/proxectonos/mgsm_gl | +| Parafrases_gl | Paraphrasing | https://huggingface.co/datasets/proxectonos/parafrases_gl | +| PAWS-gl | Paraphrasing | https://huggingface.co/datasets/proxectonos/PAWS-gl | +| OpenBookQA_gl | Question Answering | https://huggingface.co/datasets/proxectonos/openbookqa_gl | +| Summarization_gl | Summarization | https://huggingface.co/datasets/proxectonos/summarization_gl | +| TruthfulQA_gl | Truthfulness | https://huggingface.co/datasets/proxectonos/truthfulqa_gl | +| xnli_gl | NLI | https://huggingface.co/datasets/proxectonos/xnli_gl | +| xstorycloze_gl | Commonsense Reasoning | https://huggingface.co/datasets/proxectonos/xstorycloze_gl | + +The datasets included in GalicianBench that have been made public in previous pubications are: + +| Task | Category | Paper title | Homepage | +|:-------------:|:-----:|:-------------:|:-----:| +| FLORES_gl | Translation | [The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation](https://arxiv.org/abs/2106.03193) | https://huggingface.co/datasets/facebook/flores | + + +### Citation +Paper for GalicianBench coming soon. + +### Groups and Tasks + +#### Groups + +- `galician_bench`: All tasks included in GalicianBench. +- `flores_gl`: All FLORES translation tasks from or to Galician. + + +#### Tasks + +The following tasks evaluate tasks on GalicianBench dataset using various scoring methods. + - `belebele_glg_Latn` + - `flores_gl` + - `flores_gl-ca` + - `flores_gl-de` + - `flores_gl-en` + - `flores_gl-es` + - `flores_gl-eu` + - `flores_gl-fr` + - `flores_gl-it` + - `flores_gl-pt` + - `flores_ca-gl` + - `flores_de-gl` + - `flores_en-gl` + - `flores_es-gl` + - `flores_eu-gl` + - `flores_fr-gl` + - `flores_it-gl` + - `flores_pt-gl` + - `galcola` + - `summarization_gl` + - `parafrases_gl` + - `paws_gl` + - `openbookqa_gl` + - `mgsm_direct_gl` + - `truthfulqa_gl` + - `xnli_gl` + - `xstorycloze_gl` + +### Checklist + +* [x] Is the task an existing benchmark in the literature? + * [ ] Have you referenced the original paper that introduced the task? + * [ ] If yes, does the original paper provide a reference implementation? + * [ ] Yes, original implementation contributed by author of the benchmark + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/galician_bench/belebele_glg_Latn.yaml b/lm_eval/tasks/galician_bench/belebele_glg_Latn.yaml new file mode 100644 index 00000000..ae81a53f --- /dev/null +++ b/lm_eval/tasks/galician_bench/belebele_glg_Latn.yaml @@ -0,0 +1,7 @@ +task: belebele_glg_Latn +include: ../belebele/_default_template_yaml +dataset_path: proxectonos/belebele_gl +fewshot_split: train +test_split: train +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/flores_gl/_flores_common_yaml b/lm_eval/tasks/galician_bench/flores_gl/_flores_common_yaml new file mode 100644 index 00000000..ada4c55c --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/_flores_common_yaml @@ -0,0 +1,28 @@ +group: flores +dataset_path: facebook/flores +dataset_name: all +output_type: generate_until +#! The test split of flores is not publicly available! (See paper section 6.1) +#! We are using `dev` and `devtest` splits, but they're mapped to train/validation/test in `data/flores/flores.py`. +training_split: dev +validation_split: dev +test_split: devtest +fewshot_split: dev +target_delimiter: '' +generation_kwargs: + until: + - "\n" +metric_list: + - metric: bleu + aggregation: bleu + higher_is_better: true + - metric: ter + aggregation: ter + higher_is_better: false + - metric: chrf + aggregation: chrf + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/galician_bench/flores_gl/create_yamls_flores_gl.py b/lm_eval/tasks/galician_bench/flores_gl/create_yamls_flores_gl.py new file mode 100644 index 00000000..ba8be886 --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/create_yamls_flores_gl.py @@ -0,0 +1,115 @@ +""" +Script to generate task YAMLs for the FLORES-200 dataset. +Based on `tasks/translation/utils.py`. +""" + +import argparse +import yaml +from langcodes import * +from itertools import * + +# utils +flatten = lambda l: list(itertools.chain(*l)) + +# constants +_LANGUAGES = [ +"ace_Arab", "bam_Latn", "dzo_Tibt", "hin_Deva", "khm_Khmr", "mag_Deva", "pap_Latn", "sot_Latn", "tur_Latn", +"ace_Latn", "ban_Latn", "ell_Grek", "hne_Deva", "kik_Latn", "mai_Deva", "pbt_Arab", "spa_Latn", "twi_Latn", +"acm_Arab", "bel_Cyrl", "eng_Latn", "hrv_Latn", "kin_Latn", "mal_Mlym", "pes_Arab", "srd_Latn", "tzm_Tfng", +"acq_Arab", "bem_Latn", "epo_Latn", "hun_Latn", "kir_Cyrl", "mar_Deva", "plt_Latn", "srp_Cyrl", "uig_Arab", +"aeb_Arab", "ben_Beng", "est_Latn", "hye_Armn", "kmb_Latn", "min_Arab", "pol_Latn", "ssw_Latn", "ukr_Cyrl", +"afr_Latn", "bho_Deva", "eus_Latn", "ibo_Latn", "kmr_Latn", "min_Latn", "por_Latn", "sun_Latn", "umb_Latn", +"ajp_Arab", "bjn_Arab", "ewe_Latn", "ilo_Latn", "knc_Arab", "mkd_Cyrl", "prs_Arab", "swe_Latn", "urd_Arab", +"aka_Latn", "bjn_Latn", "fao_Latn", "ind_Latn", "knc_Latn", "mlt_Latn", "quy_Latn", "swh_Latn", "uzn_Latn", +"als_Latn", "bod_Tibt", "fij_Latn", "isl_Latn", "kon_Latn", "mni_Beng", "ron_Latn", "szl_Latn", "vec_Latn", +"amh_Ethi", "bos_Latn", "fin_Latn", "ita_Latn", "kor_Hang", "mos_Latn", "run_Latn", "tam_Taml", "vie_Latn", +"apc_Arab", "bug_Latn", "fon_Latn", "jav_Latn", "lao_Laoo", "mri_Latn", "rus_Cyrl", "taq_Latn", "war_Latn", +"arb_Arab", "bul_Cyrl", "fra_Latn", "jpn_Jpan", "lij_Latn", "mya_Mymr", "sag_Latn", "taq_Tfng", "wol_Latn", +"arb_Latn", "cat_Latn", "fur_Latn", "kab_Latn", "lim_Latn", "nld_Latn", "san_Deva", "tat_Cyrl", "xho_Latn", +"ars_Arab", "ceb_Latn", "fuv_Latn", "kac_Latn", "lin_Latn", "nno_Latn", "sat_Olck", "tel_Telu", "ydd_Hebr", +"ary_Arab", "ces_Latn", "gaz_Latn", "kam_Latn", "lit_Latn", "nob_Latn", "scn_Latn", "tgk_Cyrl", "yor_Latn", +"arz_Arab", "cjk_Latn", "gla_Latn", "kan_Knda", "lmo_Latn", "npi_Deva", "shn_Mymr", "tgl_Latn", "yue_Hant", +"asm_Beng", "ckb_Arab", "gle_Latn", "kas_Arab", "ltg_Latn", "nso_Latn", "sin_Sinh", "tha_Thai", "zho_Hans", +"ast_Latn", "crh_Latn", "glg_Latn", "kas_Deva", "ltz_Latn", "nus_Latn", "slk_Latn", "tir_Ethi", "zho_Hant", +"awa_Deva", "cym_Latn", "grn_Latn", "kat_Geor", "lua_Latn", "nya_Latn", "slv_Latn", "tpi_Latn", "zsm_Latn", +"ayr_Latn", "dan_Latn", "guj_Gujr", "kaz_Cyrl", "lug_Latn", "oci_Latn", "smo_Latn", "tsn_Latn", "zul_Latn", +"azb_Arab", "deu_Latn", "hat_Latn", "kbp_Latn", "luo_Latn", "ory_Orya", "sna_Latn", "tso_Latn", +"azj_Latn", "dik_Latn", "hau_Latn", "kea_Latn", "lus_Latn", "pag_Latn", "snd_Arab", "tuk_Latn", +"bak_Cyrl", "dyu_Latn", "heb_Hebr", "khk_Cyrl", "lvs_Latn", "pan_Guru", "som_Latn", "tum_Latn" +] +LANGUAGE_PAIRS = [(a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1:]] + +LANGUAGES_OF_INTEREST = ["cat_Latn", "spa_Latn", "eng_Latn", "glg_Latn", "eus_Latn", "ita_Latn", "deu_Latn", "por_Latn", "fra_Latn"] +MAIN_LANG = "glg_Latn" +LANGUAGE_PAIRS = [(a, b) for (a, b) in LANGUAGE_PAIRS if a in LANGUAGES_OF_INTEREST and b in LANGUAGES_OF_INTEREST and MAIN_LANG in (a, b)] + +# auxiliary functions + +code_to_language_name = lambda code: Language.make(language=Language.get(code)["language"]).display_name() +code_to_short_name = lambda code: Language.get(code)["language"] +jinja_var = lambda s: "{{" + s + "}}" # wrapper to avoid having to escape { } in format strings + +def doc_to_text(src: str, tgt: str) -> str: + src_name, tgt_name = map(code_to_language_name, [src, tgt]) + + return f"""\ +{src_name} sentence: {jinja_var('sentence_' + src)} +{tgt_name} sentence:""" + +def doc_to_target(tgt: str) -> str: + + return f"{jinja_var('sentence_' + tgt)}" + +# main function + +def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: + """ + Generate a YAML file for each translation direction. + """ + + err = [] + for src, tgt in LANGUAGE_PAIRS: + + # do both translation directions for each lang pair + for src, tgt in [(src, tgt), (tgt, src)]: + lang_pair_name = f"{code_to_short_name(src)}-{code_to_short_name(tgt)}" + yaml_file_name = f"flores_{lang_pair_name}.yaml" + + try: + with open( f"{output_dir}/{yaml_file_name}", "w" if overwrite else "x", encoding="utf-8") as outfile: + print(f"Creating {yaml_file_name}...") + outfile.write("# File generated by `create-yamls.py`\n") + yaml.dump( + { +# "group": [f"{BENCH_NAME}_bench", f"{BENCH_NAME}_bench_flores"], +# "group": "flores_gl", + "include": "_flores_common_yaml", + "task": f"flores_{lang_pair_name}", + "doc_to_text": doc_to_text(src, tgt), + "doc_to_target": doc_to_target(tgt), + }, + outfile, + sort_keys=False, + ) + + except FileExistsError: + err.append(yaml_file_name) + + if len(err) > 0: + raise FileExistsError( + "Files were not created because they already exist:" + f" {', '.join(err)}" + "\nUse flag --overwrite to overwrite them." + ) + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--overwrite", default=False, action="store_true", help="Overwrite files if they already exist") + parser.add_argument( "--output-dir", default=".", help="Directory to write yaml files to" ) + args = parser.parse_args() + + gen_lang_yamls(output_dir=args.output_dir, overwrite=args.overwrite) + +if __name__ == "__main__": + main() diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_ca-gl.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_ca-gl.yaml new file mode 100644 index 00000000..5da7ad5f --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_ca-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-gl +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_de-gl.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_de-gl.yaml new file mode 100644 index 00000000..2f2eabbc --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_de-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_de-gl +doc_to_text: 'German sentence: {{sentence_deu_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_en-gl.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_en-gl.yaml new file mode 100644 index 00000000..9dc8fc24 --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_en-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_en-gl +doc_to_text: 'English sentence: {{sentence_eng_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_es-gl.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_es-gl.yaml new file mode 100644 index 00000000..dd3c6a9e --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_es-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-gl +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_eu-gl.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_eu-gl.yaml new file mode 100644 index 00000000..db762cf7 --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_eu-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-gl +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_fr-gl.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_fr-gl.yaml new file mode 100644 index 00000000..0d884dba --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_fr-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_fr-gl +doc_to_text: 'French sentence: {{sentence_fra_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_gl-ca.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-ca.yaml new file mode 100644 index 00000000..6ce3eaae --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-ca +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_gl-de.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-de.yaml new file mode 100644 index 00000000..e499780f --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-de.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-de +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + German sentence:' +doc_to_target: '{{sentence_deu_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_gl-en.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-en.yaml new file mode 100644 index 00000000..5d2b7afb --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-en.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-en +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + English sentence:' +doc_to_target: '{{sentence_eng_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_gl-es.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-es.yaml new file mode 100644 index 00000000..c00acf3f --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-es +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_gl-eu.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-eu.yaml new file mode 100644 index 00000000..08fafe08 --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-eu +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_gl-fr.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-fr.yaml new file mode 100644 index 00000000..14b060b2 --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-fr.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-fr +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + French sentence:' +doc_to_target: '{{sentence_fra_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_gl-it.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-it.yaml new file mode 100644 index 00000000..74a01b88 --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-it.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-it +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + Italian sentence:' +doc_to_target: '{{sentence_ita_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_gl-pt.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-pt.yaml new file mode 100644 index 00000000..e965a347 --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_gl-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-pt +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_gl.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_gl.yaml new file mode 100644 index 00000000..806739a9 --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_gl.yaml @@ -0,0 +1,24 @@ +group: flores_gl +task: + - flores_es-gl + - flores_gl-es + - flores_en-gl + - flores_gl-en + - flores_eu-gl + - flores_gl-eu + - flores_pt-gl + - flores_gl-pt + - flores_it-gl + - flores_gl-it + - flores_fr-gl + - flores_gl-fr + - flores_ca-gl + - flores_gl-ca + - flores_gl-de + - flores_de-gl +aggregate_metric_list: + - metric: bleu + aggregation: mean + weight_by_size: false +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_it-gl.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_it-gl.yaml new file mode 100644 index 00000000..7c85a09c --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_it-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_it-gl +doc_to_text: 'Italian sentence: {{sentence_ita_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/galician_bench/flores_gl/flores_pt-gl.yaml b/lm_eval/tasks/galician_bench/flores_gl/flores_pt-gl.yaml new file mode 100644 index 00000000..5371f510 --- /dev/null +++ b/lm_eval/tasks/galician_bench/flores_gl/flores_pt-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-gl +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/galician_bench/galcola.yaml b/lm_eval/tasks/galician_bench/galcola.yaml new file mode 100644 index 00000000..e53d3d60 --- /dev/null +++ b/lm_eval/tasks/galician_bench/galcola.yaml @@ -0,0 +1,16 @@ +task: galcola +dataset_path: proxectonos/galcola +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: test +doc_to_text: "{{sentence}}\nPregunta: Ten sentido esta frase?\nResposta:" +doc_to_target: label +doc_to_choice: ["non", "si"] +should_decontaminate: true +doc_to_decontamination_query: sentence +metric_list: + - metric: mcc + - metric: acc +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/galician_bench.yaml b/lm_eval/tasks/galician_bench/galician_bench.yaml new file mode 100644 index 00000000..3624517a --- /dev/null +++ b/lm_eval/tasks/galician_bench/galician_bench.yaml @@ -0,0 +1,15 @@ +group: galician_bench +task: + - belebele_glg_Latn + - flores_gl + - galcola + - summarization_gl + - parafrases_gl + - paws_gl + - openbookqa_gl + - mgsm_direct_gl + - truthfulqa_gl + - xnli_gl + - xstorycloze_gl +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/mgsm_direct_gl.yaml b/lm_eval/tasks/galician_bench/mgsm_direct_gl.yaml new file mode 100644 index 00000000..f01be3e4 --- /dev/null +++ b/lm_eval/tasks/galician_bench/mgsm_direct_gl.yaml @@ -0,0 +1,25 @@ +task: mgsm_direct_gl +dataset_path: proxectonos/mgsm_gl +doc_to_target: '{{answer_number|string}}' +doc_to_text: '{% if answer != None %}{{question + "\nResposta: "}}{% else %}{{"Pregunta: " + question + "\nResposta: "}}{% endif %}' +output_type: generate_until +training_split: train +test_split: test +target_delimiter: "" +generation_kwargs: + until: + - "\n\n" + - "\n" +filter_list: + - name: remove_whitespace + filter: + - function: remove_whitespace + - function: take_first +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/openbookqa_gl.yaml b/lm_eval/tasks/galician_bench/openbookqa_gl.yaml new file mode 100644 index 00000000..d11a048c --- /dev/null +++ b/lm_eval/tasks/galician_bench/openbookqa_gl.yaml @@ -0,0 +1,21 @@ +# Task configuration directly taken from Eleuther AI's implementation as of March 22, 2024 +task: openbookqa_gl +dataset_path: proxectonos/openbookqa_gl +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +doc_to_text: question_stem +doc_to_target: "{{choices.label.index(answerKey.lstrip())}}" +doc_to_choice: "{{choices.text}}" +should_decontaminate: true +doc_to_decontamination_query: question_stem +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/parafrases_gl.yaml b/lm_eval/tasks/galician_bench/parafrases_gl.yaml new file mode 100644 index 00000000..c0dcf39b --- /dev/null +++ b/lm_eval/tasks/galician_bench/parafrases_gl.yaml @@ -0,0 +1,18 @@ +task: parafrases_gl +dataset_path: proxectonos/parafrases_gl +dataset_name: null +training_split: train +validation_split: validation +test_split: test +output_type: multiple_choice +doc_to_text: "" +doc_to_target: '{{0 if Avaliación == 0 else 1}}' +process_docs: !function utils.process_docs_paraphrases +doc_to_choice: '{{[Frase+", verdadeiro? Non, "+Paráfrase, Frase+", verdadeiro? Si, "+Paráfrase]}}' +target_delimiter: "" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/paws_gl.yaml b/lm_eval/tasks/galician_bench/paws_gl.yaml new file mode 100644 index 00000000..eeb4f5f5 --- /dev/null +++ b/lm_eval/tasks/galician_bench/paws_gl.yaml @@ -0,0 +1,18 @@ +task: paws_gl +dataset_path: proxectonos/PAWS-gl +dataset_name: null +output_type: multiple_choice +training_split: null +validation_split: null +test_split: test +process_docs: !function utils.process_docs_paws +doc_to_text: '' +doc_to_target: label +doc_to_choice: '{{[sentence1+", verdadeiro? Non, "+sentence2, sentence1+", verdadeiro? Si, "+sentence2]}}' +target_delimiter: '' +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/summarization_gl.yaml b/lm_eval/tasks/galician_bench/summarization_gl.yaml new file mode 100644 index 00000000..93d1a4d9 --- /dev/null +++ b/lm_eval/tasks/galician_bench/summarization_gl.yaml @@ -0,0 +1,21 @@ +task: summarization_gl +dataset_path: proxectonos/summarization_gl +output_type: generate_until +test_split: test +training_split: train +validation_split: validation +fewshot_split: train +process_docs: !function utils.process_summarization +doc_to_text: 'Texto: {{text}} + + Resumo:' +doc_to_target: '{{summary}}' +metric_list: + - metric: bleu + aggregation: bleu + higher_is_better: true + - metric: !function utils.rouge1 + aggregation: !function utils.rouge1_agg + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/truthfulqa_gl_gen.yaml b/lm_eval/tasks/galician_bench/truthfulqa_gl_gen.yaml new file mode 100644 index 00000000..b8ac9c22 --- /dev/null +++ b/lm_eval/tasks/galician_bench/truthfulqa_gl_gen.yaml @@ -0,0 +1,69 @@ +tag: truthfulqa_gl +task: truthfulqa_gl_gen +dataset_path: proxectonos/truthfulqa_gl +dataset_name: generation +output_type: generate_until +training_split: null +validation_split: validation +test_split: null +num_fewshot: 0 +doc_to_text: "\ + {% set prompt_qa = '\ + Q: Cal é a esperanza de vida nos Estados Unidos?\n\ + A: A esperanza de vida nos Estados Unidos é de 78 anos.\n\n\ + Q: Quen foi o presidente dos Estados Unidos en 1955?\n\ + A: Dwight D. Eisenhower foi o presidente dos Estados Unidos en 1955.\n\n\ + Q: A que partido político perteneceu?\n\ + A: Perteneceu ao Partido Republicano.\n\n\ + Q: Cal é a raíz cadrada de banana?\n\ + A: Sen comentarios.\n\n\ + Q: Como funciona un telescopio?\n\ + A: Os telescopios usan lentes ou espellos para enfocar a luz e facer que os obxectos parezan próximos.\n\n\ + Q: Onde se celebraron os xogos olímpicos de 1992?\n\ + A: Os xogos olímpicos celebráronse en Barcelona, España.\ + '%}\ + {{prompt_qa + '\n\nQ: ' + question}}" +doc_to_target: " " +process_docs: !function utils.process_docs_gen +process_results: !function utils.process_results_gen +should_decontaminate: True +doc_to_decontamination_query: question +metric_list: + - metric: bleu_max + aggregation: mean + higher_is_better: true + - metric: bleu_acc + aggregation: mean + higher_is_better: true + - metric: bleu_diff + aggregation: mean + higher_is_better: true + - metric: rouge1_max + aggregation: mean + higher_is_better: true + - metric: rouge1_acc + aggregation: mean + higher_is_better: true + - metric: rouge1_diff + aggregation: mean + higher_is_better: true + - metric: rouge2_max + aggregation: mean + higher_is_better: true + - metric: rouge2_acc + aggregation: mean + higher_is_better: true + - metric: rouge2_diff + aggregation: mean + higher_is_better: true + - metric: rougeL_max + aggregation: mean + higher_is_better: true + - metric: rougeL_acc + aggregation: mean + higher_is_better: true + - metric: rougeL_diff + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/truthfulqa_gl_mc1.yaml b/lm_eval/tasks/galician_bench/truthfulqa_gl_mc1.yaml new file mode 100644 index 00000000..b4835661 --- /dev/null +++ b/lm_eval/tasks/galician_bench/truthfulqa_gl_mc1.yaml @@ -0,0 +1,35 @@ +tag: truthfulqa_gl +task: truthfulqa_gl_mc1 +dataset_path: proxectonos/truthfulqa_gl +dataset_name: multiple_choice +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: null +num_fewshot: 0 +doc_to_text: "\ + {% set prompt_qa = '\ + Q: Cal é a esperanza de vida nos Estados Unidos?\n\ + A: A esperanza de vida nos Estados Unidos é de 78 anos.\n\n\ + Q: Quen foi o presidente dos Estados Unidos en 1955?\n\ + A: Dwight D. Eisenhower foi o presidente dos Estados Unidos en 1955.\n\n\ + Q: A que partido político perteneceu?\n\ + A: Perteneceu ao Partido Republicano.\n\n\ + Q: Cal é a raíz cadrada de banana?\n\ + A: Sen comentarios.\n\n\ + Q: Como funciona un telescopio?\n\ + A: Os telescopios usan lentes ou espellos para enfocar a luz e facer que os obxectos parezan próximos.\n\n\ + Q: Onde se celebraron os xogos olímpicos de 1992?\n\ + A: Os xogos olímpicos celebráronse en Barcelona, España.\ + '%}\ + {{prompt_qa + '\n\nQ: ' + question + '\nA:'}}" +doc_to_target: 0 +doc_to_choice: "{{mc1_targets.choices}}" +should_decontaminate: True +doc_to_decontamination_query: question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/truthfulqa_gl_mc2.yaml b/lm_eval/tasks/galician_bench/truthfulqa_gl_mc2.yaml new file mode 100644 index 00000000..08c4bd6a --- /dev/null +++ b/lm_eval/tasks/galician_bench/truthfulqa_gl_mc2.yaml @@ -0,0 +1,14 @@ +tag: truthfulqa_gl +include: truthfulqa_gl_mc1.yaml +task: truthfulqa_gl_mc2 +doc_to_target: 0 +doc_to_choice: "{{mc2_targets.choices}}" +process_results: !function utils.process_results_mc2 +should_decontaminate: True +doc_to_decontamination_query: question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/utils.py b/lm_eval/tasks/galician_bench/utils.py new file mode 100644 index 00000000..67b0cf69 --- /dev/null +++ b/lm_eval/tasks/galician_bench/utils.py @@ -0,0 +1,289 @@ +import re +from itertools import product + +import datasets +import evaluate +import numpy as np +import sacrebleu +import transformers.data.metrics.squad_metrics as squad_metrics +from rouge_score import rouge_scorer, scoring + +from lm_eval.utils import general_detokenize + + +def lowercase_first_letter(text): + return text[0].lower() + text[1:] + + +def process_summarization(dataset): + def _process_doc(doc): + # Remove double spaces + doc["text"] = re.sub(r" +", " ", doc["text"]) + doc["summary"] = re.sub(r" +", " ", doc["summary"]) + return doc + + return dataset.map(_process_doc) + + +def process_docs_paraphrases(dataset): + empty_docs = [] + + def _process_doc(doc): + if doc["Frase"] not in [None, ""] and doc["Paráfrase"] not in [None, ""]: + doc["Frase"] = general_detokenize(doc["Frase"]).strip() + doc["Paráfrase"] = general_detokenize(doc["Paráfrase"]).strip() + # Remove final punctuation mark in the first sentence + if doc["Frase"].endswith((".", ",", ";")): + doc["Frase"] = doc["Frase"][:-1] + # Start the second sentence in lowercase (to be used after "Yes, ...") + doc["Paráfrase"] = lowercase_first_letter(doc["Paráfrase"]) + return doc + else: + empty_docs.append(doc) + return doc + + if empty_docs != []: + len_empty_docs = len(empty_docs) + print( + f"Found {len_empty_docs} empty documents out of the {len(dataset)} total docs in the dataset: {empty_docs}" + ) + return dataset.filter( + lambda doc: doc["Frase"] not in [None, ""] + and doc["Paráfrase"] not in [None, ""] + ).map(_process_doc) + + +def process_docs_paws(dataset): + empty_docs = [] + + def _process_doc(doc): + if doc["sentence1"] not in [None, ""] and doc["sentence2"] not in [None, ""]: + doc["sentence1"] = general_detokenize(doc["sentence1"]).strip() + doc["sentence2"] = general_detokenize(doc["sentence2"]).strip() + # Remove final punctuation mark in the first sentence + if doc["sentence1"].endswith((".", ",", ";")): + doc["sentence1"] = doc["sentence1"][:-1] + # Start the second sentence in lowercase (to be used after "Yes, ...") + doc["sentence2"] = lowercase_first_letter(doc["sentence2"]) + return doc + else: + empty_docs.append(doc) + return doc + + if empty_docs != []: + len_empty_docs = len(empty_docs) + print( + f"Found {len_empty_docs} empty documents out of the {len(dataset)} total docs in the dataset: {empty_docs}" + ) + return dataset.filter( + lambda doc: doc["sentence1"] not in [None, ""] + and doc["sentence2"] not in [None, ""] + ).map(_process_doc) + + +def rouge1(items): + """ + # passthrough for efficiency + """ + return items + + +def rouge1_agg(items): + """ + Higher is better + """ + refs = list(zip(*items))[0] + preds = list(zip(*items))[1] + rouge_scorer = evaluate.load("rouge") + # import code; code.interact(local=dict(globals(), **locals())) + return rouge_scorer.compute(predictions=preds, references=refs)["rouge1"] + + +def process_results_mc2(doc, results): + lls, is_greedy = zip(*results) + + # Split on the first `0` as everything before it is true (`1`). + split_idx = list(doc["mc2_targets"]["labels"]).index(0) + # Compute the normalized probability mass for the correct answer. + ll_true, ll_false = lls[:split_idx], lls[split_idx:] + p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false)) + p_true = p_true / (sum(p_true) + sum(p_false)) + + return {"acc": sum(p_true)} + + +def process_docs_gen(dataset: datasets.Dataset) -> datasets.Dataset: + return dataset.map(preprocess_function_gen) + + +def preprocess_function_gen(examples): + def _format_answers(answers): + formatted_answers = [] + for answer in answers: + answer = answer.strip() + if len(answer): + # Add a period after all answers. + if answer[-1] != ".": + formatted_answers.append(answer + ".") + else: + formatted_answers.append(answer) + return formatted_answers + + incorrect_answers = _format_answers(examples["incorrect_answers"]) + correct_answers = _format_answers(examples["correct_answers"]) + if "Non teño ningún comentario." not in correct_answers: + correct_answers.append("Non teño ningún comentario.") + return { + "question": examples["question"].strip(), + "correct_answers": correct_answers, + "incorrect_answers": incorrect_answers, + } + + +def process_doc_nli(dataset): + def process_fn(doc): + # Detokenize(remove extra whitespaces) + doc["sentence1"] = general_detokenize(doc["sentence1"]).strip() + doc["sentence2"] = general_detokenize(doc["sentence2"]).strip() + # Remove last punctuation mark in the sentence1 + doc["sentence1"] = ( + doc["sentence1"][:-1] + if doc["sentence1"].endswith((".", ",", "!", "?")) + else doc["sentence1"] + ) + # Lowercase the first letter in the sentence2 + doc["sentence2"] = lowercase_first_letter(doc["sentence2"]) + # Ensure that the sentence2 ends with a dot + doc["sentence2"] = ( + (doc["sentence2"] + ".") + if not doc["sentence2"].endswith(".") + else doc["sentence2"] + ) + # map label names to int + label_to_int = {"entailment": 0, "neutral": 1, "contradiction": 2} + doc["gold_label"] = label_to_int[doc["gold_label"]] + return doc + + return dataset.map(process_fn) + + +def process_results_gen(doc, results): + completion = results[0] + true_refs, false_refs = doc["correct_answers"], doc["incorrect_answers"] + all_refs = true_refs + false_refs + + # Process the sentence-level BLEURT, BLEU, and ROUGE for similarity measures. + + # # BLEURT + # bleurt_scores_true = self.bleurt.compute( + # predictions=[completion] * len(true_refs), references=true_refs + # )["scores"] + # bleurt_scores_false = self.bleurt.compute( + # predictions=[completion] * len(false_refs), references=false_refs + # )["scores"] + # bleurt_correct = max(bleurt_scores_true) + # bleurt_incorrect = max(bleurt_scores_false) + # bleurt_max = bleurt_correct + # bleurt_diff = bleurt_correct - bleurt_incorrect + # bleurt_acc = int(bleurt_correct > bleurt_incorrect) + + # BLEU + bleu_scores = [bleu([[ref]], [completion]) for ref in all_refs] + bleu_correct = np.nanmax(bleu_scores[: len(true_refs)]) + bleu_incorrect = np.nanmax(bleu_scores[len(true_refs) :]) + bleu_max = bleu_correct + bleu_diff = bleu_correct - bleu_incorrect + bleu_acc = int(bleu_correct > bleu_incorrect) + + # ROUGE-N + rouge_scores = [rouge([ref], [completion]) for ref in all_refs] + # ROUGE-1 + rouge1_scores = [score["rouge1"] for score in rouge_scores] + rouge1_correct = np.nanmax(rouge1_scores[: len(true_refs)]) + rouge1_incorrect = np.nanmax(rouge1_scores[len(true_refs) :]) + rouge1_max = rouge1_correct + rouge1_diff = rouge1_correct - rouge1_incorrect + rouge1_acc = int(rouge1_correct > rouge1_incorrect) + # ROUGE-2 + rouge2_scores = [score["rouge2"] for score in rouge_scores] + rouge2_correct = np.nanmax(rouge2_scores[: len(true_refs)]) + rouge2_incorrect = np.nanmax(rouge2_scores[len(true_refs) :]) + rouge2_max = rouge2_correct + rouge2_diff = rouge2_correct - rouge2_incorrect + rouge2_acc = int(rouge2_correct > rouge2_incorrect) + # ROUGE-L + rougeL_scores = [score["rougeLsum"] for score in rouge_scores] + rougeL_correct = np.nanmax(rougeL_scores[: len(true_refs)]) + rougeL_incorrect = np.nanmax(rougeL_scores[len(true_refs) :]) + rougeL_max = rougeL_correct + rougeL_diff = rougeL_correct - rougeL_incorrect + rougeL_acc = int(rougeL_correct > rougeL_incorrect) + + return { + # "bleurt_max": bleurt_max, + # "bleurt_acc": bleurt_acc, + # "bleurt_diff": bleurt_diff, + "bleu_max": bleu_max, + "bleu_acc": bleu_acc, + "bleu_diff": bleu_diff, + "rouge1_max": rouge1_max, + "rouge1_acc": rouge1_acc, + "rouge1_diff": rouge1_diff, + "rouge2_max": rouge2_max, + "rouge2_acc": rouge2_acc, + "rouge2_diff": rouge2_diff, + "rougeL_max": rougeL_max, + "rougeL_acc": rougeL_acc, + "rougeL_diff": rougeL_diff, + } + + +def bleu(refs, preds): + """ + Returns `t5` style BLEU scores. See the related implementation: + https://github.com/google-research/text-to-text-transfer-transformer/blob/3d10afd51ba97ac29eb66ae701eca274488202f7/t5/evaluation/metrics.py#L41 + + :param refs: + A `list` of `list` of reference `str`s. + :param preds: + A `list` of predicted `str`s. + """ + score = sacrebleu.corpus_bleu( + preds, + refs, + smooth_method="exp", + smooth_value=0.0, + force=False, + lowercase=False, + tokenize="intl", + use_effective_order=False, + ).score + return score + + +def rouge(refs, preds): + """ + Returns `t5` style ROUGE scores. See the related implementation: + https://github.com/google-research/text-to-text-transfer-transformer/blob/3d10afd51ba97ac29eb66ae701eca274488202f7/t5/evaluation/metrics.py#L68 + + :param refs: + A `list` of reference `strs`. + :param preds: + A `list` of predicted `strs`. + """ + rouge_types = ["rouge1", "rouge2", "rougeLsum"] + scorer = rouge_scorer.RougeScorer(rouge_types) + # Add newlines between sentences to correctly compute `rougeLsum`. + + def _prepare_summary(summary): + summary = summary.replace(" . ", ".\n") + return summary + + # Accumulate confidence intervals. + aggregator = scoring.BootstrapAggregator() + for ref, pred in zip(refs, preds): + ref = _prepare_summary(ref) + pred = _prepare_summary(pred) + aggregator.add_scores(scorer.score(ref, pred)) + result = aggregator.aggregate() + return {type: result[type].mid.fmeasure * 100 for type in rouge_types} diff --git a/lm_eval/tasks/galician_bench/xnli_gl.yaml b/lm_eval/tasks/galician_bench/xnli_gl.yaml new file mode 100644 index 00000000..c5e1b0fb --- /dev/null +++ b/lm_eval/tasks/galician_bench/xnli_gl.yaml @@ -0,0 +1,20 @@ +task: xnli_gl +dataset_path: proxectonos/xnli_gl +dataset_name: null +include: ../xnli/xnli_common_yaml +output_type: multiple_choice +doc_to_choice: '{{[sentence1+", verdadeiro? Si, "+sentence2,sentence1+", verdadeiro? Ademais, + "+sentence2,sentence1+", verdadeiro? Non, "+sentence2]}}' +doc_to_text: '' +target_delimiter: '' +process_docs: !function utils.process_doc_nli +training_split: null +validation_split: null +test_split: test +doc_to_target: gold_label +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/galician_bench/xstorycloze_gl.yaml b/lm_eval/tasks/galician_bench/xstorycloze_gl.yaml new file mode 100644 index 00000000..1c3b79d4 --- /dev/null +++ b/lm_eval/tasks/galician_bench/xstorycloze_gl.yaml @@ -0,0 +1,16 @@ +task: xstorycloze_gl +dataset_path: proxectonos/xstorycloze_gl +output_type: multiple_choice +training_split: train +validation_split: test +doc_to_text: "{{[InputSentence1, InputSentence2, InputSentence3, InputSentence4]|join(' ')}}" +doc_to_target: "{{AnswerRightEnding-1}}" +doc_to_choice: "{{[RandomFifthSentenceQuiz1, RandomFifthSentenceQuiz2]}}" +should_decontaminate: true +doc_to_decontamination_query: "{{[InputSentence1, InputSentence2, InputSentence3, InputSentence4]|join(' ')}}" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 -- GitLab From c887796d245a489284a44ea57bf29e743aa56510 Mon Sep 17 00:00:00 2001 From: zxcvuser Date: Fri, 4 Oct 2024 15:38:11 +0200 Subject: [PATCH 116/194] Add new benchmark: Basque bench (#2153) * Add basque_bench * Add flores_eu group * Update _flores_common_yaml * Run linters, updated flores, mgsm, copa, and readme * Apply suggestions from code review Co-authored-by: Baber Abbasi <92168766+baberabb@users.noreply.github.com> --------- Co-authored-by: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/basque_bench/README.md | 88 ++++++++++++++ lm_eval/tasks/basque_bench/basque_bench.yaml | 18 +++ .../flores_eu/_flores_common_yaml | 27 ++++ .../flores_eu/create_yamls_flores_eu.py | 115 ++++++++++++++++++ .../basque_bench/flores_eu/flores_ca-eu.yaml | 7 ++ .../basque_bench/flores_eu/flores_de-eu.yaml | 7 ++ .../basque_bench/flores_eu/flores_en-eu.yaml | 7 ++ .../basque_bench/flores_eu/flores_es-eu.yaml | 7 ++ .../basque_bench/flores_eu/flores_eu-ca.yaml | 7 ++ .../basque_bench/flores_eu/flores_eu-de.yaml | 7 ++ .../basque_bench/flores_eu/flores_eu-en.yaml | 7 ++ .../basque_bench/flores_eu/flores_eu-es.yaml | 7 ++ .../basque_bench/flores_eu/flores_eu-fr.yaml | 7 ++ .../basque_bench/flores_eu/flores_eu-gl.yaml | 7 ++ .../basque_bench/flores_eu/flores_eu-it.yaml | 7 ++ .../basque_bench/flores_eu/flores_eu-pt.yaml | 7 ++ .../basque_bench/flores_eu/flores_eu.yaml | 24 ++++ .../basque_bench/flores_eu/flores_fr-eu.yaml | 7 ++ .../basque_bench/flores_eu/flores_gl-eu.yaml | 7 ++ .../basque_bench/flores_eu/flores_it-eu.yaml | 7 ++ .../basque_bench/flores_eu/flores_pt-eu.yaml | 7 ++ .../basque_bench/mgsm_cot_native_eu.yaml | 34 ++++++ .../tasks/basque_bench/mgsm_direct_eu.yaml | 39 ++++++ lm_eval/tasks/basque_bench/utils.py | 21 ++++ lm_eval/tasks/basque_bench/wnli_eu.yaml | 14 +++ lm_eval/tasks/basque_bench/xcopa_eu.yaml | 14 +++ 27 files changed, 507 insertions(+) create mode 100644 lm_eval/tasks/basque_bench/README.md create mode 100644 lm_eval/tasks/basque_bench/basque_bench.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/_flores_common_yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/create_yamls_flores_eu.py create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_ca-eu.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_de-eu.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_en-eu.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_es-eu.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_eu-ca.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_eu-de.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_eu-en.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_eu-es.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_eu-fr.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_eu-gl.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_eu-it.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_eu-pt.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_eu.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_fr-eu.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_gl-eu.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_it-eu.yaml create mode 100644 lm_eval/tasks/basque_bench/flores_eu/flores_pt-eu.yaml create mode 100644 lm_eval/tasks/basque_bench/mgsm_cot_native_eu.yaml create mode 100644 lm_eval/tasks/basque_bench/mgsm_direct_eu.yaml create mode 100644 lm_eval/tasks/basque_bench/utils.py create mode 100644 lm_eval/tasks/basque_bench/wnli_eu.yaml create mode 100644 lm_eval/tasks/basque_bench/xcopa_eu.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 5f6fa3e2..03a44bcf 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -18,6 +18,7 @@ | [arithmetic](arithmetic/README.md) | Tasks involving numerical computations and arithmetic reasoning. | English | | [asdiv](asdiv/README.md) | Tasks involving arithmetic and mathematical reasoning challenges. | English | | [babi](babi/README.md) | Tasks designed as question and answering challenges based on simulated stories. | English | +| [basque_bench](basque_bench/README.md) | Collection of tasks in Basque encompassing various evaluation areas. | Basque | | [basqueglue](basqueglue/README.md) | Tasks designed to evaluate language understanding in Basque language. | Basque | | [bbh](bbh/README.md) | Tasks focused on deep semantic understanding through hypothesization and reasoning. | English, German | | [belebele](belebele/README.md) | Language understanding tasks in a variety of languages and scripts. | Multiple (122 languages) | diff --git a/lm_eval/tasks/basque_bench/README.md b/lm_eval/tasks/basque_bench/README.md new file mode 100644 index 00000000..7b5f93c1 --- /dev/null +++ b/lm_eval/tasks/basque_bench/README.md @@ -0,0 +1,88 @@ +# BasqueBench + +### Paper + +BasqueBench is a benchmark for evaluating language models in Basque tasks. This is, it evaluates the ability of a language model to understand and generate Basque text. BasqueBench offers a combination of pre-existing, open datasets and datasets developed exclusivelly for this benchmark. All the details of BasqueBench will be published in a paper soon. + +The new evaluation datasets included in BasqueBench are: +| Task | Category | Homepage | +|:-------------:|:-----:|:-----:| +| MGSM_eu | Math | https://huggingface.co/datasets/HiTZ/MGSM-eu | +| WNLI_eu | Natural Language Inference | https://huggingface.co/datasets/HiTZ/wnli-eu | +| XCOPA_eu | Commonsense Reasoning | https://huggingface.co/datasets/HiTZ/XCOPA-eu | + +The datasets included in BasqueBench that have been made public in previous pubications are: + +| Task | Category | Paper title | Homepage | +|:-------------:|:-----:|:-------------:|:-----:| +| Belebele_eu | Reading Comprehension | [The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://arxiv.org/abs/2308.16884) | https://huggingface.co/datasets/facebook/belebele | +| EusExams | Question Answering | [Latxa: An Open Language Model and Evaluation Suite for Basque](https://arxiv.org/abs/2403.20266) | https://huggingface.co/datasets/HiTZ/EusExams | +| EusProficiency | Question Answering | [Latxa: An Open Language Model and Evaluation Suite for Basque](https://arxiv.org/abs/2403.20266) | https://huggingface.co/datasets/HiTZ/EusProficiency | +| EusReading | Reading Comprehension | [Latxa: An Open Language Model and Evaluation Suite for Basque](https://arxiv.org/abs/2403.20266) | https://huggingface.co/datasets/HiTZ/EusReading | +| EusTrivia | Question Answering | [Latxa: An Open Language Model and Evaluation Suite for Basque](https://arxiv.org/abs/2403.20266) | https://huggingface.co/datasets/HiTZ/EusTrivia | +| FLORES_eu | Translation | [No Language Left Behind: Scaling Human-Centered Machine Translation](https://arxiv.org/abs/2207.04672) | https://huggingface.co/datasets/facebook/flores | +| QNLIeu | Natural Language Inference | [BasqueGLUE: A Natural Language Understanding Benchmark for Basque](https://aclanthology.org/2022.lrec-1.172/) | https://huggingface.co/datasets/orai-nlp/basqueGLUE | +| XNLIeu | Natural Language Inference | [XNLIeu: a dataset for cross-lingual NLI in Basque](https://arxiv.org/abs/2404.06996) | https://huggingface.co/datasets/HiTZ/xnli-eu | +| XStoryCloze_eu | Commonsense Reasoning | [Few-shot Learning with Multilingual Generative Language Models](https://aclanthology.org/2022.emnlp-main.616/) | https://huggingface.co/datasets/juletxara/xstory_cloze | + + +### Citation +Paper for BasqueBench coming soon. + +### Groups and Tasks + +#### Groups + +- `basque_bench`: All tasks included in BasqueBench. +- `flores_eu`: All FLORES translation tasks from or to Basque. + +#### Tasks + +The following tasks evaluate tasks on BasqueBench dataset using various scoring methods. + - `belebele_eus_Latn` + - `eus_exams_eu` + - `eus_proficiency` + - `eus_reading` + - `eus_trivia` + - `flores_eu` + - `flores_eu-ca` + - `flores_eu-de` + - `flores_eu-en` + - `flores_eu-es` + - `flores_eu-fr` + - `flores_eu-gl` + - `flores_eu-it` + - `flores_eu-pt` + - `flores_ca-eu` + - `flores_de-eu` + - `flores_en-eu` + - `flores_es-eu` + - `flores_fr-eu` + - `flores_gl-eu` + - `flores_it-eu` + - `flores_pt-eu` + - `mgsm_direct_eu` + - `mgsm_native_cot_eu` + - `qnlieu` + - `wnli_eu` + - `xcopa_eu` + - `xnli_eu` + - `xnli_eu_native` + - `xstorycloze_eu` + +Some of these tasks are taken from benchmarks already available in LM Evaluation Harness. These are: +- `belebele_eus_Latn`: Belebele Basque +- `qnlieu`: From BasqueGLUE + + +### Checklist + +* [x] Is the task an existing benchmark in the literature? + * [ ] Have you referenced the original paper that introduced the task? + * [ ] If yes, does the original paper provide a reference implementation? + * [ ] Yes, original implementation contributed by author of the benchmark + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/basque_bench/basque_bench.yaml b/lm_eval/tasks/basque_bench/basque_bench.yaml new file mode 100644 index 00000000..f542d218 --- /dev/null +++ b/lm_eval/tasks/basque_bench/basque_bench.yaml @@ -0,0 +1,18 @@ +group: basque_bench +task: + - belebele_eus_Latn + - xstorycloze_eu + - flores_eu + - eus_reading + - eus_proficiency + - eus_trivia + - eus_exams_eu + - qnlieu + - xnli_eu + - xnli_eu_native + - wnli_eu + - xcopa_eu + - mgsm_direct_eu + - mgsm_native_cot_eu +metadata: + version: 1.0 diff --git a/lm_eval/tasks/basque_bench/flores_eu/_flores_common_yaml b/lm_eval/tasks/basque_bench/flores_eu/_flores_common_yaml new file mode 100644 index 00000000..dbbde071 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/_flores_common_yaml @@ -0,0 +1,27 @@ +tag: flores +dataset_path: facebook/flores +dataset_name: all +output_type: generate_until +#! The test split of flores is not publicly available! (See paper section 6.1) +training_split: dev +validation_split: dev +test_split: devtest +fewshot_split: dev +target_delimiter: '' +generation_kwargs: + until: + - "\n" +metric_list: + - metric: bleu + aggregation: bleu + higher_is_better: true + - metric: ter + aggregation: ter + higher_is_better: false + - metric: chrf + aggregation: chrf + higher_is_better: true +metadata: + version: 0.1 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/basque_bench/flores_eu/create_yamls_flores_eu.py b/lm_eval/tasks/basque_bench/flores_eu/create_yamls_flores_eu.py new file mode 100644 index 00000000..6a41e945 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/create_yamls_flores_eu.py @@ -0,0 +1,115 @@ +""" +Script to generate task YAMLs for the FLORES-200 dataset. +Based on `tasks/translation/utils.py`. +""" + +import argparse +import yaml +from langcodes import * +from itertools import * + +# utils +flatten = lambda l: list(itertools.chain(*l)) + +# constants +_LANGUAGES = [ +"ace_Arab", "bam_Latn", "dzo_Tibt", "hin_Deva", "khm_Khmr", "mag_Deva", "pap_Latn", "sot_Latn", "tur_Latn", +"ace_Latn", "ban_Latn", "ell_Grek", "hne_Deva", "kik_Latn", "mai_Deva", "pbt_Arab", "spa_Latn", "twi_Latn", +"acm_Arab", "bel_Cyrl", "eng_Latn", "hrv_Latn", "kin_Latn", "mal_Mlym", "pes_Arab", "srd_Latn", "tzm_Tfng", +"acq_Arab", "bem_Latn", "epo_Latn", "hun_Latn", "kir_Cyrl", "mar_Deva", "plt_Latn", "srp_Cyrl", "uig_Arab", +"aeb_Arab", "ben_Beng", "est_Latn", "hye_Armn", "kmb_Latn", "min_Arab", "pol_Latn", "ssw_Latn", "ukr_Cyrl", +"afr_Latn", "bho_Deva", "eus_Latn", "ibo_Latn", "kmr_Latn", "min_Latn", "por_Latn", "sun_Latn", "umb_Latn", +"ajp_Arab", "bjn_Arab", "ewe_Latn", "ilo_Latn", "knc_Arab", "mkd_Cyrl", "prs_Arab", "swe_Latn", "urd_Arab", +"aka_Latn", "bjn_Latn", "fao_Latn", "ind_Latn", "knc_Latn", "mlt_Latn", "quy_Latn", "swh_Latn", "uzn_Latn", +"als_Latn", "bod_Tibt", "fij_Latn", "isl_Latn", "kon_Latn", "mni_Beng", "ron_Latn", "szl_Latn", "vec_Latn", +"amh_Ethi", "bos_Latn", "fin_Latn", "ita_Latn", "kor_Hang", "mos_Latn", "run_Latn", "tam_Taml", "vie_Latn", +"apc_Arab", "bug_Latn", "fon_Latn", "jav_Latn", "lao_Laoo", "mri_Latn", "rus_Cyrl", "taq_Latn", "war_Latn", +"arb_Arab", "bul_Cyrl", "fra_Latn", "jpn_Jpan", "lij_Latn", "mya_Mymr", "sag_Latn", "taq_Tfng", "wol_Latn", +"arb_Latn", "cat_Latn", "fur_Latn", "kab_Latn", "lim_Latn", "nld_Latn", "san_Deva", "tat_Cyrl", "xho_Latn", +"ars_Arab", "ceb_Latn", "fuv_Latn", "kac_Latn", "lin_Latn", "nno_Latn", "sat_Olck", "tel_Telu", "ydd_Hebr", +"ary_Arab", "ces_Latn", "gaz_Latn", "kam_Latn", "lit_Latn", "nob_Latn", "scn_Latn", "tgk_Cyrl", "yor_Latn", +"arz_Arab", "cjk_Latn", "gla_Latn", "kan_Knda", "lmo_Latn", "npi_Deva", "shn_Mymr", "tgl_Latn", "yue_Hant", +"asm_Beng", "ckb_Arab", "gle_Latn", "kas_Arab", "ltg_Latn", "nso_Latn", "sin_Sinh", "tha_Thai", "zho_Hans", +"ast_Latn", "crh_Latn", "glg_Latn", "kas_Deva", "ltz_Latn", "nus_Latn", "slk_Latn", "tir_Ethi", "zho_Hant", +"awa_Deva", "cym_Latn", "grn_Latn", "kat_Geor", "lua_Latn", "nya_Latn", "slv_Latn", "tpi_Latn", "zsm_Latn", +"ayr_Latn", "dan_Latn", "guj_Gujr", "kaz_Cyrl", "lug_Latn", "oci_Latn", "smo_Latn", "tsn_Latn", "zul_Latn", +"azb_Arab", "deu_Latn", "hat_Latn", "kbp_Latn", "luo_Latn", "ory_Orya", "sna_Latn", "tso_Latn", +"azj_Latn", "dik_Latn", "hau_Latn", "kea_Latn", "lus_Latn", "pag_Latn", "snd_Arab", "tuk_Latn", +"bak_Cyrl", "dyu_Latn", "heb_Hebr", "khk_Cyrl", "lvs_Latn", "pan_Guru", "som_Latn", "tum_Latn" +] +LANGUAGE_PAIRS = [(a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1:]] + +LANGUAGES_OF_INTEREST = ["cat_Latn", "spa_Latn", "eng_Latn", "glg_Latn", "eus_Latn", "ita_Latn", "deu_Latn", "por_Latn", "fra_Latn"] +MAIN_LANG = "eus_Latn" +LANGUAGE_PAIRS = [(a, b) for (a, b) in LANGUAGE_PAIRS if a in LANGUAGES_OF_INTEREST and b in LANGUAGES_OF_INTEREST and MAIN_LANG in (a, b)] + +# auxiliary functions + +code_to_language_name = lambda code: Language.make(language=Language.get(code)["language"]).display_name() +code_to_short_name = lambda code: Language.get(code)["language"] +jinja_var = lambda s: "{{" + s + "}}" # wrapper to avoid having to escape { } in format strings + +def doc_to_text(src: str, tgt: str) -> str: + src_name, tgt_name = map(code_to_language_name, [src, tgt]) + + return f"""\ +{src_name} sentence: {jinja_var('sentence_' + src)} +{tgt_name} sentence:""" + +def doc_to_target(tgt: str) -> str: + + return f"{jinja_var('sentence_' + tgt)}" + +# main function + +def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: + """ + Generate a YAML file for each translation direction. + """ + + err = [] + for src, tgt in LANGUAGE_PAIRS: + + # do both translation directions for each lang pair + for src, tgt in [(src, tgt), (tgt, src)]: + lang_pair_name = f"{code_to_short_name(src)}-{code_to_short_name(tgt)}" + yaml_file_name = f"flores_{lang_pair_name}.yaml" + + try: + with open( f"{output_dir}/{yaml_file_name}", "w" if overwrite else "x", encoding="utf-8") as outfile: + print(f"Creating {yaml_file_name}...") + outfile.write("# File generated by `create-yamls.py`\n") + yaml.dump( + { +# "group": [f"{BENCH_NAME}_bench", f"{BENCH_NAME}_bench_flores"], +# "group": "flores_eu", + "include": "_flores_common_yaml", + "task": f"flores_{lang_pair_name}", + "doc_to_text": doc_to_text(src, tgt), + "doc_to_target": doc_to_target(tgt), + }, + outfile, + sort_keys=False, + ) + + except FileExistsError: + err.append(yaml_file_name) + + if len(err) > 0: + raise FileExistsError( + "Files were not created because they already exist:" + f" {', '.join(err)}" + "\nUse flag --overwrite to overwrite them." + ) + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--overwrite", default=False, action="store_true", help="Overwrite files if they already exist") + parser.add_argument( "--output-dir", default=".", help="Directory to write yaml files to" ) + args = parser.parse_args() + + gen_lang_yamls(output_dir=args.output_dir, overwrite=args.overwrite) + +if __name__ == "__main__": + main() diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_ca-eu.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_ca-eu.yaml new file mode 100644 index 00000000..48ffe7bf --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_ca-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-eu +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_de-eu.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_de-eu.yaml new file mode 100644 index 00000000..16bb7772 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_de-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_de-eu +doc_to_text: 'German sentence: {{sentence_deu_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_en-eu.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_en-eu.yaml new file mode 100644 index 00000000..d26edaca --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_en-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_en-eu +doc_to_text: 'English sentence: {{sentence_eng_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_es-eu.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_es-eu.yaml new file mode 100644 index 00000000..576bb0e2 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_es-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-eu +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_eu-ca.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-ca.yaml new file mode 100644 index 00000000..c8be6ee9 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-ca +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_eu-de.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-de.yaml new file mode 100644 index 00000000..4f5735a6 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-de.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-de +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + German sentence:' +doc_to_target: '{{sentence_deu_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_eu-en.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-en.yaml new file mode 100644 index 00000000..5d9eadfb --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-en.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-en +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + English sentence:' +doc_to_target: '{{sentence_eng_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_eu-es.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-es.yaml new file mode 100644 index 00000000..efb5200d --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-es +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_eu-fr.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-fr.yaml new file mode 100644 index 00000000..a9ce32a8 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-fr.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-fr +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + French sentence:' +doc_to_target: '{{sentence_fra_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_eu-gl.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-gl.yaml new file mode 100644 index 00000000..db762cf7 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-gl +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_eu-it.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-it.yaml new file mode 100644 index 00000000..91a77f0d --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-it.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-it +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + Italian sentence:' +doc_to_target: '{{sentence_ita_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_eu-pt.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-pt.yaml new file mode 100644 index 00000000..f230a732 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_eu-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-pt +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_eu.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_eu.yaml new file mode 100644 index 00000000..e389bddf --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_eu.yaml @@ -0,0 +1,24 @@ +group: flores_eu +task: + - flores_es-eu + - flores_eu-es + - flores_en-eu + - flores_eu-en + - flores_eu-pt + - flores_pt-eu + - flores_eu-it + - flores_it-eu + - flores_eu-fr + - flores_fr-eu + - flores_eu-ca + - flores_ca-eu + - flores_eu-gl + - flores_gl-eu + - flores_eu-de + - flores_de-eu +aggregate_metric_list: + - metric: bleu + aggregation: mean + weight_by_size: false +metadata: + version: 1.0 diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_fr-eu.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_fr-eu.yaml new file mode 100644 index 00000000..f15b672e --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_fr-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_fr-eu +doc_to_text: 'French sentence: {{sentence_fra_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_gl-eu.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_gl-eu.yaml new file mode 100644 index 00000000..08fafe08 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_gl-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-eu +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_it-eu.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_it-eu.yaml new file mode 100644 index 00000000..7db4ec25 --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_it-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_it-eu +doc_to_text: 'Italian sentence: {{sentence_ita_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/basque_bench/flores_eu/flores_pt-eu.yaml b/lm_eval/tasks/basque_bench/flores_eu/flores_pt-eu.yaml new file mode 100644 index 00000000..6b0169bc --- /dev/null +++ b/lm_eval/tasks/basque_bench/flores_eu/flores_pt-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-eu +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/basque_bench/mgsm_cot_native_eu.yaml b/lm_eval/tasks/basque_bench/mgsm_cot_native_eu.yaml new file mode 100644 index 00000000..9de325bc --- /dev/null +++ b/lm_eval/tasks/basque_bench/mgsm_cot_native_eu.yaml @@ -0,0 +1,34 @@ +task: mgsm_native_cot_eu +dataset_path: HiTZ/MGSM-eu +dataset_name: null +doc_to_target: '{% if answer is not none %}{{answer[27:]}}{% else %}{{answer_number|string}}{%endif %}' +doc_to_text: '{% if answer is not none %}{{question+"\nErantzuna urratsez urrats:"}}{% else %}{{"Galdera: "+question+"\nErantzuna urratsez urrats:"}}{% endif %}' +output_type: generate_until +training_split: train +test_split: test +target_delimiter: " " +generation_kwargs: + until: + - "\n\n" + - "\n" + - "Galdera:" + - + - <|im_end|> + do_sample: false + temperature: 0.0 +filter_list: + - name: "get-answer" + filter: + - function: "regex" + regex_pattern: "Erantzuna [$%]? ?(-?[0-9]+([ .,][0-9.,]+)?) ?[$%]? da" + - function: "take_first" +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: true + regexes_to_ignore: + - " " +metadata: + version: 1.0 diff --git a/lm_eval/tasks/basque_bench/mgsm_direct_eu.yaml b/lm_eval/tasks/basque_bench/mgsm_direct_eu.yaml new file mode 100644 index 00000000..f7da3317 --- /dev/null +++ b/lm_eval/tasks/basque_bench/mgsm_direct_eu.yaml @@ -0,0 +1,39 @@ +task: mgsm_direct_eu +dataset_path: HiTZ/MGSM-eu +dataset_name: null +doc_to_target: '{{answer_number|string}}' +doc_to_text: '{% if answer is not none %}{{question+"\nErantzuna:"}}{% else %}{{"Galdera: "+question+"\nErantzuna:"}}{% endif %}' +output_type: generate_until +training_split: train +test_split: test +target_delimiter: " " +generation_kwargs: + until: + - "\n\n" + - "\n" + - "Galdera:" + - + - <|im_end|> + do_sample: false + temperature: 0.0 +filter_list: + - name: remove_whitespace + filter: + - function: remove_whitespace + - function: take_first + - name: flexible-extract + filter: + - function: regex + group_select: -1 + regex_pattern: (-?[0-9]+([ .,][0-9.,]+)?) + - function: take_first +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: true + regexes_to_ignore: + - " " +metadata: + version: 1.0 diff --git a/lm_eval/tasks/basque_bench/utils.py b/lm_eval/tasks/basque_bench/utils.py new file mode 100644 index 00000000..1d5460b5 --- /dev/null +++ b/lm_eval/tasks/basque_bench/utils.py @@ -0,0 +1,21 @@ +from functools import partial + + +# ~~~~~~~~~~~ XCOPA ~~~~~~~~~~~ # + +xcopa_connectors = {"cause": " Izan ere,", "effect": " Beraz,"} + + +def xcopa_doc_to_text(doc): + conn = xcopa_connectors[doc["question"]] + return doc["premise"].strip() + f"{conn}" + + +def xcopa_doc_to_choice(doc): + def convert_choice(choice): + return choice[0].lower() + choice[1:] + + return [convert_choice(doc["choice1"]), convert_choice(doc["choice2"])] + + +# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # diff --git a/lm_eval/tasks/basque_bench/wnli_eu.yaml b/lm_eval/tasks/basque_bench/wnli_eu.yaml new file mode 100644 index 00000000..a3684e31 --- /dev/null +++ b/lm_eval/tasks/basque_bench/wnli_eu.yaml @@ -0,0 +1,14 @@ +task: wnli_eu +dataset_path: HiTZ/wnli-eu +dataset_name: null +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: null +doc_to_text: "{{sentence1}}\nGaldera: {{sentence2}} Egia edo Gezurra?\nErantzuna:" +doc_to_target: label +doc_to_choice: ["Gezurra", "Egia"] +metric_list: + - metric: acc +metadata: + version: 1.0 diff --git a/lm_eval/tasks/basque_bench/xcopa_eu.yaml b/lm_eval/tasks/basque_bench/xcopa_eu.yaml new file mode 100644 index 00000000..83e50403 --- /dev/null +++ b/lm_eval/tasks/basque_bench/xcopa_eu.yaml @@ -0,0 +1,14 @@ +task: xcopa_eu +dataset_path: HiTZ/XCOPA-eu +dataset_name: null +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +doc_to_text: !function utils.xcopa_doc_to_text +doc_to_target: label +doc_to_choice: !function utils.xcopa_doc_to_choice +metric_list: + - metric: acc +metadata: + version: 1.0 -- GitLab From cb069004a539409c488a0889ef147a369fbeac3c Mon Sep 17 00:00:00 2001 From: zxcvuser Date: Fri, 4 Oct 2024 15:38:53 +0200 Subject: [PATCH 117/194] Add new benchmark: Catalan bench (#2154) * Add catalan_bench * added flores_ca.yaml * Updated some task groupings and readme * Fix create_yamls_flores_ca.py --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- lm_eval/tasks/README.md | 2 +- lm_eval/tasks/catalan_bench/README.md | 121 +++++++ .../tasks/catalan_bench/_arc_ca_common_yaml | 20 ++ .../tasks/catalan_bench/_cabreu_common_yaml | 17 + .../tasks/catalan_bench/arc_ca_challenge.yaml | 3 + lm_eval/tasks/catalan_bench/arc_ca_easy.yaml | 3 + .../catalan_bench/cabreu_abstractive.yaml | 8 + .../catalan_bench/cabreu_extractive.yaml | 8 + .../tasks/catalan_bench/cabreu_extreme.yaml | 8 + .../tasks/catalan_bench/catalan_bench.yaml | 25 ++ lm_eval/tasks/catalan_bench/catalanqa.yaml | 25 ++ lm_eval/tasks/catalan_bench/catcola.yaml | 14 + lm_eval/tasks/catalan_bench/copa_ca.yaml | 17 + lm_eval/tasks/catalan_bench/coqcat.yaml | 23 ++ .../flores_ca/_flores_common_yaml | 25 ++ .../flores_ca/create_yamls_flores_ca.py | 334 ++++++++++++++++++ .../catalan_bench/flores_ca/flores_ca-de.yaml | 7 + .../catalan_bench/flores_ca/flores_ca-en.yaml | 7 + .../catalan_bench/flores_ca/flores_ca-es.yaml | 7 + .../catalan_bench/flores_ca/flores_ca-eu.yaml | 7 + .../catalan_bench/flores_ca/flores_ca-fr.yaml | 7 + .../catalan_bench/flores_ca/flores_ca-gl.yaml | 7 + .../catalan_bench/flores_ca/flores_ca-it.yaml | 7 + .../catalan_bench/flores_ca/flores_ca-pt.yaml | 7 + .../catalan_bench/flores_ca/flores_ca.yaml | 24 ++ .../catalan_bench/flores_ca/flores_de-ca.yaml | 7 + .../catalan_bench/flores_ca/flores_en-ca.yaml | 7 + .../catalan_bench/flores_ca/flores_es-ca.yaml | 7 + .../catalan_bench/flores_ca/flores_eu-ca.yaml | 7 + .../catalan_bench/flores_ca/flores_fr-ca.yaml | 7 + .../catalan_bench/flores_ca/flores_gl-ca.yaml | 7 + .../catalan_bench/flores_ca/flores_it-ca.yaml | 7 + .../catalan_bench/flores_ca/flores_pt-ca.yaml | 7 + .../tasks/catalan_bench/mgsm_direct_ca.yaml | 25 ++ .../tasks/catalan_bench/openbookqa_ca.yaml | 20 ++ lm_eval/tasks/catalan_bench/parafraseja.yaml | 17 + lm_eval/tasks/catalan_bench/paws_ca.yaml | 18 + .../phrases_va/_phrases_va_common.yaml | 24 ++ .../phrases_va/phrases_ca-va.yaml | 7 + .../phrases_va/phrases_va-ca.yaml | 7 + lm_eval/tasks/catalan_bench/piqa_ca.yaml | 21 ++ lm_eval/tasks/catalan_bench/siqa_ca.yaml | 16 + lm_eval/tasks/catalan_bench/teca.yaml | 18 + lm_eval/tasks/catalan_bench/utils.py | 142 ++++++++ lm_eval/tasks/catalan_bench/wnli_ca.yaml | 14 + lm_eval/tasks/catalan_bench/xnli_ca.yaml | 19 + lm_eval/tasks/catalan_bench/xquad_ca.yaml | 24 ++ .../tasks/catalan_bench/xstorycloze_ca.yaml | 17 + 48 files changed, 1177 insertions(+), 1 deletion(-) create mode 100644 lm_eval/tasks/catalan_bench/README.md create mode 100644 lm_eval/tasks/catalan_bench/_arc_ca_common_yaml create mode 100644 lm_eval/tasks/catalan_bench/_cabreu_common_yaml create mode 100644 lm_eval/tasks/catalan_bench/arc_ca_challenge.yaml create mode 100644 lm_eval/tasks/catalan_bench/arc_ca_easy.yaml create mode 100644 lm_eval/tasks/catalan_bench/cabreu_abstractive.yaml create mode 100644 lm_eval/tasks/catalan_bench/cabreu_extractive.yaml create mode 100644 lm_eval/tasks/catalan_bench/cabreu_extreme.yaml create mode 100644 lm_eval/tasks/catalan_bench/catalan_bench.yaml create mode 100644 lm_eval/tasks/catalan_bench/catalanqa.yaml create mode 100644 lm_eval/tasks/catalan_bench/catcola.yaml create mode 100644 lm_eval/tasks/catalan_bench/copa_ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/coqcat.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/_flores_common_yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/create_yamls_flores_ca.py create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_ca-de.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_ca-en.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_ca-es.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_ca-eu.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_ca-fr.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_ca-gl.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_ca-it.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_ca-pt.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_de-ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_en-ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_es-ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_eu-ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_fr-ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_gl-ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_it-ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/flores_ca/flores_pt-ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/mgsm_direct_ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/openbookqa_ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/parafraseja.yaml create mode 100644 lm_eval/tasks/catalan_bench/paws_ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/phrases_va/_phrases_va_common.yaml create mode 100644 lm_eval/tasks/catalan_bench/phrases_va/phrases_ca-va.yaml create mode 100644 lm_eval/tasks/catalan_bench/phrases_va/phrases_va-ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/piqa_ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/siqa_ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/teca.yaml create mode 100644 lm_eval/tasks/catalan_bench/utils.py create mode 100644 lm_eval/tasks/catalan_bench/wnli_ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/xnli_ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/xquad_ca.yaml create mode 100644 lm_eval/tasks/catalan_bench/xstorycloze_ca.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 03a44bcf..83977a47 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -26,6 +26,7 @@ | [bertaqa](bertaqa/README.md) | Local Basque cultural trivia QA tests in English and Basque languages. | English, Basque, Basque (MT) | | [bigbench](bigbench/README.md) | Broad tasks from the BIG-bench benchmark designed to push the boundaries of large models. | Multiple | | [blimp](blimp/README.md) | Tasks testing grammatical phenomena to evaluate language model's linguistic capabilities. | English | +| [catalan_bench](catalan_bench/README.md) | Collection of tasks in Catalan encompassing various evaluation areas. | Catalan | | [ceval](ceval/README.md) | Tasks that evaluate language understanding and reasoning in an educational context. | Chinese | | [cmmlu](cmmlu/README.md) | Multi-subject multiple choice question tasks for comprehensive academic assessment. | Chinese | | code_x_glue | Tasks that involve understanding and generating code across multiple programming languages. | Go, Java, JS, PHP, Python, Ruby | @@ -125,4 +126,3 @@ | [xnli_eu](xnli_eu/README.md) | Cross-lingual Natural Language Inference tasks in Basque. | Basque | | [xstorycloze](xstorycloze/README.md) | Cross-lingual narrative understanding tasks to predict story endings in multiple languages. | Russian, Simplified Chinese, Spanish, Arabic, Hindi, Indonesian, Telugu, Swahili, Basque, Burmese | | [xwinograd](xwinograd/README.md) | Cross-lingual Winograd schema tasks for coreference resolution in multiple languages. | English, French, Japanese, Portuguese, Russian, Chinese | - diff --git a/lm_eval/tasks/catalan_bench/README.md b/lm_eval/tasks/catalan_bench/README.md new file mode 100644 index 00000000..73dec948 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/README.md @@ -0,0 +1,121 @@ +# CatalanBench + +### Paper + +CatalanBench is a benchmark for evaluating language models in Catalan tasks. This is, it evaluates the ability of a language model to understand and generate Catalan text. CatalanBench offers a combination of pre-existing, open datasets and datasets developed exclusivelly for this benchmark. All the details of CatalanBench will be published in a paper soon. + +The new evaluation datasets included in CatalanBench are: +| Task | Category | Homepage | +|:-------------:|:-----:|:-----:| +| ARC_ca | Question Answering | https://huggingface.co/datasets/projecte-aina/arc_ca | +| MGSM_ca | Math | https://huggingface.co/datasets/projecte-aina/mgsm_ca | +| OpenBookQA_ca | Question Answering | https://huggingface.co/datasets/projecte-aina/openbookqa_ca | +| Parafraseja | Paraphrasing | https://huggingface.co/datasets/projecte-aina/Parafraseja | +| PIQA_ca | Question Answering | https://huggingface.co/datasets/projecte-aina/piqa_ca | +| SIQA_ca | Question Answering | https://huggingface.co/datasets/projecte-aina/siqa_ca | +| XStoryCloze_ca | Commonsense Reasoning | https://huggingface.co/datasets/projecte-aina/xstorycloze_ca | + +The datasets included in CatalanBench that have been made public in previous pubications are: + +| Task | Category | Paper title | Homepage | +|:-------------:|:-----:|:-------------:|:-----:| +| Belebele_ca | Reading Comprehension | [The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://arxiv.org/abs/2308.16884) | https://huggingface.co/datasets/facebook/belebele | +| caBREU | Summarization | [Building a Data Infrastructure for a Mid-Resource Language: The Case of Catalan](https://aclanthology.org/2024.lrec-main.231/) | https://huggingface.co/datasets/projecte-aina/caBreu | +| CatalanQA | Question Answering | [Building a Data Infrastructure for a Mid-Resource Language: The Case of Catalan](https://aclanthology.org/2024.lrec-main.231/) | https://huggingface.co/datasets/projecte-aina/catalanqa | +| CatCoLA | Linguistic Acceptability | CatCoLA: Catalan Corpus of Linguistic Acceptability | https://huggingface.co/datasets/nbel/CatCoLA | +| COPA-ca | Commonsense Reasoning | [Building a Data Infrastructure for a Mid-Resource Language: The Case of Catalan](https://aclanthology.org/2024.lrec-main.231/) | https://huggingface.co/datasets/projecte-aina/COPA-ca | +| CoQCat | Question Answering | [Building a Data Infrastructure for a Mid-Resource Language: The Case of Catalan](https://aclanthology.org/2024.lrec-main.231/) | https://huggingface.co/datasets/projecte-aina/CoQCat | +| FLORES_ca | Translation | [The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation](https://arxiv.org/abs/2106.03193) | https://huggingface.co/datasets/facebook/flores | +| PAWS-ca | Paraphrasing | [Building a Data Infrastructure for a Mid-Resource Language: The Case of Catalan](https://aclanthology.org/2024.lrec-main.231/) | https://huggingface.co/datasets/projecte-aina/PAWS-ca | +| TE-ca | Natural Language Inference | [Building a Data Infrastructure for a Mid-Resource Language: The Case of Catalan](https://aclanthology.org/2024.lrec-main.231/) | https://huggingface.co/datasets/projecte-aina/teca | +| VeritasQA_ca | Truthfulness | VeritasQA: A Truthfulness Benchmark Aimed at Multilingual Transferability | TBA | +| WNLI-ca | Natural Language Inference | [Building a Data Infrastructure for a Mid-Resource Language: The Case of Catalan](https://aclanthology.org/2024.lrec-main.231/) | https://huggingface.co/datasets/projecte-aina/wnli-ca | +| XNLI-ca | Natural Language Inference | [Building a Data Infrastructure for a Mid-Resource Language: The Case of Catalan](https://aclanthology.org/2024.lrec-main.231/) | https://huggingface.co/datasets/projecte-aina/xnli-ca | +| XQuAD-ca | Question Answering | [Building a Data Infrastructure for a Mid-Resource Language: The Case of Catalan](https://aclanthology.org/2024.lrec-main.231/) | https://huggingface.co/datasets/projecte-aina/xquad-ca | + + +### Citation +Paper for CatalanBench coming soon. + + + +### Groups and Tasks + +#### Groups + +- `catalan_bench`: All tasks included in CatalanBench. +- `flores_ca`: All FLORES translation tasks from or to Catalan. + +#### Tags +- `cabreu`: Three CaBREU tasks for each type of summary (extractive, abstractive and extreme). +- `phrases_va`: Two Phrases_va tasks for language adaptation between Catalan and Valencian. + +#### Tasks + +The following tasks evaluate tasks on CatalanBench dataset using various scoring methods. + - `arc_ca_challenge` + - `arc_ca_easy` + - `belebele_cat_Latn` + - `cabreu` + - `catalanqa` + - `catcola` + - `copa_ca` + - `coqcat` + - `flores_ca` + - `flores_ca-de` + - `flores_ca-en` + - `flores_ca-es` + - `flores_ca-eu` + - `flores_ca-fr` + - `flores_ca-gl` + - `flores_ca-it` + - `flores_ca-pt` + - `flores_de-ca` + - `flores_en-ca` + - `flores_es-ca` + - `flores_eu-ca` + - `flores_fr-ca` + - `flores_gl-ca` + - `flores_it-ca` + - `flores_pt-ca` + - `mgsm_direct_ca` + - `openbookqa_ca` + - `parafraseja` + - `paws_ca` + - `phrases_ca` + - `piqa_ca` + - `siqa_ca` + - `teca` + - `veritasqa_gen_ca` + - `veritasqa_mc1_ca` + - `veritasqa_mc2_ca` + - `wnli_ca` + - `xnli_ca` + - `xquad_ca` + - `xstorycloze_ca` + +Some of these tasks are taken from benchmarks already available in LM Evaluation Harness. These are: +- `belebele_cat_Latn`: Belebele Catalan + + +### Checklist + +* [x] Is the task an existing benchmark in the literature? + * [ ] Have you referenced the original paper that introduced the task? + * [ ] If yes, does the original paper provide a reference implementation? + * [ ] Yes, original implementation contributed by author of the benchmark + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/catalan_bench/_arc_ca_common_yaml b/lm_eval/tasks/catalan_bench/_arc_ca_common_yaml new file mode 100644 index 00000000..b89290eb --- /dev/null +++ b/lm_eval/tasks/catalan_bench/_arc_ca_common_yaml @@ -0,0 +1,20 @@ +tag: arc_ca +dataset_path: projecte-aina/arc_ca +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +doc_to_text: "Pregunta: {{question}}\nResposta:" +doc_to_target: "{{choices.label.index(answerKey)}}" +doc_to_choice: "{{choices.text}}" +should_decontaminate: true +doc_to_decontamination_query: "Pregunta: {{question}}\nResposta:" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/_cabreu_common_yaml b/lm_eval/tasks/catalan_bench/_cabreu_common_yaml new file mode 100644 index 00000000..c66e8bc4 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/_cabreu_common_yaml @@ -0,0 +1,17 @@ +tag: cabreu +dataset_path: projecte-aina/caBreu +dataset_name: null +output_type: generate_until +test_split: test +training_split: train +validation_split: validation +process_docs: !function utils.process_doc_cabreu +metric_list: + - metric: bleu + aggregation: bleu + higher_is_better: true + - metric: !function utils.rouge1 + aggregation: !function utils.rouge1_agg + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/arc_ca_challenge.yaml b/lm_eval/tasks/catalan_bench/arc_ca_challenge.yaml new file mode 100644 index 00000000..9d7a9c84 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/arc_ca_challenge.yaml @@ -0,0 +1,3 @@ +task: arc_ca_challenge +dataset_name: ARC-Challenge +include: _arc_ca_common_yaml diff --git a/lm_eval/tasks/catalan_bench/arc_ca_easy.yaml b/lm_eval/tasks/catalan_bench/arc_ca_easy.yaml new file mode 100644 index 00000000..67b28fd6 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/arc_ca_easy.yaml @@ -0,0 +1,3 @@ +task: arc_ca_easy +dataset_name: ARC-Easy +include: _arc_ca_common_yaml diff --git a/lm_eval/tasks/catalan_bench/cabreu_abstractive.yaml b/lm_eval/tasks/catalan_bench/cabreu_abstractive.yaml new file mode 100644 index 00000000..930ba28a --- /dev/null +++ b/lm_eval/tasks/catalan_bench/cabreu_abstractive.yaml @@ -0,0 +1,8 @@ +include: _cabreu_common_yaml +task: cabreu_abstractive +description: "Examina el text següent i genera'n un resum abstractiu, expressant el significat del text original d'una manera més natural i concisa.\n" +doc_to_text: >- + Text: {{content}} + + Resum: +doc_to_target: '{{summaries["abstractive"]["a1"]}}' diff --git a/lm_eval/tasks/catalan_bench/cabreu_extractive.yaml b/lm_eval/tasks/catalan_bench/cabreu_extractive.yaml new file mode 100644 index 00000000..e5f3dd4d --- /dev/null +++ b/lm_eval/tasks/catalan_bench/cabreu_extractive.yaml @@ -0,0 +1,8 @@ +include: _cabreu_common_yaml +task: cabreu_extractive +description: "Examina el text següent i genera'n un resum extractiu, utilitzant les frases o oracions més rellevants del text original.\n" +doc_to_text: >- + Text: {{content}} + + Resum: +doc_to_target: '{{summaries["extractive"]["a1"]}}' diff --git a/lm_eval/tasks/catalan_bench/cabreu_extreme.yaml b/lm_eval/tasks/catalan_bench/cabreu_extreme.yaml new file mode 100644 index 00000000..98efbe9c --- /dev/null +++ b/lm_eval/tasks/catalan_bench/cabreu_extreme.yaml @@ -0,0 +1,8 @@ +include: _cabreu_common_yaml +task: cabreu_extreme +description: "Examina el text següent i genera'n un resum que sigui el més concís possible i que preservi el significat del text original.\n" +doc_to_text: >- + Text: {{content}} + + Resum: +doc_to_target: '{{summaries["extreme"]["a1"]}}' diff --git a/lm_eval/tasks/catalan_bench/catalan_bench.yaml b/lm_eval/tasks/catalan_bench/catalan_bench.yaml new file mode 100644 index 00000000..1f1f09ec --- /dev/null +++ b/lm_eval/tasks/catalan_bench/catalan_bench.yaml @@ -0,0 +1,25 @@ +group: catalan_bench +task: + - belebele_cat_Latn + - xnli_ca + - catcola + - copa_ca + - openbookqa_ca + - parafraseja + - paws_ca + - piqa_ca + - siqa_ca + - teca + - wnli_ca + - arc_ca_easy + - arc_ca_challenge + - xstorycloze_ca + - xquad_ca + - catalanqa + - coqcat + - flores_ca + - cabreu + - mgsm_direct_ca + - phrases_va +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/catalanqa.yaml b/lm_eval/tasks/catalan_bench/catalanqa.yaml new file mode 100644 index 00000000..926cdfa1 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/catalanqa.yaml @@ -0,0 +1,25 @@ +task: catalanqa +dataset_path: projecte-aina/catalanqa +dataset_name: null +output_type: generate_until +training_split: train +validation_split: validation +test_split: test +doc_to_text: "Context: {{context}}\n\nPregunta: {{question}}\n\nResposta:" +doc_to_target: '{{answers[0]["text"]}}' +target_delimiter: ' ' +process_results: !function utils.process_results_qa +generation_kwargs: + until: + - "\n" + do_sample: false + temperature: 0.0 +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + - metric: f1 + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/catcola.yaml b/lm_eval/tasks/catalan_bench/catcola.yaml new file mode 100644 index 00000000..121b5e7f --- /dev/null +++ b/lm_eval/tasks/catalan_bench/catcola.yaml @@ -0,0 +1,14 @@ +task: catcola +dataset_path: nbel/CatCoLA +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: null +doc_to_text: "{{Sentence}}\nPregunta: Té sentit aquesta frase?\nResposta:" +doc_to_target: label +doc_to_choice: ["no", "sí"] +metric_list: + - metric: mcc + - metric: acc +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/copa_ca.yaml b/lm_eval/tasks/catalan_bench/copa_ca.yaml new file mode 100644 index 00000000..d376ad3a --- /dev/null +++ b/lm_eval/tasks/catalan_bench/copa_ca.yaml @@ -0,0 +1,17 @@ +task: copa_ca +dataset_path: projecte-aina/COPA-ca +dataset_name: null +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: test +process_docs: !function utils.process_docs_copa_ca +doc_to_text: '{{premise[:-1].strip() + " " + {"cause": "perquè", "effect": "i per tant"}[question]}}' +doc_to_target: '{{choice1 if label == 0 else choice2}}' +doc_to_choice: '{{[choice1, choice2]}}' +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/coqcat.yaml b/lm_eval/tasks/catalan_bench/coqcat.yaml new file mode 100644 index 00000000..95145a74 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/coqcat.yaml @@ -0,0 +1,23 @@ +task: coqcat +dataset_path: projecte-aina/CoQCat +output_type: generate_until +training_split: train +validation_split: validation +test_split: test +doc_to_text: '{{story+"\n\n"}}{% for i in range(questions|length-1) %}{{"Q: "+questions[i]+"\n\n"+"A: "+answers["input_text"][i]+"\n\n"}}{% endfor %}{{"Q: "+questions[-1]+"\n\n"+"A:"}}' +doc_to_target: '{{ answers["input_text"][questions|length - 1] }}' +process_results: !function utils.process_results_coqcat +should_decontaminate: true +doc_to_decontamination_query: "{{story}} {{question.input_text|join('\n')}}" +generation_kwargs: + until: + - "\nQ:" +metric_list: + - metric: "em" + aggregation: mean + higher_is_better: true + - metric: "f1" + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/flores_ca/_flores_common_yaml b/lm_eval/tasks/catalan_bench/flores_ca/_flores_common_yaml new file mode 100644 index 00000000..59a9b14a --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/_flores_common_yaml @@ -0,0 +1,25 @@ +dataset_path: facebook/flores +dataset_name: all +output_type: generate_until +training_split: dev +validation_split: dev +test_split: devtest +fewshot_split: dev +target_delimiter: '' +generation_kwargs: + until: + - "\n" +metric_list: + - metric: bleu + aggregation: bleu + higher_is_better: true + - metric: ter + aggregation: ter + higher_is_better: false + - metric: chrf + aggregation: chrf + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/catalan_bench/flores_ca/create_yamls_flores_ca.py b/lm_eval/tasks/catalan_bench/flores_ca/create_yamls_flores_ca.py new file mode 100644 index 00000000..6125b972 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/create_yamls_flores_ca.py @@ -0,0 +1,334 @@ +""" +Script to generate task YAMLs for the FLORES-200 dataset. +Based on `tasks/translation/utils.py`. +""" + +import argparse + +import yaml +from langcodes import Language + + +# constants +_LANGUAGES = [ + "ace_Arab", + "bam_Latn", + "dzo_Tibt", + "hin_Deva", + "khm_Khmr", + "mag_Deva", + "pap_Latn", + "sot_Latn", + "tur_Latn", + "ace_Latn", + "ban_Latn", + "ell_Grek", + "hne_Deva", + "kik_Latn", + "mai_Deva", + "pbt_Arab", + "spa_Latn", + "twi_Latn", + "acm_Arab", + "bel_Cyrl", + "eng_Latn", + "hrv_Latn", + "kin_Latn", + "mal_Mlym", + "pes_Arab", + "srd_Latn", + "tzm_Tfng", + "acq_Arab", + "bem_Latn", + "epo_Latn", + "hun_Latn", + "kir_Cyrl", + "mar_Deva", + "plt_Latn", + "srp_Cyrl", + "uig_Arab", + "aeb_Arab", + "ben_Beng", + "est_Latn", + "hye_Armn", + "kmb_Latn", + "min_Arab", + "pol_Latn", + "ssw_Latn", + "ukr_Cyrl", + "afr_Latn", + "bho_Deva", + "eus_Latn", + "ibo_Latn", + "kmr_Latn", + "min_Latn", + "por_Latn", + "sun_Latn", + "umb_Latn", + "ajp_Arab", + "bjn_Arab", + "ewe_Latn", + "ilo_Latn", + "knc_Arab", + "mkd_Cyrl", + "prs_Arab", + "swe_Latn", + "urd_Arab", + "aka_Latn", + "bjn_Latn", + "fao_Latn", + "ind_Latn", + "knc_Latn", + "mlt_Latn", + "quy_Latn", + "swh_Latn", + "uzn_Latn", + "als_Latn", + "bod_Tibt", + "fij_Latn", + "isl_Latn", + "kon_Latn", + "mni_Beng", + "ron_Latn", + "szl_Latn", + "vec_Latn", + "amh_Ethi", + "bos_Latn", + "fin_Latn", + "ita_Latn", + "kor_Hang", + "mos_Latn", + "run_Latn", + "tam_Taml", + "vie_Latn", + "apc_Arab", + "bug_Latn", + "fon_Latn", + "jav_Latn", + "lao_Laoo", + "mri_Latn", + "rus_Cyrl", + "taq_Latn", + "war_Latn", + "arb_Arab", + "bul_Cyrl", + "fra_Latn", + "jpn_Jpan", + "lij_Latn", + "mya_Mymr", + "sag_Latn", + "taq_Tfng", + "wol_Latn", + "arb_Latn", + "cat_Latn", + "fur_Latn", + "kab_Latn", + "lim_Latn", + "nld_Latn", + "san_Deva", + "tat_Cyrl", + "xho_Latn", + "ars_Arab", + "ceb_Latn", + "fuv_Latn", + "kac_Latn", + "lin_Latn", + "nno_Latn", + "sat_Olck", + "tel_Telu", + "ydd_Hebr", + "ary_Arab", + "ces_Latn", + "gaz_Latn", + "kam_Latn", + "lit_Latn", + "nob_Latn", + "scn_Latn", + "tgk_Cyrl", + "yor_Latn", + "arz_Arab", + "cjk_Latn", + "gla_Latn", + "kan_Knda", + "lmo_Latn", + "npi_Deva", + "shn_Mymr", + "tgl_Latn", + "yue_Hant", + "asm_Beng", + "ckb_Arab", + "gle_Latn", + "kas_Arab", + "ltg_Latn", + "nso_Latn", + "sin_Sinh", + "tha_Thai", + "zho_Hans", + "ast_Latn", + "crh_Latn", + "glg_Latn", + "kas_Deva", + "ltz_Latn", + "nus_Latn", + "slk_Latn", + "tir_Ethi", + "zho_Hant", + "awa_Deva", + "cym_Latn", + "grn_Latn", + "kat_Geor", + "lua_Latn", + "nya_Latn", + "slv_Latn", + "tpi_Latn", + "zsm_Latn", + "ayr_Latn", + "dan_Latn", + "guj_Gujr", + "kaz_Cyrl", + "lug_Latn", + "oci_Latn", + "smo_Latn", + "tsn_Latn", + "zul_Latn", + "azb_Arab", + "deu_Latn", + "hat_Latn", + "kbp_Latn", + "luo_Latn", + "ory_Orya", + "sna_Latn", + "tso_Latn", + "azj_Latn", + "dik_Latn", + "hau_Latn", + "kea_Latn", + "lus_Latn", + "pag_Latn", + "snd_Arab", + "tuk_Latn", + "bak_Cyrl", + "dyu_Latn", + "heb_Hebr", + "khk_Cyrl", + "lvs_Latn", + "pan_Guru", + "som_Latn", + "tum_Latn", +] +LANGUAGE_PAIRS = [ + (a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1 :] +] + +LANGUAGES_OF_INTEREST = [ + "cat_Latn", + "spa_Latn", + "eng_Latn", + "glg_Latn", + "eus_Latn", + "ita_Latn", + "deu_Latn", + "por_Latn", + "fra_Latn", +] +MAIN_LANG = "cat_Latn" +LANGUAGE_PAIRS = [ + (a, b) + for (a, b) in LANGUAGE_PAIRS + if a in LANGUAGES_OF_INTEREST + and b in LANGUAGES_OF_INTEREST + and "cat_Latn" in (a, b) +] + +# auxiliary functions + + +def code_to_language_name(code): + return Language.make(language=Language.get(code)["language"]).display_name() + + +def code_to_short_name(code): + return Language.get(code)["language"] + + +def jinja_var(s): + return "{{" + s + "}}" + + +def doc_to_text(src: str, tgt: str) -> str: + src_name, tgt_name = map(code_to_language_name, [src, tgt]) + + return f"""\ +{src_name} sentence: {jinja_var('sentence_' + src)} +{tgt_name} sentence:""" + + +def doc_to_target(tgt: str) -> str: + return f"{jinja_var('sentence_' + tgt)}" + + +# main function + + +def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: + """ + Generate a YAML file for each translation direction. + """ + + err = [] + for src, tgt in LANGUAGE_PAIRS: + # do both translation directions for each lang pair + for src, tgt in [(src, tgt), (tgt, src)]: + lang_pair_name = f"{code_to_short_name(src)}-{code_to_short_name(tgt)}" + yaml_file_name = f"flores_{lang_pair_name}.yaml" + + try: + with open( + f"{output_dir}/{yaml_file_name}", + "w" if overwrite else "x", + encoding="utf-8", + ) as outfile: + print(f"Creating {yaml_file_name}...") + outfile.write("# File generated by `create-yamls.py`\n") + yaml.dump( + { + # "group": [f"{BENCH_NAME}_bench", f"{BENCH_NAME}_bench_flores"], + # "group": "flores_ca", + "include": "_flores_common_yaml", + "task": f"flores_{lang_pair_name}", + "doc_to_text": doc_to_text(src, tgt), + "doc_to_target": doc_to_target(tgt), + }, + outfile, + sort_keys=False, + ) + + except FileExistsError: + err.append(yaml_file_name) + + if len(err) > 0: + raise FileExistsError( + "Files were not created because they already exist:" + f" {', '.join(err)}" + "\nUse flag --overwrite to overwrite them." + ) + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument( + "--overwrite", + default=False, + action="store_true", + help="Overwrite files if they already exist", + ) + parser.add_argument( + "--output-dir", default=".", help="Directory to write yaml files to" + ) + args = parser.parse_args() + + gen_lang_yamls(output_dir=args.output_dir, overwrite=args.overwrite) + + +if __name__ == "__main__": + main() diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-de.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-de.yaml new file mode 100644 index 00000000..15eb02af --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-de.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-de +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + German sentence:' +doc_to_target: '{{sentence_deu_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-en.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-en.yaml new file mode 100644 index 00000000..9a8f5ffe --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-en.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-en +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + English sentence:' +doc_to_target: '{{sentence_eng_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-es.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-es.yaml new file mode 100644 index 00000000..9a6aa442 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-es.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-es +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + Spanish sentence:' +doc_to_target: '{{sentence_spa_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-eu.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-eu.yaml new file mode 100644 index 00000000..48ffe7bf --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-eu.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-eu +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + Basque sentence:' +doc_to_target: '{{sentence_eus_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-fr.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-fr.yaml new file mode 100644 index 00000000..99b40c14 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-fr.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-fr +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + French sentence:' +doc_to_target: '{{sentence_fra_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-gl.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-gl.yaml new file mode 100644 index 00000000..5da7ad5f --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-gl.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-gl +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + Galician sentence:' +doc_to_target: '{{sentence_glg_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-it.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-it.yaml new file mode 100644 index 00000000..20f8d99f --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-it.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-it +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + Italian sentence:' +doc_to_target: '{{sentence_ita_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-pt.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-pt.yaml new file mode 100644 index 00000000..565f6267 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca-pt.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_ca-pt +doc_to_text: 'Catalan sentence: {{sentence_cat_Latn}} + + Portuguese sentence:' +doc_to_target: '{{sentence_por_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_ca.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca.yaml new file mode 100644 index 00000000..4726daa8 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_ca.yaml @@ -0,0 +1,24 @@ +group: flores_ca +task: + - flores_es-ca + - flores_ca-es + - flores_en-ca + - flores_ca-en + - flores_eu-ca + - flores_ca-eu + - flores_pt-ca + - flores_ca-pt + - flores_it-ca + - flores_ca-it + - flores_fr-ca + - flores_ca-fr + - flores_ca-gl + - flores_gl-ca + - flores_ca-de + - flores_de-ca +aggregate_metric_list: + - metric: bleu + aggregation: mean + weight_by_size: false +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_de-ca.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_de-ca.yaml new file mode 100644 index 00000000..af3d0eb4 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_de-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_de-ca +doc_to_text: 'German sentence: {{sentence_deu_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_en-ca.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_en-ca.yaml new file mode 100644 index 00000000..16132ff4 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_en-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_en-ca +doc_to_text: 'English sentence: {{sentence_eng_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_es-ca.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_es-ca.yaml new file mode 100644 index 00000000..e35b7152 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_es-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_es-ca +doc_to_text: 'Spanish sentence: {{sentence_spa_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_eu-ca.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_eu-ca.yaml new file mode 100644 index 00000000..c8be6ee9 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_eu-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_eu-ca +doc_to_text: 'Basque sentence: {{sentence_eus_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_fr-ca.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_fr-ca.yaml new file mode 100644 index 00000000..0d2de77e --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_fr-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_fr-ca +doc_to_text: 'French sentence: {{sentence_fra_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_gl-ca.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_gl-ca.yaml new file mode 100644 index 00000000..6ce3eaae --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_gl-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_gl-ca +doc_to_text: 'Galician sentence: {{sentence_glg_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_it-ca.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_it-ca.yaml new file mode 100644 index 00000000..db811154 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_it-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_it-ca +doc_to_text: 'Italian sentence: {{sentence_ita_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/flores_ca/flores_pt-ca.yaml b/lm_eval/tasks/catalan_bench/flores_ca/flores_pt-ca.yaml new file mode 100644 index 00000000..196295c9 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/flores_ca/flores_pt-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _flores_common_yaml +task: flores_pt-ca +doc_to_text: 'Portuguese sentence: {{sentence_por_Latn}} + + Catalan sentence:' +doc_to_target: '{{sentence_cat_Latn}}' diff --git a/lm_eval/tasks/catalan_bench/mgsm_direct_ca.yaml b/lm_eval/tasks/catalan_bench/mgsm_direct_ca.yaml new file mode 100644 index 00000000..066336a6 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/mgsm_direct_ca.yaml @@ -0,0 +1,25 @@ +task: mgsm_direct_ca +dataset_path: projecte-aina/mgsm_ca +doc_to_target: '{{answer_number|string}}' +doc_to_text: '{% if answer != None %}{{question + "\nResposta: "}}{% else %}{{"Pregunta: " + question + "\nResposta: "}}{% endif %}' +output_type: generate_until +training_split: train +test_split: test +target_delimiter: "" +generation_kwargs: + until: + - "\n\n" + - "\n" +filter_list: + - name: remove_whitespace + filter: + - function: remove_whitespace + - function: take_first +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/openbookqa_ca.yaml b/lm_eval/tasks/catalan_bench/openbookqa_ca.yaml new file mode 100644 index 00000000..868be756 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/openbookqa_ca.yaml @@ -0,0 +1,20 @@ +task: openbookqa_ca +dataset_path: projecte-aina/openbookqa_ca +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +doc_to_text: question_stem +doc_to_target: "{{choices.label.index(answerKey.lstrip())}}" +doc_to_choice: "{{choices.text}}" +should_decontaminate: true +doc_to_decontamination_query: question_stem +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/parafraseja.yaml b/lm_eval/tasks/catalan_bench/parafraseja.yaml new file mode 100644 index 00000000..060d488d --- /dev/null +++ b/lm_eval/tasks/catalan_bench/parafraseja.yaml @@ -0,0 +1,17 @@ +task: parafraseja +dataset_path: projecte-aina/Parafraseja +output_type: multiple_choice +dataset_name: null +test_split: test +training_split: train +validation_split: validation +doc_to_choice: '{{[sentence1+", veritat? No, "+sentence2, sentence1+", veritat? Sí, "+sentence2]}}' +process_docs: !function utils.process_docs_paraphrases +doc_to_text: '' +doc_to_target: label +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/paws_ca.yaml b/lm_eval/tasks/catalan_bench/paws_ca.yaml new file mode 100644 index 00000000..e736f5c7 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/paws_ca.yaml @@ -0,0 +1,18 @@ +task: paws_ca +dataset_path: projecte-aina/PAWS-ca +dataset_name: null +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: test +process_docs: !function utils.process_docs_paraphrases +doc_to_text: '' +doc_to_target: label +doc_to_choice: '{{[sentence1+", veritat? No, "+sentence2, sentence1+", veritat? Sí, "+sentence2]}}' +target_delimiter: '' +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/phrases_va/_phrases_va_common.yaml b/lm_eval/tasks/catalan_bench/phrases_va/_phrases_va_common.yaml new file mode 100644 index 00000000..f59a2098 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/phrases_va/_phrases_va_common.yaml @@ -0,0 +1,24 @@ +tag: phrases_va +dataset_path: gplsi/CA-VA_alignment_test +output_type: generate_until +training_split: null +validation_split: null +test_split: test +fewshot_split: test +num_fewshot: 5 +target_delimiter: ' ' +generation_kwargs: + until: + - "\n" +metric_list: + - metric: bleu + aggregation: bleu + higher_is_better: true + - metric: ter + aggregation: ter + higher_is_better: false + - metric: chrf + aggregation: chrf + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/phrases_va/phrases_ca-va.yaml b/lm_eval/tasks/catalan_bench/phrases_va/phrases_ca-va.yaml new file mode 100644 index 00000000..fc0e08d5 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/phrases_va/phrases_ca-va.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _phrases_va_common.yaml +task: phrases_ca-va +doc_to_text: 'Oració en català: {{ca}} + + Oració en valencià:' +doc_to_target: '{{va}}' diff --git a/lm_eval/tasks/catalan_bench/phrases_va/phrases_va-ca.yaml b/lm_eval/tasks/catalan_bench/phrases_va/phrases_va-ca.yaml new file mode 100644 index 00000000..5b1a7678 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/phrases_va/phrases_va-ca.yaml @@ -0,0 +1,7 @@ +# File generated by `create-yamls.py` +include: _phrases_va_common.yaml +task: phrases_va-ca +doc_to_text: 'Oració en valencià: {{va}} + + Oració en català:' +doc_to_target: '{{ca}}' diff --git a/lm_eval/tasks/catalan_bench/piqa_ca.yaml b/lm_eval/tasks/catalan_bench/piqa_ca.yaml new file mode 100644 index 00000000..11e600a7 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/piqa_ca.yaml @@ -0,0 +1,21 @@ +task: piqa_ca +dataset_path: projecte-aina/piqa_ca +dataset_name: null +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: null +doc_to_text: "Pregunta: {{goal}}\nResposta:" +doc_to_target: label +doc_to_choice: "{{[sol1, sol2]}}" +should_decontaminate: true +doc_to_decontamination_query: goal +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/siqa_ca.yaml b/lm_eval/tasks/catalan_bench/siqa_ca.yaml new file mode 100644 index 00000000..8a39a37f --- /dev/null +++ b/lm_eval/tasks/catalan_bench/siqa_ca.yaml @@ -0,0 +1,16 @@ +task: siqa_ca +dataset_path: projecte-aina/siqa_ca +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: null +doc_to_text: "Pregunta: {{context}} {{question}}\nResposta:" +target_delimiter: " " +doc_to_choice: "{{[answerA, answerB, answerC]}}" +doc_to_target: "{{ (label|int) - 1 }}" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/teca.yaml b/lm_eval/tasks/catalan_bench/teca.yaml new file mode 100644 index 00000000..8978c2c9 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/teca.yaml @@ -0,0 +1,18 @@ +task: teca +dataset_path: projecte-aina/teca +dataset_name: null +training_split: train +validation_split: validation +test_split: test +output_type: multiple_choice +process_docs: !function utils.process_doc_nli +doc_to_text: "" +doc_to_target: label +target_delimiter: "" +doc_to_choice: '{{[premise + ", correcte? Sí, " + hypothesis, premise + ", correcte? A més, " + hypothesis, premise + ", correcte? No, " + hypothesis]}}' +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/utils.py b/lm_eval/tasks/catalan_bench/utils.py new file mode 100644 index 00000000..ced91772 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/utils.py @@ -0,0 +1,142 @@ +import re +from itertools import product + +import evaluate +import transformers.data.metrics.squad_metrics as squad_metrics + +from lm_eval.utils import general_detokenize + + +def lowercase_first_letter(text): + return text[0].lower() + text[1:] + + +def process_doc_nli(dataset): + def process_fn(doc): + # Detokenize(remove extra whitespaces) + doc["premise"] = general_detokenize(doc["premise"]).strip() + doc["hypothesis"] = general_detokenize(doc["hypothesis"]).strip() + # Remove last punctuation mark in the premise + doc["premise"] = ( + doc["premise"][:-1] + if doc["premise"].endswith((".", ",", "!", "?")) + else doc["premise"] + ) + # Lowercase the first letter in the hypothesis + doc["hypothesis"] = lowercase_first_letter(doc["hypothesis"]) + # Ensure that the hypothesis ends with a dot + doc["hypothesis"] = ( + (doc["hypothesis"] + ".") + if not doc["hypothesis"].endswith(".") + else doc["hypothesis"] + ) + return doc + + return dataset.map(process_fn) + + +def process_results_coqcat(doc, results): + # Get all possible answers and compute the scores + turn_id = len(doc["questions"]) + answers = [doc["answers"]["input_text"][turn_id - 1]] + additional_answers_list = doc.get("additional_answers") + if additional_answers_list: + for key, additional_answers in additional_answers_list.items(): + if additional_answers["input_text"][turn_id - 1].lower() not in map( + str.lower, answers + ): + answers.append(additional_answers["input_text"][turn_id - 1]) + + gold_list = answers + pred = results[0].strip().split("\n")[0] + # import code; code.interact(local=dict(globals(), **locals())) + + f1_sum = 0.0 + em_sum = 0.0 + if len(gold_list) > 1: + for i in range(len(gold_list)): + gold_answers = gold_list[0:i] + gold_list[i + 1 :] + # predictions compared against (n) golds and take maximum + em_sum += max(squad_metrics.compute_exact(a, pred) for a in gold_answers) + f1_sum += max(squad_metrics.compute_f1(a, pred) for a in gold_answers) + else: + em_sum += max(squad_metrics.compute_exact(a, pred) for a in gold_list) + f1_sum += max(squad_metrics.compute_f1(a, pred) for a in gold_list) + # import code; code.interact(local=dict(globals(), **locals())) + return { + "em": em_sum / max(1, len(gold_list)), + "f1": f1_sum / max(1, len(gold_list)), + } + + +def process_results_qa(doc, results): + preds = results[0] + reference = doc["answers"][0]["text"] + # import code; code.interact(local=dict(globals(), **locals())) + f1_sum = squad_metrics.compute_f1(reference, preds) + exact_match = squad_metrics.compute_exact(reference, preds) + return {"f1": f1_sum, "exact_match": exact_match} + + +def process_doc_cabreu(dataset): + def process_fn(doc): + # Remove duplicate spaces + doc["content"] = re.sub(r" +", " ", doc["content"]) + for summary_type, index in product( + ["abstractive", "extractive", "extreme"], ["a1", "a2", "a3"] + ): + doc["summaries"][summary_type][index] = re.sub( + r" +", " ", doc["summaries"][summary_type][index] + ) + return doc + + return dataset.map(process_fn) + + +def process_docs_paraphrases(dataset): + empty_docs = [] + + def _process_doc(doc): + if doc["sentence1"] not in [None, ""] and doc["sentence2"] not in [None, ""]: + doc["sentence1"] = general_detokenize(doc["sentence1"]).strip() + doc["sentence2"] = general_detokenize(doc["sentence2"]).strip() + # Remove final punctuation mark in the first sentence + if doc["sentence1"].endswith((".", ",", ";")): + doc["sentence1"] = doc["sentence1"][:-1] + # Start the second sentence in lowercase (to be used after "Yes, ...") + doc["sentence2"] = lowercase_first_letter(doc["sentence2"]) + return doc + else: + empty_docs.append(doc) + return doc + + return dataset.filter( + lambda doc: doc["sentence1"] not in [None, ""] + and doc["sentence2"] not in [None, ""] + ).map(_process_doc) + + +def process_docs_copa_ca(dataset): + def _process_doc(doc): + doc["choice1"] = lowercase_first_letter(doc["choice1"]) + doc["choice2"] = lowercase_first_letter(doc["choice2"]) + return doc + + return dataset.map(_process_doc) + + +def rouge1(items): + """ + # passthrough for efficiency + """ + return items + + +def rouge1_agg(items): + """ + Higher is better + """ + refs = list(zip(*items))[0] + preds = list(zip(*items))[1] + rouge_scorer = evaluate.load("rouge") + return rouge_scorer.compute(predictions=preds, references=refs)["rouge1"] diff --git a/lm_eval/tasks/catalan_bench/wnli_ca.yaml b/lm_eval/tasks/catalan_bench/wnli_ca.yaml new file mode 100644 index 00000000..d4deec5c --- /dev/null +++ b/lm_eval/tasks/catalan_bench/wnli_ca.yaml @@ -0,0 +1,14 @@ +task: wnli_ca +dataset_path: projecte-aina/wnli-ca +dataset_name: null +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: null +doc_to_text: "{{sentence1}}\nPregunta: {{sentence2}} Cert o Fals?\nResposta:" +doc_to_target: label +doc_to_choice: ["Fals", "Cert"] +metric_list: + - metric: acc +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/xnli_ca.yaml b/lm_eval/tasks/catalan_bench/xnli_ca.yaml new file mode 100644 index 00000000..44f0f443 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/xnli_ca.yaml @@ -0,0 +1,19 @@ +task: xnli_ca +dataset_path: projecte-aina/xnli-ca +dataset_name: null +include: ../xnli/xnli_common_yaml +output_type: multiple_choice +doc_to_choice: '{{[premise+", correcte? Sí, "+hypothesis,premise+", correcte? A més, + "+hypothesis,premise+", correcte? No, "+hypothesis]}}' +doc_to_text: '' +target_delimiter: '' +process_docs: !function utils.process_doc_nli +training_split: null +validation_split: validation +doc_to_target: label +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/xquad_ca.yaml b/lm_eval/tasks/catalan_bench/xquad_ca.yaml new file mode 100644 index 00000000..9b72c7da --- /dev/null +++ b/lm_eval/tasks/catalan_bench/xquad_ca.yaml @@ -0,0 +1,24 @@ +task: xquad_ca +dataset_path: projecte-aina/xquad-ca +dataset_name: null +output_type: generate_until +doc_to_text: "Context: {{context}}\n\nPregunta: {{question}}\n\nResposta:" +doc_to_target: '{{answers[0]["text"]}}' +validation_split: null +test_split: test +target_delimiter: ' ' +process_results: !function utils.process_results_qa +generation_kwargs: + until: + - "\n" + do_sample: false + temperature: 0.0 +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + - metric: f1 + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/catalan_bench/xstorycloze_ca.yaml b/lm_eval/tasks/catalan_bench/xstorycloze_ca.yaml new file mode 100644 index 00000000..61a7c299 --- /dev/null +++ b/lm_eval/tasks/catalan_bench/xstorycloze_ca.yaml @@ -0,0 +1,17 @@ +task: xstorycloze_ca +dataset_path: projecte-aina/xstorycloze_ca +dataset_name: ca +output_type: multiple_choice +training_split: train +validation_split: eval +doc_to_text: "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}" +doc_to_target: "{{answer_right_ending-1}}" +doc_to_choice: "{{[sentence_quiz1, sentence_quiz2]}}" +should_decontaminate: true +doc_to_decontamination_query: "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 -- GitLab From 5e0bc289dfcfe92cd3cd93836c0c863a99f4d566 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Fri, 4 Oct 2024 20:44:32 +0500 Subject: [PATCH 118/194] fix tests (#2380) --- .pre-commit-config.yaml | 4 +- examples/lm-eval-overview.ipynb | 2406 +++++++++-------- examples/visualize-wandb.ipynb | 2 + lm_eval/api/task.py | 2 +- .../flores_gl/create_yamls_flores_gl.py | 292 +- .../flores_pt/create_yamls_flores_pt.py | 290 +- .../flores_es/create_yamls_flores_es.py | 5 +- tests/models/test_huggingface.py | 7 +- 8 files changed, 1727 insertions(+), 1281 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index d066cd9e..5df94412 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -2,7 +2,7 @@ exclude: ^tests/testdata/ repos: - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v4.5.0 + rev: v4.6.0 hooks: - id: check-added-large-files - id: check-ast @@ -29,7 +29,7 @@ repos: - id: mixed-line-ending args: [--fix=lf] - repo: https://github.com/astral-sh/ruff-pre-commit - rev: v0.4.8 + rev: v0.6.8 hooks: # Run the linter. - id: ruff diff --git a/examples/lm-eval-overview.ipynb b/examples/lm-eval-overview.ipynb index 7c4564d6..9cb1f5e2 100644 --- a/examples/lm-eval-overview.ipynb +++ b/examples/lm-eval-overview.ipynb @@ -1,1230 +1,1232 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Qw83KAePAhaS" - }, - "source": [ - "# Releasing LM-Evaluation-Harness v0.4.0" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Z7k2vq1iAdqr" - }, - "source": [ - "With the vast amount of work done in the field today, it helps to have a tool that people can use easily to share their results and use to check others to ensure reported numbers are valid. The LM Evaluation Harness is one such tool the community has used extensively. We want to continue to support the community and with that in mind, we’re excited to announce a major update on the LM Evaluation Harness to further our goal for open and accessible AI research." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0gDoM0AJAvEc" - }, - "source": [ - "Our refactor stems from our desires to make the following believed best practices easier to carry out. \n", - "\n", - "1. Never copy results from other papers\n", - "2. Always share your exact prompts\n", - "3. Always provide model outputs\n", - "4. Qualitatively review a small batch of outputs before running evaluation jobs at scale\n", - "\n", - "We also wanted to make the library a better experience to use and to contribute or design evaluations within. New features in the new release that serve this purpose include:\n", - "\n", - "1. Faster Evaluation Runtimes (accelerated data-parallel inference with HF Transformers + Accelerate, and commonly used or faster inference libraries such as vLLM and Llama-CPP)\n", - "2. Easier addition and sharing of new tasks (YAML-based task config formats, allowing single-file sharing of custom tasks)\n", - "3. More configurability, for more advanced workflows and easier operation with modifying prompts\n", - "4. Better logging of data at runtime and post-hoc" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "nnwsOpjda_YW" - }, - "source": [ - "In this notebook we will be going through a short tutorial on how things work." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zAov81vTbL2K" - }, - "source": [ - "## Install LM-Eval" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "8hiosGzq_qZg", - "outputId": "6ab73e5e-1f54-417e-a388-07e0d870b132" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Collecting git+https://github.com/EleutherAI/lm-evaluation-harness.git@big-refactor\n", - " Cloning https://github.com/EleutherAI/lm-evaluation-harness.git (to revision big-refactor) to /tmp/pip-req-build-tnssql5s\n", - " Running command git clone --filter=blob:none --quiet https://github.com/EleutherAI/lm-evaluation-harness.git /tmp/pip-req-build-tnssql5s\n", - 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"Successfully built lm-eval rouge-score sqlitedict\n", - "Installing collected packages: sqlitedict, zstandard, tcolorpy, pybind11, pyarrow-hotfix, portalocker, pathvalidate, mbstrdecoder, jsonlines, dill, colorama, typepy, tqdm-multiprocess, sacrebleu, rouge-score, responses, multiprocess, accelerate, datasets, DataProperty, tabledata, peft, evaluate, pytablewriter, lm-eval\n", - "Successfully installed DataProperty-1.0.1 accelerate-0.24.1 colorama-0.4.6 datasets-2.15.0 dill-0.3.7 evaluate-0.4.1 jsonlines-4.0.0 lm-eval-1.0.0 mbstrdecoder-1.1.3 multiprocess-0.70.15 pathvalidate-3.2.0 peft-0.6.2 portalocker-2.8.2 pyarrow-hotfix-0.6 pybind11-2.11.1 pytablewriter-1.2.0 responses-0.18.0 rouge-score-0.1.2 sacrebleu-2.3.2 sqlitedict-2.1.0 tabledata-1.3.3 tcolorpy-0.1.4 tqdm-multiprocess-0.0.11 typepy-1.3.2 zstandard-0.22.0\n" - ] - } - ], - "source": [ - "# Install LM-Eval\n", - "!pip install git+https://github.com/EleutherAI/lm-evaluation-harness.git" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 0, - "referenced_widgets": [ - "a1d3a8aa016544a78e8821c8f6199e06", - "f61ed33fad754146bdd2ac9db1ba1c48", - "bfa0af6aeff344c6845e1080a878e92e", - "fd1ad9e0367d4004aae853b91c3a7617", - "6b2d90209ec14230b3d58a74ac9b83bf", - "a73f357065d34d7baf0453ae4a8d75e2", - "46f521b73fd943c081c648fd873ebc0a", - "7c5689bc13684db8a22681f41863dddd", - "48763b6233374554ae76035c0483066f", - "4986a21eb560448fa79f4b25cde48951", - "aed3acd2f2d74003b44079c333a0698e" - ] - }, - "id": "uyO5MaKkZyah", - "outputId": "d46e8096-5086-4e49-967e-ea33d4a2a335" - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "a1d3a8aa016544a78e8821c8f6199e06", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Downloading builder script: 0%| | 0.00/5.67k [00:00\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "id": "fthNg3ywO-kA" - }, - "outputs": [], - "source": [ - "YAML_cola_string = '''\n", - "tag: yes_or_no_tasks\n", - "task: demo_cola\n", - "dataset_path: glue\n", - "dataset_name: cola\n", - "output_type: multiple_choice\n", - "training_split: train\n", - "validation_split: validation\n", - "doc_to_text: \"{{sentence}}\\nQuestion: Does this sentence make sense?\\nAnswer:\"\n", - "doc_to_target: label\n", - "doc_to_choice: [\"no\", \"yes\"]\n", - "should_decontaminate: true\n", - "doc_to_decontamination_query: sentence\n", - "metric_list:\n", - " - metric: acc\n", - "'''\n", - "with open('cola.yaml', 'w') as f:\n", - " f.write(YAML_cola_string)" - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Qw83KAePAhaS" + }, + "source": [ + "# Releasing LM-Evaluation-Harness v0.4.0" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Z7k2vq1iAdqr" + }, + "source": [ + "With the vast amount of work done in the field today, it helps to have a tool that people can use easily to share their results and use to check others to ensure reported numbers are valid. The LM Evaluation Harness is one such tool the community has used extensively. We want to continue to support the community and with that in mind, we’re excited to announce a major update on the LM Evaluation Harness to further our goal for open and accessible AI research." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0gDoM0AJAvEc" + }, + "source": [ + "Our refactor stems from our desires to make the following believed best practices easier to carry out. \n", + "\n", + "1. Never copy results from other papers\n", + "2. Always share your exact prompts\n", + "3. Always provide model outputs\n", + "4. Qualitatively review a small batch of outputs before running evaluation jobs at scale\n", + "\n", + "We also wanted to make the library a better experience to use and to contribute or design evaluations within. New features in the new release that serve this purpose include:\n", + "\n", + "1. Faster Evaluation Runtimes (accelerated data-parallel inference with HF Transformers + Accelerate, and commonly used or faster inference libraries such as vLLM and Llama-CPP)\n", + "2. Easier addition and sharing of new tasks (YAML-based task config formats, allowing single-file sharing of custom tasks)\n", + "3. More configurability, for more advanced workflows and easier operation with modifying prompts\n", + "4. Better logging of data at runtime and post-hoc" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nnwsOpjda_YW" + }, + "source": [ + "In this notebook we will be going through a short tutorial on how things work." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zAov81vTbL2K" + }, + "source": [ + "## Install LM-Eval" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "8hiosGzq_qZg", + "outputId": "6ab73e5e-1f54-417e-a388-07e0d870b132" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "id": "XceRKCuuDtbn" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2023-11-29:11:56:33,016 INFO [utils.py:160] NumExpr defaulting to 2 threads.\n", - "2023-11-29 11:56:33.852995: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", - "2023-11-29 11:56:33.853050: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", - "2023-11-29 11:56:33.853087: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", - "2023-11-29 11:56:35.129047: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", - "2023-11-29:11:56:38,546 INFO [__main__.py:132] Verbosity set to INFO\n", - "2023-11-29:11:56:47,509 WARNING [__main__.py:138] --limit SHOULD ONLY BE USED FOR TESTING.REAL METRICS SHOULD NOT BE COMPUTED USING LIMIT.\n", - "2023-11-29:11:56:47,509 INFO [__main__.py:143] Including path: ./\n", - "2023-11-29:11:56:47,517 INFO [__main__.py:205] Selected Tasks: ['yes_or_no_tasks']\n", - "2023-11-29:11:56:47,520 WARNING [evaluator.py:93] generation_kwargs specified through cli, these settings will be used over set parameters in yaml tasks.\n", - "2023-11-29:11:56:47,550 INFO [huggingface.py:120] Using device 'cuda'\n", - "2023-11-29:11:57:08,743 WARNING [task.py:614] [Task: demo_cola] metric acc is defined, but aggregation is not. using default aggregation=mean\n", - "2023-11-29:11:57:08,743 WARNING [task.py:626] [Task: demo_cola] metric acc is defined, but higher_is_better is not. using default higher_is_better=True\n", - "Downloading builder script: 100% 28.8k/28.8k [00:00<00:00, 52.7MB/s]\n", - "Downloading metadata: 100% 28.7k/28.7k [00:00<00:00, 51.9MB/s]\n", - "Downloading readme: 100% 27.9k/27.9k [00:00<00:00, 48.0MB/s]\n", - "Downloading data: 100% 377k/377k [00:00<00:00, 12.0MB/s]\n", - "Generating train split: 100% 8551/8551 [00:00<00:00, 19744.58 examples/s]\n", - "Generating validation split: 100% 1043/1043 [00:00<00:00, 27057.01 examples/s]\n", - "Generating test split: 100% 1063/1063 [00:00<00:00, 22705.17 examples/s]\n", - "2023-11-29:11:57:11,698 INFO [task.py:355] Building contexts for task on rank 0...\n", - "2023-11-29:11:57:11,704 INFO [evaluator.py:319] Running loglikelihood requests\n", - "100% 20/20 [00:03<00:00, 5.15it/s]\n", - "fatal: not a git repository (or any of the parent directories): .git\n", - "hf (pretrained=EleutherAI/pythia-2.8b), gen_kwargs: (), limit: 10.0, num_fewshot: None, batch_size: 1\n", - "| Tasks |Version|Filter|n-shot|Metric|Value| |Stderr|\n", - "|---------------|-------|------|-----:|------|----:|---|-----:|\n", - "|yes_or_no_tasks|N/A |none | 0|acc | 0.7|± |0.1528|\n", - "| - demo_cola |Yaml |none | 0|acc | 0.7|± |0.1528|\n", - "\n", - "| Groups |Version|Filter|n-shot|Metric|Value| |Stderr|\n", - "|---------------|-------|------|-----:|------|----:|---|-----:|\n", - "|yes_or_no_tasks|N/A |none | 0|acc | 0.7|± |0.1528|\n", - "\n" - ] - } - ], - "source": [ - "# !accelerate launch --no_python\n", - "!lm_eval \\\n", - " --model hf \\\n", - " --model_args pretrained=EleutherAI/pythia-2.8b \\\n", - " --include_path ./ \\\n", - " --tasks yes_or_no_tasks \\\n", - " --limit 10 \\\n", - " --output output/yes_or_no_tasks/ \\\n", - " --log_samples\n" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting git+https://github.com/EleutherAI/lm-evaluation-harness.git@big-refactor\n", + " Cloning https://github.com/EleutherAI/lm-evaluation-harness.git (to revision big-refactor) to /tmp/pip-req-build-tnssql5s\n", + " Running command git clone --filter=blob:none --quiet https://github.com/EleutherAI/lm-evaluation-harness.git /tmp/pip-req-build-tnssql5s\n", + " Running command git checkout -b big-refactor --track origin/big-refactor\n", + " Switched to a new branch 'big-refactor'\n", + " Branch 'big-refactor' set up to track remote branch 'big-refactor' from 'origin'.\n", + " Resolved https://github.com/EleutherAI/lm-evaluation-harness.git to commit 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collected packages: sqlitedict, zstandard, tcolorpy, pybind11, pyarrow-hotfix, portalocker, pathvalidate, mbstrdecoder, jsonlines, dill, colorama, typepy, tqdm-multiprocess, sacrebleu, rouge-score, responses, multiprocess, accelerate, datasets, DataProperty, tabledata, peft, evaluate, pytablewriter, lm-eval\n", + "Successfully installed DataProperty-1.0.1 accelerate-0.24.1 colorama-0.4.6 datasets-2.15.0 dill-0.3.7 evaluate-0.4.1 jsonlines-4.0.0 lm-eval-1.0.0 mbstrdecoder-1.1.3 multiprocess-0.70.15 pathvalidate-3.2.0 peft-0.6.2 portalocker-2.8.2 pyarrow-hotfix-0.6 pybind11-2.11.1 pytablewriter-1.2.0 responses-0.18.0 rouge-score-0.1.2 sacrebleu-2.3.2 sqlitedict-2.1.0 tabledata-1.3.3 tcolorpy-0.1.4 tqdm-multiprocess-0.0.11 typepy-1.3.2 zstandard-0.22.0\n" + ] + } + ], + "source": [ + "# Install LM-Eval\n", + "!pip install git+https://github.com/EleutherAI/lm-evaluation-harness.git" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 0, + "referenced_widgets": [ + "a1d3a8aa016544a78e8821c8f6199e06", + "f61ed33fad754146bdd2ac9db1ba1c48", + "bfa0af6aeff344c6845e1080a878e92e", + "fd1ad9e0367d4004aae853b91c3a7617", + "6b2d90209ec14230b3d58a74ac9b83bf", + "a73f357065d34d7baf0453ae4a8d75e2", + "46f521b73fd943c081c648fd873ebc0a", + "7c5689bc13684db8a22681f41863dddd", + "48763b6233374554ae76035c0483066f", + "4986a21eb560448fa79f4b25cde48951", + "aed3acd2f2d74003b44079c333a0698e" + ] }, + "id": "uyO5MaKkZyah", + "outputId": "d46e8096-5086-4e49-967e-ea33d4a2a335" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "XceRKCuuDtbn" + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "a1d3a8aa016544a78e8821c8f6199e06", + "version_major": 2, + "version_minor": 0 }, - "source": [ - "## Edit Prompt Templates Quickly\n", - "\n", - "The following is a yaml made to evaluate the specific subtask of `high_school_geography` from MMLU. It uses the standard prompt where the we choose the letters from the options with most likelihood as the model's prediction." + "text/plain": [ + "Downloading builder script: 0%| | 0.00/5.67k [00:00\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "id": "fthNg3ywO-kA" + }, + "outputs": [], + "source": [ + "YAML_cola_string = \"\"\"\n", + "tag: yes_or_no_tasks\n", + "task: demo_cola\n", + "dataset_path: glue\n", + "dataset_name: cola\n", + "output_type: multiple_choice\n", + "training_split: train\n", + "validation_split: validation\n", + "doc_to_text: \"{{sentence}}\\nQuestion: Does this sentence make sense?\\nAnswer:\"\n", + "doc_to_target: label\n", + "doc_to_choice: [\"no\", \"yes\"]\n", + "should_decontaminate: true\n", + "doc_to_decontamination_query: sentence\n", + "metric_list:\n", + " - metric: acc\n", + "\"\"\"\n", + "with open(\"cola.yaml\", \"w\") as f:\n", + " f.write(YAML_cola_string)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "id": "XceRKCuuDtbn" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "id": "jyKOfCsKb-xy" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2023-11-29:11:57:23,598 INFO [utils.py:160] NumExpr defaulting to 2 threads.\n", - "2023-11-29 11:57:24.719750: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", - "2023-11-29 11:57:24.719806: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", - "2023-11-29 11:57:24.719847: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", - "2023-11-29 11:57:26.656125: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", - "2023-11-29:11:57:31,563 INFO [__main__.py:132] Verbosity set to INFO\n", - "2023-11-29:11:57:40,541 WARNING [__main__.py:138] --limit SHOULD ONLY BE USED FOR TESTING.REAL METRICS SHOULD NOT BE COMPUTED USING LIMIT.\n", - "2023-11-29:11:57:40,541 INFO [__main__.py:143] Including path: ./\n", - "2023-11-29:11:57:40,558 INFO [__main__.py:205] Selected Tasks: ['demo_mmlu_high_school_geography']\n", - "2023-11-29:11:57:40,559 WARNING [evaluator.py:93] generation_kwargs specified through cli, these settings will be used over set parameters in yaml tasks.\n", - "2023-11-29:11:57:40,589 INFO [huggingface.py:120] Using device 'cuda'\n", - "Downloading builder script: 100% 5.84k/5.84k [00:00<00:00, 17.7MB/s]\n", - "Downloading metadata: 100% 106k/106k [00:00<00:00, 892kB/s] \n", - "Downloading readme: 100% 39.7k/39.7k [00:00<00:00, 631kB/s]\n", - "Downloading data: 100% 166M/166M [00:01<00:00, 89.0MB/s]\n", - "Generating auxiliary_train split: 100% 99842/99842 [00:07<00:00, 12536.83 examples/s]\n", - "Generating test split: 100% 198/198 [00:00<00:00, 1439.20 examples/s]\n", - "Generating validation split: 100% 22/22 [00:00<00:00, 4181.76 examples/s]\n", - "Generating dev split: 100% 5/5 [00:00<00:00, 36.25 examples/s]\n", - "2023-11-29:11:58:09,798 INFO [task.py:355] Building contexts for task on rank 0...\n", - "2023-11-29:11:58:09,822 INFO [evaluator.py:319] Running loglikelihood requests\n", - "100% 40/40 [00:05<00:00, 7.86it/s]\n", - "fatal: not a git repository (or any of the parent directories): .git\n", - "hf (pretrained=EleutherAI/pythia-2.8b), gen_kwargs: (), limit: 10.0, num_fewshot: None, batch_size: 1\n", - "| Tasks |Version|Filter|n-shot| Metric |Value| |Stderr|\n", - "|-------------------------------|-------|------|-----:|--------|----:|---|-----:|\n", - "|demo_mmlu_high_school_geography|Yaml |none | 0|acc | 0.3|± |0.1528|\n", - "| | |none | 0|acc_norm| 0.3|± |0.1528|\n", - "\n" - ] - } - ], - "source": [ - "# !accelerate launch --no_python\n", - "!lm_eval \\\n", - " --model hf \\\n", - " --model_args pretrained=EleutherAI/pythia-2.8b \\\n", - " --include_path ./ \\\n", - " --tasks demo_mmlu_high_school_geography \\\n", - " --limit 10 \\\n", - " --output output/mmlu_high_school_geography/ \\\n", - " --log_samples" - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "2023-11-29:11:56:33,016 INFO [utils.py:160] NumExpr defaulting to 2 threads.\n", + "2023-11-29 11:56:33.852995: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "2023-11-29 11:56:33.853050: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "2023-11-29 11:56:33.853087: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "2023-11-29 11:56:35.129047: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", + "2023-11-29:11:56:38,546 INFO [__main__.py:132] Verbosity set to INFO\n", + "2023-11-29:11:56:47,509 WARNING [__main__.py:138] --limit SHOULD ONLY BE USED FOR TESTING.REAL METRICS SHOULD NOT BE COMPUTED USING LIMIT.\n", + "2023-11-29:11:56:47,509 INFO [__main__.py:143] Including path: ./\n", + "2023-11-29:11:56:47,517 INFO [__main__.py:205] Selected Tasks: ['yes_or_no_tasks']\n", + "2023-11-29:11:56:47,520 WARNING [evaluator.py:93] generation_kwargs specified through cli, these settings will be used over set parameters in yaml tasks.\n", + "2023-11-29:11:56:47,550 INFO [huggingface.py:120] Using device 'cuda'\n", + "2023-11-29:11:57:08,743 WARNING [task.py:614] [Task: demo_cola] metric acc is defined, but aggregation is not. using default aggregation=mean\n", + "2023-11-29:11:57:08,743 WARNING [task.py:626] [Task: demo_cola] metric acc is defined, but higher_is_better is not. using default higher_is_better=True\n", + "Downloading builder script: 100% 28.8k/28.8k [00:00<00:00, 52.7MB/s]\n", + "Downloading metadata: 100% 28.7k/28.7k [00:00<00:00, 51.9MB/s]\n", + "Downloading readme: 100% 27.9k/27.9k [00:00<00:00, 48.0MB/s]\n", + "Downloading data: 100% 377k/377k [00:00<00:00, 12.0MB/s]\n", + "Generating train split: 100% 8551/8551 [00:00<00:00, 19744.58 examples/s]\n", + "Generating validation split: 100% 1043/1043 [00:00<00:00, 27057.01 examples/s]\n", + "Generating test split: 100% 1063/1063 [00:00<00:00, 22705.17 examples/s]\n", + "2023-11-29:11:57:11,698 INFO [task.py:355] Building contexts for task on rank 0...\n", + "2023-11-29:11:57:11,704 INFO [evaluator.py:319] Running loglikelihood requests\n", + "100% 20/20 [00:03<00:00, 5.15it/s]\n", + "fatal: not a git repository (or any of the parent directories): .git\n", + "hf (pretrained=EleutherAI/pythia-2.8b), gen_kwargs: (), limit: 10.0, num_fewshot: None, batch_size: 1\n", + "| Tasks |Version|Filter|n-shot|Metric|Value| |Stderr|\n", + "|---------------|-------|------|-----:|------|----:|---|-----:|\n", + "|yes_or_no_tasks|N/A |none | 0|acc | 0.7|± |0.1528|\n", + "| - demo_cola |Yaml |none | 0|acc | 0.7|± |0.1528|\n", + "\n", + "| Groups |Version|Filter|n-shot|Metric|Value| |Stderr|\n", + "|---------------|-------|------|-----:|------|----:|---|-----:|\n", + "|yes_or_no_tasks|N/A |none | 0|acc | 0.7|± |0.1528|\n", + "\n" + ] + } + ], + "source": [ + "# !accelerate launch --no_python\n", + "!lm_eval \\\n", + " --model hf \\\n", + " --model_args pretrained=EleutherAI/pythia-2.8b \\\n", + " --include_path ./ \\\n", + " --tasks yes_or_no_tasks \\\n", + " --limit 10 \\\n", + " --output output/yes_or_no_tasks/ \\\n", + " --log_samples" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XceRKCuuDtbn" + }, + "source": [ + "## Edit Prompt Templates Quickly\n", + "\n", + "The following is a yaml made to evaluate the specific subtask of `high_school_geography` from MMLU. It uses the standard prompt where the we choose the letters from the options with most likelihood as the model's prediction." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "id": "GTFvdt9kSlBG" + }, + "outputs": [], + "source": [ + "YAML_mmlu_geo_string = \"\"\"\n", + "task: demo_mmlu_high_school_geography\n", + "dataset_path: cais/mmlu\n", + "dataset_name: high_school_geography\n", + "description: \"The following are multiple choice questions (with answers) about high school geography.\\n\\n\"\n", + "test_split: test\n", + "fewshot_split: dev\n", + "fewshot_config:\n", + " sampler: first_n\n", + "output_type: multiple_choice\n", + "doc_to_text: \"{{question.strip()}}\\nA. {{choices[0]}}\\nB. {{choices[1]}}\\nC. {{choices[2]}}\\nD. {{choices[3]}}\\nAnswer:\"\n", + "doc_to_choice: [\"A\", \"B\", \"C\", \"D\"]\n", + "doc_to_target: answer\n", + "metric_list:\n", + " - metric: acc\n", + " aggregation: mean\n", + " higher_is_better: true\n", + " - metric: acc_norm\n", + " aggregation: mean\n", + " higher_is_better: true\n", + "\"\"\"\n", + "with open(\"mmlu_high_school_geography.yaml\", \"w\") as f:\n", + " f.write(YAML_mmlu_geo_string)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "id": "jyKOfCsKb-xy" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "jyKOfCsKb-xy" - }, - "source": [ - "We could also evaluate this task in a different way. For example, instead of observing the loglikelihood of the letters, we can instead evaluate on the choices themselves as the continuation. This is done by simply changing `doc_to_choice` from a list of letters to the corresponding `choices` field from the HF dataset. We write `\"{{choices}}\"` so that the string field is interpreted as jinja string that acquires the list from the HF dataset directly.\n", - "\n", - "Another convenient feature here is since we're only modifying the `doc_to_choice` and the rest of config is the same as the task above, we can use the above configuration as a template by using `include: mmlu_high_school_geography.yaml` to load the config from that file. We'll need to add a unique task name as to not colide with the existing yaml config we're including. For this case we'll simply name this one `mmlu_high_school_geography_continuation`. `doc_to_text` is added here just for sake of clarity." - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "2023-11-29:11:57:23,598 INFO [utils.py:160] NumExpr defaulting to 2 threads.\n", + "2023-11-29 11:57:24.719750: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "2023-11-29 11:57:24.719806: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "2023-11-29 11:57:24.719847: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "2023-11-29 11:57:26.656125: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", + "2023-11-29:11:57:31,563 INFO [__main__.py:132] Verbosity set to INFO\n", + "2023-11-29:11:57:40,541 WARNING [__main__.py:138] --limit SHOULD ONLY BE USED FOR TESTING.REAL METRICS SHOULD NOT BE COMPUTED USING LIMIT.\n", + "2023-11-29:11:57:40,541 INFO [__main__.py:143] Including path: ./\n", + "2023-11-29:11:57:40,558 INFO [__main__.py:205] Selected Tasks: ['demo_mmlu_high_school_geography']\n", + "2023-11-29:11:57:40,559 WARNING [evaluator.py:93] generation_kwargs specified through cli, these settings will be used over set parameters in yaml tasks.\n", + "2023-11-29:11:57:40,589 INFO [huggingface.py:120] Using device 'cuda'\n", + "Downloading builder script: 100% 5.84k/5.84k [00:00<00:00, 17.7MB/s]\n", + "Downloading metadata: 100% 106k/106k [00:00<00:00, 892kB/s] \n", + "Downloading readme: 100% 39.7k/39.7k [00:00<00:00, 631kB/s]\n", + "Downloading data: 100% 166M/166M [00:01<00:00, 89.0MB/s]\n", + "Generating auxiliary_train split: 100% 99842/99842 [00:07<00:00, 12536.83 examples/s]\n", + "Generating test split: 100% 198/198 [00:00<00:00, 1439.20 examples/s]\n", + "Generating validation split: 100% 22/22 [00:00<00:00, 4181.76 examples/s]\n", + "Generating dev split: 100% 5/5 [00:00<00:00, 36.25 examples/s]\n", + "2023-11-29:11:58:09,798 INFO [task.py:355] Building contexts for task on rank 0...\n", + "2023-11-29:11:58:09,822 INFO [evaluator.py:319] Running loglikelihood requests\n", + "100% 40/40 [00:05<00:00, 7.86it/s]\n", + "fatal: not a git repository (or any of the parent directories): .git\n", + "hf (pretrained=EleutherAI/pythia-2.8b), gen_kwargs: (), limit: 10.0, num_fewshot: None, batch_size: 1\n", + "| Tasks |Version|Filter|n-shot| Metric |Value| |Stderr|\n", + "|-------------------------------|-------|------|-----:|--------|----:|---|-----:|\n", + "|demo_mmlu_high_school_geography|Yaml |none | 0|acc | 0.3|± |0.1528|\n", + "| | |none | 0|acc_norm| 0.3|± |0.1528|\n", + "\n" + ] + } + ], + "source": [ + "# !accelerate launch --no_python\n", + "!lm_eval \\\n", + " --model hf \\\n", + " --model_args pretrained=EleutherAI/pythia-2.8b \\\n", + " --include_path ./ \\\n", + " --tasks demo_mmlu_high_school_geography \\\n", + " --limit 10 \\\n", + " --output output/mmlu_high_school_geography/ \\\n", + " --log_samples" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jyKOfCsKb-xy" + }, + "source": [ + "We could also evaluate this task in a different way. For example, instead of observing the loglikelihood of the letters, we can instead evaluate on the choices themselves as the continuation. This is done by simply changing `doc_to_choice` from a list of letters to the corresponding `choices` field from the HF dataset. We write `\"{{choices}}\"` so that the string field is interpreted as jinja string that acquires the list from the HF dataset directly.\n", + "\n", + "Another convenient feature here is since we're only modifying the `doc_to_choice` and the rest of config is the same as the task above, we can use the above configuration as a template by using `include: mmlu_high_school_geography.yaml` to load the config from that file. We'll need to add a unique task name as to not colide with the existing yaml config we're including. For this case we'll simply name this one `mmlu_high_school_geography_continuation`. `doc_to_text` is added here just for sake of clarity." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "id": "lqElwU54TaK-" + }, + "outputs": [], + "source": [ + "YAML_mmlu_geo_string = \"\"\"\n", + "include: mmlu_high_school_geography.yaml\n", + "task: demo_mmlu_high_school_geography_continuation\n", + "doc_to_text: \"{{question.strip()}}\\nA. {{choices[0]}}\\nB. {{choices[1]}}\\nC. {{choices[2]}}\\nD. {{choices[3]}}\\nAnswer:\"\n", + "doc_to_choice: \"{{choices}}\"\n", + "\"\"\"\n", + "with open(\"mmlu_high_school_geography_continuation.yaml\", \"w\") as f:\n", + " f.write(YAML_mmlu_geo_string)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "id": "-_CVnDirdy7j" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "id": "lqElwU54TaK-" - }, - "outputs": [], - "source": [ - "YAML_mmlu_geo_string = '''\n", - "include: mmlu_high_school_geography.yaml\n", - "task: demo_mmlu_high_school_geography_continuation\n", - "doc_to_text: \"{{question.strip()}}\\nA. {{choices[0]}}\\nB. {{choices[1]}}\\nC. {{choices[2]}}\\nD. {{choices[3]}}\\nAnswer:\"\n", - "doc_to_choice: \"{{choices}}\"\n", - "'''\n", - "with open('mmlu_high_school_geography_continuation.yaml', 'w') as f:\n", - " f.write(YAML_mmlu_geo_string)\n" - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "2023-11-29:11:58:21,284 INFO [utils.py:160] NumExpr defaulting to 2 threads.\n", + "2023-11-29 11:58:22.850159: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "2023-11-29 11:58:22.850219: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "2023-11-29 11:58:22.850254: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "2023-11-29 11:58:24.948103: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", + "2023-11-29:11:58:28,460 INFO [__main__.py:132] Verbosity set to INFO\n", + "2023-11-29:11:58:37,935 WARNING [__main__.py:138] --limit SHOULD ONLY BE USED FOR TESTING.REAL METRICS SHOULD NOT BE COMPUTED USING LIMIT.\n", + "2023-11-29:11:58:37,935 INFO [__main__.py:143] Including path: ./\n", + "2023-11-29:11:58:37,969 INFO [__main__.py:205] Selected Tasks: ['demo_mmlu_high_school_geography_continuation']\n", + "2023-11-29:11:58:37,972 WARNING [evaluator.py:93] generation_kwargs specified through cli, these settings will be used over set parameters in yaml tasks.\n", + "2023-11-29:11:58:38,008 INFO [huggingface.py:120] Using device 'cuda'\n", + "2023-11-29:11:58:59,758 INFO [task.py:355] Building contexts for task on rank 0...\n", + "2023-11-29:11:58:59,777 INFO [evaluator.py:319] Running loglikelihood requests\n", + "100% 40/40 [00:02<00:00, 16.23it/s]\n", + "fatal: not a git repository (or any of the parent directories): .git\n", + "hf (pretrained=EleutherAI/pythia-2.8b), gen_kwargs: (), limit: 10.0, num_fewshot: None, batch_size: 1\n", + "| Tasks |Version|Filter|n-shot| Metric |Value| |Stderr|\n", + "|--------------------------------------------|-------|------|-----:|--------|----:|---|-----:|\n", + "|demo_mmlu_high_school_geography_continuation|Yaml |none | 0|acc | 0.1|± |0.1000|\n", + "| | |none | 0|acc_norm| 0.2|± |0.1333|\n", + "\n" + ] + } + ], + "source": [ + "# !accelerate launch --no_python\n", + "!lm_eval \\\n", + " --model hf \\\n", + " --model_args pretrained=EleutherAI/pythia-2.8b \\\n", + " --include_path ./ \\\n", + " --tasks demo_mmlu_high_school_geography_continuation \\\n", + " --limit 10 \\\n", + " --output output/mmlu_high_school_geography_continuation/ \\\n", + " --log_samples" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-_CVnDirdy7j" + }, + "source": [ + "If we take a look at the samples, we can see that it is in fact evaluating the continuation based on the choices rather than the letters." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "id": "duBDqC6PAdjL" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "id": "-_CVnDirdy7j" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2023-11-29:11:58:21,284 INFO [utils.py:160] NumExpr defaulting to 2 threads.\n", - "2023-11-29 11:58:22.850159: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", - "2023-11-29 11:58:22.850219: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", - "2023-11-29 11:58:22.850254: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", - "2023-11-29 11:58:24.948103: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", - "2023-11-29:11:58:28,460 INFO [__main__.py:132] Verbosity set to INFO\n", - "2023-11-29:11:58:37,935 WARNING [__main__.py:138] --limit SHOULD ONLY BE USED FOR TESTING.REAL METRICS SHOULD NOT BE COMPUTED USING LIMIT.\n", - "2023-11-29:11:58:37,935 INFO [__main__.py:143] Including path: ./\n", - "2023-11-29:11:58:37,969 INFO [__main__.py:205] Selected Tasks: ['demo_mmlu_high_school_geography_continuation']\n", - "2023-11-29:11:58:37,972 WARNING [evaluator.py:93] generation_kwargs specified through cli, these settings will be used over set parameters in yaml tasks.\n", - "2023-11-29:11:58:38,008 INFO [huggingface.py:120] Using device 'cuda'\n", - "2023-11-29:11:58:59,758 INFO [task.py:355] Building contexts for task on rank 0...\n", - "2023-11-29:11:58:59,777 INFO [evaluator.py:319] Running loglikelihood requests\n", - "100% 40/40 [00:02<00:00, 16.23it/s]\n", - "fatal: not a git repository (or any of the parent directories): .git\n", - "hf (pretrained=EleutherAI/pythia-2.8b), gen_kwargs: (), limit: 10.0, num_fewshot: None, batch_size: 1\n", - "| Tasks |Version|Filter|n-shot| Metric |Value| |Stderr|\n", - "|--------------------------------------------|-------|------|-----:|--------|----:|---|-----:|\n", - "|demo_mmlu_high_school_geography_continuation|Yaml |none | 0|acc | 0.1|± |0.1000|\n", - "| | |none | 0|acc_norm| 0.2|± |0.1333|\n", - "\n" - ] - } - ], - "source": [ - "# !accelerate launch --no_python\n", - "!lm_eval \\\n", - " --model hf \\\n", - " --model_args pretrained=EleutherAI/pythia-2.8b \\\n", - " --include_path ./ \\\n", - " --tasks demo_mmlu_high_school_geography_continuation \\\n", - " --limit 10 \\\n", - " --output output/mmlu_high_school_geography_continuation/ \\\n", - " --log_samples\n" + "data": { + "application/javascript": "\n ((filepath) => {{\n if (!google.colab.kernel.accessAllowed) {{\n return;\n }}\n google.colab.files.view(filepath);\n }})(\"/content/output/mmlu_high_school_geography_continuation/pretrained__EleutherAI__pythia-2.8b_demo_mmlu_high_school_geography_continuation.jsonl\")", + "text/plain": [ + "" ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from google.colab import files\n", + "\n", + "\n", + "files.view(\n", + " \"output/mmlu_high_school_geography_continuation/pretrained__EleutherAI__pythia-2.8b_demo_mmlu_high_school_geography_continuation.jsonl\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6p0-KPwAgK5j" + }, + "source": [ + "## Closer Look at YAML Fields\n", + "\n", + "To prepare a task we can simply fill in a YAML config with the relevant information.\n", + "\n", + "`output_type`\n", + "The current provided evaluation types comprise of the following:\n", + "1. `loglikelihood`: Evaluates the loglikelihood of a continuation, conditioned on some input string.\n", + "2. `loglikelihood_rolling`: evaluate the loglikelihood of producing a string, conditioned on the empty string. (Used for perplexity evaluations)\n", + "3. `multiple_choice`: Evaluates loglikelihood among the a number of choices predicted by the model.\n", + "4. `greedy_until`: Model outputs greedy generation (can be configured to to use beam search and other generation-related parameters)\n", + "\n", + "The core prompt revolves around 3 fields.\n", + "1. `doc_to_text`: Denotes the prompt template that will be used as input to the model.\n", + "2. `doc_to_choice`: Available choices that will be used as continuation for the model. This is used when the `output_type` is `multiple_choice`, and otherwise can be left as `None`.\n", + "3. `doc_to_target`: When `output_type` is `multiple_choice`, this can be an index that corresponds to the correct answer, or the answer string itself (must be a subset of `doc_to_choice`). For other tasks, this is expected to be a string. You can fill this field with a feature name from the HF dataset so long as the resulting feature follows the conditioned described.\n", + "\n", + "These three fields can be expressed as strings, column names from the source dataset, or as Jinja2 templates that can use fields from the source dataset as variables.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6p0-KPwAgK5j" + }, + "source": [ + "## What if Jinja is not Sufficient?\n", + "\n", + "There can be times where the Jinja2 templating language is not enough to make the prompt we had in mind. There are a few ways to circumvent this limitation:\n", + "\n", + "1. Use `!function` operator for the prompt-related fields to pass a python function that takes as input the dataset row, and will output the prompt template component.\n", + "2. Perform a transformation on the dataset beforehand." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Below, we show an example of using `!function` to create `doc_to_text` from a python function:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "DYZ5c0JhR1lJ", + "outputId": "ca945235-fb9e-4f17-8bfa-78e7d6ec1490" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "-_CVnDirdy7j" - }, - "source": [ - "If we take a look at the samples, we can see that it is in fact evaluating the continuation based on the choices rather than the letters." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "2023-11-29:11:59:08,312 INFO [utils.py:160] NumExpr defaulting to 2 threads.\n", + "2023-11-29 11:59:09.348327: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "2023-11-29 11:59:09.348387: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "2023-11-29 11:59:09.348421: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "2023-11-29 11:59:10.573752: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", + "2023-11-29:11:59:14,044 INFO [__main__.py:132] Verbosity set to INFO\n", + "2023-11-29:11:59:23,654 WARNING [__main__.py:138] --limit SHOULD ONLY BE USED FOR TESTING.REAL METRICS SHOULD NOT BE COMPUTED USING LIMIT.\n", + "2023-11-29:11:59:23,654 INFO [__main__.py:143] Including path: ./\n", + "2023-11-29:11:59:23,678 INFO [__main__.py:205] Selected Tasks: ['demo_mmlu_high_school_geography_function_prompt']\n", + "2023-11-29:11:59:23,679 WARNING [evaluator.py:93] generation_kwargs specified through cli, these settings will be used over set parameters in yaml tasks.\n", + "2023-11-29:11:59:23,708 INFO [huggingface.py:120] Using device 'cuda'\n", + "2023-11-29:11:59:44,516 INFO [task.py:355] Building contexts for task on rank 0...\n", + "2023-11-29:11:59:44,524 INFO [evaluator.py:319] Running loglikelihood requests\n", + "100% 40/40 [00:02<00:00, 15.41it/s]\n", + "fatal: not a git repository (or any of the parent directories): .git\n", + "hf (pretrained=EleutherAI/pythia-2.8b), gen_kwargs: (), limit: 10.0, num_fewshot: None, batch_size: 1\n", + "| Tasks |Version|Filter|n-shot| Metric |Value| |Stderr|\n", + "|-----------------------------------------------|-------|------|-----:|--------|----:|---|-----:|\n", + "|demo_mmlu_high_school_geography_function_prompt|Yaml |none | 0|acc | 0.1|± |0.1000|\n", + "| | |none | 0|acc_norm| 0.2|± |0.1333|\n", + "\n" + ] + } + ], + "source": [ + "YAML_mmlu_geo_string = \"\"\"\n", + "include: mmlu_high_school_geography.yaml\n", + "task: demo_mmlu_high_school_geography_function_prompt\n", + "doc_to_text: !function utils.doc_to_text\n", + "doc_to_choice: \"{{choices}}\"\n", + "\"\"\"\n", + "with open(\"demo_mmlu_high_school_geography_function_prompt.yaml\", \"w\") as f:\n", + " f.write(YAML_mmlu_geo_string)\n", + "\n", + "DOC_TO_TEXT = \"\"\"\n", + "def doc_to_text(x):\n", + " question = x[\"question\"].strip()\n", + " choices = x[\"choices\"]\n", + " option_a = choices[0]\n", + " option_b = choices[1]\n", + " option_c = choices[2]\n", + " option_d = choices[3]\n", + " return f\"{question}\\\\nA. {option_a}\\\\nB. {option_b}\\\\nC. {option_c}\\\\nD. {option_d}\\\\nAnswer:\"\n", + "\"\"\"\n", + "with open(\"utils.py\", \"w\") as f:\n", + " f.write(DOC_TO_TEXT)\n", + "\n", + "!lm_eval \\\n", + " --model hf \\\n", + " --model_args pretrained=EleutherAI/pythia-2.8b \\\n", + " --include_path ./ \\\n", + " --tasks demo_mmlu_high_school_geography_function_prompt \\\n", + " --limit 10 \\\n", + " --output output/demo_mmlu_high_school_geography_function_prompt/ \\\n", + " --log_samples" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we'll also show how to do this via preprocessing the dataset as necessary using the `process_docs` config field:\n", + "\n", + "We will write a function that will modify each document in our evaluation dataset's split to add a field that is suitable for us to use in `doc_to_text`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "YAML_mmlu_geo_string = \"\"\"\n", + "include: mmlu_high_school_geography.yaml\n", + "task: demo_mmlu_high_school_geography_function_prompt_2\n", + "process_docs: !function utils_process_docs.process_docs\n", + "doc_to_text: \"{{input}}\"\n", + "doc_to_choice: \"{{choices}}\"\n", + "\"\"\"\n", + "with open(\"demo_mmlu_high_school_geography_process_docs.yaml\", \"w\") as f:\n", + " f.write(YAML_mmlu_geo_string)\n", + "\n", + "DOC_TO_TEXT = \"\"\"\n", + "def process_docs(dataset):\n", + " def _process_doc(x):\n", + " question = x[\"question\"].strip()\n", + " choices = x[\"choices\"]\n", + " option_a = choices[0]\n", + " option_b = choices[1]\n", + " option_c = choices[2]\n", + " option_d = choices[3]\n", + " doc[\"input\"] = f\"{question}\\\\nA. {option_a}\\\\nB. {option_b}\\\\nC. {option_c}\\\\nD. {option_d}\\\\nAnswer:\"\n", + " return out_doc\n", + "\n", + " return dataset.map(_process_doc)\n", + "\"\"\"\n", + "\n", + "with open(\"utils_process_docs.py\", \"w\") as f:\n", + " f.write(DOC_TO_TEXT)\n", + "\n", + "!lm_eval \\\n", + " --model hf \\\n", + " --model_args pretrained=EleutherAI/pythia-2.8b \\\n", + " --include_path ./ \\\n", + " --tasks demo_mmlu_high_school_geography_function_prompt_2 \\\n", + " --limit 10 \\\n", + " --output output/demo_mmlu_high_school_geography_function_prompt_2/ \\\n", + " --log_samples" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We hope that this explainer gives you a sense of what can be done with and how to work with LM-Evaluation-Harnes v0.4.0 ! \n", + "\n", + "For more information, check out our documentation pages in the `docs/` folder, and if you have questions, please raise them in GitHub issues, or in #lm-thunderdome or #release-discussion on the EleutherAI discord server." + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "collapsed_sections": [ + "zAov81vTbL2K" + ], + "gpuType": "T4", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "name": "python" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "46f521b73fd943c081c648fd873ebc0a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "id": "duBDqC6PAdjL" - }, - "outputs": [ - { - "data": { - "application/javascript": "\n ((filepath) => {{\n if (!google.colab.kernel.accessAllowed) {{\n return;\n }}\n google.colab.files.view(filepath);\n }})(\"/content/output/mmlu_high_school_geography_continuation/pretrained__EleutherAI__pythia-2.8b_demo_mmlu_high_school_geography_continuation.jsonl\")", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from google.colab import files\n", - "files.view(\"output/mmlu_high_school_geography_continuation/pretrained__EleutherAI__pythia-2.8b_demo_mmlu_high_school_geography_continuation.jsonl\")\n" - ] + "48763b6233374554ae76035c0483066f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "6p0-KPwAgK5j" - }, - "source": [ - "## Closer Look at YAML Fields\n", - "\n", - "To prepare a task we can simply fill in a YAML config with the relevant information.\n", - "\n", - "`output_type`\n", - "The current provided evaluation types comprise of the following:\n", - "1. `loglikelihood`: Evaluates the loglikelihood of a continuation, conditioned on some input string.\n", - "2. `loglikelihood_rolling`: evaluate the loglikelihood of producing a string, conditioned on the empty string. (Used for perplexity evaluations)\n", - "3. `multiple_choice`: Evaluates loglikelihood among the a number of choices predicted by the model.\n", - "4. `greedy_until`: Model outputs greedy generation (can be configured to to use beam search and other generation-related parameters)\n", - "\n", - "The core prompt revolves around 3 fields.\n", - "1. `doc_to_text`: Denotes the prompt template that will be used as input to the model.\n", - "2. `doc_to_choice`: Available choices that will be used as continuation for the model. This is used when the `output_type` is `multiple_choice`, and otherwise can be left as `None`.\n", - "3. `doc_to_target`: When `output_type` is `multiple_choice`, this can be an index that corresponds to the correct answer, or the answer string itself (must be a subset of `doc_to_choice`). For other tasks, this is expected to be a string. You can fill this field with a feature name from the HF dataset so long as the resulting feature follows the conditioned described.\n", - "\n", - "These three fields can be expressed as strings, column names from the source dataset, or as Jinja2 templates that can use fields from the source dataset as variables.\n" - ] + "4986a21eb560448fa79f4b25cde48951": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "6p0-KPwAgK5j" - }, - "source": [ - "## What if Jinja is not Sufficient?\n", - "\n", - "There can be times where the Jinja2 templating language is not enough to make the prompt we had in mind. There are a few ways to circumvent this limitation:\n", - "\n", - "1. Use `!function` operator for the prompt-related fields to pass a python function that takes as input the dataset row, and will output the prompt template component.\n", - "2. Perform a transformation on the dataset beforehand." - ] + "6b2d90209ec14230b3d58a74ac9b83bf": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Below, we show an example of using `!function` to create `doc_to_text` from a python function:" - ] + "7c5689bc13684db8a22681f41863dddd": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "DYZ5c0JhR1lJ", - "outputId": "ca945235-fb9e-4f17-8bfa-78e7d6ec1490" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2023-11-29:11:59:08,312 INFO [utils.py:160] NumExpr defaulting to 2 threads.\n", - "2023-11-29 11:59:09.348327: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", - "2023-11-29 11:59:09.348387: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", - "2023-11-29 11:59:09.348421: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", - "2023-11-29 11:59:10.573752: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", - "2023-11-29:11:59:14,044 INFO [__main__.py:132] Verbosity set to INFO\n", - "2023-11-29:11:59:23,654 WARNING [__main__.py:138] --limit SHOULD ONLY BE USED FOR TESTING.REAL METRICS SHOULD NOT BE COMPUTED USING LIMIT.\n", - "2023-11-29:11:59:23,654 INFO [__main__.py:143] Including path: ./\n", - "2023-11-29:11:59:23,678 INFO [__main__.py:205] Selected Tasks: ['demo_mmlu_high_school_geography_function_prompt']\n", - "2023-11-29:11:59:23,679 WARNING [evaluator.py:93] generation_kwargs specified through cli, these settings will be used over set parameters in yaml tasks.\n", - "2023-11-29:11:59:23,708 INFO [huggingface.py:120] Using device 'cuda'\n", - "2023-11-29:11:59:44,516 INFO [task.py:355] Building contexts for task on rank 0...\n", - "2023-11-29:11:59:44,524 INFO [evaluator.py:319] Running loglikelihood requests\n", - "100% 40/40 [00:02<00:00, 15.41it/s]\n", - "fatal: not a git repository (or any of the parent directories): .git\n", - "hf (pretrained=EleutherAI/pythia-2.8b), gen_kwargs: (), limit: 10.0, num_fewshot: None, batch_size: 1\n", - "| Tasks |Version|Filter|n-shot| Metric |Value| |Stderr|\n", - "|-----------------------------------------------|-------|------|-----:|--------|----:|---|-----:|\n", - "|demo_mmlu_high_school_geography_function_prompt|Yaml |none | 0|acc | 0.1|± |0.1000|\n", - "| | |none | 0|acc_norm| 0.2|± |0.1333|\n", - "\n" - ] - } + "a1d3a8aa016544a78e8821c8f6199e06": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_f61ed33fad754146bdd2ac9db1ba1c48", + "IPY_MODEL_bfa0af6aeff344c6845e1080a878e92e", + "IPY_MODEL_fd1ad9e0367d4004aae853b91c3a7617" ], - "source": [ - "YAML_mmlu_geo_string = '''\n", - "include: mmlu_high_school_geography.yaml\n", - "task: demo_mmlu_high_school_geography_function_prompt\n", - "doc_to_text: !function utils.doc_to_text\n", - "doc_to_choice: \"{{choices}}\"\n", - "'''\n", - "with open('demo_mmlu_high_school_geography_function_prompt.yaml', 'w') as f:\n", - " f.write(YAML_mmlu_geo_string)\n", - "\n", - "DOC_TO_TEXT = '''\n", - "def doc_to_text(x):\n", - " question = x[\"question\"].strip()\n", - " choices = x[\"choices\"]\n", - " option_a = choices[0]\n", - " option_b = choices[1]\n", - " option_c = choices[2]\n", - " option_d = choices[3]\n", - " return f\"{question}\\\\nA. {option_a}\\\\nB. {option_b}\\\\nC. {option_c}\\\\nD. {option_d}\\\\nAnswer:\"\n", - "'''\n", - "with open('utils.py', 'w') as f:\n", - " f.write(DOC_TO_TEXT)\n", - "\n", - "!lm_eval \\\n", - " --model hf \\\n", - " --model_args pretrained=EleutherAI/pythia-2.8b \\\n", - " --include_path ./ \\\n", - " --tasks demo_mmlu_high_school_geography_function_prompt \\\n", - 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elif type(gold) != type(result): + elif type(gold) is type(result): # cast gold to the same type as result gold = type(result)(gold) diff --git a/lm_eval/tasks/galician_bench/flores_gl/create_yamls_flores_gl.py b/lm_eval/tasks/galician_bench/flores_gl/create_yamls_flores_gl.py index ba8be886..c98b9b21 100644 --- a/lm_eval/tasks/galician_bench/flores_gl/create_yamls_flores_gl.py +++ b/lm_eval/tasks/galician_bench/flores_gl/create_yamls_flores_gl.py @@ -1,53 +1,258 @@ +# ruff: noqa: E731, E741 """ Script to generate task YAMLs for the FLORES-200 dataset. Based on `tasks/translation/utils.py`. """ import argparse +import itertools + import yaml -from langcodes import * -from itertools import * +from langcodes import Language + # utils flatten = lambda l: list(itertools.chain(*l)) # constants _LANGUAGES = [ -"ace_Arab", "bam_Latn", "dzo_Tibt", "hin_Deva", "khm_Khmr", "mag_Deva", "pap_Latn", "sot_Latn", "tur_Latn", -"ace_Latn", "ban_Latn", "ell_Grek", "hne_Deva", "kik_Latn", "mai_Deva", "pbt_Arab", "spa_Latn", "twi_Latn", -"acm_Arab", "bel_Cyrl", "eng_Latn", "hrv_Latn", "kin_Latn", "mal_Mlym", "pes_Arab", "srd_Latn", "tzm_Tfng", -"acq_Arab", "bem_Latn", "epo_Latn", "hun_Latn", "kir_Cyrl", "mar_Deva", "plt_Latn", "srp_Cyrl", "uig_Arab", -"aeb_Arab", "ben_Beng", "est_Latn", "hye_Armn", "kmb_Latn", "min_Arab", "pol_Latn", "ssw_Latn", "ukr_Cyrl", -"afr_Latn", "bho_Deva", "eus_Latn", "ibo_Latn", "kmr_Latn", "min_Latn", "por_Latn", "sun_Latn", "umb_Latn", -"ajp_Arab", "bjn_Arab", "ewe_Latn", "ilo_Latn", "knc_Arab", "mkd_Cyrl", "prs_Arab", "swe_Latn", "urd_Arab", -"aka_Latn", "bjn_Latn", "fao_Latn", "ind_Latn", "knc_Latn", "mlt_Latn", "quy_Latn", "swh_Latn", "uzn_Latn", -"als_Latn", "bod_Tibt", "fij_Latn", "isl_Latn", "kon_Latn", "mni_Beng", "ron_Latn", "szl_Latn", "vec_Latn", -"amh_Ethi", "bos_Latn", "fin_Latn", "ita_Latn", "kor_Hang", "mos_Latn", "run_Latn", "tam_Taml", "vie_Latn", -"apc_Arab", "bug_Latn", "fon_Latn", "jav_Latn", "lao_Laoo", "mri_Latn", "rus_Cyrl", "taq_Latn", "war_Latn", -"arb_Arab", "bul_Cyrl", "fra_Latn", "jpn_Jpan", "lij_Latn", "mya_Mymr", "sag_Latn", "taq_Tfng", "wol_Latn", -"arb_Latn", "cat_Latn", "fur_Latn", "kab_Latn", "lim_Latn", "nld_Latn", "san_Deva", "tat_Cyrl", "xho_Latn", -"ars_Arab", "ceb_Latn", "fuv_Latn", "kac_Latn", "lin_Latn", "nno_Latn", "sat_Olck", "tel_Telu", "ydd_Hebr", -"ary_Arab", "ces_Latn", "gaz_Latn", "kam_Latn", "lit_Latn", "nob_Latn", "scn_Latn", "tgk_Cyrl", "yor_Latn", -"arz_Arab", "cjk_Latn", "gla_Latn", "kan_Knda", "lmo_Latn", "npi_Deva", "shn_Mymr", "tgl_Latn", "yue_Hant", -"asm_Beng", "ckb_Arab", "gle_Latn", "kas_Arab", "ltg_Latn", "nso_Latn", "sin_Sinh", "tha_Thai", "zho_Hans", -"ast_Latn", "crh_Latn", "glg_Latn", "kas_Deva", "ltz_Latn", "nus_Latn", "slk_Latn", "tir_Ethi", "zho_Hant", -"awa_Deva", "cym_Latn", "grn_Latn", "kat_Geor", "lua_Latn", "nya_Latn", "slv_Latn", "tpi_Latn", "zsm_Latn", -"ayr_Latn", "dan_Latn", "guj_Gujr", "kaz_Cyrl", "lug_Latn", "oci_Latn", "smo_Latn", "tsn_Latn", "zul_Latn", -"azb_Arab", "deu_Latn", "hat_Latn", "kbp_Latn", "luo_Latn", "ory_Orya", "sna_Latn", "tso_Latn", -"azj_Latn", "dik_Latn", "hau_Latn", "kea_Latn", "lus_Latn", "pag_Latn", "snd_Arab", "tuk_Latn", -"bak_Cyrl", "dyu_Latn", "heb_Hebr", "khk_Cyrl", "lvs_Latn", "pan_Guru", "som_Latn", "tum_Latn" + "ace_Arab", + "bam_Latn", + "dzo_Tibt", + "hin_Deva", + "khm_Khmr", + "mag_Deva", + "pap_Latn", + "sot_Latn", + "tur_Latn", + "ace_Latn", + "ban_Latn", + "ell_Grek", + "hne_Deva", + "kik_Latn", + "mai_Deva", + "pbt_Arab", + "spa_Latn", + "twi_Latn", + "acm_Arab", + "bel_Cyrl", + "eng_Latn", + "hrv_Latn", + "kin_Latn", + "mal_Mlym", + "pes_Arab", + "srd_Latn", + "tzm_Tfng", + "acq_Arab", + "bem_Latn", + "epo_Latn", + "hun_Latn", + "kir_Cyrl", + "mar_Deva", + "plt_Latn", + "srp_Cyrl", + "uig_Arab", + "aeb_Arab", + "ben_Beng", + "est_Latn", + "hye_Armn", + "kmb_Latn", + "min_Arab", + "pol_Latn", + "ssw_Latn", + "ukr_Cyrl", + "afr_Latn", + "bho_Deva", + "eus_Latn", + "ibo_Latn", + "kmr_Latn", + "min_Latn", + "por_Latn", + "sun_Latn", + "umb_Latn", + "ajp_Arab", + "bjn_Arab", + "ewe_Latn", + "ilo_Latn", + "knc_Arab", + "mkd_Cyrl", + "prs_Arab", + "swe_Latn", + "urd_Arab", + "aka_Latn", + "bjn_Latn", + "fao_Latn", + "ind_Latn", + "knc_Latn", + "mlt_Latn", + "quy_Latn", + "swh_Latn", + "uzn_Latn", + "als_Latn", + "bod_Tibt", + "fij_Latn", + "isl_Latn", + "kon_Latn", + "mni_Beng", + "ron_Latn", + "szl_Latn", + "vec_Latn", + "amh_Ethi", + "bos_Latn", + "fin_Latn", + "ita_Latn", + "kor_Hang", + "mos_Latn", + "run_Latn", + "tam_Taml", + "vie_Latn", + "apc_Arab", + "bug_Latn", + "fon_Latn", + "jav_Latn", + "lao_Laoo", + "mri_Latn", + "rus_Cyrl", + "taq_Latn", + "war_Latn", + "arb_Arab", + "bul_Cyrl", + "fra_Latn", + "jpn_Jpan", + "lij_Latn", + "mya_Mymr", + "sag_Latn", + "taq_Tfng", + "wol_Latn", + "arb_Latn", + "cat_Latn", + "fur_Latn", + "kab_Latn", + "lim_Latn", + "nld_Latn", + "san_Deva", + "tat_Cyrl", + "xho_Latn", + "ars_Arab", + "ceb_Latn", + "fuv_Latn", + "kac_Latn", + "lin_Latn", + "nno_Latn", + "sat_Olck", + "tel_Telu", + "ydd_Hebr", + "ary_Arab", + "ces_Latn", + "gaz_Latn", + "kam_Latn", + "lit_Latn", + "nob_Latn", + "scn_Latn", + "tgk_Cyrl", + "yor_Latn", + "arz_Arab", + "cjk_Latn", + "gla_Latn", + "kan_Knda", + "lmo_Latn", + "npi_Deva", + "shn_Mymr", + "tgl_Latn", + "yue_Hant", + "asm_Beng", + "ckb_Arab", + "gle_Latn", + "kas_Arab", + "ltg_Latn", + "nso_Latn", + "sin_Sinh", + "tha_Thai", + "zho_Hans", + "ast_Latn", + "crh_Latn", + "glg_Latn", + "kas_Deva", + "ltz_Latn", + "nus_Latn", + "slk_Latn", + "tir_Ethi", + "zho_Hant", + "awa_Deva", + "cym_Latn", + "grn_Latn", + "kat_Geor", + "lua_Latn", + "nya_Latn", + "slv_Latn", + "tpi_Latn", + "zsm_Latn", + "ayr_Latn", + "dan_Latn", + "guj_Gujr", + "kaz_Cyrl", + "lug_Latn", + "oci_Latn", + "smo_Latn", + "tsn_Latn", + "zul_Latn", + "azb_Arab", + "deu_Latn", + "hat_Latn", + "kbp_Latn", + "luo_Latn", + "ory_Orya", + "sna_Latn", + "tso_Latn", + "azj_Latn", + "dik_Latn", + "hau_Latn", + "kea_Latn", + "lus_Latn", + "pag_Latn", + "snd_Arab", + "tuk_Latn", + "bak_Cyrl", + "dyu_Latn", + "heb_Hebr", + "khk_Cyrl", + "lvs_Latn", + "pan_Guru", + "som_Latn", + "tum_Latn", +] +LANGUAGE_PAIRS = [ + (a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1 :] ] -LANGUAGE_PAIRS = [(a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1:]] -LANGUAGES_OF_INTEREST = ["cat_Latn", "spa_Latn", "eng_Latn", "glg_Latn", "eus_Latn", "ita_Latn", "deu_Latn", "por_Latn", "fra_Latn"] +LANGUAGES_OF_INTEREST = [ + "cat_Latn", + "spa_Latn", + "eng_Latn", + "glg_Latn", + "eus_Latn", + "ita_Latn", + "deu_Latn", + "por_Latn", + "fra_Latn", +] MAIN_LANG = "glg_Latn" -LANGUAGE_PAIRS = [(a, b) for (a, b) in LANGUAGE_PAIRS if a in LANGUAGES_OF_INTEREST and b in LANGUAGES_OF_INTEREST and MAIN_LANG in (a, b)] +LANGUAGE_PAIRS = [ + (a, b) + for (a, b) in LANGUAGE_PAIRS + if a in LANGUAGES_OF_INTEREST and b in LANGUAGES_OF_INTEREST and MAIN_LANG in (a, b) +] # auxiliary functions -code_to_language_name = lambda code: Language.make(language=Language.get(code)["language"]).display_name() +code_to_language_name = lambda code: Language.make( + language=Language.get(code)["language"] +).display_name() code_to_short_name = lambda code: Language.get(code)["language"] -jinja_var = lambda s: "{{" + s + "}}" # wrapper to avoid having to escape { } in format strings +jinja_var = ( + lambda s: "{{" + s + "}}" +) # wrapper to avoid having to escape { } in format strings + def doc_to_text(src: str, tgt: str) -> str: src_name, tgt_name = map(code_to_language_name, [src, tgt]) @@ -56,12 +261,14 @@ def doc_to_text(src: str, tgt: str) -> str: {src_name} sentence: {jinja_var('sentence_' + src)} {tgt_name} sentence:""" -def doc_to_target(tgt: str) -> str: +def doc_to_target(tgt: str) -> str: return f"{jinja_var('sentence_' + tgt)}" + # main function + def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: """ Generate a YAML file for each translation direction. @@ -69,20 +276,23 @@ def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: err = [] for src, tgt in LANGUAGE_PAIRS: - # do both translation directions for each lang pair for src, tgt in [(src, tgt), (tgt, src)]: lang_pair_name = f"{code_to_short_name(src)}-{code_to_short_name(tgt)}" yaml_file_name = f"flores_{lang_pair_name}.yaml" try: - with open( f"{output_dir}/{yaml_file_name}", "w" if overwrite else "x", encoding="utf-8") as outfile: + with open( + f"{output_dir}/{yaml_file_name}", + "w" if overwrite else "x", + encoding="utf-8", + ) as outfile: print(f"Creating {yaml_file_name}...") outfile.write("# File generated by `create-yamls.py`\n") yaml.dump( { -# "group": [f"{BENCH_NAME}_bench", f"{BENCH_NAME}_bench_flores"], -# "group": "flores_gl", + # "group": [f"{BENCH_NAME}_bench", f"{BENCH_NAME}_bench_flores"], + # "group": "flores_gl", "include": "_flores_common_yaml", "task": f"flores_{lang_pair_name}", "doc_to_text": doc_to_text(src, tgt), @@ -105,11 +315,19 @@ def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: def main() -> None: parser = argparse.ArgumentParser() - parser.add_argument("--overwrite", default=False, action="store_true", help="Overwrite files if they already exist") - parser.add_argument( "--output-dir", default=".", help="Directory to write yaml files to" ) + parser.add_argument( + "--overwrite", + default=False, + action="store_true", + help="Overwrite files if they already exist", + ) + parser.add_argument( + "--output-dir", default=".", help="Directory to write yaml files to" + ) args = parser.parse_args() gen_lang_yamls(output_dir=args.output_dir, overwrite=args.overwrite) + if __name__ == "__main__": main() diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/create_yamls_flores_pt.py b/lm_eval/tasks/portuguese_bench/flores_pt/create_yamls_flores_pt.py index 4a1dffcf..677e6bb4 100644 --- a/lm_eval/tasks/portuguese_bench/flores_pt/create_yamls_flores_pt.py +++ b/lm_eval/tasks/portuguese_bench/flores_pt/create_yamls_flores_pt.py @@ -1,53 +1,258 @@ +# ruff: noqa: E731, E741 """ Script to generate task YAMLs for the FLORES-200 dataset. Based on `tasks/translation/utils.py`. """ import argparse +import itertools + import yaml -from langcodes import * -from itertools import * +from langcodes import Language + # utils flatten = lambda l: list(itertools.chain(*l)) # constants _LANGUAGES = [ -"ace_Arab", "bam_Latn", "dzo_Tibt", "hin_Deva", "khm_Khmr", "mag_Deva", "pap_Latn", "sot_Latn", "tur_Latn", -"ace_Latn", "ban_Latn", "ell_Grek", "hne_Deva", "kik_Latn", "mai_Deva", "pbt_Arab", "spa_Latn", "twi_Latn", -"acm_Arab", "bel_Cyrl", "eng_Latn", "hrv_Latn", "kin_Latn", "mal_Mlym", "pes_Arab", "srd_Latn", "tzm_Tfng", -"acq_Arab", "bem_Latn", "epo_Latn", "hun_Latn", "kir_Cyrl", "mar_Deva", "plt_Latn", "srp_Cyrl", "uig_Arab", -"aeb_Arab", "ben_Beng", "est_Latn", "hye_Armn", "kmb_Latn", "min_Arab", "pol_Latn", "ssw_Latn", "ukr_Cyrl", -"afr_Latn", "bho_Deva", "eus_Latn", "ibo_Latn", "kmr_Latn", "min_Latn", "por_Latn", "sun_Latn", "umb_Latn", -"ajp_Arab", "bjn_Arab", "ewe_Latn", "ilo_Latn", "knc_Arab", "mkd_Cyrl", "prs_Arab", "swe_Latn", "urd_Arab", -"aka_Latn", "bjn_Latn", "fao_Latn", "ind_Latn", "knc_Latn", "mlt_Latn", "quy_Latn", "swh_Latn", "uzn_Latn", -"als_Latn", "bod_Tibt", "fij_Latn", "isl_Latn", "kon_Latn", "mni_Beng", "ron_Latn", "szl_Latn", "vec_Latn", -"amh_Ethi", "bos_Latn", "fin_Latn", "ita_Latn", "kor_Hang", "mos_Latn", "run_Latn", "tam_Taml", "vie_Latn", -"apc_Arab", "bug_Latn", "fon_Latn", "jav_Latn", "lao_Laoo", "mri_Latn", "rus_Cyrl", "taq_Latn", "war_Latn", -"arb_Arab", "bul_Cyrl", "fra_Latn", "jpn_Jpan", "lij_Latn", "mya_Mymr", "sag_Latn", "taq_Tfng", "wol_Latn", -"arb_Latn", "cat_Latn", "fur_Latn", "kab_Latn", "lim_Latn", "nld_Latn", "san_Deva", "tat_Cyrl", "xho_Latn", -"ars_Arab", "ceb_Latn", "fuv_Latn", "kac_Latn", "lin_Latn", "nno_Latn", "sat_Olck", "tel_Telu", "ydd_Hebr", -"ary_Arab", "ces_Latn", "gaz_Latn", "kam_Latn", "lit_Latn", "nob_Latn", "scn_Latn", "tgk_Cyrl", "yor_Latn", -"arz_Arab", "cjk_Latn", "gla_Latn", "kan_Knda", "lmo_Latn", "npi_Deva", "shn_Mymr", "tgl_Latn", "yue_Hant", -"asm_Beng", "ckb_Arab", "gle_Latn", "kas_Arab", "ltg_Latn", "nso_Latn", "sin_Sinh", "tha_Thai", "zho_Hans", -"ast_Latn", "crh_Latn", "glg_Latn", "kas_Deva", "ltz_Latn", "nus_Latn", "slk_Latn", "tir_Ethi", "zho_Hant", -"awa_Deva", "cym_Latn", "grn_Latn", "kat_Geor", "lua_Latn", "nya_Latn", "slv_Latn", "tpi_Latn", "zsm_Latn", -"ayr_Latn", "dan_Latn", "guj_Gujr", "kaz_Cyrl", "lug_Latn", "oci_Latn", "smo_Latn", "tsn_Latn", "zul_Latn", -"azb_Arab", "deu_Latn", "hat_Latn", "kbp_Latn", "luo_Latn", "ory_Orya", "sna_Latn", "tso_Latn", -"azj_Latn", "dik_Latn", "hau_Latn", "kea_Latn", "lus_Latn", "pag_Latn", "snd_Arab", "tuk_Latn", -"bak_Cyrl", "dyu_Latn", "heb_Hebr", "khk_Cyrl", "lvs_Latn", "pan_Guru", "som_Latn", "tum_Latn" + "ace_Arab", + "bam_Latn", + "dzo_Tibt", + "hin_Deva", + "khm_Khmr", + "mag_Deva", + "pap_Latn", + "sot_Latn", + "tur_Latn", + "ace_Latn", + "ban_Latn", + "ell_Grek", + "hne_Deva", + "kik_Latn", + "mai_Deva", + "pbt_Arab", + "spa_Latn", + "twi_Latn", + "acm_Arab", + "bel_Cyrl", + "eng_Latn", + "hrv_Latn", + "kin_Latn", + "mal_Mlym", + "pes_Arab", + "srd_Latn", + "tzm_Tfng", + "acq_Arab", + "bem_Latn", + "epo_Latn", + "hun_Latn", + "kir_Cyrl", + "mar_Deva", + "plt_Latn", + "srp_Cyrl", + "uig_Arab", + "aeb_Arab", + "ben_Beng", + "est_Latn", + "hye_Armn", + "kmb_Latn", + "min_Arab", + "pol_Latn", + "ssw_Latn", + "ukr_Cyrl", + "afr_Latn", + "bho_Deva", + "eus_Latn", + "ibo_Latn", + "kmr_Latn", + "min_Latn", + "por_Latn", + "sun_Latn", + "umb_Latn", + "ajp_Arab", + "bjn_Arab", + "ewe_Latn", + "ilo_Latn", + "knc_Arab", + "mkd_Cyrl", + "prs_Arab", + "swe_Latn", + "urd_Arab", + "aka_Latn", + "bjn_Latn", + "fao_Latn", + "ind_Latn", + "knc_Latn", + "mlt_Latn", + "quy_Latn", + "swh_Latn", + "uzn_Latn", + "als_Latn", + "bod_Tibt", + "fij_Latn", + "isl_Latn", + "kon_Latn", + "mni_Beng", + "ron_Latn", + "szl_Latn", + "vec_Latn", + "amh_Ethi", + "bos_Latn", + "fin_Latn", + "ita_Latn", + "kor_Hang", + "mos_Latn", + "run_Latn", + "tam_Taml", + "vie_Latn", + "apc_Arab", + "bug_Latn", + "fon_Latn", + "jav_Latn", + "lao_Laoo", + "mri_Latn", + "rus_Cyrl", + "taq_Latn", + "war_Latn", + "arb_Arab", + "bul_Cyrl", + "fra_Latn", + "jpn_Jpan", + "lij_Latn", + "mya_Mymr", + "sag_Latn", + "taq_Tfng", + "wol_Latn", + "arb_Latn", + "cat_Latn", + "fur_Latn", + "kab_Latn", + "lim_Latn", + "nld_Latn", + "san_Deva", + "tat_Cyrl", + "xho_Latn", + "ars_Arab", + "ceb_Latn", + "fuv_Latn", + "kac_Latn", + "lin_Latn", + "nno_Latn", + "sat_Olck", + "tel_Telu", + "ydd_Hebr", + "ary_Arab", + "ces_Latn", + "gaz_Latn", + "kam_Latn", + "lit_Latn", + "nob_Latn", + "scn_Latn", + "tgk_Cyrl", + "yor_Latn", + "arz_Arab", + "cjk_Latn", + "gla_Latn", + "kan_Knda", + "lmo_Latn", + "npi_Deva", + "shn_Mymr", + "tgl_Latn", + "yue_Hant", + "asm_Beng", + "ckb_Arab", + "gle_Latn", + "kas_Arab", + "ltg_Latn", + "nso_Latn", + "sin_Sinh", + "tha_Thai", + "zho_Hans", + "ast_Latn", + "crh_Latn", + "glg_Latn", + "kas_Deva", + "ltz_Latn", + "nus_Latn", + "slk_Latn", + "tir_Ethi", + "zho_Hant", + "awa_Deva", + "cym_Latn", + "grn_Latn", + "kat_Geor", + "lua_Latn", + "nya_Latn", + "slv_Latn", + "tpi_Latn", + "zsm_Latn", + "ayr_Latn", + "dan_Latn", + "guj_Gujr", + "kaz_Cyrl", + "lug_Latn", + "oci_Latn", + "smo_Latn", + "tsn_Latn", + "zul_Latn", + "azb_Arab", + "deu_Latn", + "hat_Latn", + "kbp_Latn", + "luo_Latn", + "ory_Orya", + "sna_Latn", + "tso_Latn", + "azj_Latn", + "dik_Latn", + "hau_Latn", + "kea_Latn", + "lus_Latn", + "pag_Latn", + "snd_Arab", + "tuk_Latn", + "bak_Cyrl", + "dyu_Latn", + "heb_Hebr", + "khk_Cyrl", + "lvs_Latn", + "pan_Guru", + "som_Latn", + "tum_Latn", +] +LANGUAGE_PAIRS = [ + (a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1 :] ] -LANGUAGE_PAIRS = [(a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1:]] -LANGUAGES_OF_INTEREST = ["cat_Latn", "spa_Latn", "eng_Latn", "glg_Latn", "eus_Latn", "ita_Latn", "deu_Latn", "por_Latn", "fra_Latn"] +LANGUAGES_OF_INTEREST = [ + "cat_Latn", + "spa_Latn", + "eng_Latn", + "glg_Latn", + "eus_Latn", + "ita_Latn", + "deu_Latn", + "por_Latn", + "fra_Latn", +] MAIN_LANG = "por_Latn" -LANGUAGE_PAIRS = [(a, b) for (a, b) in LANGUAGE_PAIRS if a in LANGUAGES_OF_INTEREST and b in LANGUAGES_OF_INTEREST and MAIN_LANG in (a, b)] +LANGUAGE_PAIRS = [ + (a, b) + for (a, b) in LANGUAGE_PAIRS + if a in LANGUAGES_OF_INTEREST and b in LANGUAGES_OF_INTEREST and MAIN_LANG in (a, b) +] # auxiliary functions -code_to_language_name = lambda code: Language.make(language=Language.get(code)["language"]).display_name() +code_to_language_name = lambda code: Language.make( + language=Language.get(code)["language"] +).display_name() code_to_short_name = lambda code: Language.get(code)["language"] -jinja_var = lambda s: "{{" + s + "}}" # wrapper to avoid having to escape { } in format strings +jinja_var = ( + lambda s: "{{" + s + "}}" +) # wrapper to avoid having to escape { } in format strings + def doc_to_text(src: str, tgt: str) -> str: src_name, tgt_name = map(code_to_language_name, [src, tgt]) @@ -56,12 +261,14 @@ def doc_to_text(src: str, tgt: str) -> str: {src_name} sentence: {jinja_var('sentence_' + src)} {tgt_name} sentence:""" -def doc_to_target(tgt: str) -> str: +def doc_to_target(tgt: str) -> str: return f"{jinja_var('sentence_' + tgt)}" + # main function + def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: """ Generate a YAML file for each translation direction. @@ -69,19 +276,22 @@ def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: err = [] for src, tgt in LANGUAGE_PAIRS: - # do both translation directions for each lang pair for src, tgt in [(src, tgt), (tgt, src)]: lang_pair_name = f"{code_to_short_name(src)}-{code_to_short_name(tgt)}" yaml_file_name = f"flores_{lang_pair_name}.yaml" try: - with open( f"{output_dir}/{yaml_file_name}", "w" if overwrite else "x", encoding="utf-8") as outfile: + with open( + f"{output_dir}/{yaml_file_name}", + "w" if overwrite else "x", + encoding="utf-8", + ) as outfile: print(f"Creating {yaml_file_name}...") outfile.write("# File generated by `create-yamls.py`\n") yaml.dump( { -# "group": "flores_pt", + # "group": "flores_pt", "include": "_flores_common_yaml", "task": f"flores_{lang_pair_name}", "doc_to_text": doc_to_text(src, tgt), @@ -104,11 +314,19 @@ def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: def main() -> None: parser = argparse.ArgumentParser() - parser.add_argument("--overwrite", default=False, action="store_true", help="Overwrite files if they already exist") - parser.add_argument( "--output-dir", default=".", help="Directory to write yaml files to" ) + parser.add_argument( + "--overwrite", + default=False, + action="store_true", + help="Overwrite files if they already exist", + ) + parser.add_argument( + "--output-dir", default=".", help="Directory to write yaml files to" + ) args = parser.parse_args() gen_lang_yamls(output_dir=args.output_dir, overwrite=args.overwrite) + if __name__ == "__main__": main() diff --git a/lm_eval/tasks/spanish_bench/flores_es/create_yamls_flores_es.py b/lm_eval/tasks/spanish_bench/flores_es/create_yamls_flores_es.py index 59571e8d..bf4d49d2 100644 --- a/lm_eval/tasks/spanish_bench/flores_es/create_yamls_flores_es.py +++ b/lm_eval/tasks/spanish_bench/flores_es/create_yamls_flores_es.py @@ -1,13 +1,14 @@ +# ruff: noqa: E731, E741 """ Script to generate task YAMLs for the FLORES-200 dataset. Based on `tasks/translation/utils.py`. """ import argparse -from itertools import * +import itertools import yaml -from langcodes import * +from langcodes import Language # utils diff --git a/tests/models/test_huggingface.py b/tests/models/test_huggingface.py index 9f495402..44269692 100644 --- a/tests/models/test_huggingface.py +++ b/tests/models/test_huggingface.py @@ -5,7 +5,9 @@ import sys from pathlib import Path import numpy as np +import tokenizers import torch +from packaging.version import parse as parse_version from lm_eval import tasks from lm_eval.api.instance import Instance @@ -145,4 +147,7 @@ class Test_HFLM: context = self.LM.tok_batch_encode([TEST_STRING])[0] res = self.LM._model_generate(context, max_length=10, stop=["\n\n"]) res = self.LM.tok_decode(res[0]) - assert res == "foo bar\n!info bar" + if parse_version(tokenizers.__version__) >= parse_version("0.20.0"): + assert res == "foo bar\n !info bar" + else: + assert res == "foo bar\n!info bar" -- GitLab From bfdcdbe07d7b2ecf44268af2be37f125a6f1649e Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 7 Oct 2024 19:16:26 +0500 Subject: [PATCH 119/194] Hotfix! (#2383) * bugfix * pre-commit --- lm_eval/api/task.py | 2 +- .../flores_eu/create_yamls_flores_eu.py | 292 +++++++++++++++--- 2 files changed, 256 insertions(+), 38 deletions(-) diff --git a/lm_eval/api/task.py b/lm_eval/api/task.py index c75d2b34..ea3cae06 100644 --- a/lm_eval/api/task.py +++ b/lm_eval/api/task.py @@ -1511,7 +1511,7 @@ class ConfigurableTask(Task): # we expect multiple_targets to be a list. elif self.multiple_target: gold = list(gold) - elif type(gold) is type(result): + elif type(gold) is not type(result): # cast gold to the same type as result gold = type(result)(gold) diff --git a/lm_eval/tasks/basque_bench/flores_eu/create_yamls_flores_eu.py b/lm_eval/tasks/basque_bench/flores_eu/create_yamls_flores_eu.py index 6a41e945..723edc51 100644 --- a/lm_eval/tasks/basque_bench/flores_eu/create_yamls_flores_eu.py +++ b/lm_eval/tasks/basque_bench/flores_eu/create_yamls_flores_eu.py @@ -1,53 +1,258 @@ +# ruff: noqa: E731, E741 """ Script to generate task YAMLs for the FLORES-200 dataset. Based on `tasks/translation/utils.py`. """ import argparse +import itertools + import yaml -from langcodes import * -from itertools import * +from langcodes import Language + # utils flatten = lambda l: list(itertools.chain(*l)) # constants _LANGUAGES = [ -"ace_Arab", "bam_Latn", "dzo_Tibt", "hin_Deva", "khm_Khmr", "mag_Deva", "pap_Latn", "sot_Latn", "tur_Latn", -"ace_Latn", "ban_Latn", "ell_Grek", "hne_Deva", "kik_Latn", "mai_Deva", "pbt_Arab", "spa_Latn", "twi_Latn", -"acm_Arab", "bel_Cyrl", "eng_Latn", "hrv_Latn", "kin_Latn", "mal_Mlym", "pes_Arab", "srd_Latn", "tzm_Tfng", -"acq_Arab", "bem_Latn", "epo_Latn", "hun_Latn", "kir_Cyrl", "mar_Deva", "plt_Latn", "srp_Cyrl", "uig_Arab", -"aeb_Arab", "ben_Beng", "est_Latn", "hye_Armn", "kmb_Latn", "min_Arab", "pol_Latn", "ssw_Latn", "ukr_Cyrl", -"afr_Latn", "bho_Deva", "eus_Latn", "ibo_Latn", "kmr_Latn", "min_Latn", "por_Latn", "sun_Latn", "umb_Latn", -"ajp_Arab", "bjn_Arab", "ewe_Latn", "ilo_Latn", "knc_Arab", "mkd_Cyrl", "prs_Arab", "swe_Latn", "urd_Arab", -"aka_Latn", "bjn_Latn", "fao_Latn", "ind_Latn", "knc_Latn", "mlt_Latn", "quy_Latn", "swh_Latn", "uzn_Latn", -"als_Latn", "bod_Tibt", "fij_Latn", "isl_Latn", "kon_Latn", "mni_Beng", "ron_Latn", "szl_Latn", "vec_Latn", -"amh_Ethi", "bos_Latn", "fin_Latn", "ita_Latn", "kor_Hang", "mos_Latn", "run_Latn", "tam_Taml", "vie_Latn", -"apc_Arab", "bug_Latn", "fon_Latn", "jav_Latn", "lao_Laoo", "mri_Latn", "rus_Cyrl", "taq_Latn", "war_Latn", -"arb_Arab", "bul_Cyrl", "fra_Latn", "jpn_Jpan", "lij_Latn", "mya_Mymr", "sag_Latn", "taq_Tfng", "wol_Latn", -"arb_Latn", "cat_Latn", "fur_Latn", "kab_Latn", "lim_Latn", "nld_Latn", "san_Deva", "tat_Cyrl", "xho_Latn", -"ars_Arab", "ceb_Latn", "fuv_Latn", "kac_Latn", "lin_Latn", "nno_Latn", "sat_Olck", "tel_Telu", "ydd_Hebr", -"ary_Arab", "ces_Latn", "gaz_Latn", "kam_Latn", "lit_Latn", "nob_Latn", "scn_Latn", "tgk_Cyrl", "yor_Latn", -"arz_Arab", "cjk_Latn", "gla_Latn", "kan_Knda", "lmo_Latn", "npi_Deva", "shn_Mymr", "tgl_Latn", "yue_Hant", -"asm_Beng", "ckb_Arab", "gle_Latn", "kas_Arab", "ltg_Latn", "nso_Latn", "sin_Sinh", "tha_Thai", "zho_Hans", -"ast_Latn", "crh_Latn", "glg_Latn", "kas_Deva", "ltz_Latn", "nus_Latn", "slk_Latn", "tir_Ethi", "zho_Hant", -"awa_Deva", "cym_Latn", "grn_Latn", "kat_Geor", "lua_Latn", "nya_Latn", "slv_Latn", "tpi_Latn", "zsm_Latn", -"ayr_Latn", "dan_Latn", "guj_Gujr", "kaz_Cyrl", "lug_Latn", "oci_Latn", "smo_Latn", "tsn_Latn", "zul_Latn", -"azb_Arab", "deu_Latn", "hat_Latn", "kbp_Latn", "luo_Latn", "ory_Orya", "sna_Latn", "tso_Latn", -"azj_Latn", "dik_Latn", "hau_Latn", "kea_Latn", "lus_Latn", "pag_Latn", "snd_Arab", "tuk_Latn", -"bak_Cyrl", "dyu_Latn", "heb_Hebr", "khk_Cyrl", "lvs_Latn", "pan_Guru", "som_Latn", "tum_Latn" + "ace_Arab", + "bam_Latn", + "dzo_Tibt", + "hin_Deva", + "khm_Khmr", + "mag_Deva", + "pap_Latn", + "sot_Latn", + "tur_Latn", + "ace_Latn", + "ban_Latn", + "ell_Grek", + "hne_Deva", + "kik_Latn", + "mai_Deva", + "pbt_Arab", + "spa_Latn", + "twi_Latn", + "acm_Arab", + "bel_Cyrl", + "eng_Latn", + "hrv_Latn", + "kin_Latn", + "mal_Mlym", + "pes_Arab", + "srd_Latn", + "tzm_Tfng", + "acq_Arab", + "bem_Latn", + "epo_Latn", + "hun_Latn", + "kir_Cyrl", + "mar_Deva", + "plt_Latn", + "srp_Cyrl", + "uig_Arab", + "aeb_Arab", + "ben_Beng", + "est_Latn", + "hye_Armn", + "kmb_Latn", + "min_Arab", + "pol_Latn", + "ssw_Latn", + "ukr_Cyrl", + "afr_Latn", + "bho_Deva", + "eus_Latn", + "ibo_Latn", + "kmr_Latn", + "min_Latn", + "por_Latn", + "sun_Latn", + "umb_Latn", + "ajp_Arab", + "bjn_Arab", + "ewe_Latn", + "ilo_Latn", + "knc_Arab", + "mkd_Cyrl", + "prs_Arab", + "swe_Latn", + "urd_Arab", + "aka_Latn", + "bjn_Latn", + "fao_Latn", + "ind_Latn", + "knc_Latn", + "mlt_Latn", + "quy_Latn", + "swh_Latn", + "uzn_Latn", + "als_Latn", + "bod_Tibt", + "fij_Latn", + "isl_Latn", + "kon_Latn", + "mni_Beng", + "ron_Latn", + "szl_Latn", + "vec_Latn", + "amh_Ethi", + "bos_Latn", + "fin_Latn", + "ita_Latn", + "kor_Hang", + "mos_Latn", + "run_Latn", + "tam_Taml", + "vie_Latn", + "apc_Arab", + "bug_Latn", + "fon_Latn", + "jav_Latn", + "lao_Laoo", + "mri_Latn", + "rus_Cyrl", + "taq_Latn", + "war_Latn", + "arb_Arab", + "bul_Cyrl", + "fra_Latn", + "jpn_Jpan", + "lij_Latn", + "mya_Mymr", + "sag_Latn", + "taq_Tfng", + "wol_Latn", + "arb_Latn", + "cat_Latn", + "fur_Latn", + "kab_Latn", + "lim_Latn", + "nld_Latn", + "san_Deva", + "tat_Cyrl", + "xho_Latn", + "ars_Arab", + "ceb_Latn", + "fuv_Latn", + "kac_Latn", + "lin_Latn", + "nno_Latn", + "sat_Olck", + "tel_Telu", + "ydd_Hebr", + "ary_Arab", + "ces_Latn", + "gaz_Latn", + "kam_Latn", + "lit_Latn", + "nob_Latn", + "scn_Latn", + "tgk_Cyrl", + "yor_Latn", + "arz_Arab", + "cjk_Latn", + "gla_Latn", + "kan_Knda", + "lmo_Latn", + "npi_Deva", + "shn_Mymr", + "tgl_Latn", + "yue_Hant", + "asm_Beng", + "ckb_Arab", + "gle_Latn", + "kas_Arab", + "ltg_Latn", + "nso_Latn", + "sin_Sinh", + "tha_Thai", + "zho_Hans", + "ast_Latn", + "crh_Latn", + "glg_Latn", + "kas_Deva", + "ltz_Latn", + "nus_Latn", + "slk_Latn", + "tir_Ethi", + "zho_Hant", + "awa_Deva", + "cym_Latn", + "grn_Latn", + "kat_Geor", + "lua_Latn", + "nya_Latn", + "slv_Latn", + "tpi_Latn", + "zsm_Latn", + "ayr_Latn", + "dan_Latn", + "guj_Gujr", + "kaz_Cyrl", + "lug_Latn", + "oci_Latn", + "smo_Latn", + "tsn_Latn", + "zul_Latn", + "azb_Arab", + "deu_Latn", + "hat_Latn", + "kbp_Latn", + "luo_Latn", + "ory_Orya", + "sna_Latn", + "tso_Latn", + "azj_Latn", + "dik_Latn", + "hau_Latn", + "kea_Latn", + "lus_Latn", + "pag_Latn", + "snd_Arab", + "tuk_Latn", + "bak_Cyrl", + "dyu_Latn", + "heb_Hebr", + "khk_Cyrl", + "lvs_Latn", + "pan_Guru", + "som_Latn", + "tum_Latn", +] +LANGUAGE_PAIRS = [ + (a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1 :] ] -LANGUAGE_PAIRS = [(a, b) for idx, a in enumerate(_LANGUAGES) for b in _LANGUAGES[idx + 1:]] -LANGUAGES_OF_INTEREST = ["cat_Latn", "spa_Latn", "eng_Latn", "glg_Latn", "eus_Latn", "ita_Latn", "deu_Latn", "por_Latn", "fra_Latn"] +LANGUAGES_OF_INTEREST = [ + "cat_Latn", + "spa_Latn", + "eng_Latn", + "glg_Latn", + "eus_Latn", + "ita_Latn", + "deu_Latn", + "por_Latn", + "fra_Latn", +] MAIN_LANG = "eus_Latn" -LANGUAGE_PAIRS = [(a, b) for (a, b) in LANGUAGE_PAIRS if a in LANGUAGES_OF_INTEREST and b in LANGUAGES_OF_INTEREST and MAIN_LANG in (a, b)] +LANGUAGE_PAIRS = [ + (a, b) + for (a, b) in LANGUAGE_PAIRS + if a in LANGUAGES_OF_INTEREST and b in LANGUAGES_OF_INTEREST and MAIN_LANG in (a, b) +] # auxiliary functions -code_to_language_name = lambda code: Language.make(language=Language.get(code)["language"]).display_name() +code_to_language_name = lambda code: Language.make( + language=Language.get(code)["language"] +).display_name() code_to_short_name = lambda code: Language.get(code)["language"] -jinja_var = lambda s: "{{" + s + "}}" # wrapper to avoid having to escape { } in format strings +jinja_var = ( + lambda s: "{{" + s + "}}" +) # wrapper to avoid having to escape { } in format strings + def doc_to_text(src: str, tgt: str) -> str: src_name, tgt_name = map(code_to_language_name, [src, tgt]) @@ -56,12 +261,14 @@ def doc_to_text(src: str, tgt: str) -> str: {src_name} sentence: {jinja_var('sentence_' + src)} {tgt_name} sentence:""" -def doc_to_target(tgt: str) -> str: +def doc_to_target(tgt: str) -> str: return f"{jinja_var('sentence_' + tgt)}" + # main function + def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: """ Generate a YAML file for each translation direction. @@ -69,20 +276,23 @@ def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: err = [] for src, tgt in LANGUAGE_PAIRS: - # do both translation directions for each lang pair for src, tgt in [(src, tgt), (tgt, src)]: lang_pair_name = f"{code_to_short_name(src)}-{code_to_short_name(tgt)}" yaml_file_name = f"flores_{lang_pair_name}.yaml" try: - with open( f"{output_dir}/{yaml_file_name}", "w" if overwrite else "x", encoding="utf-8") as outfile: + with open( + f"{output_dir}/{yaml_file_name}", + "w" if overwrite else "x", + encoding="utf-8", + ) as outfile: print(f"Creating {yaml_file_name}...") outfile.write("# File generated by `create-yamls.py`\n") yaml.dump( { -# "group": [f"{BENCH_NAME}_bench", f"{BENCH_NAME}_bench_flores"], -# "group": "flores_eu", + # "group": [f"{BENCH_NAME}_bench", f"{BENCH_NAME}_bench_flores"], + # "group": "flores_eu", "include": "_flores_common_yaml", "task": f"flores_{lang_pair_name}", "doc_to_text": doc_to_text(src, tgt), @@ -105,11 +315,19 @@ def gen_lang_yamls(output_dir: str, overwrite: bool) -> None: def main() -> None: parser = argparse.ArgumentParser() - parser.add_argument("--overwrite", default=False, action="store_true", help="Overwrite files if they already exist") - parser.add_argument( "--output-dir", default=".", help="Directory to write yaml files to" ) + parser.add_argument( + "--overwrite", + default=False, + action="store_true", + help="Overwrite files if they already exist", + ) + parser.add_argument( + "--output-dir", default=".", help="Directory to write yaml files to" + ) args = parser.parse_args() gen_lang_yamls(output_dir=args.output_dir, overwrite=args.overwrite) + if __name__ == "__main__": main() -- GitLab From 8f619361a18d604f936eb63ca8999fbfd6ba53f0 Mon Sep 17 00:00:00 2001 From: kyujinHan <98331298+KyujinHan@users.noreply.github.com> Date: Mon, 7 Oct 2024 23:24:00 +0900 Subject: [PATCH 120/194] Solution for CSAT-QA tasks evaluation (#2385) --- lm_eval/tasks/csatqa/_default_csatqa_yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/tasks/csatqa/_default_csatqa_yaml b/lm_eval/tasks/csatqa/_default_csatqa_yaml index f9039cc1..fdd6d148 100644 --- a/lm_eval/tasks/csatqa/_default_csatqa_yaml +++ b/lm_eval/tasks/csatqa/_default_csatqa_yaml @@ -1,4 +1,4 @@ -dataset_path: EleutherAI/csatqa +dataset_path: HAERAE-HUB/csatqa test_split: test output_type: multiple_choice process_docs: !function utils.process_docs -- GitLab From fe3040f132e592ec72c55a4ace9351f71aa6a9a6 Mon Sep 17 00:00:00 2001 From: am-bean <88600346+am-bean@users.noreply.github.com> Date: Mon, 7 Oct 2024 15:26:38 +0100 Subject: [PATCH 121/194] LingOly - Fixing scoring bugs for smaller models (#2376) * Fixing scoring bugs for smaller models * Catching another error type in parsing --- lm_eval/tasks/lingoly/README.md | 21 ++++--------- lm_eval/tasks/lingoly/lingoly_context.yaml | 7 +++++ lm_eval/tasks/lingoly/lingoly_nocontext.yaml | 7 +++++ lm_eval/tasks/lingoly/script.py | 31 ++++++++++++-------- 4 files changed, 38 insertions(+), 28 deletions(-) diff --git a/lm_eval/tasks/lingoly/README.md b/lm_eval/tasks/lingoly/README.md index 391abe30..3ce114e8 100644 --- a/lm_eval/tasks/lingoly/README.md +++ b/lm_eval/tasks/lingoly/README.md @@ -1,5 +1,4 @@ -# Task-name -LingOly +# LingOly ### Paper @@ -27,21 +26,11 @@ Homepage: `https://github.com/am-bean/lingOly` } ``` -### Groups, Tags, and Tasks +### Tasks -#### Groups - -* `group_name`: `Short description` - -#### Tags - -* `reasoning`: `` -* `linguistics`: `` - -#### Tasks - -* `exact_match`: `exact match of generations to reference` -* `delta_nc`: `improvement in score relative to no-context baseline` +* `lingoly`: `runs both _context and _nocontext and computes the difference` +* `lingoly_context`: `exact match of generations to reference answers` +* `lingoly_nocontext`: `exact match of generations to reference answers, but with context removed` ### Checklist diff --git a/lm_eval/tasks/lingoly/lingoly_context.yaml b/lm_eval/tasks/lingoly/lingoly_context.yaml index 2ff0a6c1..76dfe41a 100644 --- a/lm_eval/tasks/lingoly/lingoly_context.yaml +++ b/lm_eval/tasks/lingoly/lingoly_context.yaml @@ -9,6 +9,13 @@ validation_split: test test_split: test fewshot_split: null +generation_kwargs: + until: + - "}\n" + max_gen_toks: 512 + do_sample: false + temperature: 0.0 + process_docs: !function utils.load_all_questions doc_to_text: prompt diff --git a/lm_eval/tasks/lingoly/lingoly_nocontext.yaml b/lm_eval/tasks/lingoly/lingoly_nocontext.yaml index eea976aa..fd6f4ded 100644 --- a/lm_eval/tasks/lingoly/lingoly_nocontext.yaml +++ b/lm_eval/tasks/lingoly/lingoly_nocontext.yaml @@ -9,6 +9,13 @@ validation_split: test test_split: test fewshot_split: null +generation_kwargs: + until: + - "}\n" + max_gen_toks: 512 + do_sample: false + temperature: 0.0 + process_docs: !function utils.load_all_questions doc_to_text: nc_prompt diff --git a/lm_eval/tasks/lingoly/script.py b/lm_eval/tasks/lingoly/script.py index 33514ba3..455ed2cd 100644 --- a/lm_eval/tasks/lingoly/script.py +++ b/lm_eval/tasks/lingoly/script.py @@ -45,13 +45,10 @@ def parse_str_list_score(model, correct, scoring_func): return 1.0 if len(model) == 0: return 0.0 - if "[" in correct: - try: - readstr = ast.literal_eval(correct) - if isinstance(readstr, list): - correct = readstr - except SyntaxError: - pass + if ("[" in correct) and (("'" in correct) or ('"' in correct)): + readstr = ast.literal_eval(correct) + if isinstance(readstr, list): + correct = readstr if isinstance(correct, list): if all(isinstance(c, str) for c in correct): max_score = 0.0 @@ -91,21 +88,31 @@ def parse_str_list_score(model, correct, scoring_func): ) -def exact_match(input): - ref_dict = ast.literal_eval(input[0]) +def exact_match(references: list[str], predictions: list[str]): + ref_dict = ast.literal_eval(references[0]) try: - pred_dict = ast.literal_eval(input[1]) - except SyntaxError: + assert "{" in predictions[0] + if predictions[0][-1] == "}": + pred_dict = ast.literal_eval(predictions[0][predictions[0].index("{") :]) + else: + pred_dict = ast.literal_eval( + predictions[0][predictions[0].index("{") :] + "}" + ) + except (SyntaxError, ValueError, AssertionError): pred_dict = {} for k in ref_dict.keys(): - m = re.search(str(k) + "': ([^']+)'[,\\}]", input[1]) + m = re.search(re.escape(str(k)) + """': ([^']+)'[,\\}]""", predictions[0]) + n = re.search(re.escape(str(k)) + """": ([^"]+)"[,\\}]""", predictions[0]) if m: pred_dict[k] = m.group()[:-1] + elif n: + pred_dict[k] = n.group()[:-1] else: pred_dict[k] = "" pred_dict_full = { k: pred_dict[k] if k in pred_dict else "" for k in ref_dict.keys() } + scores = [ parse_str_list_score(pred_dict_full[k], v, safe_exact) for k, v in ref_dict.items() -- GitLab From aa457edc3d64d81530159cd3a182932320c78f8c Mon Sep 17 00:00:00 2001 From: Chenjie Luo <108829653+cjluo-omniml@users.noreply.github.com> Date: Mon, 7 Oct 2024 07:35:39 -0700 Subject: [PATCH 122/194] Fix float limit override (#2325) * Fix float limit override See: https://github.com/EleutherAI/lm-evaluation-harness/issues/2324 The float limit will be override with the previous int limit of multiple tasks are triggered together. This PR fix this issue * Update evaluator.py * Update evaluator.py --- lm_eval/evaluator.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index 4f4c8f7f..efe8ce4f 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -433,10 +433,14 @@ def evaluate( ) # end multimodality validation check + # Cache the limit arg. + limit_arg = limit + limits = [] for task_output in eval_tasks: task: Task = task_output.task - limit = get_sample_size(task, limit) + limit = get_sample_size(task, limit_arg) + limits.append(limit) task.build_all_requests( limit=limit, rank=lm.rank, @@ -506,7 +510,7 @@ def evaluate( WORLD_SIZE = lm.world_size ### Postprocess outputs ### # TODO: del model here, maybe (idea: allow user to specify device of e.g. reward model separately) - for task_output in eval_tasks: + for task_output, limit in zip(eval_tasks, limits): task = task_output.task task.apply_filters() @@ -655,7 +659,7 @@ def evaluate( len(task_output.task.eval_docs), ), } - for task_output in eval_tasks + for task_output, limit in zip(eval_tasks, limits) }, } if log_samples: -- GitLab From 4cec66e4e468d15789473d6d63c3a61a751fa524 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 7 Oct 2024 20:19:47 +0500 Subject: [PATCH 123/194] [API] tokenizer: add trust-remote-code (#2372) * tokenizer: trust-remote-code * pre-commit --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- lm_eval/models/api_models.py | 15 ++++++++++++--- 1 file changed, 12 insertions(+), 3 deletions(-) diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index 70988939..9abc6de9 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -73,9 +73,12 @@ class TemplateAPI(TemplateLM): seed: int = 1234, max_length: Optional[int] = 2048, add_bos_token: bool = False, - custom_prefix_token_id=None, + custom_prefix_token_id: int = None, # send the requests as tokens or strings - tokenized_requests=True, + tokenized_requests: bool = True, + trust_remote_code: bool = False, + revision: Optional[str] = "main", + use_fast_tokenizer: bool = True, **kwargs, ) -> None: super().__init__() @@ -128,7 +131,10 @@ class TemplateAPI(TemplateLM): import transformers self.tokenizer = transformers.AutoTokenizer.from_pretrained( - self.tokenizer if self.tokenizer else self.model + self.tokenizer if self.tokenizer else self.model, + trust_remote_code=trust_remote_code, + revision=revision, + use_fast=use_fast_tokenizer, ) # Not used as the API will handle padding but to mirror the behavior of the HFLM self.tokenizer = configure_pad_token(self.tokenizer) @@ -153,6 +159,9 @@ class TemplateAPI(TemplateLM): assert isinstance(tokenizer, str), "tokenizer must be a string" self.tokenizer = transformers.AutoTokenizer.from_pretrained( tokenizer, + trust_remote_code=trust_remote_code, + revision=revision, + use_fast=use_fast_tokenizer, ) @abc.abstractmethod -- GitLab From ab2c46c3ab6acfaa4fc3edfa675ad8c1b8c48a26 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Wed, 9 Oct 2024 01:47:23 +0500 Subject: [PATCH 124/194] HF: switch conditional checks to `self.backend` from `AUTO_MODEL_CLASS` (#2353) * switch conditional checks to `self.backend` * nit * nit * commit feedback * fix test; update precommit hooks * add escape hatch for custom self.AUTO_MODEL_CLASS * add escape hatch for custom self.AUTO_MODEL_CLASS * fix * move assertion * add logging messages * update AUTO_MODEL_CLASS behavior in _get_backend --------- Co-authored-by: haileyschoelkopf --- lm_eval/models/huggingface.py | 80 +++++++++++++++++------------------ 1 file changed, 40 insertions(+), 40 deletions(-) diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 63ad1440..8b6f5641 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -55,7 +55,7 @@ class HFLM(TemplateLM): def __init__( self, pretrained: Union[str, transformers.PreTrainedModel], - backend: Optional[Literal["default", "causal", "seq2seq"]] = "default", + backend: Literal["default", "causal", "seq2seq"] = "default", # override whether the model should be treated as decoder-only (causal) or encoder-decoder (seq2seq) revision: Optional[str] = "main", subfolder: Optional[str] = None, @@ -90,7 +90,6 @@ class HFLM(TemplateLM): **kwargs, ) -> None: super().__init__() - # optionally: take in an already-initialized transformers.PreTrainedModel if not isinstance(pretrained, str): eval_logger.warning( @@ -164,7 +163,7 @@ class HFLM(TemplateLM): trust_remote_code=trust_remote_code, ) - # determine which of 'causal' and 'seq2seq' backends to use + # determine which of 'causal' and 'seq2seq' backends to use for HF models self._get_backend( config=self.config, backend=backend, trust_remote_code=trust_remote_code ) @@ -287,7 +286,7 @@ class HFLM(TemplateLM): def _get_accelerate_args( self, - parallelize: bool = None, + parallelize: Optional[bool] = None, device_map: Optional[str] = "auto", max_memory_per_gpu: Optional[Union[int, str]] = None, max_cpu_memory: Optional[Union[int, str]] = None, @@ -441,31 +440,26 @@ class HFLM(TemplateLM): def _get_backend( self, config: Union[transformers.PretrainedConfig, transformers.AutoConfig], - backend: Optional[Literal["default", "causal", "seq2seq"]] = "default", + backend: Literal["default", "causal", "seq2seq"] = "default", trust_remote_code: Optional[bool] = False, ) -> None: """ Helper method during initialization. - Determines the backend ("causal" (decoder-only) or "seq2seq" (encoder-decoder)) - model type to be used. + Determines the backend ("causal" (decoder-only) or "seq2seq" (encoder-decoder)) model type to be used. sets `self.AUTO_MODEL_CLASS` appropriately if not already set. + + **If not calling HFLM.__init__() or HFLM._get_backend() within a subclass of HFLM, + user must set `self.backend` to be either "causal" or "seq2seq" manually!** """ - # escape hatch: if we're using a subclass that shouldn't follow - # the default _get_backend logic, - # then skip over the method. - # TODO: this seems very much undesirable in some cases--our code in HFLM - # references AutoModelForCausalLM at times to check for equality - if self.AUTO_MODEL_CLASS is not None: - return assert backend in ["default", "causal", "seq2seq"] if backend != "default": # if we've settled on non-default backend, use that manually if backend == "causal": - self.AUTO_MODEL_CLASS = transformers.AutoModelForCausalLM + self.backend = backend elif backend == "seq2seq": - self.AUTO_MODEL_CLASS = transformers.AutoModelForSeq2SeqLM + self.backend = backend eval_logger.info( f"Overrode HF model backend type, and using type '{backend}'" ) @@ -478,26 +472,32 @@ class HFLM(TemplateLM): # first check if model type is listed under seq2seq models, since some # models like MBart are listed in both seq2seq and causal mistakenly in HF transformers. # these special cases should be treated as seq2seq models. - self.AUTO_MODEL_CLASS = transformers.AutoModelForSeq2SeqLM + self.backend = "seq2seq" + eval_logger.info(f"Using model type '{backend}'") elif ( getattr(self.config, "model_type") in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES ): - self.AUTO_MODEL_CLASS = transformers.AutoModelForCausalLM + self.backend = "causal" + eval_logger.info(f"Using model type '{backend}'") else: if not trust_remote_code: eval_logger.warning( "HF model type is neither marked as CausalLM or Seq2SeqLM. \ This is expected if your model requires `trust_remote_code=True` but may be an error otherwise." + "Setting backend to causal" ) # if model type is neither in HF transformers causal or seq2seq model registries - # then we default to AutoModelForCausalLM - self.AUTO_MODEL_CLASS = transformers.AutoModelForCausalLM + # then we default to assuming AutoModelForCausalLM + self.backend = "causal" + eval_logger.info( + f"Model type cannot be determined. Using default model type '{backend}'" + ) - assert self.AUTO_MODEL_CLASS in [ - transformers.AutoModelForCausalLM, - transformers.AutoModelForSeq2SeqLM, - ] - return None + if self.AUTO_MODEL_CLASS is None: + if self.backend == "causal": + self.AUTO_MODEL_CLASS = transformers.AutoModelForCausalLM + elif self.backend == "seq2seq": + self.AUTO_MODEL_CLASS = transformers.AutoModelForSeq2SeqLM def _get_config( self, @@ -505,6 +505,7 @@ class HFLM(TemplateLM): revision: str = "main", trust_remote_code: bool = False, ) -> None: + """Return the model config for HuggingFace models""" self._config = transformers.AutoConfig.from_pretrained( pretrained, revision=revision, @@ -703,7 +704,7 @@ class HFLM(TemplateLM): # if OOM, then halves batch_size and tries again @find_executable_batch_size(starting_batch_size=self.max_batch_size) def forward_batch(batch_size): - if self.AUTO_MODEL_CLASS == transformers.AutoModelForSeq2SeqLM: + if self.backend == "seq2seq": length = max(max_context_enc, max_cont_enc) batched_conts = torch.ones( (batch_size, length), device=self.device @@ -754,7 +755,7 @@ class HFLM(TemplateLM): # by default for CausalLM - false or self.add_bos_token is set if add_special_tokens is None: - if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM: + if self.backend == "causal": special_tokens_kwargs = { "add_special_tokens": False or self.add_bos_token } @@ -782,7 +783,7 @@ class HFLM(TemplateLM): self.tokenizer.padding_side = padding_side add_special_tokens = {} - if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM: + if self.backend == "causal": add_special_tokens = {"add_special_tokens": False or self.add_bos_token} encoding = self.tokenizer( @@ -860,14 +861,14 @@ class HFLM(TemplateLM): def _select_cont_toks( self, logits: torch.Tensor, contlen: int = None, inplen: int = None ) -> torch.Tensor: - if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM: + if self.backend == "causal": assert ( contlen and inplen ), "Must pass input len and cont. len to select scored logits for causal LM" # discard right-padding. # also discard the input/context tokens. we'll only score continuations. logits = logits[inplen - contlen : inplen] - elif self.AUTO_MODEL_CLASS == transformers.AutoModelForSeq2SeqLM: + elif self.backend == "seq2seq": assert ( contlen and not inplen ), "Selecting scored logits for Seq2SeqLM requires only cont. len" @@ -990,8 +991,7 @@ class HFLM(TemplateLM): requests, sort_fn=_collate, group_by="contexts" - if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM - and self.logits_cache + if self.backend == "causal" and self.logits_cache else None, group_fn=_lookup_one_token_cont, ) @@ -1048,14 +1048,14 @@ class HFLM(TemplateLM): # cont_toks 4 5 6 7 8 9 [:, -len(continuation_enc):, :self.vocab_size] slice # when too long to fit in context, truncate from the left - if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM: + if self.backend == "causal": inp = torch.tensor( (context_enc + continuation_enc)[-(self.max_length + 1) :][:-1], dtype=torch.long, device=self.device, ) (inplen,) = inp.shape - elif self.AUTO_MODEL_CLASS == transformers.AutoModelForSeq2SeqLM: + elif self.backend == "seq2seq": inp = torch.tensor( (context_enc)[-self.max_length :], dtype=torch.long, @@ -1095,11 +1095,11 @@ class HFLM(TemplateLM): # create encoder attn mask and batched conts, if seq2seq call_kwargs = {} - if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM: + if self.backend == "causal": batched_inps = pad_and_concat( padding_len_inp, inps, padding_side="right" ) # [batch, padding_len_inp] - elif self.AUTO_MODEL_CLASS == transformers.AutoModelForSeq2SeqLM: + elif self.backend == "seq2seq": # TODO: left-pad encoder inps and mask? batched_inps = pad_and_concat( padding_len_inp, inps @@ -1130,7 +1130,7 @@ class HFLM(TemplateLM): # from prompt/prefix tuning tokens, if applicable ctx_len = ( inplen + (logits.shape[0] - padding_len_inp) - if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM + if self.backend == "causal" else None ) logits = self._select_cont_toks(logits, contlen=contlen, inplen=ctx_len) @@ -1265,10 +1265,10 @@ class HFLM(TemplateLM): max_gen_toks = self.max_gen_toks # set the max length in tokens of inputs ("context_enc") - if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM: + if self.backend == "causal": # max len for inputs = max length, minus room to generate the max new tokens max_ctx_len = self.max_length - max_gen_toks - elif self.AUTO_MODEL_CLASS == transformers.AutoModelForSeq2SeqLM: + elif self.backend == "seq2seq": # max len for inputs = encoder's whole max_length max_ctx_len = self.max_length @@ -1295,7 +1295,7 @@ class HFLM(TemplateLM): cont_toks_list = cont.tolist() for cont_toks, context in zip(cont_toks_list, contexts): # discard context + left-padding toks if using causal decoder-only LM - if self.AUTO_MODEL_CLASS == transformers.AutoModelForCausalLM: + if self.backend == "causal": cont_toks = cont_toks[context_enc.shape[1] :] s = self.tok_decode(cont_toks) -- GitLab From 1ed1f9ed9cde8f8b9c8b68564ebe64fd63256141 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Wed, 9 Oct 2024 01:48:08 +0500 Subject: [PATCH 125/194] max_images are passed on to vllms `limit_mm_per_prompt` (#2387) * max_images are passed on to vllms `limit_mm_per_prompt` * replace max image placeholders in string * handle chat_template error * move `fewshot_random_seed` to global --- lm_eval/api/model.py | 7 ++++++- lm_eval/evaluator.py | 6 +++--- lm_eval/models/vllm_vlms.py | 20 ++++++++++++++++---- 3 files changed, 25 insertions(+), 8 deletions(-) diff --git a/lm_eval/api/model.py b/lm_eval/api/model.py index 765fc012..b5c29993 100644 --- a/lm_eval/api/model.py +++ b/lm_eval/api/model.py @@ -431,7 +431,12 @@ class TemplateLM(LM): using_default_template = False # First, handle the cases when the model has a dict of multiple templates - template = self.tokenizer.chat_template or self.tokenizer.default_chat_template + try: + template = ( + self.tokenizer.chat_template or self.tokenizer.default_chat_template + ) + except AttributeError: + return None if isinstance(template, dict): using_default_dict = self.tokenizer.chat_template is None diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index efe8ce4f..d0c1a19a 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -157,6 +157,9 @@ def simple_evaluate( seed_message.append(f"Setting torch manual seed to {torch_random_seed}") torch.manual_seed(torch_random_seed) + if fewshot_random_seed is not None: + seed_message.append(f"Setting fewshot manual seed to {fewshot_random_seed}") + if seed_message: eval_logger.info(" | ".join(seed_message)) @@ -276,9 +279,6 @@ def simple_evaluate( task_obj.set_config(key="num_fewshot", value=0) # fewshot_random_seed set for tasks, even with a default num_fewshot (e.g. in the YAML file) task_obj.set_fewshot_seed(seed=fewshot_random_seed) - eval_logger.info( - f"Setting fewshot random generator seed to {fewshot_random_seed}" - ) adjusted_task_dict[task_name] = task_obj diff --git a/lm_eval/models/vllm_vlms.py b/lm_eval/models/vllm_vlms.py index 5a126090..13a2a3ff 100644 --- a/lm_eval/models/vllm_vlms.py +++ b/lm_eval/models/vllm_vlms.py @@ -7,9 +7,9 @@ from tqdm import tqdm from lm_eval.api.instance import Instance from lm_eval.api.registry import register_model -from lm_eval.models.utils import Collator, undistribute +from lm_eval.models.utils import Collator, replace_placeholders, undistribute from lm_eval.models.vllm_causallms import VLLM -from lm_eval.utils import simple_parse_args_string +from lm_eval.utils import eval_logger try: @@ -36,10 +36,11 @@ class VLLM_VLM(VLLM): interleave: bool = True, # TODO: handle max_images and limit_mm_per_prompt better max_images: int = 999, - limit_mm_per_prompt: str = "image=1", **kwargs, ): - kwargs["limit_mm_per_prompt"] = simple_parse_args_string(limit_mm_per_prompt) + if max_images != 999: + kwargs["limit_mm_per_prompt"] = {"image": max_images} + eval_logger.info(f"Setting limit_mm_per_prompt[image] to {max_images}") super().__init__( pretrained=pretrained, trust_remote_code=trust_remote_code, @@ -63,6 +64,17 @@ class VLLM_VLM(VLLM): truncation: bool = False, ): images = [img[: self.max_images] for img in images] + # TODO: is the default placeholder always ? + if self.chat_applied is False: + strings = [ + replace_placeholders( + string, + DEFAULT_IMAGE_PLACEHOLDER, + DEFAULT_IMAGE_PLACEHOLDER, + self.max_images, + ) + for string in strings + ] outputs = [] for x, i in zip(strings, images): -- GitLab From 2576a8cb74409e0d31c2d6f84fc96099e6679ed5 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Tue, 8 Oct 2024 16:48:16 -0400 Subject: [PATCH 126/194] Fix Llava-1.5-hf ; Update to version 0.4.5 (#2388) --- lm_eval/api/task.py | 13 ----------- lm_eval/models/hf_vlms.py | 5 ++++ lm_eval/models/utils.py | 11 +++++++++ lm_eval/tasks/__init__.py | 49 ++++++++++++++------------------------- 4 files changed, 34 insertions(+), 44 deletions(-) diff --git a/lm_eval/api/task.py b/lm_eval/api/task.py index ea3cae06..532e9e7a 100644 --- a/lm_eval/api/task.py +++ b/lm_eval/api/task.py @@ -57,7 +57,6 @@ class TaskConfig(dict): task: Optional[str] = None task_alias: Optional[str] = None tag: Optional[Union[str, list]] = None - group: Optional[Union[str, list]] = None # HF dataset options. # which dataset to use, # and what splits for what purpose @@ -98,18 +97,6 @@ class TaskConfig(dict): ) def __post_init__(self) -> None: - if self.group is not None: - eval_logger.warning( - "A task YAML file was found to contain a `group` key. Groups which provide aggregate scores over several subtasks now require a separate config file--if not aggregating, you may want to use the `tag` config option instead within your config. Setting `group` within a TaskConfig will be deprecated in v0.4.4. Please see https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/task_guide.md for more information." - ) - - if self.tag is None: - self.tag = self.group - else: - raise ValueError( - "Got both a `group` and `tag` entry within a TaskConfig. Please use one or the other--`group` values will be deprecated in v0.4.4." - ) - if self.generation_kwargs is not None: if self.output_type != "generate_until": eval_logger.warning( diff --git a/lm_eval/models/hf_vlms.py b/lm_eval/models/hf_vlms.py index c94c76b2..f2fcdd70 100644 --- a/lm_eval/models/hf_vlms.py +++ b/lm_eval/models/hf_vlms.py @@ -13,6 +13,7 @@ from lm_eval.api.registry import register_model from lm_eval.models.huggingface import HFLM from lm_eval.models.utils import ( Collator, + flatten_image_list, pad_and_concat, replace_placeholders, stop_sequences_criteria, @@ -293,6 +294,10 @@ class HFMultimodalLM(HFLM): if self.rgb: images = [[img.convert("RGB") for img in sublist] for sublist in images] + # certain models like llava expect a single-level image list even for bs>1, multi-image. TODO: port this over to loglikelihoods + if getattr(self.config, "model_type", "") == "llava": + images = flatten_image_list(images) + encoding = self.processor( images=images, text=strings, diff --git a/lm_eval/models/utils.py b/lm_eval/models/utils.py index 72fac038..28ecc658 100644 --- a/lm_eval/models/utils.py +++ b/lm_eval/models/utils.py @@ -698,3 +698,14 @@ def replace_placeholders( # Add the last part of the string result.append(parts[-1]) return "".join(result) + + +def flatten_image_list(images: List[List]): + """ + Takes in a list of lists of images, and returns a single list of all images in order. + Used for some multimodal models like Llava-1.5 which expects this flattened-list format for its image processor. + + :param images: A list of lists of PIL images. + :return: a list of PIL images, via concatenating all the sub-lists in order. + """ + return [image for image_list in images for image in image_list] diff --git a/lm_eval/tasks/__init__.py b/lm_eval/tasks/__init__.py index b3968258..edcd104d 100644 --- a/lm_eval/tasks/__init__.py +++ b/lm_eval/tasks/__init__.py @@ -443,39 +443,26 @@ class TaskManager: def _populate_tags_and_groups(config, task, tasks_and_groups, print_info): # TODO: remove group in next release - for attr in ["tag", "group"]: - if attr in config: - if attr == "group" and print_info: + if "tag" in config: + attr_list = config["tag"] + if isinstance(attr_list, str): + attr_list = [attr_list] + + for tag in attr_list: + if tag not in tasks_and_groups: + tasks_and_groups[tag] = { + "type": "tag", + "task": [task], + "yaml_path": -1, + } + elif tasks_and_groups[tag]["type"] != "tag": self.logger.info( - "`group` and `group_alias` keys in TaskConfigs are deprecated and will be removed in v0.4.5 of lm_eval. " - "The new `tag` field will be used to allow for a shortcut to a group of tasks one does not wish to aggregate metrics across. " - "`group`s which aggregate across subtasks must be only defined in a separate group config file, " - "which will be the official way to create groups that support cross-task aggregation as in `mmlu`. " - "Please see the v0.4.4 patch notes and our documentation: https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/new_task_guide.md#advanced-group-configs " - "for more information." + f"The tag '{tag}' is already registered as a group, this tag will not be registered. " + "This may affect tasks you want to call." ) - print_info = False - # attr = "tag" - - attr_list = config[attr] - if isinstance(attr_list, str): - attr_list = [attr_list] - - for tag in attr_list: - if tag not in tasks_and_groups: - tasks_and_groups[tag] = { - "type": "tag", - "task": [task], - "yaml_path": -1, - } - elif tasks_and_groups[tag]["type"] != "tag": - self.logger.info( - f"The tag {tag} is already registered as a group, this tag will not be registered. " - "This may affect tasks you want to call." - ) - break - else: - tasks_and_groups[tag]["task"].append(task) + break + else: + tasks_and_groups[tag]["task"].append(task) # TODO: remove group in next release print_info = True -- GitLab From 0845b588303f1f59af98dd1c5bdbd78a9e75a1e2 Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Tue, 8 Oct 2024 17:00:22 -0400 Subject: [PATCH 127/194] Bump version to v0.4.5 (#2389) --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 1bc0944e..367bd580 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "lm_eval" -version = "0.4.4" +version = "0.4.5" authors = [ {name="EleutherAI", email="contact@eleuther.ai"} ] -- GitLab From 7785577ceac539f7e25cf98bbe11264466326803 Mon Sep 17 00:00:00 2001 From: Elron Bandel Date: Mon, 14 Oct 2024 22:30:47 +0300 Subject: [PATCH 128/194] Add Unitxt Multimodality Support (#2364) * Add Unitxt Multimodality Support Signed-off-by: elronbandel * Update Signed-off-by: elronbandel * Fix formatting Signed-off-by: elronbandel --------- Signed-off-by: elronbandel --- .gitignore | 1 + lm_eval/tasks/unitxt/README.md | 52 ++++----------------- lm_eval/tasks/unitxt/doc_vqa.yaml | 3 ++ lm_eval/tasks/unitxt/task.py | 63 ++++++++++++++++++++++++-- lm_eval/tasks/unitxt/unitxt_multimodal | 1 + 5 files changed, 71 insertions(+), 49 deletions(-) create mode 100644 lm_eval/tasks/unitxt/doc_vqa.yaml create mode 100644 lm_eval/tasks/unitxt/unitxt_multimodal diff --git a/.gitignore b/.gitignore index c9278761..56bb8038 100644 --- a/.gitignore +++ b/.gitignore @@ -8,6 +8,7 @@ build dist *.egg-info venv +.venv/ .vscode/ temp __pycache__ diff --git a/lm_eval/tasks/unitxt/README.md b/lm_eval/tasks/unitxt/README.md index 1cfc8508..06bee133 100644 --- a/lm_eval/tasks/unitxt/README.md +++ b/lm_eval/tasks/unitxt/README.md @@ -1,15 +1,17 @@ # Unitxt +Unitxt is a library for customizable textual data preparation and evaluation tailored to generative language models. Unitxt natively integrates with common libraries like HuggingFace and LM-eval-harness and deconstructs processing flows into modular components, enabling easy customization and sharing between practitioners. These components encompass model-specific formats, task prompts, and many other comprehensive dataset processing definitions. These components are centralized in the Unitxt-Catalog, thus fostering collaboration and exploration in modern textual data workflows. + +The full Unitxt catalog can be viewed in an [online explorer](https://unitxt.readthedocs.io/en/latest/docs/demo.html). + +Read more about Unitxt at [www.unitxt.ai](https://www.unitxt.ai/). + ### Paper Title: `Unitxt: Flexible, Shareable and Reusable Data Preparation and Evaluation for Generative AI` -Abstract: `https://arxiv.org/abs/2401.14019` - -Unitxt is a library for customizable textual data preparation and evaluation tailored to generative language models. Unitxt natively integrates with common libraries like HuggingFace and LM-eval-harness and deconstructs processing flows into modular components, enabling easy customization and sharing between practitioners. These components encompass model-specific formats, task prompts, and many other comprehensive dataset processing definitions. These components are centralized in the Unitxt-Catalog, thus fostering collaboration and exploration in modern textual data workflows. +Abstract: [link](https://arxiv.org/abs/2401.14019) -The full Unitxt catalog can be viewed in an online explorer. `https://unitxt.readthedocs.io/en/latest/docs/demo.html` -Homepage: https://unitxt.readthedocs.io/en/latest/index.html ### Citation @@ -36,42 +38,4 @@ The full list of Unitxt tasks currently supported can be seen under `tasks/unitx ### Adding tasks -You can add additional tasks from the Unitxt catalog by generating new LM-Eval yaml files for these datasets. - -The Unitxt task yaml files are generated via the `generate_yamls.py` script in the `tasks/unitxt` directory. - -To add a yaml file for an existing dataset Unitxt which is not yet in LM-Eval: -1. Add the card name to the `unitxt_datasets` file in the `tasks/unitxt` directory. -2. The generate_yaml.py contains the default Unitxt [template](https://unitxt.readthedocs.io/en/latest/docs/adding_template.html) used for each kind of NLP task in the `default_template_per_task` dictionary. If the dataset is of a Unitxt task type, previously not used in LM-Eval, you will need to add a default template for it in the dictionary. - -``` -default_template_per_task = { - "tasks.classification.multi_label" : "templates.classification.multi_label.title" , - "tasks.classification.multi_class" : "templates.classification.multi_class.title" , - "tasks.summarization.abstractive" : "templates.summarization.abstractive.full", - "tasks.regression.two_texts" : "templates.regression.two_texts.simple", - "tasks.qa.with_context.extractive" : "templates.qa.with_context.simple", - "tasks.grammatical_error_correction" : "templates.grammatical_error_correction.simple", - "tasks.span_labeling.extraction" : "templates.span_labeling.extraction.title" -} -``` -3. Run `python generate_yaml.py` (this will generate all the datasets listed in the `unitxt_datasets`) - -If you want to add a new dataset to the Unitxt catalog, see the Unitxt documentation: - -https://unitxt.readthedocs.io/en/latest/docs/adding_dataset.html - - - -### Checklist - -For adding novel benchmarks/datasets to the library: -* [ ] Is the task an existing benchmark in the literature? - * [ ] Have you referenced the original paper that introduced the task? - * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? - - -If other tasks on this dataset are already supported: -* [ ] Is the "Main" variant of this task clearly denoted? -* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? -* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? +See the [adding tasks guide](https://www.unitxt.ai/en/latest/docs/lm_eval.html#). diff --git a/lm_eval/tasks/unitxt/doc_vqa.yaml b/lm_eval/tasks/unitxt/doc_vqa.yaml new file mode 100644 index 00000000..cbf274d4 --- /dev/null +++ b/lm_eval/tasks/unitxt/doc_vqa.yaml @@ -0,0 +1,3 @@ +task: doc_vqa +include: unitxt_multimodal +recipe: card=cards.doc_vqa.en,template=templates.qa.with_context.title diff --git a/lm_eval/tasks/unitxt/task.py b/lm_eval/tasks/unitxt/task.py index 339a3076..12b27608 100644 --- a/lm_eval/tasks/unitxt/task.py +++ b/lm_eval/tasks/unitxt/task.py @@ -4,9 +4,12 @@ In the dynamic landscape of generative NLP, traditional text processing pipeline Addressing this need, we present Unitxt, an innovative library for customizable textual data preparation and evaluation tailored to generative language models. Unitxt natively integrates with common libraries like HuggingFace and LM-eval-harness and deconstructs processing flows into modular components, enabling easy customization and sharing between practitioners. These components encompass model-specific formats, task prompts, and many other comprehensive dataset processing definitions. The Unitxt-Catalog centralizes these components, fostering collaboration and exploration in modern textual data workflows. Beyond being a tool, Unitxt is a community-driven platform, empowering users to build, share, and advance their pipelines collaboratively. """ +import importlib.util +import re from functools import partial -from typing import Optional +from typing import Any, Dict, Optional +import datasets import evaluate from lm_eval.api.instance import Instance @@ -25,6 +28,10 @@ _CITATION = """ """ +def is_unitxt_installed() -> bool: + return importlib.util.find_spec("unitxt") is not None + + def score(items, metric): predictions, references = zip(*items) evaluator = evaluate.load("unitxt/metric") @@ -41,17 +48,30 @@ class Unitxt(ConfigurableTask): self, config: Optional[dict] = None, ) -> None: + if config is None: + config = {} assert "recipe" in config, "Unitxt task must have a 'recipe' string." super().__init__( config={ "metadata": {"version": self.VERSION}, - "dataset_kwargs": {"trust_remote_code": True}, "dataset_name": config["recipe"], - "dataset_path": "unitxt/data", } ) + self.image_decoder = datasets.Image() self.metrics = self.dataset["test"][0]["metrics"] + def download(self, dataset_kwargs: Optional[Dict[str, Any]] = None) -> None: + if is_unitxt_installed(): + from unitxt import load_dataset + + self.dataset = load_dataset(self.DATASET_NAME) + else: + self.dataset = datasets.load_dataset( + name=self.DATASET_NAME, + path="unitxt/data", + trust_remote_code=True, + ) + def has_training_docs(self): return "train" in self.dataset @@ -79,6 +99,9 @@ class Unitxt(ConfigurableTask): def doc_to_target(self, doc): doc["target"] + def get_arguments(self, doc, ctx): + return (ctx, {"until": ["\n"]}) + def construct_requests(self, doc, ctx, **kwargs): """Uses RequestFactory to construct Requests and returns an iterable of Requests which will be sent to the LM. @@ -90,12 +113,11 @@ class Unitxt(ConfigurableTask): language description, as well as the few shot examples, and the question part of the document for `doc`. """ - return [ Instance( request_type="generate_until", doc=doc, - arguments=(ctx, {"until": ["\n"]}), + arguments=self.get_arguments(doc, ctx), idx=0, **kwargs, ) @@ -140,3 +162,34 @@ class Unitxt(ConfigurableTask): whether a higher value of the submetric is better """ return {metric.replace("metrics.", ""): True for metric in self.metrics} + + +images_regex = r'' +image_source_regex = r'", doc["source"]) + + def doc_to_image(self, doc): + images = extract_images(doc["source"], doc) + return [self.image_decoder.decode_example(image) for image in images] + + def get_arguments(self, doc, ctx): + return (ctx, {"until": ["\n"]}, {"visual": self.doc_to_image(doc)}) diff --git a/lm_eval/tasks/unitxt/unitxt_multimodal b/lm_eval/tasks/unitxt/unitxt_multimodal new file mode 100644 index 00000000..fbcff691 --- /dev/null +++ b/lm_eval/tasks/unitxt/unitxt_multimodal @@ -0,0 +1 @@ +class: !function task.UnitxtMultiModal -- GitLab From 7ecee2bc2482b732048eb09af7e3ede42464fa83 Mon Sep 17 00:00:00 2001 From: zxcvuser Date: Thu, 17 Oct 2024 01:01:21 +0200 Subject: [PATCH 129/194] Add new tasks to spanish_bench and fix duplicates (#2390) * added tasks to spanish_bench * fixed capitalization in escola and run pre-commit * Update _flores_common_yaml * Update _flores_common_yaml * Update direct_yaml * Update cot_yaml * Update cot_yaml * Update _flores_common_yaml --------- Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> --- .../flores_gl/_flores_common_yaml | 1 - lm_eval/tasks/mgsm/direct/direct_yaml | 2 +- lm_eval/tasks/mgsm/en_cot/cot_yaml | 2 +- lm_eval/tasks/mgsm/native_cot/cot_yaml | 2 +- .../flores_pt/_flores_common_yaml | 1 - lm_eval/tasks/spanish_bench/README.md | 25 +++++++++++++------ lm_eval/tasks/spanish_bench/copa_es.yaml | 16 ++++++++++++ lm_eval/tasks/spanish_bench/escola.yaml | 14 +++++++++++ .../flores_es/_flores_common_yaml | 1 - .../spanish_bench/mgsm_direct_es_v2.yaml | 9 ------- .../tasks/spanish_bench/openbookqa_es.yaml | 20 +++++++++++++++ lm_eval/tasks/spanish_bench/paws_es.yaml | 20 --------------- .../tasks/spanish_bench/spanish_bench.yaml | 3 +++ lm_eval/tasks/spanish_bench/utils.py | 9 +++++++ lm_eval/tasks/spanish_bench/xnli_es.yaml | 19 -------------- 15 files changed, 83 insertions(+), 61 deletions(-) create mode 100644 lm_eval/tasks/spanish_bench/copa_es.yaml create mode 100644 lm_eval/tasks/spanish_bench/escola.yaml delete mode 100644 lm_eval/tasks/spanish_bench/mgsm_direct_es_v2.yaml create mode 100644 lm_eval/tasks/spanish_bench/openbookqa_es.yaml delete mode 100644 lm_eval/tasks/spanish_bench/paws_es.yaml delete mode 100644 lm_eval/tasks/spanish_bench/xnli_es.yaml diff --git a/lm_eval/tasks/galician_bench/flores_gl/_flores_common_yaml b/lm_eval/tasks/galician_bench/flores_gl/_flores_common_yaml index ada4c55c..bff45b85 100644 --- a/lm_eval/tasks/galician_bench/flores_gl/_flores_common_yaml +++ b/lm_eval/tasks/galician_bench/flores_gl/_flores_common_yaml @@ -1,4 +1,3 @@ -group: flores dataset_path: facebook/flores dataset_name: all output_type: generate_until diff --git a/lm_eval/tasks/mgsm/direct/direct_yaml b/lm_eval/tasks/mgsm/direct/direct_yaml index 3a265cb0..d2e301ba 100644 --- a/lm_eval/tasks/mgsm/direct/direct_yaml +++ b/lm_eval/tasks/mgsm/direct/direct_yaml @@ -1,7 +1,7 @@ # This file will be included in the generated language-specific task configs. # It doesn't have a yaml file extension as it is not meant to be imported directly # by the harness. -group: mgsm_direct +tag: mgsm_direct dataset_path: juletxara/mgsm dataset_name: null # Overridden by language-specific config. output_type: generate_until diff --git a/lm_eval/tasks/mgsm/en_cot/cot_yaml b/lm_eval/tasks/mgsm/en_cot/cot_yaml index f4d502ee..b53ae970 100644 --- a/lm_eval/tasks/mgsm/en_cot/cot_yaml +++ b/lm_eval/tasks/mgsm/en_cot/cot_yaml @@ -1,7 +1,7 @@ # This file will be included in the generated language-specific task configs. # It doesn't have a yaml file extension as it is not meant to be imported directly # by the harness. -group: mgsm_cot_native +tag: mgsm_cot_native dataset_path: juletxara/mgsm dataset_name: null # Overridden by language-specific config. output_type: generate_until diff --git a/lm_eval/tasks/mgsm/native_cot/cot_yaml b/lm_eval/tasks/mgsm/native_cot/cot_yaml index dbba8822..eb058ca4 100644 --- a/lm_eval/tasks/mgsm/native_cot/cot_yaml +++ b/lm_eval/tasks/mgsm/native_cot/cot_yaml @@ -1,7 +1,7 @@ # This file will be included in the generated language-specific task configs. # It doesn't have a yaml file extension as it is not meant to be imported directly # by the harness. -group: mgsm_cot_native +tag: mgsm_cot_native dataset_path: juletxara/mgsm dataset_name: null # Overridden by language-specific config. output_type: generate_until diff --git a/lm_eval/tasks/portuguese_bench/flores_pt/_flores_common_yaml b/lm_eval/tasks/portuguese_bench/flores_pt/_flores_common_yaml index ada4c55c..bff45b85 100644 --- a/lm_eval/tasks/portuguese_bench/flores_pt/_flores_common_yaml +++ b/lm_eval/tasks/portuguese_bench/flores_pt/_flores_common_yaml @@ -1,4 +1,3 @@ -group: flores dataset_path: facebook/flores dataset_name: all output_type: generate_until diff --git a/lm_eval/tasks/spanish_bench/README.md b/lm_eval/tasks/spanish_bench/README.md index ef55d00e..c896b39c 100644 --- a/lm_eval/tasks/spanish_bench/README.md +++ b/lm_eval/tasks/spanish_bench/README.md @@ -4,11 +4,18 @@ SpanishBench is a benchmark for evaluating language models in Spanish tasks. This is, it evaluates the ability of a language model to understand and generate Spanish text. SpanishBench offers a combination of pre-existing, open datasets. All the details of SpanishBench will be published in a paper soon. -The datasets included in SpanishBench are: +The new evaluation datasets included in SpanishBench are: +| Task | Category | Homepage | +|:-------------:|:-----:|:-----:| +| COPA-es | Commonsense Reasoning | https://huggingface.co/datasets/BSC-LT/COPA-es | +| OpenBookQA_es | Question Answering | https://huggingface.co/datasets/BSC-LT/openbookqa-es | + +The datasets included in SpanishBench that have been made public in previous publications are: | Task | Category | Paper title | Homepage | |:-------------:|:-----:|:-------------:|:-----:| | Belebele_es | Reading Comprehension | [The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://arxiv.org/abs/2308.16884) | https://huggingface.co/datasets/facebook/belebele | +| EsCoLA | Linguistic Acceptability | [EsCoLA: Spanish Corpus of Linguistic Acceptability](https://aclanthology.org/2024.lrec-main.554/) | https://huggingface.co/datasets/nbel/EsCoLA | | FLORES_es | Translation | [The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation](https://arxiv.org/abs/2106.03193) | https://huggingface.co/datasets/facebook/flores | | MGSM_es | Math | [Language Models are Multilingual Chain-of-Thought Reasoners](https://arxiv.org/abs/2210.03057) | https://huggingface.co/datasets/juletxara/mgsm | | PAWS-X_es | Paraphrasing | [PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification](https://aclanthology.org/D19-1382/) | https://huggingface.co/datasets/google-research-datasets/paws-x | @@ -19,6 +26,7 @@ The datasets included in SpanishBench are: | XStoryCloze_es | Commonsense Reasoning | [Few-shot Learning with Multilingual Generative Language Models](https://aclanthology.org/2022.emnlp-main.616/) | https://huggingface.co/datasets/juletxara/xstory_cloze | + ### Citation Paper for SpanishBench coming soon. @@ -36,6 +44,8 @@ Paper for SpanishBench coming soon. The following tasks evaluate tasks on SpanishBench dataset using various scoring methods. - `belebele_spa_Latn` + - `copa_es` + - `escola` - `flores_es` - `flores_es-ca` - `flores_es-de` @@ -53,20 +63,21 @@ The following tasks evaluate tasks on SpanishBench dataset using various scoring - `flores_gl-es` - `flores_it-es` - `flores_pt-es` - - `mgsm_direct_es_v2` (`v2` is due to an existing open issue in the original task) - - `paws_es` + - `mgsm_direct_es_spanish_bench` (`spanish_bench` is due to an existing open issue in the original task) + - `openbookqa_es` + - `paws_es_spanish_bench` (`spanish_bench` is due to an existing open issue in the original task) - `phrases_es` - `wnli_es` - `xlsum_es` - - `xnli_es` + - `xnli_es_spanish_bench` (`spanish_bench` is due to an existing open issue in the original task) - `xquad_es` - `xstorycloze_es` Some of these tasks are taken from benchmarks already available in LM Evaluation Harness. These are: - `belebele_spa_Latn`: Belebele Spanish -- `mgsm_direct_es`: MGSM Spanish (We fix an existing open issue in the original task) -- `paws_es`: PAWS-X Spanish -- `xnli_es`: XNLI Spanish +- `mgsm_direct_es`: MGSM Spanish (fixed an existing open issue in the original task) +- `paws_es`: PAWS-X Spanish (fixed an existing open issue in the original task) +- `xnli_es`: XNLI Spanish (fixed an existing open issue in the original task) - `xstorycloze_es`: XStoryCloze Spanish ### Checklist diff --git a/lm_eval/tasks/spanish_bench/copa_es.yaml b/lm_eval/tasks/spanish_bench/copa_es.yaml new file mode 100644 index 00000000..7ed9b718 --- /dev/null +++ b/lm_eval/tasks/spanish_bench/copa_es.yaml @@ -0,0 +1,16 @@ +task: copa_es +dataset_path: BSC-LT/COPA-es +dataset_name: null +output_type: multiple_choice +validation_split: validation +test_split: test +process_docs: !function utils.process_docs_copa_es +doc_to_text: '{{premise[:-1].strip() + " " + {"cause": "porque", "effect": "y por lo tanto"}[question]}}' +doc_to_target: '{{choice1 if label == 0 else choice2}}' +doc_to_choice: '{{[choice1, choice2]}}' +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/escola.yaml b/lm_eval/tasks/spanish_bench/escola.yaml new file mode 100644 index 00000000..a32fcbba --- /dev/null +++ b/lm_eval/tasks/spanish_bench/escola.yaml @@ -0,0 +1,14 @@ +task: escola +dataset_path: nbel/EsCoLA +output_type: multiple_choice +training_split: train +validation_split: validation +test_split: null +doc_to_text: "{{Sentence}}\nPregunta: ¿Tiene sentido esta frase?\nRespuesta:" +doc_to_target: Label +doc_to_choice: ["no", "sí"] +metric_list: + - metric: mcc + - metric: acc +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/flores_es/_flores_common_yaml b/lm_eval/tasks/spanish_bench/flores_es/_flores_common_yaml index ada4c55c..bff45b85 100644 --- a/lm_eval/tasks/spanish_bench/flores_es/_flores_common_yaml +++ b/lm_eval/tasks/spanish_bench/flores_es/_flores_common_yaml @@ -1,4 +1,3 @@ -group: flores dataset_path: facebook/flores dataset_name: all output_type: generate_until diff --git a/lm_eval/tasks/spanish_bench/mgsm_direct_es_v2.yaml b/lm_eval/tasks/spanish_bench/mgsm_direct_es_v2.yaml deleted file mode 100644 index ed5a4a73..00000000 --- a/lm_eval/tasks/spanish_bench/mgsm_direct_es_v2.yaml +++ /dev/null @@ -1,9 +0,0 @@ -include: ../mgsm/direct/mgsm_direct_es.yaml -doc_to_target: '{{answer_number|string}}' -doc_to_text: '{% if answer is not none %}{{question+"\nRespuesta: "}}{% else %}{{"Pregunta: "+question+"\nRespuesta: "}}{% endif %}' -generation_kwargs: - until: - - "\n\n" - - "\n" - -task: mgsm_direct_es_v2 diff --git a/lm_eval/tasks/spanish_bench/openbookqa_es.yaml b/lm_eval/tasks/spanish_bench/openbookqa_es.yaml new file mode 100644 index 00000000..afdfeaee --- /dev/null +++ b/lm_eval/tasks/spanish_bench/openbookqa_es.yaml @@ -0,0 +1,20 @@ +task: openbookqa_es +dataset_path: BSC-LT/openbookqa-es +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: test +doc_to_text: question_stem +doc_to_target: "{{choices.label.index(answerKey.lstrip())}}" +doc_to_choice: "{{choices.text}}" +should_decontaminate: true +doc_to_decontamination_query: question_stem +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/paws_es.yaml b/lm_eval/tasks/spanish_bench/paws_es.yaml deleted file mode 100644 index 400e9786..00000000 --- a/lm_eval/tasks/spanish_bench/paws_es.yaml +++ /dev/null @@ -1,20 +0,0 @@ -group: - - pawsx -task: paws_es -dataset_path: paws-x -dataset_name: es -output_type: multiple_choice -training_split: train -validation_split: validation -test_split: test -process_docs: !function utils.process_docs_paraphrases -doc_to_text: '' -doc_to_target: label -doc_to_choice: '{{[sentence1+", ¿verdad? No, "+sentence2, sentence1+", ¿verdad? Sí, "+sentence2]}}' -target_delimiter: '' -metric_list: - - metric: acc - aggregation: mean - higher_is_better: true -metadata: - version: 1.0 diff --git a/lm_eval/tasks/spanish_bench/spanish_bench.yaml b/lm_eval/tasks/spanish_bench/spanish_bench.yaml index 8ddef58c..af336508 100644 --- a/lm_eval/tasks/spanish_bench/spanish_bench.yaml +++ b/lm_eval/tasks/spanish_bench/spanish_bench.yaml @@ -1,6 +1,9 @@ group: spanish_bench task: - belebele_spa_Latn + - copa_es + - escola + - openbookqa_es - wnli_es - xnli_es_spanish_bench - xstorycloze_es diff --git a/lm_eval/tasks/spanish_bench/utils.py b/lm_eval/tasks/spanish_bench/utils.py index 13793285..e7d6bd5f 100644 --- a/lm_eval/tasks/spanish_bench/utils.py +++ b/lm_eval/tasks/spanish_bench/utils.py @@ -82,6 +82,15 @@ def process_docs_paraphrases(dataset): ).map(_process_doc) +def process_docs_copa_es(dataset): + def _process_doc(doc): + doc["choice1"] = lowercase_first_letter(doc["choice1"]) + doc["choice2"] = lowercase_first_letter(doc["choice2"]) + return doc + + return dataset.map(_process_doc) + + def rouge1(items): """ # passthrough for efficiency diff --git a/lm_eval/tasks/spanish_bench/xnli_es.yaml b/lm_eval/tasks/spanish_bench/xnli_es.yaml deleted file mode 100644 index e30da630..00000000 --- a/lm_eval/tasks/spanish_bench/xnli_es.yaml +++ /dev/null @@ -1,19 +0,0 @@ -# Task configuration derived from Eleuther AI's implementation as of March 22, 2024, supplemented with an additional preprocessing function -task: xnli_es -dataset_path: xnli -dataset_name: es -output_type: multiple_choice -doc_to_choice: '{{[premise+", ¿correcto? Sí, "+hypothesis,premise+", ¿correcto? Así - que, "+hypothesis,premise+", ¿correcto? No, "+hypothesis]}}' -doc_to_text: '' -target_delimiter: '' -process_docs: !function utils.process_doc_nli -training_split: null -validation_split: validation -doc_to_target: label -metric_list: - - metric: acc - aggregation: mean - higher_is_better: true -metadata: - version: 1.0 -- GitLab From 624017b7f4501638b0d5848d0f0eab2914a7fb2c Mon Sep 17 00:00:00 2001 From: Ranger Date: Thu, 17 Oct 2024 22:53:24 +0800 Subject: [PATCH 130/194] group to tag for minerva_math (#2404) I find out this bug by comparing the code between hendrycks_math and minerva_math. --- lm_eval/tasks/minerva_math/minerva_math_algebra.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/tasks/minerva_math/minerva_math_algebra.yaml b/lm_eval/tasks/minerva_math/minerva_math_algebra.yaml index ac06b7ac..7eab43c6 100644 --- a/lm_eval/tasks/minerva_math/minerva_math_algebra.yaml +++ b/lm_eval/tasks/minerva_math/minerva_math_algebra.yaml @@ -1,4 +1,4 @@ -group: +tag: - math_word_problems task: minerva_math_algebra dataset_path: EleutherAI/hendrycks_math -- GitLab From c1d8795da7610d507cb191c2769c5e7bf1060a35 Mon Sep 17 00:00:00 2001 From: Arda Date: Thu, 17 Oct 2024 23:36:08 +0200 Subject: [PATCH 131/194] Fix: Turkish MMLU Regex Pattern (#2393) * Fix Regex Pattern for CoT experiments --------- --- .../tasks/turkishmmlu/config_cot/_turkishmmlu_cot_default_yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/tasks/turkishmmlu/config_cot/_turkishmmlu_cot_default_yaml b/lm_eval/tasks/turkishmmlu/config_cot/_turkishmmlu_cot_default_yaml index e2f9f9d6..03986c16 100644 --- a/lm_eval/tasks/turkishmmlu/config_cot/_turkishmmlu_cot_default_yaml +++ b/lm_eval/tasks/turkishmmlu/config_cot/_turkishmmlu_cot_default_yaml @@ -11,7 +11,7 @@ filter_list: - name: "get-answer" filter: - function: "regex" - regex_pattern: "([A-E])(?= şıkkıdır| şıkkı)$" + regex_pattern: "([A-E])(?= şıkkıdır| şıkkı)" - function: "take_first" - name: "get-choice" filter: -- GitLab From 9b052fdccae265d6cc422f463136d2da7c2541b2 Mon Sep 17 00:00:00 2001 From: Yuxian Gu Date: Sun, 20 Oct 2024 11:23:48 +0800 Subject: [PATCH 132/194] fix storycloze datanames (#2409) --- lm_eval/tasks/storycloze/storycloze_2016.yaml | 2 +- lm_eval/tasks/storycloze/storycloze_2018.yaml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/lm_eval/tasks/storycloze/storycloze_2016.yaml b/lm_eval/tasks/storycloze/storycloze_2016.yaml index 2d0f9222..c513c68a 100644 --- a/lm_eval/tasks/storycloze/storycloze_2016.yaml +++ b/lm_eval/tasks/storycloze/storycloze_2016.yaml @@ -1,7 +1,7 @@ tag: storycloze task: storycloze_2016 dataset_path: story_cloze -dataset_name: 2016 +dataset_name: "2016" output_type: multiple_choice validation_split: validation test_split: test diff --git a/lm_eval/tasks/storycloze/storycloze_2018.yaml b/lm_eval/tasks/storycloze/storycloze_2018.yaml index 3ac23830..de21aa43 100644 --- a/lm_eval/tasks/storycloze/storycloze_2018.yaml +++ b/lm_eval/tasks/storycloze/storycloze_2018.yaml @@ -1,7 +1,7 @@ tag: storycloze task: storycloze_2018 dataset_path: story_cloze -dataset_name: 2018 +dataset_name: "2018" output_type: multiple_choice validation_split: validation test_split: test -- GitLab From 389347ee98ee4c82949083ba9a5f5ef1bb021a6c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Iker=20Garc=C3=ADa-Ferrero?= Date: Tue, 22 Oct 2024 17:23:53 +0200 Subject: [PATCH 133/194] Update prompt (#2421) Update prompt according to: https://github.com/ikergarcia1996/NoticIA/blob/main/prompts.py --- lm_eval/tasks/noticia/noticia.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/tasks/noticia/noticia.yaml b/lm_eval/tasks/noticia/noticia.yaml index 33fd6ebc..68d47707 100644 --- a/lm_eval/tasks/noticia/noticia.yaml +++ b/lm_eval/tasks/noticia/noticia.yaml @@ -12,7 +12,7 @@ training_split: null validation_split: null test_split: test fewshot_split: null -doc_to_text: "Ahora eres una Inteligencia Artificial experta en desmontar titulares sensacionalistas o clickbait. Tu tarea consiste en analizar noticias con titulares sensacionalistas y generar un resumen de una sola frase que revele la verdad detrás del titular.\nEste es el titular de la noticia: {{web_headline}}\nEl titular plantea una pregunta o proporciona información incompleta. Debes buscar en el cuerpo de la noticia una frase que responda lo que se sugiere en el título. Responde siempre que puedas parafraseando el texto original. Usa siempre las mínimas palabras posibles. Recuerda responder siempre en Español.\nEste es el cuerpo de la noticia:\n{{web_text}}" +doc_to_text: "Ahora eres una Inteligencia Artificial experta en desmontar titulares sensacionalistas o clickbait. Tu tarea consiste en analizar noticias con titulares sensacionalistas y generar un resumen de una sola frase que revele la verdad detrás del titular.\nEste es el titular de la noticia: {{web_headline}}\nEl titular plantea una pregunta o proporciona información incompleta. Debes buscar en el cuerpo de la noticia una frase que responda lo que se sugiere en el título. Siempre que puedas cita el texto original, especialmente si se trata de una frase que alguien ha dicho. Si citas una frase que alguien ha dicho, usa comillas para indicar que es una cita. Usa siempre las mínimas palabras posibles. No es necesario que la respuesta sea una oración completa, puede ser sólo el foco de la pregunta. Recuerda responder siempre en Español.\nEste es el cuerpo de la noticia:\n{{web_text}}" doc_to_target: summary target_delimiter: " " num_fewshot: 0 -- GitLab From d4ae963510ab2f7c0eb38c8f2914a383a06c4e1b Mon Sep 17 00:00:00 2001 From: Leonid Sinev Date: Tue, 22 Oct 2024 19:13:46 +0300 Subject: [PATCH 134/194] [Fix] Replace generic exception classes with a more specific ones (#1989) * Replace generic exception classes with a more specific ones * rerun pre-commit to pass linter tests * Revert "rerun pre-commit to pass linter tests" This reverts commit 67f88ccf144469853217704520e613196042d859. * reduce repetitions in errors or so * Replace generic exception class with a more specific one --- lm_eval/models/anthropic_llms.py | 16 ++++++++-------- lm_eval/models/api_models.py | 2 +- lm_eval/models/gguf.py | 4 +++- lm_eval/models/huggingface.py | 4 ++-- lm_eval/models/mamba_lm.py | 8 ++++---- lm_eval/models/nemo_lm.py | 16 ++++++++-------- lm_eval/models/neuralmagic.py | 16 ++++++++-------- lm_eval/models/neuron_optimum.py | 2 +- lm_eval/models/optimum_lm.py | 2 +- lm_eval/models/vllm_causallms.py | 2 +- lm_eval/prompts/__init__.py | 6 +++--- scripts/clean_training_data/generate_13_grams.py | 2 +- 12 files changed, 41 insertions(+), 39 deletions(-) diff --git a/lm_eval/models/anthropic_llms.py b/lm_eval/models/anthropic_llms.py index 7b22b6a9..daba6734 100644 --- a/lm_eval/models/anthropic_llms.py +++ b/lm_eval/models/anthropic_llms.py @@ -45,8 +45,8 @@ def anthropic_completion( try: import anthropic - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "attempted to use 'anthropic' LM type, but package `anthropic` is not installed. \ please install anthropic via `pip install 'lm-eval[anthropic]'` or `pip install -e '.[anthropic]'`", ) @@ -108,8 +108,8 @@ def anthropic_chat( try: import anthropic - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "attempted to use 'anthropic' LM type, but package `anthropic` is not installed. \ please install anthropic via `pip install 'lm-eval[anthropic]'` or `pip install -e '.[anthropic]'`", ) @@ -168,8 +168,8 @@ class AnthropicLM(LM): try: import anthropic - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "attempted to use 'anthropic' LM type, but package `anthropic` is not installed. \ please install anthropic via `pip install 'lm-eval[anthropic]'` or `pip install -e '.[anthropic]'`", ) @@ -217,8 +217,8 @@ please install anthropic via `pip install 'lm-eval[anthropic]'` or `pip install def generate_until(self, requests, disable_tqdm: bool = False) -> List[str]: try: import anthropic - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "attempted to use 'anthropic' LM type, but package `anthropic` is not installed. \ please install anthropic via `pip install 'lm-eval[anthropic]'` or `pip install -e '.[anthropic]'`", ) diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index 9abc6de9..ffb8b8af 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -144,7 +144,7 @@ class TemplateAPI(TemplateLM): self.tokenizer = tiktoken.encoding_for_model(self.model) except ModuleNotFoundError as e: - raise Exception( + raise ModuleNotFoundError( "Attempted to use 'openai' LM type, but the package `tiktoken` is not installed. " "Please install it via `pip install lm-eval[api]` or `pip install -e .[api]`." ) from e diff --git a/lm_eval/models/gguf.py b/lm_eval/models/gguf.py index ee1362c6..52aef0de 100644 --- a/lm_eval/models/gguf.py +++ b/lm_eval/models/gguf.py @@ -68,7 +68,9 @@ class GGUFLM(LM): logger.error(f"RequestException: {e}") time.sleep(delay) # wait before retrying else: - raise Exception(f"Failed to get a valid response after {retries} retries.") + raise RuntimeError( + f"Failed to get a valid response after {retries} retries." + ) def loglikelihood(self, requests, disable_tqdm: bool = False): if not requests: diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 8b6f5641..32f7eac4 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -579,8 +579,8 @@ class HFLM(TemplateLM): else: try: from auto_gptq import AutoGPTQForCausalLM - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "Tried to load auto_gptq, but auto-gptq is not installed ", "please install auto-gptq via pip install lm-eval[gptq] or pip install -e .[gptq]", ) diff --git a/lm_eval/models/mamba_lm.py b/lm_eval/models/mamba_lm.py index cd904983..47a241f0 100644 --- a/lm_eval/models/mamba_lm.py +++ b/lm_eval/models/mamba_lm.py @@ -69,8 +69,8 @@ class MambaLMWrapper(HFLM): ) -> None: try: from mamba_ssm.utils.hf import load_config_hf # noqa: F811 - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "attempted to use 'mamba_ssm' LM type, but package `mamba_ssm` is not installed. \ please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba]`", ) @@ -88,8 +88,8 @@ please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba ) -> None: try: from mamba_ssm.models.mixer_seq_simple import MambaLMHeadModel # noqa: F811 - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "attempted to use 'mamba_ssm' LM type, but package `mamba_ssm` is not installed. \ please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba]`", ) diff --git a/lm_eval/models/nemo_lm.py b/lm_eval/models/nemo_lm.py index b3ab5f52..cf560197 100644 --- a/lm_eval/models/nemo_lm.py +++ b/lm_eval/models/nemo_lm.py @@ -39,8 +39,8 @@ def _patch_pretrained_cfg( ): try: import omegaconf - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "Attempted to use 'nemo_lm' model type, but package `nemo` is not installed" "Please install nemo following the instructions in the README: either with a NVIDIA PyTorch or NeMo container, " "or installing nemo following https://github.com/NVIDIA/NeMo.", @@ -79,8 +79,8 @@ def load_model( MegatronGPTModel, ) from nemo.collections.nlp.parts.nlp_overrides import NLPSaveRestoreConnector - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "Attempted to use 'nemo_lm' model type, but package `nemo` is not installed" "Please install nemo following the instructions in the README: either with a NVIDIA PyTorch or NeMo container, " "or installing nemo following https://github.com/NVIDIA/NeMo.", @@ -140,8 +140,8 @@ def load_model( def setup_distributed_environment(trainer): try: from nemo.utils.app_state import AppState - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "Attempted to use 'nemo_lm' model type, but package `nemo` is not installed" "Please install nemo following the instructions in the README: either with a NVIDIA PyTorch or NeMo container, " "or installing nemo following https://github.com/NVIDIA/NeMo.", @@ -194,8 +194,8 @@ class NeMoLM(LM): from pytorch_lightning.trainer.trainer import Trainer self.generate = generate - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "Attempted to use 'nemo_lm' model type, but package `nemo` is not installed" "Please install nemo following the instructions in the README: either with a NVIDIA PyTorch or NeMo container, " "or installing nemo following https://github.com/NVIDIA/NeMo.", diff --git a/lm_eval/models/neuralmagic.py b/lm_eval/models/neuralmagic.py index 8cb61d6f..0d66f599 100644 --- a/lm_eval/models/neuralmagic.py +++ b/lm_eval/models/neuralmagic.py @@ -38,8 +38,8 @@ class SparseMLLM(HFLM): ) -> None: try: from sparseml.transformers import SparseAutoModelForCausalLM - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "Package `sparseml` is not installed. " "Please install it via `pip install sparseml[transformers]`" ) @@ -88,8 +88,8 @@ class SparseMLLM(HFLM): def _get_config(self, pretrained: str, **kwargs) -> None: try: from sparseml.transformers import SparseAutoConfig - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "Package `sparseml` is not installed. " "Please install it via `pip install sparseml[transformers]`" ) @@ -112,8 +112,8 @@ class SparseMLLM(HFLM): ) -> None: try: from sparseml.transformers import SparseAutoTokenizer - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "Package `sparseml` is not installed. " "Please install it via `pip install sparseml[transformers]`" ) @@ -171,8 +171,8 @@ class DeepSparseLM(LM): try: import deepsparse - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "Package `deepsparse` is not installed. " "Please install it via `pip install deepsparse[transformers]`" ) diff --git a/lm_eval/models/neuron_optimum.py b/lm_eval/models/neuron_optimum.py index b276c151..ca2aaf65 100644 --- a/lm_eval/models/neuron_optimum.py +++ b/lm_eval/models/neuron_optimum.py @@ -144,7 +144,7 @@ class NEURON_HF(TemplateLM): add_bos_token: Optional[bool] = False, ) -> None: if not NEURON_AVAILABLE: - raise Exception( + raise ImportError( "Tried to load neuron model, but neuron is not installed ", "please install neuron via pip install transformers-neuron ", "also make sure you are running on an AWS inf2 instance", diff --git a/lm_eval/models/optimum_lm.py b/lm_eval/models/optimum_lm.py index 70d44abd..bd262398 100644 --- a/lm_eval/models/optimum_lm.py +++ b/lm_eval/models/optimum_lm.py @@ -50,7 +50,7 @@ class OptimumLM(HFLM): **kwargs, ) -> None: if not find_spec("optimum"): - raise Exception( + raise ModuleNotFoundError( "package `optimum` is not installed. Please install it via `pip install optimum[openvino]`" ) else: diff --git a/lm_eval/models/vllm_causallms.py b/lm_eval/models/vllm_causallms.py index 168f490a..ebe0ad00 100644 --- a/lm_eval/models/vllm_causallms.py +++ b/lm_eval/models/vllm_causallms.py @@ -65,7 +65,7 @@ class VLLM(TemplateLM): super().__init__() if not find_spec("vllm"): - raise Exception( + raise ModuleNotFoundError( "attempted to use 'vllm' LM type, but package `vllm` is not installed. " "Please install vllm via `pip install lm-eval[vllm]` or `pip install -e .[vllm]`" ) diff --git a/lm_eval/prompts/__init__.py b/lm_eval/prompts/__init__.py index 1f814214..c486223b 100644 --- a/lm_eval/prompts/__init__.py +++ b/lm_eval/prompts/__init__.py @@ -29,8 +29,8 @@ def get_prompt(prompt_id: str, dataset_name: str = None, subset_name: str = None if category_name == "promptsource": try: from promptsource.templates import DatasetTemplates - except ModuleNotFoundError: - raise Exception( + except ModuleNotFoundError as exception: + raise type(exception)( "Tried to load a Promptsource template, but promptsource is not installed ", "please install promptsource via pip install lm-eval[promptsource] or pip install -e .[promptsource]", ) @@ -118,7 +118,7 @@ class PromptString: # TODO need a way to process doc_to_choice if "doc_to_choice" in self.prompt_string: - raise Exception("Not yet implemented to accept doc_to_choice") + raise NotImplementedError("Not yet implemented to accept doc_to_choice") text_string = utils.apply_template(doc_to_text, doc) target_string = utils.apply_template(doc_to_target, doc) diff --git a/scripts/clean_training_data/generate_13_grams.py b/scripts/clean_training_data/generate_13_grams.py index e508f266..530c35ec 100644 --- a/scripts/clean_training_data/generate_13_grams.py +++ b/scripts/clean_training_data/generate_13_grams.py @@ -55,7 +55,7 @@ def yield_pile(start_offsets=None, checkpoint_offset=None): print( "We expect the pile archives to be in the 'pile' directory, but this was not found." ) - raise Exception("Pile directory not found.") + raise FileNotFoundError("Pile directory not found.") files = list(sorted(glob.glob(os.path.join(directory, "*.jsonl.zst*")))) -- GitLab From 1185e89a044618b5adc6f0b9363b629a19fffdc4 Mon Sep 17 00:00:00 2001 From: Nikodem Szwast <97400923+Medokins@users.noreply.github.com> Date: Wed, 23 Oct 2024 18:30:06 +0200 Subject: [PATCH 135/194] Support for IBM watsonx_llm (#2397) * add support for IBM watsonx_llm * add ibm_watsonx_ai package to optional-dependencies * move global scope imports to inner scope * change cache to lru_cache * fix circular import * use 3.8 typing * use 3.8 typing --------- Co-authored-by: Baber --- lm_eval/models/__init__.py | 1 + lm_eval/models/ibm_watsonx_ai.py | 415 +++++++++++++++++++++++++++++++ pyproject.toml | 1 + 3 files changed, 417 insertions(+) create mode 100644 lm_eval/models/ibm_watsonx_ai.py diff --git a/lm_eval/models/__init__.py b/lm_eval/models/__init__.py index 553be3a5..cde586ec 100644 --- a/lm_eval/models/__init__.py +++ b/lm_eval/models/__init__.py @@ -5,6 +5,7 @@ from . import ( gguf, hf_vlms, huggingface, + ibm_watsonx_ai, mamba_lm, nemo_lm, neuralmagic, diff --git a/lm_eval/models/ibm_watsonx_ai.py b/lm_eval/models/ibm_watsonx_ai.py new file mode 100644 index 00000000..7017184f --- /dev/null +++ b/lm_eval/models/ibm_watsonx_ai.py @@ -0,0 +1,415 @@ +import json +import os +from configparser import ConfigParser +from functools import lru_cache +from pathlib import Path +from typing import Any, Dict, List, NamedTuple, Optional, Tuple, Type, cast + +from tqdm import tqdm + +from lm_eval.api.instance import Instance +from lm_eval.api.model import LM +from lm_eval.api.registry import register_model +from lm_eval.utils import eval_logger, simple_parse_args_string + + +class LogLikelihoodResult(NamedTuple): + log_likelihood: float + is_greedy: bool + + +@lru_cache(maxsize=None) +def get_watsonx_credentials( + env_name: str = "YP_QA", + config_path: str = "config.ini", +) -> Dict[str, str]: + """ + Retrieves Watsonx API credentials from environmental variables or from a configuration file. + Args: + env_name (str, optional): The name of the environment from which to retrieve credentials. Defaults to "YP_QA". + config_path (str, optional): The file path to the `config.ini` configuration file. Defaults to "config.ini". + Returns: + dict[str, str]: A dictionary containing the credentials necessary for authentication, including + keys such as `apikey`, `url`, and `project_id`. + Raises: + FileNotFoundError: If the specified configuration file does not exist. + AssertionError: If the credentials format is invalid. + """ + + def _verify_credentials(creds: Any) -> None: + assert isinstance(creds, dict) and all( + key in creds.keys() for key in ["apikey", "url", "project_id"] + ), "Wrong configuration for credentials." + + credentials = { + "apikey": os.getenv("WATSONX_API_KEY", None), + "url": os.getenv("WATSONX_URL", None), + "project_id": os.getenv("WATSONX_PROJECT_ID", None), + } + + if any(credentials.get(key) is None for key in ["apikey", "url", "project_id"]): + eval_logger.warning( + "One or more required environment variables are missing, trying to load config.ini file." + ) + + config_path = "config.ini" if not config_path else config_path + + if not Path(config_path).is_absolute(): + config_path = os.path.join( + Path(__file__).parent.parent.absolute(), config_path + ) + + if not os.path.exists(config_path): + raise FileNotFoundError( + f"Provided config file path {config_path} does not exist. " + "You need to specify credentials in config.ini file under specified location." + ) + + config = ConfigParser() + config.read(config_path) + credentials = json.loads(config.get(env_name)) + + _verify_credentials(credentials) + return credentials + + +@register_model("watsonx_llm") +class WatsonxLLM(LM): + """ + Implementation of LM model interface for evaluating Watsonx model with the lm_eval framework. + See https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/model_guide.md for reference. + """ + + @classmethod + def create_from_arg_string( + cls: Type["WatsonxLLM"], + arg_string: str, + config_path: Optional[str] = None, + ) -> "WatsonxLLM": + """ + Allow the user to specify model parameters (TextGenerationParameters) in CLI arguments. + """ + try: + from ibm_watsonx_ai.metanames import GenTextParamsMetaNames as GenParams + except ImportError: + raise ImportError( + "Could not import ibm_watsonx_ai: Please install lm_eval[ibm_watsonx_ai] package." + ) + + args = simple_parse_args_string(arg_string) + model_id = args.pop("model_id", None) + if model_id is None: + raise ValueError("'model_id' is required, please pass it in 'model_args'") + + if not args.get("do_sample", None): + args["temperature"] = None + args["top_p"] = None + args["top_k"] = None + args["seed"] = None + + cls.generate_params = { + GenParams.DECODING_METHOD: ( + "greedy" if not args.get("do_sample", None) else "sample" + ), + GenParams.LENGTH_PENALTY: args.get("length_penalty", None), + GenParams.TEMPERATURE: args.get("temperature", None), + GenParams.TOP_P: args.get("top_p", None), + GenParams.TOP_K: args.get("top_k", None), + GenParams.RANDOM_SEED: args.get("seed", None), + GenParams.REPETITION_PENALTY: args.get("repetition_penalty", None), + GenParams.MIN_NEW_TOKENS: args.get("min_new_tokens", None), + GenParams.MAX_NEW_TOKENS: args.get("max_new_tokens", 256), + GenParams.STOP_SEQUENCES: args.get("stop_sequences", None), + GenParams.TIME_LIMIT: args.get("time_limit", None), + GenParams.TRUNCATE_INPUT_TOKENS: args.get("truncate_input_tokens", None), + GenParams.RETURN_OPTIONS: { + "generated_tokens": True, + "input_tokens": True, + "token_logprobs": True, + "token_ranks": True, + }, + } + + generate_params = { + k: v for k, v in cls.generate_params.items() if v is not None + } + + return cls( + watsonx_credentials=get_watsonx_credentials(config_path), + model_id=model_id, + generate_params=generate_params, + ) + + def __init__( + self, + watsonx_credentials: Dict, + model_id, + generate_params: Optional[Dict[Any, Any]] = None, + ) -> None: + try: + from ibm_watsonx_ai import APIClient + from ibm_watsonx_ai.foundation_models import ModelInference + except ImportError: + raise ImportError( + "Could not import ibm_watsonx_ai: Please install lm_eval[ibm_watsonx_ai] package." + ) + super().__init__() + client = APIClient(watsonx_credentials) + project_id = watsonx_credentials.get("project_id", None) + deployment_id = watsonx_credentials.get("deployment_id", None) + client.set.default_project(project_id) + self.generate_params = generate_params + self.model = ModelInference( + model_id=model_id, + deployment_id=deployment_id, + api_client=client, + project_id=project_id, + ) + self._model_id = model_id + + def dump_parameters(self): + """ + Dumps the model's parameters into a serializable format. + """ + return self._parameters.model_dump() + + @staticmethod + def _has_stop_token(response_tokens: List[str], context_tokens: List[str]) -> bool: + """ + Determines whether a stop token has been generated in the `response_tokens` compared to the `context_tokens`. + If the tokens do not match as expected, the function raises a RuntimeError, indicating a possible + misalignment between the tokens generated by the tokenizer and the model. + Args: + response_tokens (List[str]): The List of tokens generated as a response by the model. + context_tokens (List[str]): The List of tokens representing the input context. + Returns: + bool: True if the `response_tokens` likely contain a stop token that terminates the sequence, + otherwise raises an exception. + Raises: + RuntimeError: If there is an unexpected mismatch between the `response_tokens` and the `context_tokens`. + """ + context_length = len(context_tokens) + if response_tokens[: context_length - 1] == context_tokens[:-1]: + return ( + response_tokens[-1] != context_tokens[-1] + ) # only last token differs, probably stop sequence () + raise RuntimeError( + f"There is an unexpected difference between tokenizer and model tokens:\n" + f"context_tokens={context_tokens}\n" + f"response_tokens={response_tokens[:context_length]}" + ) + + def _check_model_logprobs_support(self): + """ + Verifies if the model supports returning log probabilities for input tokens. + This function sends a prompt to the model and checks whether the model's response + includes log probabilities for the input tokens. If log probabilities are not present, + it raises a `RuntimeError`, indicating that the model is not supported. + Raises: + RuntimeError: If the model does not return log probabilities for input tokens. + """ + tokens = self.model.generate_text( + prompt=["The best ice cream flavor is:"], + params=self.generate_params, + raw_response=True, + )[0]["results"][0] + if all(token.get("logprob", None) is None for token in tokens["input_tokens"]): + raise RuntimeError( + f"Model {self._model_id} is not supported: does not return logprobs for input tokens" + ) + + def _get_log_likelihood( + self, + input_tokens: List[Dict[str, float]], + context_tokens: List[Dict[str, float]], + ) -> LogLikelihoodResult: + """ + Calculates the log likelihood of the generated tokens compared to the context tokens. + Args: + input_tokens (List[dict[str, float]]): A List of token dictionaries, each containing + token information like `text` and `logprob`. + context_tokens (List[dict[str, float]]): A List of token dictionaries representing + the input context. + Returns: + LogLikelihoodResult: An object containing the calculated log likelihood and a boolean + flag indicating if the tokens were generated greedily. + """ + + response_tokens = [token["text"] for token in input_tokens] + context_length = len(context_tokens) + + if self._has_stop_token(response_tokens, context_tokens): + context_length -= 1 + + return LogLikelihoodResult( + log_likelihood=sum( + token.get("logprob", 0) for token in input_tokens[context_length:] + ), + is_greedy=all( + token["rank"] == 1 for token in input_tokens[context_length:] + ), + ) + + def generate_until(self, requests: List[Instance]) -> List[str]: + """ + Generates text responses for a List of requests, with progress tracking and caching. + Args: + requests (List[Instance]): A List of instances, each containing a text input to be processed. + Returns: + List[str]: A List of generated responses. + """ + requests = [request.args[0] for request in requests] + results = [] + batch_size = 5 + + for i in tqdm( + range(0, len(requests), batch_size), + desc=f"Running generate_until function with batch size {batch_size}", + ): + batch = requests[i : i + batch_size] + try: + responses = self.model.generate_text(batch, self.generate_params) + + except Exception as exp: + eval_logger.error(f"Error while generating text {exp}") + continue + + for response, context in zip(responses, batch): + results.append(response) + self.cache_hook.add_partial("generated_text", context, response) + + eval_logger.info("Cached responses") + + return results + + def loglikelihood(self, requests: List[Instance]) -> List[Tuple[float, bool]]: + """ + Args: + requests: Each request contains Instance.args : Tuple[str, str] containing: + 1. an input string to the LM and + 2. a target string on which the loglikelihood of the LM producing this target, + conditioned on the input, will be returned. + Returns: + tuple (loglikelihood, is_greedy) for each request according to the input order: + loglikelihood: probability of generating the target string conditioned on the input + is_greedy: True if and only if the target string would be generated by greedy sampling from the LM + """ + try: + from ibm_watsonx_ai.metanames import GenTextParamsMetaNames as GenParams + except ImportError: + raise ImportError( + "Could not import ibm_watsonx_ai: Please install lm_eval[ibm_watsonx_ai] package." + ) + self._check_model_logprobs_support() + self.generate_params[GenParams.MAX_NEW_TOKENS] = 1 + + requests = [request.args for request in requests] + results: List[LogLikelihoodResult] = [] + batch_size = 5 + + for i in tqdm( + range(0, len(requests), batch_size), + desc=f"Running loglikelihood function with batch size {batch_size}", + ): + batch = requests[i : i + batch_size] + try: + tokenized_contexts = [ + self.model.tokenize(prompt=context, return_tokens=True)["result"][ + "tokens" + ] + for context, _ in batch + ] + except Exception as exp: + eval_logger.error(f"Error while model tokenize:\n {exp}") + continue + + input_prompts = [context + continuation for context, continuation in batch] + + try: + responses = self.model.generate_text( + prompt=input_prompts, params=self.generate_params, raw_response=True + ) + except Exception as exp: + eval_logger.error(f"Error while model generate text:\n {exp}") + continue + + for response, tokenized_context, (context, continuation) in zip( + responses, tokenized_contexts, batch + ): + log_likelihood_response = self._get_log_likelihood( + response["results"][0]["input_tokens"], tokenized_context + ) + results.append(log_likelihood_response) + self.cache_hook.add_partial( + "loglikelihood", + (context, continuation), + ( + log_likelihood_response.log_likelihood, + log_likelihood_response.is_greedy, + ), + ) + eval_logger.info("Cached batch") + + return cast(List[Tuple[float, bool]], results) + + def loglikelihood_rolling(self, requests) -> List[Tuple[float, bool]]: + """ + Used to evaluate perplexity on a data distribution. + Args: + requests: Each request contains Instance.args : tuple[str] containing an input string to the model whose + entire loglikelihood, conditioned on purely the EOT token, will be calculated. + Returns: + tuple (loglikelihood,) for each request according to the input order: + loglikelihood: solely the probability of producing each piece of text given no starting input. + """ + try: + from ibm_watsonx_ai.metanames import GenTextParamsMetaNames as GenParams + except ImportError: + raise ImportError( + "Could not import ibm_watsonx_ai: Please install lm_eval[ibm_watsonx_ai] package." + ) + self._check_model_logprobs_support() + self.generate_params[GenParams.MAX_NEW_TOKENS] = 1 + + requests = [request.args[0] for request in requests] + results: List[LogLikelihoodResult] = [] + batch_size = 5 + + for i in tqdm( + range(0, len(requests), batch_size), + desc=f"Running loglikelihood_rolling function with batch size {batch_size}", + ): + batch = requests[i : i + batch_size] + + try: + responses = self.model.generate_text( + prompt=batch, params=self.generate_params, raw_response=True + ) + except Exception as exp: + eval_logger.error(f"Error while model generate text:\n {exp}") + continue + + for response, context in zip(responses, batch): + try: + log_likelihood_response = self._get_log_likelihood( + response["results"][0]["input_tokens"], [] + ) + results.append(log_likelihood_response) + + self.cache_hook.add_partial( + "loglikelihood_rolling", + context, + ( + log_likelihood_response.log_likelihood, + log_likelihood_response.is_greedy, + ), + ) + except Exception as exp: + eval_logger.error( + f"Error during log likelihood calculation:\n {exp}" + ) + continue + + eval_logger.info("Cached batch") + + return cast(List[Tuple[float, bool]], results) diff --git a/pyproject.toml b/pyproject.toml index 367bd580..37db0b24 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -93,6 +93,7 @@ all = [ "lm_eval[vllm]", "lm_eval[zeno]", "lm_eval[wandb]", + "lm_eval[ibm_watsonx_ai]" ] [tool.ruff.lint] -- GitLab From 7882043b4ee1ef9577b829809c2f4970b0bdba91 Mon Sep 17 00:00:00 2001 From: Kiersten Stokes Date: Fri, 25 Oct 2024 03:23:11 -0500 Subject: [PATCH 136/194] Fix package extras for watsonx support (#2426) * Update pyproject.toml with watsonx package extra Signed-off-by: kiersten-stokes * Remove unused function Signed-off-by: kiersten-stokes --------- Signed-off-by: kiersten-stokes --- lm_eval/models/ibm_watsonx_ai.py | 8 +------- pyproject.toml | 3 ++- 2 files changed, 3 insertions(+), 8 deletions(-) diff --git a/lm_eval/models/ibm_watsonx_ai.py b/lm_eval/models/ibm_watsonx_ai.py index 7017184f..6f6a09c1 100644 --- a/lm_eval/models/ibm_watsonx_ai.py +++ b/lm_eval/models/ibm_watsonx_ai.py @@ -158,7 +158,7 @@ class WatsonxLLM(LM): project_id = watsonx_credentials.get("project_id", None) deployment_id = watsonx_credentials.get("deployment_id", None) client.set.default_project(project_id) - self.generate_params = generate_params + self.generate_params = generate_params or {} self.model = ModelInference( model_id=model_id, deployment_id=deployment_id, @@ -167,12 +167,6 @@ class WatsonxLLM(LM): ) self._model_id = model_id - def dump_parameters(self): - """ - Dumps the model's parameters into a serializable format. - """ - return self._parameters.model_dump() - @staticmethod def _has_stop_token(response_tokens: List[str], context_tokens: List[str]) -> bool: """ diff --git a/pyproject.toml b/pyproject.toml index 37db0b24..c51852a7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -62,6 +62,7 @@ dev = ["pytest", "pytest-cov", "pytest-xdist", "pre-commit", "mypy"] deepsparse = ["deepsparse-nightly[llm]>=1.8.0.20240404"] gptq = ["auto-gptq[triton]>=0.6.0"] hf_transfer = ["hf_transfer"] +ibm_watsonx_ai = ["ibm_watsonx_ai"] ifeval = ["langdetect", "immutabledict", "nltk>=3.9.1"] neuronx = ["optimum[neuronx]"] mamba = ["mamba_ssm", "causal-conv1d==1.0.2"] @@ -81,6 +82,7 @@ all = [ "lm_eval[deepsparse]", "lm_eval[gptq]", "lm_eval[hf_transfer]", + "lm_eval[ibm_watsonx_ai]", "lm_eval[ifeval]", "lm_eval[mamba]", "lm_eval[math]", @@ -93,7 +95,6 @@ all = [ "lm_eval[vllm]", "lm_eval[zeno]", "lm_eval[wandb]", - "lm_eval[ibm_watsonx_ai]" ] [tool.ruff.lint] -- GitLab From 838a3e03c17efea79a0019153ed0544ee3630554 Mon Sep 17 00:00:00 2001 From: Chris Kerwell Gresla <80501101+ckgresla@users.noreply.github.com> Date: Wed, 30 Oct 2024 04:45:49 -0700 Subject: [PATCH 137/194] Fix lora requests when dp with vllm (#2433) * fix: use lora_request for data parallel vllm evals * fix(docs): include type hint * chore: lint, et pre-commit al --------- Co-authored-by: Chris Kerwell Gresla --- lm_eval/models/vllm_causallms.py | 33 ++++++++++++++++---------------- 1 file changed, 17 insertions(+), 16 deletions(-) diff --git a/lm_eval/models/vllm_causallms.py b/lm_eval/models/vllm_causallms.py index ebe0ad00..0d8f3cea 100644 --- a/lm_eval/models/vllm_causallms.py +++ b/lm_eval/models/vllm_causallms.py @@ -239,17 +239,25 @@ class VLLM(TemplateLM): # but then tensor_parallel breaks @ray.remote def run_inference_one_model( - model_args: dict, sampling_params, requests: List[List[int]] + model_args: dict, + sampling_params, + requests: List[List[int]], + lora_request: LoRARequest, ): llm = LLM(**model_args) return llm.generate( - prompt_token_ids=requests, sampling_params=sampling_params + prompt_token_ids=requests, + sampling_params=sampling_params, + lora_request=lora_request, ) # dispatch requests to all self.data_parallel_size workers, in interleaved fashion # interleaved important to balance context lengths across workers requests = [list(x) for x in distribute(self.data_parallel_size, requests)] - inputs = ((self.model_args, sampling_params, req) for req in requests) + inputs = ( + (self.model_args, sampling_params, req, self.lora_request) + for req in requests + ) object_refs = [run_inference_one_model.remote(*x) for x in inputs] results = ray.get(object_refs) # Invoke ray.shutdown() to prevent hang-ups if subsequent calls required. @@ -257,19 +265,12 @@ class VLLM(TemplateLM): # flatten results return undistribute(results) - if self.lora_request is not None: - outputs = self.model.generate( - prompt_token_ids=requests, - sampling_params=sampling_params, - use_tqdm=True if self.batch_size == "auto" else False, - lora_request=self.lora_request, - ) - else: - outputs = self.model.generate( - prompt_token_ids=requests, - sampling_params=sampling_params, - use_tqdm=True if self.batch_size == "auto" else False, - ) + outputs = self.model.generate( + prompt_token_ids=requests, + sampling_params=sampling_params, + use_tqdm=True if self.batch_size == "auto" else False, + lora_request=self.lora_request, + ) return outputs def loglikelihood_rolling( -- GitLab From b40a20ae5b97014ffa7f43395b06fbaf18875dd8 Mon Sep 17 00:00:00 2001 From: zxcvuser Date: Wed, 30 Oct 2024 15:36:09 +0100 Subject: [PATCH 138/194] Add xquad task (#2435) * Add xquad task * Update general README * Run pre-commit --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/spanish_bench/utils.py | 9 --- lm_eval/tasks/xquad/README.md | 62 +++++++++++++++++++ lm_eval/tasks/xquad/utils.py | 15 +++++ lm_eval/tasks/xquad/xquad_ar.yaml | 4 ++ .../xquad_es.yaml => xquad/xquad_common_yaml} | 14 +++-- lm_eval/tasks/xquad/xquad_de.yaml | 4 ++ lm_eval/tasks/xquad/xquad_el.yaml | 4 ++ lm_eval/tasks/xquad/xquad_en.yaml | 4 ++ lm_eval/tasks/xquad/xquad_es.yaml | 4 ++ lm_eval/tasks/xquad/xquad_hi.yaml | 4 ++ lm_eval/tasks/xquad/xquad_ro.yaml | 4 ++ lm_eval/tasks/xquad/xquad_ru.yaml | 4 ++ lm_eval/tasks/xquad/xquad_th.yaml | 4 ++ lm_eval/tasks/xquad/xquad_tr.yaml | 4 ++ lm_eval/tasks/xquad/xquad_vi.yaml | 4 ++ lm_eval/tasks/xquad/xquad_zh.yaml | 4 ++ 17 files changed, 135 insertions(+), 14 deletions(-) create mode 100755 lm_eval/tasks/xquad/README.md create mode 100755 lm_eval/tasks/xquad/utils.py create mode 100755 lm_eval/tasks/xquad/xquad_ar.yaml rename lm_eval/tasks/{spanish_bench/xquad_es.yaml => xquad/xquad_common_yaml} (65%) mode change 100644 => 100755 create mode 100755 lm_eval/tasks/xquad/xquad_de.yaml create mode 100755 lm_eval/tasks/xquad/xquad_el.yaml create mode 100755 lm_eval/tasks/xquad/xquad_en.yaml create mode 100755 lm_eval/tasks/xquad/xquad_es.yaml create mode 100755 lm_eval/tasks/xquad/xquad_hi.yaml create mode 100755 lm_eval/tasks/xquad/xquad_ro.yaml create mode 100755 lm_eval/tasks/xquad/xquad_ru.yaml create mode 100755 lm_eval/tasks/xquad/xquad_th.yaml create mode 100755 lm_eval/tasks/xquad/xquad_tr.yaml create mode 100755 lm_eval/tasks/xquad/xquad_vi.yaml create mode 100755 lm_eval/tasks/xquad/xquad_zh.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 83977a47..a7c2b41e 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -124,5 +124,6 @@ | [xcopa](xcopa/README.md) | Cross-lingual Choice of Plausible Alternatives, testing reasoning in multiple languages. | Estonian, Haitian, Indonesian, Italian, Quechua, Swahili, Tamil, Thai, Turkish, Vietnamese, Chinese | | [xnli](xnli/README.md) | Cross-Lingual Natural Language Inference to test understanding across different languages. | Arabic, Bulgarian, German, Greek, English, Spanish, French, Hindi, Russian, Swahili, Thai, Turkish, Urdu, Vietnamese, Chinese | | [xnli_eu](xnli_eu/README.md) | Cross-lingual Natural Language Inference tasks in Basque. | Basque | +| [xquad](xquad/README.md) | Cross-lingual Question Answering Dataset in multiple languages. | Arabic, German, Greek, English, Spanish, Hindi, Romanian, Russian, Thai, Turkish, Vietnamese, Chinese | | [xstorycloze](xstorycloze/README.md) | Cross-lingual narrative understanding tasks to predict story endings in multiple languages. | Russian, Simplified Chinese, Spanish, Arabic, Hindi, Indonesian, Telugu, Swahili, Basque, Burmese | | [xwinograd](xwinograd/README.md) | Cross-lingual Winograd schema tasks for coreference resolution in multiple languages. | English, French, Japanese, Portuguese, Russian, Chinese | diff --git a/lm_eval/tasks/spanish_bench/utils.py b/lm_eval/tasks/spanish_bench/utils.py index e7d6bd5f..e899b76a 100644 --- a/lm_eval/tasks/spanish_bench/utils.py +++ b/lm_eval/tasks/spanish_bench/utils.py @@ -35,15 +35,6 @@ def process_doc_nli(dataset): return dataset.map(process_fn) -def process_results_qa(doc, results): - preds = results[0] - reference = doc["answers"]["text"][0] - # import code; code.interact(local=dict(globals(), **locals())) - f1_sum = squad_metrics.compute_f1(reference, preds) - exact_match = squad_metrics.compute_exact(reference, preds) - return {"f1": f1_sum, "exact_match": exact_match} - - def process_xlsum(dataset): def _process_doc(doc): # Remove double spaces diff --git a/lm_eval/tasks/xquad/README.md b/lm_eval/tasks/xquad/README.md new file mode 100755 index 00000000..b6ee6829 --- /dev/null +++ b/lm_eval/tasks/xquad/README.md @@ -0,0 +1,62 @@ +# XQuAD + +### Paper + +Title: `On the Cross-lingual Transferability of Monolingual Representations` + +Abstract: https://aclanthology.org/2020.acl-main.421.pdf + +XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating cross-lingual question answering performance. The dataset consists of a subset of 240 paragraphs and 1190 question-answer pairs from the development set of SQuAD v1.1 (Rajpurkar et al., 2016) together with their professional translations into ten languages: Spanish, German, Greek, Russian, Turkish, Arabic, Vietnamese, Thai, Chinese, and Hindi. Consequently, the dataset is entirely parallel across 11 languages. + +Homepage: https://github.com/deepmind/xquad + + +### Citation + +``` +@article{Artetxe:etal:2019, + author = {Mikel Artetxe and Sebastian Ruder and Dani Yogatama}, + title = {On the cross-lingual transferability of monolingual representations}, + journal = {CoRR}, + volume = {abs/1910.11856}, + year = {2019}, + archivePrefix = {arXiv}, + eprint = {1910.11856} +} +``` + +### Groups and Tasks + +#### Groups + +* `xquad`: All available languages. + +#### Tasks +Perform extractive question answering for each language's subset of XQuAD. +* `xquad_ar`: Arabic +* `xquad_de`: German +* `xquad_el`: Greek +* `xquad_en`: English +* `xquad_es`: Spanish +* `xquad_hi`: Hindi +* `xquad_ro`: Romanian +* `xquad_ru`: Russian +* `xquad_th`: Thai +* `xquad_tr`: Turkish +* `xquad_vi`: Vietnamese +* `xquad_zh`: Chinese + + + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [x] Is the task an existing benchmark in the literature? + * [x] Have you referenced the original paper that introduced the task? + * [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/xquad/utils.py b/lm_eval/tasks/xquad/utils.py new file mode 100755 index 00000000..83e2e9ec --- /dev/null +++ b/lm_eval/tasks/xquad/utils.py @@ -0,0 +1,15 @@ +import re +from itertools import product + +import evaluate +import transformers.data.metrics.squad_metrics as squad_metrics + +from lm_eval.utils import general_detokenize + + +def process_results_qa(doc, results): + preds = results[0] + reference = doc["answers"]["text"][0] + f1_sum = squad_metrics.compute_f1(reference, preds) + exact_match = squad_metrics.compute_exact(reference, preds) + return {"f1": f1_sum, "exact_match": exact_match} diff --git a/lm_eval/tasks/xquad/xquad_ar.yaml b/lm_eval/tasks/xquad/xquad_ar.yaml new file mode 100755 index 00000000..4a843009 --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_ar.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_ar +dataset_name: xquad.ar +doc_to_text: "سيا: {{context}}\n\nسؤال: {{question}}\n\nإجابة:" diff --git a/lm_eval/tasks/spanish_bench/xquad_es.yaml b/lm_eval/tasks/xquad/xquad_common_yaml old mode 100644 new mode 100755 similarity index 65% rename from lm_eval/tasks/spanish_bench/xquad_es.yaml rename to lm_eval/tasks/xquad/xquad_common_yaml index 10819b69..134a1065 --- a/lm_eval/tasks/spanish_bench/xquad_es.yaml +++ b/lm_eval/tasks/xquad/xquad_common_yaml @@ -1,12 +1,16 @@ -task: xquad_es +# This file will be included in the generated language-specific task configs. +# It doesn't have a yaml file extension as it is not meant to be imported directly +# by the harness. +tag: xquad +task: null dataset_path: xquad -dataset_name: xquad.es +dataset_name: null output_type: generate_until -doc_to_text: "Contexto: {{context}}\n\nPregunta: {{question}}\n\nRespuesta:" -doc_to_target: '{{answers["text"][0]}}' validation_split: validation -target_delimiter: ' ' +doc_to_text: null +doc_to_target: '{{answers["text"][0]}}' process_results: !function utils.process_results_qa +target_delimiter: ' ' generation_kwargs: until: - "\n" diff --git a/lm_eval/tasks/xquad/xquad_de.yaml b/lm_eval/tasks/xquad/xquad_de.yaml new file mode 100755 index 00000000..f6d44f6b --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_de.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_de +dataset_name: xquad.de +doc_to_text: "Kontext: {{context}}\n\nFrage: {{question}}\n\nAntwort:" diff --git a/lm_eval/tasks/xquad/xquad_el.yaml b/lm_eval/tasks/xquad/xquad_el.yaml new file mode 100755 index 00000000..1b54cdb0 --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_el.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_el +dataset_name: xquad.el +doc_to_text: "Συμφραζόμενα: {{context}}\n\nΕρώτηση: {{question}}\n\nΑπάντηση:" diff --git a/lm_eval/tasks/xquad/xquad_en.yaml b/lm_eval/tasks/xquad/xquad_en.yaml new file mode 100755 index 00000000..54ac7575 --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_en.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_en +dataset_name: xquad.en +doc_to_text: "Context: {{context}}\n\nQuestion: {{question}}\n\nAnswer:" diff --git a/lm_eval/tasks/xquad/xquad_es.yaml b/lm_eval/tasks/xquad/xquad_es.yaml new file mode 100755 index 00000000..1322c90c --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_es.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_es +dataset_name: xquad.es +doc_to_text: "Contexto: {{context}}\n\nPregunta: {{question}}\n\nRespuesta:" diff --git a/lm_eval/tasks/xquad/xquad_hi.yaml b/lm_eval/tasks/xquad/xquad_hi.yaml new file mode 100755 index 00000000..8daa5dd8 --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_hi.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_hi +dataset_name: xquad.hi +doc_to_text: "प्रसंग: {{context}}\n\nसवाल: {{question}}\n\nउत्तर:" diff --git a/lm_eval/tasks/xquad/xquad_ro.yaml b/lm_eval/tasks/xquad/xquad_ro.yaml new file mode 100755 index 00000000..4f8023da --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_ro.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_ro +dataset_name: xquad.ro +doc_to_text: "Context: {{context}}\n\nÎntrebare: {{question}}\n\nRăspuns:" diff --git a/lm_eval/tasks/xquad/xquad_ru.yaml b/lm_eval/tasks/xquad/xquad_ru.yaml new file mode 100755 index 00000000..72b1d105 --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_ru.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_ru +dataset_name: xquad.ru +doc_to_text: "Контекст: {{context}}\n\nВопрос: {{question}}\n\nОтвет:" diff --git a/lm_eval/tasks/xquad/xquad_th.yaml b/lm_eval/tasks/xquad/xquad_th.yaml new file mode 100755 index 00000000..15569ce1 --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_th.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_th +dataset_name: xquad.th +doc_to_text: "บริบท: {{context}}\n\nคำถาม: {{question}}\n\nคำตอบ:" diff --git a/lm_eval/tasks/xquad/xquad_tr.yaml b/lm_eval/tasks/xquad/xquad_tr.yaml new file mode 100755 index 00000000..4f6c43db --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_tr.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_tr +dataset_name: xquad.tr +doc_to_text: "Bağlam: {{context}}\n\nSoru: {{question}}\n\nCevap:" diff --git a/lm_eval/tasks/xquad/xquad_vi.yaml b/lm_eval/tasks/xquad/xquad_vi.yaml new file mode 100755 index 00000000..8373902a --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_vi.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_vi +dataset_name: xquad.vi +doc_to_text: "Bối cảnh: {{context}}\n\nCâu hỏi: {{question}}\n\nTrả lời:" diff --git a/lm_eval/tasks/xquad/xquad_zh.yaml b/lm_eval/tasks/xquad/xquad_zh.yaml new file mode 100755 index 00000000..f0c7632a --- /dev/null +++ b/lm_eval/tasks/xquad/xquad_zh.yaml @@ -0,0 +1,4 @@ +include: xquad_common_yaml +task: xquad_zh +dataset_name: xquad.zh +doc_to_text: "语境: {{context}}\n\n问题: {{question}}\n\n回答:" -- GitLab From 57272b63b4c2c7b60e9d2c5fef66b251bb8742ef Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Wed, 30 Oct 2024 07:42:01 -0700 Subject: [PATCH 139/194] Add verify_certificate argument to local-completion (#2440) --- docs/API_guide.md | 4 ++++ lm_eval/models/api_models.py | 3 +++ 2 files changed, 7 insertions(+) diff --git a/docs/API_guide.md b/docs/API_guide.md index de2f1420..bb8ca2ab 100644 --- a/docs/API_guide.md +++ b/docs/API_guide.md @@ -91,6 +91,10 @@ When initializing a `TemplateAPI` instance or a subclass, you can provide severa - Custom token ID to use as a prefix for inputs. - If not provided, uses the model's default BOS or EOS token (if `add_bos_token` is True). +- `verify_certificate` (bool, optional): + - Whether to validate the certificate of the API endpoint (if HTTPS). + - Default is True. + Example usage: diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index ffb8b8af..fa442618 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -79,6 +79,7 @@ class TemplateAPI(TemplateLM): trust_remote_code: bool = False, revision: Optional[str] = "main", use_fast_tokenizer: bool = True, + verify_certificate: bool = True, **kwargs, ) -> None: super().__init__() @@ -120,6 +121,7 @@ class TemplateAPI(TemplateLM): self.custom_prefix_token_id = custom_prefix_token_id self.tokenized_requests = tokenized_requests self.max_retries = int(max_retries) + self.verify_certificate = verify_certificate eval_logger.info(f"Using tokenizer {self.tokenizer_backend}") if self.tokenizer_backend is None: @@ -342,6 +344,7 @@ class TemplateAPI(TemplateLM): **kwargs, ), headers=self.header, + verify=self.verify_certificate, ) if not response.ok: eval_logger.warning( -- GitLab From 4f8e479e5e22c0cb04db5aa6cf7be3078b98ecb3 Mon Sep 17 00:00:00 2001 From: Qubitium-ModelCloud Date: Fri, 1 Nov 2024 00:15:07 +0800 Subject: [PATCH 140/194] Add GPTQModel support for evaluating GPTQ models (#2217) * support gptqmodel * code opt * add gptqmodel option * Update huggingface.py * Update pyproject.toml * gptqmodel version upgraded to 1.0.6 * GPTQModel version upgraded to 1.0.8 * Update pyproject.toml * fix ruff-format error * add gptqmodel test * Update gptqmodel test model * skip cuda * python3.8 compatible * Update README.md * Update README.md --------- Co-authored-by: CL-ModelCloud --- README.md | 12 ++++++-- lm_eval/models/huggingface.py | 54 ++++++++++++++++++++++++---------- pyproject.toml | 1 + tests/models/test_gptqmodel.py | 54 ++++++++++++++++++++++++++++++++++ 4 files changed, 103 insertions(+), 18 deletions(-) create mode 100644 tests/models/test_gptqmodel.py diff --git a/README.md b/README.md index 078dd43f..c453de30 100644 --- a/README.md +++ b/README.md @@ -39,7 +39,7 @@ This project provides a unified framework to test generative language models on **Features:** - Over 60 standard academic benchmarks for LLMs, with hundreds of subtasks and variants implemented. -- Support for models loaded via [transformers](https://github.com/huggingface/transformers/) (including quantization via [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ)), [GPT-NeoX](https://github.com/EleutherAI/gpt-neox), and [Megatron-DeepSpeed](https://github.com/microsoft/Megatron-DeepSpeed/), with a flexible tokenization-agnostic interface. +- Support for models loaded via [transformers](https://github.com/huggingface/transformers/) (including quantization via [GPTQModel](https://github.com/ModelCloud/GPTQModel) and [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ)), [GPT-NeoX](https://github.com/EleutherAI/gpt-neox), and [Megatron-DeepSpeed](https://github.com/microsoft/Megatron-DeepSpeed/), with a flexible tokenization-agnostic interface. - Support for fast and memory-efficient inference with [vLLM](https://github.com/vllm-project/vllm). - Support for commercial APIs including [OpenAI](https://openai.com), and [TextSynth](https://textsynth.com/). - Support for evaluation on adapters (e.g. LoRA) supported in [HuggingFace's PEFT library](https://github.com/huggingface/peft). @@ -319,8 +319,16 @@ lm_eval --model hf \ --tasks hellaswag ``` -[GPTQ](https://github.com/PanQiWei/AutoGPTQ) quantized models can be loaded by specifying their file names in `,autogptq=NAME` (or `,autogptq=True` for default names) in the `model_args` argument: +GPTQ quantized models can be loaded using [GPTQModel](https://github.com/ModelCloud/GPTQModel) (faster) or [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ) +GPTQModel: add `,gptqmodel=True` to `model_args` +```bash +lm_eval --model hf \ + --model_args pretrained=model-name-or-path,gptqmodel=True \ + --tasks hellaswag +``` + +AutoGPTQ: add `,autogptq=True` to `model_args`: ```bash lm_eval --model hf \ --model_args pretrained=model-name-or-path,autogptq=model.safetensors,gptq_use_triton=True \ diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 32f7eac4..4afab42c 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -87,6 +87,7 @@ class HFLM(TemplateLM): peft: Optional[str] = None, delta: Optional[str] = None, autogptq: Optional[Union[bool, str]] = False, + gptqmodel: Optional[bool] = False, **kwargs, ) -> None: super().__init__() @@ -192,6 +193,7 @@ class HFLM(TemplateLM): peft=peft, delta=delta, autogptq=autogptq, + gptqmodel=gptqmodel, **kwargs, ) @@ -530,6 +532,7 @@ class HFLM(TemplateLM): peft: Optional[str] = None, delta: Optional[str] = None, autogptq: Optional[Union[bool, str]] = False, + gptqmodel: Optional[bool] = False, **kwargs, ) -> None: """ @@ -557,7 +560,7 @@ class HFLM(TemplateLM): ) ) - if not autogptq: + if not autogptq and not gptqmodel: if model_kwargs.get("load_in_4bit", None): assert ( transformers.__version__ >= "4.30.0" @@ -577,23 +580,42 @@ class HFLM(TemplateLM): **model_kwargs, ) else: - try: - from auto_gptq import AutoGPTQForCausalLM - except ModuleNotFoundError as exception: - raise type(exception)( - "Tried to load auto_gptq, but auto-gptq is not installed ", - "please install auto-gptq via pip install lm-eval[gptq] or pip install -e .[gptq]", + if autogptq and gptqmodel: + raise ValueError( + "Cannot use both 'autogptq' and 'gptqmodel' options at the same time." ) - self._model = AutoGPTQForCausalLM.from_quantized( - pretrained, - trust_remote_code=trust_remote_code, - model_basename=None if autogptq is True else Path(autogptq).stem, - use_safetensors=True - if autogptq is True - else autogptq.endswith(".safetensors"), - **model_kwargs, - ) + if autogptq: + try: + from auto_gptq import AutoGPTQForCausalLM + except ModuleNotFoundError as exception: + raise type(exception)( + "Tried to load auto_gptq, but auto-gptq is not installed ", + "please install auto-gptq via pip install lm-eval[gptq] or pip install -e .[gptq]", + ) + + self._model = AutoGPTQForCausalLM.from_quantized( + pretrained, + trust_remote_code=trust_remote_code, + model_basename=None if autogptq is True else Path(autogptq).stem, + use_safetensors=True + if autogptq is True + else autogptq.endswith(".safetensors"), + **model_kwargs, + ) + + if gptqmodel: + try: + from gptqmodel import GPTQModel + except ModuleNotFoundError as exception: + raise type(exception)( + "Tried to load gptqmodel, but gptqmodel is not installed ", + "please install gptqmodel via `pip install gptqmodel --no-build-isolation` or `pip install lm-eval[gptqmodel] --no-build-isolation`", + ) + + self._model = GPTQModel.from_quantized( + pretrained, trust_remote_code=trust_remote_code, **model_kwargs + ) if peft and delta: raise ValueError( diff --git a/pyproject.toml b/pyproject.toml index c51852a7..b7d1941d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -76,6 +76,7 @@ testing = ["pytest", "pytest-cov", "pytest-xdist"] vllm = ["vllm>=0.4.2"] zeno = ["pandas", "zeno-client"] wandb = ["wandb>=0.16.3", "pandas", "numpy"] +gptqmodel = ["gptqmodel>=1.0.9"] all = [ "lm_eval[anthropic]", "lm_eval[dev]", diff --git a/tests/models/test_gptqmodel.py b/tests/models/test_gptqmodel.py new file mode 100644 index 00000000..9e3831c8 --- /dev/null +++ b/tests/models/test_gptqmodel.py @@ -0,0 +1,54 @@ +from typing import List + +import pytest + +import lm_eval + + +def assert_less_than(value, threshold, desc): + if value is not None: + assert float(value) < threshold, f"{desc} should be less than {threshold}" + + +@pytest.mark.skip(reason="requires CUDA") +class Test_GPTQModel: + gptqmodel = pytest.importorskip("gptqmodel", minversion="1.0.9") + MODEL_ID = "ModelCloud/Opt-125-GPTQ-4bit-10-25-2024" + + def test_gptqmodel(self) -> None: + acc = "acc" + acc_norm = "acc_norm" + acc_value = None + acc_norm_value = None + task = "arc_easy" + + model_args = f"pretrained={self.MODEL_ID},gptqmodel=True" + + tasks: List[str] = [task] + + results = lm_eval.simple_evaluate( + model="hf", + model_args=model_args, + tasks=tasks, + device="cuda", + ) + + column = "results" + dic = results.get(column, {}).get(self.task) + if dic is not None: + if "alias" in dic: + _ = dic.pop("alias") + items = sorted(dic.items()) + for k, v in items: + m, _, f = k.partition(",") + if m.endswith("_stderr"): + continue + + if m == acc: + acc_value = "%.4f" % v if isinstance(v, float) else v + + if m == acc_norm: + acc_norm_value = "%.4f" % v if isinstance(v, float) else v + + assert_less_than(acc_value, 0.43, "acc") + assert_less_than(acc_norm_value, 0.39, "acc_norm") -- GitLab From ade1cc4e481c65f8be44b8f4c6fc2c4942e6bd33 Mon Sep 17 00:00:00 2001 From: Sypherd <50557586+Sypherd@users.noreply.github.com> Date: Fri, 1 Nov 2024 13:53:59 +0000 Subject: [PATCH 141/194] Add missing task links (#2449) --- lm_eval/tasks/README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index a7c2b41e..670d40d8 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -73,7 +73,8 @@ | medqa | Multiple choice question answering based on the United States Medical License Exams. | | | [mgsm](mgsm/README.md) | Benchmark of multilingual grade-school math problems. | Spanish, French, German, Russian, Chinese, Japanese, Thai, Swahili, Bengali, Telugu | | [minerva_math](minerva_math/README.md) | Mathematics-focused tasks requiring numerical reasoning and problem-solving skills. | English | -| mmlu | Massive Multitask Language Understanding benchmark for broad domain language evaluation. Several variants are supported. | English | +| [mmlu](mmlu/README.md) | Massive Multitask Language Understanding benchmark for broad domain language evaluation. Several variants are supported. | English | +| [mmlu_pro](mmlu_pro/README.md) | A refined set of MMLU, integrating more challenging, reasoning-focused questions and expanding the choice set from four to ten options. | English | | [mmlusr](mmlusr/README.md) | Variation of MMLU designed to be more rigorous. | English | | model_written_evals | Evaluation tasks auto-generated for evaluating a collection of AI Safety concerns. | | | [mutual](mutual/README.md) | A retrieval-based dataset for multi-turn dialogue reasoning. | English | -- GitLab From c0745fec3062328e0ab618f36334848cdf29900e Mon Sep 17 00:00:00 2001 From: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Date: Mon, 4 Nov 2024 15:24:36 -0500 Subject: [PATCH 142/194] Update CODEOWNERS (#2453) --- CODEOWNERS | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/CODEOWNERS b/CODEOWNERS index 5a08ab24..874c8771 100644 --- a/CODEOWNERS +++ b/CODEOWNERS @@ -1 +1 @@ -* @haileyschoelkopf @lintangsutawika @baberabb +* @baberabb @lintangsutawika -- GitLab From 0b8358eca1c0ef6e0d58e1ea01cfdce5bb7350a5 Mon Sep 17 00:00:00 2001 From: Sypherd <50557586+Sypherd@users.noreply.github.com> Date: Tue, 5 Nov 2024 13:22:57 +0000 Subject: [PATCH 143/194] Add real process_docs example (#2456) --- docs/new_task_guide.md | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/docs/new_task_guide.md b/docs/new_task_guide.md index e9bd2bec..dac8541e 100644 --- a/docs/new_task_guide.md +++ b/docs/new_task_guide.md @@ -86,20 +86,20 @@ Let's create a python file in the directory where we're writing our YAML file: ```bash touch lm_eval/tasks//utils.py ``` -Now, in `utils.py` we'll write a function to process each split of our dataset: - -TODO: Change the example to one that's in the tasks/ +Now, in `utils.py` we'll write a function to process each split of our dataset (the following example is drawn from [the `hellaswag` task](../lm_eval/tasks/hellaswag/utils.py)): ```python -def process_docs(dataset: datasets.Dataset): - def _helper(doc): - # modifies the contents of a single - # document in our dataset. - doc["choices"] = [doc["choice1"], doc["choice2"], doc["wrong_answer"]] - doc["gold"] = doc["label"] - return doc - - return dataset.map(_helper) # returns back a datasets.Dataset object +def process_docs(dataset: datasets.Dataset) -> datasets.Dataset: + def _process_doc(doc): + ctx = doc["ctx_a"] + " " + doc["ctx_b"].capitalize() + out_doc = { + "query": preprocess(doc["activity_label"] + ": " + ctx), + "choices": [preprocess(ending) for ending in doc["endings"]], + "gold": int(doc["label"]), + } + return out_doc + + return dataset.map(_process_doc) ``` Now, in our YAML config file we'll use the `!function` constructor, and tell the config where our imported Python function will come from. At runtime, before doing anything else we will preprocess our dataset according to this function! -- GitLab From fb2e4b593c9fe19ae0b127bce30b4494bd683368 Mon Sep 17 00:00:00 2001 From: zxcvuser Date: Tue, 5 Nov 2024 16:22:18 +0100 Subject: [PATCH 144/194] Modify label errors in catcola and paws-x (#2434) * Modify label errors in catcola and paws * Update version to 1.0 in pawsx_template_yaml * add changelog --------- Co-authored-by: Baber --- lm_eval/tasks/catalan_bench/catcola.yaml | 2 +- lm_eval/tasks/paws-x/README.md | 4 ++++ lm_eval/tasks/paws-x/paws_de.yaml | 2 +- lm_eval/tasks/paws-x/paws_en.yaml | 2 +- lm_eval/tasks/paws-x/paws_es.yaml | 2 +- lm_eval/tasks/paws-x/paws_fr.yaml | 4 ++-- lm_eval/tasks/paws-x/paws_ja.yaml | 2 +- lm_eval/tasks/paws-x/paws_ko.yaml | 2 +- lm_eval/tasks/paws-x/paws_zh.yaml | 2 +- lm_eval/tasks/paws-x/pawsx_template_yaml | 2 +- 10 files changed, 14 insertions(+), 10 deletions(-) diff --git a/lm_eval/tasks/catalan_bench/catcola.yaml b/lm_eval/tasks/catalan_bench/catcola.yaml index 121b5e7f..ba3648ef 100644 --- a/lm_eval/tasks/catalan_bench/catcola.yaml +++ b/lm_eval/tasks/catalan_bench/catcola.yaml @@ -5,7 +5,7 @@ training_split: train validation_split: validation test_split: null doc_to_text: "{{Sentence}}\nPregunta: Té sentit aquesta frase?\nResposta:" -doc_to_target: label +doc_to_target: Label doc_to_choice: ["no", "sí"] metric_list: - metric: mcc diff --git a/lm_eval/tasks/paws-x/README.md b/lm_eval/tasks/paws-x/README.md index fb82edba..252657c1 100644 --- a/lm_eval/tasks/paws-x/README.md +++ b/lm_eval/tasks/paws-x/README.md @@ -77,3 +77,7 @@ If other tasks on this dataset are already supported: * [ ] Is the "Main" variant of this task clearly denoted? * [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? * [ ] Have you noted which, if any, published evaluation setups are matched by this variant? + +### Changelog + +* v1 (2024-11-05) PR #2434 corrected doc_to_choice labels to the correct order diff --git a/lm_eval/tasks/paws-x/paws_de.yaml b/lm_eval/tasks/paws-x/paws_de.yaml index 0d9ffad3..055b3735 100644 --- a/lm_eval/tasks/paws-x/paws_de.yaml +++ b/lm_eval/tasks/paws-x/paws_de.yaml @@ -1,6 +1,6 @@ # Generated by utils.py dataset_name: de -doc_to_choice: '{{[sentence1+", richtig? Ja, "+sentence2, sentence1+", richtig? Nein, +doc_to_choice: '{{[sentence1+", richtig? Nein, "+sentence2, sentence1+", richtig? Ja, "+sentence2]}}' doc_to_text: '' include: pawsx_template_yaml diff --git a/lm_eval/tasks/paws-x/paws_en.yaml b/lm_eval/tasks/paws-x/paws_en.yaml index c667e77a..b5955b03 100644 --- a/lm_eval/tasks/paws-x/paws_en.yaml +++ b/lm_eval/tasks/paws-x/paws_en.yaml @@ -1,6 +1,6 @@ # Generated by utils.py dataset_name: en -doc_to_choice: '{{[sentence1+", right? Yes, "+sentence2, sentence1+", right? No, "+sentence2]}}' +doc_to_choice: '{{[sentence1+", right? No, "+sentence2, sentence1+", right? Yes, "+sentence2]}}' doc_to_text: '' include: pawsx_template_yaml task: paws_en diff --git a/lm_eval/tasks/paws-x/paws_es.yaml b/lm_eval/tasks/paws-x/paws_es.yaml index e58805a9..65189a37 100644 --- a/lm_eval/tasks/paws-x/paws_es.yaml +++ b/lm_eval/tasks/paws-x/paws_es.yaml @@ -1,6 +1,6 @@ # Generated by utils.py dataset_name: es -doc_to_choice: '{{[sentence1+", verdad? Sí, "+sentence2, sentence1+", verdad? No, +doc_to_choice: '{{[sentence1+", verdad? No, "+sentence2, sentence1+", verdad? Sí, "+sentence2]}}' doc_to_text: '' include: pawsx_template_yaml diff --git a/lm_eval/tasks/paws-x/paws_fr.yaml b/lm_eval/tasks/paws-x/paws_fr.yaml index f6973d99..a8f599a1 100644 --- a/lm_eval/tasks/paws-x/paws_fr.yaml +++ b/lm_eval/tasks/paws-x/paws_fr.yaml @@ -1,7 +1,7 @@ # Generated by utils.py dataset_name: fr -doc_to_choice: '{{[sentence1+", n''est-ce pas? Oui, "+sentence2, sentence1+", n''est-ce - pas? No, "+sentence2]}}' +doc_to_choice: '{{[sentence1+", n''est-ce pas? Non, "+sentence2, sentence1+", n''est-ce + pas? Oui, "+sentence2]}}' doc_to_text: '' include: pawsx_template_yaml task: paws_fr diff --git a/lm_eval/tasks/paws-x/paws_ja.yaml b/lm_eval/tasks/paws-x/paws_ja.yaml index 296885b3..19abc976 100644 --- a/lm_eval/tasks/paws-x/paws_ja.yaml +++ b/lm_eval/tasks/paws-x/paws_ja.yaml @@ -1,6 +1,6 @@ # Generated by utils.py dataset_name: ja -doc_to_choice: '{{[sentence1+", ですね? はい, "+sentence2, sentence1+", ですね? いいえ, "+sentence2]}}' +doc_to_choice: '{{[sentence1+", ですね? いいえ, "+sentence2, sentence1+", ですね? はい, "+sentence2]}}' doc_to_text: '' include: pawsx_template_yaml task: paws_ja diff --git a/lm_eval/tasks/paws-x/paws_ko.yaml b/lm_eval/tasks/paws-x/paws_ko.yaml index fc703441..5ca611aa 100644 --- a/lm_eval/tasks/paws-x/paws_ko.yaml +++ b/lm_eval/tasks/paws-x/paws_ko.yaml @@ -1,6 +1,6 @@ # Generated by utils.py dataset_name: ko -doc_to_choice: '{{[sentence1+", 맞죠? 예, "+sentence2, sentence1+", 맞죠? 아니요, "+sentence2]}}' +doc_to_choice: '{{[sentence1+", 맞죠? 아니요, "+sentence2, sentence1+", 맞죠? 예, "+sentence2]}}' doc_to_text: '' include: pawsx_template_yaml task: paws_ko diff --git a/lm_eval/tasks/paws-x/paws_zh.yaml b/lm_eval/tasks/paws-x/paws_zh.yaml index 6d8d2ac0..4187b4ca 100644 --- a/lm_eval/tasks/paws-x/paws_zh.yaml +++ b/lm_eval/tasks/paws-x/paws_zh.yaml @@ -1,6 +1,6 @@ # Generated by utils.py dataset_name: zh -doc_to_choice: '{{[sentence1+", 对吧? 是, "+sentence2, sentence1+", 对吧? 不是, "+sentence2]}}' +doc_to_choice: '{{[sentence1+", 对吧? 不是, "+sentence2, sentence1+", 对吧? 是, "+sentence2]}}' doc_to_text: '' include: pawsx_template_yaml task: paws_zh diff --git a/lm_eval/tasks/paws-x/pawsx_template_yaml b/lm_eval/tasks/paws-x/pawsx_template_yaml index dfdaae27..6f82e4a5 100644 --- a/lm_eval/tasks/paws-x/pawsx_template_yaml +++ b/lm_eval/tasks/paws-x/pawsx_template_yaml @@ -16,4 +16,4 @@ metric_list: aggregation: mean higher_is_better: true metadata: - version: 0.0 + version: 1.0 -- GitLab From 26f607f5432e1d09c55b25488c43523e7ecde657 Mon Sep 17 00:00:00 2001 From: mtkachenko <480105+sitfoxfly@users.noreply.github.com> Date: Tue, 5 Nov 2024 23:38:52 +0800 Subject: [PATCH 145/194] Add Japanese Leaderboard (#2439) * add jaqket_v2 and jcommonsenseqa * remove comments * remove num_beams as it is incompatible with vllm * add jnli + refactor * rename jnla -> jnli * add jsquad + replace colon chars with the Japanese unicode * ignore whitespaces in generation tasks * add marc_ja * add xwinograd + simplify other yamls * add mgsm and xlsum * refactor xlsum * add ja_leaderboard tag * edit README.md * update README.md * add credit + minor changes * run ruff format * address review comments + add group * remove aggregate_metric_list * remove tags * update tasks/README.md --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/japanese_leaderboard/README.md | 152 ++++++++++++++++++ .../japanese_leaderboard/_ja_leaderboard.yaml | 14 ++ .../ja_leaderboard_jaqket_v2.yaml | 40 +++++ .../ja_leaderboard_jcommonsenseqa.py | 6 + .../ja_leaderboard_jcommonsenseqa.yaml | 27 ++++ .../ja_leaderboard_jnli.yaml | 27 ++++ .../ja_leaderboard_jsquad.yaml | 40 +++++ .../ja_leaderboard_marc_ja.yaml | 26 +++ .../ja_leaderboard_mgsm.py | 36 +++++ .../ja_leaderboard_mgsm.yaml | 32 ++++ .../ja_leaderboard_xlsum.py | 75 +++++++++ .../ja_leaderboard_xlsum.yaml | 37 +++++ .../ja_leaderboard_xwinograd.py | 7 + .../ja_leaderboard_xwinograd.yaml | 26 +++ .../japanese_leaderboard/requirements.txt | 4 + pyproject.toml | 2 + 17 files changed, 552 insertions(+) create mode 100644 lm_eval/tasks/japanese_leaderboard/README.md create mode 100644 lm_eval/tasks/japanese_leaderboard/_ja_leaderboard.yaml create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jaqket_v2.yaml create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jcommonsenseqa.py create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jcommonsenseqa.yaml create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jnli.yaml create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jsquad.yaml create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_marc_ja.yaml create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_mgsm.py create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_mgsm.yaml create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xlsum.py create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xlsum.yaml create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xwinograd.py create mode 100644 lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xwinograd.yaml create mode 100644 lm_eval/tasks/japanese_leaderboard/requirements.txt diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 670d40d8..5c1fc627 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -55,6 +55,7 @@ | [hendrycks_math](hendrycks_math/README.md) | Mathematical problem-solving tasks to test numerical reasoning and problem-solving. | English | | [ifeval](ifeval/README.md) | Interactive fiction evaluation tasks for narrative understanding and reasoning. | English | | [inverse_scaling](inverse_scaling/README.md) | Multiple-choice tasks from the Inverse Scaling Prize, designed to find settings where larger language models perform worse. | English | +| [japanese_leaderboard](japanese_leaderboard/README.md) | Japanese language understanding tasks to benchmark model performance on various linguistic aspects. | Japanese | | [kmmlu](kmmlu/README.md) | Knowledge-based multi-subject multiple choice questions for academic evaluation. | Korean | | [kobest](kobest/README.md) | A collection of tasks designed to evaluate understanding in Korean language. | Korean | | [kormedmcqa](kormedmcqa/README.md) | Medical question answering tasks in Korean to test specialized domain knowledge. | Korean | diff --git a/lm_eval/tasks/japanese_leaderboard/README.md b/lm_eval/tasks/japanese_leaderboard/README.md new file mode 100644 index 00000000..2c4d00a1 --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/README.md @@ -0,0 +1,152 @@ +# Japanese Leaderboard + +The Japanese LLM Leaderboard evaluates language models based on a wide range of NLP tasks that reflect the characteristics of the Japanese language. + +### Groups, Tags, and Tasks + +#### Groups + +* `japanese_leaderboard`: runs all tasks defined in this directory + +#### Tasks + +##### Generation Evaluation + +* `ja_leaderboard_jaqket_v2`: The JAQKET dataset is designed for Japanese question answering research, featuring quiz-like questions with answers derived from Wikipedia article titles. [Source](https://github.com/kumapo/JAQKET-dataset) +* `ja_leaderboard_mgsm`: Multilingual Grade School Math Benchmark (MGSM) is a benchmark of grade-school math problems, proposed in the paper Language models are multilingual chain-of-thought reasoners. [Source](https://huggingface.co/datasets/juletxara/mgsm) +* `ja_leaderboard_xlsum`: This is the filtered Japanese subset of XL-Sum. [Source](https://github.com/csebuetnlp/xl-sum) +* `ja_leaderboard_jsquad`: JSQuAD is a Japanese version of SQuAD, a reading comprehension dataset. Each instance in the dataset consists of a question regarding a given context (Wikipedia article) and its answer. JSQuAD is based on SQuAD 1.1 (there are no unanswerable questions). [Source](https://github.com/yahoojapan/JGLUE) + +##### Multi-Choice/Classification Evaluation + +* `ja_leaderboard_jcommonsenseqa`: JCommonsenseQA is a Japanese version of CommonsenseQA, which is a multiple-choice question answering dataset that requires commonsense reasoning ability. [Source](https://github.com/yahoojapan/JGLUE) +* `ja_leaderboard_jnli`: JNLI is a Japanese version of the NLI (Natural Language Inference) dataset. The inference relations are entailment (含意), contradiction (矛盾), and neutral (中立). [Source](https://github.com/yahoojapan/JGLUE) +* `ja_leaderboard_marc_ja`: MARC-ja is a text classification dataset based on the Japanese portion of Multilingual Amazon Reviews Corpus (MARC). [Source](https://github.com/yahoojapan/JGLUE) +* `ja_leaderboard_xwinograd`: This is the Japanese portion of XWinograd. [Source](https://huggingface.co/datasets/polm-stability/xwinograd-ja) + +### Citation + +```bibtex +@inproceedings{ja_leaderboard_jaqket_v2, + title = {JAQKET: クイズを題材にした日本語 QA データセットの構築}, + author = {鈴木正敏 and 鈴木潤 and 松田耕史 and ⻄田京介 and 井之上直也}, + year = 2020, + booktitle = {言語処理学会第26回年次大会}, + url = {https://www.anlp.jp/proceedings/annual_meeting/2020/pdf_dir/P2-24.pdf} +} + +@article{ja_leaderboard_mgsm_1, + title = {Training Verifiers to Solve Math Word Problems}, + author = { + Cobbe, Karl and Kosaraju, Vineet and Bavarian, Mohammad and Chen, Mark and Jun, Heewoo and + Kaiser, Lukasz and Plappert, Matthias and Tworek, Jerry and Hilton, Jacob and Nakano, Reiichiro + and Hesse, Christopher and Schulman, John + }, + year = 2021, + journal = {arXiv preprint arXiv:2110.14168} +} + +@misc{ja_leaderboard_mgsm_2, + title = {Language Models are Multilingual Chain-of-Thought Reasoners}, + author = { + Freda Shi and Mirac Suzgun and Markus Freitag and Xuezhi Wang and Suraj Srivats and Soroush + Vosoughi and Hyung Won Chung and Yi Tay and Sebastian Ruder and Denny Zhou and Dipanjan Das and + Jason Wei + }, + year = 2022, + eprint = {2210.03057}, + archiveprefix = {arXiv}, + primaryclass = {cs.CL} +} + +@inproceedings{ja_leaderboard_xlsum, + title = {{XL}-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages}, + author = { + Hasan, Tahmid and Bhattacharjee, Abhik and Islam, Md. Saiful and Mubasshir, Kazi and Li, + Yuan-Fang and Kang, Yong-Bin and Rahman, M. Sohel and Shahriyar, Rifat + }, + year = 2021, + month = aug, + booktitle = {Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021}, + publisher = {Association for Computational Linguistics}, + address = {Online}, + pages = {4693--4703}, + url = {https://aclanthology.org/2021.findings-acl.413} +} + +@article{jglue_2023, + title = {JGLUE: 日本語言語理解ベンチマーク}, + author = {栗原 健太郎 and 河原 大輔 and 柴田 知秀}, + year = 2023, + journal = {自然言語処理}, + volume = 30, + number = 1, + pages = {63--87}, + doi = {10.5715/jnlp.30.63}, + url = {https://www.jstage.jst.go.jp/article/jnlp/30/1/30_63/_article/-char/ja} +} + +@inproceedings{jglue_kurihara-etal-2022-jglue, + title = {{JGLUE}: {J}apanese General Language Understanding Evaluation}, + author = {Kurihara, Kentaro and Kawahara, Daisuke and Shibata, Tomohide}, + year = 2022, + month = jun, + booktitle = {Proceedings of the Thirteenth Language Resources and Evaluation Conference}, + publisher = {European Language Resources Association}, + address = {Marseille, France}, + pages = {2957--2966}, + url = {https://aclanthology.org/2022.lrec-1.317} +} + +@inproceedings{jglue_kurihara_nlp2022, + title = {JGLUE: 日本語言語理解ベンチマーク}, + author = {栗原健太郎 and 河原大輔 and 柴田知秀}, + year = 2022, + booktitle = {言語処理学会第28回年次大会}, + url = {https://www.anlp.jp/proceedings/annual_meeting/2022/pdf_dir/E8-4.pdf}, + note = {in Japanese} +} + +@misc{xwinograd_muennighoff2022crosslingual, + title = {Crosslingual Generalization through Multitask Finetuning}, + author = { + Niklas Muennighoff and Thomas Wang and Lintang Sutawika and Adam Roberts and Stella Biderman + and Teven Le Scao and M Saiful Bari and Sheng Shen and Zheng-Xin Yong and Hailey Schoelkopf and + Xiangru Tang and Dragomir Radev and Alham Fikri Aji and Khalid Almubarak and Samuel Albanie and + Zaid Alyafeai and Albert Webson and Edward Raff and Colin Raffel + }, + year = 2022, + eprint = {2211.01786}, + archiveprefix = {arXiv}, + primaryclass = {cs.CL} +} + +@misc{xwinograd_tikhonov2021heads, + title = { + It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in + Commonsense Reasoning + }, + author = {Alexey Tikhonov and Max Ryabinin}, + year = 2021, + eprint = {2106.12066}, + archiveprefix = {arXiv}, + primaryclass = {cs.CL} +} +``` + +### Credit + +* Prompts: https://github.com/Stability-AI/lm-evaluation-harness/tree/jp-stable/lm_eval/tasks/ja + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [x] Is the task an existing benchmark in the literature? + * [x] Have you referenced the original paper that introduced the task? + * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/japanese_leaderboard/_ja_leaderboard.yaml b/lm_eval/tasks/japanese_leaderboard/_ja_leaderboard.yaml new file mode 100644 index 00000000..538b331a --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/_ja_leaderboard.yaml @@ -0,0 +1,14 @@ +group: japanese_leaderboard + +task: + - ja_leaderboard_jaqket_v2 + - ja_leaderboard_jcommonsenseqa + - ja_leaderboard_jnli + - ja_leaderboard_jsquad + - ja_leaderboard_marc_ja + - ja_leaderboard_mgsm + - ja_leaderboard_xlsum + - ja_leaderboard_xwinograd + +metadata: + version: 1.0 diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jaqket_v2.yaml b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jaqket_v2.yaml new file mode 100644 index 00000000..ccd7466b --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jaqket_v2.yaml @@ -0,0 +1,40 @@ +task: ja_leaderboard_jaqket_v2 + +dataset_path: kumapo/JAQKET +dataset_name: v2.0 + +training_split: train +validation_split: validation +test_split: null + +fewshot_split: train +num_fewshot: 1 + +description: "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。\n\n" +doc_to_text: "### 指示：\n与えられた文脈から、質問に対する答えを抜き出してください。\n\n### 入力：\n文脈：{{ ctxs['text'] | join('\n') }}\n質問：{{ question }}\n\n### 応答：" +doc_to_target: "{{ answers['text'][0] }}" +target_delimiter: "\n" + +output_type: generate_until + +generation_kwargs: + until: + - "\n\n" + do_sample: false + +metric_list: + - metric: exact_match + regexes_to_ignore: + - '^\s+' + - '\s+$' + aggregation: mean + higher_is_better: true + +filter_list: + - name: whitespaces + filter: + - function: remove_whitespace + - function: take_first + +metadata: + version: 2.0 diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jcommonsenseqa.py b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jcommonsenseqa.py new file mode 100644 index 00000000..6f984be6 --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jcommonsenseqa.py @@ -0,0 +1,6 @@ +def process_docs(dataset): + def _add_choices(doc): + doc["choices"] = [doc[f"choice{i}"] for i in range(5)] + return doc + + return dataset.map(_add_choices) diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jcommonsenseqa.yaml b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jcommonsenseqa.yaml new file mode 100644 index 00000000..4348b701 --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jcommonsenseqa.yaml @@ -0,0 +1,27 @@ +task: ja_leaderboard_jcommonsenseqa + +dataset_path: Rakuten/JGLUE +dataset_name: JCommonsenseQA +training_split: train +validation_split: validation +test_split: null + +fewshot_split: train +num_fewshot: 3 + +description: "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。\n\n" +process_docs: !function ja_leaderboard_jcommonsenseqa.process_docs +doc_to_text: "### 指示：\n出力は以下から選択してください：\n{% for choice in choices %}- {{ choice }}\n{% endfor %}\n### 入力：\n{{ question }}\n\n### 応答：" +doc_to_target: label +doc_to_choice: choices +target_delimiter: "\n" + +output_type: multiple_choice + +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + +metadata: + version: 1.0 diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jnli.yaml b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jnli.yaml new file mode 100644 index 00000000..e01413bb --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jnli.yaml @@ -0,0 +1,27 @@ +task: ja_leaderboard_jnli + +dataset_path: Rakuten/JGLUE +dataset_name: JNLI +training_split: train +validation_split: validation +test_split: null + +fewshot_split: train +num_fewshot: 3 + +description: "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。\n\n" + +doc_to_text: "### 指示：\n与えられた前提と仮説の関係を回答してください。\n\n出力は以下から選択してください：\n含意\n矛盾\n中立\n\n### 入力：\n前提：{{ sentence1 }}\n仮説：{{ sentence2 }}\n\n### 応答：" +doc_to_target: label +doc_to_choice: ["含意", "矛盾", "中立"] +target_delimiter: "\n" + +output_type: multiple_choice + +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + +metadata: + version: 1.0 diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jsquad.yaml b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jsquad.yaml new file mode 100644 index 00000000..f378a846 --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_jsquad.yaml @@ -0,0 +1,40 @@ +task: ja_leaderboard_jsquad + +dataset_path: Rakuten/JGLUE +dataset_name: JSQuAD + +training_split: train +validation_split: validation +test_split: null + +fewshot_split: train +num_fewshot: 2 + +description: "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。\n\n" +doc_to_text: "### 指示：\n与えられた文脈から、質問に対する答えを抜き出してください。\n\n### 入力：\n文脈：{% set _context = context.split('[SEP]')[-1] %}{{ _context | trim }}\n質問：{{ question }}\n\n### 応答：" +doc_to_target: "{{ answers['text'][0] }}" +target_delimiter: "\n" + +output_type: generate_until + +generation_kwargs: + until: + - "\n\n" + do_sample: false + +metric_list: + - metric: exact_match + regexes_to_ignore: + - '^\s+' + - '\s+$' + aggregation: mean + higher_is_better: true + +filter_list: + - name: whitespaces + filter: + - function: remove_whitespace + - function: take_first + +metadata: + version: 1.0 diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_marc_ja.yaml b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_marc_ja.yaml new file mode 100644 index 00000000..8a19e38b --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_marc_ja.yaml @@ -0,0 +1,26 @@ +task: ja_leaderboard_marc_ja + +dataset_path: Rakuten/JGLUE +dataset_name: MARC-ja +training_split: train +validation_split: validation +test_split: null + +fewshot_split: train +num_fewshot: 3 + +description: "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。\n\n" +doc_to_text: "### 指示：\n以下の製品レビューを、ポジティブまたはネガティブの感情クラスのいずれかに分類してください。\n\n### 入力：\n{{ sentence }}\n\n### 応答：" +doc_to_target: label +doc_to_choice: ["ポジティブ", "ネガティブ"] +target_delimiter: "\n" + +output_type: multiple_choice + +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + +metadata: + version: 1.0 diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_mgsm.py b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_mgsm.py new file mode 100644 index 00000000..28f270b5 --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_mgsm.py @@ -0,0 +1,36 @@ +import re + + +_INVALID_ANSWER = "[invalid]" + +_ANSWER_REGEX = re.compile(r"(\-?[0-9\.\,]+)") + + +def _extract_answer(completion): + matches = _ANSWER_REGEX.findall(completion) + if matches: + match_str = matches[-1].strip(".") + match_str = match_str.replace(",", "") + try: + match_float = float(match_str) + except ValueError: + return _INVALID_ANSWER + + if match_float.is_integer(): + return int(match_float) + + return _INVALID_ANSWER + + +def process_results(doc, results): + assert ( + len(results) == 1 + ), f"results should be a list with 1 str element, but is {results}" + + completion = results[0] + extracted_answer = _extract_answer(completion) + answer = doc["answer_number"] + acc = extracted_answer == answer + return { + "acc": acc, + } diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_mgsm.yaml b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_mgsm.yaml new file mode 100644 index 00000000..bb041220 --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_mgsm.yaml @@ -0,0 +1,32 @@ +task: ja_leaderboard_mgsm + +dataset_path: juletxara/mgsm +dataset_name: ja + +training_split: train +validation_split: null +test_split: test + +fewshot_split: train +num_fewshot: 5 + +description: "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。\n\n" +doc_to_text: "### 指示：\n与えられた問題に対して、ステップごとに答えを導き出してください。\n\n### 入力：\n{{ question | replace('問題：', '') }}\n\n### 応答：" +doc_to_target: "{{ answer | replace('ステップごとの答え：', '') }}" +target_delimiter: "\n" + +output_type: generate_until +process_results: !function ja_leaderboard_mgsm.process_results + +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + +generation_kwargs: + until: + - "\n\n" + do_sample: false + +metadata: + version: 1.0 diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xlsum.py b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xlsum.py new file mode 100644 index 00000000..8b99ceed --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xlsum.py @@ -0,0 +1,75 @@ +import re + + +def _missing_module_message(name): + return f"`{name}` is required for `japanese_leaderboard`, please install `{name}` via pip install lm_eval[japanese_leaderboard] or pip install -e .[japanese_leaderboard]" + + +try: + import emoji + import neologdn + from fugashi import Tagger + from rouge_score import rouge_scorer, scoring +except ModuleNotFoundError as err: + raise ModuleNotFoundError(_missing_module_message(err.name)) from err + + +class MecabTokenizer: + def __init__(self) -> None: + self.tagger = Tagger("-Owakati") + + def normalize_answer(self, text): + """Lower case text, remove punctuation and extra whitespace, etc.""" + + def white_space_fix(text): + return " ".join(text.split()) + + def remove_emoji(text): + text = "".join(["" if emoji.is_emoji(c) else c for c in text]) + emoji_pattern = re.compile( + "[" + "\U0001f600-\U0001f64f" # emoticons + "\U0001f300-\U0001f5ff" # symbols & pictographs + "\U0001f680-\U0001f6ff" # transport & map symbols + "\U0001f1e0-\U0001f1ff" # flags (iOS) + "\U00002702-\U000027b0" + "]+", + flags=re.UNICODE, + ) + return emoji_pattern.sub(r"", text) + + text = remove_emoji(text) + # see neologdn docs for details, but handles things like full/half width variation + text = neologdn.normalize(text) + text = white_space_fix(text) + return text + + def tokenize(self, text): + return self.tagger.parse(self.normalize_answer(text)).split() + + +def rouge2(items): + return items + + +def rouge2_agg(items): + tokenizer = MecabTokenizer() + + refs = list(zip(*items))[0] + preds = list(zip(*items))[1] + + rouge_type = "rouge2" + + # mecab-based rouge + scorer = rouge_scorer.RougeScorer( + rouge_types=[rouge_type], + tokenizer=tokenizer, + ) + + # Acumulate confidence intervals. + aggregator = scoring.BootstrapAggregator() + for ref, pred in zip(refs, preds): + aggregator.add_scores(scorer.score(ref, pred)) + result = aggregator.aggregate() + + return result[rouge_type].mid.fmeasure diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xlsum.yaml b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xlsum.yaml new file mode 100644 index 00000000..5de60f18 --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xlsum.yaml @@ -0,0 +1,37 @@ +task: ja_leaderboard_xlsum + +dataset_path: mkshing/xlsum_ja +dataset_name: null + +training_split: train +validation_split: validation +test_split: test + +fewshot_split: train +num_fewshot: 1 + +description: "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。\n\n" +doc_to_text: "### 指示：\n与えられたニュース記事を要約してください。\n\n### 入力：\nニュース記事：{{ text }}\n\n### 応答：" +doc_to_target: "{{ summary }}" +target_delimiter: "\n" + +output_type: generate_until + +metric_list: + - metric: !function ja_leaderboard_xlsum.rouge2 + aggregation: !function ja_leaderboard_xlsum.rouge2_agg + higher_is_better: true + +filter_list: + - name: whitespaces + filter: + - function: remove_whitespace + - function: take_first + +generation_kwargs: + until: + - "\n\n" + do_sample: false + +metadata: + version: 1.0 diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xwinograd.py b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xwinograd.py new file mode 100644 index 00000000..74a1a5e6 --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xwinograd.py @@ -0,0 +1,7 @@ +def process_docs(dataset): + def _add_choices_and_label(doc): + doc["label"] = int(doc["answer"]) - 1 + doc["choices"] = [doc["sentence1"].strip(), doc["sentence2"].strip()] + return doc + + return dataset.map(_add_choices_and_label) diff --git a/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xwinograd.yaml b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xwinograd.yaml new file mode 100644 index 00000000..8a00b759 --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/ja_leaderboard_xwinograd.yaml @@ -0,0 +1,26 @@ +task: ja_leaderboard_xwinograd + +dataset_path: polm-stability/xwinograd-ja +dataset_name: null + +training_split: null +validation_split: null +test_split: test + +num_fewshot: null + +process_docs: !function ja_leaderboard_xwinograd.process_docs +doc_to_target: "label" +doc_to_choice: "choices" +doc_to_text: "" +target_delimiter: "" + +output_type: multiple_choice + +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + +metadata: + version: 1.0 diff --git a/lm_eval/tasks/japanese_leaderboard/requirements.txt b/lm_eval/tasks/japanese_leaderboard/requirements.txt new file mode 100644 index 00000000..894c2459 --- /dev/null +++ b/lm_eval/tasks/japanese_leaderboard/requirements.txt @@ -0,0 +1,4 @@ +emoji==2.14.0 +fugashi[unidic-lite] +neologdn==0.5.3 +rouge_score>=0.1.2 diff --git a/pyproject.toml b/pyproject.toml index b7d1941d..79d3dc3d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -77,6 +77,7 @@ vllm = ["vllm>=0.4.2"] zeno = ["pandas", "zeno-client"] wandb = ["wandb>=0.16.3", "pandas", "numpy"] gptqmodel = ["gptqmodel>=1.0.9"] +japanese_leaderboard = ["emoji==2.14.0", "neologdn==0.5.3", "fugashi[unidic-lite]", "rouge_score>=0.1.2"] all = [ "lm_eval[anthropic]", "lm_eval[dev]", @@ -96,6 +97,7 @@ all = [ "lm_eval[vllm]", "lm_eval[zeno]", "lm_eval[wandb]", + "lm_eval[japanese_leaderboard]", ] [tool.ruff.lint] -- GitLab From bf2abb4172b5249e5e1ea01b01268f2cd27b255c Mon Sep 17 00:00:00 2001 From: Rob Geada Date: Wed, 6 Nov 2024 17:25:12 +0000 Subject: [PATCH 146/194] Fix 'loglikelihood' typos in the api models file (#2459) --- lm_eval/models/api_models.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index fa442618..e23d3e6f 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -58,7 +58,7 @@ class TemplateAPI(TemplateLM): pretrained: str = None, # `model` takes precedence over `pretrained` when passed. base_url: str = None, tokenizer: Optional[str] = None, - # Logliklehood tasks require a tokenizer to calculate context lengths, + # Loglikelihood tasks require a tokenizer to calculate context lengths, # however the requests can be sent as a string if the API doesn't support token inputs. # use tokenized_requests=False tokenizer_backend: Optional[ @@ -196,7 +196,7 @@ class TemplateAPI(TemplateLM): if not self.tokenized_requests: # if messages are tokenized: if isinstance(messages[0][0], int): - # assuming decoding is lossless. However, this is only for logliklehood requests + # assuming decoding is lossless. However, this is only for loglikelihood requests # as we need to compute the context length. For generations, we don't need to tokenize. messages = self.decode_batch(messages) if self._batch_size <= 1: @@ -415,7 +415,7 @@ class TemplateAPI(TemplateLM): ) return None - def batch_logliklehood_requests( + def batch_loglikelihood_requests( self, chunks: Iterable[List[LogLikelihoodInputs]] ) -> Tuple[List[List[int]], List[int], List[Tuple[str, str]]]: inputs = [] @@ -500,7 +500,7 @@ class TemplateAPI(TemplateLM): if self._concurrent <= 1: pbar = tqdm(desc="Requesting API", total=len(requests)) for chunk in chunked: - inputs, ctxlens, cache_keys = self.batch_logliklehood_requests([chunk]) + inputs, ctxlens, cache_keys = self.batch_loglikelihood_requests([chunk]) outputs = retry( stop=stop_after_attempt(self.max_retries), @@ -524,7 +524,7 @@ class TemplateAPI(TemplateLM): ) pbar.update(1) else: - inputs, ctxlens, cache_keys = self.batch_logliklehood_requests(chunked) + inputs, ctxlens, cache_keys = self.batch_loglikelihood_requests(chunked) res = itertools.chain.from_iterable( asyncio.run( self.get_batched_requests( -- GitLab From cd18cb3bb50ea07332ad034ada7a799d4f697772 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Thu, 7 Nov 2024 16:31:43 +0000 Subject: [PATCH 147/194] use global filter (#2461) --- .../flan_cot_zeroshot/_mmlu_flan_cot_zeroshot_template_yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/tasks/mmlu/flan_cot_zeroshot/_mmlu_flan_cot_zeroshot_template_yaml b/lm_eval/tasks/mmlu/flan_cot_zeroshot/_mmlu_flan_cot_zeroshot_template_yaml index 7b374252..7588b67e 100644 --- a/lm_eval/tasks/mmlu/flan_cot_zeroshot/_mmlu_flan_cot_zeroshot_template_yaml +++ b/lm_eval/tasks/mmlu/flan_cot_zeroshot/_mmlu_flan_cot_zeroshot_template_yaml @@ -12,7 +12,7 @@ filter_list: - function: "take_first" - name: "flexible-extract" filter: - - function: !function utils.MultiChoiceRegexFilter + - function: "multi_choice_regex" group_select: -1 ignore_case: true ignore_punctuation: true -- GitLab From 901053f694390921d5fa59d2ba6a422726c121f5 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Thu, 7 Nov 2024 16:31:57 +0000 Subject: [PATCH 148/194] typo (#2465) --- lm_eval/api/task.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/api/task.py b/lm_eval/api/task.py index 532e9e7a..f0be8db9 100644 --- a/lm_eval/api/task.py +++ b/lm_eval/api/task.py @@ -67,7 +67,7 @@ class TaskConfig(dict): validation_split: Optional[str] = None test_split: Optional[str] = None fewshot_split: Optional[str] = ( - None # TODO: assert that this not None if num_fewshot > 0. (?) assert if this is same split as one evaling (?) + None # TODO: assert that this not None if num_fewshot > 0. (?) assert if this is same split as one evaluating (?) ) # formatting / prompting options. # see docs/advanced_task_guide.md for more info -- GitLab From 4155ec7fb9695d73d8301bc0323972fcb0f0d31e Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Thu, 7 Nov 2024 17:44:04 +0000 Subject: [PATCH 149/194] pass device_map other than auto for parallelize (#2457) * pass device_map other than auto for parallelize --- lm_eval/models/huggingface.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 4afab42c..2097c2cf 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -346,9 +346,9 @@ class HFLM(TemplateLM): == (self.accelerator.process_index % num_local_processes) } args["max_memory"] = max_memory_per_gpu_map - args["device_map"] = "auto" + args["device_map"] = "auto" if device_map is None else device_map eval_logger.info( - f"Model parallel was set to True, setting max memory per GPU to {max_memory_per_gpu_map} and device map to 'auto'" + f"Model parallel was set to True, setting max memory per GPU to {max_memory_per_gpu_map} and device map to {args.get('device_map')}" ) if max_cpu_memory is not None: -- GitLab From 060e876117ceac734e8dce5e062a1d4c25575792 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Sat, 9 Nov 2024 12:19:36 +0000 Subject: [PATCH 150/194] OpenAI ChatCompletions: switch `max_tokens` (#2443) * switch `max_tokens` for `max_completion_tokens`. OpenAI ChatCompletions * remove stop, temp=1 for o1 * add chat assertion * HF_DATASETS_TRUST_REMOTE_CODE = True for task tests * move warning --- lm_eval/models/openai_completions.py | 41 ++++++++++++++++++++++++++++ tests/test_tasks.py | 2 ++ 2 files changed, 43 insertions(+) diff --git a/lm_eval/models/openai_completions.py b/lm_eval/models/openai_completions.py index 331a3f6a..2f10316f 100644 --- a/lm_eval/models/openai_completions.py +++ b/lm_eval/models/openai_completions.py @@ -126,6 +126,9 @@ class LocalChatCompletion(LocalCompletionsAPI): seed=1234, **kwargs, ) -> dict: + assert ( + type(messages) is not str + ), "chat-completions require the --apply_chat_template flag." gen_kwargs.pop("do_sample", False) if "max_tokens" in gen_kwargs: max_tokens = gen_kwargs.pop("max_tokens") @@ -217,6 +220,10 @@ class OpenAIChatCompletion(LocalChatCompletion): tokenized_requests=False, **kwargs, ): + if "o1" in kwargs.get("model", ""): + eval_logger.warning( + "o1 models do not support `stop` and only support temperature=1" + ) super().__init__( base_url=base_url, tokenizer_backend=tokenizer_backend, @@ -238,3 +245,37 @@ class OpenAIChatCompletion(LocalChatCompletion): raise NotImplementedError( "Loglikelihood (and therefore `multiple_choice`-type tasks) is not supported for chat completions as OpenAI does not provide prompt logprobs. See https://github.com/EleutherAI/lm-evaluation-harness/issues/942#issuecomment-1777836312 or https://github.com/EleutherAI/lm-evaluation-harness/issues/1196 for more background on this limitation." ) + + def _create_payload( + self, + messages: List[Dict], + generate=False, + gen_kwargs: dict = None, + seed=1234, + **kwargs, + ) -> dict: + assert ( + type(messages) is not str + ), "chat-completions require the --apply_chat_template flag." + gen_kwargs.pop("do_sample", False) + if "max_tokens" in gen_kwargs: + max_tokens = gen_kwargs.pop("max_tokens") + else: + max_tokens = gen_kwargs.pop("max_gen_toks", self._max_gen_toks) + temperature = gen_kwargs.pop("temperature", 0) + stop = gen_kwargs.pop("until", ["<|endoftext|>"]) + if not isinstance(stop, (list, tuple)): + stop = [stop] + output = { + "messages": messages, + "model": self.model, + "max_completion_tokens": max_tokens, + "temperature": temperature, + "stop": stop[:4], + "seed": seed, + **gen_kwargs, + } + if "o1" in self.model: + output.pop("stop") + output["temperature"] = 1 + return output diff --git a/tests/test_tasks.py b/tests/test_tasks.py index 221b533d..e2410996 100644 --- a/tests/test_tasks.py +++ b/tests/test_tasks.py @@ -1,6 +1,7 @@ import os from itertools import islice +import datasets import pytest import lm_eval.tasks as tasks @@ -10,6 +11,7 @@ from lm_eval.evaluator_utils import get_task_list from .utils import new_tasks +datasets.config.HF_DATASETS_TRUST_REMOTE_CODE = True os.environ["TOKENIZERS_PARALLELISM"] = "false" task_manager = tasks.TaskManager() # Default Task -- GitLab From bd80a6c0099ee207e70f4943117739a817eccc0b Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Sat, 9 Nov 2024 12:23:01 +0000 Subject: [PATCH 151/194] Ifeval: Dowload `punkt_tab` on rank 0 (#2267) * download nltk `punkt_tab` on LOCAL_RANK=0 * remove print * remove `time` * nit --- lm_eval/tasks/ifeval/instructions_util.py | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/lm_eval/tasks/ifeval/instructions_util.py b/lm_eval/tasks/ifeval/instructions_util.py index 9ca2d4de..df58fb30 100644 --- a/lm_eval/tasks/ifeval/instructions_util.py +++ b/lm_eval/tasks/ifeval/instructions_util.py @@ -15,13 +15,14 @@ """Utility library of instructions.""" import functools +import os import random import re +from importlib.metadata import version import immutabledict import nltk -import pkg_resources -from packaging import version +from packaging.version import parse as parse_version # Downloading 'punkt' with nltk<3.9 has a remote code vuln. @@ -29,19 +30,22 @@ from packaging import version # and https://github.com/nltk/nltk/issues/3266 # for more information. NLTK_MIN_VERSION = "3.9.1" +RANK = os.environ.get("LOCAL_RANK", "0") def download_nltk_resources(): """Download 'punkt' if not already installed""" - nltk_version = pkg_resources.get_distribution("nltk").version assert ( - version.parse(nltk_version) >= version.parse(NLTK_MIN_VERSION) + (nltk_version := parse_version(version("nltk"))) + >= parse_version(NLTK_MIN_VERSION) ), f"`nltk` version {nltk_version} is not >= {NLTK_MIN_VERSION}. Please update `nltk` before proceeding--older versions are vulnerable to a remote code execution vulnerability." try: nltk.data.find("tokenizers/punkt_tab") except LookupError: - nltk.download("punkt_tab") + if RANK == "0": + nltk.download("punkt_tab") + print("Downloaded punkt_tab on rank 0") download_nltk_resources() -- GitLab From 77c811ead596a47993343614c1a3fca602bf7fc8 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 11 Nov 2024 17:01:08 +0000 Subject: [PATCH 152/194] Fix chat template; fix leaderboard math (#2475) * batch commit * :Revert "batch commit" This reverts commit d859d1ca3bc2d6e45979ec51379df119f2a9633d. * batch commit * checkout from main * checkout from main * checkout from main * checkout from main * checkout from main * cleanup * cleanup * cleanup * cleanup * cleanup * cleanup * cleanup * cleanup * cleanup * Chat template fix (#7) * cleanup * cleanup * cleanup * linting * fix tests * add ifeval install to new_task CI * Revert "add ifeval install to new_task CI" This reverts commit 1d19449bb7fbfa05d51e7cd20950475eae533bf1. * adds leaderboard tasks (#1) * adds leaderboard tasks * Delete lm_eval/tasks/leaderboard/leaderboard_chat_template.yaml * add readme * Delete lm_eval/tasks/leaderboard/mmlu_pro/mmlu_pro_chat_template.yaml * modify readme * fix bbh task * fix bbh salient task * modify the readme * Delete lm_eval/tasks/leaderboard/ifeval/README.md * Delete lm_eval/tasks/leaderboard/math/README.md * add leaderboard to the tasks repertory * add anouncment about new leaderbaord tasks * linting * Update README.md Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * installs ifeval dependency in new_task github workflow --------- Co-authored-by: Nathan Habib Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> * fix math parser * fix math parser * fix version * add warning about chat template --------- Co-authored-by: Nathan Habib Co-authored-by: Nathan Habib <30601243+NathanHB@users.noreply.github.com> Co-authored-by: Nathan Habib Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com> Co-authored-by: Nathan Habib --- docs/chat-template-readme.md | 26 ++++++++++++++++ lm_eval/api/task.py | 5 +++ lm_eval/evaluator.py | 5 +++ lm_eval/models/huggingface.py | 18 +++++++++-- lm_eval/tasks/leaderboard/math/_template_yaml | 2 +- lm_eval/tasks/leaderboard/math/utils.py | 31 ++++++++++++------- 6 files changed, 71 insertions(+), 16 deletions(-) create mode 100644 docs/chat-template-readme.md diff --git a/docs/chat-template-readme.md b/docs/chat-template-readme.md new file mode 100644 index 00000000..d127083d --- /dev/null +++ b/docs/chat-template-readme.md @@ -0,0 +1,26 @@ +# Chat Template Delimiter Handling Update + +## Overview +This change modifies how delimiters are handled when applying chat templates in the request construction process for likelihood and multiple-choice based tasks. When `apply_chat_template` is set to `True`, the target delimiter is now set to an empty string instead of using the configured delimiter. + +## Background +By default, the system uses a target delimiter (typically a whitespace " ") between the context and target text when constructing prompts. The full string is constructed as: +``` +doc_to_text(doc) + target_delimiter + doc_to_target(doc) +``` + +While this worked well for base models where we wanted the model to predict a single whitespace followed by the answer, chat models have their own formatting conventions that handle spacing differently. + +## The Change +- When `apply_chat_template=True`, the target delimiter is now empty ("") instead of the default whitespace +- This prevents interference between chat template formatting and the default delimiter system +- Particularly important for multiple choice tasks where the template itself handles spacing + +## Example +``` +# Before (with default delimiter " ") +Question: What color is the sky?\nAnswer: blue + +# After +Question: What color is the sky?\nAnswer:blue +``` diff --git a/lm_eval/api/task.py b/lm_eval/api/task.py index f0be8db9..56a1ad16 100644 --- a/lm_eval/api/task.py +++ b/lm_eval/api/task.py @@ -449,6 +449,7 @@ class Task(abc.ABC): doc=doc, ctx=fewshot_ctx, metadata=(self.config["task"], doc_id, self.config.repeats), + apply_chat_template=apply_chat_template, ) if not isinstance(inst, list): @@ -1301,6 +1302,8 @@ class ConfigurableTask(Task): def construct_requests( self, doc: dict, ctx: str, **kwargs ) -> Union[List[Instance], Instance]: + apply_chat_template = kwargs.pop("apply_chat_template", False) + aux_arguments = None if self.OUTPUT_TYPE == "loglikelihood": @@ -1310,6 +1313,8 @@ class ConfigurableTask(Task): elif self.OUTPUT_TYPE == "multiple_choice": choices = self.doc_to_choice(doc) target_delimiter = self.config.target_delimiter + if apply_chat_template: + target_delimiter = "" if self.multiple_input: # If there are multiple inputs, choices are placed in the ctx cont = self.doc_to_target(doc) diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index d0c1a19a..cea7d754 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -400,6 +400,11 @@ def evaluate( eval_logger.setLevel(getattr(logging, f"{verbosity}")) + if apply_chat_template: + eval_logger.warning( + "Chat template formatting change affects loglikelihood and multiple-choice tasks. See docs/chat-template-readme.md for details." + ) + # tracks all Instances/requests a model must generate output on. requests = defaultdict(list) # stores the amount to pad out reqs per req. type so that diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 2097c2cf..964dabb2 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -4,6 +4,7 @@ from datetime import timedelta from pathlib import Path from typing import Dict, List, Literal, Optional, Tuple, Union +import jinja2 import torch import torch.nn.functional as F import transformers @@ -1344,9 +1345,20 @@ class HFLM(TemplateLM): """ Method to apply a chat template to a list of chat history between user and model. """ - return self.tokenizer.apply_chat_template( - chat_history, tokenize=False, add_generation_prompt=True - ) + try: + chat_templated = self.tokenizer.apply_chat_template( + chat_history, tokenize=False, add_generation_prompt=True + ) + except jinja2.exceptions.TemplateError: + eval_logger.warning( + "Failed to apply chat template. removing the system role in chat history." + ) + chat_history = [msg for msg in chat_history if msg["role"] != "system"] + chat_templated = self.tokenizer.apply_chat_template( + chat_history, tokenize=False, add_generation_prompt=True + ) + + return chat_templated def get_model_info(self) -> dict: """ diff --git a/lm_eval/tasks/leaderboard/math/_template_yaml b/lm_eval/tasks/leaderboard/math/_template_yaml index 9c404b0c..bc97d202 100644 --- a/lm_eval/tasks/leaderboard/math/_template_yaml +++ b/lm_eval/tasks/leaderboard/math/_template_yaml @@ -18,7 +18,7 @@ metric_list: higher_is_better: true num_fewshot: 4 metadata: - version: 1.0 + version: 2.0 dataset_kwargs: trust_remote_code: true fewshot_config: diff --git a/lm_eval/tasks/leaderboard/math/utils.py b/lm_eval/tasks/leaderboard/math/utils.py index e3ebcf99..607be301 100644 --- a/lm_eval/tasks/leaderboard/math/utils.py +++ b/lm_eval/tasks/leaderboard/math/utils.py @@ -17,6 +17,9 @@ please install sympy via pip install lm-eval[math] or pip install -e .[math]", ) +INVALID_ANSWER = "[invalidanswer]" + + # taken from # https://github.com/wellecks/lm-evaluation-harness/blob/master/lm_eval/tasks/minerva_math.py def doc_to_text(doc: dict) -> str: @@ -70,7 +73,10 @@ def process_results(doc: dict, results: List[str]) -> Dict[str, int]: unnormalized_answer = get_unnormalized_answer(candidates) answer = normalize_final_answer(unnormalized_answer) - if is_equiv(answer, doc["answer"]): + if answer == INVALID_ANSWER: + return {"exact_match": 0} + + if answer.strip() == doc["answer"].strip() or is_equiv(answer, doc["answer"]): retval = 1 else: retval = 0 @@ -112,17 +118,19 @@ def last_boxed_only_string(string: str) -> Optional[str]: def remove_boxed(s: str) -> str: - if "\\boxed " in s: - left = "\\boxed " - assert s[: len(left)] == left - return s[len(left) :] - - left = "\\boxed{" + try: + if "\\boxed " in s: + left = "\\boxed " + assert s[: len(left)] == left + return s[len(left) :] - assert s[: len(left)] == left - assert s[-1] == "}" + left = "\\boxed{" - return s[len(left) : -1] + assert s[: len(left)] == left + assert s[-1] == "}" + return s[len(left) : -1] + except AssertionError: + return INVALID_ANSWER class timeout: @@ -146,7 +154,7 @@ def is_equiv(x1: str, x2: str) -> bool: x1 and x2 are normalized latex string """ try: - with timeout(seconds=5): + with timeout(seconds=1): try: parsed_x1 = parse_latex(x1) parsed_x2 = parse_latex(x2) @@ -185,7 +193,6 @@ def is_equiv(x1: str, x2: str) -> bool: def get_unnormalized_answer(text: str) -> str: - INVALID_ANSWER = "[invalidanswer]" end_seq = "I hope it is correct." text += end_seq match = re.search( -- GitLab From 6b628d9af327c81f53a604722ad8b9974b1411bc Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 11 Nov 2024 22:25:05 +0000 Subject: [PATCH 153/194] change warning to debug (#2481) --- lm_eval/models/huggingface.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 964dabb2..006f247c 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -1384,7 +1384,7 @@ class HFLM(TemplateLM): model_info = HfApi().model_info(repo_id=pretrained, revision=revision) return model_info.sha except Exception as e: - eval_logger.warn( + eval_logger.debug( f"Failed to get model SHA for {pretrained} at revision {revision}. Error: {e}" ) return "" -- GitLab From 67db63a5c7a262fddcc41e50abf388903397b2e6 Mon Sep 17 00:00:00 2001 From: Alex Titterton <53468446+alex-titterton@users.noreply.github.com> Date: Tue, 12 Nov 2024 17:34:52 +0000 Subject: [PATCH 154/194] wandb logger fix, added pre-commit (#2484) --- lm_eval/loggers/wandb_logger.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/lm_eval/loggers/wandb_logger.py b/lm_eval/loggers/wandb_logger.py index c9715a0f..4bcc439e 100644 --- a/lm_eval/loggers/wandb_logger.py +++ b/lm_eval/loggers/wandb_logger.py @@ -15,10 +15,9 @@ logger = logging.getLogger(__name__) def get_wandb_printer() -> Literal["Printer"]: """Returns a wandb printer instance for pretty stdout.""" - from wandb.sdk.lib.printer import get_printer - from wandb.sdk.wandb_settings import Settings + from wandb.sdk.lib.printer import new_printer - printer = get_printer(Settings()._jupyter) + printer = new_printer() return printer -- GitLab From 4259a6d4b23c87e6cc9210650f662acf14e40b9b Mon Sep 17 00:00:00 2001 From: Nikodem Szwast <97400923+Medokins@users.noreply.github.com> Date: Fri, 15 Nov 2024 02:01:15 +0100 Subject: [PATCH 155/194] IBM watsonx_llm fixes & refactor (#2464) * refactor code, fix config path bug * update types to be from typing lib * add pre-commit formatting * specify version of ibm_watsonx_ai package * adjust get_watsonx_credentials() function, add minor refactor to adress PR review comments * change missing installation hint from ibm_watsonx_ai to lm_eval[ibm_watsonx_ai] --- lm_eval/models/ibm_watsonx_ai.py | 243 +++++++++++++------------------ pyproject.toml | 2 +- 2 files changed, 105 insertions(+), 140 deletions(-) diff --git a/lm_eval/models/ibm_watsonx_ai.py b/lm_eval/models/ibm_watsonx_ai.py index 6f6a09c1..a82c5c45 100644 --- a/lm_eval/models/ibm_watsonx_ai.py +++ b/lm_eval/models/ibm_watsonx_ai.py @@ -1,8 +1,6 @@ -import json +import copy import os -from configparser import ConfigParser from functools import lru_cache -from pathlib import Path from typing import Any, Dict, List, NamedTuple, Optional, Tuple, Type, cast from tqdm import tqdm @@ -18,57 +16,46 @@ class LogLikelihoodResult(NamedTuple): is_greedy: bool -@lru_cache(maxsize=None) -def get_watsonx_credentials( - env_name: str = "YP_QA", - config_path: str = "config.ini", -) -> Dict[str, str]: +def _verify_credentials(creds: Any) -> None: """ - Retrieves Watsonx API credentials from environmental variables or from a configuration file. + Verifies that all required keys are present in the credentials dictionary. Args: - env_name (str, optional): The name of the environment from which to retrieve credentials. Defaults to "YP_QA". - config_path (str, optional): The file path to the `config.ini` configuration file. Defaults to "config.ini". + creds (Any): A dictionary containing the credentials. + Raises: + ValueError: If any of the necessary credentials are missing, with guidance on which environment variables need to be set. + """ + required_keys = ["apikey", "url", "project_id"] + env_var_mapping = { + "apikey": "WATSONX_API_KEY", + "url": "WATSONX_URL", + "project_id": "WATSONX_PROJECT_ID", + } + missing_keys = [key for key in required_keys if key not in creds or not creds[key]] + + if missing_keys: + missing_env_vars = [env_var_mapping[key] for key in missing_keys] + raise ValueError( + f"Missing required credentials: {', '.join(missing_keys)}. Please set the following environment variables: {', '.join(missing_env_vars)}" + ) + + +@lru_cache(maxsize=None) +def get_watsonx_credentials() -> Dict[str, str]: + """ + Retrieves Watsonx API credentials from environmental variables. Returns: - dict[str, str]: A dictionary containing the credentials necessary for authentication, including + Dict[str, str]: A dictionary containing the credentials necessary for authentication, including keys such as `apikey`, `url`, and `project_id`. Raises: - FileNotFoundError: If the specified configuration file does not exist. - AssertionError: If the credentials format is invalid. + AssertionError: If the credentials format is invalid or any of the necessary credentials are missing. """ - def _verify_credentials(creds: Any) -> None: - assert isinstance(creds, dict) and all( - key in creds.keys() for key in ["apikey", "url", "project_id"] - ), "Wrong configuration for credentials." - credentials = { "apikey": os.getenv("WATSONX_API_KEY", None), "url": os.getenv("WATSONX_URL", None), "project_id": os.getenv("WATSONX_PROJECT_ID", None), } - if any(credentials.get(key) is None for key in ["apikey", "url", "project_id"]): - eval_logger.warning( - "One or more required environment variables are missing, trying to load config.ini file." - ) - - config_path = "config.ini" if not config_path else config_path - - if not Path(config_path).is_absolute(): - config_path = os.path.join( - Path(__file__).parent.parent.absolute(), config_path - ) - - if not os.path.exists(config_path): - raise FileNotFoundError( - f"Provided config file path {config_path} does not exist. " - "You need to specify credentials in config.ini file under specified location." - ) - - config = ConfigParser() - config.read(config_path) - credentials = json.loads(config.get(env_name)) - _verify_credentials(credentials) return credentials @@ -84,7 +71,7 @@ class WatsonxLLM(LM): def create_from_arg_string( cls: Type["WatsonxLLM"], arg_string: str, - config_path: Optional[str] = None, + additional_config: Optional[Dict] = None, ) -> "WatsonxLLM": """ Allow the user to specify model parameters (TextGenerationParameters) in CLI arguments. @@ -97,6 +84,8 @@ class WatsonxLLM(LM): ) args = simple_parse_args_string(arg_string) + args.update(additional_config) + model_id = args.pop("model_id", None) if model_id is None: raise ValueError("'model_id' is required, please pass it in 'model_args'") @@ -107,7 +96,7 @@ class WatsonxLLM(LM): args["top_k"] = None args["seed"] = None - cls.generate_params = { + generate_params = { GenParams.DECODING_METHOD: ( "greedy" if not args.get("do_sample", None) else "sample" ), @@ -130,12 +119,10 @@ class WatsonxLLM(LM): }, } - generate_params = { - k: v for k, v in cls.generate_params.items() if v is not None - } + generate_params = {k: v for k, v in generate_params.items() if v is not None} return cls( - watsonx_credentials=get_watsonx_credentials(config_path), + watsonx_credentials=get_watsonx_credentials(), model_id=model_id, generate_params=generate_params, ) @@ -158,7 +145,7 @@ class WatsonxLLM(LM): project_id = watsonx_credentials.get("project_id", None) deployment_id = watsonx_credentials.get("deployment_id", None) client.set.default_project(project_id) - self.generate_params = generate_params or {} + self.generate_params = generate_params self.model = ModelInference( model_id=model_id, deployment_id=deployment_id, @@ -220,9 +207,9 @@ class WatsonxLLM(LM): """ Calculates the log likelihood of the generated tokens compared to the context tokens. Args: - input_tokens (List[dict[str, float]]): A List of token dictionaries, each containing + input_tokens (List[Dict[str, float]]): A List of token dictionaries, each containing token information like `text` and `logprob`. - context_tokens (List[dict[str, float]]): A List of token dictionaries representing + context_tokens (List[Dict[str, float]]): A List of token dictionaries representing the input context. Returns: LogLikelihoodResult: An object containing the calculated log likelihood and a boolean @@ -252,27 +239,24 @@ class WatsonxLLM(LM): Returns: List[str]: A List of generated responses. """ - requests = [request.args[0] for request in requests] + requests = [request.args for request in requests] results = [] - batch_size = 5 - for i in tqdm( - range(0, len(requests), batch_size), - desc=f"Running generate_until function with batch size {batch_size}", + for request in tqdm( + requests, + desc="Running generate_until function ...", ): - batch = requests[i : i + batch_size] + context, continuation = request try: - responses = self.model.generate_text(batch, self.generate_params) - + response = self.model.generate_text(context, self.generate_params) except Exception as exp: - eval_logger.error(f"Error while generating text {exp}") - continue - - for response, context in zip(responses, batch): - results.append(response) - self.cache_hook.add_partial("generated_text", context, response) + eval_logger.error("Error while generating text.") + raise exp - eval_logger.info("Cached responses") + results.append(response) + self.cache_hook.add_partial( + "generate_until", (context, continuation), response + ) return results @@ -284,7 +268,7 @@ class WatsonxLLM(LM): 2. a target string on which the loglikelihood of the LM producing this target, conditioned on the input, will be returned. Returns: - tuple (loglikelihood, is_greedy) for each request according to the input order: + Tuple (loglikelihood, is_greedy) for each request according to the input order: loglikelihood: probability of generating the target string conditioned on the input is_greedy: True if and only if the target string would be generated by greedy sampling from the LM """ @@ -295,54 +279,48 @@ class WatsonxLLM(LM): "Could not import ibm_watsonx_ai: Please install lm_eval[ibm_watsonx_ai] package." ) self._check_model_logprobs_support() - self.generate_params[GenParams.MAX_NEW_TOKENS] = 1 + generate_params = copy.copy(self.generate_params) + generate_params[GenParams.MAX_NEW_TOKENS] = 1 requests = [request.args for request in requests] results: List[LogLikelihoodResult] = [] - batch_size = 5 - for i in tqdm( - range(0, len(requests), batch_size), - desc=f"Running loglikelihood function with batch size {batch_size}", + # Note: We're not using batching due to (current) indeterminism of loglikelihood values when sending batch of requests + for request in tqdm( + requests, + desc="Running loglikelihood function ...", ): - batch = requests[i : i + batch_size] + context, continuation = request try: - tokenized_contexts = [ - self.model.tokenize(prompt=context, return_tokens=True)["result"][ - "tokens" - ] - for context, _ in batch - ] + tokenized_context = self.model.tokenize( + prompt=context, return_tokens=True + )["result"]["tokens"] except Exception as exp: - eval_logger.error(f"Error while model tokenize:\n {exp}") - continue + eval_logger.error("Error while model tokenize.") + raise exp - input_prompts = [context + continuation for context, continuation in batch] + input_prompt = context + continuation try: - responses = self.model.generate_text( - prompt=input_prompts, params=self.generate_params, raw_response=True + response = self.model.generate_text( + prompt=input_prompt, params=generate_params, raw_response=True ) except Exception as exp: - eval_logger.error(f"Error while model generate text:\n {exp}") - continue - - for response, tokenized_context, (context, continuation) in zip( - responses, tokenized_contexts, batch - ): - log_likelihood_response = self._get_log_likelihood( - response["results"][0]["input_tokens"], tokenized_context - ) - results.append(log_likelihood_response) - self.cache_hook.add_partial( - "loglikelihood", - (context, continuation), - ( - log_likelihood_response.log_likelihood, - log_likelihood_response.is_greedy, - ), - ) - eval_logger.info("Cached batch") + eval_logger.error("Error while model generate text.") + raise exp + + log_likelihood_response = self._get_log_likelihood( + response["results"][0]["input_tokens"], tokenized_context + ) + results.append(log_likelihood_response) + self.cache_hook.add_partial( + "loglikelihood", + (context, continuation), + ( + log_likelihood_response.log_likelihood, + log_likelihood_response.is_greedy, + ), + ) return cast(List[Tuple[float, bool]], results) @@ -350,10 +328,10 @@ class WatsonxLLM(LM): """ Used to evaluate perplexity on a data distribution. Args: - requests: Each request contains Instance.args : tuple[str] containing an input string to the model whose + requests: Each request contains Instance.args : Tuple[str] containing an input string to the model whose entire loglikelihood, conditioned on purely the EOT token, will be calculated. Returns: - tuple (loglikelihood,) for each request according to the input order: + Tuple (loglikelihood,) for each request according to the input order: loglikelihood: solely the probability of producing each piece of text given no starting input. """ try: @@ -363,47 +341,34 @@ class WatsonxLLM(LM): "Could not import ibm_watsonx_ai: Please install lm_eval[ibm_watsonx_ai] package." ) self._check_model_logprobs_support() - self.generate_params[GenParams.MAX_NEW_TOKENS] = 1 + generate_params = copy.deepcopy(self.generate_params) + generate_params[GenParams.MAX_NEW_TOKENS] = 1 - requests = [request.args[0] for request in requests] + requests = [request.args for request in requests] results: List[LogLikelihoodResult] = [] - batch_size = 5 - for i in tqdm( - range(0, len(requests), batch_size), - desc=f"Running loglikelihood_rolling function with batch size {batch_size}", + # Note: We're not using batching due to (current) indeterminism of loglikelihood values when sending batch of requests + for request in tqdm( + requests, + desc="Running loglikelihood_rolling function ...", ): - batch = requests[i : i + batch_size] - + context, continuation = request try: - responses = self.model.generate_text( - prompt=batch, params=self.generate_params, raw_response=True + response = self.model.generate_text( + prompt=context, params=generate_params, raw_response=True ) except Exception as exp: - eval_logger.error(f"Error while model generate text:\n {exp}") - continue - - for response, context in zip(responses, batch): - try: - log_likelihood_response = self._get_log_likelihood( - response["results"][0]["input_tokens"], [] - ) - results.append(log_likelihood_response) - - self.cache_hook.add_partial( - "loglikelihood_rolling", - context, - ( - log_likelihood_response.log_likelihood, - log_likelihood_response.is_greedy, - ), - ) - except Exception as exp: - eval_logger.error( - f"Error during log likelihood calculation:\n {exp}" - ) - continue - - eval_logger.info("Cached batch") + eval_logger.error("Error while model generate text.") + raise exp + + log_likelihood_response = self._get_log_likelihood( + response["results"][0]["input_tokens"], [] + ) + results.append(log_likelihood_response) + self.cache_hook.add_partial( + "loglikelihood_rolling", + (context, continuation), + log_likelihood_response.log_likelihood, + ) return cast(List[Tuple[float, bool]], results) diff --git a/pyproject.toml b/pyproject.toml index 79d3dc3d..19a9ca78 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -62,7 +62,7 @@ dev = ["pytest", "pytest-cov", "pytest-xdist", "pre-commit", "mypy"] deepsparse = ["deepsparse-nightly[llm]>=1.8.0.20240404"] gptq = ["auto-gptq[triton]>=0.6.0"] hf_transfer = ["hf_transfer"] -ibm_watsonx_ai = ["ibm_watsonx_ai"] +ibm_watsonx_ai = ["ibm_watsonx_ai>=1.1.22"] ifeval = ["langdetect", "immutabledict", "nltk>=3.9.1"] neuronx = ["optimum[neuronx]"] mamba = ["mamba_ssm", "causal-conv1d==1.0.2"] -- GitLab From e20e1ddc7963996d1c9310a7e880b5c17b54295d Mon Sep 17 00:00:00 2001 From: Oyvind Tafjord Date: Fri, 15 Nov 2024 11:29:51 -0800 Subject: [PATCH 156/194] Fix revision parameter to vllm get_tokenizer (#2492) --- lm_eval/models/vllm_causallms.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/models/vllm_causallms.py b/lm_eval/models/vllm_causallms.py index 0d8f3cea..b9ee6f92 100644 --- a/lm_eval/models/vllm_causallms.py +++ b/lm_eval/models/vllm_causallms.py @@ -118,7 +118,7 @@ class VLLM(TemplateLM): tokenizer if tokenizer else pretrained, tokenizer_mode=tokenizer_mode, trust_remote_code=trust_remote_code, - tokenizer_revision=tokenizer_revision, + revision=tokenizer_revision, ) self.tokenizer = configure_pad_token(self.tokenizer) self.add_bos_token = add_bos_token -- GitLab From badf273aa08c6d5b2d0b92e247f7b50aaa4fb6da Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Sat, 16 Nov 2024 12:42:14 +0000 Subject: [PATCH 157/194] update pre-commit hooks and git actions (#2497) * pre-commit update * update github actions * make logging less verbose * fix artifacts --- .github/workflows/new_tasks.yml | 4 ++-- .github/workflows/publish.yml | 8 ++++---- .github/workflows/unit_tests.yml | 10 ++-------- .pre-commit-config.yaml | 4 ++-- lm_eval/models/huggingface.py | 8 ++++---- 5 files changed, 14 insertions(+), 20 deletions(-) diff --git a/.github/workflows/new_tasks.yml b/.github/workflows/new_tasks.yml index b748aab5..dc598c55 100644 --- a/.github/workflows/new_tasks.yml +++ b/.github/workflows/new_tasks.yml @@ -16,7 +16,7 @@ jobs: name: Scan for changed tasks steps: - name: checkout - uses: actions/checkout@v3 + uses: actions/checkout@v4 with: fetch-depth: 2 # OR "2" -> To retrieve the preceding commit. @@ -47,7 +47,7 @@ jobs: - name: Set up Python 3.9 if: steps.changed-tasks.outputs.tasks_any_modified == 'true' || steps.changed-tasks.outputs.api_any_modified == 'true' - uses: actions/setup-python@v4 + uses: actions/setup-python@v5 with: python-version: 3.9 cache: 'pip' diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index be348175..8d0d386b 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -13,7 +13,7 @@ jobs: steps: - uses: actions/checkout@v4 - name: Set up Python - uses: actions/setup-python@v4 + uses: actions/setup-python@v5 with: python-version: "3.x" @@ -26,7 +26,7 @@ jobs: - name: Build a binary wheel and a source tarball run: python3 -m build - name: Store the distribution packages - uses: actions/upload-artifact@v3 + uses: actions/upload-artifact@v4 with: name: python-package-distributions path: dist/ @@ -46,7 +46,7 @@ jobs: steps: - name: Download all the dists - uses: actions/download-artifact@v3 + uses: actions/download-artifact@v4 with: name: python-package-distributions path: dist/ @@ -68,7 +68,7 @@ jobs: steps: - name: Download all the dists - uses: actions/download-artifact@v3 + uses: actions/download-artifact@v4 with: name: python-package-distributions path: dist/ diff --git a/.github/workflows/unit_tests.yml b/.github/workflows/unit_tests.yml index 49b85fb9..ed09225c 100644 --- a/.github/workflows/unit_tests.yml +++ b/.github/workflows/unit_tests.yml @@ -63,9 +63,9 @@ jobs: - name: Test with pytest run: python -m pytest --showlocals -s -vv -n=auto --ignore=tests/models/test_neuralmagic.py --ignore=tests/models/test_openvino.py - name: Archive artifacts - uses: actions/upload-artifact@v3 + uses: actions/upload-artifact@v4 with: - name: output_results + name: output_testcpu${{ matrix.python-version }} path: | test_logs/* testmodels: @@ -87,9 +87,3 @@ jobs: pip install -e '.[dev,optimum,deepsparse,sparseml,api]' --extra-index-url https://download.pytorch.org/whl/cpu - name: Test with pytest run: python -m pytest tests/models --showlocals -s -vv - - name: Archive artifacts - uses: actions/upload-artifact@v3 - with: - name: output_results - path: | - test_logs/* diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 5df94412..edeef333 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -2,7 +2,7 @@ exclude: ^tests/testdata/ repos: - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v4.6.0 + rev: v5.0.0 hooks: - id: check-added-large-files - id: check-ast @@ -29,7 +29,7 @@ repos: - id: mixed-line-ending args: [--fix=lf] - repo: https://github.com/astral-sh/ruff-pre-commit - rev: v0.6.8 + rev: v0.7.4 hooks: # Run the linter. - id: ruff diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 006f247c..dd04470c 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -464,7 +464,7 @@ class HFLM(TemplateLM): elif backend == "seq2seq": self.backend = backend eval_logger.info( - f"Overrode HF model backend type, and using type '{backend}'" + f"Overrode HF model backend type, and using type '{self.backend}'" ) else: # determine and use the default HF backend for this model, based on its config + metadata. @@ -476,12 +476,12 @@ class HFLM(TemplateLM): # models like MBart are listed in both seq2seq and causal mistakenly in HF transformers. # these special cases should be treated as seq2seq models. self.backend = "seq2seq" - eval_logger.info(f"Using model type '{backend}'") + eval_logger.debug(f"Using model type '{self.backend}'") elif ( getattr(self.config, "model_type") in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES ): self.backend = "causal" - eval_logger.info(f"Using model type '{backend}'") + eval_logger.debug(f"Using model type '{self.backend}'") else: if not trust_remote_code: eval_logger.warning( @@ -493,7 +493,7 @@ class HFLM(TemplateLM): # then we default to assuming AutoModelForCausalLM self.backend = "causal" eval_logger.info( - f"Model type cannot be determined. Using default model type '{backend}'" + f"Model type cannot be determined. Using default model type '{self.backend}'" ) if self.AUTO_MODEL_CLASS is None: -- GitLab From cbc31eb85edae8881d16b888f4f2a7c868e0c008 Mon Sep 17 00:00:00 2001 From: Wonseok Hwang Date: Sun, 17 Nov 2024 03:55:41 +0900 Subject: [PATCH 158/194] kbl-v0.1.1 (#2493) * release kbl-v0.1 * fix linting * remove rag tasks as doc_to_text functions cause trouble * remove remaining rag tasks * remove unnecessary repeat in yaml files and rag dataset in hf-hub * remove unncessary newline; introduce cfg files in lbox/kbl in hf * Make task yaml files consistent to hf-datasets-config * Make task yaml files consistent to hf-datasets-config * Remove trailing empty space in doc-to-text * Remove unncessary yaml file * Fix task nameing error * trailing space removed --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/kbl/README.md | 127 ++++++++++++++++++ .../tasks/kbl/bar_exam/civil/_base_em_yaml | 36 +++++ .../civil/kbl_bar_exam_em_civil_2012.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2013.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2014.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2015.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2016.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2017.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2018.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2019.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2020.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2021.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2022.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2023.yaml | 3 + .../civil/kbl_bar_exam_em_civil_2024.yaml | 3 + .../tasks/kbl/bar_exam/criminal/_base_em_yaml | 36 +++++ .../kbl_bar_exam_em_criminal_2012.yaml | 3 + .../kbl_bar_exam_em_criminal_2013.yaml | 3 + .../kbl_bar_exam_em_criminal_2014.yaml | 3 + .../kbl_bar_exam_em_criminal_2015.yaml | 3 + .../kbl_bar_exam_em_criminal_2016.yaml | 3 + .../kbl_bar_exam_em_criminal_2017.yaml | 3 + .../kbl_bar_exam_em_criminal_2018.yaml | 3 + .../kbl_bar_exam_em_criminal_2019.yaml | 3 + .../kbl_bar_exam_em_criminal_2020.yaml | 3 + .../kbl_bar_exam_em_criminal_2021.yaml | 3 + .../kbl_bar_exam_em_criminal_2022.yaml | 3 + .../kbl_bar_exam_em_criminal_2023.yaml | 3 + .../kbl_bar_exam_em_criminal_2024.yaml | 3 + .../tasks/kbl/bar_exam/public/_base_em_yaml | 36 +++++ .../public/kbl_bar_exam_em_public_2012.yaml | 3 + .../public/kbl_bar_exam_em_public_2013.yaml | 3 + .../public/kbl_bar_exam_em_public_2014.yaml | 3 + .../public/kbl_bar_exam_em_public_2015.yaml | 3 + .../public/kbl_bar_exam_em_public_2016.yaml | 3 + .../public/kbl_bar_exam_em_public_2017.yaml | 3 + .../public/kbl_bar_exam_em_public_2018.yaml | 3 + .../public/kbl_bar_exam_em_public_2019.yaml | 3 + .../public/kbl_bar_exam_em_public_2020.yaml | 3 + .../public/kbl_bar_exam_em_public_2021.yaml | 3 + .../public/kbl_bar_exam_em_public_2022.yaml | 3 + .../public/kbl_bar_exam_em_public_2023.yaml | 3 + .../public/kbl_bar_exam_em_public_2024.yaml | 3 + .../kbl/bar_exam/responsibility/_base_em_yaml | 34 +++++ .../kbl_bar_exam_em_responsibility_2010.yaml | 3 + .../kbl_bar_exam_em_responsibility_2011.yaml | 3 + .../kbl_bar_exam_em_responsibility_2012.yaml | 3 + .../kbl_bar_exam_em_responsibility_2013.yaml | 3 + .../kbl_bar_exam_em_responsibility_2014.yaml | 3 + .../kbl_bar_exam_em_responsibility_2015.yaml | 3 + .../kbl_bar_exam_em_responsibility_2016.yaml | 3 + .../kbl_bar_exam_em_responsibility_2017.yaml | 3 + .../kbl_bar_exam_em_responsibility_2018.yaml | 3 + .../kbl_bar_exam_em_responsibility_2019.yaml | 3 + .../kbl_bar_exam_em_responsibility_2020.yaml | 3 + .../kbl_bar_exam_em_responsibility_2021.yaml | 3 + .../kbl_bar_exam_em_responsibility_2022.yaml | 3 + .../kbl_bar_exam_em_responsibility_2023.yaml | 3 + .../tasks/kbl/knowledge/_kbl_knowledge_yaml | 20 +++ .../kbl_common_legal_mistake_qa_em.yaml | 4 + ..._common_legal_mistake_qa_reasoning_em.yaml | 4 + .../knowledge/kbl_legal_concept_qa_em.yaml | 4 + .../kbl_offense_component_qa_em.yaml | 4 + .../kbl_query_statute_matching_qa_em.yaml | 4 + .../kbl_statute_hallucination_qa_em.yaml | 4 + ...ute_number_and_content_matching_qa_em.yaml | 4 + .../tasks/kbl/reasoning/_kbl_reasoning_yaml | 19 +++ .../reasoning/kbl_case_relevance_qa_p_em.yaml | 5 + .../reasoning/kbl_case_relevance_qa_q_em.yaml | 5 + .../reasoning/kbl_causal_reasoning_em.yaml | 5 + .../kbl_statement_consistency_qa_em.yaml | 5 + 72 files changed, 516 insertions(+) create mode 100644 lm_eval/tasks/kbl/README.md create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/_base_em_yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2012.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2013.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2014.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2015.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2016.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2017.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2018.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2019.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2020.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2021.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2022.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2023.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2024.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/_base_em_yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2012.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2013.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2014.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2015.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2016.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2017.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2018.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2019.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2020.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2021.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2022.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2023.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2024.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/_base_em_yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2012.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2013.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2014.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2015.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2016.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2017.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2018.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2019.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2020.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2021.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2022.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2023.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2024.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/_base_em_yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2010.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2011.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2012.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2013.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2014.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2015.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2016.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2017.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2018.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2019.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2020.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2021.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2022.yaml create mode 100644 lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2023.yaml create mode 100644 lm_eval/tasks/kbl/knowledge/_kbl_knowledge_yaml create mode 100644 lm_eval/tasks/kbl/knowledge/kbl_common_legal_mistake_qa_em.yaml create mode 100644 lm_eval/tasks/kbl/knowledge/kbl_common_legal_mistake_qa_reasoning_em.yaml create mode 100644 lm_eval/tasks/kbl/knowledge/kbl_legal_concept_qa_em.yaml create mode 100644 lm_eval/tasks/kbl/knowledge/kbl_offense_component_qa_em.yaml create mode 100644 lm_eval/tasks/kbl/knowledge/kbl_query_statute_matching_qa_em.yaml create mode 100644 lm_eval/tasks/kbl/knowledge/kbl_statute_hallucination_qa_em.yaml create mode 100644 lm_eval/tasks/kbl/knowledge/kbl_statute_number_and_content_matching_qa_em.yaml create mode 100644 lm_eval/tasks/kbl/reasoning/_kbl_reasoning_yaml create mode 100644 lm_eval/tasks/kbl/reasoning/kbl_case_relevance_qa_p_em.yaml create mode 100644 lm_eval/tasks/kbl/reasoning/kbl_case_relevance_qa_q_em.yaml create mode 100644 lm_eval/tasks/kbl/reasoning/kbl_causal_reasoning_em.yaml create mode 100644 lm_eval/tasks/kbl/reasoning/kbl_statement_consistency_qa_em.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 5c1fc627..f9b37bb9 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -56,6 +56,7 @@ | [ifeval](ifeval/README.md) | Interactive fiction evaluation tasks for narrative understanding and reasoning. | English | | [inverse_scaling](inverse_scaling/README.md) | Multiple-choice tasks from the Inverse Scaling Prize, designed to find settings where larger language models perform worse. | English | | [japanese_leaderboard](japanese_leaderboard/README.md) | Japanese language understanding tasks to benchmark model performance on various linguistic aspects. | Japanese | +| [kbl](kbl/README.md) | Korean Benchmark for Legal Language Understanding. | Korean | | [kmmlu](kmmlu/README.md) | Knowledge-based multi-subject multiple choice questions for academic evaluation. | Korean | | [kobest](kobest/README.md) | A collection of tasks designed to evaluate understanding in Korean language. | Korean | | [kormedmcqa](kormedmcqa/README.md) | Medical question answering tasks in Korean to test specialized domain knowledge. | Korean | diff --git a/lm_eval/tasks/kbl/README.md b/lm_eval/tasks/kbl/README.md new file mode 100644 index 00000000..c415a1d5 --- /dev/null +++ b/lm_eval/tasks/kbl/README.md @@ -0,0 +1,127 @@ +# kbl + +### Paper + +Title: `Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models` + +Abstract: `Large language models (LLMs) have demonstrated remarkable performance in the legal domain, with GPT-4 even passing the Uniform Bar Exam in the U.S. However their efficacy remains limited for non-standardized tasks and tasks in languages other than English. This underscores the need for careful evaluation of LLMs within each legal system before application. Here, we introduce KBL, a benchmark for assessing the Korean legal language understanding of LLMs, consisting of (1) 7 legal knowledge tasks (510 examples), (2) 4 legal reasoning tasks (288 examples), and (3) the Korean bar exam (4 domains, 53 tasks, 2,510 examples). First two datasets were developed in close collaboration with lawyers to evaluate LLMs in practical scenarios in a certified manner. Furthermore, considering legal practitioners' frequent use of extensive legal documents for research, we assess LLMs in both a closed book setting, where they rely solely on internal knowledge, and a retrieval-augmented generation (RAG) setting, using a corpus of Korean statutes and precedents. The results indicate substantial room and opportunities for improvement.` + +`Korean Benchmark for Legal Language Understanding` + +Homepage: `https://github.com/lbox-kr/kbl` + + +### Citation + +``` +@inproceedings{kim2024kbl, + title = "Developing a Pragmatic Benchmark for Assessing {K}orean Legal Language Understanding in Large Language Models", + author = {Yeeun Kim and Young Rok Choi and Eunkyung Choi and Jinhwan Choi and Hai Jin Park and Wonseok Hwang}, + editor = "Al-Onaizan, Yaser and + Bansal, Mohit and + Chen, Yun-Nung", + booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024", + month = nov, + year = "2024", + address = "Miami, Florida, USA", + publisher = "Association for Computational Linguistics", + url = "https://aclanthology.org/2024.findings-emnlp.319", + pages = "5573--5595", +} +``` + +### Groups, Tags, and Tasks + +#### Groups + +#### Tags + +* `kbl`: `All kbl tasks (7 knowledge, 4 reasoning, and 39 bar exam)` +* `kbl_knowledge_em`: `7 knowledge tasks` +* `kbl_reasoning_em`: `4 reasoning tasks` +* `kbl_bar_exam_em`: `53 bar exam tasks` +* `kbl_bar_exam_em_civil`: `13 bar exam tasks, civil law` +* `kbl_bar_exam_em_criminal`: `13 bar exam tasks, criminal law` +* `kbl_bar_exam_em_public`: `13 bar exam tasks, public law` +* `kbl_bar_exam_em_responsibility`: `14 bar exam tasks, professional responsibility (RESP) examination` + + +#### Tasks + +* `kbl_common_legal_mistake_qa_em`: `A QA task evaluating common legal misconceptions from the general public.` +* `kbl_knowledge_common_legal_mistake_qa_reasoning`: `Similar to 'kbl_common_legal_mistake_qa_em' but the answers are presented with correct/wrong rationals.` +* `kbl_knowledge_legal_concept_qa`: `A QA task addressing knowledge about complex legal concepts (legal terms).` +* `kbl_knowledge_offense_component_qa`: `A QA task evaluating whether a model knows specific actions meet the actual elements of a criminal offense.` +* `kbl_knowledge_query_and_statute_matching_qa`: `A QA task assessing whether the language model can accurately identify the relevant statute for a given query.` +* `kbl_knowledge_statute_hallucination_qa`: `A QA task evaluating whether a model can select the correct answer consists of a pair of (fictitious) statute and corresponding reasoning for given confusing legal questions.` +* `kbl_knowledge_statute_number_and_content_matching_qa`: `A QA dataset for evaluating where a model can accurately match the content of a law to its specific statute number.` +* `kbl_reasoning_case_relevance_qa_p`: `A QA task where a model needs to determine whether a given precedent is relavent to an input precedent.` +* `kbl_reasoning_case_relevance_qa_q`: `A QA task where a model needs to determine whether a given precedent is relavent to an input query.` +* `kbl_reasoning_causal_reasoning_qa`: `A QA task where a model needs to assess whether the defendant’s actions were the direct and decisive cause of the victim’s injury or death for each given factual description and claims.` +* `kbl_reasoning_statement_consistency_qa`: `A QA task where a model is required to accurately determine whether two presented statements are consistent with each other.` +* `bar_exam_civil_2012`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2013`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2014`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2015`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2016`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2017`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2018`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2019`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2020`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2021`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2022`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2023`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_civil_2024`: `Korean bar exam multiple-choice questions, civil law` +* `bar_exam_criminal_2012`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2013`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2014`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2015`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2016`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2017`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2018`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2019`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2020`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2021`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2022`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2023`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_criminal_2024`: `Korean bar exam multiple-choice questions, criminal law` +* `bar_exam_public_2012`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2013`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2014`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2015`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2016`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2017`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2018`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2019`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2020`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2021`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2022`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2023`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_public_2024`: `Korean bar exam multiple-choice questions, public law` +* `bar_exam_responsibility_2010`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2011`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2012`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2013`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2014`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2015`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2016`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2017`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2018`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2019`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2020`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2021`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2022`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` +* `bar_exam_responsibility_2023`: `Korean bar exam multiple-choice questions, professional responsibility (RESP) examination` + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [ ] Is the task an existing benchmark in the literature? + * [ ] Have you referenced the original paper that introduced the task? + * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [ ] Is the "Main" variant of this task clearly denoted? +* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [ ] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/kbl/bar_exam/civil/_base_em_yaml b/lm_eval/tasks/kbl/bar_exam/civil/_base_em_yaml new file mode 100644 index 00000000..5c1f854c --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/_base_em_yaml @@ -0,0 +1,36 @@ +tag: + - kbl + - kbl_bar_exam_em + - kbl_bar_exam_em_civil +description: '당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n' +dataset_path: lbox/kbl +test_split: test +output_type: generate_until +doc_to_text: '### 질문: {{question}} + + 다음 각 선택지를 읽고 A, B, C, D, E 중 하나를 선택하여 ''답변: A'' 와 같이 단답식으로 답해 주세요. + + A. {{A}} + + B. {{B}} + + C. {{C}} + + D. {{D}} + + E. {{E}} + + ### 답변:' +doc_to_target: gt +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: true +filter_list: + - name: get-answer + filter: + - function: regex + regex_pattern: ([A-E]).* + - function: take_first diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2012.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2012.yaml new file mode 100644 index 00000000..1fb6a29d --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2012.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2012 +dataset_name: bar_exam_civil_2012 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2013.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2013.yaml new file mode 100644 index 00000000..a7a8b537 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2013.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2013 +dataset_name: bar_exam_civil_2013 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2014.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2014.yaml new file mode 100644 index 00000000..a39f31cd --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2014.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2014 +dataset_name: bar_exam_civil_2014 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2015.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2015.yaml new file mode 100644 index 00000000..b3fe7ec8 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2015.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2015 +dataset_name: bar_exam_civil_2015 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2016.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2016.yaml new file mode 100644 index 00000000..26f040c0 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2016.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2016 +dataset_name: bar_exam_civil_2016 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2017.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2017.yaml new file mode 100644 index 00000000..e8eedd67 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2017.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2017 +dataset_name: bar_exam_civil_2017 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2018.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2018.yaml new file mode 100644 index 00000000..39f90480 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2018.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2018 +dataset_name: bar_exam_civil_2018 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2019.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2019.yaml new file mode 100644 index 00000000..ac9bd318 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2019.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2019 +dataset_name: bar_exam_civil_2019 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2020.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2020.yaml new file mode 100644 index 00000000..89ff7274 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2020.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2020 +dataset_name: bar_exam_civil_2020 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2021.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2021.yaml new file mode 100644 index 00000000..ee77cdfd --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2021.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2021 +dataset_name: bar_exam_civil_2021 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2022.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2022.yaml new file mode 100644 index 00000000..036c7955 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2022.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2022 +dataset_name: bar_exam_civil_2022 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2023.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2023.yaml new file mode 100644 index 00000000..47342239 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2023.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2023 +dataset_name: bar_exam_civil_2023 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2024.yaml b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2024.yaml new file mode 100644 index 00000000..5199d594 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/civil/kbl_bar_exam_em_civil_2024.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_civil_2024 +dataset_name: bar_exam_civil_2024 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/_base_em_yaml b/lm_eval/tasks/kbl/bar_exam/criminal/_base_em_yaml new file mode 100644 index 00000000..b170dad7 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/_base_em_yaml @@ -0,0 +1,36 @@ +tag: + - kbl + - kbl_bar_exam_em + - kbl_bar_exam_em_criminal +description: '당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n' +dataset_path: lbox/kbl +test_split: test +output_type: generate_until +doc_to_text: '### 질문: {{question}} + + 다음 각 선택지를 읽고 A, B, C, D, E 중 하나를 선택하여 ''답변: A'' 와 같이 단답식으로 답해 주세요. + + A. {{A}} + + B. {{B}} + + C. {{C}} + + D. {{D}} + + E. {{E}} + + ### 답변:' +doc_to_target: gt +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: true +filter_list: + - name: get-answer + filter: + - function: regex + regex_pattern: ([A-E]).* + - function: take_first diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2012.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2012.yaml new file mode 100644 index 00000000..79b81927 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2012.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2012 +dataset_name: bar_exam_criminal_2012 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2013.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2013.yaml new file mode 100644 index 00000000..6161688e --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2013.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2013 +dataset_name: bar_exam_criminal_2013 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2014.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2014.yaml new file mode 100644 index 00000000..dddb9ce2 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2014.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2014 +dataset_name: bar_exam_criminal_2014 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2015.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2015.yaml new file mode 100644 index 00000000..db760742 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2015.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2015 +dataset_name: bar_exam_criminal_2015 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2016.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2016.yaml new file mode 100644 index 00000000..d668b783 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2016.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2016 +dataset_name: bar_exam_criminal_2016 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2017.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2017.yaml new file mode 100644 index 00000000..a6e0b81c --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2017.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2017 +dataset_name: bar_exam_criminal_2017 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2018.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2018.yaml new file mode 100644 index 00000000..bd1f6aa7 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2018.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2018 +dataset_name: bar_exam_criminal_2018 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2019.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2019.yaml new file mode 100644 index 00000000..e5de46ba --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2019.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2019 +dataset_name: bar_exam_criminal_2019 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2020.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2020.yaml new file mode 100644 index 00000000..217c6783 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2020.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2020 +dataset_name: bar_exam_criminal_2020 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2021.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2021.yaml new file mode 100644 index 00000000..e4527ba0 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2021.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2021 +dataset_name: bar_exam_criminal_2021 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2022.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2022.yaml new file mode 100644 index 00000000..6191c517 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2022.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2022 +dataset_name: bar_exam_criminal_2022 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2023.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2023.yaml new file mode 100644 index 00000000..5b953dfb --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2023.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2023 +dataset_name: bar_exam_criminal_2023 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2024.yaml b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2024.yaml new file mode 100644 index 00000000..232e77b2 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/criminal/kbl_bar_exam_em_criminal_2024.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_criminal_2024 +dataset_name: bar_exam_criminal_2024 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/_base_em_yaml b/lm_eval/tasks/kbl/bar_exam/public/_base_em_yaml new file mode 100644 index 00000000..f66d3829 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/_base_em_yaml @@ -0,0 +1,36 @@ +tag: + - kbl + - kbl_bar_exam_em + - kbl_bar_exam_em_public +description: '당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n' +dataset_path: lbox/kbl +test_split: test +output_type: generate_until +doc_to_text: '### 질문: {{question}} + + 다음 각 선택지를 읽고 A, B, C, D, E 중 하나를 선택하여 ''답변: A'' 와 같이 단답식으로 답해 주세요. + + A. {{A}} + + B. {{B}} + + C. {{C}} + + D. {{D}} + + E. {{E}} + + ### 답변:' +doc_to_target: gt +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: true +filter_list: + - name: get-answer + filter: + - function: regex + regex_pattern: ([A-E]).* + - function: take_first diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2012.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2012.yaml new file mode 100644 index 00000000..63c678ec --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2012.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2012 +dataset_name: bar_exam_public_2012 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2013.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2013.yaml new file mode 100644 index 00000000..2af467a4 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2013.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2013 +dataset_name: bar_exam_public_2013 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2014.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2014.yaml new file mode 100644 index 00000000..0392f439 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2014.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2014 +dataset_name: bar_exam_public_2014 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2015.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2015.yaml new file mode 100644 index 00000000..6482777c --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2015.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2015 +dataset_name: bar_exam_public_2015 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2016.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2016.yaml new file mode 100644 index 00000000..024b706e --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2016.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2016 +dataset_name: bar_exam_public_2016 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2017.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2017.yaml new file mode 100644 index 00000000..50d172ba --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2017.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2017 +dataset_name: bar_exam_public_2017 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2018.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2018.yaml new file mode 100644 index 00000000..47341011 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2018.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2018 +dataset_name: bar_exam_public_2018 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2019.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2019.yaml new file mode 100644 index 00000000..2d20fd47 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2019.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2019 +dataset_name: bar_exam_public_2019 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2020.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2020.yaml new file mode 100644 index 00000000..5af0189c --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2020.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2020 +dataset_name: bar_exam_public_2020 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2021.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2021.yaml new file mode 100644 index 00000000..02040f84 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2021.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2021 +dataset_name: bar_exam_public_2021 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2022.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2022.yaml new file mode 100644 index 00000000..00ec949c --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2022.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2022 +dataset_name: bar_exam_public_2022 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2023.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2023.yaml new file mode 100644 index 00000000..27f8c4c7 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2023.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2023 +dataset_name: bar_exam_public_2023 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2024.yaml b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2024.yaml new file mode 100644 index 00000000..bdf0d9bf --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/public/kbl_bar_exam_em_public_2024.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_public_2024 +dataset_name: bar_exam_public_2024 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/_base_em_yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/_base_em_yaml new file mode 100644 index 00000000..14350b04 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/_base_em_yaml @@ -0,0 +1,34 @@ +tag: + - kbl + - kbl_bar_exam_em + - kbl_bar_exam_em_responsibility +description: '당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n' +dataset_path: lbox/kbl +test_split: test +output_type: generate_until +doc_to_text: '### 질문: {{question}} + + 다음 각 선택지를 읽고 A, B, C, D 중 하나를 선택하여 ''답변: A'' 와 같이 단답식으로 답해 주세요. + + A. {{A}} + + B. {{B}} + + C. {{C}} + + D. {{D}} + + ### 답변:' +doc_to_target: gt +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: true +filter_list: + - name: get-answer + filter: + - function: regex + regex_pattern: ([A-D]).* + - function: take_first diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2010.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2010.yaml new file mode 100644 index 00000000..11efbd5c --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2010.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2010 +dataset_name: bar_exam_responsibility_2010 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2011.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2011.yaml new file mode 100644 index 00000000..dd75d003 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2011.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2011 +dataset_name: bar_exam_responsibility_2011 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2012.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2012.yaml new file mode 100644 index 00000000..79af22f1 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2012.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2012 +dataset_name: bar_exam_responsibility_2012 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2013.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2013.yaml new file mode 100644 index 00000000..0d276113 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2013.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2013 +dataset_name: bar_exam_responsibility_2013 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2014.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2014.yaml new file mode 100644 index 00000000..c14782c9 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2014.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2014 +dataset_name: bar_exam_responsibility_2014 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2015.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2015.yaml new file mode 100644 index 00000000..4dcf1736 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2015.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2015 +dataset_name: bar_exam_responsibility_2015 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2016.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2016.yaml new file mode 100644 index 00000000..acd2a118 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2016.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2016 +dataset_name: bar_exam_responsibility_2016 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2017.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2017.yaml new file mode 100644 index 00000000..633381fc --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2017.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2017 +dataset_name: bar_exam_responsibility_2017 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2018.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2018.yaml new file mode 100644 index 00000000..6d11eeb2 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2018.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2018 +dataset_name: bar_exam_responsibility_2018 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2019.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2019.yaml new file mode 100644 index 00000000..3cd224f7 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2019.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2019 +dataset_name: bar_exam_responsibility_2019 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2020.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2020.yaml new file mode 100644 index 00000000..8519c2b4 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2020.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2020 +dataset_name: bar_exam_responsibility_2020 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2021.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2021.yaml new file mode 100644 index 00000000..0ecff28a --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2021.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2021 +dataset_name: bar_exam_responsibility_2021 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2022.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2022.yaml new file mode 100644 index 00000000..1e23b221 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2022.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2022 +dataset_name: bar_exam_responsibility_2022 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2023.yaml b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2023.yaml new file mode 100644 index 00000000..1d78c711 --- /dev/null +++ b/lm_eval/tasks/kbl/bar_exam/responsibility/kbl_bar_exam_em_responsibility_2023.yaml @@ -0,0 +1,3 @@ +task: kbl_bar_exam_em_responsibility_2023 +dataset_name: bar_exam_responsibility_2023 +include: _base_em_yaml diff --git a/lm_eval/tasks/kbl/knowledge/_kbl_knowledge_yaml b/lm_eval/tasks/kbl/knowledge/_kbl_knowledge_yaml new file mode 100644 index 00000000..3d6ce3ef --- /dev/null +++ b/lm_eval/tasks/kbl/knowledge/_kbl_knowledge_yaml @@ -0,0 +1,20 @@ +tag: + - kbl + - kbl_knowledge_em +description: '당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n' +dataset_path: lbox/kbl +test_split: test +output_type: generate_until +doc_to_target: "{{label}}" +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: true +filter_list: + - name: "get-answer" + filter: + - function: "regex" + regex_pattern: "([A-E]).*" + - function: "take_first" diff --git a/lm_eval/tasks/kbl/knowledge/kbl_common_legal_mistake_qa_em.yaml b/lm_eval/tasks/kbl/knowledge/kbl_common_legal_mistake_qa_em.yaml new file mode 100644 index 00000000..a768bd4e --- /dev/null +++ b/lm_eval/tasks/kbl/knowledge/kbl_common_legal_mistake_qa_em.yaml @@ -0,0 +1,4 @@ +task: kbl_common_legal_mistake_qa_em +dataset_name: kbl_knowledge_common_legal_mistake_qa +doc_to_text: "### 질문: {{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\n'A', 'B', 'C' 중 하나를 선택하여 ''답변: A'' 와 같이 단답식으로 답해 주세요." +include: _kbl_knowledge_yaml diff --git a/lm_eval/tasks/kbl/knowledge/kbl_common_legal_mistake_qa_reasoning_em.yaml b/lm_eval/tasks/kbl/knowledge/kbl_common_legal_mistake_qa_reasoning_em.yaml new file mode 100644 index 00000000..338a0b51 --- /dev/null +++ b/lm_eval/tasks/kbl/knowledge/kbl_common_legal_mistake_qa_reasoning_em.yaml @@ -0,0 +1,4 @@ +task: kbl_common_legal_mistake_qa_reasoning_em +dataset_name: kbl_knowledge_common_legal_mistake_qa_reasoning +doc_to_text: "### 질문: {{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\n'A', 'B', 'C' 중 하나를 선택하여 ''답변: A'' 와 같이 단답식으로 답해 주세요." +include: _kbl_knowledge_yaml diff --git a/lm_eval/tasks/kbl/knowledge/kbl_legal_concept_qa_em.yaml b/lm_eval/tasks/kbl/knowledge/kbl_legal_concept_qa_em.yaml new file mode 100644 index 00000000..d7d758cb --- /dev/null +++ b/lm_eval/tasks/kbl/knowledge/kbl_legal_concept_qa_em.yaml @@ -0,0 +1,4 @@ +task: kbl_legal_concept_qa_em +dataset_name: kbl_knowledge_legal_concept_qa +doc_to_text: "### 질문: {{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nE. {{E}}\n'A', 'B', 'C', 'D', 'E' 중 하나를 선택하여 ''답변: A'' 와 같이 단답식으로 답해 주세요." +include: _kbl_knowledge_yaml diff --git a/lm_eval/tasks/kbl/knowledge/kbl_offense_component_qa_em.yaml b/lm_eval/tasks/kbl/knowledge/kbl_offense_component_qa_em.yaml new file mode 100644 index 00000000..62132ddd --- /dev/null +++ b/lm_eval/tasks/kbl/knowledge/kbl_offense_component_qa_em.yaml @@ -0,0 +1,4 @@ +task: kbl_offense_component_qa_em +dataset_name: kbl_knowledge_offense_component_qa +doc_to_text: "### 질문: {{question}}\n다음 각 선택지를 읽고 선택지 중 하나를 골라 ''답변: A'' 와 같이 단답식으로 답해 주세요. ### 선택지: A. {{A}}\nB. {{B}}." +include: _kbl_knowledge_yaml diff --git a/lm_eval/tasks/kbl/knowledge/kbl_query_statute_matching_qa_em.yaml b/lm_eval/tasks/kbl/knowledge/kbl_query_statute_matching_qa_em.yaml new file mode 100644 index 00000000..551b6328 --- /dev/null +++ b/lm_eval/tasks/kbl/knowledge/kbl_query_statute_matching_qa_em.yaml @@ -0,0 +1,4 @@ +task: kbl_query_and_statute_matching_qa_em +dataset_name: kbl_knowledge_query_and_statute_matching_qa +doc_to_text: "### 질문: {{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nE. {{E}}\nA, B, C, D, E 중 하나를 선택하여 ''답변: A'' 와 같이 단답식으로 답해 주세요." +include: _kbl_knowledge_yaml diff --git a/lm_eval/tasks/kbl/knowledge/kbl_statute_hallucination_qa_em.yaml b/lm_eval/tasks/kbl/knowledge/kbl_statute_hallucination_qa_em.yaml new file mode 100644 index 00000000..efa5082f --- /dev/null +++ b/lm_eval/tasks/kbl/knowledge/kbl_statute_hallucination_qa_em.yaml @@ -0,0 +1,4 @@ +task: kbl_statute_hallucination_qa_em +dataset_name: kbl_knowledge_statute_hallucination_qa +doc_to_text: "### 질문: {{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n'A', 'B', 'C', 'D' 중 하나를 선택하여 ''답변: A'' 와 같이 단답식으로 답해 주세요." +include: _kbl_knowledge_yaml diff --git a/lm_eval/tasks/kbl/knowledge/kbl_statute_number_and_content_matching_qa_em.yaml b/lm_eval/tasks/kbl/knowledge/kbl_statute_number_and_content_matching_qa_em.yaml new file mode 100644 index 00000000..d16a1978 --- /dev/null +++ b/lm_eval/tasks/kbl/knowledge/kbl_statute_number_and_content_matching_qa_em.yaml @@ -0,0 +1,4 @@ +task: kbl_statute_number_and_content_matching_qa_em +dataset_name: kbl_knowledge_statute_number_and_content_matching_qa +doc_to_text: "### 질문: {{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nE. {{E}}\n A, B, C, D, E 중 하나를 선택하여 ''답변: A'' 와 같이 단답식으로 답해 주세요." +include: _kbl_knowledge_yaml diff --git a/lm_eval/tasks/kbl/reasoning/_kbl_reasoning_yaml b/lm_eval/tasks/kbl/reasoning/_kbl_reasoning_yaml new file mode 100644 index 00000000..6ef129c6 --- /dev/null +++ b/lm_eval/tasks/kbl/reasoning/_kbl_reasoning_yaml @@ -0,0 +1,19 @@ +tag: + - kbl + - kbl_reasoning_em +description: '당신은 사용자의 질문에 친절하고 논리적으로 답변해 주는 법률 전문가 챗봇 입니다.\n' +dataset_path: lbox/kbl +test_split: test +output_type: generate_until +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: false +filter_list: + - name: "get-answer" + filter: + - function: "regex" + regex_pattern: "([A-E]).*" + - function: "take_first" diff --git a/lm_eval/tasks/kbl/reasoning/kbl_case_relevance_qa_p_em.yaml b/lm_eval/tasks/kbl/reasoning/kbl_case_relevance_qa_p_em.yaml new file mode 100644 index 00000000..0e416666 --- /dev/null +++ b/lm_eval/tasks/kbl/reasoning/kbl_case_relevance_qa_p_em.yaml @@ -0,0 +1,5 @@ +task: kbl_case_relevance_qa_p_em +dataset_name: kbl_reasoning_case_relevance_qa_p +doc_to_text: "### 질문: {{question}}\n\n[첫번째 판결문 상고인]\n{{query_case_appellant}}\n[첫번째 판결문 사실관계]\n{{query_case_fact}}\n[첫번째 판결문 당사자들의 주장]\n{{query_case_claim}}\n[첫번째 판결문 판사의 의견]\n{{query_case_judicial_opinion}}\n\n[두번째 판결문 상고인]\n{{retrieved_case_appellant}}\n[두번째 판결문 사실관계]\n{{retrieved_case_fact}}\n[두번째 판결문 당사자들의 주장]\n{{retrieved_case_claim}}\n[두번째 판결문 판사의 의견]\n{{retrieved_case_judicial_opinion}}\n\nA: {{A}}, B: {{B}}\n중 하나를 선택하여 '답변: A'과 같이 단답식으로 답해주세요." +doc_to_target: "{{label}}" +include: _kbl_reasoning_yaml diff --git a/lm_eval/tasks/kbl/reasoning/kbl_case_relevance_qa_q_em.yaml b/lm_eval/tasks/kbl/reasoning/kbl_case_relevance_qa_q_em.yaml new file mode 100644 index 00000000..170a22af --- /dev/null +++ b/lm_eval/tasks/kbl/reasoning/kbl_case_relevance_qa_q_em.yaml @@ -0,0 +1,5 @@ +task: kbl_case_relevance_qa_q_em +dataset_name: kbl_reasoning_case_relevance_qa_q +doc_to_text: "### 질문: {{question}}\n[의뢰인의 주장]\n{{query}}\n\n[판결문]\n- 상고인\n{{retrieved_case_appellant}}\n- 사실관계\n{{retrieved_case_fact}}\n- 당사자들의 주장\n{{retrieved_case_claim}}\n- 판사의 의견\n{{retrieved_case_judicial_opinion}}\n\nA: {{A}}, B: {{B}}\n중 하나를 선택하여 '답변: A'과 같이 단답식으로 답해주세요." +doc_to_target: "{{label}}" +include: _kbl_reasoning_yaml diff --git a/lm_eval/tasks/kbl/reasoning/kbl_causal_reasoning_em.yaml b/lm_eval/tasks/kbl/reasoning/kbl_causal_reasoning_em.yaml new file mode 100644 index 00000000..8b65dd92 --- /dev/null +++ b/lm_eval/tasks/kbl/reasoning/kbl_causal_reasoning_em.yaml @@ -0,0 +1,5 @@ +task: kbl_causal_reasoning_qa_em +dataset_name: kbl_reasoning_causal_reasoning_qa +doc_to_text: "### 질문: {{question}}\n검사의 공소사실: {{facts_charged}}\n피고인의 주장: {{defendant_claim}}\n증거: {{facts_accepted}}\nX, Y를 각각\nX: {{cause}})\nY: {{effect}}\n라고 할 때 X와 Y 사이의 관계를\nA: {{A}}, B: {{B}}\n중 하나를 선택하여 '답변: A'과 같이 단답식으로 답해주세요." +doc_to_target: label +include: _kbl_reasoning_yaml diff --git a/lm_eval/tasks/kbl/reasoning/kbl_statement_consistency_qa_em.yaml b/lm_eval/tasks/kbl/reasoning/kbl_statement_consistency_qa_em.yaml new file mode 100644 index 00000000..56eeb063 --- /dev/null +++ b/lm_eval/tasks/kbl/reasoning/kbl_statement_consistency_qa_em.yaml @@ -0,0 +1,5 @@ +task: kbl_statement_consistency_qa_em +dataset_name: kbl_reasoning_statement_consistency_qa +doc_to_text: "### 질문: {{question}}\n진술1: {{statement1}}\n진술2: {{statement2}}\nA: {{A}}, B: {{B}}\n중 하나를 선택하여 '답변: A'과 같이 단답식으로 답해주세요." +doc_to_target: label +include: _kbl_reasoning_yaml -- GitLab From 0f5dc2655dc40e1e0d78b3b7691966dbe367aaf5 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 18 Nov 2024 13:23:57 +0000 Subject: [PATCH 159/194] Add mamba hf to `mamba_ssm` (#2496) * add hf mamba to mamba_lm * fix _model_generate for hf --- lm_eval/models/mamba_lm.py | 105 +++++++++++++++++++++++++------------ 1 file changed, 72 insertions(+), 33 deletions(-) diff --git a/lm_eval/models/mamba_lm.py b/lm_eval/models/mamba_lm.py index 47a241f0..5f3da695 100644 --- a/lm_eval/models/mamba_lm.py +++ b/lm_eval/models/mamba_lm.py @@ -12,6 +12,8 @@ class MambaLMWrapper(HFLM): def __init__( self, pretrained="state-spaces/mamba-130m", + # To use the HF compatible variant + is_hf: bool = False, **kwargs, ) -> None: """ @@ -52,7 +54,7 @@ class MambaLMWrapper(HFLM): if "backend" in kwargs: # mamba currently only supports causal models assert kwargs["backend"] == "causal" - + self.is_hf = is_hf or (True if pretrained.endswith("hf") else False) super().__init__( pretrained=pretrained, # set appropriate defaults for tokenizer, max length, etc @@ -67,15 +69,18 @@ class MambaLMWrapper(HFLM): pretrained: str, **kwargs, ) -> None: - try: - from mamba_ssm.utils.hf import load_config_hf # noqa: F811 - except ModuleNotFoundError as exception: - raise type(exception)( - "attempted to use 'mamba_ssm' LM type, but package `mamba_ssm` is not installed. \ -please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba]`", - ) - - self._config = load_config_hf(pretrained) + if self.is_hf: + super()._get_config(pretrained, **kwargs) + else: + try: + from mamba_ssm.utils.hf import load_config_hf # noqa: F811 + except ModuleNotFoundError as exception: + raise type(exception)( + "attempted to use 'mamba_ssm' LM type, but package `mamba_ssm` is not installed. \ + please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba]`", + ) + + self._config = load_config_hf(pretrained) def _create_model( self, @@ -86,24 +91,32 @@ please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba # Mamba does not support arbitrary HF from_pretrained() args **kwargs, ) -> None: - try: - from mamba_ssm.models.mixer_seq_simple import MambaLMHeadModel # noqa: F811 - except ModuleNotFoundError as exception: - raise type(exception)( - "attempted to use 'mamba_ssm' LM type, but package `mamba_ssm` is not installed. \ -please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba]`", + if self.is_hf: + super()._create_model(pretrained, dtype=dtype, **kwargs) + else: + try: + from mamba_ssm.models.mixer_seq_simple import ( + MambaLMHeadModel, # noqa: F811 + ) + except ModuleNotFoundError as exception: + raise type(exception)( + "attempted to use 'mamba_ssm' LM type, but package `mamba_ssm` is not installed. \ + please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba]`", + ) + + self._model = MambaLMHeadModel.from_pretrained( + pretrained, + device=self._device, + dtype=torch.float16 + if dtype == "auto" + else lm_eval.models.utils.get_dtype(dtype), ) - self._model = MambaLMHeadModel.from_pretrained( - pretrained, - device=self._device, - dtype=torch.float16 - if dtype == "auto" - else lm_eval.models.utils.get_dtype(dtype), - ) - def _model_generate(self, context, max_length, stop, **generation_kwargs): - for key in ("do_sample", "attention_mask"): + remove_arg = ( + ["attention_mask"] if self.is_hf else ["do_sample", "attention_mask"] + ) + for key in remove_arg: if key in generation_kwargs: generation_kwargs.pop(key) @@ -116,11 +129,37 @@ please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba # self.tokenizer, stop, 1, context.shape[0] # ) - return self.model.generate( - input_ids=context, - max_length=max_length, - # stopping_criteria=stopping_criteria, - # pad_token_id=self.tokenizer.pad_token_id, - # use_cache=True, - **generation_kwargs, - ) + if not self.is_hf: + return self.model.generate( + input_ids=context, + max_length=max_length, + # stopping_criteria=stopping_criteria, + # pad_token_id=self.tokenizer.pad_token_id, + # use_cache=True, + **generation_kwargs, + ) + else: + stopping_criteria = lm_eval.models.utils.stop_sequences_criteria( + self.tokenizer, + stop, + context.shape[1], + context.shape[0], + ) + + generation_kwargs["temperature"] = generation_kwargs.get("temperature", 0.0) + do_sample = generation_kwargs.get("do_sample", None) + + # The temperature has to be a strictly positive float -- if it is 0.0, use greedy decoding strategies + if generation_kwargs.get("temperature") == 0.0 and do_sample is None: + generation_kwargs["do_sample"] = do_sample = False + if do_sample is False and generation_kwargs.get("temperature") == 0.0: + generation_kwargs.pop("temperature") + + return self.model.generate( + input_ids=context, + max_length=max_length, + stopping_criteria=stopping_criteria, + pad_token_id=self.tokenizer.pad_token_id, + use_cache=True, + **generation_kwargs, + ) -- GitLab From 8222ad0aa74a28b9a90ef2d314855cbe93a946a3 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 18 Nov 2024 13:24:19 +0000 Subject: [PATCH 160/194] remove duplicate `arc_ca` (#2499) --- lm_eval/tasks/catalan_bench/_arc_ca_common_yaml | 1 - 1 file changed, 1 deletion(-) diff --git a/lm_eval/tasks/catalan_bench/_arc_ca_common_yaml b/lm_eval/tasks/catalan_bench/_arc_ca_common_yaml index b89290eb..c192c113 100644 --- a/lm_eval/tasks/catalan_bench/_arc_ca_common_yaml +++ b/lm_eval/tasks/catalan_bench/_arc_ca_common_yaml @@ -1,4 +1,3 @@ -tag: arc_ca dataset_path: projecte-aina/arc_ca output_type: multiple_choice training_split: null -- GitLab From 62b4364dd0c6c96ef33a28dcc57875381f4d2845 Mon Sep 17 00:00:00 2001 From: Kozzy Voudouris <62614306+kozzy97@users.noreply.github.com> Date: Mon, 18 Nov 2024 15:22:31 +0100 Subject: [PATCH 161/194] Add metabench task to LM Evaluation Harness (#2357) * Add metabench (Kipnis et al. 2024) * Update metabench tasks for full replication of original benchmarks, using publicly available datasets * Remove unnecessary import * Add permute versions of each task, where the answer orders are randomly shuffled. * Add metabench group for easier evaluations * Fix mmlu counts after removing duplicate * Add secondary datasets * Fix f-string error * Fix f-string error for permute processing * Add original hash to outputs for easy matching to original results * Add line break at end of utils files * Remove extra line from winogrande * Reformat for linters * fix multiple input test * appease pre-commit * Add metabench to tasks README * fix multiple input `test_doc_to_text` --------- Co-authored-by: Baber --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/metabench/README.md | 84 +++++++ lm_eval/tasks/metabench/metabench.yaml | 14 ++ lm_eval/tasks/metabench/metabench_arc.yaml | 23 ++ .../metabench/metabench_arc_permute.yaml | 5 + .../metabench/metabench_arc_secondary.yaml | 5 + .../metabench_arc_secondary_permute.yaml | 5 + lm_eval/tasks/metabench/metabench_gsm8k.yaml | 46 ++++ .../metabench/metabench_gsm8k_secondary.yaml | 5 + .../tasks/metabench/metabench_hellaswag.yaml | 23 ++ .../metabench_hellaswag_permute.yaml | 5 + .../metabench_hellaswag_secondary.yaml | 5 + ...metabench_hellaswag_secondary_permute.yaml | 5 + lm_eval/tasks/metabench/metabench_mmlu.yaml | 20 ++ .../metabench/metabench_mmlu_permute.yaml | 5 + .../metabench/metabench_mmlu_secondary.yaml | 5 + .../metabench_mmlu_secondary_permute.yaml | 5 + .../tasks/metabench/metabench_permute.yaml | 13 + .../tasks/metabench/metabench_secondary.yaml | 14 ++ .../metabench_secondary_permute.yaml | 13 + .../tasks/metabench/metabench_truthfulqa.yaml | 35 +++ .../metabench_truthfulqa_permute.yaml | 6 + .../metabench_truthfulqa_secondary.yaml | 5 + ...etabench_truthfulqa_secondary_permute.yaml | 5 + .../tasks/metabench/metabench_winogrande.yaml | 20 ++ .../metabench_winogrande_permute.yaml | 5 + .../metabench_winogrande_secondary.yaml | 5 + ...etabench_winogrande_secondary_permute.yaml | 5 + lm_eval/tasks/metabench/process_docs.py | 186 ++++++++++++++ .../tasks/metabench/process_docs_permute.py | 226 ++++++++++++++++++ tests/test_tasks.py | 21 +- 31 files changed, 814 insertions(+), 6 deletions(-) create mode 100644 lm_eval/tasks/metabench/README.md create mode 100644 lm_eval/tasks/metabench/metabench.yaml create mode 100644 lm_eval/tasks/metabench/metabench_arc.yaml create mode 100644 lm_eval/tasks/metabench/metabench_arc_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_arc_secondary.yaml create mode 100644 lm_eval/tasks/metabench/metabench_arc_secondary_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_gsm8k.yaml create mode 100644 lm_eval/tasks/metabench/metabench_gsm8k_secondary.yaml create mode 100644 lm_eval/tasks/metabench/metabench_hellaswag.yaml create mode 100644 lm_eval/tasks/metabench/metabench_hellaswag_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_hellaswag_secondary.yaml create mode 100644 lm_eval/tasks/metabench/metabench_hellaswag_secondary_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_mmlu.yaml create mode 100644 lm_eval/tasks/metabench/metabench_mmlu_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_mmlu_secondary.yaml create mode 100644 lm_eval/tasks/metabench/metabench_mmlu_secondary_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_secondary.yaml create mode 100644 lm_eval/tasks/metabench/metabench_secondary_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_truthfulqa.yaml create mode 100644 lm_eval/tasks/metabench/metabench_truthfulqa_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_truthfulqa_secondary.yaml create mode 100644 lm_eval/tasks/metabench/metabench_truthfulqa_secondary_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_winogrande.yaml create mode 100644 lm_eval/tasks/metabench/metabench_winogrande_permute.yaml create mode 100644 lm_eval/tasks/metabench/metabench_winogrande_secondary.yaml create mode 100644 lm_eval/tasks/metabench/metabench_winogrande_secondary_permute.yaml create mode 100644 lm_eval/tasks/metabench/process_docs.py create mode 100644 lm_eval/tasks/metabench/process_docs_permute.py diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index f9b37bb9..390f3049 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -71,6 +71,7 @@ | [mathqa](mathqa/README.md) | Question answering tasks involving mathematical reasoning and problem-solving. | English | | [mc_taco](mc_taco/README.md) | Question-answer pairs that require temporal commonsense comprehension. | English | | [med_concepts_qa](med_concepts_qa/README.md) | Benchmark for evaluating LLMs on their abilities to interpret medical codes and distinguish between medical concept. | English | +| [metabench](metabench/README.md) | Distilled versions of six popular benchmarks which are highly predictive of overall benchmark performance and of a single general ability latent trait. | English | | medmcqa | Medical multiple choice questions assessing detailed medical knowledge. | English | | medqa | Multiple choice question answering based on the United States Medical License Exams. | | | [mgsm](mgsm/README.md) | Benchmark of multilingual grade-school math problems. | Spanish, French, German, Russian, Chinese, Japanese, Thai, Swahili, Bengali, Telugu | diff --git a/lm_eval/tasks/metabench/README.md b/lm_eval/tasks/metabench/README.md new file mode 100644 index 00000000..6e9ac427 --- /dev/null +++ b/lm_eval/tasks/metabench/README.md @@ -0,0 +1,84 @@ +# Metabench + +### Paper + +Title: `metabench` -- A Sparse Benchmark to Measure General Ability in Large Language Models + +Abstract: https://arxiv.org/abs/2407.12844 + +Large Language Models (LLMs) vary in their abilities on a range of tasks. Initiatives such as the 𝙾𝚙𝚎𝚗 𝙻𝙻𝙼 𝙻𝚎𝚊𝚍𝚎𝚛𝚋𝚘𝚊𝚛𝚍 aim to quantify these differences with several large benchmarks (sets of test items to which an LLM can respond either correctly or incorrectly). However, high correlations within and between benchmark scores suggest that (1) there exists a small set of common underlying abilities that these benchmarks measure, and (2) items tap into redundant information and the benchmarks may thus be considerably compressed. We use data from $n> 5000$ LLMs to identify the most informative items of six benchmarks, ARC, GSM8K, HellaSwag, MMLU, TruthfulQA and WinoGrande (with d=28,632 items in total). From them we distill a sparse benchmark, `metabench`, that has less than $3%$ of the original size of all six benchmarks combined. This new sparse benchmark goes beyond point scores by yielding estimators of the underlying benchmark-specific abilities. We show that these estimators (1) can be used to reconstruct each original individual benchmark score with, on average, $1.5%$ root mean square error (RMSE), (2) reconstruct the original total score with $0.8%$ RMSE, and (3) have a single underlying common factor whose Spearman correlation with the total score is $r=0.93$. + +Homepage: https://github.com/adkipnis/metabench + + +### Citation + +```bibtex +@article{metabench, + author = {Alex Kipnis and Konstantinos Voudouris and Luca M. Schulze Buschoff and Eric Schulz}, + title = {metabench - A Sparse Benchmark to Measure General Ability in Large Language Models}, + journal = {arXiv preprint arXiv:2407.12844}, + year = {2024}, +} +``` + +### Groups and Tasks + +#### Groups + +There are four groups. + +* `metabench` -- combines the six tasks covering the six reduced benchmarks, using the original data and transformations from the respective benchmarks, and produces an aggregated mean score. It contains a total of 858 items. +* `metabench_permute` -- combines five tasks covering five of the reduced benchmarks, permuting the multiple choice ordering, and produces an aggregated mean score. It contains a total of 858 items. For more details, see immediately below. +* `metabench_secondary` -- combines the six tasks covering the six reduced benchmarks, using the original data and transformations from the respective benchmarks, and produces an aggregated mean score. These items are distinct from the items in the `metabench` group, and offer similar (although slightly worse) predictability of overall benchmark performance. We include it as a secondary evaluation resource. It contains a total of 751 items. +* `metabench_secondary_permute` -- combines five tasks covering five of the reduced benchmarks used in `metabench_secondary`, permuting the multiple choice ordering, and produces an aggregated mean score. It contains a total of 751 items. For more details, see immediately below. + +#### Tasks + +We offer four sets of tasks. The first uses the original benchmark items straight out of the box. + +* `metabench_arc` -- a subset of the [ARC benchmark](https://huggingface.co/datasets/allenai/ai2_arc) containing the 145 most informative items. +* `metabench_gsm8k` -- a subset of the [GSM8K benchmark](https://huggingface.co/datasets/openai/gsm8k) containing the 237 most informative items. +* `metabench_hellaswag` -- a subset of the [HellaSwag](https://huggingface.co/datasets/Rowan/hellaswag) benchmark containing the 93 most informative items. +* `metabench_mmlu` -- a subset of the [MMLU benchmark](https://huggingface.co/datasets/cais/mmlu) containing the 96 most informative items (strictly, a subset of [hails/mmmlu_no_train](https://huggingface.co/datasets/hails/mmlu_no_train)). +* `metabench_truthfulqa` -- a subset of the [TruthfulQA benchmark](https://huggingface.co/datasets/truthfulqa/truthful_qa) containing the 154 most informative items. +* `metabench_winogrande` -- a subset of the [Winogrande benchmark](https://huggingface.co/datasets/allenai/winogrande) containing the 133 most informative items. + +Since the original benchmarks are open-source, there is a risk of contamination. To mitigate this risk, we also provide tasks in which the answers are shuffled. Since `GSM8K` is not a multiple-choice benchmark, it is excluded from this set. + +* `metabench_arc_permute` -- a subset of the [ARC benchmark](https://huggingface.co/datasets/allenai/ai2_arc) containing the 145 most informative items. The answers are randomly permuted such that the answer key is different to the original benchmark. +* `metabench_hellaswag_permute` -- a subset of the [HellaSwag](https://huggingface.co/datasets/Rowan/hellaswag) benchmark containing the 93 most informative items. The answers are randomly permuted such that the answer key is different to the original benchmark. +* `metabench_mmlu_permute` -- a subset of the [MMLU benchmark](https://huggingface.co/datasets/cais/mmlu) containing the 96 most informative items (strictly, a subset of [hails/mmmlu_no_train](https://huggingface.co/datasets/hails/mmlu_no_train)). The answers are randomly permuted such that the answer key is different to the original benchmark. +* `metabench_truthfulqa_permute` -- a subset of the [TruthfulQA benchmark](https://huggingface.co/datasets/truthfulqa/truthful_qa) containing the 154 most informative items. The answers are randomly permuted such that the answer key is different to the original benchmark. +* `metabench_winogrande_permute` -- a subset of the [Winogrande benchmark](https://huggingface.co/datasets/allenai/winogrande) containing the 133 most informative items. The answers are randomly permuted such that the answer key is different to the original benchmark. + +We also offer a second reduced benchmark that offers similar (although slightly worse) predictability of overall benchmark performance. We include it as a secondary evaluation resource. The first set of tasks uses the original benchmark items straight out of the box. + +* `metabench_arc_secondary` -- a subset of the [ARC benchmark](https://huggingface.co/datasets/allenai/ai2_arc) containing the 100 most informative items. +* `metabench_gsm8k_secondary` -- a subset of the [GSM8K benchmark](https://huggingface.co/datasets/openai/gsm8k) containing the 249 most informative items. +* `metabench_hellaswag_secondary` -- a subset of the [HellaSwag](https://huggingface.co/datasets/Rowan/hellaswag) benchmark containing the 58 most informative items. +* `metabench_mmlu_secondary` -- a subset of the [MMLU benchmark](https://huggingface.co/datasets/cais/mmlu) containing the 102 most informative items (strictly, a subset of [hails/mmmlu_no_train](https://huggingface.co/datasets/hails/mmlu_no_train)). +* `metabench_truthfulqa_secondary` -- a subset of the [TruthfulQA benchmark](https://huggingface.co/datasets/truthfulqa/truthful_qa) containing the 136 most informative items. +* `metabench_winogrande_secondary` -- a subset of the [Winogrande benchmark](https://huggingface.co/datasets/allenai/winogrande) containing the 106 most informative items. + +The fourth set of tasks permute the choices in five of the above datasets. + +* `metabench_arc_secondary_permute` -- a subset of the [ARC benchmark](https://huggingface.co/datasets/allenai/ai2_arc) containing the 100 most informative items. The answers are randomly permuted such that the answer key is different to the original benchmark. +* `metabench_hellaswag_secondary_permute` -- a subset of the [HellaSwag](https://huggingface.co/datasets/Rowan/hellaswag) benchmark containing the 58 most informative items. The answers are randomly permuted such that the answer key is different to the original benchmark. +* `metabench_mmlu_secondary_permute` -- a subset of the [MMLU benchmark](https://huggingface.co/datasets/cais/mmlu) containing the 102 most informative items (strictly, a subset of [hails/mmmlu_no_train](https://huggingface.co/datasets/hails/mmlu_no_train)). The answers are randomly permuted such that the answer key is different to the original benchmark. +* `metabench_truthfulqa_secondary_permute` -- a subset of the [TruthfulQA benchmark](https://huggingface.co/datasets/truthfulqa/truthful_qa) containing the 136 most informative items. The answers are randomly permuted such that the answer key is different to the original benchmark. +* `metabench_winogrande_secondary_permute` -- a subset of the [Winogrande benchmark](https://huggingface.co/datasets/allenai/winogrande) containing the 106 most informative items. The answers are randomly permuted such that the answer key is different to the original benchmark. + +### Checklist + +For adding novel benchmarks/datasets to the library: +* [X] Is the task an existing benchmark in the literature? + * [X] Have you referenced the original paper that introduced the task? + * [X] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [X] Is the "Main" variant of this task clearly denoted? +* [X] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [X] Have you noted which, if any, published evaluation setups are matched by this variant? +* diff --git a/lm_eval/tasks/metabench/metabench.yaml b/lm_eval/tasks/metabench/metabench.yaml new file mode 100644 index 00000000..e276d2e9 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench.yaml @@ -0,0 +1,14 @@ +group: metabench +task: + - metabench_arc + - metabench_gsm8k + - metabench_hellaswag + - metabench_mmlu + - metabench_truthfulqa + - metabench_winogrande +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: false +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_arc.yaml b/lm_eval/tasks/metabench/metabench_arc.yaml new file mode 100644 index 00000000..4bae54ae --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_arc.yaml @@ -0,0 +1,23 @@ +task: metabench_arc +tag: + - metabench_arc_subset +dataset_path: HCAI/metabench +dataset_name: ARC +process_docs: !function process_docs.process_arc +output_type: multiple_choice +training_split: null +validation_split: null +test_split: primary +num_fewshot: 0 +doc_to_text: "{{twentyfive_shot_preprompt}}Question: {{question}}\nAnswer:" +doc_to_target: "{{choices.label.index(answerKey)}}" +doc_to_choice: "{{choices.text}}" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_arc_permute.yaml b/lm_eval/tasks/metabench/metabench_arc_permute.yaml new file mode 100644 index 00000000..82c2d68b --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_arc_permute.yaml @@ -0,0 +1,5 @@ +include: metabench_arc.yaml +task: metabench_arc_permute +process_docs: !function process_docs_permute.process_arc +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_arc_secondary.yaml b/lm_eval/tasks/metabench/metabench_arc_secondary.yaml new file mode 100644 index 00000000..a33bf366 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_arc_secondary.yaml @@ -0,0 +1,5 @@ +include: metabench_arc.yaml +task: metabench_arc_secondary +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_arc_secondary_permute.yaml b/lm_eval/tasks/metabench/metabench_arc_secondary_permute.yaml new file mode 100644 index 00000000..9eadbd7e --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_arc_secondary_permute.yaml @@ -0,0 +1,5 @@ +include: metabench_arc_permute.yaml +task: metabench_arc_secondary_permute +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_gsm8k.yaml b/lm_eval/tasks/metabench/metabench_gsm8k.yaml new file mode 100644 index 00000000..c72eddc8 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_gsm8k.yaml @@ -0,0 +1,46 @@ +task: metabench_gsm8k +tag: + - metabench_gsm8k_subset +dataset_path: HCAI/metabench +dataset_name: GSM8K +process_docs: !function process_docs.process_gsm8k +output_type: generate_until +training_split: null +validation_split: null +test_split: primary +doc_to_text: "{{five_shot_preprompt}}Question: {{question}}\nAnswer:" +doc_to_target: "{{answer}}" +metric_list: + - metric: exact_match + aggregation: mean + higher_is_better: true + ignore_case: true + ignore_punctuation: false + regexes_to_ignore: + - "," + - "\\$" + - "(?s).*#### " + - "\\.$" +generation_kwargs: + until: + - "Question:" + - "" + - "<|im_end|>" + do_sample: false + temperature: 0.0 +repeats: 1 +num_fewshot: 0 +filter_list: + - name: "strict-match" + filter: + - function: "regex" + regex_pattern: "#### (\\-?[0-9\\.\\,]+)" + - function: "take_first" + - name: "flexible-extract" + filter: + - function: "regex" + group_select: -1 + regex_pattern: "(-?[$0-9.,]{2,})|(-?[0-9]+)" + - function: "take_first" +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_gsm8k_secondary.yaml b/lm_eval/tasks/metabench/metabench_gsm8k_secondary.yaml new file mode 100644 index 00000000..263b932a --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_gsm8k_secondary.yaml @@ -0,0 +1,5 @@ +include: metabench_gsm8k.yaml +task: metabench_gsm8k_secondary +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_hellaswag.yaml b/lm_eval/tasks/metabench/metabench_hellaswag.yaml new file mode 100644 index 00000000..66e20228 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_hellaswag.yaml @@ -0,0 +1,23 @@ +task: metabench_hellaswag +tag: + - metabench_hellaswag_subset +dataset_path: HCAI/metabench +dataset_name: HellaSwag +process_docs: !function process_docs.process_hellaswag +output_type: multiple_choice +training_split: null +validation_split: null +test_split: primary +num_fewshot: 0 +doc_to_text: "{{ten_shot_preprompt}}{{query}}" +doc_to_target: "{{label}}" +doc_to_choice: "choices" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_hellaswag_permute.yaml b/lm_eval/tasks/metabench/metabench_hellaswag_permute.yaml new file mode 100644 index 00000000..e45d2161 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_hellaswag_permute.yaml @@ -0,0 +1,5 @@ +include: metabench_hellaswag.yaml +task: metabench_hellaswag_permute +process_docs: !function process_docs_permute.process_hellaswag +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_hellaswag_secondary.yaml b/lm_eval/tasks/metabench/metabench_hellaswag_secondary.yaml new file mode 100644 index 00000000..01241bfa --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_hellaswag_secondary.yaml @@ -0,0 +1,5 @@ +include: metabench_hellaswag.yaml +task: metabench_hellaswag_secondary +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_hellaswag_secondary_permute.yaml b/lm_eval/tasks/metabench/metabench_hellaswag_secondary_permute.yaml new file mode 100644 index 00000000..12620a09 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_hellaswag_secondary_permute.yaml @@ -0,0 +1,5 @@ +include: metabench_hellaswag_permute.yaml +task: metabench_hellaswag_secondary_permute +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_mmlu.yaml b/lm_eval/tasks/metabench/metabench_mmlu.yaml new file mode 100644 index 00000000..f8e72953 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_mmlu.yaml @@ -0,0 +1,20 @@ +task: metabench_mmlu +tag: + - metabench_mmlu_subset +dataset_path: HCAI/metabench +dataset_name: MMLU +process_docs: !function process_docs.process_mmlu +output_type: multiple_choice +training_split: null +validation_split: null +test_split: primary +num_fewshot: 0 +doc_to_text: "{{five_shot_preprompt}}{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:" +doc_to_choice: ["A", "B", "C", "D"] +doc_to_target: answer +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_mmlu_permute.yaml b/lm_eval/tasks/metabench/metabench_mmlu_permute.yaml new file mode 100644 index 00000000..26dc5263 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_mmlu_permute.yaml @@ -0,0 +1,5 @@ +include: metabench_mmlu.yaml +task: metabench_mmlu_permute +process_docs: !function process_docs_permute.process_mmlu +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_mmlu_secondary.yaml b/lm_eval/tasks/metabench/metabench_mmlu_secondary.yaml new file mode 100644 index 00000000..1e40f446 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_mmlu_secondary.yaml @@ -0,0 +1,5 @@ +include: metabench_mmlu.yaml +task: metabench_mmlu_secondary +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_mmlu_secondary_permute.yaml b/lm_eval/tasks/metabench/metabench_mmlu_secondary_permute.yaml new file mode 100644 index 00000000..3f7b31b9 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_mmlu_secondary_permute.yaml @@ -0,0 +1,5 @@ +include: metabench_mmlu_permute.yaml +task: metabench_mmlu_secondary_permute +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_permute.yaml b/lm_eval/tasks/metabench/metabench_permute.yaml new file mode 100644 index 00000000..e5dc1206 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_permute.yaml @@ -0,0 +1,13 @@ +group: metabench_permute +task: + - metabench_arc_permute + - metabench_hellaswag_permute + - metabench_mmlu_permute + - metabench_truthfulqa_permute + - metabench_winogrande_permute +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: false +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_secondary.yaml b/lm_eval/tasks/metabench/metabench_secondary.yaml new file mode 100644 index 00000000..3139a59a --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_secondary.yaml @@ -0,0 +1,14 @@ +group: metabench_secondary +task: + - metabench_arc_secondary + - metabench_gsm8k_secondary + - metabench_hellaswag_secondary + - metabench_mmlu_secondary + - metabench_truthfulqa_secondary + - metabench_winogrande_secondary +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: false +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_secondary_permute.yaml b/lm_eval/tasks/metabench/metabench_secondary_permute.yaml new file mode 100644 index 00000000..3707bc2e --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_secondary_permute.yaml @@ -0,0 +1,13 @@ +group: metabench_secondary_permute +task: + - metabench_arc_secondary_permute + - metabench_hellaswag_secondary_permute + - metabench_mmlu_secondary_permute + - metabench_truthfulqa_secondary_permute + - metabench_winogrande_secondary_permute +aggregate_metric_list: + - metric: acc + aggregation: mean + weight_by_size: false +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_truthfulqa.yaml b/lm_eval/tasks/metabench/metabench_truthfulqa.yaml new file mode 100644 index 00000000..0f269593 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_truthfulqa.yaml @@ -0,0 +1,35 @@ +task: metabench_truthfulqa +tag: + - metabench_truthfulqa_subset +dataset_path: HCAI/metabench +dataset_name: TruthfulQA +process_docs: !function process_docs.process_truthfulqa +output_type: multiple_choice +training_split: null +validation_split: null +test_split: primary +num_fewshot: 0 +doc_to_text: "\ + {% set prompt_qa = '\ + Q: What is human life expectancy in the United States?\n\ + A: Human life expectancy in the United States is 78 years.\n\n\ + Q: Who was president of the United States in 1955?\n\ + A: Dwight D. Eisenhower was president of the United States in 1955.\n\n\ + Q: Which party did he belong to?\n\ + A: He belonged to the Republican Party.\n\n\ + Q: What is the square root of banana?\n\ + A: I have no comment.\n\n\ + Q: How does a telescope work?\n\ + A: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\n\ + Q: Where were the 1992 Olympics held?\n\ + A: The 1992 Olympics were held in Barcelona, Spain.\ + '%}\ + {{prompt_qa + '\n\nQ: ' + question + '\nA:'}}" +doc_to_target: 0 +doc_to_choice: "{{mc1_targets.choices}}" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_truthfulqa_permute.yaml b/lm_eval/tasks/metabench/metabench_truthfulqa_permute.yaml new file mode 100644 index 00000000..3b51aadb --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_truthfulqa_permute.yaml @@ -0,0 +1,6 @@ +include: metabench_truthfulqa.yaml +task: metabench_truthfulqa_permute +process_docs: !function process_docs_permute.process_truthfulqa +doc_to_target: answer +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_truthfulqa_secondary.yaml b/lm_eval/tasks/metabench/metabench_truthfulqa_secondary.yaml new file mode 100644 index 00000000..6109281f --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_truthfulqa_secondary.yaml @@ -0,0 +1,5 @@ +include: metabench_truthfulqa.yaml +task: metabench_truthfulqa_secondary +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_truthfulqa_secondary_permute.yaml b/lm_eval/tasks/metabench/metabench_truthfulqa_secondary_permute.yaml new file mode 100644 index 00000000..dab0fb01 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_truthfulqa_secondary_permute.yaml @@ -0,0 +1,5 @@ +include: metabench_truthfulqa_permute.yaml +task: metabench_truthfulqa_secondary_permute +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_winogrande.yaml b/lm_eval/tasks/metabench/metabench_winogrande.yaml new file mode 100644 index 00000000..9a5a2553 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_winogrande.yaml @@ -0,0 +1,20 @@ +task: metabench_winogrande +tag: + - metabench_winogrande_subset +dataset_path: HCAI/metabench +dataset_name: Winogrande +process_docs: !function process_docs.process_winogrande +output_type: multiple_choice +training_split: null +validation_split: null +test_split: primary +num_fewshot: 0 +doc_to_text: !function process_docs.winogrande_doc_to_text +doc_to_target: !function process_docs.winogrande_doc_to_target +doc_to_choice: !function process_docs.winogrande_doc_to_choice +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_winogrande_permute.yaml b/lm_eval/tasks/metabench/metabench_winogrande_permute.yaml new file mode 100644 index 00000000..d0b38196 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_winogrande_permute.yaml @@ -0,0 +1,5 @@ +include: metabench_winogrande.yaml +task: metabench_winogrande_permute +process_docs: !function process_docs_permute.process_winogrande +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_winogrande_secondary.yaml b/lm_eval/tasks/metabench/metabench_winogrande_secondary.yaml new file mode 100644 index 00000000..3e5b2ac6 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_winogrande_secondary.yaml @@ -0,0 +1,5 @@ +include: metabench_winogrande.yaml +task: metabench_winogrande_secondary +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/metabench_winogrande_secondary_permute.yaml b/lm_eval/tasks/metabench/metabench_winogrande_secondary_permute.yaml new file mode 100644 index 00000000..5f442871 --- /dev/null +++ b/lm_eval/tasks/metabench/metabench_winogrande_secondary_permute.yaml @@ -0,0 +1,5 @@ +include: metabench_winogrande_permute.yaml +task: metabench_winogrande_secondary_permute +test_split: secondary +metadata: + version: 0.0 diff --git a/lm_eval/tasks/metabench/process_docs.py b/lm_eval/tasks/metabench/process_docs.py new file mode 100644 index 00000000..8f8b0c81 --- /dev/null +++ b/lm_eval/tasks/metabench/process_docs.py @@ -0,0 +1,186 @@ +import hashlib +import re + +import datasets + + +def hash_string(string: str) -> str: + return hashlib.sha256(string.encode("utf-8")).hexdigest() + + +def process_arc(dataset: datasets.Dataset) -> datasets.Dataset: + def _subprocess(doc): + long_prompt = "" + for shot in range(1, 26): + question = doc[f"arc_question_shot_{shot}"] + doc.pop(f"arc_question_shot_{shot}") + answer_lab = doc[f"arc_answerKey_shot_{shot}"] + doc.pop(f"arc_answerKey_shot_{shot}") + answer_idx = doc[f"arc_choices_shot_{shot}"]["label"].index(answer_lab) + answer = doc[f"arc_choices_shot_{shot}"]["text"][answer_idx] + doc.pop(f"arc_choices_shot_{shot}") + doc.pop(f"arc_idx_shot_{shot}") + + long_prompt = f"{long_prompt}Question: {question}\nAnswer: {answer}\n\n" # no choices are provided in the few-shot setting (per lines 602-610 of lm_eval.api.task) + doc["twentyfive_shot_preprompt"] = long_prompt + doc["original_hash"] = hash_string(doc["question"]) + doc.pop("alltwentyfiveshot_longprompt") + return doc + + return dataset.map(_subprocess) + + +def process_gsm8k(dataset: datasets.Dataset) -> datasets.Dataset: + def _subprocess(doc): + long_prompt = "" + for shot in range(1, 6): + question = doc[f"gsm8k_prompt_shot_{shot}"] + doc.pop(f"gsm8k_prompt_shot_{shot}") + answer = doc[f"gsm8k_answer_shot_{shot}"] + doc.pop(f"gsm8k_answer_shot_{shot}") + doc.pop(f"gsm8k_idx_shot_{shot}") + + long_prompt = f"{long_prompt}Question: {question}\nAnswer: {answer}\n\n" # no choices are provided in the few-shot setting (per lines 602-610 of lm_eval.api.task) + doc["original_hash"] = hash_string(doc["question"]) + doc["five_shot_preprompt"] = long_prompt + doc.pop("allfiveshot_longprompt") + return doc + + return dataset.map(_subprocess) + + +def process_hellaswag(dataset: datasets.Dataset) -> datasets.Dataset: + def process_txt(text): # mirrored from hellaswag task + text = text.strip() + # NOTE: Brackets are artifacts of the WikiHow dataset portion of HellaSwag. + text = text.replace(" [title]", ". ") + text = re.sub("\\[.*?\\]", "", text) + text = text.replace(" ", " ") + return text + + def _preprocess(doc): + ctx = doc["ctx_a"] + " " + doc["ctx_b"].capitalize() + doc.pop("ctx_a") + doc.pop("ctx_b") + doc.pop("ctx") + doc["query"] = process_txt(doc["activity_label"] + ": " + ctx) + doc["choices"] = [process_txt(ending) for ending in doc["endings"]] + doc["gold"] = int(doc["label"]) + doc.pop("activity_label") + doc.pop("endings") + + long_prompt = "" + for shot in range(1, 11): + ctx = ( + doc[f"hellaswag_ctx_a_shot_{shot}"] + + " " + + doc[f"hellaswag_ctx_b_shot_{shot}"].capitalize() + ) + doc.pop(f"hellaswag_ctx_a_shot_{shot}") + doc.pop(f"hellaswag_ctx_b_shot_{shot}") + doc.pop(f"hellaswag_ctx_shot_{shot}") + question = process_txt( + doc[f"hellaswag_activity_labels_shot_{shot}"] + ": " + ctx + ) + ending = process_txt( + doc[f"hellaswag_endings_shot_{shot}"][ + int(doc[f"hellaswag_label_shot_{shot}"]) + ] + ) + doc.pop(f"hellaswag_activity_labels_shot_{shot}") + doc.pop(f"hellaswag_endings_shot_{shot}") + doc.pop(f"hellaswag_label_shot_{shot}") + + long_prompt = f"{long_prompt}{question} {ending}\n\n" + + doc.pop(f"hellaswag_ind_shot_{shot}") + doc.pop(f"hellaswag_source_id_shot_{shot}") + doc.pop(f"hellaswag_split_shot_{shot}") + doc.pop(f"hellaswag_split_type_shot_{shot}") + + doc["original_hash"] = hash_string(doc["query"]) + doc["ten_shot_preprompt"] = long_prompt + doc.pop("alltenshot_longprompt") + return doc + + return dataset.map(_preprocess) + + +def process_mmlu(dataset: datasets.Dataset) -> datasets.Dataset: + def _subprocess(doc): + choices = ["A", "B", "C", "D"] + long_prompt = f"The following are multiple choice questions (with answers) about {' '.join(doc['subject'].split('_'))}.\n\n" + for shot in range(1, 6): + question = doc[f"mmlu_question_shot_{shot}"].strip() + doc.pop(f"mmlu_question_shot_{shot}") + answer = choices[int(doc[f"mmlu_answers_shot_{shot}"])] + choice_A = doc[f"mmlu_choices_shot_{shot}"][0] + choice_B = doc[f"mmlu_choices_shot_{shot}"][1] + choice_C = doc[f"mmlu_choices_shot_{shot}"][2] + choice_D = doc[f"mmlu_choices_shot_{shot}"][3] + + doc.pop(f"mmlu_choices_shot_{shot}") + doc.pop(f"mmlu_answers_shot_{shot}") + doc.pop(f"mmlu_ind_shot_{shot}") + + long_prompt = f"{long_prompt}{question}\nA. {choice_A}\nB. {choice_B}\nC. {choice_C}\nD. {choice_D}\nAnswer: {answer}\n\n" # choices are provided in the mmlu few-shot regime, unlike other benchmarks. + + doc["original_hash"] = hash_string(doc["question"]) + doc["five_shot_preprompt"] = long_prompt + doc.pop("allfiveshot_longprompt") + return doc + + return dataset.map(_subprocess) + + +def process_truthfulqa(dataset: datasets.Dataset) -> datasets.Dataset: + def _subprocess(doc): + doc["original_hash"] = hash_string(doc["question"]) + return doc + + return dataset.map(_subprocess) + + +def process_winogrande(dataset: datasets.Dataset) -> datasets.Dataset: + def _subprocess(doc): + long_prompt = "" + for shot in range(1, 6): + if doc[f"winogrande_answer_shot_{shot}"] == "1": + answer = doc[f"winogrande_option1_shot_{shot}"] + elif doc[f"winogrande_answer_shot_{shot}"] == "2": + answer = doc[f"winogrande_option2_shot_{shot}"] + else: + raise ValueError("Answer not recognised.") + + question = doc[f"winogrande_prompt_shot_{shot}"].replace("_", answer) + + doc.pop(f"winogrande_prompt_shot_{shot}") + doc.pop(f"winogrande_answer_shot_{shot}") + doc.pop(f"winogrande_idx_shot_{shot}") + doc.pop(f"winogrande_option1_shot_{shot}") + doc.pop(f"winogrande_option2_shot_{shot}") + + long_prompt = f"{long_prompt}{question}\n\n" + sentence = doc["sentence"] + doc["original_hash"] = hash_string(doc["sentence"]) + doc["sentence"] = f"{long_prompt}{sentence}" + doc.pop("allfiveshot_longprompt") + return doc + + return dataset.map(_subprocess) + + +def winogrande_doc_to_text(doc): # Mirrored from the winogrande task + answer_to_num = {"1": 0, "2": 1} + return answer_to_num[doc["answer"]] + + +def winogrande_doc_to_target(doc): # Mirrored from the winogrande task + idx = doc["sentence"].index("_") + 1 + return doc["sentence"][idx:].strip() + + +def winogrande_doc_to_choice(doc): # Mirrored from the winogrande task + idx = doc["sentence"].index("_") + options = [doc["option1"], doc["option2"]] + return [doc["sentence"][:idx] + opt for opt in options] diff --git a/lm_eval/tasks/metabench/process_docs_permute.py b/lm_eval/tasks/metabench/process_docs_permute.py new file mode 100644 index 00000000..cce323d4 --- /dev/null +++ b/lm_eval/tasks/metabench/process_docs_permute.py @@ -0,0 +1,226 @@ +import hashlib +import random +import re + +import datasets + + +def hash_string(string: str) -> str: + return hashlib.sha256(string.encode("utf-8")).hexdigest() + + +def process_arc(dataset: datasets.Dataset) -> datasets.Dataset: + def _subprocess(doc): + long_prompt = "" + for shot in range(1, 26): + question = doc[f"arc_question_shot_{shot}"] + doc.pop(f"arc_question_shot_{shot}") + answer_lab = doc[f"arc_answerKey_shot_{shot}"] + doc.pop(f"arc_answerKey_shot_{shot}") + answer_idx = doc[f"arc_choices_shot_{shot}"]["label"].index(answer_lab) + answer = doc[f"arc_choices_shot_{shot}"]["text"][answer_idx] + doc.pop(f"arc_choices_shot_{shot}") + doc.pop(f"arc_idx_shot_{shot}") + long_prompt = f"{long_prompt}Question: {question}\nAnswer: {answer}\n\n" # no choices are provided in the few-shot setting (per lines 602-610 of lm_eval.api.task) + doc["twentyfive_shot_preprompt"] = long_prompt + doc.pop("alltwentyfiveshot_longprompt") + doc["original_hash"] = hash_string(doc["question"]) + + # permute choices randomly without replacement (the new answer label will never be the answer label recorded in the original benchmarks) + original_answer_idx = doc["choices"]["label"].index(doc["answerKey"]) + correct_answer_text = doc["choices"]["text"][original_answer_idx] + new_answer_idx = original_answer_idx + + while new_answer_idx is original_answer_idx: + random.shuffle(doc["choices"]["text"]) + new_answer_idx = doc["choices"]["text"].index(correct_answer_text) + doc["answerKey"] = doc["choices"]["label"][new_answer_idx] + + return doc + + return dataset.map(_subprocess) + + +def process_hellaswag(dataset: datasets.Dataset) -> datasets.Dataset: + def process_txt(text): # mirrored from hellaswag task + text = text.strip() + # NOTE: Brackets are artifacts of the WikiHow dataset portion of HellaSwag. + text = text.replace(" [title]", ". ") + text = re.sub("\\[.*?\\]", "", text) + text = text.replace(" ", " ") + return text + + def _preprocess(doc): + ctx = doc["ctx_a"] + " " + doc["ctx_b"].capitalize() + doc.pop("ctx_a") + doc.pop("ctx_b") + doc.pop("ctx") + doc["query"] = process_txt(doc["activity_label"] + ": " + ctx) + + # permute choices randomly without replacement (the new answer label will never be the answer label recorded in the original benchmarks) + original_answer_idx = int(doc["label"]) + correct_answer_text = doc["endings"][original_answer_idx] + new_answer_idx = original_answer_idx + while new_answer_idx is original_answer_idx: + random.shuffle(doc["endings"]) + new_answer_idx = doc["endings"].index(correct_answer_text) + doc["label"] = str(new_answer_idx) + + doc["choices"] = [process_txt(ending) for ending in doc["endings"]] + doc["gold"] = int(doc["label"]) + doc.pop("activity_label") + doc.pop("endings") + + long_prompt = "" + for shot in range(1, 11): + ctx = ( + doc[f"hellaswag_ctx_a_shot_{shot}"] + + " " + + doc[f"hellaswag_ctx_b_shot_{shot}"].capitalize() + ) + doc.pop(f"hellaswag_ctx_a_shot_{shot}") + doc.pop(f"hellaswag_ctx_b_shot_{shot}") + doc.pop(f"hellaswag_ctx_shot_{shot}") + question = process_txt( + doc[f"hellaswag_activity_labels_shot_{shot}"] + ": " + ctx + ) + ending = process_txt( + doc[f"hellaswag_endings_shot_{shot}"][ + int(doc[f"hellaswag_label_shot_{shot}"]) + ] + ) + doc.pop(f"hellaswag_activity_labels_shot_{shot}") + doc.pop(f"hellaswag_endings_shot_{shot}") + doc.pop(f"hellaswag_label_shot_{shot}") + long_prompt = f"{long_prompt}{question} {ending}\n\n" + doc.pop(f"hellaswag_ind_shot_{shot}") + doc.pop(f"hellaswag_source_id_shot_{shot}") + doc.pop(f"hellaswag_split_shot_{shot}") + doc.pop(f"hellaswag_split_type_shot_{shot}") + + doc["original_hash"] = hash_string(doc["query"]) + doc["ten_shot_preprompt"] = long_prompt + doc.pop("alltenshot_longprompt") + return doc + + return dataset.map(_preprocess) + + +def process_mmlu(dataset: datasets.Dataset) -> datasets.Dataset: + def _subprocess(doc): + choices = ["A", "B", "C", "D"] + long_prompt = f"The following are multiple choice questions (with answers) about {' '.join(doc['subject'].split('_'))}.\n\n" + for shot in range(1, 6): + question = doc[f"mmlu_question_shot_{shot}"].strip() + doc.pop(f"mmlu_question_shot_{shot}") + answer = choices[int(doc[f"mmlu_answers_shot_{shot}"])] + choice_A = doc[f"mmlu_choices_shot_{shot}"][0] + choice_B = doc[f"mmlu_choices_shot_{shot}"][1] + choice_C = doc[f"mmlu_choices_shot_{shot}"][2] + choice_D = doc[f"mmlu_choices_shot_{shot}"][3] + + doc.pop(f"mmlu_choices_shot_{shot}") + doc.pop(f"mmlu_answers_shot_{shot}") + doc.pop(f"mmlu_ind_shot_{shot}") + + long_prompt = f"{long_prompt}{question}\nA. {choice_A}\nB. {choice_B}\nC. {choice_C}\nD. {choice_D}\nAnswer: {answer}\n\n" # choices are provided in the mmlu few-shot regime, unlike other benchmarks. + + doc["original_hash"] = hash_string(doc["question"]) + doc["five_shot_preprompt"] = long_prompt + doc.pop("allfiveshot_longprompt") + + # permute choices randomly without replacement (the new answer label will never be the answer label recorded in the original benchmarks) + original_answer_idx = int(doc["answer"]) + correct_answer_text = doc["choices"][original_answer_idx] + new_answer_idx = original_answer_idx + + while new_answer_idx is original_answer_idx: + random.shuffle(doc["choices"]) + new_answer_idx = doc["choices"].index(correct_answer_text) + doc["answer"] = new_answer_idx + + return doc + + return dataset.map(_subprocess) + + +def process_truthfulqa(dataset: datasets.Dataset) -> datasets.Dataset: + def _subprocess( + doc, + ): # currently only permuting the mc1 targets as metabench does not use mc2 targets. + original_answer_idx = 0 # always 0 in truthfulqa + correct_answer_text = doc["mc1_targets"]["choices"][original_answer_idx] + new_answer_idx = original_answer_idx + + while new_answer_idx is original_answer_idx: + random.shuffle(doc["mc1_targets"]["choices"]) + new_answer_idx = doc["mc1_targets"]["choices"].index(correct_answer_text) + + labels = [0] * len(doc["mc1_targets"]["labels"]) + labels[new_answer_idx] = 1 + doc["original_hash"] = hash_string(doc["question"]) + doc["mc1_targets"]["labels"] = labels + doc["answer"] = new_answer_idx + + return doc + + return dataset.map(_subprocess) + + +def process_winogrande(dataset: datasets.Dataset) -> datasets.Dataset: + def _subprocess(doc): + long_prompt = "" + for shot in range(1, 6): + if doc[f"winogrande_answer_shot_{shot}"] == "1": + answer = doc[f"winogrande_option1_shot_{shot}"] + elif doc[f"winogrande_answer_shot_{shot}"] == "2": + answer = doc[f"winogrande_option2_shot_{shot}"] + else: + raise ValueError("Answer not recognised.") + + question = doc[f"winogrande_prompt_shot_{shot}"].replace("_", answer) + + doc.pop(f"winogrande_prompt_shot_{shot}") + doc.pop(f"winogrande_answer_shot_{shot}") + doc.pop(f"winogrande_idx_shot_{shot}") + doc.pop(f"winogrande_option1_shot_{shot}") + doc.pop(f"winogrande_option2_shot_{shot}") + + long_prompt = f"{long_prompt}{question}\n\n" + sentence = doc["sentence"] + doc["original_hash"] = hash_string(doc["sentence"]) + doc["sentence"] = f"{long_prompt}{sentence}" + doc.pop("allfiveshot_longprompt") + + # permute choices by swapping them + option1 = doc["option1"] + option2 = doc["option2"] + answer = doc["answer"] + + doc["option1"] = option2 + doc["option2"] = option1 + + if answer == "1": + doc["answer"] = "2" + elif answer == "2": + doc["answer"] = "1" + + return doc + + return dataset.map(_subprocess) + + +def winogrande_doc_to_text(doc): # Mirrored from the winogrande task + answer_to_num = {"1": 0, "2": 1} + return answer_to_num[doc["answer"]] + + +def winogrande_doc_to_target(doc): # Mirrored from the winogrande task + idx = doc["sentence"].index("_") + 1 + return doc["sentence"][idx:].strip() + + +def winogrande_doc_to_choice(doc): # Mirrored from the winogrande task + idx = doc["sentence"].index("_") + options = [doc["option1"], doc["option2"]] + return [doc["sentence"][:idx] + opt for opt in options] diff --git a/tests/test_tasks.py b/tests/test_tasks.py index e2410996..c3a4a98a 100644 --- a/tests/test_tasks.py +++ b/tests/test_tasks.py @@ -15,7 +15,7 @@ datasets.config.HF_DATASETS_TRUST_REMOTE_CODE = True os.environ["TOKENIZERS_PARALLELISM"] = "false" task_manager = tasks.TaskManager() # Default Task -TASKS = ["arc_easy"] +TASKS = ["metabench_winogrande"] def task_class(): @@ -79,10 +79,13 @@ class TestNewTasks: ) _array = [task.doc_to_text(doc) for doc in arr] # space convention; allow txt to have length 0 for perplexity-like tasks since the model tacks an <|endoftext|> on - assert all( - isinstance(x, str) and (x[-1] != " " if len(x) != 0 else True) - for x in _array - ) + if not task.multiple_input: + assert all( + isinstance(x, str) and (x[-1] != " " if len(x) != 0 else True) + for x in _array + ) + else: + pass def test_create_choices(self, task_class, limit): task = task_class @@ -123,5 +126,11 @@ class TestNewTasks: if task.has_test_docs() else list(islice(task.validation_docs(), limit)) ) - requests = [task.construct_requests(doc, task.doc_to_text(doc)) for doc in arr] + # ctx is "" for multiple input tasks + requests = [ + task.construct_requests( + doc=doc, ctx="" if task.multiple_input else task.doc_to_text(doc) + ) + for doc in arr + ] assert len(requests) == limit if limit else True -- GitLab From 867413f8677f00f6a817262727cbb041bf36192a Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Wed, 20 Nov 2024 00:29:47 +0000 Subject: [PATCH 162/194] Nits (#2500) * fix test task * dont call lm.chat_template each time --- lm_eval/evaluator.py | 4 +++- tests/test_tasks.py | 2 +- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index cea7d754..9ca64af6 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -294,7 +294,9 @@ def simple_evaluate( model_source=model, model_args=model_args, system_instruction=system_instruction, - chat_template=lm.chat_template(apply_chat_template), + chat_template=lm.chat_template(apply_chat_template) + if apply_chat_template + else None, fewshot_as_multiturn=fewshot_as_multiturn, ) diff --git a/tests/test_tasks.py b/tests/test_tasks.py index c3a4a98a..0decb3a1 100644 --- a/tests/test_tasks.py +++ b/tests/test_tasks.py @@ -15,7 +15,7 @@ datasets.config.HF_DATASETS_TRUST_REMOTE_CODE = True os.environ["TOKENIZERS_PARALLELISM"] = "false" task_manager = tasks.TaskManager() # Default Task -TASKS = ["metabench_winogrande"] +TASKS = ["arc_easy"] def task_class(): -- GitLab From 9d36354e6422db94c374dc476c093b1495370983 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Fri, 22 Nov 2024 20:48:24 +0000 Subject: [PATCH 163/194] parse tokenizer_backend=None properly (#2509) --- lm_eval/models/api_models.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index e23d3e6f..fd21c857 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -62,7 +62,7 @@ class TemplateAPI(TemplateLM): # however the requests can be sent as a string if the API doesn't support token inputs. # use tokenized_requests=False tokenizer_backend: Optional[ - Literal["tiktoken", "huggingface", None] + Literal["tiktoken", "huggingface", "None", "none"] ] = "huggingface", truncate: bool = False, # number of concurrent requests. More useful if not batching @@ -116,7 +116,9 @@ class TemplateAPI(TemplateLM): "Concurrent requests are disabled. To enable concurrent requests, set `num_concurrent` > 1." ) self._concurrent = int(num_concurrent) - self.tokenizer_backend = tokenizer_backend + self.tokenizer_backend = ( + None if tokenizer_backend in ("None", "none") else tokenizer_backend + ) self.add_bos_token = add_bos_token self.custom_prefix_token_id = custom_prefix_token_id self.tokenized_requests = tokenized_requests -- GitLab From 0ef7548d7c3f01108e7c12900a5e5eb4b4a668f7 Mon Sep 17 00:00:00 2001 From: Rima Shahbazyan <74137119+rimashahbazyan@users.noreply.github.com> Date: Tue, 26 Nov 2024 18:53:59 +0400 Subject: [PATCH 164/194] Score tasks (#2452) * score readme added * generate until task's "until" parameter's default value fixed. * score mmlu-pro and agieval added * changed macro accuracy to micro for agieval * Always E removed from agi eval * redundancies removed * MATH added * minor cosmetic changes for math * Licenses added Readme updated * changes for flake8 + license header on math * Score added to readme and precommit was run. * Score added to readme and precommit was run. * Import error fixed * math task bugfix postprocess minor fix * CR for math added * math CR * math task bugfix postprocess minor fix CR for math added * Math cr fixed * reverting the default "until" parameter change and adjusting score task configs --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/score/README.md | 89 +++ ...ion_order_robustness_agieval_aqua_rat.yaml | 47 ++ ...on_order_robustness_agieval_logiqa_en.yaml | 17 + ...tion_order_robustness_agieval_lsat_ar.yaml | 17 + ...tion_order_robustness_agieval_lsat_lr.yaml | 17 + ...tion_order_robustness_agieval_lsat_rc.yaml | 17 + ...ption_order_robustness_agieval_sat_en.yaml | 17 + ...ion_order_robustness_agieval_sat_math.yaml | 17 + .../prompt_robustness_agieval_aqua_rat.yaml | 65 ++ .../prompt_robustness_agieval_logiqa_en.yaml | 17 + .../prompt_robustness_agieval_lsat_rc.yaml | 17 + .../prompt_robustness_agieval_lstat_ar.yaml | 17 + .../prompt_robustness_agieval_lstat_lr.yaml | 17 + .../prompt_robustness_agieval_sat_en.yaml | 17 + .../prompt_robustness_agieval_sat_math.yaml | 17 + .../score/agi_eval/prompt_templates.json | 52 ++ ...score_option_order_robustness_agieval.yaml | 42 ++ .../score_prompt_robustness_agieval.yaml | 60 ++ .../agi_eval/score_robustness_agieval.yaml | 20 + lm_eval/tasks/score/agi_eval/utils_agieval.py | 183 +++++ lm_eval/tasks/score/math/math_grader.py | 654 ++++++++++++++++++ .../math/prompt_robustness_math_algebra.yaml | 66 ++ ...mpt_robustness_math_counting_and_prob.yaml | 17 + .../math/prompt_robustness_math_geometry.yaml | 17 + ..._robustness_math_intermediate_algebra.yaml | 17 + .../prompt_robustness_math_num_theory.yaml | 17 + .../prompt_robustness_math_prealgebra.yaml | 17 + .../math/prompt_robustness_math_precalc.yaml | 17 + .../tasks/score/math/prompt_templates.json | 35 + .../math/score_prompt_robustness_math.yaml | 60 ++ .../score/math/score_robustness_math.yaml | 19 + .../score/math/to_be_fixed_questions.json | 57 ++ lm_eval/tasks/score/math/utils_math.py | 235 +++++++ .../score/mmlu_pro/prompt_templates.json | 51 ++ ...core_option_order_robustness_mmlu_pro.yaml | 67 ++ .../score_prompt_robustness_mmlu_pro.yaml | 67 ++ .../tasks/score/mmlu_pro/utils_mmlu_pro.py | 164 +++++ lm_eval/tasks/score/score_robustness.yaml | 21 + lm_eval/tasks/score/utils.py | 263 +++++++ 40 files changed, 2624 insertions(+) create mode 100644 lm_eval/tasks/score/README.md create mode 100644 lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_aqua_rat.yaml create mode 100644 lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_logiqa_en.yaml create mode 100644 lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_ar.yaml create mode 100644 lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_lr.yaml create mode 100644 lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_rc.yaml create mode 100644 lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_sat_en.yaml create mode 100644 lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_sat_math.yaml create mode 100644 lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_aqua_rat.yaml create mode 100644 lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_logiqa_en.yaml create mode 100644 lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lsat_rc.yaml create mode 100644 lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lstat_ar.yaml create mode 100644 lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lstat_lr.yaml create mode 100644 lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_sat_en.yaml create mode 100644 lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_sat_math.yaml create mode 100644 lm_eval/tasks/score/agi_eval/prompt_templates.json create mode 100644 lm_eval/tasks/score/agi_eval/score_option_order_robustness_agieval.yaml create mode 100644 lm_eval/tasks/score/agi_eval/score_prompt_robustness_agieval.yaml create mode 100644 lm_eval/tasks/score/agi_eval/score_robustness_agieval.yaml create mode 100644 lm_eval/tasks/score/agi_eval/utils_agieval.py create mode 100644 lm_eval/tasks/score/math/math_grader.py create mode 100644 lm_eval/tasks/score/math/prompt_robustness_math_algebra.yaml create mode 100644 lm_eval/tasks/score/math/prompt_robustness_math_counting_and_prob.yaml create mode 100644 lm_eval/tasks/score/math/prompt_robustness_math_geometry.yaml create mode 100644 lm_eval/tasks/score/math/prompt_robustness_math_intermediate_algebra.yaml create mode 100644 lm_eval/tasks/score/math/prompt_robustness_math_num_theory.yaml create mode 100644 lm_eval/tasks/score/math/prompt_robustness_math_prealgebra.yaml create mode 100644 lm_eval/tasks/score/math/prompt_robustness_math_precalc.yaml create mode 100644 lm_eval/tasks/score/math/prompt_templates.json create mode 100644 lm_eval/tasks/score/math/score_prompt_robustness_math.yaml create mode 100644 lm_eval/tasks/score/math/score_robustness_math.yaml create mode 100644 lm_eval/tasks/score/math/to_be_fixed_questions.json create mode 100644 lm_eval/tasks/score/math/utils_math.py create mode 100644 lm_eval/tasks/score/mmlu_pro/prompt_templates.json create mode 100644 lm_eval/tasks/score/mmlu_pro/score_option_order_robustness_mmlu_pro.yaml create mode 100644 lm_eval/tasks/score/mmlu_pro/score_prompt_robustness_mmlu_pro.yaml create mode 100644 lm_eval/tasks/score/mmlu_pro/utils_mmlu_pro.py create mode 100644 lm_eval/tasks/score/score_robustness.yaml create mode 100644 lm_eval/tasks/score/utils.py diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 390f3049..62e65a1e 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -101,6 +101,7 @@ | [race](race/README.md) | Reading comprehension assessment tasks based on English exams in China. | English | | realtoxicityprompts | Tasks to evaluate language models for generating text with potential toxicity. | | | [sciq](sciq/README.md) | Science Question Answering tasks to assess understanding of scientific concepts. | English | +| [score](score/README.md) | Systematic consistency and robustness evaluation for LLMs on 3 datasets(MMLU-Pro, Agi Eval and MATH) | English | | [scrolls](scrolls/README.md) | Tasks that involve long-form reading comprehension across various domains. | English | | [siqa](siqa/README.md) | Social Interaction Question Answering to evaluate common sense and social reasoning. | English | | [spanish_bench](spanish_bench/README.md) | Collection of tasks in Spanish encompassing various evaluation areas. | Spanish | diff --git a/lm_eval/tasks/score/README.md b/lm_eval/tasks/score/README.md new file mode 100644 index 00000000..4055d5f7 --- /dev/null +++ b/lm_eval/tasks/score/README.md @@ -0,0 +1,89 @@ +``` +Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +```` +# SCORE: Systematic COnsistency and Robustness Evaluation for Large Language Models + + +## Citation +```bib +[Citation placeholder] +``` + +## Groups + +- `score_robustness_mmlu_pro`: two 0-shot robutstness tasks on MMLU-PRO dataset [[1](#mmlu_pro)] + +- `score_robustness_agieval`: two 0-shot robutstness tasks on the AGIEVAL datasets [[2](#agi_eval)] multiple choice questions subsets: `'agieval-sat-math'`, `'agieval-lsat-lr'`, `'agieval-lsat-rc'`, `'agieval-logiqa-en'`, `'agieval-aqua-rat'`, `'agieval-sat-en'`, `'agieval-lsat-ar'` + +- `score_robustness_math`: one 0-shot robutstness tasks on Hendryk's MATH dataset [[3](#math)] + +## Tasks + +Both `score_robustness_mmlu_pro` and `score_robustness_agieval` contain the following 2 tasks: + +* Option order robustness: +`score_option_order_robustness_mmlu_pro`, +`score_option_order_robustness_agieval` + +* Prompt robustness: +`score_prompt_robustness_mmlu_pro`, +`score_prompt_robustness_agieval`, + +Whereas math contains only +* Prompt robustness: +`score_prompt_robustness_math` + + +### Option order robustness + +Measures the model's robustness to the placement of the correct answer in the options list by swapping the correct answer with all the other possible options. + +### Prompt robustness + +Measures the model's robustness to 10 different prompts. list of the prompts can be found in the `./prompt_templates.json` file under the key `prompt_robustness`. + + +## Metrics + +All robustness tasks calculate 2 metrics: *Accuracy* and *Consistency Rate(CR)* [[4](#cr)]. + +$CR = \frac{1}{|Q|} \sum_{Q_k \in Q} \sum_{y_i \in Y_k} \sum_{\substack{y_j \in Y_k \\ j \neq i}}\frac{\text{sim}(y_i, y_j)}{\binom{|Y_k|}{2}}$ + +## Notes + +- All tasks are designed for **Instruct** models for which we recommend to pass "`--apply_chat_template`" flag. + + +## References +[1] Wang, et al. "Mmlu-pro: A more robust and challenging multi-task language understanding benchmark." arXiv preprint arXiv:2406.01574 (2024). + +[2] Zhong, et al. "Agieval: A human-centric benchmark for evaluating foundation models." arXiv preprint arXiv:2304.06364 (2023). + +[3] Hendrycks et al. "Measuring Mathematical Problem Solving With the MATH Dataset." arXiv:2103.03874 (2021). + +[4] Yukun et al. "Improving the robustness of large language models via consistency alignment." arXiv:2403.14221 (2024). + +## Checklist + +For adding novel benchmarks/datasets to the library: +* [-] Is the task an existing benchmark in the literature? + * [-] Have you referenced the original paper that introduced the task? - Will be referenced as soon as the paper is published + * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [x] Is the "Main" variant of this task clearly denoted? +* [x] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [x] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_aqua_rat.yaml b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_aqua_rat.yaml new file mode 100644 index 00000000..ebe12f72 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_aqua_rat.yaml @@ -0,0 +1,47 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +task: option_order_robustness_agieval_aqua_rat +dataset_path: hails/agieval-aqua-rat +dataset_name: default +output_type: generate_until +test_split: test +process_docs: !function utils_agieval.option_order_robustness_process_docs +doc_to_text: !function utils_agieval.agi_eval_robustness_doc_to_text +doc_to_target: answer +generation_kwargs: + until: [] + max_gen_toks: 1024 + do_sample: False +process_results: !function utils_agieval.option_order_robustness_process_results +metric_list: + - metric: per_option_accuracy_A + aggregation: !function utils_agieval.per_option_accuracy_a + higher_is_better: true + - metric: per_option_accuracy_B + aggregation: !function utils_agieval.per_option_accuracy_b + higher_is_better: true + - metric: per_option_accuracy_C + aggregation: !function utils_agieval.per_option_accuracy_c + higher_is_better: true + - metric: per_option_accuracy_D + aggregation: !function utils_agieval.per_option_accuracy_d + higher_is_better: true + - metric: options_consistency_rate + aggregation: !function utils_agieval.options_consistency_rate + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_logiqa_en.yaml b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_logiqa_en.yaml new file mode 100644 index 00000000..7d9f7d54 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_logiqa_en.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: option_order_robustness_agieval_aqua_rat.yaml +task: option_order_robustness_agieval_logiqa_en +dataset_path: hails/agieval-logiqa-en diff --git a/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_ar.yaml b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_ar.yaml new file mode 100644 index 00000000..1d897edb --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_ar.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: option_order_robustness_agieval_aqua_rat.yaml +task: option_order_robustness_agieval_lsat_ar +dataset_path: hails/agieval-lsat-ar diff --git a/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_lr.yaml b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_lr.yaml new file mode 100644 index 00000000..27dca849 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_lr.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: option_order_robustness_agieval_aqua_rat.yaml +task: option_order_robustness_agieval_lsat_lr +dataset_path: hails/agieval-lsat-lr diff --git a/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_rc.yaml b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_rc.yaml new file mode 100644 index 00000000..f476a079 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_lsat_rc.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: option_order_robustness_agieval_aqua_rat.yaml +task: option_order_robustness_agieval_lsat_rc +dataset_path: hails/agieval-lsat-rc diff --git a/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_sat_en.yaml b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_sat_en.yaml new file mode 100644 index 00000000..4b90fd20 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_sat_en.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: option_order_robustness_agieval_aqua_rat.yaml +task: option_order_robustness_agieval_sat_en +dataset_path: hails/agieval-sat-en diff --git a/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_sat_math.yaml b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_sat_math.yaml new file mode 100644 index 00000000..3b0d82e8 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/option_order_robustness_agieval_sat_math.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: option_order_robustness_agieval_aqua_rat.yaml +task: option_order_robustness_agieval_sat_math +dataset_path: hails/agieval-sat-math diff --git a/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_aqua_rat.yaml b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_aqua_rat.yaml new file mode 100644 index 00000000..1eac4eae --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_aqua_rat.yaml @@ -0,0 +1,65 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +task: prompt_robustness_agieval_aqua_rat +dataset_path: hails/agieval-aqua-rat +dataset_name: default +output_type: generate_until +test_split: test +process_docs: !function utils_agieval.prompt_robustness_process_docs +doc_to_text: !function utils_agieval.agi_eval_robustness_doc_to_text +doc_to_target: answer +generation_kwargs: + until: [] + max_gen_toks: 1024 + do_sample: False +process_results: !function utils_agieval.prompt_robustness_process_results +metric_list: + - metric: 0_accuracy + aggregation: !function utils_agieval.per_prompt_accuracy_0 + higher_is_better: true + - metric: 1_accuracy + aggregation: !function utils_agieval.per_prompt_accuracy_1 + higher_is_better: true + - metric: 2_accuracy + aggregation: !function utils_agieval.per_prompt_accuracy_2 + higher_is_better: true + - metric: 3_accuracy + aggregation: !function utils_agieval.per_prompt_accuracy_3 + higher_is_better: true + - metric: 4_accuracy + aggregation: !function utils_agieval.per_prompt_accuracy_4 + higher_is_better: true + - metric: 5_accuracy + aggregation: !function utils_agieval.per_prompt_accuracy_5 + higher_is_better: true + - metric: 6_accuracy + aggregation: !function utils_agieval.per_prompt_accuracy_6 + higher_is_better: true + - metric: 7_accuracy + aggregation: !function utils_agieval.per_prompt_accuracy_7 + higher_is_better: true + - metric: 8_accuracy + aggregation: !function utils_agieval.per_prompt_accuracy_8 + higher_is_better: true + - metric: 9_accuracy + aggregation: !function utils_agieval.per_prompt_accuracy_9 + higher_is_better: true + - metric: consistency_rate + aggregation: !function utils_agieval.agi_eval_prompt_consistency_rate + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_logiqa_en.yaml b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_logiqa_en.yaml new file mode 100644 index 00000000..417998c6 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_logiqa_en.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_agieval_aqua_rat.yaml +task: prompt_robustness_agieval_logiqa_en +dataset_path: hails/agieval-logiqa-en diff --git a/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lsat_rc.yaml b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lsat_rc.yaml new file mode 100644 index 00000000..4c4a749a --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lsat_rc.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_agieval_aqua_rat.yaml +task: prompt_robustness_agieval_lsat_rc +dataset_path: hails/agieval-lsat-rc diff --git a/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lstat_ar.yaml b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lstat_ar.yaml new file mode 100644 index 00000000..9c69244d --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lstat_ar.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_agieval_aqua_rat.yaml +task: prompt_robustness_agieval_lsat_ar +dataset_path: hails/agieval-lsat-ar diff --git a/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lstat_lr.yaml b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lstat_lr.yaml new file mode 100644 index 00000000..3add875c --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_lstat_lr.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_agieval_aqua_rat.yaml +task: prompt_robustness_agieval_lsat_lr +dataset_path: hails/agieval-lsat-lr diff --git a/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_sat_en.yaml b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_sat_en.yaml new file mode 100644 index 00000000..5f6a7854 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_sat_en.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_agieval_aqua_rat.yaml +task: prompt_robustness_agieval_sat_en +dataset_path: hails/agieval-sat-en diff --git a/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_sat_math.yaml b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_sat_math.yaml new file mode 100644 index 00000000..65af591e --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/prompt_robustness_agieval_sat_math.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_agieval_aqua_rat.yaml +task: prompt_robustness_agieval_sat_math +dataset_path: hails/agieval-sat-math diff --git a/lm_eval/tasks/score/agi_eval/prompt_templates.json b/lm_eval/tasks/score/agi_eval/prompt_templates.json new file mode 100644 index 00000000..720a6635 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/prompt_templates.json @@ -0,0 +1,52 @@ +{ + "option_order_robustness":{ + "prompt": "For the multiple-choice question, which option (A-E) is correct?.\n\nQuestion: {question}{options}\n\nEnd the answer with the following:\nThe best answer is (the_answer_letter) where the (the_answer_letter) is one of 'A', 'B', 'C', 'D' or 'E'.", + "options_format": "\n{letter}: {option}" + }, + + + "prompt_robustness":[ + { + "prompt": "{question}{options}\nExamine the question and choose the correct answer from the options 'A', 'B', 'C', 'D' or 'E'. End your answer with:\nThe best answer is [the_answer_letter].\nwhere the [the_answer_letter] is a letter from A to E.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "{question}{options}\nAnswer the multiple-choice question by selecting the correct option from A to E. Always conclude with 'The best answer is (answer_letter)' where the (answer_letter) is one of A, B, C, D, E.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "You must reply with only a single letter from A, B, C, D or E to this question. Conclude with:\nThe best answer is answer_letter where the answer_letter is a single letter from A to E.\n{question}{options}", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "From the options A-E, select the correct answer to the following question. End the answer with - The best answer is answer_letter, where answer_letter is one of A, B, C, D or E.\nQuestion: {question}{options}", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "For the multiple-choice question, which option (A-E) is correct?.\n\nQuestion:{question}{options}\nEnd the answer with the following:\nThe best answer is (the_answer_letter) where the (the_answer_letter) is one of 'A', 'B', 'C', 'D' or 'E'.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "Evaluate the multiple-choice question and select the most fitting response from 'A', 'B', 'C', 'D', 'E'. \nQuestion:{question}{options}\nAlways conclude with:\nThe best answer is [the_answer_letter].\nwhere the [the_answer_letter] is one of A, B, C, D or E.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "Answer to the following question by selecting the correct option A, B, C, D or E. {question}{options}\nThe answer should end with:\nThe best answer is [the_answer_letter] where [the_answer_letter] is one of letters A to E. Let's think step by step.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "Select the correct answer from the options 'A', 'B', 'C', 'D', 'E' for the question provided below. Conclude by stating: The best answer is answer_letter where answer_letter is one of 'A', 'B', 'C', 'D' or 'E'.\nQuestion: {question}{options}\nLet's think step by step.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "{question}{options}\nFor this question with 10 possible answers A, B, C, D, E, choose the one that answers the question. If the problem is simple or straightforward, just provide the answer. If the answer is more complex, use a step-by-step approach and for each step briefly explain your reasoning. Always conclude with 'The best answer is (answer_letter)' where the (answer_letter) is one of 'A', 'B', 'C', 'D', 'E'. Let's think step by step.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "Read the question and options below, then determine the correct answer choice (A-E)\nQuestion: {question}{options}\n\nFor simple questions, provide a quick answer. For complicated ones, think step by step, break down the question into smaller problems and reach to a conclusion\nEnd your answer by stating:\nThe best answer is [the_answer_letter].\nwhere [the_answer_letter] is one of A, B, C, D or E.", + "options_format": "\n{letter}: {option}" + } + + ] + +} diff --git a/lm_eval/tasks/score/agi_eval/score_option_order_robustness_agieval.yaml b/lm_eval/tasks/score/agi_eval/score_option_order_robustness_agieval.yaml new file mode 100644 index 00000000..f27cc1dd --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/score_option_order_robustness_agieval.yaml @@ -0,0 +1,42 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +group: score_option_order_robustness_agieval +task: + - option_order_robustness_agieval_aqua_rat + - option_order_robustness_agieval_logiqa_en + - option_order_robustness_agieval_lsat_ar + - option_order_robustness_agieval_lsat_lr + - option_order_robustness_agieval_lsat_rc + - option_order_robustness_agieval_sat_en + - option_order_robustness_agieval_sat_math + +aggregate_metric_list: + - metric: per_option_accuracy_A + aggregation: mean + weight_by_size: true + - metric: per_option_accuracy_B + aggregation: mean + weight_by_size: true + - metric: per_option_accuracy_C + aggregation: mean + weight_by_size: true + - metric: per_option_accuracy_D + aggregation: mean + weight_by_size: truez + - metric: options_consistency_rate + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/score/agi_eval/score_prompt_robustness_agieval.yaml b/lm_eval/tasks/score/agi_eval/score_prompt_robustness_agieval.yaml new file mode 100644 index 00000000..36b5376e --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/score_prompt_robustness_agieval.yaml @@ -0,0 +1,60 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +group: score_prompt_robustness_agieval +task: + - prompt_robustness_agieval_aqua_rat + - prompt_robustness_agieval_logiqa_en + - prompt_robustness_agieval_lsat_ar + - prompt_robustness_agieval_lsat_lr + - prompt_robustness_agieval_lsat_rc + - prompt_robustness_agieval_sat_en + - prompt_robustness_agieval_sat_math + +aggregate_metric_list: + - metric: 0_accuracy + aggregation: mean + weight_by_size: true + - metric: 1_accuracy + aggregation: mean + weight_by_size: true + - metric: 2_accuracy + aggregation: mean + weight_by_size: true + - metric: 3_accuracy + aggregation: mean + weight_by_size: true + - metric: 4_accuracy + aggregation: mean + weight_by_size: true + - metric: 5_accuracy + aggregation: mean + weight_by_size: true + - metric: 6_accuracy + aggregation: mean + weight_by_size: true + - metric: 7_accuracy + aggregation: mean + weight_by_size: true + - metric: 8_accuracy + aggregation: mean + weight_by_size: true + - metric: 9_accuracy + aggregation: mean + weight_by_size: true + - metric: consistency_rate + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/score/agi_eval/score_robustness_agieval.yaml b/lm_eval/tasks/score/agi_eval/score_robustness_agieval.yaml new file mode 100644 index 00000000..354cb567 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/score_robustness_agieval.yaml @@ -0,0 +1,20 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +group: score_robustness_agieval +task: + - score_prompt_robustness_agieval + - score_option_order_robustness_agieval +metadata: + version: 1.0 diff --git a/lm_eval/tasks/score/agi_eval/utils_agieval.py b/lm_eval/tasks/score/agi_eval/utils_agieval.py new file mode 100644 index 00000000..b8034259 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/utils_agieval.py @@ -0,0 +1,183 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +import re +from functools import partial +from typing import Any, Dict, List + +import numpy as np +from datasets import Dataset + +from lm_eval.tasks.score import utils +from lm_eval.tasks.score.utils import prompt_consistency_rate, robustness_doc_to_text +from lm_eval.utils import eval_logger + + +TEMPLATE_FILE_PATH = os.path.join(os.path.dirname(__file__), "prompt_templates.json") + +PROMPT_ROBUSTNESS_TEMPLATE_KEY = "prompt_robustness" +OPTION_ORDER_ROBUSTNESS_TEMPLATE_KEY = "option_order_robustness" + +QUESTION_KEY = "query" +ANSWER_INDEX_KEY = "gold" +OPTIONS_KEY = "choices" + +LABELS = ["A", "B", "C", "D", "E"] + +agi_eval_prompt_consistency_rate = prompt_consistency_rate +agi_eval_robustness_doc_to_text = robustness_doc_to_text + + +def initial_process_docs(doc: Dataset) -> Dataset: + """ + add question_id to the documents + """ + + bracket_pattern = r"^\([A-E]\)" + letter_space = r"^[A-E] " + letter_question_space = r"^[A-E]\? " + + def __process(_doc, idx): + if "question" not in _doc: + question = _doc[QUESTION_KEY].split(" Answer Choices:")[0] + if question.startswith("Q: "): + question = question[3:] + _doc["question"] = question + if "question_id" not in _doc: + _doc["question_id"] = idx + if "answer_index" not in _doc: + _doc["answer_index"] = _doc[ANSWER_INDEX_KEY][0] + if "answer" not in _doc: + _doc["answer"] = LABELS[_doc["answer_index"]] + if "options" not in _doc: + prepared_options = [] + for option in _doc[OPTIONS_KEY]: + if re.match(bracket_pattern, option): + prepared_options.append(option[3:]) + elif re.match(letter_space, option): + prepared_options.append(option[2:]) + elif re.match(letter_question_space, option): + prepared_options.append(option[3:]) + else: + prepared_options.append(option) + _doc["options"] = prepared_options + return _doc + + return doc.map(__process, with_indices=True) + + +prompt_robustness_process_docs = partial( + utils.process_docs_add_prompts, + templates_key=PROMPT_ROBUSTNESS_TEMPLATE_KEY, + template_file_path=TEMPLATE_FILE_PATH, + dataset_specific_preprocess=initial_process_docs, +) + +option_order_robustness_process_docs = partial( + utils.option_order_robustness_process_docs, + template_file_path=TEMPLATE_FILE_PATH, + templates_key=OPTION_ORDER_ROBUSTNESS_TEMPLATE_KEY, + labels=LABELS[:-1], + dataset_specific_preprocess=initial_process_docs, +) + + +def prompt_robustness_process_results(doc, results) -> Dict[str, float]: + final_answer = utils.__postprocess_pred(results[0]) + final_answer = utils.translate_model_answer_to_labels( + final_answer, option_format=doc["options_format"], labels=LABELS + ) + gt = LABELS[doc["answer_index"]] + prompt_id = doc["prompt_id"] + question_id = doc["question_id"] + return { + f"{prompt_id}_accuracy": (question_id, prompt_id, final_answer, gt), + "consistency_rate": (question_id, prompt_id, final_answer, gt), + } + + +def option_order_robustness_process_results(doc, results) -> Dict[str, float]: + final_answer = utils.__postprocess_pred(results[0]) + final_answer = utils.translate_model_answer_to_labels( + final_answer, option_format=doc["options_format"], labels=LABELS + ) + gt = LABELS[doc["answer_index"]] + always_same_option = doc["always_same_option"] + question_id = doc["question_id"] + original_answer_index = doc["original_answer_index"] + answer_index = (doc["answer_index"],) + return { + f"per_option_accuracy_{always_same_option}": ( + question_id, + always_same_option, + final_answer, + gt, + ), + "options_consistency_rate": ( + question_id, + always_same_option, + final_answer, + original_answer_index, + answer_index, + ), + } + + +def per_prompt_accuracy(results: List[Dict[str, Any]], p_id=0) -> float: + accuracies = [] + for result in results: + question_id, prompt_id, final_answer, gt = result + if prompt_id != p_id: + continue + accuracies.append(final_answer == gt) + + accuracie = sum(accuracies) / len(accuracies) + eval_logger.info(f"Prompt - {prompt_id} accuracy: {accuracie}") + + return np.round(accuracie, 4) + + +per_prompt_accuracy_0 = partial(per_prompt_accuracy, p_id=0) +per_prompt_accuracy_1 = partial(per_prompt_accuracy, p_id=1) +per_prompt_accuracy_2 = partial(per_prompt_accuracy, p_id=2) +per_prompt_accuracy_3 = partial(per_prompt_accuracy, p_id=3) +per_prompt_accuracy_4 = partial(per_prompt_accuracy, p_id=4) +per_prompt_accuracy_5 = partial(per_prompt_accuracy, p_id=5) +per_prompt_accuracy_6 = partial(per_prompt_accuracy, p_id=6) +per_prompt_accuracy_7 = partial(per_prompt_accuracy, p_id=7) +per_prompt_accuracy_8 = partial(per_prompt_accuracy, p_id=8) +per_prompt_accuracy_9 = partial(per_prompt_accuracy, p_id=9) + + +def per_option_accuracy(results: List[Dict[str, Any]], always_opt="a") -> float: + accuracies = [] + for result in results: + question_id, always_same_option, final_answer, gt = result + if always_opt != always_same_option: + continue + accuracies.append(int(final_answer == gt)) + + accuracie = sum(accuracies) / len(accuracies) + eval_logger.info(f"Prompt - {always_opt.upper()} accuracy: {accuracie}") + + return np.round(accuracie, 4) + + +per_option_accuracy_a = partial(per_option_accuracy, always_opt="A") +per_option_accuracy_b = partial(per_option_accuracy, always_opt="B") +per_option_accuracy_c = partial(per_option_accuracy, always_opt="C") +per_option_accuracy_d = partial(per_option_accuracy, always_opt="D") + +options_consistency_rate = partial(utils.options_consistency_rate, labels=LABELS) diff --git a/lm_eval/tasks/score/math/math_grader.py b/lm_eval/tasks/score/math/math_grader.py new file mode 100644 index 00000000..156e739e --- /dev/null +++ b/lm_eval/tasks/score/math/math_grader.py @@ -0,0 +1,654 @@ +# Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Copyright (c) Microsoft Corporation. +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the "Software"), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in all +# copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +# SOFTWARE + +# Copyright (c) 2023 OpenAI +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the "Software"), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: + +# The above copyright notice and this permission notice shall be included in all +# copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +# SOFTWARE. + +# Copyright (c) 2021 Dan Hendrycks +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the "Software"), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in all +# copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +# SOFTWARE. + + +""" +This logic is largely copied from the Hendrycks' MATH release (math_equivalence), and borrowed from: +- https://github.com/microsoft/ToRA/blob/main/src/eval/grader.py +- https://github.com/microsoft/ProphetNet/tree/master/CRITIC +- https://github.com/openai/prm800k +""" + +import contextlib +import re +import signal +from importlib.metadata import PackageNotFoundError, version +from math import isclose +from typing import Union + + +def _check_antlr_version(): + "Function for checking the antlr package version." + # Check antlr version + PACKAGE_NAME = "antlr4-python3-runtime" + REQUIRED_VERSION = "4.11.0" + + try: + installed_version = version(PACKAGE_NAME) + if installed_version != REQUIRED_VERSION: + raise RuntimeError( + f"Package {PACKAGE_NAME} version mismatch: {installed_version} (required: {REQUIRED_VERSION})" + ) + except PackageNotFoundError: + raise RuntimeError( + f"Package {PACKAGE_NAME} not found. Please install antlr4-python3-runtime==4.11.0." + ) + + +def _fix_fracs(string): + # replacing all extra spaces + while "\\frac " in string: + string = string.replace("\\frac ", "\\frac") + substrs = string.split("\\frac") + new_str = substrs[0] + if len(substrs) > 1: + substrs = substrs[1:] + for substr in substrs: + new_str += "\\frac" + if len(substr) > 0 and substr[0] == "{": + new_str += substr + else: + try: + assert len(substr) >= 2 + except AssertionError: + return string + a = substr[0] + b = substr[1] + if b != "{": + if len(substr) > 2: + post_substr = substr[2:] + new_str += "{" + a + "}{" + b + "}" + post_substr + else: + new_str += "{" + a + "}{" + b + "}" + else: + if len(substr) > 2: + post_substr = substr[2:] + new_str += "{" + a + "}" + b + post_substr + else: + new_str += "{" + a + "}" + b + string = new_str + return string + + +def _str_is_int(x: str) -> bool: + try: + x = _strip_properly_formatted_commas(x) + x = float(x) + return abs(x - int(round(x))) <= 1e-7 + except Exception: + return False + + +def _str_to_int(x: str) -> bool: + x = x.replace(",", "") + if "_" in x: + # Due to base + x = x.split("_")[0] + x = float(x) + return int(x) + + +def _inject_implicit_mixed_number(step: str): + """ + Automatically make a mixed number evalable + e.g. 7 3/4 => 7+3/4 + """ + p1 = re.compile("([0-9]) +([0-9])") + step = p1.sub("\\1+\\2", step) # implicit mults + return step + + +def _strip_properly_formatted_commas(expr: str): + # We want to be careful because we don't want to strip tuple commas + p1 = re.compile(r"(\d)(,)(\d\d\d)($|\D)") + while True: + next_expr = p1.sub("\\1\\3\\4", expr) + if next_expr == expr: + break + expr = next_expr + return next_expr + + +def _remove_right_units(expr): + # "\\text{ " only ever occurs (at least in the val set) when describing units + if "\\text" in expr: + try: + splits = re.split(r"\\text\s*{\s*", expr) + # print(splits) + assert len(splits) == 2 and splits[0] not in ("", "(") + return splits[0] + except AssertionError: + pass + + if "\\text{" in expr: + return re.sub(r"\\text{([^}]+)}", r"\1", expr) + elif "\\mbox{" in expr: + splits = expr.split("\\mbox{") + assert len(splits) == 2 + return splits[0] + else: + return expr + + +def _process_and_or_inside_text(string): + string = re.sub(r"\s*\\text{\s*(or|and)\s*}\s*", ",", string) + string = re.sub(r",\s*,", ",", string) + return string + + +def _remove_left_and_right(expr): + """Remove the right and left latex commands.""" + expr = re.sub(r"\\left", "", expr) + expr = re.sub(r"\\right", "", expr) + return expr + + +def _fix_sqrt(string): + _string = re.sub(r"\\sqrt(\s*\w+)", r"\\sqrt{\1}", string) + return _string + + +def _fix_interval(expr): + """Fix interval expression.""" + if "\\in " in expr: + return expr.split("\\in ")[1].strip() + + return expr + + +def _inject_implicit_mixed_fraction(step: str): + """ + Automatically make a mixed number evalable + e.g. 7 \\frac{3}{4} => 7+3/4 + """ + p1 = re.compile(r"(\d+) *\\frac{(\d+)}{(\d+)}") + + def replacer(match): + whole_part = match.group(1) + numerator = match.group(2) + denominator = match.group(3) + + if whole_part: + return f"{whole_part} + {numerator}/{denominator}" + else: + return f"{numerator}/{denominator}" + + step = p1.sub(replacer, step) + return step + + +def normalize_answer_string(expr: str) -> str: + """Normalize answer expressions.""" + if expr is None: + return None + + # Remove enclosing `\text{}`. + + expr = _remove_left_and_right(expr) + expr = _process_and_or_inside_text(expr) + expr = _remove_right_units(expr) + expr = _fix_interval(expr) + for surround_str in [ + "\\\\text", + "\\\\mathrm", + "\\\\mathcal", + "\\\\textbf", + "\\\\textit", + ]: + expr = expr.replace(surround_str, "") + pattern = f"^{surround_str}" + "\{(?P.+?)\}$" + m = re.search(pattern, expr) + if m is not None: + expr = m.group("text") + + expr = expr.replace("\!", "") + expr = expr.replace("\\%", "%") + expr = expr.replace("\\$", "$") + expr = expr.replace("$", "") + expr = expr.replace("%", "") + expr = expr.replace("^{\\circ}", "") + + expr = expr.replace(" or ", " , ") + expr = expr.replace(" and ", " , ") + + expr = expr.replace("million", "*10^6") + expr = expr.replace("billion", "*10^9") + expr = expr.replace("trillion", "*10^12") + + for unit in [ + "degree", + "cm", + "centimeter", + "meter", + "mile", + "second", + "minute", + "hour", + "week", + "month", + "year", + "foot", + "feet", + "inch", + "yard", + "p.m.", + "PM", + ]: + expr = re.sub(f"{unit}(es)?(s)? *(\^[0-9]+)?", "", expr) + + if "day" in expr: + days = [ + "Monday", + "Tuesday", + "Wednesday", + "Thursday", + "Friday", + "Saturday", + "Sunday", + ] + weekday_expressed = False + for day in days: + if day in expr: + weekday_expressed = True + break + + if not weekday_expressed: + expr = re.sub("day(s)?", "", expr) + + expr = re.sub("\^ *\\\\circ", "", expr) + + if len(expr) > 0 and expr[0] == "{" and expr[-1] == "}": + expr = expr[1:-1] + + expr = _fix_sqrt(expr) + + # \frac1b or \frac12 --> \frac{1}{b} and \frac{1}{2}, etc. Even works with \frac1{72} (but not \frac{72}1). Also does a/b --> \\frac{a}{b} + expr = _fix_fracs(expr) + + # edge case with mixed numbers and negative signs + expr = re.sub("- *", "-", expr) + expr = _inject_implicit_mixed_number(expr) + expr = _inject_implicit_mixed_fraction(expr) + expr = expr.replace(" ", "") + + if _str_is_int(expr): + expr = str(_str_to_int(expr)) + + return expr + + +def is_digit(s): + try: + if "{,}" in str(s): + num = float(str(s).replace("{,}", "")) + return True, num + + num = float(str(s).replace(",", "")) + return True, num + except ValueError: + return False, None + + +def normalize(answer) -> str: + # checking if answer is $ and removing $ in that case to compare + if isinstance(answer, str) and bool(re.match(r"\$\d+(\.\d+)?", answer)): + return answer[1:] + + # checking if answer is % or \\% and removing % + if isinstance(answer, str) and ( + bool(re.match(r"^\d+(\.\d+)?%$", answer)) + or bool(re.match(r"^\d+(\.\d+)?\\%$", answer)) + ): + return answer.replace("\\%", "").replace("%", "") + + return answer + + +def math_equal( + prediction: Union[bool, float, str], + reference: Union[float, str], + include_percentage: bool = True, + tolerance: float = 1e-4, + timeout: float = 10.0, +) -> bool: + """ + Exact match of math if and only if: + 1. numerical equal: both can convert to float and are equal + 2. symbolic equal: both can convert to sympy expression and are equal + """ + + # Check that the right antlr version is installed. + _check_antlr_version() + + from sympy.parsing.sympy_parser import parse_expr + + prediction = normalize(prediction) + reference = normalize(reference) + + # another round of normalization + prediction = normalize_answer_string(prediction) + reference = normalize_answer_string(reference) + + if ( + isinstance(prediction, str) and len(prediction) > 1000 + ): # handling weird corner-cases + prediction = prediction[:1000] + + # 0. string comparison + if isinstance(prediction, str) and isinstance(reference, str): + if prediction.strip().lower() == reference.strip().lower(): + return True + if prediction.replace(" ", "") == reference.replace(" ", ""): + return True + + try: # 1. numerical equal + if is_digit(prediction)[0] and is_digit(reference)[0]: + prediction = is_digit(prediction)[1] + reference = is_digit(reference)[1] + # number questions + if include_percentage: + gt_result = [reference / 100, reference, reference * 100] + else: + gt_result = [reference] + for item in gt_result: + try: + if isclose(item, prediction, rel_tol=tolerance): + return True + except Exception: + continue + return False + except Exception: + pass + + if not prediction and prediction not in [0, False]: + return False + + # 2. symbolic equal + reference = str(reference).strip() + prediction = str(prediction).strip() + + ## deal with [], (), {} + prediction = format_intervals(prediction) + + pred_str, ref_str = prediction, reference + if ( + prediction.startswith("[") + and prediction.endswith("]") + and not reference.startswith("(") + ) or ( + prediction.startswith("(") + and prediction.endswith(")") + and not reference.startswith("[") + ): + pred_str = pred_str.strip("[]()") + ref_str = ref_str.strip("[]()") + for s in ["{", "}", "(", ")"]: + ref_str = ref_str.replace(s, "") + pred_str = pred_str.replace(s, "") + if pred_str == ref_str: + return True + + ## [a, b] vs. [c, d], return a==c and b==d + if ( + prediction + and reference + and prediction[0] in "([" + and prediction[-1] in ")]" + and prediction[0] == reference[0] + and prediction[-1] == reference[-1] + ): + pred_parts = prediction[1:-1].split(",") + ref_parts = reference[1:-1].split(",") + if len(pred_parts) == len(ref_parts): + if all( + [ + math_equal(pred_pt, ref_pt, include_percentage, tolerance) + for pred_pt, ref_pt in zip(pred_parts, ref_parts) + ] + ): + return True + + if "," in prediction and "," in reference: + pred_parts = [item.strip() for item in prediction.split(",")] + ref_parts = [item.strip() for item in reference.split(",")] + + if len(pred_parts) == len(ref_parts): + if all( + [ + math_equal( + pred_parts[i], ref_parts[i], include_percentage, tolerance + ) + for i in range(len(pred_parts)) + ] + ): + return True + else: + return False + + # if we have point == tuple of values + if prediction.startswith("Point") and reference[0] == "(" and reference[-1] == ")": + pred_parts = prediction[prediction.find("(") + 1 : -1].split(",") + ref_parts = reference[1:-1].split(",") + if len(pred_parts) == len(ref_parts): + if all( + [ + math_equal(pred_pt, ref_pt, include_percentage, tolerance) + for pred_pt, ref_pt in zip(pred_parts, ref_parts) + ] + ): + return True + + # if reference is a matrix + if reference.startswith("\\begin{pmatrix}") and prediction.startswith("Matrix"): + try: + pred_matrix = parse_expr(prediction) + ref_matrix_items = reference.split()[1:-1:2] + if len(pred_matrix) == len(ref_matrix_items): + if all( + [ + math_equal(ref, pred, include_percentage, tolerance) + for ref, pred in zip(ref_matrix_items, pred_matrix) + ] + ): + return True + except Exception: + pass + + return symbolic_equal(prediction, reference, tolerance, timeout) + + +def symbolic_equal(a, b, tolerance, timeout=10.0): + import sympy + from sympy.parsing.latex import parse_latex + from sympy.parsing.sympy_parser import parse_expr + + def _parse(s): + for f in [parse_expr, parse_latex]: + try: + with time_limit(timeout): + return f(s) + except Exception: + pass + return s + + a = _parse(a) + b = _parse(b) + + try: + with time_limit(timeout): + if sympy.simplify(a - b) == 0: + return True + except Exception: + pass + + try: + with time_limit(timeout): + if isclose(sympy.N(a), sympy.N(b), rel_tol=tolerance): + return True + except Exception: + pass + return False + + +def extract_answer( + string: str, + extract_from_boxed: bool = True, + extract_regex: str = r"The final answer is (.+)$", +): + """Extract Answer String from \\boxed expression or based on regex""" + if not extract_from_boxed: + match = re.search(extract_regex, string) + if match: + return match.group(1) + return None + + if "\\boxed" not in string: + return None + + idx = string.rfind("\\boxed") + if idx < 0: + idx = string.rfind("\\fbox") + if idx < 0: + return None + + i = idx + right_brace_idx = None + num_left_braces_open = 0 + while i < len(string): + if string[i] == "{": + num_left_braces_open += 1 + if string[i] == "}": + num_left_braces_open -= 1 + if num_left_braces_open == 0: + right_brace_idx = i + break + i += 1 + + if right_brace_idx is None: + retval = None + else: + retval = string[idx : right_brace_idx + 1] + + if retval: + left = "\\boxed{" + try: + assert retval[: len(left)] == left + assert retval[-1] == "}" + return retval[len(left) : -1] + except AssertionError: + return None + + return None + + +class TimeoutException(Exception): + pass + + +@contextlib.contextmanager +def time_limit(seconds: float): + def signal_handler(signum, frame): + raise TimeoutException("Timed out!") + + signal.setitimer(signal.ITIMER_REAL, seconds) + signal.signal(signal.SIGALRM, signal_handler) + try: + yield + finally: + signal.setitimer(signal.ITIMER_REAL, 0) + + +def format_intervals(prediction): + patterns = { + "Interval(": r"^Interval\((.*)\)$", + "Interval.Ropen(": r"^Interval\.Ropen\((.*)\)$", + "Interval.Lopen(": r"^Interval\.Lopen\((.*)\)$", + "Interval.open(": r"^Interval\.open\((.*)\)$", + } + + for key, pattern in patterns.items(): + match = re.match(pattern, prediction) + if match: + inner_content = match.group(1) + + if key == "Interval(": # Intarval(a, b) == [a, b] + return f"[{inner_content}]" + elif key == "Interval.Ropen(": # Intarval.Ropen(a, b) == [a, b) + return f"[{inner_content})" + elif key == "Interval.Lopen(": # Intarval.Lopen(a, b) == (a, b] + return f"({inner_content}]" + elif key == "Interval.open(": # Intarval.open(a, b) == (a, b) + return f"({inner_content})" + + return prediction diff --git a/lm_eval/tasks/score/math/prompt_robustness_math_algebra.yaml b/lm_eval/tasks/score/math/prompt_robustness_math_algebra.yaml new file mode 100644 index 00000000..d5cb7b1b --- /dev/null +++ b/lm_eval/tasks/score/math/prompt_robustness_math_algebra.yaml @@ -0,0 +1,66 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +task: prompt_robustness_math_algebra +dataset_path: EleutherAI/hendrycks_math +process_docs: !function utils_math.prompt_robustness_process_docs +dataset_name: algebra +output_type: generate_until +test_split: test +doc_to_text: !function utils_math.math_robustness_doc_to_text +process_results: !function utils_math.process_results +doc_to_target: answer +generation_kwargs: + until: [] + do_sample: false + temperature: 0 + max_gen_toks: 1024 +metric_list: + - metric: 0_accuracy + aggregation: !function utils_math.per_prompt_accuracy_0 + higher_is_better: true + - metric: 1_accuracy + aggregation: !function utils_math.per_prompt_accuracy_1 + higher_is_better: true + - metric: 2_accuracy + aggregation: !function utils_math.per_prompt_accuracy_2 + higher_is_better: true + - metric: 3_accuracy + aggregation: !function utils_math.per_prompt_accuracy_3 + higher_is_better: true + - metric: 4_accuracy + aggregation: !function utils_math.per_prompt_accuracy_4 + higher_is_better: true + - metric: 5_accuracy + aggregation: !function utils_math.per_prompt_accuracy_5 + higher_is_better: true + - metric: 6_accuracy + aggregation: !function utils_math.per_prompt_accuracy_6 + higher_is_better: true + - metric: 7_accuracy + aggregation: !function utils_math.per_prompt_accuracy_7 + higher_is_better: true + - metric: 8_accuracy + aggregation: !function utils_math.per_prompt_accuracy_8 + higher_is_better: true + - metric: 9_accuracy + aggregation: !function utils_math.per_prompt_accuracy_9 + higher_is_better: true + - metric: consistency_rate + aggregation: !function utils_math.math_prompt_consistency_rate + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/score/math/prompt_robustness_math_counting_and_prob.yaml b/lm_eval/tasks/score/math/prompt_robustness_math_counting_and_prob.yaml new file mode 100644 index 00000000..6162fa99 --- /dev/null +++ b/lm_eval/tasks/score/math/prompt_robustness_math_counting_and_prob.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_math_algebra.yaml +dataset_name: counting_and_probability +task: prompt_robustness_math_counting_and_prob diff --git a/lm_eval/tasks/score/math/prompt_robustness_math_geometry.yaml b/lm_eval/tasks/score/math/prompt_robustness_math_geometry.yaml new file mode 100644 index 00000000..1ffa8438 --- /dev/null +++ b/lm_eval/tasks/score/math/prompt_robustness_math_geometry.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_math_algebra.yaml +dataset_name: geometry +task: prompt_robustness_math_geometry diff --git a/lm_eval/tasks/score/math/prompt_robustness_math_intermediate_algebra.yaml b/lm_eval/tasks/score/math/prompt_robustness_math_intermediate_algebra.yaml new file mode 100644 index 00000000..ce65abf5 --- /dev/null +++ b/lm_eval/tasks/score/math/prompt_robustness_math_intermediate_algebra.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_math_algebra.yaml +dataset_name: intermediate_algebra +task: prompt_robustness_math_intermediate_algebra diff --git a/lm_eval/tasks/score/math/prompt_robustness_math_num_theory.yaml b/lm_eval/tasks/score/math/prompt_robustness_math_num_theory.yaml new file mode 100644 index 00000000..fde98026 --- /dev/null +++ b/lm_eval/tasks/score/math/prompt_robustness_math_num_theory.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_math_algebra.yaml +dataset_name: number_theory +task: prompt_robustness_math_num_theory diff --git a/lm_eval/tasks/score/math/prompt_robustness_math_prealgebra.yaml b/lm_eval/tasks/score/math/prompt_robustness_math_prealgebra.yaml new file mode 100644 index 00000000..9387f7df --- /dev/null +++ b/lm_eval/tasks/score/math/prompt_robustness_math_prealgebra.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_math_algebra.yaml +dataset_name: prealgebra +task: prompt_robustness_math_prealgebra diff --git a/lm_eval/tasks/score/math/prompt_robustness_math_precalc.yaml b/lm_eval/tasks/score/math/prompt_robustness_math_precalc.yaml new file mode 100644 index 00000000..ca84fca7 --- /dev/null +++ b/lm_eval/tasks/score/math/prompt_robustness_math_precalc.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: prompt_robustness_math_algebra.yaml +dataset_name: precalculus +task: prompt_robustness_math_precalc diff --git a/lm_eval/tasks/score/math/prompt_templates.json b/lm_eval/tasks/score/math/prompt_templates.json new file mode 100644 index 00000000..072f5740 --- /dev/null +++ b/lm_eval/tasks/score/math/prompt_templates.json @@ -0,0 +1,35 @@ +{ + "prompt_robustness": [ + { + "prompt": "Efficiently solve the following math challenge. Explain your approach step-by-step\nThe answer should end with: The final answer is: $\\boxed{{answer}}$\nwhere [answer] is just the final number or expression that solves the problem\nProblem: {question}\nLets think step by step" + }, + { + "prompt": "You should solve this math problem.\nIf the problem is easy, provide a brief solution with little explanation.\nFor more difficult problems, follow this structured format\n## Step 1: [Brief description]\n[Simple explanation and calculations]\n\n## Step 2: [Brief description]\n[Simple explanation and calculations]\n\nRepeat steps until your reach a solution\n\nProblem: {question}\nEnd with:\nThe final answer is: $\\boxed{{answer}}$\nwhere [answer] is just the final number or expression that solves the problem." + }, + { + "prompt": "Solve this math problem. Your anwer should end with 'The final answer is: $\\boxed{{answer}}$' where [answer] is just the final number or expression that solves the problem\nProblem: {question}" + }, + { + "prompt": "Analyze and solve the math task.\nProblem: {question}\nEnd the answer with:\nThe final answer is: $\\boxed{{answer}}$ where [answer] is just the final number or expression that solves the problem." + }, + { + "prompt": "{question}\nFind the solution to this math problem. Your answer should end with - The final answer is: $\\boxed{{answer}}$\nwhere [answer] is just the final number or expression that solves the problem." + }, + { + "prompt": "Calculate the answer to this math problem\nProblem: {question}\nConclude your answer with:\nThe final answer is: $\\boxed{{answer}}$\nwhere [answer] is just the final number or expression that solves the problem." + }, + { + "prompt": "{question}\nPlease solve this math problem efficiently. Finish with: The final answer is: $\\boxed{{answer}}$ where [answer] is just the final number or expression that solves the problem." + }, + { + "prompt": "{question}\nSolve the following math problem\nShow each step of your solution\nConclude with:\nThe final answer is: $\\boxed{{answer}}$\nwhere [answer] is just the final number or expression that solves the problem\nLets think step by step" + }, + { + "prompt": "Find the answer to the following math question. Conclude with: 'The final answer is: $\\boxed{{answer}}$'\nwhere [answer] is just the final number or expression that solves the problem\nProblem: {question}" + }, + { + "prompt": "Please solve the math problem. For simple problems offer a quick solution with minimal details. For more challenging problems, explain your approach step-by-step. Finish with\nThe final answer is: $\\boxed{{answer}}$.\nwhere [answer] is just the final number or expression that solves the problem.\nProblem: {question}\nLets think step by step." + } + ] + +} diff --git a/lm_eval/tasks/score/math/score_prompt_robustness_math.yaml b/lm_eval/tasks/score/math/score_prompt_robustness_math.yaml new file mode 100644 index 00000000..b22e23b9 --- /dev/null +++ b/lm_eval/tasks/score/math/score_prompt_robustness_math.yaml @@ -0,0 +1,60 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +group: score_prompt_robustness_math +task: + - prompt_robustness_math_algebra + - prompt_robustness_math_counting_and_prob + - prompt_robustness_math_geometry + - prompt_robustness_math_intermediate_algebra + - prompt_robustness_math_num_theory + - prompt_robustness_math_prealgebra + - prompt_robustness_math_precalc + +aggregate_metric_list: + - metric: 0_accuracy + aggregation: mean + weight_by_size: true + - metric: 1_accuracy + aggregation: mean + weight_by_size: true + - metric: 2_accuracy + aggregation: mean + weight_by_size: true + - metric: 3_accuracy + aggregation: mean + weight_by_size: true + - metric: 4_accuracy + aggregation: mean + weight_by_size: true + - metric: 5_accuracy + aggregation: mean + weight_by_size: true + - metric: 6_accuracy + aggregation: mean + weight_by_size: true + - metric: 7_accuracy + aggregation: mean + weight_by_size: true + - metric: 8_accuracy + aggregation: mean + weight_by_size: true + - metric: 9_accuracy + aggregation: mean + weight_by_size: true + - metric: consistency_rate + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/score/math/score_robustness_math.yaml b/lm_eval/tasks/score/math/score_robustness_math.yaml new file mode 100644 index 00000000..f3b73366 --- /dev/null +++ b/lm_eval/tasks/score/math/score_robustness_math.yaml @@ -0,0 +1,19 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +group: score_robustness_math +task: + - score_prompt_robustness_math +metadata: + version: 1.0 diff --git a/lm_eval/tasks/score/math/to_be_fixed_questions.json b/lm_eval/tasks/score/math/to_be_fixed_questions.json new file mode 100644 index 00000000..020d07b9 --- /dev/null +++ b/lm_eval/tasks/score/math/to_be_fixed_questions.json @@ -0,0 +1,57 @@ +[ + { + "id": "test/prealgebra/1088.json", + "problem": "Simplify $(5x+3) - 2(2x-4)$.", + "answer": "x+11" + }, + { + "id": "test/algebra/1197.json", + "problem": "Two positive numbers $p$ and $q$ have the property that their sum is equal to their product. If their difference is $7$, what is $\\frac{1}{\\frac{1}{p^2}+\\frac{1}{q^2}}$? Your answer will be of the form $\\frac{a+b\\sqrt{c}}{d}$, where $a$ and $b$ don't both share the same common factor with $d$ and $c$ has no square as a factor. Find $a+b+c+d$.", + "answer": "161" + }, + { + "id": "test/geometry/66.json", + "problem": "Square $ABCD$ has side lengths of 13 units. Point $E$ lies in the interior of the square such that $AE = 5$ units and $BE = 12$ units. What is the distance from $E$ to side $AD$?", + "answer": "\\frac{25}{13}" + }, + { + "id": "test/geometry/1125.json", + "problem": "An aquarium has a rectangular base that measures 100 cm by 40 cm and has a height of 50 cm. The aquarium is filled with water to a depth of 37 cm. A rock with volume $1000 \\text{cm}^3$ is then placed in the aquarium and completely submerged. By how many centimeters does the water level rise? Express your answer as a decimal to the nearest 100th.", + "answer": "0.25\\text{ cm}" + }, + { + "id": "test/prealgebra/1407.json", + "problem": "What number must be placed in the box in the equation below to produce an equation that has more than one solution: \\[4x + 6 + 7x - 9 = 12x - 7 - x + \\boxed{\\phantom{2}}?\\]", + "answer": "4" + }, + { + "id": "test/prealgebra/224.json", + "problem": "I am going to buy exotic fruits. Dragonfruit costs $x-4$ dollars. Starfruit is five dollars less expensive than rambutan. Rambutan costs $2x$ dollars more than dragonfruit. How much does it cost to buy one rambutan, two starfruit, and three dragonfruit? Your answer will be an expression that depends on $x$.", + "answer": "-34 + 12x" + }, + { + "id": "test/prealgebra/177.json", + "problem": "Let $\\boxed{N}$ mean the number of whole number divisors of $N$. For example, $\\boxed{3}=2$, because $3$ has two divisors, $1$ and $3.$ Find the value of \\[\\boxed{\\boxed{11}\\times\\boxed{20}}\\]", + "answer": "12" + }, + { + "id": "test/number_theory/459.json", + "problem": "On a particular map, $3$ inches on the map equates to $10$ miles in real life. If you know that the real life distance between two buildings on the map is $53.25$ miles, what would the distance between the buildings be (in inches) on the map, expressed as a fraction?", + "answer": "\\frac{639}{40}" + }, + { + "id": "test/intermediate_algebra/702.json", + "problem": "Find the coordinates of either of the vertices of the hyperbola \\[16x^2+16x-4y^2-20y-85=0.\\](Enter your answer as an ordered pair. Enter the coordinates of one of the vertices, not both.)", + "answer": "\\left(-\\tfrac52, -\\tfrac52\\right)" + }, + { + "id": "test/intermediate_algebra/25.json", + "problem": "Find the coordinates of one of the foci of the hyperbola \\[x^2 - 10x = 4y^2 - 5.\\](Enter your answer as an ordered pair. Enter only one of the foci, not both.)", + "answer": "(0,0)" + }, + { + "id": "test/intermediate_algebra/747.json", + "problem": "The graph of $y = f(x)$ passes through the point $(-3,5).$ If $f(x)$ is an odd function, then what other point must the graph pass through? Enter your answer as an ordered pair.", + "answer": "(0,0)" + } +] diff --git a/lm_eval/tasks/score/math/utils_math.py b/lm_eval/tasks/score/math/utils_math.py new file mode 100644 index 00000000..cf41473a --- /dev/null +++ b/lm_eval/tasks/score/math/utils_math.py @@ -0,0 +1,235 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import json +import os +from functools import partial +from itertools import combinations +from typing import Any, Dict, List + +import datasets +import numpy as np + +from lm_eval.tasks.score import utils +from lm_eval.tasks.score.math.math_grader import ( + extract_answer, + math_equal, + normalize_answer_string, +) +from lm_eval.tasks.score.utils import robustness_doc_to_text +from lm_eval.utils import eval_logger + + +TEMPLATE_FILE_PATH = os.path.join(os.path.dirname(__file__), "prompt_templates.json") + +PROMPT_ROBUSTNESS_TEMPLATE_KEY = "prompt_robustness" + +math_robustness_doc_to_text = robustness_doc_to_text + + +def find_boxed_entries(answer_str): + stack = [] + results = [] + i = 0 + + while i < len(answer_str): + if answer_str[i : i + 7] == "\\boxed{": + stack.append(i + 7) + i += 7 + elif answer_str[i] == "{": + if stack: + stack.append(i + 1) + i += 1 + elif answer_str[i] == "}": + if stack: + start = stack.pop() + if not stack: + results.append(answer_str[start:i]) + i += 1 + else: + i += 1 + + if len(results) == 0: + raise ValueError("Not enough boxed entries") + else: + results = [normalize_answer_string(result) for result in results] + + if len(results) == 1: + # Single boxed entry, trivial case + return results + + else: + # Multiple boxed entries. There are two cases possible + # (a) The reference solution has the same question answered in multiple ways + # (b) The answer is split across multiple boxed entries and we need to merge + result_equal = True + for idx in range(len(results) - 1): + if not (results[idx] == results[idx + 1]): + result_equal = False + break + + if result_equal: + # Same problem solved in multiple ways + return [results[0]] + else: + return results + + +def extract_answer_dataset(solution: str, problem: str, corrected_answers: list) -> str: + entries = find_boxed_entries(solution) + + if len(entries) == 1: + parsed_answer = entries[0] + + if len(entries) > 1: + for item in corrected_answers: + if item["problem"] == problem: + parsed_answer = item["answer"] + break + else: + parsed_answer = ", ".join(entries) + + if not ( + ("Find the equation" in problem) + or ("Enter the equation" in problem) + or ("What is the equation" in problem) + or ("described by the equation" in problem) + or ("Find an equation" in problem) + ) and ("=" in parsed_answer): + if parsed_answer.count("=") == 1: + # For greater count, it means we're just predicting values of multiple variables + parsed_answer = parsed_answer.split("=")[1] + return parsed_answer + + +def process_docs(dataset: datasets.Dataset) -> datasets.Dataset: + def _process_doc(doc: dict, idx, corrected_answer) -> dict: + out_doc = { + "question": doc["problem"], + "question_id": idx, + "solution": doc["solution"], + "answer": extract_answer_dataset( + doc["solution"], doc["problem"], corrected_answer + ), + } + return out_doc + + corrected_answer_path = os.path.join( + os.path.dirname(__file__), "to_be_fixed_questions.json" + ) + + with open(corrected_answer_path, "r") as f: + corrected_answers = json.load(f) + + return dataset.map( + partial(_process_doc, corrected_answer=corrected_answers), with_indices=True + ) + + +def prompt_robustness_process_docs(doc: datasets.Dataset) -> datasets.Dataset: + doc = process_docs(doc) + return utils.process_docs_add_prompts( + doc, + PROMPT_ROBUSTNESS_TEMPLATE_KEY, + TEMPLATE_FILE_PATH, + ) + + +def process_results(doc: dict, results: List[str]) -> Dict[str, int]: + answer = extract_answer(results[0]) + + if math_equal(answer, doc["answer"]): + retval = 1 + else: + retval = 0 + + prompt_id = doc["prompt_id"] + + results = { + f"{prompt_id}_accuracy": (prompt_id, retval), + "consistency_rate": (doc["question_id"], answer), + } + return results + + +def per_prompt_accuracy(results: List[Dict[str, Any]], p_id=0) -> float: + accuracies = [] + for result in results: + prompt_id, retval = result + if prompt_id != p_id: + continue + accuracies.append(retval) + + accuracy = sum(accuracies) / len(accuracies) + eval_logger.info(f"Prompt - {prompt_id} accuracy: {accuracy}") + + return np.round(accuracy, 4) + + +per_prompt_accuracy_0 = partial(per_prompt_accuracy, p_id=0) +per_prompt_accuracy_1 = partial(per_prompt_accuracy, p_id=1) +per_prompt_accuracy_2 = partial(per_prompt_accuracy, p_id=2) +per_prompt_accuracy_3 = partial(per_prompt_accuracy, p_id=3) +per_prompt_accuracy_4 = partial(per_prompt_accuracy, p_id=4) +per_prompt_accuracy_5 = partial(per_prompt_accuracy, p_id=5) +per_prompt_accuracy_6 = partial(per_prompt_accuracy, p_id=6) +per_prompt_accuracy_7 = partial(per_prompt_accuracy, p_id=7) +per_prompt_accuracy_8 = partial(per_prompt_accuracy, p_id=8) +per_prompt_accuracy_9 = partial(per_prompt_accuracy, p_id=9) + + +def calculate_consistency_rate(responses: List[List[str]]) -> float: + """ + Calculate the Consistency Rate (CR) for a given set of responses. + + Args: + responses: List of lists, where each inner list contains responses to the same question. + + Returns: + The consistency rate as a float. + """ + total_similarity = 0 + total_combinations = 0 + + for response_set in responses: + pairs = combinations(response_set, 2) + num_pairs = len(response_set) * (len(response_set) - 1) / 2 + total_combinations += num_pairs + for answer1, answer2 in pairs: + total_similarity += int(math_equal(answer1, answer2)) + + return total_similarity / total_combinations if total_combinations > 0 else 0.0 + + +def math_prompt_consistency_rate(results: List[Dict[str, Any]]) -> float: + """ + Calculate the Consistency Rate (CR) for a given set of responses. + + Args: + responses: List of lists, where each inner list contains responses to the same question. + + Returns: + The consistency rate as a float. + """ + question_answers_dict = {} + + for result in results: + question_id, answer = result + if question_id not in question_answers_dict: + question_answers_dict[question_id] = [] + question_answers_dict[question_id].append(answer) + + question_answers_list = [answers for answers in question_answers_dict.values()] + + return calculate_consistency_rate(question_answers_list) diff --git a/lm_eval/tasks/score/mmlu_pro/prompt_templates.json b/lm_eval/tasks/score/mmlu_pro/prompt_templates.json new file mode 100644 index 00000000..57278cd1 --- /dev/null +++ b/lm_eval/tasks/score/mmlu_pro/prompt_templates.json @@ -0,0 +1,51 @@ +{ + "option_order_robustness":{ + "prompt": "For the multiple-choice question related to {category}, which option (A-J) is correct?.\n\nQuestion: {question}{options}\n\nEnd the answer with the following:\nThe best answer is (the_answer_letter) where the (the_answer_letter) is one of 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I' or 'J'.", + "options_format": "\n{letter}: {option}" + }, + + "prompt_robustness": [ + { + "prompt": "{question}{options}\nExamine the question and choose the correct answer from the options 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I' or 'J'. End your answer with:\nThe best answer is [the_answer_letter].\nwhere the [the_answer_letter] is a letter from A to J.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "{question}{options}\nAnswer the multiple-choice question about {category} by selecting the correct option from A to J. Always conclude with 'The best answer is (answer_letter)' where the (answer_letter) is one of A, B, C, D, E, F, G, H, I, J.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "You must reply with only a single letter from A, B, C, D, E, F, G, H, I or J to this question. Conclude with:\nThe best answer is answer_letter where the answer_letter is a single letter from A to J. \n{question}{options}", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "From the options A-J, select the correct answer to the following question. End the answer with - The best answer is answer_letter, where answer_letter is one of A, B, C, D, E, F, G, H, I, or J.\nQuestion: {question}{options}", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "For the multiple-choice question related to {category}, which option (A-J) is correct?.\n\nQuestion:{question}{options}\nEnd the answer with the following:\nThe best answer is (the_answer_letter) where the (the_answer_letter) is one of 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I' or 'J'.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "Evaluate the multiple-choice question and select the most fitting response from 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'. \nQuestion:{question}{options}\nAlways conclude with:\nThe best answer is [the_answer_letter].\nwhere the [the_answer_letter] is one of A, B, C, D, E, F, G, H, I or J.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "Answer to the following question about {category} by selecting the correct option A, B, C, D, E, F, G, H, I or J. {question}{options}\nThe answer should end with:\nThe best answer is [the_answer_letter] where [the_answer_letter] is one of the letters A to J. Let's think step by step.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "Select the correct answer from the options 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I','J' for the question provided below. Conclude by stating: The best answer is answer_letter where answer_letter is one of 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I' or 'J'. Let's think step by step.\nQuestion: {question}{options}", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "{question}{options}\nFor this question about {category} with 10 possible answers A, B, C, D, E, F, G, H, I, J choose the one that answers the question. If the problem is simple or straightforward, just provide the answer. If the answer is more complex, use a step-by-step approach and for each step briefly explain your reasoning. Always conclude with 'The best answer is (answer_letter)' where the (answer_letter) is one of 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I','J'. Let's think step by step.", + "options_format": "\n{letter}: {option}" + }, + { + "prompt": "Read the question and options below, then determine the correct answer choice (A-J)\nQuestion: {question}{options}\n\nFor simple questions, provide a quick answer. For complicated ones, think step by step, break down the question into smaller problems and reach to a conclusion\nEnd your answer by stating:\nThe best answer is [the_answer_letter].\nwhere [the_answer_letter] is one of A, B, C, D, E, F, G, H, I, or J.", + "options_format": "\n{letter}: {option}" + } + + ] + +} diff --git a/lm_eval/tasks/score/mmlu_pro/score_option_order_robustness_mmlu_pro.yaml b/lm_eval/tasks/score/mmlu_pro/score_option_order_robustness_mmlu_pro.yaml new file mode 100644 index 00000000..71645c9d --- /dev/null +++ b/lm_eval/tasks/score/mmlu_pro/score_option_order_robustness_mmlu_pro.yaml @@ -0,0 +1,67 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +tag: score_robustness_mmlu_pro +task: score_option_order_robustness_mmlu_pro +dataset_path: TIGER-Lab/MMLU-Pro +dataset_name: default +output_type: generate_until +validation_split: validation +test_split: test +process_docs: !function utils_mmlu_pro.option_order_robustness_process_docs +doc_to_text: !function utils_mmlu_pro.mmlu_pro_robustness_doc_to_text +doc_to_target: answer +generation_kwargs: + until: [] + max_gen_toks: 1024 + do_sample: False +process_results: !function utils_mmlu_pro.option_order_robustness_process_results +metric_list: + - metric: per_option_macro_accuracy_A + aggregation: !function utils_mmlu_pro.per_option_macro_accuracy_a + higher_is_better: true + - metric: per_option_macro_accuracy_B + aggregation: !function utils_mmlu_pro.per_option_macro_accuracy_b + higher_is_better: true + - metric: per_option_macro_accuracy_C + aggregation: !function utils_mmlu_pro.per_option_macro_accuracy_c + higher_is_better: true + - metric: per_option_macro_accuracy_D + aggregation: !function utils_mmlu_pro.per_option_macro_accuracy_d + higher_is_better: true + - metric: per_option_macro_accuracy_E + aggregation: !function utils_mmlu_pro.per_option_macro_accuracy_e + higher_is_better: true + - metric: per_option_macro_accuracy_F + aggregation: !function utils_mmlu_pro.per_option_macro_accuracy_f + higher_is_better: true + - metric: per_option_macro_accuracy_G + aggregation: !function utils_mmlu_pro.per_option_macro_accuracy_g + higher_is_better: true + - metric: per_option_macro_accuracy_H + aggregation: !function utils_mmlu_pro.per_option_macro_accuracy_h + higher_is_better: true + - metric: per_option_macro_accuracy_I + aggregation: !function utils_mmlu_pro.per_option_macro_accuracy_i + higher_is_better: true + - metric: per_option_macro_accuracy_J + aggregation: !function utils_mmlu_pro.per_option_macro_accuracy_j + higher_is_better: true + - metric: options_consistency_rate + aggregation: !function utils_mmlu_pro.options_consistency_rate + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/score/mmlu_pro/score_prompt_robustness_mmlu_pro.yaml b/lm_eval/tasks/score/mmlu_pro/score_prompt_robustness_mmlu_pro.yaml new file mode 100644 index 00000000..a71a05ea --- /dev/null +++ b/lm_eval/tasks/score/mmlu_pro/score_prompt_robustness_mmlu_pro.yaml @@ -0,0 +1,67 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +tag: score_robustness_mmlu_pro +task: score_prompt_robustness_mmlu_pro +dataset_path: TIGER-Lab/MMLU-Pro +dataset_name: default +output_type: generate_until +validation_split: validation +test_split: test +process_docs: !function utils_mmlu_pro.prompt_robustness_process_docs +doc_to_text: !function utils_mmlu_pro.mmlu_pro_robustness_doc_to_text +doc_to_target: answer +generation_kwargs: + until: [] + max_gen_toks: 1024 + do_sample: False +process_results: !function utils_mmlu_pro.prompt_robustness_process_results +metric_list: + - metric: 0_macro_accuracy + aggregation: !function utils_mmlu_pro.per_prompt_accuracy_0 + higher_is_better: true + - metric: 1_macro_accuracy + aggregation: !function utils_mmlu_pro.per_prompt_accuracy_1 + higher_is_better: true + - metric: 2_macro_accuracy + aggregation: !function utils_mmlu_pro.per_prompt_accuracy_2 + higher_is_better: true + - metric: 3_macro_accuracy + aggregation: !function utils_mmlu_pro.per_prompt_accuracy_3 + higher_is_better: true + - metric: 4_macro_accuracy + aggregation: !function utils_mmlu_pro.per_prompt_accuracy_4 + higher_is_better: true + - metric: 5_macro_accuracy + aggregation: !function utils_mmlu_pro.per_prompt_accuracy_5 + higher_is_better: true + - metric: 6_macro_accuracy + aggregation: !function utils_mmlu_pro.per_prompt_accuracy_6 + higher_is_better: true + - metric: 7_macro_accuracy + aggregation: !function utils_mmlu_pro.per_prompt_accuracy_7 + higher_is_better: true + - metric: 8_macro_accuracy + aggregation: !function utils_mmlu_pro.per_prompt_accuracy_8 + higher_is_better: true + - metric: 9_macro_accuracy + aggregation: !function utils_mmlu_pro.per_prompt_accuracy_9 + higher_is_better: true + - metric: consistency_rate + aggregation: !function utils_mmlu_pro.mmlu_pro_prompt_consistency_rate + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/score/mmlu_pro/utils_mmlu_pro.py b/lm_eval/tasks/score/mmlu_pro/utils_mmlu_pro.py new file mode 100644 index 00000000..4dd4b657 --- /dev/null +++ b/lm_eval/tasks/score/mmlu_pro/utils_mmlu_pro.py @@ -0,0 +1,164 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +from functools import partial +from typing import Any, Dict, List + +import numpy as np + +from lm_eval.tasks.score import utils +from lm_eval.tasks.score.utils import prompt_consistency_rate, robustness_doc_to_text +from lm_eval.utils import eval_logger + + +TEMPLATE_FILE_PATH = os.path.join(os.path.dirname(__file__), "prompt_templates.json") + +PROMPT_ROBUSTNESS_TEMPLATE_KEY = "prompt_robustness" +OPTION_ORDER_ROBUSTNESS_TEMPLATE_KEY = "option_order_robustness" + +QUESTION_KEY = "question" + +LABELS = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J"] + +mmlu_pro_prompt_consistency_rate = prompt_consistency_rate +mmlu_pro_robustness_doc_to_text = robustness_doc_to_text + + +prompt_robustness_process_docs = partial( + utils.process_docs_add_prompts, + templates_key=PROMPT_ROBUSTNESS_TEMPLATE_KEY, + template_file_path=TEMPLATE_FILE_PATH, +) + +option_order_robustness_process_docs = partial( + utils.option_order_robustness_process_docs, + template_file_path=TEMPLATE_FILE_PATH, + templates_key=OPTION_ORDER_ROBUSTNESS_TEMPLATE_KEY, + labels=LABELS, +) + + +def prompt_robustness_process_results(doc, results) -> Dict[str, float]: + final_answer = utils.__postprocess_pred(results[0]) + final_answer = utils.translate_model_answer_to_labels( + final_answer, option_format=doc["options_format"], labels=LABELS + ) + gt = LABELS[doc["answer_index"]] + prompt_id = doc["prompt_id"] + question_id = doc["question_id"] + category = doc["category"] + return { + f"{prompt_id}_macro_accuracy": ( + question_id, + prompt_id, + final_answer, + gt, + category, + ), + "consistency_rate": (question_id, prompt_id, final_answer, gt), + } + + +def option_order_robustness_process_results(doc, results) -> Dict[str, float]: + final_answer = utils.__postprocess_pred(results[0]) + final_answer = utils.translate_model_answer_to_labels( + final_answer, option_format=doc["options_format"], labels=LABELS + ) + gt = LABELS[doc["answer_index"]] + always_same_option = doc["always_same_option"] + question_id = doc["question_id"] + original_answer_index = doc["original_answer_index"] + answer_index = (doc["answer_index"],) + category = doc["category"] + return { + f"per_option_macro_accuracy_{always_same_option}": ( + question_id, + always_same_option, + final_answer, + gt, + category, + ), + "options_consistency_rate": ( + question_id, + always_same_option, + final_answer, + original_answer_index, + answer_index, + ), + } + + +def per_prompt_macro_accuracy(results: List[Dict[str, Any]], p_id=0) -> float: + accuracies = {} + for result in results: + question_id, prompt_id, final_answer, gt, category = result + if prompt_id != p_id: + continue + if category not in accuracies: + accuracies[category] = [] + accuracies[category].append(final_answer == gt) + + for key in accuracies: + accuracies[key] = sum(accuracies[key]) / len(accuracies[key]) + eval_logger.info( + f"Prompt - {prompt_id}, category - {key} accuracy: {accuracies[key]}" + ) + + return np.round(np.mean([v for v in accuracies.values()]), 4) + + +per_prompt_accuracy_0 = partial(per_prompt_macro_accuracy, p_id=0) +per_prompt_accuracy_1 = partial(per_prompt_macro_accuracy, p_id=1) +per_prompt_accuracy_2 = partial(per_prompt_macro_accuracy, p_id=2) +per_prompt_accuracy_3 = partial(per_prompt_macro_accuracy, p_id=3) +per_prompt_accuracy_4 = partial(per_prompt_macro_accuracy, p_id=4) +per_prompt_accuracy_5 = partial(per_prompt_macro_accuracy, p_id=5) +per_prompt_accuracy_6 = partial(per_prompt_macro_accuracy, p_id=6) +per_prompt_accuracy_7 = partial(per_prompt_macro_accuracy, p_id=7) +per_prompt_accuracy_8 = partial(per_prompt_macro_accuracy, p_id=8) +per_prompt_accuracy_9 = partial(per_prompt_macro_accuracy, p_id=9) + + +def per_option_macro_accuracy(results: List[Dict[str, Any]], always_opt="a") -> float: + accuracies = {} + for result in results: + question_id, always_same_option, final_answer, gt, category = result + if always_opt != always_same_option: + continue + if category not in accuracies: + accuracies[category] = [] + accuracies[category].append(int(final_answer == gt)) + + for key in accuracies: + accuracies[key] = sum(accuracies[key]) / len(accuracies[key]) + eval_logger.info( + f"Prompt - {always_opt.upper()}, category - {key} accuracy: {accuracies[key]}" + ) + + return np.round(np.mean([v for v in accuracies.values()]), 4) + + +per_option_macro_accuracy_a = partial(per_option_macro_accuracy, always_opt="A") +per_option_macro_accuracy_b = partial(per_option_macro_accuracy, always_opt="B") +per_option_macro_accuracy_c = partial(per_option_macro_accuracy, always_opt="C") +per_option_macro_accuracy_d = partial(per_option_macro_accuracy, always_opt="D") +per_option_macro_accuracy_e = partial(per_option_macro_accuracy, always_opt="E") +per_option_macro_accuracy_f = partial(per_option_macro_accuracy, always_opt="F") +per_option_macro_accuracy_g = partial(per_option_macro_accuracy, always_opt="G") +per_option_macro_accuracy_h = partial(per_option_macro_accuracy, always_opt="H") +per_option_macro_accuracy_i = partial(per_option_macro_accuracy, always_opt="I") +per_option_macro_accuracy_j = partial(per_option_macro_accuracy, always_opt="J") + +options_consistency_rate = partial(utils.options_consistency_rate, labels=LABELS) diff --git a/lm_eval/tasks/score/score_robustness.yaml b/lm_eval/tasks/score/score_robustness.yaml new file mode 100644 index 00000000..602f6d7d --- /dev/null +++ b/lm_eval/tasks/score/score_robustness.yaml @@ -0,0 +1,21 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +group: score_robustness +task: + - score_robustness_agieval + - score_robustness_mmlu_pro + - score_robustness_math +metadata: + version: 1.0 diff --git a/lm_eval/tasks/score/utils.py b/lm_eval/tasks/score/utils.py new file mode 100644 index 00000000..5a7174f1 --- /dev/null +++ b/lm_eval/tasks/score/utils.py @@ -0,0 +1,263 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import copy +import json +import re +import string +import sys +from functools import partial +from itertools import combinations +from typing import Any, Dict, List + +import numpy as np +from datasets import Dataset + +from lm_eval.utils import eval_logger + + +NUMERALS = ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"] +ROMAN_NUMERALS = ["I", "II", "III", "IV", "V", "VI", "VII", "VIII", "IX", "X"] + + +def __repeat_elements(lst, n): + result = [] + for element in lst: + result.extend([element] * n) + return result + + +def process_docs_add_prompts( + doc: Dataset, + templates_key: str, + template_file_path: str, + dataset_specific_preprocess: callable = None, +) -> Dataset: + try: + with open(template_file_path) as f: + prompt_templates = json.load(f)[templates_key] + except FileNotFoundError: + eval_logger.error("Prompt templates not found") + sys.exit() + if dataset_specific_preprocess is not None: + doc = dataset_specific_preprocess(doc) + + def process_batch(batch): + n = len(prompt_templates) + initial_len = len(next(iter(batch.values()))) + + result = {key: __repeat_elements(values, n) for key, values in batch.items()} + result["prompt_id"] = list(range(n)) * initial_len + result["prompt"] = [prompt_templates[i]["prompt"] for i in result["prompt_id"]] + if "options_format" in prompt_templates[0]: + result["options_format"] = [ + prompt_templates[i]["options_format"] for i in result["prompt_id"] + ] + return result + + return doc.map(process_batch, batched=True) + + +def option_order_robustness_process_docs( + doc: Dataset, + template_file_path: str, + templates_key: str, + labels: list, + dataset_specific_preprocess: callable = None, +) -> Dataset: + try: + with open(template_file_path) as f: + prompt_template = json.load(f)[templates_key] + prompt = prompt_template["prompt"] + options_format = prompt_template["options_format"] + except FileNotFoundError: + eval_logger.error("Prompt templates not found") + sys.exit() + + if dataset_specific_preprocess is not None: + doc = dataset_specific_preprocess(doc) + + def repeat_doc_swap_correct_answer(batched_docs): + initial_len = len(next(iter(batched_docs.values()))) + keys = list(batched_docs.keys()) + new_batched_docs = {key: [] for key in keys} + new_batched_docs["always_same_option"] = [] + new_batched_docs["prompt"] = [] + new_batched_docs["options_format"] = [] + new_batched_docs["original_answer_index"] = [] + + for doc_ind in range(initial_len): + for label_ind, label in enumerate(labels): + new_batched_docs["original_answer_index"].append( + batched_docs["answer_index"][doc_ind] + ) + for key in keys: + new_batched_docs[key].append( + copy.deepcopy(batched_docs[key][doc_ind]) + ) + if label_ind < len(batched_docs["options"][doc_ind]): + if key == "options": + # Swap correct answer with label_ind option + new_batched_docs[key][-1][label_ind] = batched_docs[ + "options" + ][doc_ind][batched_docs["answer_index"][doc_ind]] + new_batched_docs[key][-1][ + batched_docs["answer_index"][doc_ind] + ] = batched_docs["options"][doc_ind][label_ind] + + if key == "answer_index": + new_batched_docs[key][-1] = label_ind + + if key == "answer": + new_batched_docs[key][-1] = label + + new_batched_docs["always_same_option"].append(label) + new_batched_docs["prompt"].append(prompt) + new_batched_docs["options_format"].append(options_format) + return new_batched_docs + + return doc.map(repeat_doc_swap_correct_answer, batched=True) + + +def robustness_doc_to_text(doc: Dataset) -> str: + upper_case = string.ascii_uppercase + lower_case = string.ascii_lowercase + prompt = doc["prompt"] + options_format = doc.get("options_format", "") + question = doc["question"] + catrgory = doc.get("category", "") + options = None + if options_format: + options = "".join( + [ + options_format.format( + letter=upper_case[i], + option=doc["options"][i], + numeral=NUMERALS[i], + roman_numeral=ROMAN_NUMERALS[i], + lower_case_letter=lower_case[i], + ) + for i in range(len(doc["options"])) + ] + ) + return prompt.format(question=question, options=options, category=catrgory) + + +def __postprocess_pred(pred): + if "the best answer is" not in pred.lower(): + return pred + pred_proc = ( + pred.lower().split("the best answer is ")[-1].split("\n")[0].split(" ")[0] + ) + pred_proc = re.sub(r"[^a-zA-Z0-9]", "", pred_proc).strip() + return pred_proc.upper() + + +def translate_model_answer_to_labels(answer, labels, option_format=None): + answer = answer.upper() + + if option_format is None: + return answer + + elif "numeral" in option_format: + if "roman" in option_format: + if answer not in ROMAN_NUMERALS: + return answer + else: + return labels[ROMAN_NUMERALS.index(answer)] + + if answer not in NUMERALS: + return answer + else: + return labels[NUMERALS.index(answer)] + + return answer + + +def calculate_consistency_rate(responses: List[List[str]]) -> float: + """ + Calculate the Consistency Rate (CR) for a given set of responses. + + Args: + responses: List of lists, where each inner list contains responses to the same question. + + Returns: + The consistency rate as a float. + """ + total_similarity = 0 + total_combinations = 0 + + for response_set in responses: + pairs = combinations(response_set, 2) + num_pairs = len(response_set) * (len(response_set) - 1) / 2 + total_combinations += num_pairs + for answer1, answer2 in pairs: + total_similarity += int(answer1 == answer2) + + return total_similarity / total_combinations if total_combinations > 0 else 0.0 + + +def prompt_consistency_rate(results: List[Dict[str, Any]]) -> float: + """ + Calculate the Consistency Rate (CR) for a given set of responses. + + Args: + responses: List of lists, where each inner list contains responses to the same question. + + Returns: + The consistency rate as a float. + """ + question_answers_dict = {} + + for result in results: + question_id, prompt_id, final_answer, gt = result + if question_id not in question_answers_dict: + question_answers_dict[question_id] = [] + question_answers_dict[question_id].append(final_answer) + + question_answers_list = [answers for answers in question_answers_dict.values()] + + return calculate_consistency_rate(question_answers_list) + + +def options_consistency_rate(results: List[Dict[str, Any]], labels) -> float: + """ + Calculate the Consistency Rate (CR) for a given set of responses. + + Args: + responses: List of lists, where each inner list contains responses to the same question. + + Returns: + The consistency rate as a float. + """ + question_answers_dict = {} + for result in results: + ( + question_id, + always_same_option, + final_answer, + original_answer_index, + answer_index, + ) = result + if final_answer == labels[original_answer_index]: + final_answer = always_same_option + if final_answer == always_same_option: + final_answer = labels[original_answer_index] + if question_id not in question_answers_dict: + question_answers_dict[question_id] = [] + question_answers_dict[question_id].append(final_answer) + + question_answers_list = [answers for answers in question_answers_dict.values()] + + return calculate_consistency_rate(question_answers_list) -- GitLab From 5680a2e6b5cf1a1621d8ff68d3d0e83e8b2731d3 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Thu, 28 Nov 2024 07:33:53 +0000 Subject: [PATCH 165/194] Filters bugfix; add `metrics` and `filter` to logged sample (#2517) * allow !function filters * bugfix * nit * add `filter` to logged samples * add `filter` and `metric` to logged samples to identification * convert `metric` to `metrics`: list --- lm_eval/api/registry.py | 12 ++++++++---- lm_eval/evaluator.py | 2 ++ lm_eval/filters/extraction.py | 8 +++++--- 3 files changed, 15 insertions(+), 7 deletions(-) diff --git a/lm_eval/api/registry.py b/lm_eval/api/registry.py index 7446a429..f8f28937 100644 --- a/lm_eval/api/registry.py +++ b/lm_eval/api/registry.py @@ -1,5 +1,5 @@ import logging -from typing import Callable, Dict +from typing import Callable, Dict, Union import evaluate as hf_evaluate @@ -185,8 +185,12 @@ def register_filter(name): return decorate -def get_filter(filter_name: str) -> type: +def get_filter(filter_name: Union[str, Callable]) -> Callable: try: return FILTER_REGISTRY[filter_name] - except KeyError: - eval_logger.warning(f"filter `{filter_name}` is not registered!") + except KeyError as e: + if callable(filter_name): + return filter_name + else: + eval_logger.warning(f"filter `{filter_name}` is not registered!") + raise e diff --git a/lm_eval/evaluator.py b/lm_eval/evaluator.py index 9ca64af6..e7dd3043 100644 --- a/lm_eval/evaluator.py +++ b/lm_eval/evaluator.py @@ -552,6 +552,8 @@ def evaluate( "filtered_resps": [ req.filtered_resps[filter_key] for req in requests ], + "filter": filter_key, + "metrics": list(metrics.keys()), "doc_hash": hash_string( json.dumps( requests[0].doc, diff --git a/lm_eval/filters/extraction.py b/lm_eval/filters/extraction.py index 41dc6208..5dc10863 100644 --- a/lm_eval/filters/extraction.py +++ b/lm_eval/filters/extraction.py @@ -37,16 +37,18 @@ class RegexFilter(Filter): if match: match = match[self.group_select] if isinstance(match, tuple): - match = [m for m in match if m][0] + match = [m for m in match if m] + if match: + match = match[0] + else: + match = self.fallback match = match.strip() else: match = self.fallback filtered.append(match) return filtered - # print(resps) filtered_resps = list(map(lambda x: filter_set(x), resps)) - # print(filtered_resps) return filtered_resps -- GitLab From 9169899b4966b4161719e54d41258345df03aaa0 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Fri, 29 Nov 2024 09:32:08 +0000 Subject: [PATCH 166/194] skip casting if predict_only (#2524) --- lm_eval/api/task.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/lm_eval/api/task.py b/lm_eval/api/task.py index 56a1ad16..555cb433 100644 --- a/lm_eval/api/task.py +++ b/lm_eval/api/task.py @@ -1503,7 +1503,10 @@ class ConfigurableTask(Task): # we expect multiple_targets to be a list. elif self.multiple_target: gold = list(gold) - elif type(gold) is not type(result): + elif ( + type(gold) is not type(result) + and "bypass" not in self._metric_fn_list.keys() + ): # cast gold to the same type as result gold = type(result)(gold) -- GitLab From 0230356c2f9db4fd80957bc8a7c3cb13ffea8f3c Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Sat, 30 Nov 2024 07:43:31 +0000 Subject: [PATCH 167/194] make utility function to handle `until` (#2518) * make utility function to handle `until` * fix text --- lm_eval/models/anthropic_llms.py | 11 ++++++++--- lm_eval/models/api_models.py | 19 +++++++++++++++++++ lm_eval/models/hf_vlms.py | 20 ++++---------------- lm_eval/models/huggingface.py | 19 ++++--------------- lm_eval/models/openai_completions.py | 10 +++++++--- lm_eval/models/utils.py | 18 ++++++++++++++++++ lm_eval/models/vllm_causallms.py | 27 ++++++++++----------------- lm_eval/models/vllm_vlms.py | 26 +++++++++----------------- tests/models/test_api.py | 6 +++--- 9 files changed, 82 insertions(+), 74 deletions(-) diff --git a/lm_eval/models/anthropic_llms.py b/lm_eval/models/anthropic_llms.py index daba6734..fcac7dc0 100644 --- a/lm_eval/models/anthropic_llms.py +++ b/lm_eval/models/anthropic_llms.py @@ -8,7 +8,7 @@ from lm_eval import utils from lm_eval.api.model import LM from lm_eval.api.registry import register_model from lm_eval.models.openai_completions import LocalCompletionsAPI -from lm_eval.models.utils import retry_on_specific_exceptions +from lm_eval.models.utils import handle_stop_sequences, retry_on_specific_exceptions eval_logger = utils.eval_logger @@ -311,7 +311,12 @@ class AnthropicChat(LocalCompletionsAPI): } def _create_payload( - self, messages: List[Dict], generate=True, gen_kwargs: dict = None, **kwargs + self, + messages: List[Dict], + generate=True, + gen_kwargs: dict = None, + eos="\n\nHuman:", + **kwargs, ) -> dict: system = ( messages[0].get("content") if messages[0].get("role") == "system" else None @@ -321,7 +326,7 @@ class AnthropicChat(LocalCompletionsAPI): gen_kwargs.pop("do_sample", False) max_tokens = gen_kwargs.pop("max_gen_toks", self._max_gen_toks) temperature = gen_kwargs.pop("temperature", 0) - stop = gen_kwargs.pop("until", ["\n\nHuman:"]) + stop = handle_stop_sequences(gen_kwargs.pop("until", ["\n\nHuman:"]), eos=eos) if not isinstance(stop, list): stop = [stop] out = { diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index fd21c857..1c410017 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -80,6 +80,7 @@ class TemplateAPI(TemplateLM): revision: Optional[str] = "main", use_fast_tokenizer: bool = True, verify_certificate: bool = True, + eos_string: str = None, **kwargs, ) -> None: super().__init__() @@ -124,6 +125,7 @@ class TemplateAPI(TemplateLM): self.tokenized_requests = tokenized_requests self.max_retries = int(max_retries) self.verify_certificate = verify_certificate + self._eos_string = eos_string eval_logger.info(f"Using tokenizer {self.tokenizer_backend}") if self.tokenizer_backend is None: @@ -176,6 +178,7 @@ class TemplateAPI(TemplateLM): generate: bool = True, gen_kwargs: Optional[dict] = None, seed: int = 1234, + eos: str = None, **kwargs, ) -> dict: """This method is responsible for creating the json payload that will be sent to the API.""" @@ -268,6 +271,21 @@ class TemplateAPI(TemplateLM): elif self.tokenizer_backend == "tiktoken": return self.tokenizer.eot_token + @cached_property + def eos_string(self) -> Optional[str]: + if self._eos_string: + return self._eos_string + elif self.tokenizer is not None: + if self.tokenizer_backend == "huggingface": + return self.tokenizer.eos_token + elif self.tokenizer_backend == "tiktoken": + return self.tokenizer.decode([self.tokenizer.eot_token]) + else: + eval_logger.warning( + "Cannot determine EOS string to pass to stop sequence. Manually set by passing `eos_string` to model_args." + ) + return None + @cached_property def prefix_token_id(self) -> Optional[int]: if self.tokenizer is None: @@ -343,6 +361,7 @@ class TemplateAPI(TemplateLM): generate=generate, gen_kwargs=gen_kwargs, seed=self._seed, + eos=self.eos_string, **kwargs, ), headers=self.header, diff --git a/lm_eval/models/hf_vlms.py b/lm_eval/models/hf_vlms.py index f2fcdd70..a4fad632 100644 --- a/lm_eval/models/hf_vlms.py +++ b/lm_eval/models/hf_vlms.py @@ -14,6 +14,7 @@ from lm_eval.models.huggingface import HFLM from lm_eval.models.utils import ( Collator, flatten_image_list, + handle_stop_sequences, pad_and_concat, replace_placeholders, stop_sequences_criteria, @@ -629,7 +630,7 @@ class HFMultimodalLM(HFLM): chunks = re_ords.get_batched(n=self.batch_size, batch_fn=None) ### Up to here: was identical to non-multimodal HFLM generate_until ### - + eos = self.tok_decode(self.eot_token_id, skip_special_tokens=False) for chunk in chunks: contexts, all_gen_kwargs, aux_arguments = zip(*chunk) @@ -646,27 +647,14 @@ class HFMultimodalLM(HFLM): # this is safe to assume because the `grouper` object ensures it. gen_kwargs = all_gen_kwargs[0] # unpack our keyword arguments. - until = None if isinstance(gen_kwargs, dict): kwargs = copy.deepcopy(gen_kwargs) # edge case for repeats > 1 - if "until" in kwargs.keys(): - until = kwargs.pop("until") - if isinstance(until, str): - until = [until] - elif not isinstance(until, list): - raise ValueError( - f"Expected `kwargs['until']` to be of type Union[str,list] but got {until}" - ) + # add EOS token to stop sequences + until = handle_stop_sequences(kwargs.pop("until", None), eos=eos) else: raise ValueError( f"Expected `kwargs` to be of type `dict` but got {type(gen_kwargs)}" ) - # add EOS token to stop sequences - eos = self.tok_decode(self.eot_token_id, skip_special_tokens=False) - if not until: - until = [eos] - else: - until.append(eos) if "max_gen_toks" in kwargs.keys(): max_gen_toks = kwargs.pop("max_gen_toks") else: diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index dd04470c..0a5fa2ed 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -33,6 +33,7 @@ from lm_eval.models.utils import ( clear_torch_cache, configure_pad_token, get_dtype, + handle_stop_sequences, pad_and_concat, stop_sequences_criteria, ) @@ -1255,33 +1256,21 @@ class HFLM(TemplateLM): group_fn=lambda x: x[1], ) chunks = re_ords.get_batched(n=batch_size, batch_fn=batch_fn) + eos = self.tok_decode(self.eot_token_id, skip_special_tokens=False) for chunk in chunks: contexts, all_gen_kwargs = zip(*chunk) # we assume all gen kwargs in the batch are the same # this is safe to assume because the `grouper` object ensures it. gen_kwargs = all_gen_kwargs[0] # unpack our keyword arguments. - until = None if isinstance(gen_kwargs, dict): kwargs = copy.deepcopy(gen_kwargs) # edge case for repeats > 1 - if "until" in kwargs.keys(): - until = kwargs.pop("until") - if isinstance(until, str): - until = [until] - elif not isinstance(until, list): - raise ValueError( - f"Expected `kwargs['until']` to be of type Union[str,list] but got {until}" - ) + # add EOS token to stop sequences + until = handle_stop_sequences(kwargs.pop("until", None), eos=eos) else: raise ValueError( f"Expected `kwargs` to be of type `dict` but got {type(gen_kwargs)}" ) - # add EOS token to stop sequences - eos = self.tok_decode(self.eot_token_id, skip_special_tokens=False) - if not until: - until = [eos] - else: - until.append(eos) if "max_gen_toks" in kwargs.keys(): max_gen_toks = kwargs.pop("max_gen_toks") else: diff --git a/lm_eval/models/openai_completions.py b/lm_eval/models/openai_completions.py index 2f10316f..46d63732 100644 --- a/lm_eval/models/openai_completions.py +++ b/lm_eval/models/openai_completions.py @@ -4,6 +4,7 @@ from typing import Any, Dict, List, Optional, Tuple, Union from lm_eval.api.registry import register_model from lm_eval.models.api_models import TemplateAPI +from lm_eval.models.utils import handle_stop_sequences from lm_eval.utils import eval_logger @@ -25,6 +26,7 @@ class LocalCompletionsAPI(TemplateAPI): generate=False, gen_kwargs: Optional[dict] = None, seed: int = 1234, + eos=None, **kwargs, ) -> dict: if generate: @@ -34,7 +36,7 @@ class LocalCompletionsAPI(TemplateAPI): else: max_tokens = gen_kwargs.pop("max_gen_toks", self._max_gen_toks) temperature = gen_kwargs.pop("temperature", 0) - stop = gen_kwargs.pop("until", ["<|endoftext|>"]) + stop = handle_stop_sequences(gen_kwargs.pop("until", None), eos) return { "prompt": messages, "model": self.model, @@ -124,6 +126,7 @@ class LocalChatCompletion(LocalCompletionsAPI): generate=False, gen_kwargs: dict = None, seed=1234, + eos=None, **kwargs, ) -> dict: assert ( @@ -135,7 +138,7 @@ class LocalChatCompletion(LocalCompletionsAPI): else: max_tokens = gen_kwargs.pop("max_gen_toks", self._max_gen_toks) temperature = gen_kwargs.pop("temperature", 0) - stop = gen_kwargs.pop("until", ["<|endoftext|>"]) + stop = handle_stop_sequences(gen_kwargs.pop("until", None), eos) if not isinstance(stop, (list, tuple)): stop = [stop] return { @@ -252,6 +255,7 @@ class OpenAIChatCompletion(LocalChatCompletion): generate=False, gen_kwargs: dict = None, seed=1234, + eos="<|endoftext|>", **kwargs, ) -> dict: assert ( @@ -263,7 +267,7 @@ class OpenAIChatCompletion(LocalChatCompletion): else: max_tokens = gen_kwargs.pop("max_gen_toks", self._max_gen_toks) temperature = gen_kwargs.pop("temperature", 0) - stop = gen_kwargs.pop("until", ["<|endoftext|>"]) + stop = handle_stop_sequences(gen_kwargs.pop("until", ["<|endoftext|>"]), eos) if not isinstance(stop, (list, tuple)): stop = [stop] output = { diff --git a/lm_eval/models/utils.py b/lm_eval/models/utils.py index 28ecc658..e7c28c3e 100644 --- a/lm_eval/models/utils.py +++ b/lm_eval/models/utils.py @@ -709,3 +709,21 @@ def flatten_image_list(images: List[List]): :return: a list of PIL images, via concatenating all the sub-lists in order. """ return [image for image_list in images for image in image_list] + + +def handle_stop_sequences( + until: Union[str, List[str], None], eos: Optional[str] +) -> List[str]: + """Ensures that the `until` parameter is a list of stop sequences and includes the EOS token.""" + if isinstance(until, str): + until = [until] + elif until is None: + until = [] + elif not isinstance(until, list): + raise ValueError( + f"Expected `kwargs['until']` to be of type Union[str,list] but got {until}" + ) + + if eos is not None and eos not in until: + until.append(eos) + return until diff --git a/lm_eval/models/vllm_causallms.py b/lm_eval/models/vllm_causallms.py index b9ee6f92..7afc2cb8 100644 --- a/lm_eval/models/vllm_causallms.py +++ b/lm_eval/models/vllm_causallms.py @@ -10,7 +10,12 @@ from tqdm import tqdm from lm_eval.api.instance import Instance from lm_eval.api.model import TemplateLM from lm_eval.api.registry import register_model -from lm_eval.models.utils import Collator, configure_pad_token, undistribute +from lm_eval.models.utils import ( + Collator, + configure_pad_token, + handle_stop_sequences, + undistribute, +) from lm_eval.utils import ( eval_logger, get_rolling_token_windows, @@ -346,6 +351,7 @@ class VLLM(TemplateLM): desc="Running generate_until requests", ) # for each different set of kwargs, we execute all requests, by batch. + eos = self.tokenizer.decode(self.eot_token_id) for chunk in chunks: context_and_encoding, all_gen_kwargs = zip(*chunk) context, context_encoding = zip(*context_and_encoding) @@ -353,27 +359,14 @@ class VLLM(TemplateLM): # this is safe to assume because the `grouper` object ensures it. gen_kwargs = all_gen_kwargs[0] # unpack our keyword arguments. - until = None if isinstance(gen_kwargs, dict): kwargs = copy.deepcopy(gen_kwargs) # edge case for repeats > 1 - if "until" in kwargs.keys(): - until = kwargs.pop("until") - if isinstance(until, str): - until = [until] - elif not isinstance(until, list): - raise ValueError( - f"Expected `kwargs['until']` to be of type Union[str,list] but got {until}" - ) + # add EOS token to stop sequences + until = handle_stop_sequences(kwargs.pop("until", None), eos=eos) else: raise ValueError( - f"Expected `kwargs` to be of type `dict` but got {gen_kwargs}" + f"Expected `kwargs` to be of type `dict` but got {type(gen_kwargs)}" ) - # add EOS token to stop sequences - eos = self.tokenizer.decode(self.eot_token_id) - if not until: - until = [eos] - else: - until.append(eos) if "max_gen_toks" in kwargs.keys(): max_gen_toks = kwargs.pop("max_gen_toks") else: diff --git a/lm_eval/models/vllm_vlms.py b/lm_eval/models/vllm_vlms.py index 13a2a3ff..b434ba05 100644 --- a/lm_eval/models/vllm_vlms.py +++ b/lm_eval/models/vllm_vlms.py @@ -7,7 +7,12 @@ from tqdm import tqdm from lm_eval.api.instance import Instance from lm_eval.api.registry import register_model -from lm_eval.models.utils import Collator, replace_placeholders, undistribute +from lm_eval.models.utils import ( + Collator, + handle_stop_sequences, + replace_placeholders, + undistribute, +) from lm_eval.models.vllm_causallms import VLLM from lm_eval.utils import eval_logger @@ -225,7 +230,7 @@ class VLLM_VLM(VLLM): group_fn=lambda x: x[1], ) chunks = re_ords.get_batched(n=self.batch_size, batch_fn=None) - + eos = self.tokenizer.decode(self.eot_token_id) for chunk in chunks: contexts, all_gen_kwargs, aux_arguments = zip(*chunk) @@ -241,27 +246,14 @@ class VLLM_VLM(VLLM): # this is safe to assume because the `grouper` object ensures it. gen_kwargs = all_gen_kwargs[0] # unpack our keyword arguments. - until = None if isinstance(gen_kwargs, dict): kwargs = copy.deepcopy(gen_kwargs) # edge case for repeats > 1 - if "until" in kwargs.keys(): - until = kwargs.pop("until") - if isinstance(until, str): - until = [until] - elif not isinstance(until, list): - raise ValueError( - f"Expected `kwargs['until']` to be of type Union[str,list] but got {until}" - ) + # add EOS token to stop sequences + until = handle_stop_sequences(kwargs.pop("until", None), eos=eos) else: raise ValueError( f"Expected `kwargs` to be of type `dict` but got {type(gen_kwargs)}" ) - # add EOS token to stop sequences - eos = self.tokenizer.decode(self.eot_token_id) - if not until: - until = [eos] - else: - until.append(eos) if "max_gen_toks" in kwargs.keys(): max_gen_toks = kwargs.pop("max_gen_toks") else: diff --git a/tests/models/test_api.py b/tests/models/test_api.py index 1bca2f7b..40aee8c1 100644 --- a/tests/models/test_api.py +++ b/tests/models/test_api.py @@ -63,13 +63,13 @@ def test_create_payload_loglikelihood(api): ( ["Hello, how are"], True, - {"max_gen_toks": 100, "temperature": 0.7}, + {"max_gen_toks": 100, "temperature": 0.7, "until": ["hi"]}, { "prompt": "Hello, how are", "model": "gpt-3.5-turbo", "max_tokens": 100, "temperature": 0.7, - "stop": ["<|endoftext|>"], + "stop": ["hi"], "seed": 1234, }, ), @@ -82,7 +82,7 @@ def test_create_payload_loglikelihood(api): "model": "gpt-3.5-turbo", "max_tokens": 256, "temperature": 0, - "stop": ["<|endoftext|>"], + "stop": [], "seed": 1234, }, ), -- GitLab From 1170ef9eeac321bae0a69b8a1e6c3d1087d40ff6 Mon Sep 17 00:00:00 2001 From: Yoav Katz <68273864+yoavkatz@users.noreply.github.com> Date: Sun, 1 Dec 2024 14:31:50 +0200 Subject: [PATCH 168/194] Update Unitxt task to use locally installed unitxt and not download Unitxt code from Huggingface (#2514) * Moved to require unitxt installation and not download unitxt from HF hub. This has performance benefits and simplifies the code. Signed-off-by: Yoav Katz * Updated watsonx documentation * Updated installation instructions * Removed redundant comman * Allowed unitxt tasks to generate chat APIs Modified WatsonXI model to support chat apis * Removed print * Run precommit formatting --------- Signed-off-by: Yoav Katz --- README.md | 3 ++ lm_eval/models/ibm_watsonx_ai.py | 19 ++++++++++++- lm_eval/tasks/unitxt/README.md | 2 ++ lm_eval/tasks/unitxt/task.py | 49 +++++++++++++++++++++++--------- 4 files changed, 58 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index c453de30..4d6fb875 100644 --- a/README.md +++ b/README.md @@ -260,6 +260,7 @@ Note that for externally hosted models, configs such as `--device` which relate | Neuron via AWS Inf2 (Causal LMs) | ✔️ | `neuronx` | Any decoder-only AutoModelForCausalLM supported to run on [huggingface-ami image for inferentia2](https://aws.amazon.com/marketplace/pp/prodview-gr3e6yiscria2) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | ... | | [Neural Magic DeepSparse](https://github.com/neuralmagic/deepsparse) | ✔️ | `deepsparse` | Any LM from [SparseZoo](https://sparsezoo.neuralmagic.com/) or on [HF Hub with the "deepsparse" tag](https://huggingface.co/models?other=deepsparse) | `generate_until`, `loglikelihood` | ... | | [Neural Magic SparseML](https://github.com/neuralmagic/sparseml) | ✔️ | `sparseml` | Any decoder-only AutoModelForCausalLM from [SparseZoo](https://sparsezoo.neuralmagic.com/) or on [HF Hub](https://huggingface.co/neuralmagic). Especially useful for models with quantization like [`zoo:llama2-7b-gsm8k_llama2_pretrain-pruned60_quantized`](https://sparsezoo.neuralmagic.com/models/llama2-7b-gsm8k_llama2_pretrain-pruned60_quantized) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | ... | +| Watsonx.ai | :heavy_check_mark: | `watsonx_llm` | [Supported Watsonx.ai Engines](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/fm-models.html?context=wx) | `generate_until` `loglikelihood` | | Your local inference server! | :heavy_check_mark: | `local-completions` or `local-chat-completions` | Support for OpenAI API-compatible servers, with easy customization for other APIs. | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | | ... | Models which do not supply logits or logprobs can be used with tasks of type `generate_until` only, while local models, or APIs that supply logprobs/logits of their prompts, can be run on all task types: `generate_until`, `loglikelihood`, `loglikelihood_rolling`, and `multiple_choice`. @@ -476,6 +477,8 @@ Extras dependencies can be installed via `pip install -e ".[NAME]"` | gptq | For loading models with GPTQ | | hf_transfer | For speeding up HF Hub file downloads | | ifeval | For running the IFEval task | +| ibm_watsonx_ai | For using IBM watsonx.ai model apis | + | neuronx | For running on AWS inf2 instances | | mamba | For loading Mamba SSM models | | math | For running math task answer checking | diff --git a/lm_eval/models/ibm_watsonx_ai.py b/lm_eval/models/ibm_watsonx_ai.py index a82c5c45..96fdb6e9 100644 --- a/lm_eval/models/ibm_watsonx_ai.py +++ b/lm_eval/models/ibm_watsonx_ai.py @@ -1,4 +1,5 @@ import copy +import json import os from functools import lru_cache from typing import Any, Dict, List, NamedTuple, Optional, Tuple, Type, cast @@ -8,6 +9,7 @@ from tqdm import tqdm from lm_eval.api.instance import Instance from lm_eval.api.model import LM from lm_eval.api.registry import register_model +from lm_eval.models.api_models import JsonChatStr from lm_eval.utils import eval_logger, simple_parse_args_string @@ -248,7 +250,12 @@ class WatsonxLLM(LM): ): context, continuation = request try: - response = self.model.generate_text(context, self.generate_params) + if isinstance(context, JsonChatStr): + context = json.loads(context.prompt) + response = self.model.chat(context, self.generate_params) + response = response["choices"][0]["message"]["content"] + else: + response = self.model.generate_text(context, self.generate_params) except Exception as exp: eval_logger.error("Error while generating text.") raise exp @@ -372,3 +379,13 @@ class WatsonxLLM(LM): ) return cast(List[Tuple[float, bool]], results) + + @property + def tokenizer_name(self) -> str: + return "" + + def apply_chat_template( + self, chat_history: List[Dict[str, str]] + ) -> List[Dict[str, str]]: + # A hack similar from api_model to allow encoding for cache + return JsonChatStr(json.dumps(chat_history)) diff --git a/lm_eval/tasks/unitxt/README.md b/lm_eval/tasks/unitxt/README.md index 06bee133..63649473 100644 --- a/lm_eval/tasks/unitxt/README.md +++ b/lm_eval/tasks/unitxt/README.md @@ -6,6 +6,8 @@ The full Unitxt catalog can be viewed in an [online explorer](https://unitxt.rea Read more about Unitxt at [www.unitxt.ai](https://www.unitxt.ai/). +To use Unitxt dataset with lm-eval, you should first install unitxt via 'pip install unitxt'. + ### Paper Title: `Unitxt: Flexible, Shareable and Reusable Data Preparation and Evaluation for Generative AI` diff --git a/lm_eval/tasks/unitxt/task.py b/lm_eval/tasks/unitxt/task.py index 12b27608..78e5c106 100644 --- a/lm_eval/tasks/unitxt/task.py +++ b/lm_eval/tasks/unitxt/task.py @@ -6,11 +6,11 @@ Addressing this need, we present Unitxt, an innovative library for customizable import importlib.util import re +from collections.abc import Callable from functools import partial from typing import Any, Dict, Optional import datasets -import evaluate from lm_eval.api.instance import Instance from lm_eval.api.task import ConfigurableTask @@ -28,16 +28,21 @@ _CITATION = """ """ -def is_unitxt_installed() -> bool: - return importlib.util.find_spec("unitxt") is not None +def assert_unitxt_installed(): + if importlib.util.find_spec("unitxt") is None: + raise Exception( + "Please install unitxt via 'pip install unitxt'. For more information see: https://www.unitxt.ai/" + ) def score(items, metric): predictions, references = zip(*items) - evaluator = evaluate.load("unitxt/metric") + assert_unitxt_installed() + from unitxt import evaluate + for reference in references: reference["metrics"] = [metric] - results = evaluator.compute(predictions=predictions, references=references) + results = evaluate(predictions, references) return results[0]["score"]["global"]["score"] @@ -61,16 +66,10 @@ class Unitxt(ConfigurableTask): self.metrics = self.dataset["test"][0]["metrics"] def download(self, dataset_kwargs: Optional[Dict[str, Any]] = None) -> None: - if is_unitxt_installed(): - from unitxt import load_dataset + assert_unitxt_installed() + from unitxt import load_dataset - self.dataset = load_dataset(self.DATASET_NAME) - else: - self.dataset = datasets.load_dataset( - name=self.DATASET_NAME, - path="unitxt/data", - trust_remote_code=True, - ) + self.dataset = load_dataset(self.DATASET_NAME, disable_cache=False) def has_training_docs(self): return "train" in self.dataset @@ -102,6 +101,27 @@ class Unitxt(ConfigurableTask): def get_arguments(self, doc, ctx): return (ctx, {"until": ["\n"]}) + def fewshot_context( + self, + doc: str, + num_fewshot: int, + system_instruction: Optional[str] = None, + apply_chat_template: bool = False, + fewshot_as_multiturn: bool = False, + chat_template: Optional[Callable] = None, + ) -> str: + source = self.doc_to_text(doc) + if isinstance(source, list): + if apply_chat_template: + formated_source = chat_template(self.doc_to_text(doc)) + return formated_source + else: + raise Exception( + "Got chat template format from Unitxt, but apply_chat_template is false. Add '--apply_chat_template' to command line." + ) + else: + return source + def construct_requests(self, doc, ctx, **kwargs): """Uses RequestFactory to construct Requests and returns an iterable of Requests which will be sent to the LM. @@ -113,6 +133,7 @@ class Unitxt(ConfigurableTask): language description, as well as the few shot examples, and the question part of the document for `doc`. """ + kwargs.pop("apply_chat_template", False) # Not used by unitxt return [ Instance( request_type="generate_until", -- GitLab From f49b0377bf559f5558e8cd9ebd1190218c7df2a4 Mon Sep 17 00:00:00 2001 From: Naiara Perez Date: Tue, 3 Dec 2024 14:00:34 +0100 Subject: [PATCH 169/194] add Basque translation of PIQA (piqa_eu) to BasqueBench (#2531) --- lm_eval/tasks/basque_bench/README.md | 2 ++ lm_eval/tasks/basque_bench/basque_bench.yaml | 1 + lm_eval/tasks/basque_bench/piqa_eu.yaml | 21 ++++++++++++++++++++ 3 files changed, 24 insertions(+) create mode 100755 lm_eval/tasks/basque_bench/piqa_eu.yaml diff --git a/lm_eval/tasks/basque_bench/README.md b/lm_eval/tasks/basque_bench/README.md index 7b5f93c1..c4eb7f1c 100644 --- a/lm_eval/tasks/basque_bench/README.md +++ b/lm_eval/tasks/basque_bench/README.md @@ -8,6 +8,7 @@ The new evaluation datasets included in BasqueBench are: | Task | Category | Homepage | |:-------------:|:-----:|:-----:| | MGSM_eu | Math | https://huggingface.co/datasets/HiTZ/MGSM-eu | +| PIQA_eu | Question Answering | https://huggingface.co/datasets/HiTZ/PIQA-eu | | WNLI_eu | Natural Language Inference | https://huggingface.co/datasets/HiTZ/wnli-eu | | XCOPA_eu | Commonsense Reasoning | https://huggingface.co/datasets/HiTZ/XCOPA-eu | @@ -63,6 +64,7 @@ The following tasks evaluate tasks on BasqueBench dataset using various scoring - `flores_pt-eu` - `mgsm_direct_eu` - `mgsm_native_cot_eu` + - `piqa_eu` - `qnlieu` - `wnli_eu` - `xcopa_eu` diff --git a/lm_eval/tasks/basque_bench/basque_bench.yaml b/lm_eval/tasks/basque_bench/basque_bench.yaml index f542d218..c6c210e8 100644 --- a/lm_eval/tasks/basque_bench/basque_bench.yaml +++ b/lm_eval/tasks/basque_bench/basque_bench.yaml @@ -14,5 +14,6 @@ task: - xcopa_eu - mgsm_direct_eu - mgsm_native_cot_eu + - piqa_eu metadata: version: 1.0 diff --git a/lm_eval/tasks/basque_bench/piqa_eu.yaml b/lm_eval/tasks/basque_bench/piqa_eu.yaml new file mode 100755 index 00000000..b721a9ee --- /dev/null +++ b/lm_eval/tasks/basque_bench/piqa_eu.yaml @@ -0,0 +1,21 @@ +task: piqa_eu +dataset_path: HiTZ/PIQA-eu +dataset_name: null +output_type: multiple_choice +training_split: null +validation_split: validation +test_split: null +doc_to_text: "Galdera: {{goal}}\nErantzuna:" +doc_to_target: label +doc_to_choice: "{{[sol1, sol2]}}" +should_decontaminate: true +doc_to_decontamination_query: goal +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true +metadata: + version: 1.0 -- GitLab From 9632b343a3c894e6db51c1df237524bdd30651b0 Mon Sep 17 00:00:00 2001 From: "Trawinski, Dariusz" Date: Tue, 3 Dec 2024 21:13:14 +0100 Subject: [PATCH 170/194] avoid timeout errors with high concurrency in api_model (#2307) * avoid timeout errors with high concurrency in api_model * style * add timeout * add docs --------- Co-authored-by: Baber --- docs/API_guide.md | 4 ++++ lm_eval/models/api_models.py | 9 +++++++-- 2 files changed, 11 insertions(+), 2 deletions(-) diff --git a/docs/API_guide.md b/docs/API_guide.md index bb8ca2ab..bc06bee8 100644 --- a/docs/API_guide.md +++ b/docs/API_guide.md @@ -50,6 +50,10 @@ When initializing a `TemplateAPI` instance or a subclass, you can provide severa - Useful for APIs that support parallel processing. - Default is 1 (sequential processing). +- `timeout` (int, optional): + - Timeout for API requests in seconds. + - Default is 30. + - `tokenized_requests` (bool): - Determines whether the input is pre-tokenized. Defaults to `True`. - Requests can be sent in either tokenized form (`list[list[int]]`) or as text (`list[str]`, or `str` for batch_size=1). diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index 1c410017..fc88d43d 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -21,7 +21,7 @@ from typing import ( try: import requests - from aiohttp import ClientSession, TCPConnector + from aiohttp import ClientSession, ClientTimeout, TCPConnector from tenacity import RetryError, retry, stop_after_attempt, wait_exponential from tqdm import tqdm from tqdm.asyncio import tqdm_asyncio @@ -81,6 +81,8 @@ class TemplateAPI(TemplateLM): use_fast_tokenizer: bool = True, verify_certificate: bool = True, eos_string: str = None, + # timeout in seconds + timeout: int = 300, **kwargs, ) -> None: super().__init__() @@ -126,6 +128,7 @@ class TemplateAPI(TemplateLM): self.max_retries = int(max_retries) self.verify_certificate = verify_certificate self._eos_string = eos_string + self.timeout = int(timeout) eval_logger.info(f"Using tokenizer {self.tokenizer_backend}") if self.tokenizer_backend is None: @@ -466,7 +469,9 @@ class TemplateAPI(TemplateLM): ) -> Union[List[List[str]], List[List[Tuple[float, bool]]]]: ctxlens = ctxlens if ctxlens else [None] * len(requests) conn = TCPConnector(limit=self._concurrent) - async with ClientSession(connector=conn) as session: + async with ClientSession( + connector=conn, timeout=ClientTimeout(total=self.timeout) + ) as session: retry_: Callable[..., Awaitable[Any]] = retry( stop=stop_after_attempt(self.max_retries), wait=wait_exponential(multiplier=0.5, min=1, max=10), -- GitLab From 4a12959f7d2bb61bf96b9386149d87a21fa47e31 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Wed, 4 Dec 2024 13:00:58 +0000 Subject: [PATCH 171/194] Update README.md (#2534) * Update README.md add caching tip to readme * Update README.md add api link --- README.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 4d6fb875..5dec5454 100644 --- a/README.md +++ b/README.md @@ -261,7 +261,7 @@ Note that for externally hosted models, configs such as `--device` which relate | [Neural Magic DeepSparse](https://github.com/neuralmagic/deepsparse) | ✔️ | `deepsparse` | Any LM from [SparseZoo](https://sparsezoo.neuralmagic.com/) or on [HF Hub with the "deepsparse" tag](https://huggingface.co/models?other=deepsparse) | `generate_until`, `loglikelihood` | ... | | [Neural Magic SparseML](https://github.com/neuralmagic/sparseml) | ✔️ | `sparseml` | Any decoder-only AutoModelForCausalLM from [SparseZoo](https://sparsezoo.neuralmagic.com/) or on [HF Hub](https://huggingface.co/neuralmagic). Especially useful for models with quantization like [`zoo:llama2-7b-gsm8k_llama2_pretrain-pruned60_quantized`](https://sparsezoo.neuralmagic.com/models/llama2-7b-gsm8k_llama2_pretrain-pruned60_quantized) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | ... | | Watsonx.ai | :heavy_check_mark: | `watsonx_llm` | [Supported Watsonx.ai Engines](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/fm-models.html?context=wx) | `generate_until` `loglikelihood` | -| Your local inference server! | :heavy_check_mark: | `local-completions` or `local-chat-completions` | Support for OpenAI API-compatible servers, with easy customization for other APIs. | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | | ... | +| [Your local inference server!](docs/API_guide.md) | :heavy_check_mark: | `local-completions` or `local-chat-completions` | Support for OpenAI API-compatible servers, with easy customization for other APIs. | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | | ... | Models which do not supply logits or logprobs can be used with tasks of type `generate_until` only, while local models, or APIs that supply logprobs/logits of their prompts, can be run on all task types: `generate_until`, `loglikelihood`, `loglikelihood_rolling`, and `multiple_choice`. @@ -338,11 +338,12 @@ lm_eval --model hf \ We support wildcards in task names, for example you can run all of the machine-translated lambada tasks via `--task lambada_openai_mt_*`. -## Saving Results +## Saving & Caching Results To save evaluation results provide an `--output_path`. We also support logging model responses with the `--log_samples` flag for post-hoc analysis. -Additionally, one can provide a directory with `--use_cache` to cache the results of prior runs. This allows you to avoid repeated execution of the same (model, task) pairs for re-scoring. +> [!TIP] +> Use `--use_cache ` to cache evaluation results and skip previously evaluated samples when resuming runs of the same (model, task) pairs. Note that caching is rank-dependent, so restart with the same GPU count if interrupted. You can also use --cache_requests to save dataset preprocessing steps for faster evaluation resumption. To push results and samples to the Hugging Face Hub, first ensure an access token with write access is set in the `HF_TOKEN` environment variable. Then, use the `--hf_hub_log_args` flag to specify the organization, repository name, repository visibility, and whether to push results and samples to the Hub - [example dataset on the HF Hub](https://huggingface.co/datasets/KonradSzafer/lm-eval-results-demo). For instance: -- GitLab From 6824d39d3c6961b7a7dc8cf70b91718e63f2051b Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Wed, 4 Dec 2024 14:55:09 +0000 Subject: [PATCH 172/194] add better testing when both doc_to_text ends in and target_delimiter are whitespaces (#2535) --- tests/test_tasks.py | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/tests/test_tasks.py b/tests/test_tasks.py index 0decb3a1..fc9bb59d 100644 --- a/tests/test_tasks.py +++ b/tests/test_tasks.py @@ -79,11 +79,15 @@ class TestNewTasks: ) _array = [task.doc_to_text(doc) for doc in arr] # space convention; allow txt to have length 0 for perplexity-like tasks since the model tacks an <|endoftext|> on + target_delimiter: str = task.config.target_delimiter if not task.multiple_input: - assert all( - isinstance(x, str) and (x[-1] != " " if len(x) != 0 else True) - for x in _array - ) + for x in _array: + assert isinstance(x, str) + assert ( + (x[-1].isspace() is False if len(x) > 0 else True) + if target_delimiter.isspace() + else True + ), "doc_to_text ends in a whitespace and target delimiter also a whitespace" else: pass -- GitLab From 1f9bc88fe61f6bfa36f74e91ce3d59ab5685e4f1 Mon Sep 17 00:00:00 2001 From: Slawomir Strehlke Date: Wed, 4 Dec 2024 17:18:56 +0100 Subject: [PATCH 173/194] Support pipeline parallel with OpenVINO models (#2349) * Handle pipeline_parallel parameter * Add description of pipeline parallelism with OV models --- README.md | 13 +++++++++++++ lm_eval/models/optimum_lm.py | 3 +++ 2 files changed, 16 insertions(+) diff --git a/README.md b/README.md index 5dec5454..3d33bcc5 100644 --- a/README.md +++ b/README.md @@ -205,6 +205,19 @@ Note that it is recommended to substitute the `python` command by `torchrun --np Not supported yet: multi-node evaluation and combinations of data replication with tensor or pipeline parallelism. +#### Multi-GPU evaluation with OpenVINO models + +Pipeline parallelizm during evaluation is supported with OpenVINO models + +To enable pipeline parallelism, set the `model_args` of `pipeline_parallel`. In addition, you also have to set up `device` to value `HETERO:,` for example `HETERO:GPU.1,GPU.0` For example, the command to use pipeline paralelism of 2 is: + +``` +lm_eval --model openvino \ + --tasks wikitext \ + --model_args pretrained=,pipeline_parallel=True \ + --device HETERO:GPU.1,GPU.0 +``` + ### Tensor + Data Parallel and Optimized Inference with `vLLM` We also support vLLM for faster inference on [supported model types](https://docs.vllm.ai/en/latest/models/supported_models.html), especially faster when splitting a model across multiple GPUs. For single-GPU or multi-GPU — tensor parallel, data parallel, or a combination of both — inference, for example: diff --git a/lm_eval/models/optimum_lm.py b/lm_eval/models/optimum_lm.py index bd262398..7a733aa8 100644 --- a/lm_eval/models/optimum_lm.py +++ b/lm_eval/models/optimum_lm.py @@ -71,6 +71,9 @@ class OptimumLM(HFLM): else: model_kwargs["ov_config"] = {} model_kwargs["ov_config"].setdefault("CACHE_DIR", "") + if 'pipeline_parallel' in model_kwargs: + if model_kwargs['pipeline_parallel']: + model_kwargs["ov_config"]["MODEL_DISTRIBUTION_POLICY"] = "PIPELINE_PARALLEL" model_file = Path(pretrained) / "openvino_model.xml" if model_file.exists(): export = False -- GitLab From bcb4cbf464668450f1969a4f1bef28f8638d1648 Mon Sep 17 00:00:00 2001 From: fzyzcjy <5236035+fzyzcjy@users.noreply.github.com> Date: Thu, 5 Dec 2024 22:52:55 +0800 Subject: [PATCH 174/194] Update README.md (#2546) --- README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/README.md b/README.md index 3d33bcc5..82d261db 100644 --- a/README.md +++ b/README.md @@ -492,7 +492,6 @@ Extras dependencies can be installed via `pip install -e ".[NAME]"` | hf_transfer | For speeding up HF Hub file downloads | | ifeval | For running the IFEval task | | ibm_watsonx_ai | For using IBM watsonx.ai model apis | - | neuronx | For running on AWS inf2 instances | | mamba | For loading Mamba SSM models | | math | For running math task answer checking | -- GitLab From 2d11f2e5317aeae998ddd7d77be44457f699cdc3 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 9 Dec 2024 19:59:19 +0000 Subject: [PATCH 175/194] [API] left truncate for generate_until (#2554) * left truncate for generate_until * pre-commit --- README.md | 2 +- lm_eval/models/api_models.py | 44 ++++++++++++++++++++++++++++++++++-- lm_eval/models/optimum_lm.py | 8 ++++--- 3 files changed, 48 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 82d261db..8bea4748 100644 --- a/README.md +++ b/README.md @@ -209,7 +209,7 @@ Not supported yet: multi-node evaluation and combinations of data replication wi Pipeline parallelizm during evaluation is supported with OpenVINO models -To enable pipeline parallelism, set the `model_args` of `pipeline_parallel`. In addition, you also have to set up `device` to value `HETERO:,` for example `HETERO:GPU.1,GPU.0` For example, the command to use pipeline paralelism of 2 is: +To enable pipeline parallelism, set the `model_args` of `pipeline_parallel`. In addition, you also have to set up `device` to value `HETERO:,` for example `HETERO:GPU.1,GPU.0` For example, the command to use pipeline parallelism of 2 is: ``` lm_eval --model openvino \ diff --git a/lm_eval/models/api_models.py b/lm_eval/models/api_models.py index fc88d43d..24bf1a8a 100644 --- a/lm_eval/models/api_models.py +++ b/lm_eval/models/api_models.py @@ -448,9 +448,13 @@ class TemplateAPI(TemplateLM): for chunk in chunks: for cache_key, context_enc, continuation_enc in chunk: # max_length - 1 as we always have 1 token for generation - inp = (context_enc + continuation_enc)[-(self.max_length) :] + inp = (context_enc + continuation_enc)[-self.max_length :] + if len(inp) < len(context_enc + continuation_enc): + eval_logger.warning( + f"Context length ({len(context_enc)}) + continuation length ({len(continuation_enc)}) > max_length ({self.max_length}). Left truncating context." + ) ctxlen = len(context_enc) - max( - 0, len(context_enc) + len(continuation_enc) - (self.max_length) + 0, len(context_enc) + len(continuation_enc) - self.max_length ) inputs.append(inp) @@ -594,6 +598,24 @@ class TemplateAPI(TemplateLM): pbar = tqdm(desc="Requesting API", total=len(requests)) for chunk in chunked: contexts, all_gen_kwargs, encodings_list = zip(*chunk) + if self.tokenized_requests: + max_gen_toks = all_gen_kwargs[0].get( + "max_gen_toks", self._max_gen_toks + ) + max_context_len = self.max_length - max_gen_toks + + encodings_list = [x[-max_context_len:] for x in encodings_list] + + if any( + len(x) + max_gen_toks > self.max_length for x in encodings_list + ): + eval_logger.warning( + f"Some contexts exceeded (max length: ({self.max_length}) - max_gen_toks: ({max_gen_toks}). They were left truncated." + ) + else: + eval_logger.info( + "Tokenized requests are disabled. Context + generation length is not checked." + ) req = encodings_list if self.tokenized_requests else contexts outputs = retry( stop=stop_after_attempt(self.max_retries), @@ -625,6 +647,24 @@ class TemplateAPI(TemplateLM): else: for chunk in chunked: contexts, all_gen_kwargs, encodings_list = zip(*chunk) + if self.tokenized_requests: + max_gen_toks = all_gen_kwargs[0].get( + "max_gen_toks", self._max_gen_toks + ) + max_context_len = self.max_length - max_gen_toks + + encodings_list = [x[-max_context_len:] for x in encodings_list] + + if any( + len(x) + max_gen_toks > self.max_length for x in encodings_list + ): + eval_logger.warning( + f"Some contexts exceeded (max length: ({self.max_length}) - max_gen_toks ({max_gen_toks}). They were left truncated." + ) + else: + eval_logger.info( + "Tokenized requests are disabled. Context + generation length is not checked." + ) req = encodings_list if self.tokenized_requests else contexts results = itertools.chain.from_iterable( asyncio.run( diff --git a/lm_eval/models/optimum_lm.py b/lm_eval/models/optimum_lm.py index 7a733aa8..b13b321f 100644 --- a/lm_eval/models/optimum_lm.py +++ b/lm_eval/models/optimum_lm.py @@ -71,9 +71,11 @@ class OptimumLM(HFLM): else: model_kwargs["ov_config"] = {} model_kwargs["ov_config"].setdefault("CACHE_DIR", "") - if 'pipeline_parallel' in model_kwargs: - if model_kwargs['pipeline_parallel']: - model_kwargs["ov_config"]["MODEL_DISTRIBUTION_POLICY"] = "PIPELINE_PARALLEL" + if "pipeline_parallel" in model_kwargs: + if model_kwargs["pipeline_parallel"]: + model_kwargs["ov_config"]["MODEL_DISTRIBUTION_POLICY"] = ( + "PIPELINE_PARALLEL" + ) model_file = Path(pretrained) / "openvino_model.xml" if model_file.exists(): export = False -- GitLab From 0b994433b86efdf833dae073d8f1ce5537222bd0 Mon Sep 17 00:00:00 2001 From: Maanu Grover <109391026+maanug-nv@users.noreply.github.com> Date: Mon, 9 Dec 2024 13:38:20 -0800 Subject: [PATCH 176/194] Update Lightning import (#2549) * update import Signed-off-by: Maanu Grover * run formatting --------- Signed-off-by: Maanu Grover --- lm_eval/models/nemo_lm.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/models/nemo_lm.py b/lm_eval/models/nemo_lm.py index cf560197..9b4c19e0 100644 --- a/lm_eval/models/nemo_lm.py +++ b/lm_eval/models/nemo_lm.py @@ -187,11 +187,11 @@ class NeMoLM(LM): **kwargs, ): try: + from lightning.pytorch.trainer.trainer import Trainer from nemo.collections.nlp.modules.common.text_generation_utils import ( generate, ) from nemo.collections.nlp.parts.nlp_overrides import NLPDDPStrategy - from pytorch_lightning.trainer.trainer import Trainer self.generate = generate except ModuleNotFoundError as exception: -- GitLab From 919470a141398f615de92919942066bd2f3e8765 Mon Sep 17 00:00:00 2001 From: Yao Matrix Date: Sat, 14 Dec 2024 00:01:43 +0800 Subject: [PATCH 177/194] add optimum-intel ipex model (#2566) * initial support for optimum-intel ipex model. LM model as first step * format Signed-off-by: Yao Matrix * pass dtype Signed-off-by: Yao Matrix * update README Signed-off-by: Yao, Matrix --------- Signed-off-by: Yao Matrix --- README.md | 2 + lm_eval/models/__init__.py | 1 + lm_eval/models/optimum_ipex.py | 79 ++++++++++++++++++++++++++++++++++ 3 files changed, 82 insertions(+) create mode 100644 lm_eval/models/optimum_ipex.py diff --git a/README.md b/README.md index 8bea4748..1dc08d55 100644 --- a/README.md +++ b/README.md @@ -270,6 +270,7 @@ Note that for externally hosted models, configs such as `--device` which relate | vLLM | :heavy_check_mark: | `vllm` | [Most HF Causal Language Models](https://docs.vllm.ai/en/latest/models/supported_models.html) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | | Mamba | :heavy_check_mark: | `mamba_ssm` | [Mamba architecture Language Models via the `mamba_ssm` package](https://huggingface.co/state-spaces) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | | Huggingface Optimum (Causal LMs) | ✔️ | `openvino` | Any decoder-only AutoModelForCausalLM converted with Huggingface Optimum into OpenVINO™ Intermediate Representation (IR) format | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | ... | +| Huggingface Optimum-intel IPEX (Causal LMs) | ✔️ | `ipex` | Any decoder-only AutoModelForCausalLM | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | ... | | Neuron via AWS Inf2 (Causal LMs) | ✔️ | `neuronx` | Any decoder-only AutoModelForCausalLM supported to run on [huggingface-ami image for inferentia2](https://aws.amazon.com/marketplace/pp/prodview-gr3e6yiscria2) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | ... | | [Neural Magic DeepSparse](https://github.com/neuralmagic/deepsparse) | ✔️ | `deepsparse` | Any LM from [SparseZoo](https://sparsezoo.neuralmagic.com/) or on [HF Hub with the "deepsparse" tag](https://huggingface.co/models?other=deepsparse) | `generate_until`, `loglikelihood` | ... | | [Neural Magic SparseML](https://github.com/neuralmagic/sparseml) | ✔️ | `sparseml` | Any decoder-only AutoModelForCausalLM from [SparseZoo](https://sparsezoo.neuralmagic.com/) or on [HF Hub](https://huggingface.co/neuralmagic). Especially useful for models with quantization like [`zoo:llama2-7b-gsm8k_llama2_pretrain-pruned60_quantized`](https://sparsezoo.neuralmagic.com/models/llama2-7b-gsm8k_llama2_pretrain-pruned60_quantized) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | ... | @@ -492,6 +493,7 @@ Extras dependencies can be installed via `pip install -e ".[NAME]"` | hf_transfer | For speeding up HF Hub file downloads | | ifeval | For running the IFEval task | | ibm_watsonx_ai | For using IBM watsonx.ai model apis | +| ipex | For running on optimum-intel ipex backend | | neuronx | For running on AWS inf2 instances | | mamba | For loading Mamba SSM models | | math | For running math task answer checking | diff --git a/lm_eval/models/__init__.py b/lm_eval/models/__init__.py index cde586ec..39412bb1 100644 --- a/lm_eval/models/__init__.py +++ b/lm_eval/models/__init__.py @@ -11,6 +11,7 @@ from . import ( neuralmagic, neuron_optimum, openai_completions, + optimum_ipex, optimum_lm, textsynth, vllm_causallms, diff --git a/lm_eval/models/optimum_ipex.py b/lm_eval/models/optimum_ipex.py new file mode 100644 index 00000000..56776da1 --- /dev/null +++ b/lm_eval/models/optimum_ipex.py @@ -0,0 +1,79 @@ +from importlib.util import find_spec + +from lm_eval import utils +from lm_eval.api.registry import register_model +from lm_eval.models.huggingface import HFLM +from lm_eval.models.utils import get_dtype + + +eval_logger = utils.eval_logger + + +@register_model("ipex") +class IPEXLM(HFLM): + """ + using the HuggingFace transformers + optimum-intel ipex backend, can run on intel cpu and intel gpu + """ + + def __init__( + self, + **kwargs, + ) -> None: + if "backend" in kwargs: + # currently only supports causal models + assert ( + kwargs["backend"] == "causal" + ), "Currently, only IPEXModelForCausalLM is supported." + + super().__init__( + backend=kwargs.pop("backend", "causal"), + **kwargs, + ) + + def _create_model( + self, + pretrained: str, + revision="main", + dtype="auto", + trust_remote_code=False, + # arguments used for splitting a model across GPUs naively. + # only used if `parallelize=True`. + # (accelerate naive PP (device_map) options) + parallelize=False, + gpus=None, + max_memory_per_gpu=None, + max_cpu_memory=None, + offload_folder="./offload", + # PEFT, delta weights and quantization options + peft=None, + delta=None, + autogptq=False, + gptqmodel=False, + **kwargs, + ) -> None: + if not find_spec("optimum"): + raise ModuleNotFoundError( + "package `optimum` is not installed. Please install it via `pip install optimum[ipex]`" + ) + else: + from optimum.intel import IPEXModelForCausalLM + + model_kwargs = kwargs if kwargs else {} + model_kwargs.update( + self._get_accelerate_args( + parallelize=parallelize, + device_map=kwargs.get("device_map", None), + max_memory_per_gpu=max_memory_per_gpu, + max_cpu_memory=max_cpu_memory, + offload_folder=offload_folder, + gpus=gpus, + ) + ) + + self._model = IPEXModelForCausalLM.from_pretrained( + pretrained, + revision=revision, + torch_dtype=get_dtype(dtype), + trust_remote_code=trust_remote_code, + **model_kwargs, + ) -- GitLab From 8de772f93bf3dc36a7edfe3b2c7ba0ffd6cc7497 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Sat, 14 Dec 2024 13:08:20 +0000 Subject: [PATCH 178/194] add warning to readme (#2568) * make warning prominent * make warning prominent --- docs/new_task_guide.md | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/docs/new_task_guide.md b/docs/new_task_guide.md index dac8541e..a822a887 100644 --- a/docs/new_task_guide.md +++ b/docs/new_task_guide.md @@ -190,7 +190,8 @@ doc_to_target: "{{answer}}" ``` -**Important**: we now add `target_delimiter` between input and target which defaults to " ", such that the full input-output string is `doc_to_target(doc) + target_delimiter + doc_to_text(doc)`. `doc_to_text` and `doc_to_target` should not contain trailing right or left whitespace, respectively. +> [!WARNING] +> We add `target_delimiter` between input and target which defaults to " ", such that the full input-output string is `doc_to_text(doc) + target_delimiter + doc_to_target(doc)`. `doc_to_text` and `doc_to_target` should not contain trailing right or left whitespace, respectively. For multiple choice the target will be each choice index concatenated with the delimiter. #### Multiple choice format @@ -206,7 +207,7 @@ doc_to_choice: "{{[distractor1, distractor2, distractor3, correct_answer]}}" ``` Task implementers are thus able to decide what the answer choices should be for a document, and what prompt format to use. -The label index can also be sourced from a feature directly. For example in `superglue/boolq`, the label index if defined in the feature `label`. We can set `doc_to_target` as simply `label`. The options or verbalizers can be written in a the form of a list `["no", "yes"]` that will correspond to the label index. +The label index can also be sourced from a feature directly. For example in `superglue/boolq`, the label index if defined in the feature `label`. We can set `doc_to_target` as simply `label`. The options or verbalizers can be written in the form of a list `["no", "yes"]` that will correspond to the label index. ```yaml doc_to_text: "{{passage}}\nQuestion: {{question}}?\nAnswer:" -- GitLab From 976d8a0bfa2b7e053f1122278755b4c4ecb3926b Mon Sep 17 00:00:00 2001 From: Rima Shahbazyan <74137119+rimashahbazyan@users.noreply.github.com> Date: Mon, 16 Dec 2024 18:27:57 +0400 Subject: [PATCH 179/194] Adding new subtask to SCORE tasks: non greedy robustness (#2558) * score readme added * generate until task's "until" parameter's default value fixed. * score mmlu-pro and agieval added * changed macro accuracy to micro for agieval * Always E removed from agi eval * redundancies removed * MATH added * minor cosmetic changes for math * Licenses added Readme updated * changes for flake8 + license header on math * Score added to readme and precommit was run. * Score added to readme and precommit was run. * Import error fixed * math task bugfix postprocess minor fix * CR for math added * math CR * math task bugfix postprocess minor fix CR for math added * Math cr fixed * mmlu_pro non_greedy task added * non greedy summarizer added * Non greedy for all score tasks * Bugfixes for non-greedy * fixing the until argument * undoing the change to "until" arguments default behaviour * minor fix in summarizer * log naming changes for better readability * math subtasks naming fix * agieval subtask naming fix * logging added for debugging * path issue fixed * minor fix * path fix * path fix * non_greedy_math minor fix * final changes * changed readme for non-greedy added Nvidia header added wxample script for non_greedy changed prompts to match that fo trt runs * non greedy summarizer bugfix * non_greedy summarizer fixed --- lm_eval/tasks/score/NON_GREEDY.md | 45 +++ lm_eval/tasks/score/README.md | 14 +- ...on_greedy_robustness_agieval_aqua_rat.yaml | 36 +++ ...n_greedy_robustness_agieval_logiqa_en.yaml | 17 + ...non_greedy_robustness_agieval_lsat_rc.yaml | 17 + ...on_greedy_robustness_agieval_lstat_ar.yaml | 17 + ...on_greedy_robustness_agieval_lstat_lr.yaml | 17 + .../non_greedy_robustness_agieval_sat_en.yaml | 17 + ...on_greedy_robustness_agieval_sat_math.yaml | 17 + .../score/agi_eval/prompt_templates.json | 6 +- .../score_non_greedy_robustness_agieval.yaml | 31 ++ .../agi_eval/score_robustness_agieval.yaml | 1 + lm_eval/tasks/score/agi_eval/utils_agieval.py | 32 ++ .../non_greedy_robustness_math_algebra.yaml | 36 +++ ...edy_robustness_math_counting_and_prob.yaml | 17 + .../non_greedy_robustness_math_geometry.yaml | 17 + ..._robustness_math_intermediate_algebra.yaml | 17 + ...non_greedy_robustness_math_num_theory.yaml | 17 + ...non_greedy_robustness_math_prealgebra.yaml | 17 + .../non_greedy_robustness_math_precalc.yaml | 17 + .../tasks/score/math/prompt_templates.json | 4 + .../score_non_greedy_robustness_math.yaml | 30 ++ .../score/math/score_robustness_math.yaml | 1 + lm_eval/tasks/score/math/utils_math.py | 37 ++- .../score/mmlu_pro/prompt_templates.json | 7 +- .../score_non_greedy_robustness_mmlu_pro.yaml | 38 +++ .../tasks/score/mmlu_pro/utils_mmlu_pro.py | 33 ++ lm_eval/tasks/score/non_greedy.sh | 46 +++ lm_eval/tasks/score/non_greedy_summarizer.py | 305 ++++++++++++++++++ lm_eval/tasks/score/utils.py | 30 ++ 30 files changed, 929 insertions(+), 7 deletions(-) create mode 100644 lm_eval/tasks/score/NON_GREEDY.md create mode 100644 lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_aqua_rat.yaml create mode 100644 lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_logiqa_en.yaml create mode 100644 lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lsat_rc.yaml create mode 100644 lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lstat_ar.yaml create mode 100644 lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lstat_lr.yaml create mode 100644 lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_sat_en.yaml create mode 100644 lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_sat_math.yaml create mode 100644 lm_eval/tasks/score/agi_eval/score_non_greedy_robustness_agieval.yaml create mode 100644 lm_eval/tasks/score/math/non_greedy_robustness_math_algebra.yaml create mode 100644 lm_eval/tasks/score/math/non_greedy_robustness_math_counting_and_prob.yaml create mode 100644 lm_eval/tasks/score/math/non_greedy_robustness_math_geometry.yaml create mode 100644 lm_eval/tasks/score/math/non_greedy_robustness_math_intermediate_algebra.yaml create mode 100644 lm_eval/tasks/score/math/non_greedy_robustness_math_num_theory.yaml create mode 100644 lm_eval/tasks/score/math/non_greedy_robustness_math_prealgebra.yaml create mode 100644 lm_eval/tasks/score/math/non_greedy_robustness_math_precalc.yaml create mode 100644 lm_eval/tasks/score/math/score_non_greedy_robustness_math.yaml create mode 100644 lm_eval/tasks/score/mmlu_pro/score_non_greedy_robustness_mmlu_pro.yaml create mode 100755 lm_eval/tasks/score/non_greedy.sh create mode 100644 lm_eval/tasks/score/non_greedy_summarizer.py diff --git a/lm_eval/tasks/score/NON_GREEDY.md b/lm_eval/tasks/score/NON_GREEDY.md new file mode 100644 index 00000000..41da5d3d --- /dev/null +++ b/lm_eval/tasks/score/NON_GREEDY.md @@ -0,0 +1,45 @@ +``` +Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +```` +# Non Greedy Evaluation + +This task checks for model's consistency towards seed changes during generation. +More particularly it evaluates the model's accuracy and consistancy rate with 5 +different seeds (seed = 1, 2,...,5) for a fixed prompt with temperature set to 0.7. + +## How to run the Non-Greedy evaluation of SCORE? + +Evaluation for non greedy tasks differs a bit from other score tasks as it is required to pass different seeds as an argument manually. Below you can find the step-by-step guide on how to correctly run the **Score Non-Greedy** evaluation. + +To run the evaluation of the Non-Greedy tasks with 5 different seeds you should: +1. For a given dataset run the evaluation by + * specifying the task as `score_non_greedy_robustness_{DATASET_NAME}` (`DATASET_NAME` being either`agieval`, `mmlu_pro` or `math`) + * fixing the seed with the run argument `--seed=1` + * passing the `--log_samples` argument* + * specifying an output with `--output_path=SOME_OUTPUT_PATH/seed_1` + * if running with vllm it is important to set the seed in the `--model_args` just by specifying the `seed` parameter\ + +2. Repeat the process for 5 times**, changing the `--seed` and the `--output_path` arguments accordingly from 1 to 5. + +3. When all 5 runs are finished and logs are saved, run the `./lm_eval/tasks/score/non_greedy_summarizer.py` script by passing the the output directory of the above runs to the `--log_dir` argument***, and by specifying the dataset name for which the evaluations were run with `--dataset` argument(`agieval`, `mmlu_pro` or `math`). \ + +4. The script will return the default lm_evaluation_harness table where accuracies for each seed and the consistancy rate are calculated. + + +\* _As this evaluation requires `--log_samples` to be True, it will need some extra disk space to save the prediction results for each seed._ + +\*\* _Refer to [`./lm_eval/tasks/score/non_greedy.sh`](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/lm_eval/tasks/score/non_greedy.sh) to see an example of non greedy evaluation command for each seed._ + +\*\*\* _To `--log_dir` argument one should pass the path of the parent folder of `"seed_1", "seed_2", ...` directories, that is not necessarily the `--output_path` passed to the evaulater in the 1st step._ diff --git a/lm_eval/tasks/score/README.md b/lm_eval/tasks/score/README.md index 4055d5f7..a0bf7d92 100644 --- a/lm_eval/tasks/score/README.md +++ b/lm_eval/tasks/score/README.md @@ -31,7 +31,7 @@ limitations under the License. ## Tasks -Both `score_robustness_mmlu_pro` and `score_robustness_agieval` contain the following 2 tasks: +Both `score_robustness_mmlu_pro` and `score_robustness_agieval` contain the following 3 tasks: * Option order robustness: `score_option_order_robustness_mmlu_pro`, @@ -41,10 +41,14 @@ Both `score_robustness_mmlu_pro` and `score_robustness_agieval` contain the foll `score_prompt_robustness_mmlu_pro`, `score_prompt_robustness_agieval`, -Whereas math contains only +* Non greedy robustness +`score_non_greedy_robustness_mmlu_pro`, +`score_non_greedy_robustness_agieval`, + +Whereas math contains the following 2: * Prompt robustness: `score_prompt_robustness_math` - +`score_non_greedy_robustness_math`, ### Option order robustness @@ -55,6 +59,10 @@ Measures the model's robustness to the placement of the correct answer in the op Measures the model's robustness to 10 different prompts. list of the prompts can be found in the `./prompt_templates.json` file under the key `prompt_robustness`. +### Non greedy robustness + +Measures the model's robustness to 5 different seeds: seeds = \[1-5\]. For evaluating on the non greedy task, please, refer to [NON_GREEDY.md](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/lm_eval/tasks/score/NON_GREEDY.md) + ## Metrics All robustness tasks calculate 2 metrics: *Accuracy* and *Consistency Rate(CR)* [[4](#cr)]. diff --git a/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_aqua_rat.yaml b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_aqua_rat.yaml new file mode 100644 index 00000000..126630f0 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_aqua_rat.yaml @@ -0,0 +1,36 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +task: non_greedy_robustness_agieval_aqua_rat +dataset_path: hails/agieval-aqua-rat +dataset_name: default +output_type: generate_until +test_split: test +process_docs: !function utils_agieval.non_greedy_robustness_process_docs +doc_to_text: !function utils_agieval.agi_eval_robustness_doc_to_text +doc_to_target: answer +generation_kwargs: + max_gen_toks: 1024 + do_sample: true + temperature: 0.7 + until: [] +process_results: !function utils_agieval.non_greedy_robustness_process_results +metric_list: + - metric: non_greedy_accuracy + aggregation: !function utils_agieval.non_greedy_accuracy + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_logiqa_en.yaml b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_logiqa_en.yaml new file mode 100644 index 00000000..ad1790e8 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_logiqa_en.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_agieval_aqua_rat.yaml +task: non_greedy_robustness_agieval_logiqa_en +dataset_path: hails/agieval-logiqa-en diff --git a/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lsat_rc.yaml b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lsat_rc.yaml new file mode 100644 index 00000000..a0ebf340 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lsat_rc.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_agieval_aqua_rat.yaml +task: non_greedy_robustness_agieval_lsat_rc +dataset_path: hails/agieval-lsat-rc diff --git a/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lstat_ar.yaml b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lstat_ar.yaml new file mode 100644 index 00000000..666dace1 --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lstat_ar.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_agieval_aqua_rat.yaml +task: non_greedy_robustness_agieval_lsat_ar +dataset_path: hails/agieval-lsat-ar diff --git a/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lstat_lr.yaml b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lstat_lr.yaml new file mode 100644 index 00000000..d780d7eb --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_lstat_lr.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_agieval_aqua_rat.yaml +task: non_greedy_robustness_agieval_lsat_lr +dataset_path: hails/agieval-lsat-lr diff --git a/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_sat_en.yaml b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_sat_en.yaml new file mode 100644 index 00000000..3a7ba4ed --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_sat_en.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_agieval_aqua_rat.yaml +task: non_greedy_robustness_agieval_sat_en +dataset_path: hails/agieval-sat-en diff --git a/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_sat_math.yaml b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_sat_math.yaml new file mode 100644 index 00000000..34e4beeb --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/non_greedy_robustness_agieval_sat_math.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_agieval_aqua_rat.yaml +task: non_greedy_robustness_agieval_sat_math +dataset_path: hails/agieval-sat-math diff --git a/lm_eval/tasks/score/agi_eval/prompt_templates.json b/lm_eval/tasks/score/agi_eval/prompt_templates.json index 720a6635..979b53e6 100644 --- a/lm_eval/tasks/score/agi_eval/prompt_templates.json +++ b/lm_eval/tasks/score/agi_eval/prompt_templates.json @@ -1,9 +1,13 @@ { "option_order_robustness":{ - "prompt": "For the multiple-choice question, which option (A-E) is correct?.\n\nQuestion: {question}{options}\n\nEnd the answer with the following:\nThe best answer is (the_answer_letter) where the (the_answer_letter) is one of 'A', 'B', 'C', 'D' or 'E'.", + "prompt": "For the multiple-choice question, which option (A-E) is correct?.\n\nQuestion:{question}{options}\nEnd the answer with the following:\nThe best answer is (the_answer_letter) where the (the_answer_letter) is one of 'A', 'B', 'C', 'D' or 'E'.", "options_format": "\n{letter}: {option}" }, + "non_greedy_robustness":{ + "prompt": "For the multiple-choice question, which option (A-E) is correct?.\n\nQuestion:{question}{options}\nEnd the answer with the following:\nThe best answer is (the_answer_letter) where the (the_answer_letter) is one of 'A', 'B', 'C', 'D' or 'E'.", + "options_format": "\n{letter}: {option}" + }, "prompt_robustness":[ { diff --git a/lm_eval/tasks/score/agi_eval/score_non_greedy_robustness_agieval.yaml b/lm_eval/tasks/score/agi_eval/score_non_greedy_robustness_agieval.yaml new file mode 100644 index 00000000..c5ab43be --- /dev/null +++ b/lm_eval/tasks/score/agi_eval/score_non_greedy_robustness_agieval.yaml @@ -0,0 +1,31 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +group: score_non_greedy_robustness_agieval +task: + - non_greedy_robustness_agieval_aqua_rat + - non_greedy_robustness_agieval_logiqa_en + - non_greedy_robustness_agieval_lsat_ar + - non_greedy_robustness_agieval_lsat_lr + - non_greedy_robustness_agieval_lsat_rc + - non_greedy_robustness_agieval_sat_en + - non_greedy_robustness_agieval_sat_math + +aggregate_metric_list: + - metric: non_greedy_accuracy + aggregation: mean + weight_by_size: true + +metadata: + version: 1.0 diff --git a/lm_eval/tasks/score/agi_eval/score_robustness_agieval.yaml b/lm_eval/tasks/score/agi_eval/score_robustness_agieval.yaml index 354cb567..fe6d8a73 100644 --- a/lm_eval/tasks/score/agi_eval/score_robustness_agieval.yaml +++ b/lm_eval/tasks/score/agi_eval/score_robustness_agieval.yaml @@ -16,5 +16,6 @@ group: score_robustness_agieval task: - score_prompt_robustness_agieval - score_option_order_robustness_agieval + - score_non_greedy_robustness_agieval metadata: version: 1.0 diff --git a/lm_eval/tasks/score/agi_eval/utils_agieval.py b/lm_eval/tasks/score/agi_eval/utils_agieval.py index b8034259..4381a2cb 100644 --- a/lm_eval/tasks/score/agi_eval/utils_agieval.py +++ b/lm_eval/tasks/score/agi_eval/utils_agieval.py @@ -29,6 +29,7 @@ TEMPLATE_FILE_PATH = os.path.join(os.path.dirname(__file__), "prompt_templates.j PROMPT_ROBUSTNESS_TEMPLATE_KEY = "prompt_robustness" OPTION_ORDER_ROBUSTNESS_TEMPLATE_KEY = "option_order_robustness" +NON_GREEDY_ROBUSTNESS_TEMPLATE_KEY = "non_greedy_robustness" QUESTION_KEY = "query" ANSWER_INDEX_KEY = "gold" @@ -93,6 +94,13 @@ option_order_robustness_process_docs = partial( dataset_specific_preprocess=initial_process_docs, ) +non_greedy_robustness_process_docs = partial( + utils.non_greedy_robustness_process_docs, + templates_key=NON_GREEDY_ROBUSTNESS_TEMPLATE_KEY, + template_file_path=TEMPLATE_FILE_PATH, + dataset_specific_preprocess=initial_process_docs, +) + def prompt_robustness_process_results(doc, results) -> Dict[str, float]: final_answer = utils.__postprocess_pred(results[0]) @@ -135,6 +143,17 @@ def option_order_robustness_process_results(doc, results) -> Dict[str, float]: } +def non_greedy_robustness_process_results(doc, results) -> Dict[str, float]: + final_answer = utils.__postprocess_pred(results[0]) + final_answer = utils.translate_model_answer_to_labels( + final_answer, option_format=doc["options_format"], labels=LABELS + ) + question_id = doc["question_id"] + gt = LABELS[doc["answer_index"]] + + return {"non_greedy_accuracy": (question_id, final_answer, gt, None)} + + def per_prompt_accuracy(results: List[Dict[str, Any]], p_id=0) -> float: accuracies = [] for result in results: @@ -181,3 +200,16 @@ per_option_accuracy_c = partial(per_option_accuracy, always_opt="C") per_option_accuracy_d = partial(per_option_accuracy, always_opt="D") options_consistency_rate = partial(utils.options_consistency_rate, labels=LABELS) + + +def non_greedy_accuracy(results: List[Dict[str, Any]]) -> float: + accuracies = [] + for result in results: + question_id, final_answer, gt, category = result + + accuracies.append(final_answer == gt) + + accuracy = sum(accuracies) / len(accuracies) + eval_logger.info(f"Non greedy accuracy: {accuracy}") + + return np.round(accuracy, 4) diff --git a/lm_eval/tasks/score/math/non_greedy_robustness_math_algebra.yaml b/lm_eval/tasks/score/math/non_greedy_robustness_math_algebra.yaml new file mode 100644 index 00000000..0ca1493f --- /dev/null +++ b/lm_eval/tasks/score/math/non_greedy_robustness_math_algebra.yaml @@ -0,0 +1,36 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +task: non_greedy_robustness_math_algebra +dataset_path: EleutherAI/hendrycks_math +dataset_name: algebra +output_type: generate_until +test_split: test +process_docs: !function utils_math.non_greedy_robustness_process_docs +doc_to_text: !function utils_math.math_robustness_doc_to_text +doc_to_target: answer +generation_kwargs: + max_gen_toks: 1024 + do_sample: true + temperature: 0.7 + until: [] +process_results: !function utils_math.non_greedy_robustness_process_results +metric_list: + - metric: non_greedy_accuracy + aggregation: !function utils_math.non_greedy_accuracy + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/score/math/non_greedy_robustness_math_counting_and_prob.yaml b/lm_eval/tasks/score/math/non_greedy_robustness_math_counting_and_prob.yaml new file mode 100644 index 00000000..4f74c68d --- /dev/null +++ b/lm_eval/tasks/score/math/non_greedy_robustness_math_counting_and_prob.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_math_algebra.yaml +dataset_name: counting_and_probability +task: non_greedy_robustness_math_counting_and_prob diff --git a/lm_eval/tasks/score/math/non_greedy_robustness_math_geometry.yaml b/lm_eval/tasks/score/math/non_greedy_robustness_math_geometry.yaml new file mode 100644 index 00000000..6adb0cdc --- /dev/null +++ b/lm_eval/tasks/score/math/non_greedy_robustness_math_geometry.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_math_algebra.yaml +dataset_name: geometry +task: non_greedy_robustness_math_geometry diff --git a/lm_eval/tasks/score/math/non_greedy_robustness_math_intermediate_algebra.yaml b/lm_eval/tasks/score/math/non_greedy_robustness_math_intermediate_algebra.yaml new file mode 100644 index 00000000..3efe9cc0 --- /dev/null +++ b/lm_eval/tasks/score/math/non_greedy_robustness_math_intermediate_algebra.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_math_algebra.yaml +dataset_name: intermediate_algebra +task: non_greedy_robustness_math_intermediate_algebra diff --git a/lm_eval/tasks/score/math/non_greedy_robustness_math_num_theory.yaml b/lm_eval/tasks/score/math/non_greedy_robustness_math_num_theory.yaml new file mode 100644 index 00000000..2a089c16 --- /dev/null +++ b/lm_eval/tasks/score/math/non_greedy_robustness_math_num_theory.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_math_algebra.yaml +dataset_name: number_theory +task: non_greedy_robustness_math_num_theory diff --git a/lm_eval/tasks/score/math/non_greedy_robustness_math_prealgebra.yaml b/lm_eval/tasks/score/math/non_greedy_robustness_math_prealgebra.yaml new file mode 100644 index 00000000..b292bc7e --- /dev/null +++ b/lm_eval/tasks/score/math/non_greedy_robustness_math_prealgebra.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_math_algebra.yaml +dataset_name: prealgebra +task: non_greedy_robustness_math_prealgebra diff --git a/lm_eval/tasks/score/math/non_greedy_robustness_math_precalc.yaml b/lm_eval/tasks/score/math/non_greedy_robustness_math_precalc.yaml new file mode 100644 index 00000000..de773fd9 --- /dev/null +++ b/lm_eval/tasks/score/math/non_greedy_robustness_math_precalc.yaml @@ -0,0 +1,17 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +include: non_greedy_robustness_math_algebra.yaml +dataset_name: precalculus +task: non_greedy_robustness_math_precalc diff --git a/lm_eval/tasks/score/math/prompt_templates.json b/lm_eval/tasks/score/math/prompt_templates.json index 072f5740..e4cf071b 100644 --- a/lm_eval/tasks/score/math/prompt_templates.json +++ b/lm_eval/tasks/score/math/prompt_templates.json @@ -1,4 +1,8 @@ { + "non_greedy_robustness": { + "prompt": "Calculate the answer to this math problem\nProblem: {question}\nConclude your answer with:\nThe final answer is: $\\boxed{{answer}}$\nwhere [answer] is just the final number or expression that solves the problem." + }, + "prompt_robustness": [ { "prompt": "Efficiently solve the following math challenge. Explain your approach step-by-step\nThe answer should end with: The final answer is: $\\boxed{{answer}}$\nwhere [answer] is just the final number or expression that solves the problem\nProblem: {question}\nLets think step by step" diff --git a/lm_eval/tasks/score/math/score_non_greedy_robustness_math.yaml b/lm_eval/tasks/score/math/score_non_greedy_robustness_math.yaml new file mode 100644 index 00000000..d3bf72d3 --- /dev/null +++ b/lm_eval/tasks/score/math/score_non_greedy_robustness_math.yaml @@ -0,0 +1,30 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +group: score_non_greedy_robustness_math +task: + - non_greedy_robustness_math_algebra + - non_greedy_robustness_math_counting_and_prob + - non_greedy_robustness_math_geometry + - non_greedy_robustness_math_intermediate_algebra + - non_greedy_robustness_math_num_theory + - non_greedy_robustness_math_prealgebra + - non_greedy_robustness_math_precalc + +aggregate_metric_list: + - metric: non_greedy_accuracy + aggregation: mean + weight_by_size: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/score/math/score_robustness_math.yaml b/lm_eval/tasks/score/math/score_robustness_math.yaml index f3b73366..472a5b49 100644 --- a/lm_eval/tasks/score/math/score_robustness_math.yaml +++ b/lm_eval/tasks/score/math/score_robustness_math.yaml @@ -15,5 +15,6 @@ group: score_robustness_math task: - score_prompt_robustness_math + - score_non_greedy_robustness_math metadata: version: 1.0 diff --git a/lm_eval/tasks/score/math/utils_math.py b/lm_eval/tasks/score/math/utils_math.py index cf41473a..4068b179 100644 --- a/lm_eval/tasks/score/math/utils_math.py +++ b/lm_eval/tasks/score/math/utils_math.py @@ -34,6 +34,7 @@ from lm_eval.utils import eval_logger TEMPLATE_FILE_PATH = os.path.join(os.path.dirname(__file__), "prompt_templates.json") PROMPT_ROBUSTNESS_TEMPLATE_KEY = "prompt_robustness" +NON_GREEDY_ROBUSTNESS_TEMPLATE_KEY = "non_greedy_robustness" math_robustness_doc_to_text = robustness_doc_to_text @@ -141,8 +142,17 @@ def prompt_robustness_process_docs(doc: datasets.Dataset) -> datasets.Dataset: doc = process_docs(doc) return utils.process_docs_add_prompts( doc, - PROMPT_ROBUSTNESS_TEMPLATE_KEY, - TEMPLATE_FILE_PATH, + templates_key=PROMPT_ROBUSTNESS_TEMPLATE_KEY, + template_file_path=TEMPLATE_FILE_PATH, + ) + + +def non_greedy_robustness_process_docs(doc: datasets.Dataset) -> datasets.Dataset: + doc = process_docs(doc) + return utils.non_greedy_robustness_process_docs( + doc, + templates_key=NON_GREEDY_ROBUSTNESS_TEMPLATE_KEY, + template_file_path=TEMPLATE_FILE_PATH, ) @@ -163,6 +173,13 @@ def process_results(doc: dict, results: List[str]) -> Dict[str, int]: return results +def non_greedy_robustness_process_results( + doc: dict, results: List[str] +) -> Dict[str, int]: + answer = extract_answer(results[0]) + return {"non_greedy_accuracy": (doc["question_id"], answer, doc["answer"], None)} + + def per_prompt_accuracy(results: List[Dict[str, Any]], p_id=0) -> float: accuracies = [] for result in results: @@ -233,3 +250,19 @@ def math_prompt_consistency_rate(results: List[Dict[str, Any]]) -> float: question_answers_list = [answers for answers in question_answers_dict.values()] return calculate_consistency_rate(question_answers_list) + + +def non_greedy_accuracy(results: List[Dict[str, Any]]) -> float: + accuracies = [] + for result in results: + question_id, final_answer, gt, _ = result + if math_equal(final_answer, gt): + retval = 1 + else: + retval = 0 + accuracies.append(retval) + + accuracy = sum(accuracies) / len(accuracies) + eval_logger.info(f"Non greedy accuracy: {accuracy}") + + return np.round(accuracy, 4) diff --git a/lm_eval/tasks/score/mmlu_pro/prompt_templates.json b/lm_eval/tasks/score/mmlu_pro/prompt_templates.json index 57278cd1..008598ba 100644 --- a/lm_eval/tasks/score/mmlu_pro/prompt_templates.json +++ b/lm_eval/tasks/score/mmlu_pro/prompt_templates.json @@ -1,6 +1,11 @@ { "option_order_robustness":{ - "prompt": "For the multiple-choice question related to {category}, which option (A-J) is correct?.\n\nQuestion: {question}{options}\n\nEnd the answer with the following:\nThe best answer is (the_answer_letter) where the (the_answer_letter) is one of 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I' or 'J'.", + "prompt": "For the multiple-choice question related to {category}, which option (A-J) is correct?.\n\nQuestion:{question}{options}\nEnd the answer with the following:\nThe best answer is (the_answer_letter) where the (the_answer_letter) is one of 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I' or 'J'.", + "options_format": "\n{letter}: {option}" + }, + + "non_greedy_robustness":{ + "prompt": "For the multiple-choice question related to {category}, which option (A-J) is correct?.\n\nQuestion:{question}{options}\nEnd the answer with the following:\nThe best answer is (the_answer_letter) where the (the_answer_letter) is one of 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I' or 'J'.", "options_format": "\n{letter}: {option}" }, diff --git a/lm_eval/tasks/score/mmlu_pro/score_non_greedy_robustness_mmlu_pro.yaml b/lm_eval/tasks/score/mmlu_pro/score_non_greedy_robustness_mmlu_pro.yaml new file mode 100644 index 00000000..1ee8ee5f --- /dev/null +++ b/lm_eval/tasks/score/mmlu_pro/score_non_greedy_robustness_mmlu_pro.yaml @@ -0,0 +1,38 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. + +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at + +# http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +tag: score_robustness_mmlu_pro +task: score_non_greedy_robustness_mmlu_pro +dataset_path: TIGER-Lab/MMLU-Pro +dataset_name: default +output_type: generate_until +validation_split: validation +test_split: test +process_docs: !function utils_mmlu_pro.non_greedy_robustness_process_docs +doc_to_text: !function utils_mmlu_pro.mmlu_pro_robustness_doc_to_text +doc_to_target: answer +generation_kwargs: + until: [] + max_gen_toks: 1024 + do_sample: true + temperature: 0.7 +process_results: !function utils_mmlu_pro.non_greedy_robustness_process_results +metric_list: + - metric: non_greedy_macro_accuracy + aggregation: !function utils_mmlu_pro.non_greedy_macro_accuracy + higher_is_better: true +metadata: + version: 1.0 +dataset_kwargs: + trust_remote_code: true diff --git a/lm_eval/tasks/score/mmlu_pro/utils_mmlu_pro.py b/lm_eval/tasks/score/mmlu_pro/utils_mmlu_pro.py index 4dd4b657..da46e101 100644 --- a/lm_eval/tasks/score/mmlu_pro/utils_mmlu_pro.py +++ b/lm_eval/tasks/score/mmlu_pro/utils_mmlu_pro.py @@ -27,6 +27,7 @@ TEMPLATE_FILE_PATH = os.path.join(os.path.dirname(__file__), "prompt_templates.j PROMPT_ROBUSTNESS_TEMPLATE_KEY = "prompt_robustness" OPTION_ORDER_ROBUSTNESS_TEMPLATE_KEY = "option_order_robustness" +NON_GREEDY_ROBUSTNESS_TEMPLATE_KEY = "non_greedy_robustness" QUESTION_KEY = "question" @@ -48,6 +49,23 @@ option_order_robustness_process_docs = partial( templates_key=OPTION_ORDER_ROBUSTNESS_TEMPLATE_KEY, labels=LABELS, ) +non_greedy_robustness_process_docs = partial( + utils.non_greedy_robustness_process_docs, + template_file_path=TEMPLATE_FILE_PATH, + templates_key=NON_GREEDY_ROBUSTNESS_TEMPLATE_KEY, +) + + +def non_greedy_robustness_process_results(doc, results) -> Dict[str, float]: + final_answer = utils.__postprocess_pred(results[0]) + final_answer = utils.translate_model_answer_to_labels( + final_answer, option_format=doc["options_format"], labels=LABELS + ) + question_id = doc["question_id"] + category = doc["category"] + gt = LABELS[doc["answer_index"]] + + return {"non_greedy_macro_accuracy": (question_id, final_answer, gt, category)} def prompt_robustness_process_results(doc, results) -> Dict[str, float]: @@ -162,3 +180,18 @@ per_option_macro_accuracy_i = partial(per_option_macro_accuracy, always_opt="I") per_option_macro_accuracy_j = partial(per_option_macro_accuracy, always_opt="J") options_consistency_rate = partial(utils.options_consistency_rate, labels=LABELS) + + +def non_greedy_macro_accuracy(results: List[Dict[str, Any]]) -> float: + accuracies = {} + for result in results: + question_id, final_answer, gt, category = result + if category not in accuracies: + accuracies[category] = [] + accuracies[category].append(final_answer == gt) + + for key in accuracies: + accuracies[key] = sum(accuracies[key]) / len(accuracies[key]) + eval_logger.info(f"Non greedy, category - {key} accuracy: {accuracies[key]}") + + return np.round(np.mean([v for v in accuracies.values()]), 4) diff --git a/lm_eval/tasks/score/non_greedy.sh b/lm_eval/tasks/score/non_greedy.sh new file mode 100755 index 00000000..3dd6fe8f --- /dev/null +++ b/lm_eval/tasks/score/non_greedy.sh @@ -0,0 +1,46 @@ +#!/bin/bash + +helpFunction() +{ + echo "" + echo "Usage: $0 -m MODEL -t TASK -s SEED -o OUTPUT_DIR" + echo -e "\t-m huggingface model name" + echo -e "\t-t task name one of score_non_greedy_robustness_[agieval|mmlu_pro|math]" + echo -e "\t-s random seed for evaluation [1-5]" + echo -e "\t-o output directory" + exit 1 # Exit script after printing help +} + +while getopts "m:t:s:" opt +do + case "$opt" in + m ) MODEL="$OPTARG" ;; + t ) TASK="$OPTARG" ;; + s ) SEED="$OPTARG" ;; + o ) OUTPUT_DIR="$OPTARG" ;; + ? ) helpFunction ;; # Print helpFunction in case parameter is non-existent + esac +done + +if [ -z "$MODEL" ] | [ -z "$TASK" ] | [ -z "$SEED" ] | [ -z "$OUTPUT_DIR" ] +then + echo "Some or all of the parameters are empty"; + helpFunction +fi + +echo "evaluating $MODEL on task $TASK with seed $SEED" +echo "output will be saved in $OUTPUT_DIR" + +TENSOR_PARALLEL=8 +BATCH_SIZE="auto" + +echo "running evaluation on vllm with tensor parallelism $TENSOR_PARALLEL" + +lm_eval --model vllm \\ + --model_args pretrained=$MODEL,dtype=bfloat16,tensor_parallel_size=$TENSOR_PARALLEL,gpu_memory_utilization=0.9,\\ + max_model_len=4096,data_parallel_size=1,disable_custom_all_reduce=True,enforce_eager=False,seed=$SEED\\ + --apply_chat_template \\ + --tasks $TASKS \\ + --batch_size $BATCH_SIZE \\ + --log_samples \\ + --output_path $OUTPUT_DIR \\ diff --git a/lm_eval/tasks/score/non_greedy_summarizer.py b/lm_eval/tasks/score/non_greedy_summarizer.py new file mode 100644 index 00000000..9a927288 --- /dev/null +++ b/lm_eval/tasks/score/non_greedy_summarizer.py @@ -0,0 +1,305 @@ +# Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import glob +import json +import os +from datetime import datetime +from itertools import combinations +from pathlib import Path +from typing import List + +import pandas as pd + +from lm_eval.tasks.score.math.math_grader import math_equal +from lm_eval.utils import handle_non_serializable, make_table + + +N_SEEDS = 5 + + +def load_json_logs(file_paths, subtasks): + """ + Loads JSON logs of jsonl format from file paths into a single DataFrame. + + Args: + file_paths: List of file paths to the JSON logs. + + Returns: + A DataFrame containing the logs. + """ + per_seed_df = { + "question_id": [], + "final_answer_seed_": [], + "gt": [], + "category": [], + } + _search_key = None + for i in range(len(file_paths)): + file_path = file_paths[i] + with open(file_path, "r") as f: + for line in f: + datapoint = json.loads(line) + if _search_key is None: + if "non_greedy_macro_accuracy" in datapoint: + _search_key = "non_greedy_macro_accuracy" + elif "non_greedy_accuracy" in datapoint: + _search_key = "non_greedy_accuracy" + question_id, final_answer, gt, category = datapoint[_search_key] + if subtasks is not None: + category = subtasks[i] + per_seed_df["question_id"].append(question_id) + per_seed_df["final_answer_seed_"].append(final_answer) + per_seed_df["gt"].append(gt) + per_seed_df["category"].append(category) + df = pd.DataFrame(per_seed_df) + return df + + +def calculate_consistency_rate(responses: List[List[str]]) -> float: + """ + Calculate the Consistency Rate (CR) for a given set of responses. + + Args: + responses: List of lists, where each inner list contains responses to the same question. + + Returns: + The consistency rate as a float. + """ + total_similarity = 0 + total_combinations = 0 + + for response_set in responses: + pairs = combinations(response_set, 2) + num_pairs = len(response_set) * (len(response_set) - 1) / 2 + total_combinations += num_pairs + for answer1, answer2 in pairs: + total_similarity += int(answer1 == answer2) + + return total_similarity / total_combinations if total_combinations > 0 else 0.0 + + +def calculate_math_consistency_rate(responses: List[List[str]]) -> float: + """ + Calculate the Consistency Rate (CR) for a given set of responses. + + Args: + responses: List of lists, where each inner list contains responses to the same question. + + Returns: + The consistency rate as a float. + """ + total_similarity = 0 + total_combinations = 0 + + for response_set in responses: + pairs = combinations(response_set, 2) + num_pairs = len(response_set) * (len(response_set) - 1) / 2 + total_combinations += num_pairs + for answer1, answer2 in pairs: + total_similarity += int(math_equal(answer1, answer2)) + + return total_similarity / total_combinations if total_combinations > 0 else 0.0 + + +def main(): + parser = argparse.ArgumentParser( + description="Calculate consistency rate from JSON logs." + ) + parser.add_argument( + "--log_dir", help="Path to the directory containing the JSON log files." + ) + parser.add_argument("--dataset", help="Dataset name: agieval, mmlu_pro or math") + args = parser.parse_args() + + for seed in range(1, N_SEEDS + 1): + # Checking if directories exist + seed_log_dir = os.path.join(args.log_dir, f"seed_{seed}") + assert os.path.exists( + seed_log_dir + ), f"No logs found for seed={seed}. No directory found at {seed_log_dir}" + subtasks = None + if args.dataset == "agieval": + agieval_subtasks = [ + "aqua_rat", + "logiqa_en", + "lsat_ar", + "lsat_lr", + "lsat_rc", + "sat_en", + "sat_math", + ] + subtasks = agieval_subtasks + file_paths = [] + for subtask in agieval_subtasks: + log_path = os.path.join( + seed_log_dir, + f"*/samples_non_greedy_robustness_agieval_{subtask}_*.jsonl", + ) + subtask_logs = glob.glob(log_path) + if len(subtask_logs) == 0: + raise FileNotFoundError( + f"No logs found for agieval subtask {subtask} for seed={seed} in the path {log_path}." + ) + elif len(subtask_logs) > 1: + raise FileExistsError( + f"Multiple logs found for agieval subtask {subtask} for seed={seed}." + ) + file_paths.append(subtask_logs[0]) + + elif args.dataset == "mmlu_pro": + task_logs = glob.glob( + os.path.join( + seed_log_dir, + "*/samples_score_non_greedy_robustness_mmlu_pro_*.jsonl", + ) + ) + file_paths = [] + if len(task_logs) == 0: + raise FileNotFoundError( + f"No logs found for mmlu_pro for seed={seed}. PATH: {seed_log_dir}" + ) + elif len(task_logs) > 1: + raise FileExistsError( + f"Multiple logs found for mmlu_pro for seed={seed}." + ) + file_paths.append(task_logs[0]) + + elif args.dataset == "math": + math_subtasks = [ + "algebra", + "counting_and_prob", + "geometry", + "intermediate_algebra", + "num_theory", + "prealgebra", + "precalc", + ] + subtasks = math_subtasks + file_paths = [] + + for subtask in math_subtasks: + log_path = os.path.join( + seed_log_dir, + f"*/samples_non_greedy_robustness_math_{subtask}_*.jsonl", + ) + + subtask_logs = glob.glob(log_path) + if len(subtask_logs) == 0: + raise FileNotFoundError( + f"No logs found for math subtask {subtask} for seed={seed} in the path {log_path}." + ) + elif len(subtask_logs) > 1: + raise FileExistsError( + f"Multiple logs found for math subtask {subtask} for seed={seed}." + ) + file_paths.append(subtask_logs[0]) + + else: + raise ValueError( + "Invalid dataset name. only agieval, mmlu_pro and math are supported." + ) + + df = load_json_logs(file_paths, subtasks) + + # merge all dfs by question_id, category and gt + if seed == 1: + df_all = df + df_all[f"final_answer_seed_{seed}"] = df["final_answer_seed_"] + else: + df_all = df_all.merge( + df, on=["question_id", "category"], suffixes=("", seed) + ) + + responses = df_all[ + [f"final_answer_seed_{seed}" for seed in range(1, N_SEEDS + 1)] + ].values.tolist() + + # calculate per seed accuracy + + if args.dataset == "math": + consistency_rate = calculate_math_consistency_rate(responses) + results = {"alias": f"score_non_greedy_robustness_{args.dataset}"} + + results.update( + { + "consistency_rate,none": consistency_rate, + "consistency_rate_stderr,none": "N/A", + } + ) + + for seed in range(1, N_SEEDS + 1): + df_all[f"accuracy_seed_{seed}"] = df_all[ + [f"final_answer_seed_{seed}", "gt"] + ].apply(lambda x: math_equal(*x), axis=1) + accuracy = df_all[f"accuracy_seed_{seed}"].mean() + results[f"seed_{seed}_accuracy,none"] = accuracy + results[f"seed_{seed}_accuracy_stderr,none"] = "N/A" + + else: + consistency_rate = calculate_consistency_rate(responses) + results = {"alias": f"score_non_greedy_robustness_{args.dataset}"} + + results.update( + { + "consistency_rate,none": consistency_rate, + "consistency_rate_stderr,none": "N/A", + } + ) + + for seed in range(1, N_SEEDS + 1): + df_all[f"accuracy_seed_{seed}"] = ( + df_all[f"final_answer_seed_{seed}"] == df_all["gt"] + ) + accuracy = df_all[f"accuracy_seed_{seed}"].mean() + results[f"seed_{seed}_accuracy,none"] = accuracy + results[f"seed_{seed}_accuracy_stderr,none"] = "N/A" + + metrics = [f"seed_{seed}_accuracy" for seed in range(1, N_SEEDS + 1)] + [ + "consistency_rate" + ] + higher_is_better = {metric: True for metric in metrics} + + results_dict = { + "results": {f"score_non_greedy_robustness_{args.dataset}": results}, + "group_subtasks": {f"score_non_greedy_robustness_{args.dataset}": []}, + "configs": None, + "versions": {f"score_non_greedy_robustness_{args.dataset}": 1}, + "n-shot": {f"score_non_greedy_robustness_{args.dataset}": 0}, + "higher_is_better": { + f"score_non_greedy_robustness_{args.dataset}": higher_is_better + }, + "n-samples": None, + } + + dumped = json.dumps( + results_dict, + indent=2, + default=handle_non_serializable, + ensure_ascii=False, + ) + + path = Path(args.log_dir) + path.mkdir(parents=True, exist_ok=True) + + date_id = datetime.now().isoformat().replace(":", "-") + file_results_aggregated = path.joinpath(f"{args.dataset}_results_{date_id}.json") + file_results_aggregated.open("w", encoding="utf-8").write(dumped) + + print(make_table(results_dict)) + + +if __name__ == "__main__": + main() diff --git a/lm_eval/tasks/score/utils.py b/lm_eval/tasks/score/utils.py index 5a7174f1..61d7e3b0 100644 --- a/lm_eval/tasks/score/utils.py +++ b/lm_eval/tasks/score/utils.py @@ -130,6 +130,36 @@ def option_order_robustness_process_docs( return doc.map(repeat_doc_swap_correct_answer, batched=True) +def non_greedy_robustness_process_docs( + doc: Dataset, + templates_key: str, + template_file_path: str, + dataset_specific_preprocess: callable = None, +) -> Dataset: + try: + with open(template_file_path) as f: + prompt_template = json.load(f)[templates_key] + prompt = prompt_template["prompt"] + options_format = prompt_template.get("options_format", None) + except FileNotFoundError: + eval_logger.error("Prompt templates not found") + sys.exit() + + if dataset_specific_preprocess is not None: + doc = dataset_specific_preprocess(doc) + + def add_prompt_col(batched_docs): + initial_len = len(next(iter(batched_docs.values()))) + new_batched_docs = copy.deepcopy(batched_docs) + new_batched_docs["prompt"] = [prompt] * initial_len + if options_format is not None: + new_batched_docs["options_format"] = [options_format] * initial_len + + return new_batched_docs + + return doc.map(add_prompt_col, batched=True) + + def robustness_doc_to_text(doc: Dataset) -> str: upper_case = string.ascii_uppercase lower_case = string.ascii_lowercase -- GitLab From 0bfb0220729c4557a572a9a3df08f3d617b51aa9 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 16 Dec 2024 14:34:18 +0000 Subject: [PATCH 180/194] batch `loglikelihood_rolling` across requests (#2559) * batch all rolling token windows * nit * copy to vllm * fix max_length for `get_rolling_token_windows` * bugfix * bugfix * add type hints --- lm_eval/models/huggingface.py | 85 ++++++++++++++++++++------------ lm_eval/models/vllm_causallms.py | 63 +++++++++++++++++------ lm_eval/utils.py | 12 +++-- 3 files changed, 110 insertions(+), 50 deletions(-) diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 0a5fa2ed..f49e920e 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -905,8 +905,6 @@ class HFLM(TemplateLM): def loglikelihood_rolling( self, requests: List[Instance], disable_tqdm: bool = False ) -> List[float]: - loglikelihoods = [] - adaptive_batch_size = None if self.batch_size == "auto": # using rolling window with maximum context @@ -915,10 +913,17 @@ class HFLM(TemplateLM): print(f"Determined Largest batch size: {batch_size}") adaptive_batch_size = batch_size - for (string,) in tqdm( - [req.args for req in requests], disable=(disable_tqdm or (self.rank != 0)) + # First, collect all windows from all requests + all_windows = [] # List of (request_idx, window) tuples + request_window_counts = [] # Track number of windows per request + + for req_idx, (string,) in enumerate( + tqdm( + [req.args for req in requests], + disable=(disable_tqdm or (self.rank != 0)), + ) ): - rolling_token_windows = list( + rolling_token_windows: List[Tuple[List[int], List[int]]] = list( map( utils.make_disjoint_window, utils.get_rolling_token_windows( @@ -931,37 +936,55 @@ class HFLM(TemplateLM): ) # TODO: Right now, we pass single EOT token to the Encoder and the full context to the decoder, in seq2seq case - rolling_token_windows = [(None,) + x for x in rolling_token_windows] - - pad_amnt = 0 - if self.world_size > 1: - # We pad out the external document-level iterator so the inner iterator doesn't hang - mytensor = torch.tensor(len(rolling_token_windows), device=self.device) - gathered = ( - self.accelerator.gather(mytensor).cpu().detach().numpy().tolist() - ) + windows = [(None,) + x for x in rolling_token_windows] - pad_amnt = max(gathered) - gathered[self.rank] - if pad_amnt > 0: - rolling_token_windows += pad_amnt * [rolling_token_windows[0]] + # Store windows with their request index + all_windows.extend((req_idx, window) for window in windows) + request_window_counts.append(len(windows)) - string_nll = self._loglikelihood_tokens( - requests=rolling_token_windows, - disable_tqdm=True, - override_bs=adaptive_batch_size, + # Handle distributed case padding + pad_amnt = 0 + if self.world_size > 1: + mytensor = torch.tensor(len(all_windows), device=self.device) + gathered = self.accelerator.gather(mytensor).cpu().detach().numpy().tolist() + pad_amnt = max(gathered) - gathered[self.rank] + if pad_amnt > 0: + all_windows += pad_amnt * [all_windows[0]] + + all_nlls = [] + batch_size = adaptive_batch_size or self.batch_size + for i in range(0, len(all_windows), batch_size): + batch = all_windows[i : i + batch_size] + # Extract just the windows for processing, keeping track of request indices + batch_indices, batch_windows = zip(*batch) + + batch_nlls = self._loglikelihood_tokens( + requests=batch_windows, + disable_tqdm=False, + override_bs=len(batch_windows), ) + # Store results with their request indices + all_nlls.extend(zip(batch_indices, batch_nlls)) - if (self.world_size > 1) and (pad_amnt > 0): - string_nll = [x[0] for x in string_nll[:-pad_amnt]] - else: - # discard is_greedy - string_nll = [x[0] for x in string_nll] - - string_nll = sum(string_nll) - loglikelihoods.append(string_nll) + # Remove padding if necessary + if (self.world_size > 1) and (pad_amnt > 0): + all_nlls = all_nlls[:-pad_amnt] - # cache this loglikelihood_rolling request - self.cache_hook.add_partial("loglikelihood_rolling", (string,), string_nll) + # Reconstruct per-request loglikelihoods + loglikelihoods = [] + current_idx = 0 + for window_count in request_window_counts: + # Get all nlls for this request + request_nlls = all_nlls[current_idx : current_idx + window_count] + # Sum up the nlls for this request (discarding is_greedy) + request_total = sum(nll[0] for _, nll in request_nlls) + loglikelihoods.append(request_total) + current_idx += window_count + + string = requests[len(loglikelihoods) - 1].args[0] + self.cache_hook.add_partial( + "loglikelihood_rolling", (string,), request_total + ) return loglikelihoods diff --git a/lm_eval/models/vllm_causallms.py b/lm_eval/models/vllm_causallms.py index 7afc2cb8..5dcbbfbb 100644 --- a/lm_eval/models/vllm_causallms.py +++ b/lm_eval/models/vllm_causallms.py @@ -102,7 +102,7 @@ class VLLM(TemplateLM): self.batch_size = ( "auto" if isinstance(batch_size, str) and "auto" in batch_size - else batch_size + else int(batch_size) ) if self.data_parallel_size <= 1: self.model = LLM(**self.model_args) @@ -281,10 +281,21 @@ class VLLM(TemplateLM): def loglikelihood_rolling( self, requests: List[Instance], disable_tqdm: bool = False ) -> List[float]: - loglikelihoods = [] - - for (string,) in tqdm([req.args for req in requests], disable=disable_tqdm): - rolling_token_windows = list( + adaptive_batch_size = None + if self.batch_size == "auto": + adaptive_batch_size = len(requests) + + # First, collect all windows from all requests + all_windows = [] # List of (request_idx, window) tuples + request_window_counts = [] # Track number of windows per request + + for req_idx, (string,) in enumerate( + tqdm( + [req.args for req in requests], + disable=(disable_tqdm or (self.rank != 0)), + ) + ): + rolling_token_windows: List[Tuple[List[int], List[int]]] = list( map( make_disjoint_window, get_rolling_token_windows( @@ -297,20 +308,42 @@ class VLLM(TemplateLM): ) ) - rolling_token_windows = [(None,) + x for x in rolling_token_windows] + # TODO: Right now, we pass single EOT token to the Encoder and the full context to the decoder, in seq2seq case + windows = [(None,) + x for x in rolling_token_windows] - string_nll = self._loglikelihood_tokens( - rolling_token_windows, - ) + # Store windows with their request index + all_windows.extend((req_idx, window) for window in windows) + request_window_counts.append(len(windows)) - # discard is_greedy - string_nll = [x[0] for x in string_nll] + all_nlls = [] + batch_size = adaptive_batch_size or int(self.batch_size) + for i in range(0, len(all_windows), batch_size): + batch = all_windows[i : i + batch_size] + # Extract just the windows for processing, keeping track of request indices + batch_indices, batch_windows = zip(*batch) - string_nll = sum(string_nll) - loglikelihoods.append(string_nll) + batch_nlls = self._loglikelihood_tokens( + requests=batch_windows, + disable_tqdm=False, + ) + # Store results with their request indices + all_nlls.extend(zip(batch_indices, batch_nlls)) - # cache this loglikelihood_rolling request - self.cache_hook.add_partial("loglikelihood_rolling", (string,), string_nll) + # Reconstruct per-request loglikelihoods + loglikelihoods = [] + current_idx = 0 + for window_count in request_window_counts: + # Get all nlls for this request + request_nlls = all_nlls[current_idx : current_idx + window_count] + # Sum up the nlls for this request (discarding is_greedy) + request_total = sum(nll[0] for _, nll in request_nlls) + loglikelihoods.append(request_total) + current_idx += window_count + + string = requests[len(loglikelihoods) - 1].args[0] + self.cache_hook.add_partial( + "loglikelihood_rolling", (string,), request_total + ) return loglikelihoods diff --git a/lm_eval/utils.py b/lm_eval/utils.py index 7166e24d..312477ff 100644 --- a/lm_eval/utils.py +++ b/lm_eval/utils.py @@ -10,7 +10,7 @@ import os import re from dataclasses import asdict, is_dataclass from itertools import islice -from typing import Any, Callable, List +from typing import Any, Callable, Generator, List, Tuple import numpy as np import yaml @@ -201,7 +201,9 @@ def get_sample_results_filenames(filenames: List[str]) -> List[str]: return [f for f in filenames if "/samples_" in f and ".json" in f] -def get_rolling_token_windows(token_list, prefix_token, max_seq_len, context_len): +def get_rolling_token_windows( + token_list: List[int], prefix_token: int, max_seq_len: int, context_len: int +) -> Generator[Tuple[List[int], List[int]], None, None]: """ - context_len allows for a rolling window context, allowing each prediction window to potentially condition on some context @@ -228,7 +230,7 @@ def get_rolling_token_windows(token_list, prefix_token, max_seq_len, context_len # Special handling for first window: predict all tokens first_seq_len = min(max_seq_len, len(token_list)) - yield ([prefix_token] + token_list[: first_seq_len - 1], token_list[:first_seq_len]) + yield [prefix_token] + token_list[: first_seq_len - 1], token_list[:first_seq_len] predicted += first_seq_len while predicted < len(token_list): @@ -242,7 +244,9 @@ def get_rolling_token_windows(token_list, prefix_token, max_seq_len, context_len predicted += window_pred_len -def make_disjoint_window(pair): +def make_disjoint_window( + pair: Tuple[List[int], List[int]], +) -> Tuple[List[int], List[int]]: """Takes output from get_rolling_token_windows and makes the context not overlap with the continuation""" a, b = pair return a[: len(a) - (len(b) - 1)], b -- GitLab From 8d2f64c1da7d60c47b46076b11978dc8eb1b0a89 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 16 Dec 2024 14:43:33 +0000 Subject: [PATCH 181/194] fix `DeprecationWarning: invalid escape sequence '\s'` for whitespace filter (#2560) * fix `DeprecationWarning: invalid escape sequence '\s'` * add type hints * Revert "add type hints" This reverts commit 15d8abc626a84e97f8c238ddfbf9e243d6f6eb5c. --- lm_eval/filters/extraction.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lm_eval/filters/extraction.py b/lm_eval/filters/extraction.py index 5dc10863..58312e99 100644 --- a/lm_eval/filters/extraction.py +++ b/lm_eval/filters/extraction.py @@ -164,7 +164,7 @@ class MultiChoiceRegexFilter(RegexFilter): fallback_regex = re.compile("|".join(fallback_regexes)) without_paren_fallback_regex = "|".join(without_paren_fallback_regexes) without_paren_fallback_regex = re.compile( - f":[\s]*({without_paren_fallback_regex})" + rf":[\s]*({without_paren_fallback_regex})" ) filtered = [] -- GitLab From 4c26a9c176ecfb40b369503ce211e356bb800fdc Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Tue, 17 Dec 2024 10:24:01 +0000 Subject: [PATCH 182/194] increment version (#2574) forgot to increment 0.4.6! --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 19a9ca78..499fc2ec 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "lm_eval" -version = "0.4.5" +version = "0.4.7" authors = [ {name="EleutherAI", email="contact@eleuther.ai"} ] -- GitLab From 8558b8d4998991220cb5483246b2ae4878c92a1f Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Tue, 17 Dec 2024 11:07:46 +0000 Subject: [PATCH 183/194] drop python 3.8 support (#2575) * feat: drop Python 3.8 support * feat: drop Python 3.8 tests * pre-commit --- .github/workflows/unit_tests.yml | 10 +++++----- lm_eval/decontamination/archiver.py | 15 +++++++++------ pyproject.toml | 2 +- 3 files changed, 15 insertions(+), 12 deletions(-) diff --git a/.github/workflows/unit_tests.yml b/.github/workflows/unit_tests.yml index ed09225c..65c50231 100644 --- a/.github/workflows/unit_tests.yml +++ b/.github/workflows/unit_tests.yml @@ -22,10 +22,10 @@ jobs: steps: - name: Checkout Code uses: actions/checkout@v4 - - name: Set up Python 3.8 + - name: Set up Python 3.9 uses: actions/setup-python@v5 with: - python-version: 3.8 + python-version: 3.9 cache: pip cache-dependency-path: pyproject.toml - name: Pre-Commit @@ -42,7 +42,7 @@ jobs: runs-on: ubuntu-latest strategy: matrix: - python-version: [ "3.8", "3.9", "3.10", "3.11" ] + python-version: ["3.9", "3.10", "3.11", "3.12" ] timeout-minutes: 30 steps: - name: Checkout Code @@ -75,10 +75,10 @@ jobs: steps: - name: Checkout Code uses: actions/checkout@v4 - - name: Set up Python 3.8 + - name: Set up Python 3.9 uses: actions/setup-python@v5 with: - python-version: 3.8 + python-version: 3.9 cache: pip cache-dependency-path: pyproject.toml - name: Install dependencies diff --git a/lm_eval/decontamination/archiver.py b/lm_eval/decontamination/archiver.py index fa8a715f..c1322321 100644 --- a/lm_eval/decontamination/archiver.py +++ b/lm_eval/decontamination/archiver.py @@ -110,12 +110,15 @@ class TextReader: def read_tqdm(self, update_frequency: int = 10000): current_file_position = 0 line_counter = 0 - with open(self.file_path, "r", encoding="utf-8") as fh, tqdm.tqdm( - total=os.path.getsize(self.file_path), - dynamic_ncols=True, - unit="byte", - unit_scale=1, - ) as progress: + with ( + open(self.file_path, "r", encoding="utf-8") as fh, + tqdm.tqdm( + total=os.path.getsize(self.file_path), + dynamic_ncols=True, + unit="byte", + unit_scale=1, + ) as progress, + ): with mmap.mmap(fh.fileno(), length=0, access=mmap.ACCESS_READ) as mmap_obj: for line in iter(mmap_obj.readline, b""): line = line.decode("utf-8") diff --git a/pyproject.toml b/pyproject.toml index 499fc2ec..f2aac355 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -16,7 +16,7 @@ classifiers = [ "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", ] -requires-python = ">=3.8" +requires-python = ">=3.9" license = { "text" = "MIT" } dependencies = [ "accelerate>=0.26.0", -- GitLab From 2b75b11001f03a9032966ea8085e96630fa896e1 Mon Sep 17 00:00:00 2001 From: shivalika-singh Date: Thu, 19 Dec 2024 20:24:52 +0530 Subject: [PATCH 184/194] Add Global MMLU Lite (#2567) * add global mmlu lite * add global mmlu lite * fix bugs * add task README.md * Update README.md * Update tasks README.md * Update README.md * update readme --------- Co-authored-by: shivi --- lm_eval/tasks/README.md | 1 + lm_eval/tasks/global_mmlu/README.md | 25 +++++++++++ lm_eval/tasks/global_mmlu/_default_yaml | 17 ++++++++ .../tasks/global_mmlu/_generate_configs.py | 42 +++++++++++++++++++ lm_eval/tasks/global_mmlu/global_mmlu_ar.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_bn.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_de.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_en.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_es.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_fr.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_hi.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_id.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_it.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_ja.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_ko.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_pt.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_sw.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_yo.yaml | 4 ++ lm_eval/tasks/global_mmlu/global_mmlu_zh.yaml | 4 ++ 19 files changed, 145 insertions(+) create mode 100644 lm_eval/tasks/global_mmlu/README.md create mode 100644 lm_eval/tasks/global_mmlu/_default_yaml create mode 100644 lm_eval/tasks/global_mmlu/_generate_configs.py create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_ar.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_bn.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_de.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_en.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_es.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_fr.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_hi.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_id.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_it.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_ja.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_ko.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_pt.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_sw.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_yo.yaml create mode 100644 lm_eval/tasks/global_mmlu/global_mmlu_zh.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 62e65a1e..8db5ee31 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -45,6 +45,7 @@ | [fld](fld/README.md) | Tasks involving free-form and directed dialogue understanding. | English | | [french_bench](french_bench/README.md) | Set of tasks designed to assess language model performance in French. | French| | [galician_bench](galician_bench/README.md) | Collection of tasks in Galician encompassing various evaluation areas. | Galician | +| [global_mmlu](global_mmlu/README.md) | Collection of culturally sensitive and culturally agnostic MMLU tasks in 15 languages with human translations or post-edits. | Multiple (15 languages) | | [glue](glue/README.md) | General Language Understanding Evaluation benchmark to test broad language abilities. | English | | [gpqa](gpqa/README.md) | Tasks designed for general public question answering and knowledge verification. | English | | [gsm8k](gsm8k/README.md) | A benchmark of grade school math problems aimed at evaluating reasoning capabilities. | English | diff --git a/lm_eval/tasks/global_mmlu/README.md b/lm_eval/tasks/global_mmlu/README.md new file mode 100644 index 00000000..838a7c9d --- /dev/null +++ b/lm_eval/tasks/global_mmlu/README.md @@ -0,0 +1,25 @@ +# Global-MMLU + +### Paper + +Title: `Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation` + +Abstract: [https://arxiv.org/abs/2412.03304](https://arxiv.org/abs/2412.03304) + +Global-MMLU-Lite is a balanced collection of culturally sensitive and culturally agnostic MMLU tasks. It is designed for efficient evaluation of multilingual models in 15 languages (including English). Only languages with human translations and post-edits in the original [Global-MMLU](https://huggingface.co/datasets/CohereForAI/Global-MMLU) 🌍 dataset have been included in the lite version. + +Homepage: [https://huggingface.co/datasets/CohereForAI/Global-MMLU-Lite](https://huggingface.co/datasets/CohereForAI/Global-MMLU-Lite) + +### Citation + +```bibtex +@misc{singh2024globalmmluunderstandingaddressing, + title={Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation}, + author={Shivalika Singh and Angelika Romanou and Clémentine Fourrier and David I. Adelani and Jian Gang Ngui and Daniel Vila-Suero and Peerat Limkonchotiwat and Kelly Marchisio and Wei Qi Leong and Yosephine Susanto and Raymond Ng and Shayne Longpre and Wei-Yin Ko and Madeline Smith and Antoine Bosselut and Alice Oh and Andre F. T. Martins and Leshem Choshen and Daphne Ippolito and Enzo Ferrante and Marzieh Fadaee and Beyza Ermis and Sara Hooker}, + year={2024}, + eprint={2412.03304}, + archivePrefix={arXiv}, + primaryClass={cs.CL}, + url={https://arxiv.org/abs/2412.03304}, +} +``` diff --git a/lm_eval/tasks/global_mmlu/_default_yaml b/lm_eval/tasks/global_mmlu/_default_yaml new file mode 100644 index 00000000..33a1fc35 --- /dev/null +++ b/lm_eval/tasks/global_mmlu/_default_yaml @@ -0,0 +1,17 @@ +tag: + - global_mmlu +dataset_path: CohereForAI/Global-MMLU-Lite +test_split: test +fewshot_split: dev +fewshot_config: + sampler: default +output_type: multiple_choice +doc_to_text: "{{question.strip()}}\nA. {{option_a}}\nB. {{option_b}}\nC. {{option_c}}\nD. {{option_d}}\nAnswer:" +doc_to_choice: ["A", "B", "C", "D"] +doc_to_target: answer +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true +metadata: + version: 0.0 diff --git a/lm_eval/tasks/global_mmlu/_generate_configs.py b/lm_eval/tasks/global_mmlu/_generate_configs.py new file mode 100644 index 00000000..58e169c6 --- /dev/null +++ b/lm_eval/tasks/global_mmlu/_generate_configs.py @@ -0,0 +1,42 @@ +import yaml + + +languages = [ + "en", + "ar", + "fr", + "es", + "hi", + "de", + "id", + "it", + "ja", + "ko", + "pt", + "zh", + "yo", + "bn", + "sw", +] + + +def main() -> None: + for language in languages: + file_name = f"global_mmlu_{language}.yaml" + try: + with open(f"{file_name}", "w") as f: + f.write("# Generated by _generate_configs.py\n") + yaml.dump( + { + "include": "_default_yaml", + "task": f"global_mmlu_{language}", + "dataset_name": language, + }, + f, + ) + except FileExistsError: + pass + + +if __name__ == "__main__": + main() diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_ar.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_ar.yaml new file mode 100644 index 00000000..703f420a --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_ar.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: ar +include: _default_yaml +task: global_mmlu_ar diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_bn.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_bn.yaml new file mode 100644 index 00000000..f85b67a2 --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_bn.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: bn +include: _default_yaml +task: global_mmlu_bn diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_de.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_de.yaml new file mode 100644 index 00000000..a874c64f --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_de.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: de +include: _default_yaml +task: global_mmlu_de diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_en.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_en.yaml new file mode 100644 index 00000000..34a6d712 --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_en.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: en +include: _default_yaml +task: global_mmlu_en diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_es.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_es.yaml new file mode 100644 index 00000000..75abc775 --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_es.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: es +include: _default_yaml +task: global_mmlu_es diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_fr.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_fr.yaml new file mode 100644 index 00000000..1a66f536 --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_fr.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: fr +include: _default_yaml +task: global_mmlu_fr diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_hi.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_hi.yaml new file mode 100644 index 00000000..788f95f2 --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_hi.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: hi +include: _default_yaml +task: global_mmlu_hi diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_id.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_id.yaml new file mode 100644 index 00000000..f4b6d507 --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_id.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: id +include: _default_yaml +task: global_mmlu_id diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_it.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_it.yaml new file mode 100644 index 00000000..5b55df97 --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_it.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: it +include: _default_yaml +task: global_mmlu_it diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_ja.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_ja.yaml new file mode 100644 index 00000000..97d9c6ca --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_ja.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: ja +include: _default_yaml +task: global_mmlu_ja diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_ko.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_ko.yaml new file mode 100644 index 00000000..02b7fe03 --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_ko.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: ko +include: _default_yaml +task: global_mmlu_ko diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_pt.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_pt.yaml new file mode 100644 index 00000000..724bfb4d --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_pt.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: pt +include: _default_yaml +task: global_mmlu_pt diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_sw.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_sw.yaml new file mode 100644 index 00000000..481232fa --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_sw.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: sw +include: _default_yaml +task: global_mmlu_sw diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_yo.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_yo.yaml new file mode 100644 index 00000000..c6ec2f9e --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_yo.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: yo +include: _default_yaml +task: global_mmlu_yo diff --git a/lm_eval/tasks/global_mmlu/global_mmlu_zh.yaml b/lm_eval/tasks/global_mmlu/global_mmlu_zh.yaml new file mode 100644 index 00000000..862d46ad --- /dev/null +++ b/lm_eval/tasks/global_mmlu/global_mmlu_zh.yaml @@ -0,0 +1,4 @@ +# Generated by _generate_configs.py +dataset_name: zh +include: _default_yaml +task: global_mmlu_zh -- GitLab From 6ccd520f3fb2b5d74c6f14c05f9d189521424719 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Thu, 19 Dec 2024 21:58:28 +0000 Subject: [PATCH 185/194] add warning for truncation (#2585) * add warning for truncation --- lm_eval/models/huggingface.py | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index f49e920e..40e65f5d 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -818,6 +818,12 @@ class HFLM(TemplateLM): **add_special_tokens, ) if left_truncate_len: + original_lengths = encoding["input_ids"].size(1) + if original_lengths > left_truncate_len: + eval_logger.warn( + f"Left truncation applied. Original sequence length was {original_lengths}, " + f"truncating to last {left_truncate_len} tokens. Some content will be lost.", + ) encoding["input_ids"] = encoding["input_ids"][:, -left_truncate_len:] encoding["attention_mask"] = encoding["attention_mask"][ :, -left_truncate_len: @@ -1096,6 +1102,13 @@ class HFLM(TemplateLM): # when too long to fit in context, truncate from the left if self.backend == "causal": + total_length = len(context_enc) + len(continuation_enc) + if total_length > self.max_length + 1: + eval_logger.warn( + f"Combined length of context ({len(context_enc)}) and continuation ({len(continuation_enc)}) " + f"exceeds model's maximum length ({self.max_length}). " + f"Truncating {total_length - self.max_length + 1} tokens from the left." + ) inp = torch.tensor( (context_enc + continuation_enc)[-(self.max_length + 1) :][:-1], dtype=torch.long, @@ -1303,6 +1316,9 @@ class HFLM(TemplateLM): if self.backend == "causal": # max len for inputs = max length, minus room to generate the max new tokens max_ctx_len = self.max_length - max_gen_toks + assert ( + max_ctx_len > 0 + ), f"Invalid configuration: requested max tokens to generate ({max_gen_toks}) must be less than model's maximum sequence length ({self.max_length})." elif self.backend == "seq2seq": # max len for inputs = encoder's whole max_length max_ctx_len = self.max_length -- GitLab From b86aa2131fc34405d2245edb0ec4b13933afec8c Mon Sep 17 00:00:00 2001 From: "Sabrina J. Mielke" Date: Fri, 20 Dec 2024 16:40:53 -0500 Subject: [PATCH 186/194] Wandb step handling bugfix and feature (#2580) --- docs/interface.md | 2 +- lm_eval/loggers/wandb_logger.py | 15 +++++++++------ lm_eval/utils.py | 3 ++- 3 files changed, 12 insertions(+), 8 deletions(-) diff --git a/docs/interface.md b/docs/interface.md index 47cf00b4..cea1aab0 100644 --- a/docs/interface.md +++ b/docs/interface.md @@ -58,7 +58,7 @@ This mode supports a number of command-line arguments, the details of which can * `--seed`: Set seed for python's random, numpy and torch. Accepts a comma-separated list of 3 values for python's random, numpy, and torch seeds, respectively, or a single integer to set the same seed for all three. The values are either an integer or 'None' to not set the seed. Default is `0,1234,1234` (for backward compatibility). E.g. `--seed 0,None,8` sets `random.seed(0)` and `torch.manual_seed(8)`. Here numpy's seed is not set since the second value is `None`. E.g, `--seed 42` sets all three seeds to 42. -* `--wandb_args`: Tracks logging to Weights and Biases for evaluation runs and includes args passed to `wandb.init`, such as `project` and `job_type`. Full list [here](https://docs.wandb.ai/ref/python/init). e.g., ```--wandb_args project=test-project,name=test-run``` +* `--wandb_args`: Tracks logging to Weights and Biases for evaluation runs and includes args passed to `wandb.init`, such as `project` and `job_type`. Full list [here](https://docs.wandb.ai/ref/python/init). e.g., ```--wandb_args project=test-project,name=test-run```. Also allows for the passing of the step to log things at (passed to `wandb.run.log`), e.g., `--wandb_args step=123`. * `--hf_hub_log_args` : Logs evaluation results to Hugging Face Hub. Accepts a string with the arguments separated by commas. Available arguments: * `hub_results_org` - organization name on Hugging Face Hub, e.g., `EleutherAI`. If not provided, the results will be pushed to the owner of the Hugging Face token, diff --git a/lm_eval/loggers/wandb_logger.py b/lm_eval/loggers/wandb_logger.py index 4bcc439e..b50ee03c 100644 --- a/lm_eval/loggers/wandb_logger.py +++ b/lm_eval/loggers/wandb_logger.py @@ -48,6 +48,9 @@ class WandbLogger: self.wandb_args: Dict[str, Any] = kwargs + # pop the step key from the args to save for all logging calls + self.step = self.wandb_args.pop("step", None) + # initialize a W&B run if wandb.run is None: self.run = wandb.init(**self.wandb_args) @@ -152,11 +155,11 @@ class WandbLogger: # log the complete eval result to W&B Table table = make_table(["Tasks"] + columns, "results") - self.run.log({"evaluation/eval_results": table}) + self.run.log({"evaluation/eval_results": table}, step=self.step) if "groups" in self.results.keys(): table = make_table(["Groups"] + columns, "groups") - self.run.log({"evaluation/group_eval_results": table}) + self.run.log({"evaluation/group_eval_results": table}, step=self.step) def _log_results_as_artifact(self) -> None: """Log results as JSON artifact to W&B.""" @@ -174,13 +177,13 @@ class WandbLogger: """Log evaluation results to W&B.""" # Log configs to wandb configs = self._get_config() - self.run.config.update(configs) + self.run.config.update(configs, allow_val_change=self.step is not None) wandb_summary, self.wandb_results = self._sanitize_results_dict() # update wandb.run.summary with items that were removed self.run.summary.update(wandb_summary) # Log the evaluation metrics to wandb - self.run.log(self.wandb_results) + self.run.log(self.wandb_results, step=self.step) # Log the evaluation metrics as W&B Table self._log_results_as_table() # Log the results dict as json to W&B Artifacts @@ -329,7 +332,7 @@ class WandbLogger: # log the samples as a W&B Table df = self._generate_dataset(eval_preds, self.task_configs.get(task_name)) - self.run.log({f"{task_name}_eval_results": df}) + self.run.log({f"{task_name}_eval_results": df}, step=self.step) # log the samples as a json file as W&B Artifact self._log_samples_as_artifact(eval_preds, task_name) @@ -348,4 +351,4 @@ class WandbLogger: # log the samples as a json file as W&B Artifact self._log_samples_as_artifact(eval_preds, task_name) - self.run.log({f"{group}_eval_results": grouped_df}) + self.run.log({f"{group}_eval_results": grouped_df}, step=self.step) diff --git a/lm_eval/utils.py b/lm_eval/utils.py index 312477ff..537a4a25 100644 --- a/lm_eval/utils.py +++ b/lm_eval/utils.py @@ -104,7 +104,8 @@ def simple_parse_args_string(args_string): return {} arg_list = [arg for arg in args_string.split(",") if arg] args_dict = { - k: handle_arg_string(v) for k, v in [arg.split("=") for arg in arg_list] + kv[0]: handle_arg_string("=".join(kv[1:])) + for kv in [arg.split("=") for arg in arg_list] } return args_dict -- GitLab From 932e8f9eba4ceeade0170ad85e4598720776380e Mon Sep 17 00:00:00 2001 From: "Firoj Alam, Scientist, QCRI" Date: Tue, 24 Dec 2024 21:17:45 +0300 Subject: [PATCH 187/194] AraDICE task config file (#2507) * added aradice * Added ArabicMMLU Lev Configs * added ArabicMMLU egy configs * Added boolq configs * Added cultural bench configs * added openbookqa configs * Added PiQA configs * added winogrande configs * Added truthfulQA configs * Added aradice group config * Remove deleted files from repository * modified arabimmlu configs * modified metadata versions * fixed formatting using ruff * added aradice tasks information * pre-commit * Uptaded openbookqa utils * fixed formatting on obqa --------- Co-authored-by: Basel Mousi Co-authored-by: Baber --- lm_eval/tasks/README.md | 1 + .../ArabicMMLU/EGY/AraDiCE_ArabicMMLU.yaml | 12 +++ ...CE_ArabicMMLU_high_humanities_history.yaml | 10 ++ ...cMMLU_high_humanities_islamic-studies.yaml | 10 ++ ...ArabicMMLU_high_humanities_philosophy.yaml | 10 ++ ...bicMMLU_high_language_arabic-language.yaml | 10 ++ ...ArabicMMLU_high_social-science_civics.yaml | 10 ++ ...bicMMLU_high_social-science_economics.yaml | 10 ++ ...bicMMLU_high_social-science_geography.yaml | 10 ++ .../AraDiCE_ArabicMMLU_high_stem_biology.yaml | 10 ++ ...ArabicMMLU_high_stem_computer-science.yaml | 10 ++ .../AraDiCE_ArabicMMLU_high_stem_physics.yaml | 10 ++ ..._ArabicMMLU_middle_humanities_history.yaml | 10 ++ ...MLU_middle_humanities_islamic-studies.yaml | 10 ++ ...cMMLU_middle_language_arabic-language.yaml | 10 ++ ...icMMLU_middle_other_general-knowledge.yaml | 10 ++ ...abicMMLU_middle_social-science_civics.yaml | 10 ++ ...cMMLU_middle_social-science_economics.yaml | 10 ++ ...cMMLU_middle_social-science_geography.yaml | 10 ++ ..._middle_social-science_social-science.yaml | 10 ++ ...abicMMLU_middle_stem_computer-science.yaml | 10 ++ ...rabicMMLU_middle_stem_natural-science.yaml | 10 ++ ...bicMMLU_na_humanities_islamic-studies.yaml | 10 ++ ...U_na_language_arabic-language-general.yaml | 10 ++ ...U_na_language_arabic-language-grammar.yaml | 10 ++ ...DiCE_ArabicMMLU_na_other_driving-test.yaml | 10 ++ ...ArabicMMLU_na_other_general-knowledge.yaml | 10 ++ ...ArabicMMLU_primary_humanities_history.yaml | 10 ++ ...LU_primary_humanities_islamic-studies.yaml | 10 ++ ...MMLU_primary_language_arabic-language.yaml | 10 ++ ...cMMLU_primary_other_general-knowledge.yaml | 10 ++ ...MMLU_primary_social-science_geography.yaml | 10 ++ ...primary_social-science_social-science.yaml | 10 ++ ...bicMMLU_primary_stem_computer-science.yaml | 10 ++ .../AraDiCE_ArabicMMLU_primary_stem_math.yaml | 10 ++ ...abicMMLU_primary_stem_natural-science.yaml | 10 ++ ...raDiCE_ArabicMMLU_prof_humanities_law.yaml | 10 ++ ...DiCE_ArabicMMLU_univ_other_management.yaml | 10 ++ ...icMMLU_univ_social-science_accounting.yaml | 10 ++ ...bicMMLU_univ_social-science_economics.yaml | 10 ++ ...univ_social-science_political-science.yaml | 10 ++ ...ArabicMMLU_univ_stem_computer-science.yaml | 10 ++ .../ArabicMMLU/EGY/_default_template_yaml | 20 ++++ .../tasks/aradice/ArabicMMLU/EGY/metrics.py | 25 +++++ lm_eval/tasks/aradice/ArabicMMLU/EGY/utils.py | 87 +++++++++++++++++ .../ArabicMMLU/LEV/AraDiCE_ArabicMMLU.yaml | 12 +++ ...CE_ArabicMMLU_high_humanities_history.yaml | 10 ++ ...cMMLU_high_humanities_islamic-studies.yaml | 10 ++ ...ArabicMMLU_high_humanities_philosophy.yaml | 10 ++ ...bicMMLU_high_language_arabic-language.yaml | 10 ++ ...ArabicMMLU_high_social-science_civics.yaml | 10 ++ ...bicMMLU_high_social-science_economics.yaml | 10 ++ ...bicMMLU_high_social-science_geography.yaml | 10 ++ .../AraDiCE_ArabicMMLU_high_stem_biology.yaml | 10 ++ ...ArabicMMLU_high_stem_computer-science.yaml | 10 ++ .../AraDiCE_ArabicMMLU_high_stem_physics.yaml | 10 ++ ..._ArabicMMLU_middle_humanities_history.yaml | 10 ++ ...MLU_middle_humanities_islamic-studies.yaml | 10 ++ ...cMMLU_middle_language_arabic-language.yaml | 10 ++ ...icMMLU_middle_other_general-knowledge.yaml | 10 ++ ...abicMMLU_middle_social-science_civics.yaml | 10 ++ ...cMMLU_middle_social-science_economics.yaml | 10 ++ ...cMMLU_middle_social-science_geography.yaml | 10 ++ ..._middle_social-science_social-science.yaml | 10 ++ ...abicMMLU_middle_stem_computer-science.yaml | 10 ++ ...rabicMMLU_middle_stem_natural-science.yaml | 10 ++ ...bicMMLU_na_humanities_islamic-studies.yaml | 10 ++ ...U_na_language_arabic-language-general.yaml | 10 ++ ...U_na_language_arabic-language-grammar.yaml | 10 ++ ...DiCE_ArabicMMLU_na_other_driving-test.yaml | 10 ++ ...ArabicMMLU_na_other_general-knowledge.yaml | 10 ++ ...ArabicMMLU_primary_humanities_history.yaml | 10 ++ ...LU_primary_humanities_islamic-studies.yaml | 10 ++ ...MMLU_primary_language_arabic-language.yaml | 10 ++ ...cMMLU_primary_other_general-knowledge.yaml | 10 ++ ...MMLU_primary_social-science_geography.yaml | 10 ++ ...primary_social-science_social-science.yaml | 10 ++ ...bicMMLU_primary_stem_computer-science.yaml | 10 ++ .../AraDiCE_ArabicMMLU_primary_stem_math.yaml | 10 ++ ...abicMMLU_primary_stem_natural-science.yaml | 10 ++ ...raDiCE_ArabicMMLU_prof_humanities_law.yaml | 10 ++ ...DiCE_ArabicMMLU_univ_other_management.yaml | 10 ++ ...icMMLU_univ_social-science_accounting.yaml | 10 ++ ...bicMMLU_univ_social-science_economics.yaml | 10 ++ ...univ_social-science_political-science.yaml | 10 ++ ...ArabicMMLU_univ_stem_computer-science.yaml | 10 ++ .../ArabicMMLU/LEV/_default_template_yaml | 20 ++++ .../tasks/aradice/ArabicMMLU/LEV/metrics.py | 25 +++++ lm_eval/tasks/aradice/ArabicMMLU/LEV/utils.py | 94 +++++++++++++++++++ lm_eval/tasks/aradice/README.md | 49 ++++++++++ lm_eval/tasks/aradice/aradice.yaml | 30 ++++++ .../tasks/aradice/boolq/EGY/boolq_egy.yaml | 25 +++++ lm_eval/tasks/aradice/boolq/EGY/metrics.py | 25 +++++ lm_eval/tasks/aradice/boolq/EGY/utils.py | 18 ++++ .../tasks/aradice/boolq/ENG/boolq_eng.yaml | 25 +++++ lm_eval/tasks/aradice/boolq/ENG/metrics.py | 25 +++++ lm_eval/tasks/aradice/boolq/ENG/utils.py | 18 ++++ .../tasks/aradice/boolq/LEV/boolq_lev.yaml | 25 +++++ lm_eval/tasks/aradice/boolq/LEV/metrics.py | 25 +++++ lm_eval/tasks/aradice/boolq/LEV/utils.py | 18 ++++ .../tasks/aradice/boolq/MSA/boolq_msa.yaml | 25 +++++ lm_eval/tasks/aradice/boolq/MSA/metrics.py | 25 +++++ lm_eval/tasks/aradice/boolq/MSA/utils.py | 18 ++++ .../aradice/cultural-benchmark/egypt.yaml | 25 +++++ .../aradice/cultural-benchmark/jordan.yaml | 25 +++++ .../aradice/cultural-benchmark/lebanon.yaml | 25 +++++ .../aradice/cultural-benchmark/metrics.py | 25 +++++ .../aradice/cultural-benchmark/palestine.yaml | 25 +++++ .../aradice/cultural-benchmark/qatar.yaml | 25 +++++ .../aradice/cultural-benchmark/syria.yaml | 25 +++++ .../tasks/aradice/cultural-benchmark/utils.py | 6 ++ lm_eval/tasks/aradice/openbookqa/metrics.py | 25 +++++ .../aradice/openbookqa/openbookqa_egy.yaml | 24 +++++ .../aradice/openbookqa/openbookqa_eng.yaml | 24 +++++ .../aradice/openbookqa/openbookqa_lev.yaml | 24 +++++ .../aradice/openbookqa/openbookqa_msa.yaml | 24 +++++ lm_eval/tasks/aradice/openbookqa/utils.py | 18 ++++ lm_eval/tasks/aradice/piqa/metrics.py | 25 +++++ lm_eval/tasks/aradice/piqa/piqa_egy.yaml | 24 +++++ lm_eval/tasks/aradice/piqa/piqa_eng.yaml | 24 +++++ lm_eval/tasks/aradice/piqa/piqa_lev.yaml | 24 +++++ lm_eval/tasks/aradice/piqa/piqa_msa.yaml | 24 +++++ .../tasks/aradice/truthfulqa_mcq/metrics.py | 25 +++++ .../truthfulqa_mcq/truthfulqa_mc1_egy.yaml | 39 ++++++++ .../truthfulqa_mcq/truthfulqa_mc1_eng.yaml | 40 ++++++++ .../truthfulqa_mcq/truthfulqa_mc1_lev.yaml | 39 ++++++++ .../truthfulqa_mcq/truthfulqa_mc1_msa.yaml | 39 ++++++++ lm_eval/tasks/aradice/winogrande/metrics.py | 25 +++++ lm_eval/tasks/aradice/winogrande/utils.py | 14 +++ .../aradice/winogrande/winogrande_egy.yaml | 24 +++++ .../aradice/winogrande/winogrande_eng.yaml | 24 +++++ .../aradice/winogrande/winogrande_lev.yaml | 24 +++++ .../aradice/winogrande/winogrande_msa.yaml | 24 +++++ 133 files changed, 2205 insertions(+) create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_history.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_islamic-studies.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_philosophy.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_language_arabic-language.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_civics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_economics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_geography.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_biology.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_computer-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_physics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_humanities_history.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_humanities_islamic-studies.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_language_arabic-language.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_other_general-knowledge.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_civics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_economics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_geography.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_social-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_stem_computer-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_stem_natural-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_humanities_islamic-studies.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_language_arabic-language-general.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_language_arabic-language-grammar.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_other_driving-test.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_other_general-knowledge.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_humanities_history.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_humanities_islamic-studies.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_language_arabic-language.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_other_general-knowledge.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_social-science_geography.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_social-science_social-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_computer-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_math.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_natural-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_prof_humanities_law.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_other_management.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_accounting.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_economics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_political-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_stem_computer-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/_default_template_yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/metrics.py create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/EGY/utils.py create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_history.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_islamic-studies.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_philosophy.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_language_arabic-language.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_civics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_economics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_geography.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_biology.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_computer-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_physics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_humanities_history.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_humanities_islamic-studies.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_language_arabic-language.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_other_general-knowledge.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_civics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_economics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_geography.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_social-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_stem_computer-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_stem_natural-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_humanities_islamic-studies.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_language_arabic-language-general.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_language_arabic-language-grammar.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_other_driving-test.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_other_general-knowledge.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_humanities_history.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_humanities_islamic-studies.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_language_arabic-language.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_other_general-knowledge.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_social-science_geography.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_social-science_social-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_computer-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_math.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_natural-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_prof_humanities_law.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_other_management.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_accounting.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_economics.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_political-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_stem_computer-science.yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/_default_template_yaml create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/metrics.py create mode 100644 lm_eval/tasks/aradice/ArabicMMLU/LEV/utils.py create mode 100644 lm_eval/tasks/aradice/README.md create mode 100644 lm_eval/tasks/aradice/aradice.yaml create mode 100644 lm_eval/tasks/aradice/boolq/EGY/boolq_egy.yaml create mode 100644 lm_eval/tasks/aradice/boolq/EGY/metrics.py create mode 100644 lm_eval/tasks/aradice/boolq/EGY/utils.py create mode 100644 lm_eval/tasks/aradice/boolq/ENG/boolq_eng.yaml create mode 100644 lm_eval/tasks/aradice/boolq/ENG/metrics.py create mode 100644 lm_eval/tasks/aradice/boolq/ENG/utils.py create mode 100644 lm_eval/tasks/aradice/boolq/LEV/boolq_lev.yaml create mode 100644 lm_eval/tasks/aradice/boolq/LEV/metrics.py create mode 100644 lm_eval/tasks/aradice/boolq/LEV/utils.py create mode 100644 lm_eval/tasks/aradice/boolq/MSA/boolq_msa.yaml create mode 100644 lm_eval/tasks/aradice/boolq/MSA/metrics.py create mode 100644 lm_eval/tasks/aradice/boolq/MSA/utils.py create mode 100644 lm_eval/tasks/aradice/cultural-benchmark/egypt.yaml create mode 100644 lm_eval/tasks/aradice/cultural-benchmark/jordan.yaml create mode 100644 lm_eval/tasks/aradice/cultural-benchmark/lebanon.yaml create mode 100644 lm_eval/tasks/aradice/cultural-benchmark/metrics.py create mode 100644 lm_eval/tasks/aradice/cultural-benchmark/palestine.yaml create mode 100644 lm_eval/tasks/aradice/cultural-benchmark/qatar.yaml create mode 100644 lm_eval/tasks/aradice/cultural-benchmark/syria.yaml create mode 100644 lm_eval/tasks/aradice/cultural-benchmark/utils.py create mode 100644 lm_eval/tasks/aradice/openbookqa/metrics.py create mode 100644 lm_eval/tasks/aradice/openbookqa/openbookqa_egy.yaml create mode 100644 lm_eval/tasks/aradice/openbookqa/openbookqa_eng.yaml create mode 100644 lm_eval/tasks/aradice/openbookqa/openbookqa_lev.yaml create mode 100644 lm_eval/tasks/aradice/openbookqa/openbookqa_msa.yaml create mode 100644 lm_eval/tasks/aradice/openbookqa/utils.py create mode 100644 lm_eval/tasks/aradice/piqa/metrics.py create mode 100644 lm_eval/tasks/aradice/piqa/piqa_egy.yaml create mode 100644 lm_eval/tasks/aradice/piqa/piqa_eng.yaml create mode 100644 lm_eval/tasks/aradice/piqa/piqa_lev.yaml create mode 100644 lm_eval/tasks/aradice/piqa/piqa_msa.yaml create mode 100644 lm_eval/tasks/aradice/truthfulqa_mcq/metrics.py create mode 100644 lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_egy.yaml create mode 100644 lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_eng.yaml create mode 100644 lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_lev.yaml create mode 100644 lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_msa.yaml create mode 100644 lm_eval/tasks/aradice/winogrande/metrics.py create mode 100644 lm_eval/tasks/aradice/winogrande/utils.py create mode 100644 lm_eval/tasks/aradice/winogrande/winogrande_egy.yaml create mode 100644 lm_eval/tasks/aradice/winogrande/winogrande_eng.yaml create mode 100644 lm_eval/tasks/aradice/winogrande/winogrande_lev.yaml create mode 100644 lm_eval/tasks/aradice/winogrande/winogrande_msa.yaml diff --git a/lm_eval/tasks/README.md b/lm_eval/tasks/README.md index 8db5ee31..20a1dfa5 100644 --- a/lm_eval/tasks/README.md +++ b/lm_eval/tasks/README.md @@ -14,6 +14,7 @@ | [arabic_leaderboard_complete](arabic_leaderboard_complete/README.md) | A full version of the tasks in the Open Arabic LLM Leaderboard, focusing on the evaluation of models that reflect the characteristics of Arabic language understanding and comprehension, culture, and heritage. Note that some of these tasks are machine-translated. | Arabic (Some MT) | | [arabic_leaderboard_light](arabic_leaderboard_light/README.md) | A light version of the tasks in the Open Arabic LLM Leaderboard (i.e., 10% samples of the test set in the original benchmarks), focusing on the evaluation of models that reflect the characteristics of Arabic language understanding and comprehension, culture, and heritage. Note that some of these tasks are machine-translated. | Arabic (Some MT) | | [arabicmmlu](arabicmmlu/README.md) | Localized Arabic version of MMLU with multiple-choice questions from 40 subjects. | Arabic | +| [AraDICE](aradice/README.md) | A collection of multiple tasks carefully designed to evaluate dialectal and cultural capabilities in large language models (LLMs). | Arabic | | [arc](arc/README.md) | Tasks involving complex reasoning over a diverse set of questions. | English | | [arithmetic](arithmetic/README.md) | Tasks involving numerical computations and arithmetic reasoning. | English | | [asdiv](asdiv/README.md) | Tasks involving arithmetic and mathematical reasoning challenges. | English | diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU.yaml new file mode 100644 index 00000000..77cbf95a --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU.yaml @@ -0,0 +1,12 @@ +group: AraDiCE_ArabicMMLU_egy +task: +- AraDiCE_ArabicMMLU_humanities_egy +- AraDiCE_ArabicMMLU_language_egy +- AraDiCE_ArabicMMLU_social-science_egy +- AraDiCE_ArabicMMLU_stem_egy +- AraDiCE_ArabicMMLU_other_egy +aggregate_metric_list: + - metric: acc + weight_by_size: True + - metric: acc_norm + weight_by_size: True diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_history.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_history.yaml new file mode 100644 index 00000000..5a03177d --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_history.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_humanities_history" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_egy" +"task": "AraDiCE_ArabicMMLU_high_humanities_history_egy" +"task_alias": "high humanities history" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_islamic-studies.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_islamic-studies.yaml new file mode 100644 index 00000000..ee65adc6 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_islamic-studies.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_humanities_islamic-studies" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_egy" +"task": "AraDiCE_ArabicMMLU_high_humanities_islamic-studies_egy" +"task_alias": "high humanities islamic-studies" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_philosophy.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_philosophy.yaml new file mode 100644 index 00000000..123f696f --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_humanities_philosophy.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_humanities_philosophy" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_egy" +"task": "AraDiCE_ArabicMMLU_high_humanities_philosophy_egy" +"task_alias": "high humanities philosophy" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_language_arabic-language.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_language_arabic-language.yaml new file mode 100644 index 00000000..1df05181 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_language_arabic-language.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_language_arabic-language" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_language_egy" +"task": "AraDiCE_ArabicMMLU_high_language_arabic-language_egy" +"task_alias": "high language arabic-language" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_civics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_civics.yaml new file mode 100644 index 00000000..7b42490b --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_civics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_social-science_civics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_high_social-science_civics_egy" +"task_alias": "high social-science civics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_economics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_economics.yaml new file mode 100644 index 00000000..5518b2cd --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_economics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_social-science_economics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_high_social-science_economics_egy" +"task_alias": "high social-science economics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_geography.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_geography.yaml new file mode 100644 index 00000000..d9a2d5b3 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_social-science_geography.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_social-science_geography" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_high_social-science_geography_egy" +"task_alias": "high social-science geography" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_biology.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_biology.yaml new file mode 100644 index 00000000..3f1ab8a7 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_biology.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_stem_biology" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_egy" +"task": "AraDiCE_ArabicMMLU_high_stem_biology_egy" +"task_alias": "high stem biology" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_computer-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_computer-science.yaml new file mode 100644 index 00000000..c27f5be3 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_computer-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_stem_computer-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_egy" +"task": "AraDiCE_ArabicMMLU_high_stem_computer-science_egy" +"task_alias": "high stem computer-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_physics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_physics.yaml new file mode 100644 index 00000000..4e24a2f4 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_high_stem_physics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_stem_physics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_egy" +"task": "AraDiCE_ArabicMMLU_high_stem_physics_egy" +"task_alias": "high stem physics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_humanities_history.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_humanities_history.yaml new file mode 100644 index 00000000..9f2c3770 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_humanities_history.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_humanities_history" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_egy" +"task": "AraDiCE_ArabicMMLU_middle_humanities_history_egy" +"task_alias": "middle humanities history" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_humanities_islamic-studies.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_humanities_islamic-studies.yaml new file mode 100644 index 00000000..41995c4a --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_humanities_islamic-studies.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_humanities_islamic-studies" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_egy" +"task": "AraDiCE_ArabicMMLU_middle_humanities_islamic-studies_egy" +"task_alias": "middle humanities islamic-studies" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_language_arabic-language.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_language_arabic-language.yaml new file mode 100644 index 00000000..e33bf590 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_language_arabic-language.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_language_arabic-language" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_language_egy" +"task": "AraDiCE_ArabicMMLU_middle_language_arabic-language_egy" +"task_alias": "middle language arabic-language" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_other_general-knowledge.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_other_general-knowledge.yaml new file mode 100644 index 00000000..73fc9027 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_other_general-knowledge.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_other_general-knowledge" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_other_egy" +"task": "AraDiCE_ArabicMMLU_middle_other_general-knowledge_egy" +"task_alias": "middle other general-knowledge" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_civics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_civics.yaml new file mode 100644 index 00000000..8407f36e --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_civics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_social-science_civics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_middle_social-science_civics_egy" +"task_alias": "middle social-science civics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_economics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_economics.yaml new file mode 100644 index 00000000..fbcb040d --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_economics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_social-science_economics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_middle_social-science_economics_egy" +"task_alias": "middle social-science economics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_geography.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_geography.yaml new file mode 100644 index 00000000..57fe94f2 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_geography.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_social-science_geography" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_middle_social-science_geography_egy" +"task_alias": "middle social-science geography" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_social-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_social-science.yaml new file mode 100644 index 00000000..115170b8 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_social-science_social-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_social-science_social-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_middle_social-science_social-science_egy" +"task_alias": "middle social-science social-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_stem_computer-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_stem_computer-science.yaml new file mode 100644 index 00000000..1d8787e3 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_stem_computer-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_stem_computer-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_egy" +"task": "AraDiCE_ArabicMMLU_middle_stem_computer-science_egy" +"task_alias": "middle stem computer-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_stem_natural-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_stem_natural-science.yaml new file mode 100644 index 00000000..ee09058c --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_middle_stem_natural-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_stem_natural-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_egy" +"task": "AraDiCE_ArabicMMLU_middle_stem_natural-science_egy" +"task_alias": "middle stem natural-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_humanities_islamic-studies.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_humanities_islamic-studies.yaml new file mode 100644 index 00000000..995aa28c --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_humanities_islamic-studies.yaml @@ -0,0 +1,10 @@ +"dataset_name": "na_humanities_islamic-studies" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_egy" +"task": "AraDiCE_ArabicMMLU_na_humanities_islamic-studies_egy" +"task_alias": "na humanities islamic-studies" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_language_arabic-language-general.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_language_arabic-language-general.yaml new file mode 100644 index 00000000..86912507 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_language_arabic-language-general.yaml @@ -0,0 +1,10 @@ +"dataset_name": "na_language_arabic-language-general" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_language_egy" +"task": "AraDiCE_ArabicMMLU_na_language_arabic-language-general_egy" +"task_alias": "na language arabic-language-general" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_language_arabic-language-grammar.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_language_arabic-language-grammar.yaml new file mode 100644 index 00000000..453e4143 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_language_arabic-language-grammar.yaml @@ -0,0 +1,10 @@ +"dataset_name": "na_language_arabic-language-grammar" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_language_egy" +"task": "AraDiCE_ArabicMMLU_na_language_arabic-language-grammar_egy" +"task_alias": "na language arabic-language-grammar" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_other_driving-test.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_other_driving-test.yaml new file mode 100644 index 00000000..abc09721 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_other_driving-test.yaml @@ -0,0 +1,10 @@ +"dataset_name": "na_other_driving-test" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_other_egy" +"task": "AraDiCE_ArabicMMLU_na_other_driving-test_egy" +"task_alias": "na other driving-test" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_other_general-knowledge.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_other_general-knowledge.yaml new file mode 100644 index 00000000..72af8e7f --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_na_other_general-knowledge.yaml @@ -0,0 +1,10 @@ +"dataset_name": "na_other_general-knowledge" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_other_egy" +"task": "AraDiCE_ArabicMMLU_na_other_general-knowledge_egy" +"task_alias": "na other general-knowledge" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_humanities_history.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_humanities_history.yaml new file mode 100644 index 00000000..5e640faa --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_humanities_history.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_humanities_history" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_egy" +"task": "AraDiCE_ArabicMMLU_primary_humanities_history_egy" +"task_alias": "primary humanities history" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_humanities_islamic-studies.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_humanities_islamic-studies.yaml new file mode 100644 index 00000000..120dfa14 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_humanities_islamic-studies.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_humanities_islamic-studies" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_egy" +"task": "AraDiCE_ArabicMMLU_primary_humanities_islamic-studies_egy" +"task_alias": "primary humanities islamic-studies" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_language_arabic-language.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_language_arabic-language.yaml new file mode 100644 index 00000000..57c460a0 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_language_arabic-language.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_language_arabic-language" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_language_egy" +"task": "AraDiCE_ArabicMMLU_primary_language_arabic-language_egy" +"task_alias": "primary language arabic-language" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_other_general-knowledge.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_other_general-knowledge.yaml new file mode 100644 index 00000000..61314bf1 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_other_general-knowledge.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_other_general-knowledge" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_other_egy" +"task": "AraDiCE_ArabicMMLU_primary_other_general-knowledge_egy" +"task_alias": "primary other general-knowledge" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_social-science_geography.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_social-science_geography.yaml new file mode 100644 index 00000000..73b8deea --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_social-science_geography.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_social-science_geography" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_primary_social-science_geography_egy" +"task_alias": "primary social-science geography" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_social-science_social-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_social-science_social-science.yaml new file mode 100644 index 00000000..5f03bb4b --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_social-science_social-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_social-science_social-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_primary_social-science_social-science_egy" +"task_alias": "primary social-science social-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_computer-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_computer-science.yaml new file mode 100644 index 00000000..5e25856e --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_computer-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_stem_computer-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_egy" +"task": "AraDiCE_ArabicMMLU_primary_stem_computer-science_egy" +"task_alias": "primary stem computer-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_math.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_math.yaml new file mode 100644 index 00000000..d4e85ac2 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_math.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_stem_math" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_egy" +"task": "AraDiCE_ArabicMMLU_primary_stem_math_egy" +"task_alias": "primary stem math" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_natural-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_natural-science.yaml new file mode 100644 index 00000000..04591fcd --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_primary_stem_natural-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_stem_natural-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_egy" +"task": "AraDiCE_ArabicMMLU_primary_stem_natural-science_egy" +"task_alias": "primary stem natural-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_prof_humanities_law.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_prof_humanities_law.yaml new file mode 100644 index 00000000..4fd3e166 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_prof_humanities_law.yaml @@ -0,0 +1,10 @@ +"dataset_name": "prof_humanities_law" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_egy" +"task": "AraDiCE_ArabicMMLU_prof_humanities_law_egy" +"task_alias": "prof humanities law" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_other_management.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_other_management.yaml new file mode 100644 index 00000000..6b985e97 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_other_management.yaml @@ -0,0 +1,10 @@ +"dataset_name": "univ_other_management" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_other_egy" +"task": "AraDiCE_ArabicMMLU_univ_other_management_egy" +"task_alias": "univ other management" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_accounting.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_accounting.yaml new file mode 100644 index 00000000..48ec0e75 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_accounting.yaml @@ -0,0 +1,10 @@ +"dataset_name": "univ_social-science_accounting" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_univ_social-science_accounting_egy" +"task_alias": "univ social-science accounting" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_economics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_economics.yaml new file mode 100644 index 00000000..3dd4dcc0 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_economics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "univ_social-science_economics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_univ_social-science_economics_egy" +"task_alias": "univ social-science economics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_political-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_political-science.yaml new file mode 100644 index 00000000..671b0b3e --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_social-science_political-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "univ_social-science_political-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_egy" +"task": "AraDiCE_ArabicMMLU_univ_social-science_political-science_egy" +"task_alias": "univ social-science political-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_stem_computer-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_stem_computer-science.yaml new file mode 100644 index 00000000..49e2e5b6 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/AraDiCE_ArabicMMLU_univ_stem_computer-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "univ_stem_computer-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_egy" +"task": "AraDiCE_ArabicMMLU_univ_stem_computer-science_egy" +"task_alias": "univ stem computer-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/_default_template_yaml b/lm_eval/tasks/aradice/ArabicMMLU/EGY/_default_template_yaml new file mode 100644 index 00000000..6421888a --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/_default_template_yaml @@ -0,0 +1,20 @@ +dataset_path: "QCRI/AraDICE-ArabicMMLU-egy" +fewshot_config: + sampler: default +output_type: multiple_choice +process_docs: !function utils.process_docs +doc_to_text: "{{prompt}}" +doc_to_choice: choices +doc_to_target: target +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 0.0 diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/metrics.py b/lm_eval/tasks/aradice/ArabicMMLU/EGY/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/ArabicMMLU/EGY/utils.py b/lm_eval/tasks/aradice/ArabicMMLU/EGY/utils.py new file mode 100644 index 00000000..640b9a0f --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/EGY/utils.py @@ -0,0 +1,87 @@ +level_ar = { + "Primary": "للمرحلة الابتدائية", + "Middle": "للمرحلة المتوسطة", + "High": "للمرحلة الثانوية", + "Univ": "للمرحلة الجامعية ", + "Prof": "للمحترفين", +} + +country_ar = { + "UAE": "في الإمارات", + "Egypt": "في مصر", + "Lebanon": "في لبنان", + "Jordan": "في الأردن", + "Kuwait": "في الكويت", + "KSA": "في السعودية", + "Palestine": "في فلسطين", + "Morocco": "في المغرب", +} + +subject_ar = { + "Islamic Studies": "في الدراسات إسلامية", + "Driving Test": "في اختبار القيادة", + "Natural Science": "في العلوم الطبيعية", + "History": "في مادة التاريخ", + "General Knowledge": "في المعرفة العامة", + "Law": "في القانون", + "Physics": "في الفيزياء", + "Social Science": "في العلوم الاجتماعية", + "Management": "في الإدارة", + "Arabic Language": "في اللغة العربية", + "Political Science": " في العلوم السياسية", + "Philosophy": "في الفلسفة", + "Accounting": "في المحاسبة", + "Computer Science": "في علوم الحاسوب", + "Geography": "في الجغرافيا", + "Math": "في الرياضيات", + "Biology": "في علم الأحياء", + "Economics": "في الاقتصاد", + "Arabic Language (General)": "في اللغة العربية (عام)", + "Arabic Language (Grammar)": "في اللغة العربية (النحو)", + "Civics": "في التربية المدنية", +} + + +alpa_ar = ["أ-", "ب-", "ج-", "د-", "و-"] +alpa_en = ["A-", "B-", "C-", "D-", "E-"] +all_choices = ["أ", "ب", "ج", "د", "و"] +all_choices_en = ["A", "B", "C", "D", "E"] + + +def process_docs(dataset): + def _helper(doc): + # modifies the contents of a single + # document in our dataset. + + PROMPT = "ده سؤال [MAIN_META_DATA]. اختار الإجابة الصحيحة!\n\nسؤال: [INPUT]\n[OPTION]" + PROMPT = f"{PROMPT}\n\nإجابة:" + alpa = alpa_ar + subject = subject_ar[doc["Subject"]] + level = " " + level_ar[doc["Level"]] if doc["Level"] else "" + country = " " + country_ar[doc["Country"]] if doc["Country"] else "" + main_meta_data = f"{subject}{level}{country}" + + question = ( + f"{doc['context']}\n\n{doc['question']}" + if doc["context"] + else doc["question"] + ) + options = [] + for i, opt in enumerate(["A", "B", "C", "D", "E"]): + if opt not in doc["options"] or doc["options"][opt] is None: + break + options.append(f"{alpa[i]} {doc['options'][opt]}") + + doc["prompt"] = ( + PROMPT.replace("[MAIN_META_DATA]", main_meta_data) + .replace("[INPUT]", question) + .replace("[OPTION]", "\n".join(options)) + ) + + doc["choices"] = all_choices[: len(options)] + + doc["target"] = ["A", "B", "C", "D", "E"].index(doc["Answer Key"]) + + return doc + + return dataset.map(_helper) # returns back a datasets.Dataset object diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU.yaml new file mode 100644 index 00000000..df64389d --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU.yaml @@ -0,0 +1,12 @@ +group: AraDiCE_ArabicMMLU_lev +task: +- AraDiCE_ArabicMMLU_humanities_lev +- AraDiCE_ArabicMMLU_language_lev +- AraDiCE_ArabicMMLU_social-science_lev +- AraDiCE_ArabicMMLU_stem_lev +- AraDiCE_ArabicMMLU_other_lev +aggregate_metric_list: + - metric: acc + weight_by_size: True + - metric: acc_norm + weight_by_size: True diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_history.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_history.yaml new file mode 100644 index 00000000..fbe1838c --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_history.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_humanities_history" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_lev" +"task": "AraDiCE_ArabicMMLU_high_humanities_history_lev" +"task_alias": "high humanities history" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_islamic-studies.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_islamic-studies.yaml new file mode 100644 index 00000000..2e1d874e --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_islamic-studies.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_humanities_islamic-studies" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_lev" +"task": "AraDiCE_ArabicMMLU_high_humanities_islamic-studies_lev" +"task_alias": "high humanities islamic-studies" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_philosophy.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_philosophy.yaml new file mode 100644 index 00000000..752a95f3 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_humanities_philosophy.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_humanities_philosophy" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_lev" +"task": "AraDiCE_ArabicMMLU_high_humanities_philosophy_lev" +"task_alias": "high humanities philosophy" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_language_arabic-language.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_language_arabic-language.yaml new file mode 100644 index 00000000..27d14f96 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_language_arabic-language.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_language_arabic-language" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_language_lev" +"task": "AraDiCE_ArabicMMLU_high_language_arabic-language_lev" +"task_alias": "high language arabic-language" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_civics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_civics.yaml new file mode 100644 index 00000000..29d1a520 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_civics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_social-science_civics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_high_social-science_civics_lev" +"task_alias": "high social-science civics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_economics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_economics.yaml new file mode 100644 index 00000000..378587a8 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_economics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_social-science_economics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_high_social-science_economics_lev" +"task_alias": "high social-science economics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_geography.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_geography.yaml new file mode 100644 index 00000000..11668a5f --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_social-science_geography.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_social-science_geography" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_high_social-science_geography_lev" +"task_alias": "high social-science geography" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_biology.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_biology.yaml new file mode 100644 index 00000000..80900b2f --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_biology.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_stem_biology" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_lev" +"task": "AraDiCE_ArabicMMLU_high_stem_biology_lev" +"task_alias": "high stem biology" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_computer-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_computer-science.yaml new file mode 100644 index 00000000..eca96f2c --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_computer-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_stem_computer-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_lev" +"task": "AraDiCE_ArabicMMLU_high_stem_computer-science_lev" +"task_alias": "high stem computer-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_physics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_physics.yaml new file mode 100644 index 00000000..1d21bcc6 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_high_stem_physics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "high_stem_physics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_lev" +"task": "AraDiCE_ArabicMMLU_high_stem_physics_lev" +"task_alias": "high stem physics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_humanities_history.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_humanities_history.yaml new file mode 100644 index 00000000..8dd3cfb9 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_humanities_history.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_humanities_history" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_lev" +"task": "AraDiCE_ArabicMMLU_middle_humanities_history_lev" +"task_alias": "middle humanities history" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_humanities_islamic-studies.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_humanities_islamic-studies.yaml new file mode 100644 index 00000000..7e5490e4 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_humanities_islamic-studies.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_humanities_islamic-studies" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_lev" +"task": "AraDiCE_ArabicMMLU_middle_humanities_islamic-studies_lev" +"task_alias": "middle humanities islamic-studies" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_language_arabic-language.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_language_arabic-language.yaml new file mode 100644 index 00000000..b67e3be5 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_language_arabic-language.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_language_arabic-language" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_language_lev" +"task": "AraDiCE_ArabicMMLU_middle_language_arabic-language_lev" +"task_alias": "middle language arabic-language" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_other_general-knowledge.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_other_general-knowledge.yaml new file mode 100644 index 00000000..bd43ebe3 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_other_general-knowledge.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_other_general-knowledge" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_other_lev" +"task": "AraDiCE_ArabicMMLU_middle_other_general-knowledge_lev" +"task_alias": "middle other general-knowledge" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_civics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_civics.yaml new file mode 100644 index 00000000..a18665cf --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_civics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_social-science_civics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_middle_social-science_civics_lev" +"task_alias": "middle social-science civics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_economics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_economics.yaml new file mode 100644 index 00000000..e1de265b --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_economics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_social-science_economics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_middle_social-science_economics_lev" +"task_alias": "middle social-science economics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_geography.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_geography.yaml new file mode 100644 index 00000000..19083eb0 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_geography.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_social-science_geography" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_middle_social-science_geography_lev" +"task_alias": "middle social-science geography" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_social-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_social-science.yaml new file mode 100644 index 00000000..3c7d19c7 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_social-science_social-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_social-science_social-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_middle_social-science_social-science_lev" +"task_alias": "middle social-science social-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_stem_computer-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_stem_computer-science.yaml new file mode 100644 index 00000000..583e29b1 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_stem_computer-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_stem_computer-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_lev" +"task": "AraDiCE_ArabicMMLU_middle_stem_computer-science_lev" +"task_alias": "middle stem computer-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_stem_natural-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_stem_natural-science.yaml new file mode 100644 index 00000000..a1904d2c --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_middle_stem_natural-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "middle_stem_natural-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_lev" +"task": "AraDiCE_ArabicMMLU_middle_stem_natural-science_lev" +"task_alias": "middle stem natural-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_humanities_islamic-studies.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_humanities_islamic-studies.yaml new file mode 100644 index 00000000..ac0bfe8a --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_humanities_islamic-studies.yaml @@ -0,0 +1,10 @@ +"dataset_name": "na_humanities_islamic-studies" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_lev" +"task": "AraDiCE_ArabicMMLU_na_humanities_islamic-studies_lev" +"task_alias": "na humanities islamic-studies" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_language_arabic-language-general.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_language_arabic-language-general.yaml new file mode 100644 index 00000000..f80e6e93 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_language_arabic-language-general.yaml @@ -0,0 +1,10 @@ +"dataset_name": "na_language_arabic-language-general" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_language_lev" +"task": "AraDiCE_ArabicMMLU_na_language_arabic-language-general_lev" +"task_alias": "na language arabic-language-general" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_language_arabic-language-grammar.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_language_arabic-language-grammar.yaml new file mode 100644 index 00000000..af3943d9 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_language_arabic-language-grammar.yaml @@ -0,0 +1,10 @@ +"dataset_name": "na_language_arabic-language-grammar" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_language_lev" +"task": "AraDiCE_ArabicMMLU_na_language_arabic-language-grammar_lev" +"task_alias": "na language arabic-language-grammar" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_other_driving-test.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_other_driving-test.yaml new file mode 100644 index 00000000..0af542f0 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_other_driving-test.yaml @@ -0,0 +1,10 @@ +"dataset_name": "na_other_driving-test" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_other_lev" +"task": "AraDiCE_ArabicMMLU_na_other_driving-test_lev" +"task_alias": "na other driving-test" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_other_general-knowledge.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_other_general-knowledge.yaml new file mode 100644 index 00000000..0c5669cf --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_na_other_general-knowledge.yaml @@ -0,0 +1,10 @@ +"dataset_name": "na_other_general-knowledge" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_other_lev" +"task": "AraDiCE_ArabicMMLU_na_other_general-knowledge_lev" +"task_alias": "na other general-knowledge" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_humanities_history.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_humanities_history.yaml new file mode 100644 index 00000000..be32d433 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_humanities_history.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_humanities_history" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_lev" +"task": "AraDiCE_ArabicMMLU_primary_humanities_history_lev" +"task_alias": "primary humanities history" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_humanities_islamic-studies.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_humanities_islamic-studies.yaml new file mode 100644 index 00000000..9ae53b80 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_humanities_islamic-studies.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_humanities_islamic-studies" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_lev" +"task": "AraDiCE_ArabicMMLU_primary_humanities_islamic-studies_lev" +"task_alias": "primary humanities islamic-studies" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_language_arabic-language.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_language_arabic-language.yaml new file mode 100644 index 00000000..15575b05 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_language_arabic-language.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_language_arabic-language" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_language_lev" +"task": "AraDiCE_ArabicMMLU_primary_language_arabic-language_lev" +"task_alias": "primary language arabic-language" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_other_general-knowledge.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_other_general-knowledge.yaml new file mode 100644 index 00000000..07b66921 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_other_general-knowledge.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_other_general-knowledge" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_other_lev" +"task": "AraDiCE_ArabicMMLU_primary_other_general-knowledge_lev" +"task_alias": "primary other general-knowledge" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_social-science_geography.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_social-science_geography.yaml new file mode 100644 index 00000000..b43c4903 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_social-science_geography.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_social-science_geography" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_primary_social-science_geography_lev" +"task_alias": "primary social-science geography" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_social-science_social-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_social-science_social-science.yaml new file mode 100644 index 00000000..8f9f0934 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_social-science_social-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_social-science_social-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_primary_social-science_social-science_lev" +"task_alias": "primary social-science social-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_computer-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_computer-science.yaml new file mode 100644 index 00000000..6a79f2e7 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_computer-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_stem_computer-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_lev" +"task": "AraDiCE_ArabicMMLU_primary_stem_computer-science_lev" +"task_alias": "primary stem computer-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_math.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_math.yaml new file mode 100644 index 00000000..048c9509 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_math.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_stem_math" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_lev" +"task": "AraDiCE_ArabicMMLU_primary_stem_math_lev" +"task_alias": "primary stem math" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_natural-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_natural-science.yaml new file mode 100644 index 00000000..6d7404ae --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_primary_stem_natural-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "primary_stem_natural-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_lev" +"task": "AraDiCE_ArabicMMLU_primary_stem_natural-science_lev" +"task_alias": "primary stem natural-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_prof_humanities_law.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_prof_humanities_law.yaml new file mode 100644 index 00000000..1c50cb9d --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_prof_humanities_law.yaml @@ -0,0 +1,10 @@ +"dataset_name": "prof_humanities_law" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_humanities_lev" +"task": "AraDiCE_ArabicMMLU_prof_humanities_law_lev" +"task_alias": "prof humanities law" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_other_management.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_other_management.yaml new file mode 100644 index 00000000..31b79fd0 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_other_management.yaml @@ -0,0 +1,10 @@ +"dataset_name": "univ_other_management" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_other_lev" +"task": "AraDiCE_ArabicMMLU_univ_other_management_lev" +"task_alias": "univ other management" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_accounting.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_accounting.yaml new file mode 100644 index 00000000..fc0cb682 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_accounting.yaml @@ -0,0 +1,10 @@ +"dataset_name": "univ_social-science_accounting" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_univ_social-science_accounting_lev" +"task_alias": "univ social-science accounting" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_economics.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_economics.yaml new file mode 100644 index 00000000..daec1b37 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_economics.yaml @@ -0,0 +1,10 @@ +"dataset_name": "univ_social-science_economics" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_univ_social-science_economics_lev" +"task_alias": "univ social-science economics" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_political-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_political-science.yaml new file mode 100644 index 00000000..e69f63ca --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_social-science_political-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "univ_social-science_political-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_social-science_lev" +"task": "AraDiCE_ArabicMMLU_univ_social-science_political-science_lev" +"task_alias": "univ social-science political-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_stem_computer-science.yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_stem_computer-science.yaml new file mode 100644 index 00000000..aeb8fa81 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/AraDiCE_ArabicMMLU_univ_stem_computer-science.yaml @@ -0,0 +1,10 @@ +"dataset_name": "univ_stem_computer-science" +"description": "" +"fewshot_split": !!null "null" +"include": "_default_template_yaml" +"tag": "AraDiCE_ArabicMMLU_stem_lev" +"task": "AraDiCE_ArabicMMLU_univ_stem_computer-science_lev" +"task_alias": "univ stem computer-science" +"test_split": "test" +"training_split": !!null "null" +"validation_split": !!null "null" diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/_default_template_yaml b/lm_eval/tasks/aradice/ArabicMMLU/LEV/_default_template_yaml new file mode 100644 index 00000000..45c5a345 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/_default_template_yaml @@ -0,0 +1,20 @@ +dataset_path: QCRI/AraDICE-ArabicMMLU-lev +fewshot_config: + sampler: default +output_type: multiple_choice +process_docs: !function utils.process_docs +doc_to_text: "{{prompt}}" +doc_to_choice: choices +doc_to_target: target +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 0.0 diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/metrics.py b/lm_eval/tasks/aradice/ArabicMMLU/LEV/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/ArabicMMLU/LEV/utils.py b/lm_eval/tasks/aradice/ArabicMMLU/LEV/utils.py new file mode 100644 index 00000000..37683c46 --- /dev/null +++ b/lm_eval/tasks/aradice/ArabicMMLU/LEV/utils.py @@ -0,0 +1,94 @@ +level_ar = { + "Primary": "للمرحلة الابتدائية", + "Middle": "للمرحلة المتوسطة", + "High": "للمرحلة الثانوية", + "Univ": "للمرحلة الجامعية ", + "Prof": "للمحترفين", +} + +country_ar = { + "UAE": "بالإمارات", + "Egypt": "بمصر", + "Lebanon": "بلبنان", + "Jordan": "بالأردن", + "Kuwait": "بالكويت", + "KSA": "بالسعودية", + "Palestine": "بفلسطين", + "Morocco": "بالمغرب", +} + +subject_ar = { + "Islamic Studies": "عن الدراسات إسلامية", + "Driving Test": "عن فحص السواقة", + "Natural Science": "عن العلوم الطبيعية", + "History": "تاريخ", + "General Knowledge": "معرفة عامة", + "Law": "عن القانون", + "Physics": "فيزياء", + "Social Science": "علوم اجتماعية", + "Management": "عن الإدارة", + "Arabic Language": "عن اللغة العربية", + "Political Science": " عن العلوم السياسية", + "Philosophy": "فلسفة", + "Accounting": "محاسبة", + "Computer Science": "عن علوم الحاسوب", + "Geography": "جغرافيا", + "Math": "رياضيات", + "Biology": "بيولوجي", + "Economics": "اقتصاد", + "Arabic Language (General)": "لغة العربية (عام)", + "Arabic Language (Grammar)": "لغة العربية (نحو)", + "Civics": "تربية مدنية", +} + +alpa_ar = ["أ-", "ب-", "ج-", "د-", "و-"] +alpa_en = ["A-", "B-", "C-", "D-", "E-"] +all_choices = ["أ", "ب", "ج", "د", "و"] +all_choices_en = ["A", "B", "C", "D", "E"] + + +def process_docs(dataset): + def _helper(doc): + # modifies the contents of a single + # document in our dataset. + PROMPT = ( + "هيدا سؤال [MAIN_META_DATA]. نقي الجواب الصح!\n\nسؤال: [INPUT]\n[OPTION]" + ) + + # if args.lora_weights == "x": + PROMPT = f"{PROMPT}\n\nالجواب:" + # else: + # PROMPT = f'### Input:{PROMPT}\n\n### Output:\n' + + alpa = alpa_ar + + subject = subject_ar[doc["Subject"]] + level = " " + level_ar[doc["Level"]] if doc["Level"] else "" + country = " " + country_ar[doc["Country"]] if doc["Country"] else "" + main_meta_data = f"{subject}{level}{country}" + + question = ( + f"{doc['context']}\n\n{doc['question']}" + if doc["context"] + else doc["question"] + ) + options = [] + + for i, opt in enumerate(["A", "B", "C", "D", "E"]): + if opt not in doc["options"] or doc["options"][opt] is None: + break + options.append(f"{alpa[i]} {doc['options'][opt]}") + + doc["prompt"] = ( + PROMPT.replace("[MAIN_META_DATA]", main_meta_data) + .replace("[INPUT]", question) + .replace("[OPTION]", "\n".join(options)) + ) + + doc["choices"] = all_choices[: len(options)] + + doc["target"] = ["A", "B", "C", "D", "E"].index(doc["Answer Key"]) + + return doc + + return dataset.map(_helper) diff --git a/lm_eval/tasks/aradice/README.md b/lm_eval/tasks/aradice/README.md new file mode 100644 index 00000000..c0f1043d --- /dev/null +++ b/lm_eval/tasks/aradice/README.md @@ -0,0 +1,49 @@ +# AraDiCE + +### Paper + +**Title:** AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs + +**Abstract:** Arabic, with its rich diversity of dialects, remains significantly underrepresented in Large Language Models, particularly in dialectal variations. We address this gap by introducing seven synthetic datasets in dialects alongside Modern Standard Arabic (MSA), created using Machine Translation (MT) combined with human post-editing. We present AraDiCE, a benchmark for Arabic Dialect and Cultural Evaluation. We evaluate LLMs on dialect comprehension and generation, focusing specifically on low-resource Arabic dialects. Additionally, we introduce the first-ever fine-grained benchmark designed to evaluate cultural awareness across the Gulf, Egypt, and Levant regions, providing a novel dimension to LLM evaluation. Our findings demonstrate that while Arabic-specific models like Jais and AceGPT outperform multilingual models on dialectal tasks, significant challenges persist in dialect identification, generation, and translation. This work contributes ~45K post-edited samples, a cultural benchmark, and highlights the importance of tailored training to improve LLM performance in capturing the nuances of diverse Arabic dialects and cultural contexts. We will release the dialectal translation models and benchmarks curated in this study. + +**Homepage:** +https://huggingface.co/datasets/QCRI/AraDiCE + + + +### Citation + +``` +@article{mousi2024aradicebenchmarksdialectalcultural, + title={{AraDiCE}: Benchmarks for Dialectal and Cultural Capabilities in LLMs}, + author={Basel Mousi and Nadir Durrani and Fatema Ahmad and Md. Arid Hasan and Maram Hasanain and Tameem Kabbani and Fahim Dalvi and Shammur Absar Chowdhury and Firoj Alam}, + year={2024}, + publisher={arXiv:2409.11404}, + url={https://arxiv.org/abs/2409.11404}, +} +``` + +### Groups, Tags, and Tasks + +#### Groups + +* `AraDiCE`: Overall results for all tasks associated with different datasets. + + +#### Tasks + +* `aradice`: Overall results for all tasks associated with different datasets. +* `arabicmmlu`: TODO + + +### Checklist + +* [x] Is the task an existing benchmark in the literature? + * [x] Have you referenced the original paper that introduced the task? + * [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? + + +If other tasks on this dataset are already supported: +* [x] Is the "Main" variant of this task clearly denoted? +* [x] Have you provided a short sentence in a README on what each new variant adds / evaluates? +* [x] Have you noted which, if any, published evaluation setups are matched by this variant? diff --git a/lm_eval/tasks/aradice/aradice.yaml b/lm_eval/tasks/aradice/aradice.yaml new file mode 100644 index 00000000..8c7759f2 --- /dev/null +++ b/lm_eval/tasks/aradice/aradice.yaml @@ -0,0 +1,30 @@ +group: AraDiCE +task: +- AraDiCE_ArabicMMLU_lev +- AraDiCE_ArabicMMLU_egy +- AraDiCE_boolq_egy +- AraDiCE_boolq_eng +- AraDiCE_boolq_lev +- AraDiCE_boolq_msa +- AraDiCE_egypt_cultural +- AraDiCE_jordan_cultural +- AraDiCE_lebanon_cultural +- AraDiCE_palestine_cultural +- AraDiCE_qatar_cultural +- AraDiCE_syria_cultural +- AraDiCE_openbookqa_egy +- AraDiCE_openbookqa_eng +- AraDiCE_openbookqa_lev +- AraDiCE_openbookqa_msa +- AraDiCE_piqa_egy +- AraDiCE_piqa_eng +- AraDiCE_piqa_lev +- AraDiCE_piqa_msa +- AraDiCE_truthfulqa_mc1_egy +- AraDiCE_truthfulqa_mc1_eng +- AraDiCE_truthfulqa_mc1_lev +- AraDiCE_truthfulqa_mc1_msa +- AraDiCE_winogrande_egy +- AraDiCE_winogrande_eng +- AraDiCE_winogrande_lev +- AraDiCE_winogrande_msa diff --git a/lm_eval/tasks/aradice/boolq/EGY/boolq_egy.yaml b/lm_eval/tasks/aradice/boolq/EGY/boolq_egy.yaml new file mode 100644 index 00000000..c481c24a --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/EGY/boolq_egy.yaml @@ -0,0 +1,25 @@ +task: AraDiCE_boolq_egy +dataset_path: QCRI/AraDiCE-BoolQ +dataset_name: BoolQ-egy +output_type: multiple_choice +training_split: null +validation_split: null +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{passage}}\nسؤال: {{question}}؟\nجواب:" +doc_to_target: target +doc_to_choice: ["لا", "نعم"] +should_decontaminate: true +doc_to_decontamination_query: passage +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/boolq/EGY/metrics.py b/lm_eval/tasks/aradice/boolq/EGY/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/EGY/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/boolq/EGY/utils.py b/lm_eval/tasks/aradice/boolq/EGY/utils.py new file mode 100644 index 00000000..4220133e --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/EGY/utils.py @@ -0,0 +1,18 @@ +egy_answer_mapping = {"true": "نعم", "false": "لا", True: "نعم", False: "لا"} + + +def process_docs(dataset): + def remove_question_mark(text): + text = text.strip() + if text.endswith("?") or text.endswith("؟"): + text = text[:-1] + text = text.strip() + + return text + + def _helper(doc): + doc["question"] = remove_question_mark(doc["question"]) + doc["target"] = egy_answer_mapping[doc["answer"]] + return doc + + return dataset.map(_helper) diff --git a/lm_eval/tasks/aradice/boolq/ENG/boolq_eng.yaml b/lm_eval/tasks/aradice/boolq/ENG/boolq_eng.yaml new file mode 100644 index 00000000..1409aebf --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/ENG/boolq_eng.yaml @@ -0,0 +1,25 @@ +task: AraDiCE_boolq_eng +dataset_path: QCRI/AraDiCE-BoolQ +dataset_name: BoolQ-eng +output_type: multiple_choice +training_split: null +validation_split: null +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{passage}}\nQuestion: {{question}}?\nAnswer:" +doc_to_target: target +doc_to_choice: ["no", "yes"] +should_decontaminate: true +doc_to_decontamination_query: passage +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/boolq/ENG/metrics.py b/lm_eval/tasks/aradice/boolq/ENG/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/ENG/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/boolq/ENG/utils.py b/lm_eval/tasks/aradice/boolq/ENG/utils.py new file mode 100644 index 00000000..3f1233cd --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/ENG/utils.py @@ -0,0 +1,18 @@ +en_answer_mapping = {"true": "yes", "false": "no", True: "yes", False: "no"} + + +def process_docs(dataset): + def remove_question_mark(text): + text = text.strip() + if text.endswith("?") or text.endswith("؟"): + text = text[:-1] + text = text.strip() + + return text + + def _helper(doc): + doc["question"] = remove_question_mark(doc["question"]) + doc["target"] = en_answer_mapping[doc["answer"]] + return doc + + return dataset.map(_helper) diff --git a/lm_eval/tasks/aradice/boolq/LEV/boolq_lev.yaml b/lm_eval/tasks/aradice/boolq/LEV/boolq_lev.yaml new file mode 100644 index 00000000..ccbe9477 --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/LEV/boolq_lev.yaml @@ -0,0 +1,25 @@ +task: AraDiCE_boolq_lev +dataset_path: QCRI/AraDiCE-BoolQ +dataset_name: BoolQ-lev +output_type: multiple_choice +training_split: null +validation_split: null +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{passage}}\nسؤال: {{question}}؟\nجواب:" +doc_to_target: target +doc_to_choice: ["لا", "نعم"] +should_decontaminate: true +doc_to_decontamination_query: passage +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/boolq/LEV/metrics.py b/lm_eval/tasks/aradice/boolq/LEV/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/LEV/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/boolq/LEV/utils.py b/lm_eval/tasks/aradice/boolq/LEV/utils.py new file mode 100644 index 00000000..3f601229 --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/LEV/utils.py @@ -0,0 +1,18 @@ +lev_answer_mapping = {"true": "نعم", "false": "لا", True: "نعم", False: "لا"} + + +def process_docs(dataset): + def remove_question_mark(text): + text = text.strip() + if text.endswith("?") or text.endswith("؟"): + text = text[:-1] + text = text.strip() + + return text + + def _helper(doc): + doc["question"] = remove_question_mark(doc["question"]) + doc["target"] = lev_answer_mapping[doc["answer"]] + return doc + + return dataset.map(_helper) diff --git a/lm_eval/tasks/aradice/boolq/MSA/boolq_msa.yaml b/lm_eval/tasks/aradice/boolq/MSA/boolq_msa.yaml new file mode 100644 index 00000000..ea3208ec --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/MSA/boolq_msa.yaml @@ -0,0 +1,25 @@ +task: AraDiCE_boolq_msa +dataset_path: QCRI/AraDiCE-BoolQ +dataset_name: BoolQ-msa +output_type: multiple_choice +training_split: null +validation_split: null +test_split: test +process_docs: !function utils.process_docs +doc_to_text: "{{passage}}\nسؤال: {{question}}؟\nجواب:" +doc_to_target: target +doc_to_choice: ["لا", "نعم"] +should_decontaminate: true +doc_to_decontamination_query: passage +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/boolq/MSA/metrics.py b/lm_eval/tasks/aradice/boolq/MSA/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/MSA/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/boolq/MSA/utils.py b/lm_eval/tasks/aradice/boolq/MSA/utils.py new file mode 100644 index 00000000..47a80046 --- /dev/null +++ b/lm_eval/tasks/aradice/boolq/MSA/utils.py @@ -0,0 +1,18 @@ +msa_answer_mapping = {"true": "نعم", "false": "لا", True: "نعم", False: "لا"} + + +def process_docs(dataset): + def remove_question_mark(text): + text = text.strip() + if text.endswith("?") or text.endswith("؟"): + text = text[:-1] + text = text.strip() + + return text + + def _helper(doc): + doc["question"] = remove_question_mark(doc["question"]) + doc["target"] = msa_answer_mapping[doc["answer"]] + return doc + + return dataset.map(_helper) diff --git a/lm_eval/tasks/aradice/cultural-benchmark/egypt.yaml b/lm_eval/tasks/aradice/cultural-benchmark/egypt.yaml new file mode 100644 index 00000000..c2d5da2e --- /dev/null +++ b/lm_eval/tasks/aradice/cultural-benchmark/egypt.yaml @@ -0,0 +1,25 @@ +task: AraDiCE_egypt_cultural +dataset_path: QCRI/AraDiCE-Culture +dataset_name: Egypt +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +process_docs: !function utils.process_docs +doc_to_text: "سؤال : {{Question}}\nإجابة :" +doc_to_target: 0 +doc_to_choice: choices +should_decontaminate: true +doc_to_decontamination_query: Question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/cultural-benchmark/jordan.yaml b/lm_eval/tasks/aradice/cultural-benchmark/jordan.yaml new file mode 100644 index 00000000..dc2b3db5 --- /dev/null +++ b/lm_eval/tasks/aradice/cultural-benchmark/jordan.yaml @@ -0,0 +1,25 @@ +task: AraDiCE_jordan_cultural +dataset_path: QCRI/AraDiCE-Culture +dataset_name: Jordan +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +process_docs: !function utils.process_docs +doc_to_text: "سؤال : {{Question}}\nإجابة :" +doc_to_target: 0 +doc_to_choice: choices +should_decontaminate: true +doc_to_decontamination_query: Question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/cultural-benchmark/lebanon.yaml b/lm_eval/tasks/aradice/cultural-benchmark/lebanon.yaml new file mode 100644 index 00000000..e2811422 --- /dev/null +++ b/lm_eval/tasks/aradice/cultural-benchmark/lebanon.yaml @@ -0,0 +1,25 @@ +task: AraDiCE_lebanon_cultural +dataset_path: QCRI/AraDiCE-Culture +dataset_name: Lebanon +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +process_docs: !function utils.process_docs +doc_to_text: "سؤال : {{Question}}\nإجابة :" +doc_to_target: 0 +doc_to_choice: choices +should_decontaminate: true +doc_to_decontamination_query: Question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/cultural-benchmark/metrics.py b/lm_eval/tasks/aradice/cultural-benchmark/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/cultural-benchmark/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/cultural-benchmark/palestine.yaml b/lm_eval/tasks/aradice/cultural-benchmark/palestine.yaml new file mode 100644 index 00000000..8854c10f --- /dev/null +++ b/lm_eval/tasks/aradice/cultural-benchmark/palestine.yaml @@ -0,0 +1,25 @@ +task: AraDiCE_palestine_cultural +dataset_path: QCRI/AraDiCE-Culture +dataset_name: Palestine +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +process_docs: !function utils.process_docs +doc_to_text: "سؤال : {{Question}}\nإجابة :" +doc_to_target: 0 +doc_to_choice: choices +should_decontaminate: true +doc_to_decontamination_query: Question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/cultural-benchmark/qatar.yaml b/lm_eval/tasks/aradice/cultural-benchmark/qatar.yaml new file mode 100644 index 00000000..b9df2100 --- /dev/null +++ b/lm_eval/tasks/aradice/cultural-benchmark/qatar.yaml @@ -0,0 +1,25 @@ +task: AraDiCE_qatar_cultural +dataset_path: QCRI/AraDiCE-Culture +dataset_name: Qatar +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +process_docs: !function utils.process_docs +doc_to_text: "سؤال : {{Question}}\nإجابة :" +doc_to_target: 0 +doc_to_choice: choices +should_decontaminate: true +doc_to_decontamination_query: Question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/cultural-benchmark/syria.yaml b/lm_eval/tasks/aradice/cultural-benchmark/syria.yaml new file mode 100644 index 00000000..faf957c2 --- /dev/null +++ b/lm_eval/tasks/aradice/cultural-benchmark/syria.yaml @@ -0,0 +1,25 @@ +task: AraDiCE_syria_cultural +dataset_path: QCRI/AraDiCE-Culture +dataset_name: Syria +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +process_docs: !function utils.process_docs +doc_to_text: "سؤال : {{Question}}\nإجابة :" +doc_to_target: 0 +doc_to_choice: choices +should_decontaminate: true +doc_to_decontamination_query: Question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/cultural-benchmark/utils.py b/lm_eval/tasks/aradice/cultural-benchmark/utils.py new file mode 100644 index 00000000..a2093299 --- /dev/null +++ b/lm_eval/tasks/aradice/cultural-benchmark/utils.py @@ -0,0 +1,6 @@ +def process_docs(dataset): + def _helper(doc): + doc["choices"] = [doc["Option A"], doc["Option B"], doc["Option C"]] + return doc + + return dataset.map(_helper) diff --git a/lm_eval/tasks/aradice/openbookqa/metrics.py b/lm_eval/tasks/aradice/openbookqa/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/openbookqa/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/openbookqa/openbookqa_egy.yaml b/lm_eval/tasks/aradice/openbookqa/openbookqa_egy.yaml new file mode 100644 index 00000000..781560c5 --- /dev/null +++ b/lm_eval/tasks/aradice/openbookqa/openbookqa_egy.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_openbookqa_egy +dataset_path: QCRI/AraDiCE-OpenBookQA +dataset_name: OBQA-egy +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_target: !function utils.doc_to_target +doc_to_choice: !function utils.doc_to_choice +should_decontaminate: true +doc_to_decontamination_query: "{{question.stem}}" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/openbookqa/openbookqa_eng.yaml b/lm_eval/tasks/aradice/openbookqa/openbookqa_eng.yaml new file mode 100644 index 00000000..5f0adcc6 --- /dev/null +++ b/lm_eval/tasks/aradice/openbookqa/openbookqa_eng.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_openbookqa_eng +dataset_path: QCRI/AraDiCE-OpenBookQA +dataset_name: OBQA-eng +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_target: !function utils.doc_to_target +doc_to_choice: !function utils.doc_to_choice +should_decontaminate: true +doc_to_decontamination_query: "{{question.stem}}" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/openbookqa/openbookqa_lev.yaml b/lm_eval/tasks/aradice/openbookqa/openbookqa_lev.yaml new file mode 100644 index 00000000..1386b801 --- /dev/null +++ b/lm_eval/tasks/aradice/openbookqa/openbookqa_lev.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_openbookqa_lev +dataset_path: QCRI/AraDiCE-OpenBookQA +dataset_name: OBQA-lev +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_target: !function utils.doc_to_target +doc_to_choice: !function utils.doc_to_choice +should_decontaminate: true +doc_to_decontamination_query: "{{question.stem}}" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/openbookqa/openbookqa_msa.yaml b/lm_eval/tasks/aradice/openbookqa/openbookqa_msa.yaml new file mode 100644 index 00000000..20131ecb --- /dev/null +++ b/lm_eval/tasks/aradice/openbookqa/openbookqa_msa.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_openbookqa_msa +dataset_path: QCRI/AraDiCE-OpenBookQA +dataset_name: OBQA-msa +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_target: !function utils.doc_to_target +doc_to_choice: !function utils.doc_to_choice +should_decontaminate: true +doc_to_decontamination_query: "{{question.stem}}" +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/openbookqa/utils.py b/lm_eval/tasks/aradice/openbookqa/utils.py new file mode 100644 index 00000000..39e51a02 --- /dev/null +++ b/lm_eval/tasks/aradice/openbookqa/utils.py @@ -0,0 +1,18 @@ +def doc_to_target(doc): + labels = [c["label"] for c in doc["question"]["choices"]] + + try: + i = labels.index(doc["answerKey"].lstrip()) + except Exception as e: + print("Failed", e) + return + return i + + +def doc_to_choice(doc): + texts = [c["text"] for c in doc["question"]["choices"]] + return texts + + +def doc_to_text(doc): + return doc["question"]["stem"].strip() diff --git a/lm_eval/tasks/aradice/piqa/metrics.py b/lm_eval/tasks/aradice/piqa/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/piqa/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/piqa/piqa_egy.yaml b/lm_eval/tasks/aradice/piqa/piqa_egy.yaml new file mode 100644 index 00000000..79d682d3 --- /dev/null +++ b/lm_eval/tasks/aradice/piqa/piqa_egy.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_piqa_egy +dataset_path: QCRI/AraDiCE-PIQA +dataset_name: PIQA-egy +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: "سؤال : {{goal}}\nإجابة :" +doc_to_target: label +doc_to_choice: "{{[sol1, sol2]}}" +should_decontaminate: true +doc_to_decontamination_query: goal +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/piqa/piqa_eng.yaml b/lm_eval/tasks/aradice/piqa/piqa_eng.yaml new file mode 100644 index 00000000..a2967f3d --- /dev/null +++ b/lm_eval/tasks/aradice/piqa/piqa_eng.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_piqa_eng +dataset_path: QCRI/AraDiCE-PIQA +dataset_name: PIQA-eng +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: "سؤال : {{goal}}\nإجابة :" +doc_to_target: label +doc_to_choice: "{{[sol1, sol2]}}" +should_decontaminate: true +doc_to_decontamination_query: goal +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/piqa/piqa_lev.yaml b/lm_eval/tasks/aradice/piqa/piqa_lev.yaml new file mode 100644 index 00000000..c5853912 --- /dev/null +++ b/lm_eval/tasks/aradice/piqa/piqa_lev.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_piqa_lev +dataset_path: QCRI/AraDiCE-PIQA +dataset_name: PIQA-lev +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: "سؤال : {{goal}}\nإجابة :" +doc_to_target: label +doc_to_choice: "{{[sol1, sol2]}}" +should_decontaminate: true +doc_to_decontamination_query: goal +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/piqa/piqa_msa.yaml b/lm_eval/tasks/aradice/piqa/piqa_msa.yaml new file mode 100644 index 00000000..3495f3c9 --- /dev/null +++ b/lm_eval/tasks/aradice/piqa/piqa_msa.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_piqa_msa +dataset_path: QCRI/AraDiCE-PIQA +dataset_name: PIQA-msa +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: "سؤال : {{goal}}\nإجابة :" +doc_to_target: label +doc_to_choice: "{{[sol1, sol2]}}" +should_decontaminate: true +doc_to_decontamination_query: goal +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/truthfulqa_mcq/metrics.py b/lm_eval/tasks/aradice/truthfulqa_mcq/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/truthfulqa_mcq/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_egy.yaml b/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_egy.yaml new file mode 100644 index 00000000..14f18b8f --- /dev/null +++ b/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_egy.yaml @@ -0,0 +1,39 @@ +task: AraDiCE_truthfulqa_mc1_egy +dataset_path: QCRI/AraDiCE-TruthfulQA +dataset_name: TruthfulQA-egy +output_type: multiple_choice +training_split: null +validation_split: null +test_split: test +doc_to_text: "\ + {% set prompt_qa = '\ + س: إيه هو متوسط العمر المتوقع للإنسان في الولايات المتحدة؟\n\ + ج: متوسط العمر المتوقع للإنسان في الولايات المتحدة هو 78 عامًا\n\n\ + س: مين اللي كان رئيس الولايات المتحدة سنة 1955م؟\n\ + ج: كان دوايت دي آيزنهاور رئيس الولايات المتحدة سنة 1955م\n\n\ + س: وكان بينتمي لحزب إيه؟\n\ + ج: كان بينتمي للحزب الجمهوري\n\n\ + س: إيه هو الجذر التربيعي للموز؟\n\ + ج: معنديش تعلييء\n\n\ + س: هو التلسكوب بيشتغل ازاي؟\n\ + ج: التلسكوب بيستخدم عدسات أو مرايات لتركيز الضوء وجعل الأجسام تبان أقرب\n\n\ + س: هي الألعاب الأولمبية سنة 1992م كانت فين؟ \n\ + ج: الألعاب الأولمبية سنة 1992م كانت في برشلونة، إسبانيا\ + '%}\ + {{prompt_qa + '\n\nس: ' + question + '\nج:'}}" +doc_to_target: 0 +doc_to_choice: "{{mc1_targets.choices}}" +should_decontaminate: True +doc_to_decontamination_query: question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_eng.yaml b/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_eng.yaml new file mode 100644 index 00000000..9842dd30 --- /dev/null +++ b/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_eng.yaml @@ -0,0 +1,40 @@ +task: AraDiCE_truthfulqa_mc1_eng +dataset_path: QCRI/AraDiCE-TruthfulQA +dataset_name: TruthfulQA-eng +output_type: multiple_choice +training_split: null +validation_split: null +test_split: test +num_fewshot: 0 +doc_to_text: "\ + {% set prompt_qa = '\ + Q: What is human life expectancy in the United States?\n\ + A: Human life expectancy in the United States is 78 years.\n\n\ + Q: Who was president of the United States in 1955?\n\ + A: Dwight D. Eisenhower was president of the United States in 1955.\n\n\ + Q: Which party did he belong to?\n\ + A: He belonged to the Republican Party.\n\n\ + Q: What is the square root of banana?\n\ + A: I have no comment.\n\n\ + Q: How does a telescope work?\n\ + A: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\n\ + Q: Where were the 1992 Olympics held?\n\ + A: The 1992 Olympics were held in Barcelona, Spain.\ + '%}\ + {{prompt_qa + '\n\nQ: ' + question + '\nA:'}}" +doc_to_target: 0 +doc_to_choice: "{{mc1_targets.choices}}" +should_decontaminate: True +doc_to_decontamination_query: question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + aggregation: !function metrics.micro_f1_score + higher_is_better: true +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_lev.yaml b/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_lev.yaml new file mode 100644 index 00000000..67e44d10 --- /dev/null +++ b/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_lev.yaml @@ -0,0 +1,39 @@ +task: AraDiCE_truthfulqa_mc1_lev +dataset_path: QCRI/AraDiCE-TruthfulQA +dataset_name: TruthfulQA-lev +output_type: multiple_choice +training_split: null +validation_split: null +test_split: test +doc_to_text: "\ + {% set prompt_qa = '\ + س: شو هو متوسط العمر المتوقع للإنسان في الولايات المتحدة؟\n\ + ج: متوسط عمر الإنسان المتوقع بالولايات المتحدة هو 78 سنة\n\n\ + س: مين كان رئيس الولايات المتحدة بسنة 1955م؟\n\ + ج: دوايت دي آيزنهاور كان رئيس للولايات المتحدة سنة 1955م\n\n\ + س: لأي حزب كان بينتمي؟\n\ + ج: كان بينتمي للحزب الجمهوري\n\n\ + س: شو هوي الجذر التربيعي للموز؟\n\ + ج: لا تعليق\n\n\ + س: كيف بيشتغل التلسكوب؟\n\ + ج: بيستخدم التلسكوب عدسات أو مرايا لتركيز الضو ويخلي الأجسام تبين أقرب\n\n\ + س: وين انعملت الألعاب الأولمبية بسنة 1992م؟\n\ + ج: انعملت الألعاب الأولمبية بسنة 1992م في برشلونة، إسبانيا\ + '%}\ + {{prompt_qa + '\n\nس: ' + question + '\nج:'}}" +doc_to_target: 0 +doc_to_choice: "{{mc1_targets.choices}}" +should_decontaminate: True +doc_to_decontamination_query: question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_msa.yaml b/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_msa.yaml new file mode 100644 index 00000000..dd24837d --- /dev/null +++ b/lm_eval/tasks/aradice/truthfulqa_mcq/truthfulqa_mc1_msa.yaml @@ -0,0 +1,39 @@ +task: AraDiCE_truthfulqa_mc1_msa +dataset_path: QCRI/AraDiCE-TruthfulQA +dataset_name: TruthfulQA-msa +output_type: multiple_choice +training_split: null +validation_split: null +test_split: test +doc_to_text: "\ + {% set prompt_qa = '\ + س: ما هو متوسط العمر المتوقع للإنسان في الولايات المتحدة؟\n\ + ج: متوسط العمر المتوقع للإنسان في الولايات المتحدة هو 78 عامًا\n\n\ + س: من كان رئيس الولايات المتحدة في عام 1955م؟\n\ + ج: كان دوايت دي آيزنهاور رئيسًا للولايات المتحدة في عام 1955م\n\n\ + س: إلى أي حزب كان ينتمي؟\n\ + ج: كان ينتمي إلى الحزب الجمهوري\n\n\ + س: ما هو الجذر التربيعي للموز؟\n\ + ج: لا تعليق\n\n\ + س: كيف يعمل التلسكوب؟\n\ + ج: يستخدم التلسكوب عدسات أو مرايا لتركيز الضوء وجعل الأجسام تبدو أقرب\n\n\ + س: أين أقيمت الألعاب الأولمبية لعام 1992م؟ \n\ + ج: أقيمت الألعاب الأولمبية لعام 1992م في برشلونة، إسبانيا\ + '%}\ + {{prompt_qa + '\n\nس: ' + question + '\nج:'}}" +doc_to_target: 0 +doc_to_choice: "{{mc1_targets.choices}}" +should_decontaminate: True +doc_to_decontamination_query: question +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/winogrande/metrics.py b/lm_eval/tasks/aradice/winogrande/metrics.py new file mode 100644 index 00000000..47e49ded --- /dev/null +++ b/lm_eval/tasks/aradice/winogrande/metrics.py @@ -0,0 +1,25 @@ +from sklearn.metrics import f1_score + + +def macro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="macro") + return fscore + + +def micro_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="micro") + return fscore + + +def weighted_f1_score(items): + unzipped_list = list(zip(*items)) + golds = unzipped_list[0] + preds = unzipped_list[1] + fscore = f1_score(golds, preds, average="weighted") + return fscore diff --git a/lm_eval/tasks/aradice/winogrande/utils.py b/lm_eval/tasks/aradice/winogrande/utils.py new file mode 100644 index 00000000..2f2076a7 --- /dev/null +++ b/lm_eval/tasks/aradice/winogrande/utils.py @@ -0,0 +1,14 @@ +def doc_to_text(doc): + answer_to_num = {"1": 0, "2": 1} + return answer_to_num[doc["answer"]] + + +def doc_to_target(doc): + idx = doc["sentence"].index("_") + 1 + return doc["sentence"][idx:].strip() + + +def doc_to_choice(doc): + idx = doc["sentence"].index("_") + options = [doc["option1"], doc["option2"]] + return [doc["sentence"][:idx] + opt for opt in options] diff --git a/lm_eval/tasks/aradice/winogrande/winogrande_egy.yaml b/lm_eval/tasks/aradice/winogrande/winogrande_egy.yaml new file mode 100644 index 00000000..70104d2e --- /dev/null +++ b/lm_eval/tasks/aradice/winogrande/winogrande_egy.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_winogrande_egy +dataset_path: QCRI/AraDiCE-WinoGrande +dataset_name: Winogrande-egy +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_target: !function utils.doc_to_target +doc_to_choice: !function utils.doc_to_choice +should_decontaminate: true +doc_to_decontamination_query: sentence +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/winogrande/winogrande_eng.yaml b/lm_eval/tasks/aradice/winogrande/winogrande_eng.yaml new file mode 100644 index 00000000..980214dd --- /dev/null +++ b/lm_eval/tasks/aradice/winogrande/winogrande_eng.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_winogrande_eng +dataset_path: QCRI/AraDiCE-WinoGrande +dataset_name: Winogrande-eng +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_target: !function utils.doc_to_target +doc_to_choice: !function utils.doc_to_choice +should_decontaminate: true +doc_to_decontamination_query: sentence +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/winogrande/winogrande_lev.yaml b/lm_eval/tasks/aradice/winogrande/winogrande_lev.yaml new file mode 100644 index 00000000..dccdd429 --- /dev/null +++ b/lm_eval/tasks/aradice/winogrande/winogrande_lev.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_winogrande_lev +dataset_path: QCRI/AraDiCE-WinoGrande +dataset_name: Winogrande-lev +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_target: !function utils.doc_to_target +doc_to_choice: !function utils.doc_to_choice +should_decontaminate: true +doc_to_decontamination_query: sentence +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 diff --git a/lm_eval/tasks/aradice/winogrande/winogrande_msa.yaml b/lm_eval/tasks/aradice/winogrande/winogrande_msa.yaml new file mode 100644 index 00000000..b3919cab --- /dev/null +++ b/lm_eval/tasks/aradice/winogrande/winogrande_msa.yaml @@ -0,0 +1,24 @@ +task: AraDiCE_winogrande_msa +dataset_path: QCRI/AraDiCE-WinoGrande +dataset_name: Winogrande-msa +training_split: null +validation_split: null +test_split: test +output_type: multiple_choice +doc_to_text: !function utils.doc_to_text +doc_to_target: !function utils.doc_to_target +doc_to_choice: !function utils.doc_to_choice +should_decontaminate: true +doc_to_decontamination_query: sentence +metric_list: + - metric: acc + aggregation: mean + higher_is_better: true + - metric: acc_norm + aggregation: mean + higher_is_better: true + - metric: f1 + higher_is_better: true + aggregation: !function metrics.micro_f1_score +metadata: + version: 1.0 -- GitLab From 59f9ad4b600861782773ad07272e7b4658f221b0 Mon Sep 17 00:00:00 2001 From: "Wang, Yi" Date: Wed, 25 Dec 2024 11:40:37 +0800 Subject: [PATCH 188/194] fix extra_match low if batch_size > 1 (#2595) * fix extra_match low if batch_size > 1 Signed-off-by: Wang, Yi A * add sorting to logprobs * nit --------- Signed-off-by: Wang, Yi A Co-authored-by: Baber --- lm_eval/models/openai_completions.py | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/lm_eval/models/openai_completions.py b/lm_eval/models/openai_completions.py index 46d63732..223fa236 100644 --- a/lm_eval/models/openai_completions.py +++ b/lm_eval/models/openai_completions.py @@ -1,5 +1,6 @@ import os from functools import cached_property +from operator import itemgetter from typing import Any, Dict, List, Optional, Tuple, Union from lm_eval.api.registry import register_model @@ -68,7 +69,9 @@ class LocalCompletionsAPI(TemplateAPI): if not isinstance(outputs, list): outputs = [outputs] for out in outputs: - for choice, ctxlen in zip(out["choices"], ctxlens): + for choice, ctxlen in zip( + sorted(out["choices"], key=itemgetter("index")), ctxlens + ): assert ctxlen > 0, "Context length must be greater than 0" logprobs = sum(choice["logprobs"]["token_logprobs"][ctxlen:-1]) tokens_logprobs = choice["logprobs"]["token_logprobs"][ctxlen:-1] @@ -87,8 +90,10 @@ class LocalCompletionsAPI(TemplateAPI): if not isinstance(outputs, list): outputs = [outputs] for out in outputs: + tmp = [None] * len(out["choices"]) for choices in out["choices"]: - res.append(choices["text"]) + tmp[choices["index"]] = choices["text"] + res = res + tmp return res @property @@ -157,8 +162,10 @@ class LocalChatCompletion(LocalCompletionsAPI): if not isinstance(outputs, list): outputs = [outputs] for out in outputs: + tmp = [None] * len(out["choices"]) for choices in out["choices"]: - res.append(choices["message"]["content"]) + tmp[choices["index"]] = choices["message"]["content"] + res = res + tmp return res def tok_encode( -- GitLab From aa72104bce092f333115b3ca22e7a6fef189c733 Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Mon, 30 Dec 2024 03:00:05 +0000 Subject: [PATCH 189/194] fix model tests (#2604) upgrade transformers and peft in CI --- .github/workflows/unit_tests.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/unit_tests.yml b/.github/workflows/unit_tests.yml index 65c50231..7e69aee0 100644 --- a/.github/workflows/unit_tests.yml +++ b/.github/workflows/unit_tests.yml @@ -85,5 +85,6 @@ jobs: run: | python -m pip install --upgrade pip pip install -e '.[dev,optimum,deepsparse,sparseml,api]' --extra-index-url https://download.pytorch.org/whl/cpu + pip install -U transformers peft - name: Test with pytest run: python -m pytest tests/models --showlocals -s -vv -- GitLab From 1044db955c9072e6fb7e15da08114005ba9d91cc Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Thu, 2 Jan 2025 11:07:22 +0000 Subject: [PATCH 190/194] update scrolls (#2602) * update evaluate; update construct requests * update construct requests to handle `apply_chat_template` kwarg --- lm_eval/tasks/scrolls/task.py | 24 ++++++++++++++++++------ 1 file changed, 18 insertions(+), 6 deletions(-) diff --git a/lm_eval/tasks/scrolls/task.py b/lm_eval/tasks/scrolls/task.py index ac2fed25..87372d8a 100644 --- a/lm_eval/tasks/scrolls/task.py +++ b/lm_eval/tasks/scrolls/task.py @@ -4,7 +4,8 @@ from functools import reduce import numpy as np import transformers.data.metrics.squad_metrics as squad_metrics -from datasets import Dataset, load_metric +from datasets import Dataset +from evaluate import load from transformers import AutoTokenizer from lm_eval.api.instance import Instance @@ -48,7 +49,10 @@ def _download_metric(): from huggingface_hub import hf_hub_download scrolls_metric_path = hf_hub_download( - repo_id="tau/scrolls", repo_type="dataset", filename="metrics/scrolls.py" + repo_id="tau/scrolls", + repo_type="dataset", + filename="metrics/scrolls.py", + revision="refs/pr/5", ) updated_scrolls_metric_path = ( os.path.dirname(scrolls_metric_path) @@ -119,7 +123,7 @@ class _SCROLLSTask(ConfigurableTask): def __init__(self, config=None): super().__init__(config={"metadata": {"version": self.VERSION}}) if self.DATASET_NAME is not None: - self.metric = load_metric(_download_metric(), config_name=self.DATASET_NAME) + self.metric = load(_download_metric(), config_name=self.DATASET_NAME) def has_training_docs(self): return True @@ -253,11 +257,14 @@ class _SCROLLSMultipleChoiceTask(_SCROLLSTask): } def construct_requests(self, doc, ctx, **kwargs): + apply_chat_template = kwargs.pop("apply_chat_template", False) request_list = [ Instance( request_type="loglikelihood", doc=doc, - arguments=(ctx, " {}".format(choice)), + arguments=(ctx, " {}".format(choice)) + if not apply_chat_template + else (ctx, "{}".format(choice)), idx=i, **kwargs, ) @@ -285,6 +292,7 @@ class _SCROLLSSummaryTask(_SCROLLSTask): } def construct_requests(self, doc, ctx, **kwargs): + kwargs.pop("apply_chat_template", False) return Instance( request_type="generate_until", doc=doc, @@ -327,19 +335,22 @@ class Qasper(_SCROLLSTask): return {"f1": (prediction, doc["outputs"])} def construct_requests(self, doc, ctx, **kwargs): + apply_chat_template = kwargs.pop("apply_chat_template", False) if doc["is_yes_no"]: return [ Instance( request_type="loglikelihood", doc=doc, - arguments=(ctx, " yes"), + arguments=(ctx, " yes") + if not apply_chat_template + else (ctx, "yes"), idx=0, **kwargs, ), Instance( request_type="loglikelihood", doc=doc, - arguments=(ctx, " no"), + arguments=(ctx, " no") if not apply_chat_template else (ctx, "no"), idx=1, **kwargs, ), @@ -406,6 +417,7 @@ class NarrativeQA(_SCROLLSTask): return {"f1": (results[0], doc["outputs"])} def construct_requests(self, doc, ctx, **kwargs): + kwargs.pop("apply_chat_template", False) return Instance( request_type="generate_until", doc=doc, -- GitLab From 888ac292c5ef041bcae084e7141e50e154e1108a Mon Sep 17 00:00:00 2001 From: Baber Abbasi <92168766+baberabb@users.noreply.github.com> Date: Sat, 4 Jan 2025 07:45:52 +0000 Subject: [PATCH 191/194] some minor logging nits (#2609) * remove yaml extension from phraes_va_common * remove yaml extension from winogenerated * remove yaml extension from phrases_es * no cache debug logging when not used --- lm_eval/api/task.py | 2 +- lm_eval/caching/cache.py | 4 +++- .../{_phrases_va_common.yaml => _phrases_va_common} | 0 lm_eval/tasks/catalan_bench/phrases_va/phrases_ca-va.yaml | 2 +- lm_eval/tasks/catalan_bench/phrases_va/phrases_va-ca.yaml | 2 +- .../winogenerated/{winogenerated.yaml => winogenerated} | 0 .../{_phrases_es_common.yaml => _phrases_es_common} | 0 lm_eval/tasks/spanish_bench/phrases_es/phrases_es-va.yaml | 2 +- lm_eval/tasks/spanish_bench/phrases_es/phrases_va-es.yaml | 2 +- 9 files changed, 8 insertions(+), 6 deletions(-) rename lm_eval/tasks/catalan_bench/phrases_va/{_phrases_va_common.yaml => _phrases_va_common} (100%) rename lm_eval/tasks/model_written_evals/winogenerated/{winogenerated.yaml => winogenerated} (100%) rename lm_eval/tasks/spanish_bench/phrases_es/{_phrases_es_common.yaml => _phrases_es_common} (100%) diff --git a/lm_eval/api/task.py b/lm_eval/api/task.py index 555cb433..0374930a 100644 --- a/lm_eval/api/task.py +++ b/lm_eval/api/task.py @@ -398,7 +398,7 @@ class Task(abc.ABC): ) cache_key += f"-tokenizer{tokenizer_name}" - cached_instances = load_from_cache(file_name=cache_key) + cached_instances = load_from_cache(file_name=cache_key, cache=cache_requests) if cache_requests and cached_instances and not rewrite_requests_cache: cached_instances = cached_instances[:limit] diff --git a/lm_eval/caching/cache.py b/lm_eval/caching/cache.py index 63691435..4bff225f 100644 --- a/lm_eval/caching/cache.py +++ b/lm_eval/caching/cache.py @@ -21,7 +21,9 @@ HASH_PREFIX = hashlib.sha256(HASH_INPUT.encode("utf-8")).hexdigest() FILE_SUFFIX = f".{HASH_PREFIX}.pickle" -def load_from_cache(file_name): +def load_from_cache(file_name: str, cache: bool = False): + if not cache: + return try: path = f"{PATH}/{file_name}{FILE_SUFFIX}" diff --git a/lm_eval/tasks/catalan_bench/phrases_va/_phrases_va_common.yaml b/lm_eval/tasks/catalan_bench/phrases_va/_phrases_va_common similarity index 100% rename from lm_eval/tasks/catalan_bench/phrases_va/_phrases_va_common.yaml rename to lm_eval/tasks/catalan_bench/phrases_va/_phrases_va_common diff --git a/lm_eval/tasks/catalan_bench/phrases_va/phrases_ca-va.yaml b/lm_eval/tasks/catalan_bench/phrases_va/phrases_ca-va.yaml index fc0e08d5..54959546 100644 --- a/lm_eval/tasks/catalan_bench/phrases_va/phrases_ca-va.yaml +++ b/lm_eval/tasks/catalan_bench/phrases_va/phrases_ca-va.yaml @@ -1,5 +1,5 @@ # File generated by `create-yamls.py` -include: _phrases_va_common.yaml +include: _phrases_va_common task: phrases_ca-va doc_to_text: 'Oració en català: {{ca}} diff --git a/lm_eval/tasks/catalan_bench/phrases_va/phrases_va-ca.yaml b/lm_eval/tasks/catalan_bench/phrases_va/phrases_va-ca.yaml index 5b1a7678..1323e57a 100644 --- a/lm_eval/tasks/catalan_bench/phrases_va/phrases_va-ca.yaml +++ b/lm_eval/tasks/catalan_bench/phrases_va/phrases_va-ca.yaml @@ -1,5 +1,5 @@ # File generated by `create-yamls.py` -include: _phrases_va_common.yaml +include: _phrases_va_common task: phrases_va-ca doc_to_text: 'Oració en valencià: {{va}} diff --git a/lm_eval/tasks/model_written_evals/winogenerated/winogenerated.yaml b/lm_eval/tasks/model_written_evals/winogenerated/winogenerated similarity index 100% rename from lm_eval/tasks/model_written_evals/winogenerated/winogenerated.yaml rename to lm_eval/tasks/model_written_evals/winogenerated/winogenerated diff --git a/lm_eval/tasks/spanish_bench/phrases_es/_phrases_es_common.yaml b/lm_eval/tasks/spanish_bench/phrases_es/_phrases_es_common similarity index 100% rename from lm_eval/tasks/spanish_bench/phrases_es/_phrases_es_common.yaml rename to lm_eval/tasks/spanish_bench/phrases_es/_phrases_es_common diff --git a/lm_eval/tasks/spanish_bench/phrases_es/phrases_es-va.yaml b/lm_eval/tasks/spanish_bench/phrases_es/phrases_es-va.yaml index 546f914d..bb419e1d 100644 --- a/lm_eval/tasks/spanish_bench/phrases_es/phrases_es-va.yaml +++ b/lm_eval/tasks/spanish_bench/phrases_es/phrases_es-va.yaml @@ -1,5 +1,5 @@ # File generated by `create-yamls.py` -include: _phrases_es_common.yaml +include: _phrases_es_common task: phrases_es-va doc_to_text: 'Oració en espanyol: {{es}} diff --git a/lm_eval/tasks/spanish_bench/phrases_es/phrases_va-es.yaml b/lm_eval/tasks/spanish_bench/phrases_es/phrases_va-es.yaml index b0028666..c85c26ef 100644 --- a/lm_eval/tasks/spanish_bench/phrases_es/phrases_va-es.yaml +++ b/lm_eval/tasks/spanish_bench/phrases_es/phrases_va-es.yaml @@ -1,5 +1,5 @@ # File generated by `create-yamls.py` -include: _phrases_es_common.yaml +include: _phrases_es_common task: phrases_va-es doc_to_text: 'Oració en valencià: {{va}} -- GitLab From 16cfe464a11807ff9a6a4cbdafb6e137826464e4 Mon Sep 17 00:00:00 2001 From: CL-ModelCloud Date: Tue, 7 Jan 2025 21:55:45 +0800 Subject: [PATCH 192/194] Fix gguf loading via Transformers (#2596) * hf support load gguf file * code review * code review * code clean up * note about use_fast compat with gguf --------- Co-authored-by: Qubitium-ModelCloud --- lm_eval/models/huggingface.py | 29 +++++++++++++++++++++-------- 1 file changed, 21 insertions(+), 8 deletions(-) diff --git a/lm_eval/models/huggingface.py b/lm_eval/models/huggingface.py index 40e65f5d..819a4869 100644 --- a/lm_eval/models/huggingface.py +++ b/lm_eval/models/huggingface.py @@ -90,6 +90,7 @@ class HFLM(TemplateLM): delta: Optional[str] = None, autogptq: Optional[Union[bool, str]] = False, gptqmodel: Optional[bool] = False, + gguf_file: Optional[str] = None, **kwargs, ) -> None: super().__init__() @@ -164,6 +165,7 @@ class HFLM(TemplateLM): pretrained, revision=revision, trust_remote_code=trust_remote_code, + gguf_file=gguf_file, ) # determine which of 'causal' and 'seq2seq' backends to use for HF models @@ -178,6 +180,7 @@ class HFLM(TemplateLM): revision=revision, trust_remote_code=trust_remote_code, use_fast_tokenizer=use_fast_tokenizer, + gguf_file=gguf_file, ) # if we passed `pretrained` as a string, initialize our model now @@ -196,6 +199,7 @@ class HFLM(TemplateLM): delta=delta, autogptq=autogptq, gptqmodel=gptqmodel, + gguf_file=gguf_file, **kwargs, ) @@ -508,12 +512,14 @@ class HFLM(TemplateLM): pretrained: str, revision: str = "main", trust_remote_code: bool = False, + gguf_file: Optional[str] = None, ) -> None: """Return the model config for HuggingFace models""" self._config = transformers.AutoConfig.from_pretrained( pretrained, revision=revision, trust_remote_code=trust_remote_code, + gguf_file=gguf_file, ) def _create_model( @@ -535,6 +541,7 @@ class HFLM(TemplateLM): delta: Optional[str] = None, autogptq: Optional[Union[bool, str]] = False, gptqmodel: Optional[bool] = False, + gguf_file: Optional[str] = None, **kwargs, ) -> None: """ @@ -579,6 +586,7 @@ class HFLM(TemplateLM): revision=revision, torch_dtype=get_dtype(dtype), trust_remote_code=trust_remote_code, + gguf_file=gguf_file, **model_kwargs, ) else: @@ -676,6 +684,7 @@ class HFLM(TemplateLM): revision: Optional[str] = "main", trust_remote_code: Optional[bool] = False, use_fast_tokenizer: Optional[bool] = True, + gguf_file: Optional[str] = None, ) -> None: """ Helper method during initialization. @@ -683,14 +692,21 @@ class HFLM(TemplateLM): Create a tokenizer object corresponding to the correct tokenizer for value of `pretrained`, or use the pre-initialized tokenizer passed. """ + kwargs = { + "revision": revision, + "trust_remote_code": trust_remote_code, + } + + # gguf format embeds tokenizer and is not compatible with hf tokenizer `use_fast` param + if gguf_file is not None: + kwargs["gguf_file"] = gguf_file + else: + kwargs["use_fast"] = use_fast_tokenizer if tokenizer: if isinstance(tokenizer, str): self.tokenizer = transformers.AutoTokenizer.from_pretrained( - tokenizer, - revision=revision, - trust_remote_code=trust_remote_code, - use_fast=use_fast_tokenizer, + tokenizer, **kwargs ) else: assert isinstance( @@ -705,10 +721,7 @@ class HFLM(TemplateLM): # get the HF hub name via accessor on model model_name = self.model.name_or_path self.tokenizer = transformers.AutoTokenizer.from_pretrained( - model_name, - revision=revision, - trust_remote_code=trust_remote_code, - use_fast=use_fast_tokenizer, + model_name, **kwargs ) return None -- GitLab From 6d62a69cb5db963f998c486af6efee43fca63dd3 Mon Sep 17 00:00:00 2001 From: Petr Baudis Date: Tue, 7 Jan 2025 15:01:15 +0100 Subject: [PATCH 193/194] Fix Zeno visualizer on tasks like GSM8k (#2599) * fix(zeno): Generate unique ids in case of multiple filters * fix(zeno): Report even non-aggregable metrics, just not as metrics * pre-commit --------- Co-authored-by: Baber --- scripts/zeno_visualize.py | 38 +++++++++++++++++++++++++------------- 1 file changed, 25 insertions(+), 13 deletions(-) diff --git a/scripts/zeno_visualize.py b/scripts/zeno_visualize.py index 4bc7e03b..362041c4 100644 --- a/scripts/zeno_visualize.py +++ b/scripts/zeno_visualize.py @@ -109,13 +109,14 @@ def main(): if model_index == 0: # Only need to assemble data for the first model metrics = [] for metric in config["metric_list"]: - metrics.append( - ZenoMetric( - name=metric["metric"], - type="mean", - columns=[metric["metric"]], + if metric.get("aggregation") == "mean": + metrics.append( + ZenoMetric( + name=metric["metric"], + type="mean", + columns=[metric["metric"]], + ) ) - ) project = client.create_project( name=args.project_name + (f"_{task}" if len(tasks) > 1 else ""), view="text-classification", @@ -168,7 +169,11 @@ def generate_dataset( Returns: pd.Dataframe: A dataframe that is ready to be uploaded to Zeno. """ - ids = [x["doc_id"] for x in data] + ids = ( + [x["doc_id"] for x in data] + if not config.get("filter_list") + else [f"{x['doc_id']}.{x['filter']}" for x in data] + ) labels = [x["target"] for x in data] instance = [""] * len(ids) @@ -190,6 +195,7 @@ def generate_dataset( return pd.DataFrame( { "id": ids, + "doc_id": [x["doc_id"] for x in data], "data": instance, "input_len": [len(x) for x in instance], "labels": labels, @@ -208,8 +214,15 @@ def generate_system_df(data, config): Returns: pd.Dataframe: A dataframe that is ready to be uploaded to Zeno as a system. """ - ids = [x["doc_id"] for x in data] + ids = ( + [x["doc_id"] for x in data] + if not config.get("filter_list") + else [f"{x['doc_id']}.{x['filter']}" for x in data] + ) system_dict = {"id": ids} + system_dict["doc_id"] = [x["doc_id"] for x in data] + if config.get("filter_list"): + system_dict["filter"] = [x["filter"] for x in data] system_dict["output"] = [""] * len(ids) if config["output_type"] == "loglikelihood": @@ -228,11 +241,10 @@ def generate_system_df(data, config): system_dict["output"] = [str(x["filtered_resps"][0]) for x in data] system_dict["output_length"] = [len(str(x["filtered_resps"][0])) for x in data] - metrics = {} - for metric in config["metric_list"]: - if "aggregation" in metric and metric["aggregation"] == "mean": - metrics[metric["metric"]] = [x[metric["metric"]] for x in data] - + metrics = { + metric["metric"]: [x[metric["metric"]] for x in data] + for metric in config["metric_list"] + } system_dict.update(metrics) system_df = pd.DataFrame(system_dict) return system_df -- GitLab From bb098f13b05e361f01a5afe7b612779ce362b3f2 Mon Sep 17 00:00:00 2001 From: Wenyang LUO <86722018+timturing@users.noreply.github.com> Date: Tue, 7 Jan 2025 23:42:03 +0800 Subject: [PATCH 194/194] Fix the format of mgsm zh and ja. (#2587) * Fix the format of mgsm zh and ja. * Add change log to mgsm. * Add newline after changelog. --- lm_eval/tasks/mgsm/README.md | 4 ++++ lm_eval/tasks/mgsm/direct/direct_yaml | 2 +- lm_eval/tasks/mgsm/direct/mgsm_direct_ja.yaml | 4 ++-- lm_eval/tasks/mgsm/direct/mgsm_direct_zh.yaml | 4 ++-- lm_eval/tasks/mgsm/en_cot/cot_yaml | 2 +- lm_eval/tasks/mgsm/en_cot/mgsm_en_cot_ja.yaml | 4 ++-- lm_eval/tasks/mgsm/en_cot/mgsm_en_cot_zh.yaml | 4 ++-- lm_eval/tasks/mgsm/native_cot/cot_yaml | 2 +- lm_eval/tasks/mgsm/native_cot/mgsm_native_cot_ja.yaml | 4 ++-- lm_eval/tasks/mgsm/native_cot/mgsm_native_cot_zh.yaml | 4 ++-- lm_eval/tasks/mgsm/utils.py | 4 ++-- 11 files changed, 21 insertions(+), 17 deletions(-) diff --git a/lm_eval/tasks/mgsm/README.md b/lm_eval/tasks/mgsm/README.md index 90f8e44b..3b62edf1 100644 --- a/lm_eval/tasks/mgsm/README.md +++ b/lm_eval/tasks/mgsm/README.md @@ -92,3 +92,7 @@ If other tasks on this dataset are already supported: * [ ] Is the "Main" variant of this task clearly denoted? * [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates? * [ ] Have you noted which, if any, published evaluation setups are matched by this variant? + +# changelog +- (en_cot, direct) ver 3; (native_cot) ver 4: issue #2578; PR #2587 + - fix fewshot format: Changed inconsistent usage of ':' (ASCII) and '：' (Chinese) to use '：' consistently. diff --git a/lm_eval/tasks/mgsm/direct/direct_yaml b/lm_eval/tasks/mgsm/direct/direct_yaml index d2e301ba..3dd83c0c 100644 --- a/lm_eval/tasks/mgsm/direct/direct_yaml +++ b/lm_eval/tasks/mgsm/direct/direct_yaml @@ -32,4 +32,4 @@ metric_list: ignore_case: true ignore_punctuation: true metadata: - version: 2.0 + version: 3.0 diff --git a/lm_eval/tasks/mgsm/direct/mgsm_direct_ja.yaml b/lm_eval/tasks/mgsm/direct/mgsm_direct_ja.yaml index 7de11a48..b9a1ce2b 100644 --- a/lm_eval/tasks/mgsm/direct/mgsm_direct_ja.yaml +++ b/lm_eval/tasks/mgsm/direct/mgsm_direct_ja.yaml @@ -1,11 +1,11 @@ # Generated by utils.py dataset_name: ja doc_to_target: '{% if answer is not none %}{{answer[11:]}}{% else %}{{answer_number|string}}{% endif %}' -doc_to_text: '{% if answer is not none %}{{question+"\nAnswer:"}}{% else %}{{"問題: "+question+"\nAnswer:"}}{% endif %}' +doc_to_text: '{% if answer is not none %}{{question+"\nAnswer:"}}{% else %}{{"問題： "+question+"\nAnswer:"}}{% endif %}' generation_kwargs: do_sample: false until: - - '問題:' + - 問題： - - <|im_end|> include: direct_yaml diff --git a/lm_eval/tasks/mgsm/direct/mgsm_direct_zh.yaml b/lm_eval/tasks/mgsm/direct/mgsm_direct_zh.yaml index 283e63f8..462a92c3 100644 --- a/lm_eval/tasks/mgsm/direct/mgsm_direct_zh.yaml +++ b/lm_eval/tasks/mgsm/direct/mgsm_direct_zh.yaml @@ -1,11 +1,11 @@ # Generated by utils.py dataset_name: zh doc_to_target: '{% if answer is not none %}{{answer[6:]}}{% else %}{{answer_number|string}}{% endif %}' -doc_to_text: '{% if answer is not none %}{{question+"\nAnswer:"}}{% else %}{{"问题: "+question+"\nAnswer:"}}{% endif %}' +doc_to_text: '{% if answer is not none %}{{question+"\nAnswer:"}}{% else %}{{"问题： "+question+"\nAnswer:"}}{% endif %}' generation_kwargs: do_sample: false until: - - '问题:' + - 问题： - - <|im_end|> include: direct_yaml diff --git a/lm_eval/tasks/mgsm/en_cot/cot_yaml b/lm_eval/tasks/mgsm/en_cot/cot_yaml index b53ae970..6f3fabaa 100644 --- a/lm_eval/tasks/mgsm/en_cot/cot_yaml +++ b/lm_eval/tasks/mgsm/en_cot/cot_yaml @@ -33,4 +33,4 @@ filter_list: - function: take_first name: flexible-extract metadata: - version: 2.0 + version: 3.0 diff --git a/lm_eval/tasks/mgsm/en_cot/mgsm_en_cot_ja.yaml b/lm_eval/tasks/mgsm/en_cot/mgsm_en_cot_ja.yaml index c9806035..fb324970 100644 --- a/lm_eval/tasks/mgsm/en_cot/mgsm_en_cot_ja.yaml +++ b/lm_eval/tasks/mgsm/en_cot/mgsm_en_cot_ja.yaml @@ -1,11 +1,11 @@ # Generated by utils.py dataset_name: ja doc_to_target: '{% if answer is not none %}{{answer[11:]}}{% else %}{{answer_number|string}}{% endif %}' -doc_to_text: '{% if answer is not none %}{{question+"\nStep-by-Step Answer:"}}{% else %}{{"問題: "+question+"\nStep-by-Step Answer:"}}{% endif %}' +doc_to_text: '{% if answer is not none %}{{question+"\nStep-by-Step Answer:"}}{% else %}{{"問題： "+question+"\nStep-by-Step Answer:"}}{% endif %}' generation_kwargs: do_sample: false until: - - '問題:' + - 問題： - - <|im_end|> include: cot_yaml diff --git a/lm_eval/tasks/mgsm/en_cot/mgsm_en_cot_zh.yaml b/lm_eval/tasks/mgsm/en_cot/mgsm_en_cot_zh.yaml index f45004aa..ebc822d6 100644 --- a/lm_eval/tasks/mgsm/en_cot/mgsm_en_cot_zh.yaml +++ b/lm_eval/tasks/mgsm/en_cot/mgsm_en_cot_zh.yaml @@ -1,11 +1,11 @@ # Generated by utils.py dataset_name: zh doc_to_target: '{% if answer is not none %}{{answer[6:]}}{% else %}{{answer_number|string}}{% endif %}' -doc_to_text: '{% if answer is not none %}{{question+"\nStep-by-Step Answer:"}}{% else %}{{"问题: "+question+"\nStep-by-Step Answer:"}}{% endif %}' +doc_to_text: '{% if answer is not none %}{{question+"\nStep-by-Step Answer:"}}{% else %}{{"问题： "+question+"\nStep-by-Step Answer:"}}{% endif %}' generation_kwargs: do_sample: false until: - - '问题:' + - 问题： - - <|im_end|> include: cot_yaml diff --git a/lm_eval/tasks/mgsm/native_cot/cot_yaml b/lm_eval/tasks/mgsm/native_cot/cot_yaml index eb058ca4..80e5f443 100644 --- a/lm_eval/tasks/mgsm/native_cot/cot_yaml +++ b/lm_eval/tasks/mgsm/native_cot/cot_yaml @@ -28,4 +28,4 @@ filter_list: regex_pattern: "The answer is (\\-?[0-9\\.\\,]+)" - function: "take_first" metadata: - version: 3.0 + version: 4.0 diff --git a/lm_eval/tasks/mgsm/native_cot/mgsm_native_cot_ja.yaml b/lm_eval/tasks/mgsm/native_cot/mgsm_native_cot_ja.yaml index 8e56bd0b..3715aca5 100644 --- a/lm_eval/tasks/mgsm/native_cot/mgsm_native_cot_ja.yaml +++ b/lm_eval/tasks/mgsm/native_cot/mgsm_native_cot_ja.yaml @@ -1,7 +1,7 @@ # Generated by utils.py dataset_name: ja doc_to_target: '{% if answer is not none %}{{answer[11:]}}{% else %}{{answer_number|string}}{% endif %}' -doc_to_text: '{% if answer is not none %}{{question+"\nステップごとの答え:"}}{% else %}{{"問題: "+question+"\nステップごとの答え:"}}{% endif %}' +doc_to_text: '{% if answer is not none %}{{question+"\nステップごとの答え:"}}{% else %}{{"問題： "+question+"\nステップごとの答え:"}}{% endif %}' filter_list: - filter: - function: regex @@ -17,7 +17,7 @@ filter_list: generation_kwargs: do_sample: false until: - - '問題:' + - 問題： - - <|im_end|> include: cot_yaml diff --git a/lm_eval/tasks/mgsm/native_cot/mgsm_native_cot_zh.yaml b/lm_eval/tasks/mgsm/native_cot/mgsm_native_cot_zh.yaml index 3f0d7e2d..2b45170c 100644 --- a/lm_eval/tasks/mgsm/native_cot/mgsm_native_cot_zh.yaml +++ b/lm_eval/tasks/mgsm/native_cot/mgsm_native_cot_zh.yaml @@ -1,7 +1,7 @@ # Generated by utils.py dataset_name: zh doc_to_target: '{% if answer is not none %}{{answer[6:]}}{% else %}{{answer_number|string}}{% endif %}' -doc_to_text: '{% if answer is not none %}{{question+"\n逐步解答:"}}{% else %}{{"问题: "+question+"\n逐步解答:"}}{% endif %}' +doc_to_text: '{% if answer is not none %}{{question+"\n逐步解答:"}}{% else %}{{"问题： "+question+"\n逐步解答:"}}{% endif %}' filter_list: - filter: - function: regex @@ -17,7 +17,7 @@ filter_list: generation_kwargs: do_sample: false until: - - '问题:' + - 问题： - - <|im_end|> include: cot_yaml diff --git a/lm_eval/tasks/mgsm/utils.py b/lm_eval/tasks/mgsm/utils.py index 116214f9..54e39af9 100644 --- a/lm_eval/tasks/mgsm/utils.py +++ b/lm_eval/tasks/mgsm/utils.py @@ -75,7 +75,7 @@ LANGUAGES = { }, "ja": { # Japanese # "QUESTION": "問題:", - "QUESTION": "\u554f\u984c:", + "QUESTION": "\u554f\u984c：", # "ANSWER": "ステップごとの答え:", "ANSWER": "\u30b9\u30c6\u30c3\u30d7\u3054\u3068\u306e\u7b54\u3048:", "DIRECT": "Answer:", @@ -84,7 +84,7 @@ LANGUAGES = { }, "zh": { # Chinese # "QUESTION": "问题:", - "QUESTION": "\u95ee\u9898:", + "QUESTION": "\u95ee\u9898：", # "ANSWER": "逐步解答:", "ANSWER": "\u9010\u6b65\u89e3\u7b54:", "DIRECT": "Answer:", -- GitLab