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README.md
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...@@ -9,7 +9,7 @@ This project provides a unified framework to test autoregressive language models ...@@ -9,7 +9,7 @@ This project provides a unified framework to test autoregressive language models
Features: Features:
- 100+ tasks implemented - 200+ tasks implemented
- Support for GPT-2, GPT-3, GPT-Neo, GPT-NeoX, and GPT-J, with flexible tokenization-agnostic interface - Support for GPT-2, GPT-3, GPT-Neo, GPT-NeoX, and GPT-J, with flexible tokenization-agnostic interface
- Task versioning to ensure reproducibility - Task versioning to ensure reproducibility
...@@ -51,6 +51,15 @@ python main.py \ ...@@ -51,6 +51,15 @@ python main.py \
--tasks lambada,hellaswag --tasks lambada,hellaswag
``` ```
And if you want to verify the data integrity of the tasks you're performing in addition to running the tasks themselves, you can use the `--check_integrity` flag:
```bash
python main.py \
--model gpt3 \
--model_args engine=davinci \
--tasks lambada,hellaswag \
--check_integrity
```
To evaluate mesh-transformer-jax models that are not available on HF, please invoke eval harness through [this script](https://github.com/kingoflolz/mesh-transformer-jax/blob/master/eval_harness.py). To evaluate mesh-transformer-jax models that are not available on HF, please invoke eval harness through [this script](https://github.com/kingoflolz/mesh-transformer-jax/blob/master/eval_harness.py).
## Implementing new tasks ## Implementing new tasks
...@@ -90,257 +99,269 @@ To implement a new task in eval harness, see [this guide](./docs/task_guide.md). ...@@ -90,257 +99,269 @@ To implement a new task in eval harness, see [this guide](./docs/task_guide.md).
### Full Task List ### Full Task List
| Task Name |Train|Val|Test|Val/Test Docs| Metrics | | Task Name |Train|Val|Test|Val/Test Docs| Metrics |
|---------------------------------------------------------|-----|---|----|------------:|------------------------------------------------------------------------------| |---------------------------------------------------------|-----|---|----|------------:|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|cola |✓ |✓ | | 1043|mcc | |cola |✓ |✓ | | 1043|mcc |
|mnli |✓ |✓ | | 9815|acc | |mnli |✓ |✓ | | 9815|acc |
|mnli_mismatched |✓ |✓ | | 9832|acc | |mnli_mismatched |✓ |✓ | | 9832|acc |
|mrpc |✓ |✓ | | 408|acc, f1 | |mrpc |✓ |✓ | | 408|acc, f1 |
|rte |✓ |✓ | | 277|acc | |rte |✓ |✓ | | 277|acc |
|qnli |✓ |✓ | | 5463|acc | |qnli |✓ |✓ | | 5463|acc |
|qqp |✓ |✓ | | 40430|acc, f1 | |qqp |✓ |✓ | | 40430|acc, f1 |
|sst |✓ |✓ | | 872|acc | |sst |✓ |✓ | | 872|acc |
|wnli |✓ |✓ | | 71|acc | |wnli |✓ |✓ | | 71|acc |
|boolq |✓ |✓ | | 3270|acc | |boolq |✓ |✓ | | 3270|acc |
|cb |✓ |✓ | | 56|acc, f1 | |cb |✓ |✓ | | 56|acc, f1 |
|copa |✓ |✓ | | 100|acc | |copa |✓ |✓ | | 100|acc |
|multirc |✓ |✓ | | 4848|acc | |multirc |✓ |✓ | | 4848|acc |
|record |✓ |✓ | | 10000|f1, em | |record |✓ |✓ | | 10000|f1, em |
|wic |✓ |✓ | | 638|acc | |wic |✓ |✓ | | 638|acc |
|wsc |✓ |✓ | | 104|acc | |wsc |✓ |✓ | | 104|acc |
|coqa |✓ |✓ | | 500|f1, em | |coqa |✓ |✓ | | 500|f1, em |
|drop |✓ |✓ | | 9536|em, f1 | |drop |✓ |✓ | | 9536|em, f1 |
|lambada | |✓ | | 5153|ppl, acc | |lambada | |✓ | | 5153|ppl, acc |
|lambada_cloze | |✓ | | 5153|ppl, acc | |lambada_cloze | |✓ | | 5153|ppl, acc |
|wikitext | |✓ |✓ | 62|word_perplexity, byte_perplexity, bits_per_byte | |lambada_mt_en | |✓ | | 5153|ppl, acc |
|piqa |✓ |✓ | | 1838|acc, acc_norm | |lambada_mt_fr | |✓ | | 5153|ppl, acc |
|prost | | |✓ | 18736|acc, acc_norm | |lambada_mt_de | |✓ | | 5153|ppl, acc |
|pubmedqa | | |✓ | 1000|acc | |lambada_mt_it | |✓ | | 5153|ppl, acc |
|sciq |✓ |✓ |✓ | 1000|acc, acc_norm | |lambada_mt_es | |✓ | | 5153|ppl, acc |
|qa4mre_2011 | | |✓ | 120|acc, acc_norm | |wikitext | |✓ |✓ | 62|word_perplexity, byte_perplexity, bits_per_byte |
|qa4mre_2012 | | |✓ | 160|acc, acc_norm | |piqa |✓ |✓ | | 1838|acc, acc_norm |
|qa4mre_2013 | | |✓ | 284|acc, acc_norm | |prost | | |✓ | 18736|acc, acc_norm |
|triviaqa |✓ |✓ | | 11313|acc | |mc_taco | |✓ |✓ | 9442|f1, em |
|arc_easy |✓ |✓ |✓ | 2376|acc, acc_norm | |pubmedqa | | |✓ | 1000|acc |
|arc_challenge |✓ |✓ |✓ | 1172|acc, acc_norm | |sciq |✓ |✓ |✓ | 1000|acc, acc_norm |
|logiqa |✓ |✓ |✓ | 651|acc, acc_norm | |qa4mre_2011 | | |✓ | 120|acc, acc_norm |
|hellaswag |✓ |✓ | | 10042|acc, acc_norm | |qa4mre_2012 | | |✓ | 160|acc, acc_norm |
|openbookqa |✓ |✓ |✓ | 500|acc, acc_norm | |qa4mre_2013 | | |✓ | 284|acc, acc_norm |
|squad2 |✓ |✓ | | 11873|exact, f1, HasAns_exact, HasAns_f1, NoAns_exact, NoAns_f1, best_exact, best_f1| |triviaqa |✓ |✓ | | 11313|acc |
|race |✓ |✓ |✓ | 1045|acc | |arc_easy |✓ |✓ |✓ | 2376|acc, acc_norm |
|mathqa |✓ |✓ |✓ | 2985|acc, acc_norm | |arc_challenge |✓ |✓ |✓ | 1172|acc, acc_norm |
|headqa_es |✓ |✓ |✓ | 2742|acc, acc_norm | |logiqa |✓ |✓ |✓ | 651|acc, acc_norm |
|headqa_en |✓ |✓ |✓ | 2742|acc, acc_norm | |hellaswag |✓ |✓ | | 10042|acc, acc_norm |
|webqs |✓ | |✓ | 2032|acc | |openbookqa |✓ |✓ |✓ | 500|acc, acc_norm |
|wsc273 | | |✓ | 273|acc | |squad2 |✓ |✓ | | 11873|exact, f1, HasAns_exact, HasAns_f1, NoAns_exact, NoAns_f1, best_exact, best_f1 |
|winogrande |✓ |✓ | | 1267|acc | |race |✓ |✓ |✓ | 1045|acc |
|anli_r1 |✓ |✓ |✓ | 1000|acc | |headqa |✓ |✓ |✓ | 2742|acc, acc_norm |
|anli_r2 |✓ |✓ |✓ | 1000|acc | |headqa_es |✓ |✓ |✓ | 2742|acc, acc_norm |
|anli_r3 |✓ |✓ |✓ | 1200|acc | |headqa_en |✓ |✓ |✓ | 2742|acc, acc_norm |
|ethics_cm |✓ | |✓ | 3885|acc | |mathqa |✓ |✓ |✓ | 2985|acc, acc_norm |
|ethics_deontology |✓ | |✓ | 3596|acc, em | |webqs |✓ | |✓ | 2032|acc |
|ethics_justice |✓ | |✓ | 2704|acc, em | |wsc273 | | |✓ | 273|acc |
|ethics_utilitarianism_original | | |✓ | 4808|acc | |winogrande |✓ |✓ | | 1267|acc |
|ethics_utilitarianism |✓ | |✓ | 4808|acc | |anli_r1 |✓ |✓ |✓ | 1000|acc |
|ethics_virtue |✓ | |✓ | 4975|acc, em | |anli_r2 |✓ |✓ |✓ | 1000|acc |
|math_algebra |✓ | |✓ | 1187|acc | |anli_r3 |✓ |✓ |✓ | 1200|acc |
|math_counting_and_prob |✓ | |✓ | 474|acc | |ethics_cm |✓ | |✓ | 3885|acc |
|math_geometry |✓ | |✓ | 479|acc | |ethics_deontology |✓ | |✓ | 3596|acc, em |
|math_intermediate_algebra |✓ | |✓ | 903|acc | |ethics_justice |✓ | |✓ | 2704|acc, em |
|math_num_theory |✓ | |✓ | 540|acc | |ethics_utilitarianism_original | | |✓ | 4808|acc |
|math_prealgebra |✓ | |✓ | 871|acc | |ethics_utilitarianism |✓ | |✓ | 4808|acc |
|math_precalc |✓ | |✓ | 546|acc | |ethics_virtue |✓ | |✓ | 4975|acc, em |
|arithmetic_2da | |✓ | | 2000|acc | |truthfulqa_mc | |✓ | | 817|mc1, mc2 |
|arithmetic_2ds | |✓ | | 2000|acc | |truthfulqa_gen | |✓ | | 817|bleurt_max, bleurt_acc, bleurt_diff, bleu_max, bleu_acc, bleu_diff, rouge1_max, rouge1_acc, rouge1_diff, rouge2_max, rouge2_acc, rouge2_diff, rougeL_max, rougeL_acc, rougeL_diff|
|arithmetic_3da | |✓ | | 2000|acc | |mutual |✓ |✓ | | 886|r@1, r@2, mrr |
|arithmetic_3ds | |✓ | | 2000|acc | |mutual_plus |✓ |✓ | | 886|r@1, r@2, mrr |
|arithmetic_4da | |✓ | | 2000|acc | |math_algebra |✓ | |✓ | 1187|acc |
|arithmetic_4ds | |✓ | | 2000|acc | |math_counting_and_prob |✓ | |✓ | 474|acc |
|arithmetic_5da | |✓ | | 2000|acc | |math_geometry |✓ | |✓ | 479|acc |
|arithmetic_5ds | |✓ | | 2000|acc | |math_intermediate_algebra |✓ | |✓ | 903|acc |
|arithmetic_2dm | |✓ | | 2000|acc | |math_num_theory |✓ | |✓ | 540|acc |
|arithmetic_1dc | |✓ | | 2000|acc | |math_prealgebra |✓ | |✓ | 871|acc |
|hendrycksTest-abstract_algebra |✓ |✓ |✓ | 100|acc, acc_norm | |math_precalc |✓ | |✓ | 546|acc |
|hendrycksTest-anatomy |✓ |✓ |✓ | 135|acc, acc_norm | |math_asdiv | |✓ | | 2305|acc |
|hendrycksTest-astronomy |✓ |✓ |✓ | 152|acc, acc_norm | |arithmetic_2da | |✓ | | 2000|acc |
|hendrycksTest-business_ethics |✓ |✓ |✓ | 100|acc, acc_norm | |arithmetic_2ds | |✓ | | 2000|acc |
|hendrycksTest-clinical_knowledge |✓ |✓ |✓ | 265|acc, acc_norm | |arithmetic_3da | |✓ | | 2000|acc |
|hendrycksTest-college_biology |✓ |✓ |✓ | 144|acc, acc_norm | |arithmetic_3ds | |✓ | | 2000|acc |
|hendrycksTest-college_chemistry |✓ |✓ |✓ | 100|acc, acc_norm | |arithmetic_4da | |✓ | | 2000|acc |
|hendrycksTest-college_computer_science |✓ |✓ |✓ | 100|acc, acc_norm | |arithmetic_4ds | |✓ | | 2000|acc |
|hendrycksTest-college_mathematics |✓ |✓ |✓ | 100|acc, acc_norm | |arithmetic_5da | |✓ | | 2000|acc |
|hendrycksTest-college_medicine |✓ |✓ |✓ | 173|acc, acc_norm | |arithmetic_5ds | |✓ | | 2000|acc |
|hendrycksTest-college_physics |✓ |✓ |✓ | 102|acc, acc_norm | |arithmetic_2dm | |✓ | | 2000|acc |
|hendrycksTest-computer_security |✓ |✓ |✓ | 100|acc, acc_norm | |arithmetic_1dc | |✓ | | 2000|acc |
|hendrycksTest-conceptual_physics |✓ |✓ |✓ | 235|acc, acc_norm | |hendrycksTest-abstract_algebra |✓ |✓ |✓ | 100|acc, acc_norm |
|hendrycksTest-econometrics |✓ |✓ |✓ | 114|acc, acc_norm | |hendrycksTest-anatomy |✓ |✓ |✓ | 135|acc, acc_norm |
|hendrycksTest-electrical_engineering |✓ |✓ |✓ | 145|acc, acc_norm | |hendrycksTest-astronomy |✓ |✓ |✓ | 152|acc, acc_norm |
|hendrycksTest-elementary_mathematics |✓ |✓ |✓ | 378|acc, acc_norm | |hendrycksTest-business_ethics |✓ |✓ |✓ | 100|acc, acc_norm |
|hendrycksTest-formal_logic |✓ |✓ |✓ | 126|acc, acc_norm | |hendrycksTest-clinical_knowledge |✓ |✓ |✓ | 265|acc, acc_norm |
|hendrycksTest-global_facts |✓ |✓ |✓ | 100|acc, acc_norm | |hendrycksTest-college_biology |✓ |✓ |✓ | 144|acc, acc_norm |
|hendrycksTest-high_school_biology |✓ |✓ |✓ | 310|acc, acc_norm | |hendrycksTest-college_chemistry |✓ |✓ |✓ | 100|acc, acc_norm |
|hendrycksTest-high_school_chemistry |✓ |✓ |✓ | 203|acc, acc_norm | |hendrycksTest-college_computer_science |✓ |✓ |✓ | 100|acc, acc_norm |
|hendrycksTest-high_school_computer_science |✓ |✓ |✓ | 100|acc, acc_norm | |hendrycksTest-college_mathematics |✓ |✓ |✓ | 100|acc, acc_norm |
|hendrycksTest-high_school_european_history |✓ |✓ |✓ | 165|acc, acc_norm | |hendrycksTest-college_medicine |✓ |✓ |✓ | 173|acc, acc_norm |
|hendrycksTest-high_school_geography |✓ |✓ |✓ | 198|acc, acc_norm | |hendrycksTest-college_physics |✓ |✓ |✓ | 102|acc, acc_norm |
|hendrycksTest-high_school_government_and_politics |✓ |✓ |✓ | 193|acc, acc_norm | |hendrycksTest-computer_security |✓ |✓ |✓ | 100|acc, acc_norm |
|hendrycksTest-high_school_macroeconomics |✓ |✓ |✓ | 390|acc, acc_norm | |hendrycksTest-conceptual_physics |✓ |✓ |✓ | 235|acc, acc_norm |
|hendrycksTest-high_school_mathematics |✓ |✓ |✓ | 270|acc, acc_norm | |hendrycksTest-econometrics |✓ |✓ |✓ | 114|acc, acc_norm |
|hendrycksTest-high_school_microeconomics |✓ |✓ |✓ | 238|acc, acc_norm | |hendrycksTest-electrical_engineering |✓ |✓ |✓ | 145|acc, acc_norm |
|hendrycksTest-high_school_physics |✓ |✓ |✓ | 151|acc, acc_norm | |hendrycksTest-elementary_mathematics |✓ |✓ |✓ | 378|acc, acc_norm |
|hendrycksTest-high_school_psychology |✓ |✓ |✓ | 545|acc, acc_norm | |hendrycksTest-formal_logic |✓ |✓ |✓ | 126|acc, acc_norm |
|hendrycksTest-high_school_statistics |✓ |✓ |✓ | 216|acc, acc_norm | |hendrycksTest-global_facts |✓ |✓ |✓ | 100|acc, acc_norm |
|hendrycksTest-high_school_us_history |✓ |✓ |✓ | 204|acc, acc_norm | |hendrycksTest-high_school_biology |✓ |✓ |✓ | 310|acc, acc_norm |
|hendrycksTest-high_school_world_history |✓ |✓ |✓ | 237|acc, acc_norm | |hendrycksTest-high_school_chemistry |✓ |✓ |✓ | 203|acc, acc_norm |
|hendrycksTest-human_aging |✓ |✓ |✓ | 223|acc, acc_norm | |hendrycksTest-high_school_computer_science |✓ |✓ |✓ | 100|acc, acc_norm |
|hendrycksTest-human_sexuality |✓ |✓ |✓ | 131|acc, acc_norm | |hendrycksTest-high_school_european_history |✓ |✓ |✓ | 165|acc, acc_norm |
|hendrycksTest-international_law |✓ |✓ |✓ | 121|acc, acc_norm | |hendrycksTest-high_school_geography |✓ |✓ |✓ | 198|acc, acc_norm |
|hendrycksTest-jurisprudence |✓ |✓ |✓ | 108|acc, acc_norm | |hendrycksTest-high_school_government_and_politics |✓ |✓ |✓ | 193|acc, acc_norm |
|hendrycksTest-logical_fallacies |✓ |✓ |✓ | 163|acc, acc_norm | |hendrycksTest-high_school_macroeconomics |✓ |✓ |✓ | 390|acc, acc_norm |
|hendrycksTest-machine_learning |✓ |✓ |✓ | 112|acc, acc_norm | |hendrycksTest-high_school_mathematics |✓ |✓ |✓ | 270|acc, acc_norm |
|hendrycksTest-management |✓ |✓ |✓ | 103|acc, acc_norm | |hendrycksTest-high_school_microeconomics |✓ |✓ |✓ | 238|acc, acc_norm |
|hendrycksTest-marketing |✓ |✓ |✓ | 234|acc, acc_norm | |hendrycksTest-high_school_physics |✓ |✓ |✓ | 151|acc, acc_norm |
|hendrycksTest-medical_genetics |✓ |✓ |✓ | 100|acc, acc_norm | |hendrycksTest-high_school_psychology |✓ |✓ |✓ | 545|acc, acc_norm |
|hendrycksTest-miscellaneous |✓ |✓ |✓ | 783|acc, acc_norm | |hendrycksTest-high_school_statistics |✓ |✓ |✓ | 216|acc, acc_norm |
|hendrycksTest-moral_disputes |✓ |✓ |✓ | 346|acc, acc_norm | |hendrycksTest-high_school_us_history |✓ |✓ |✓ | 204|acc, acc_norm |
|hendrycksTest-moral_scenarios |✓ |✓ |✓ | 895|acc, acc_norm | |hendrycksTest-high_school_world_history |✓ |✓ |✓ | 237|acc, acc_norm |
|hendrycksTest-nutrition |✓ |✓ |✓ | 306|acc, acc_norm | |hendrycksTest-human_aging |✓ |✓ |✓ | 223|acc, acc_norm |
|hendrycksTest-philosophy |✓ |✓ |✓ | 311|acc, acc_norm | |hendrycksTest-human_sexuality |✓ |✓ |✓ | 131|acc, acc_norm |
|hendrycksTest-prehistory |✓ |✓ |✓ | 324|acc, acc_norm | |hendrycksTest-international_law |✓ |✓ |✓ | 121|acc, acc_norm |
|hendrycksTest-professional_accounting |✓ |✓ |✓ | 282|acc, acc_norm | |hendrycksTest-jurisprudence |✓ |✓ |✓ | 108|acc, acc_norm |
|hendrycksTest-professional_law |✓ |✓ |✓ | 1534|acc, acc_norm | |hendrycksTest-logical_fallacies |✓ |✓ |✓ | 163|acc, acc_norm |
|hendrycksTest-professional_medicine |✓ |✓ |✓ | 272|acc, acc_norm | |hendrycksTest-machine_learning |✓ |✓ |✓ | 112|acc, acc_norm |
|hendrycksTest-professional_psychology |✓ |✓ |✓ | 612|acc, acc_norm | |hendrycksTest-management |✓ |✓ |✓ | 103|acc, acc_norm |
|hendrycksTest-public_relations |✓ |✓ |✓ | 110|acc, acc_norm | |hendrycksTest-marketing |✓ |✓ |✓ | 234|acc, acc_norm |
|hendrycksTest-security_studies |✓ |✓ |✓ | 245|acc, acc_norm | |hendrycksTest-medical_genetics |✓ |✓ |✓ | 100|acc, acc_norm |
|hendrycksTest-sociology |✓ |✓ |✓ | 201|acc, acc_norm | |hendrycksTest-miscellaneous |✓ |✓ |✓ | 783|acc, acc_norm |
|hendrycksTest-us_foreign_policy |✓ |✓ |✓ | 100|acc, acc_norm | |hendrycksTest-moral_disputes |✓ |✓ |✓ | 346|acc, acc_norm |
|hendrycksTest-virology |✓ |✓ |✓ | 166|acc, acc_norm | |hendrycksTest-moral_scenarios |✓ |✓ |✓ | 895|acc, acc_norm |
|hendrycksTest-world_religions |✓ |✓ |✓ | 171|acc, acc_norm | |hendrycksTest-nutrition |✓ |✓ |✓ | 306|acc, acc_norm |
|wmt14-en-fr | | |✓ | 3003|bleu, chrf, ter | |hendrycksTest-philosophy |✓ |✓ |✓ | 311|acc, acc_norm |
|wmt14-fr-en | | |✓ | 3003|bleu, chrf, ter | |hendrycksTest-prehistory |✓ |✓ |✓ | 324|acc, acc_norm |
|wmt16-en-ro | | |✓ | 1999|bleu, chrf, ter | |hendrycksTest-professional_accounting |✓ |✓ |✓ | 282|acc, acc_norm |
|wmt16-ro-en | | |✓ | 1999|bleu, chrf, ter | |hendrycksTest-professional_law |✓ |✓ |✓ | 1534|acc, acc_norm |
|wmt16-de-en | | |✓ | 2999|bleu, chrf, ter | |hendrycksTest-professional_medicine |✓ |✓ |✓ | 272|acc, acc_norm |
|wmt16-en-de | | |✓ | 2999|bleu, chrf, ter | |hendrycksTest-professional_psychology |✓ |✓ |✓ | 612|acc, acc_norm |
|wmt20-cs-en | | |✓ | 664|bleu, chrf, ter | |hendrycksTest-public_relations |✓ |✓ |✓ | 110|acc, acc_norm |
|wmt20-de-en | | |✓ | 785|bleu, chrf, ter | |hendrycksTest-security_studies |✓ |✓ |✓ | 245|acc, acc_norm |
|wmt20-de-fr | | |✓ | 1619|bleu, chrf, ter | |hendrycksTest-sociology |✓ |✓ |✓ | 201|acc, acc_norm |
|wmt20-en-cs | | |✓ | 1418|bleu, chrf, ter | |hendrycksTest-us_foreign_policy |✓ |✓ |✓ | 100|acc, acc_norm |
|wmt20-en-de | | |✓ | 1418|bleu, chrf, ter | |hendrycksTest-virology |✓ |✓ |✓ | 166|acc, acc_norm |
|wmt20-en-iu | | |✓ | 2971|bleu, chrf, ter | |hendrycksTest-world_religions |✓ |✓ |✓ | 171|acc, acc_norm |
|wmt20-en-ja | | |✓ | 1000|bleu, chrf, ter | |wmt14-en-fr | | |✓ | 3003|bleu, chrf, ter |
|wmt20-en-km | | |✓ | 2320|bleu, chrf, ter | |wmt14-fr-en | | |✓ | 3003|bleu, chrf, ter |
|wmt20-en-pl | | |✓ | 1000|bleu, chrf, ter | |wmt16-en-ro | | |✓ | 1999|bleu, chrf, ter |
|wmt20-en-ps | | |✓ | 2719|bleu, chrf, ter | |wmt16-ro-en | | |✓ | 1999|bleu, chrf, ter |
|wmt20-en-ru | | |✓ | 2002|bleu, chrf, ter | |wmt16-de-en | | |✓ | 2999|bleu, chrf, ter |
|wmt20-en-ta | | |✓ | 1000|bleu, chrf, ter | |wmt16-en-de | | |✓ | 2999|bleu, chrf, ter |
|wmt20-en-zh | | |✓ | 1418|bleu, chrf, ter | |wmt20-cs-en | | |✓ | 664|bleu, chrf, ter |
|wmt20-fr-de | | |✓ | 1619|bleu, chrf, ter | |wmt20-de-en | | |✓ | 785|bleu, chrf, ter |
|wmt20-iu-en | | |✓ | 2971|bleu, chrf, ter | |wmt20-de-fr | | |✓ | 1619|bleu, chrf, ter |
|wmt20-ja-en | | |✓ | 993|bleu, chrf, ter | |wmt20-en-cs | | |✓ | 1418|bleu, chrf, ter |
|wmt20-km-en | | |✓ | 2320|bleu, chrf, ter | |wmt20-en-de | | |✓ | 1418|bleu, chrf, ter |
|wmt20-pl-en | | |✓ | 1001|bleu, chrf, ter | |wmt20-en-iu | | |✓ | 2971|bleu, chrf, ter |
|wmt20-ps-en | | |✓ | 2719|bleu, chrf, ter | |wmt20-en-ja | | |✓ | 1000|bleu, chrf, ter |
|wmt20-ru-en | | |✓ | 991|bleu, chrf, ter | |wmt20-en-km | | |✓ | 2320|bleu, chrf, ter |
|wmt20-ta-en | | |✓ | 997|bleu, chrf, ter | |wmt20-en-pl | | |✓ | 1000|bleu, chrf, ter |
|wmt20-zh-en | | |✓ | 2000|bleu, chrf, ter | |wmt20-en-ps | | |✓ | 2719|bleu, chrf, ter |
|iwslt17-en-ar | | |✓ | 1460|bleu, chrf, ter | |wmt20-en-ru | | |✓ | 2002|bleu, chrf, ter |
|iwslt17-ar-en | | |✓ | 1460|bleu, chrf, ter | |wmt20-en-ta | | |✓ | 1000|bleu, chrf, ter |
|anagrams1 | |✓ | | 10000|acc | |wmt20-en-zh | | |✓ | 1418|bleu, chrf, ter |
|anagrams2 | |✓ | | 10000|acc | |wmt20-fr-de | | |✓ | 1619|bleu, chrf, ter |
|cycle_letters | |✓ | | 10000|acc | |wmt20-iu-en | | |✓ | 2971|bleu, chrf, ter |
|random_insertion | |✓ | | 10000|acc | |wmt20-ja-en | | |✓ | 993|bleu, chrf, ter |
|reversed_words | |✓ | | 10000|acc | |wmt20-km-en | | |✓ | 2320|bleu, chrf, ter |
|pile_arxiv | |✓ |✓ | 2407|word_perplexity, byte_perplexity, bits_per_byte | |wmt20-pl-en | | |✓ | 1001|bleu, chrf, ter |
|pile_books3 | |✓ |✓ | 269|word_perplexity, byte_perplexity, bits_per_byte | |wmt20-ps-en | | |✓ | 2719|bleu, chrf, ter |
|pile_bookcorpus2 | |✓ |✓ | 28|word_perplexity, byte_perplexity, bits_per_byte | |wmt20-ru-en | | |✓ | 991|bleu, chrf, ter |
|pile_dm-mathematics | |✓ |✓ | 1922|word_perplexity, byte_perplexity, bits_per_byte | |wmt20-ta-en | | |✓ | 997|bleu, chrf, ter |
|pile_enron | |✓ |✓ | 1010|word_perplexity, byte_perplexity, bits_per_byte | |wmt20-zh-en | | |✓ | 2000|bleu, chrf, ter |
|pile_europarl | |✓ |✓ | 157|word_perplexity, byte_perplexity, bits_per_byte | |iwslt17-en-ar | | |✓ | 1460|bleu, chrf, ter |
|pile_freelaw | |✓ |✓ | 5101|word_perplexity, byte_perplexity, bits_per_byte | |iwslt17-ar-en | | |✓ | 1460|bleu, chrf, ter |
|pile_github | |✓ |✓ | 18195|word_perplexity, byte_perplexity, bits_per_byte | |anagrams1 | |✓ | | 10000|acc |
|pile_gutenberg | |✓ |✓ | 80|word_perplexity, byte_perplexity, bits_per_byte | |anagrams2 | |✓ | | 10000|acc |
|pile_hackernews | |✓ |✓ | 1632|word_perplexity, byte_perplexity, bits_per_byte | |cycle_letters | |✓ | | 10000|acc |
|pile_nih-exporter | |✓ |✓ | 1884|word_perplexity, byte_perplexity, bits_per_byte | |random_insertion | |✓ | | 10000|acc |
|pile_opensubtitles | |✓ |✓ | 642|word_perplexity, byte_perplexity, bits_per_byte | |reversed_words | |✓ | | 10000|acc |
|pile_openwebtext2 | |✓ |✓ | 32925|word_perplexity, byte_perplexity, bits_per_byte | |pile_arxiv | |✓ |✓ | 2407|word_perplexity, byte_perplexity, bits_per_byte |
|pile_philpapers | |✓ |✓ | 68|word_perplexity, byte_perplexity, bits_per_byte | |pile_books3 | |✓ |✓ | 269|word_perplexity, byte_perplexity, bits_per_byte |
|pile_pile-cc | |✓ |✓ | 52790|word_perplexity, byte_perplexity, bits_per_byte | |pile_bookcorpus2 | |✓ |✓ | 28|word_perplexity, byte_perplexity, bits_per_byte |
|pile_pubmed-abstracts | |✓ |✓ | 29895|word_perplexity, byte_perplexity, bits_per_byte | |pile_dm-mathematics | |✓ |✓ | 1922|word_perplexity, byte_perplexity, bits_per_byte |
|pile_pubmed-central | |✓ |✓ | 5911|word_perplexity, byte_perplexity, bits_per_byte | |pile_enron | |✓ |✓ | 1010|word_perplexity, byte_perplexity, bits_per_byte |
|pile_stackexchange | |✓ |✓ | 30378|word_perplexity, byte_perplexity, bits_per_byte | |pile_europarl | |✓ |✓ | 157|word_perplexity, byte_perplexity, bits_per_byte |
|pile_uspto | |✓ |✓ | 11415|word_perplexity, byte_perplexity, bits_per_byte | |pile_freelaw | |✓ |✓ | 5101|word_perplexity, byte_perplexity, bits_per_byte |
|pile_ubuntu-irc | |✓ |✓ | 22|word_perplexity, byte_perplexity, bits_per_byte | |pile_github | |✓ |✓ | 18195|word_perplexity, byte_perplexity, bits_per_byte |
|pile_wikipedia | |✓ |✓ | 17511|word_perplexity, byte_perplexity, bits_per_byte | |pile_gutenberg | |✓ |✓ | 80|word_perplexity, byte_perplexity, bits_per_byte |
|pile_youtubesubtitles | |✓ | | 1000|acc |pile_hackernews | |✓ |✓ | 1632|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_adjunct_island | |✓ | | 1000|acc |pile_nih-exporter | |✓ |✓ | 1884|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_anaphor_gender_agreement | |✓ | | 1000|acc |pile_opensubtitles | |✓ |✓ | 642|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_anaphor_number_agreement | |✓ | | 1000|acc |pile_openwebtext2 | |✓ |✓ | 32925|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_animate_subject_passive | |✓ | | 1000|acc |pile_philpapers | |✓ |✓ | 68|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_animate_subject_trans | |✓ | | 1000|acc |pile_pile-cc | |✓ |✓ | 52790|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_causative | |✓ | | 1000|acc |pile_pubmed-abstracts | |✓ |✓ | 29895|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_complex_NP_island | |✓ | | 1000|acc |pile_pubmed-central | |✓ |✓ | 5911|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_coordinate_structure_constraint_complex_left_branch| |✓ | | 1000|acc |pile_stackexchange | |✓ |✓ | 30378|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_coordinate_structure_constraint_object_extraction | |✓ | | 1000|acc |pile_uspto | |✓ |✓ | 11415|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_determiner_noun_agreement_1 | |✓ | | 1000|acc |pile_ubuntu-irc | |✓ |✓ | 22|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_determiner_noun_agreement_2 | |✓ | | 1000|acc |pile_wikipedia | |✓ |✓ | 17511|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_determiner_noun_agreement_irregular_1 | |✓ | | 1000|acc |pile_youtubesubtitles | |✓ |✓ | 342|word_perplexity, byte_perplexity, bits_per_byte |
|blimp_determiner_noun_agreement_irregular_2 | |✓ | | 1000|acc |blimp_adjunct_island | |✓ | | 1000|acc |
|blimp_determiner_noun_agreement_with_adj_2 | |✓ | | 1000|acc |blimp_anaphor_gender_agreement | |✓ | | 1000|acc |
|blimp_determiner_noun_agreement_with_adj_irregular_1 | |✓ | | 1000|acc |blimp_anaphor_number_agreement | |✓ | | 1000|acc |
|blimp_determiner_noun_agreement_with_adj_irregular_2 | |✓ | | 1000|acc |blimp_animate_subject_passive | |✓ | | 1000|acc |
|blimp_determiner_noun_agreement_with_adjective_1 | |✓ | | 1000|acc |blimp_animate_subject_trans | |✓ | | 1000|acc |
|blimp_distractor_agreement_relational_noun | |✓ | | 1000|acc |blimp_causative | |✓ | | 1000|acc |
|blimp_distractor_agreement_relative_clause | |✓ | | 1000|acc |blimp_complex_NP_island | |✓ | | 1000|acc |
|blimp_drop_argument | |✓ | | 1000|acc |blimp_coordinate_structure_constraint_complex_left_branch| |✓ | | 1000|acc |
|blimp_ellipsis_n_bar_1 | |✓ | | 1000|acc |blimp_coordinate_structure_constraint_object_extraction | |✓ | | 1000|acc |
|blimp_ellipsis_n_bar_2 | |✓ | | 1000|acc |blimp_determiner_noun_agreement_1 | |✓ | | 1000|acc |
|blimp_existential_there_object_raising | |✓ | | 1000|acc |blimp_determiner_noun_agreement_2 | |✓ | | 1000|acc |
|blimp_existential_there_quantifiers_1 | |✓ | | 1000|acc |blimp_determiner_noun_agreement_irregular_1 | |✓ | | 1000|acc |
|blimp_existential_there_quantifiers_2 | |✓ | | 1000|acc |blimp_determiner_noun_agreement_irregular_2 | |✓ | | 1000|acc |
|blimp_existential_there_subject_raising | |✓ | | 1000|acc |blimp_determiner_noun_agreement_with_adj_2 | |✓ | | 1000|acc |
|blimp_expletive_it_object_raising | |✓ | | 1000|acc |blimp_determiner_noun_agreement_with_adj_irregular_1 | |✓ | | 1000|acc |
|blimp_inchoative | |✓ | | 1000|acc |blimp_determiner_noun_agreement_with_adj_irregular_2 | |✓ | | 1000|acc |
|blimp_intransitive | |✓ | | 1000|acc |blimp_determiner_noun_agreement_with_adjective_1 | |✓ | | 1000|acc |
|blimp_irregular_past_participle_adjectives | |✓ | | 1000|acc |blimp_distractor_agreement_relational_noun | |✓ | | 1000|acc |
|blimp_irregular_past_participle_verbs | |✓ | | 1000|acc |blimp_distractor_agreement_relative_clause | |✓ | | 1000|acc |
|blimp_irregular_plural_subject_verb_agreement_1 | |✓ | | 1000|acc |blimp_drop_argument | |✓ | | 1000|acc |
|blimp_irregular_plural_subject_verb_agreement_2 | |✓ | | 1000|acc |blimp_ellipsis_n_bar_1 | |✓ | | 1000|acc |
|blimp_left_branch_island_echo_question | |✓ | | 1000|acc |blimp_ellipsis_n_bar_2 | |✓ | | 1000|acc |
|blimp_left_branch_island_simple_question | |✓ | | 1000|acc |blimp_existential_there_object_raising | |✓ | | 1000|acc |
|blimp_matrix_question_npi_licensor_present | |✓ | | 1000|acc |blimp_existential_there_quantifiers_1 | |✓ | | 1000|acc |
|blimp_npi_present_1 | |✓ | | 1000|acc |blimp_existential_there_quantifiers_2 | |✓ | | 1000|acc |
|blimp_npi_present_2 | |✓ | | 1000|acc |blimp_existential_there_subject_raising | |✓ | | 1000|acc |
|blimp_only_npi_licensor_present | |✓ | | 1000|acc |blimp_expletive_it_object_raising | |✓ | | 1000|acc |
|blimp_only_npi_scope | |✓ | | 1000|acc |blimp_inchoative | |✓ | | 1000|acc |
|blimp_passive_1 | |✓ | | 1000|acc |blimp_intransitive | |✓ | | 1000|acc |
|blimp_passive_2 | |✓ | | 1000|acc |blimp_irregular_past_participle_adjectives | |✓ | | 1000|acc |
|blimp_principle_A_c_command | |✓ | | 1000|acc |blimp_irregular_past_participle_verbs | |✓ | | 1000|acc |
|blimp_principle_A_case_1 | |✓ | | 1000|acc |blimp_irregular_plural_subject_verb_agreement_1 | |✓ | | 1000|acc |
|blimp_principle_A_case_2 | |✓ | | 1000|acc |blimp_irregular_plural_subject_verb_agreement_2 | |✓ | | 1000|acc |
|blimp_principle_A_domain_1 | |✓ | | 1000|acc |blimp_left_branch_island_echo_question | |✓ | | 1000|acc |
|blimp_principle_A_domain_2 | |✓ | | 1000|acc |blimp_left_branch_island_simple_question | |✓ | | 1000|acc |
|blimp_principle_A_domain_3 | |✓ | | 1000|acc |blimp_matrix_question_npi_licensor_present | |✓ | | 1000|acc |
|blimp_principle_A_reconstruction | |✓ | | 1000|acc |blimp_npi_present_1 | |✓ | | 1000|acc |
|blimp_regular_plural_subject_verb_agreement_1 | |✓ | | 1000|acc |blimp_npi_present_2 | |✓ | | 1000|acc |
|blimp_regular_plural_subject_verb_agreement_2 | |✓ | | 1000|acc |blimp_only_npi_licensor_present | |✓ | | 1000|acc |
|blimp_sentential_negation_npi_licensor_present | |✓ | | 1000|acc |blimp_only_npi_scope | |✓ | | 1000|acc |
|blimp_sentential_negation_npi_scope | |✓ | | 1000|acc |blimp_passive_1 | |✓ | | 1000|acc |
|blimp_sentential_subject_island | |✓ | | 1000|acc |blimp_passive_2 | |✓ | | 1000|acc |
|blimp_superlative_quantifiers_1 | |✓ | | 1000|acc |blimp_principle_A_c_command | |✓ | | 1000|acc |
|blimp_superlative_quantifiers_2 | |✓ | | 1000|acc |blimp_principle_A_case_1 | |✓ | | 1000|acc |
|blimp_tough_vs_raising_1 | |✓ | | 1000|acc |blimp_principle_A_case_2 | |✓ | | 1000|acc |
|blimp_tough_vs_raising_2 | |✓ | | 1000|acc |blimp_principle_A_domain_1 | |✓ | | 1000|acc |
|blimp_transitive | |✓ | | 1000|acc |blimp_principle_A_domain_2 | |✓ | | 1000|acc |
|blimp_wh_island | |✓ | | 1000|acc |blimp_principle_A_domain_3 | |✓ | | 1000|acc |
|blimp_wh_questions_object_gap | |✓ | | 1000|acc |blimp_principle_A_reconstruction | |✓ | | 1000|acc |
|blimp_wh_questions_subject_gap | |✓ | | 1000|acc |blimp_regular_plural_subject_verb_agreement_1 | |✓ | | 1000|acc |
|blimp_wh_questions_subject_gap_long_distance | |✓ | | 1000|acc |blimp_regular_plural_subject_verb_agreement_2 | |✓ | | 1000|acc |
|blimp_wh_vs_that_no_gap | |✓ | | 1000|acc |blimp_sentential_negation_npi_licensor_present | |✓ | | 1000|acc |
|blimp_wh_vs_that_no_gap_long_distance | |✓ | | 1000|acc |blimp_sentential_negation_npi_scope | |✓ | | 1000|acc |
|blimp_wh_vs_that_with_gap | |✓ | | 1000|acc |blimp_sentential_subject_island | |✓ | | 1000|acc |
|blimp_wh_vs_that_with_gap_long_distance | |✓ | | 1000|acc |blimp_superlative_quantifiers_1 | |✓ | | 1000|acc |
|blimp_superlative_quantifiers_2 | |✓ | | 1000|acc |
|blimp_tough_vs_raising_1 | |✓ | | 1000|acc |
|blimp_tough_vs_raising_2 | |✓ | | 1000|acc |
|blimp_transitive | |✓ | | 1000|acc |
|blimp_wh_island | |✓ | | 1000|acc |
|blimp_wh_questions_object_gap | |✓ | | 1000|acc |
|blimp_wh_questions_subject_gap | |✓ | | 1000|acc |
|blimp_wh_questions_subject_gap_long_distance | |✓ | | 1000|acc |
|blimp_wh_vs_that_no_gap | |✓ | | 1000|acc |
|blimp_wh_vs_that_no_gap_long_distance | |✓ | | 1000|acc |
|blimp_wh_vs_that_with_gap | |✓ | | 1000|acc |
|blimp_wh_vs_that_with_gap_long_distance | |✓ | | 1000|acc |
## Usage ## Usage
......
lm_eval/evaluator.py
View file @ bf19a7a1
import collections import collections
import itertools import itertools
import pathlib
import random import random
import lm_eval.metrics import lm_eval.metrics
import lm_eval.models import lm_eval.models
...@@ -7,13 +8,15 @@ import lm_eval.tasks ...@@ -7,13 +8,15 @@ import lm_eval.tasks
import lm_eval.base import lm_eval.base
import lm_eval.decontamination import lm_eval.decontamination
import numpy as np import numpy as np
from lm_eval.utils import positional_deprecated from lm_eval.utils import positional_deprecated, run_task_tests
@positional_deprecated @positional_deprecated
def simple_evaluate(model, model_args=None, tasks=[], def simple_evaluate(model, model_args=None, tasks=[],
num_fewshot=0, batch_size=None, device=None, num_fewshot=0, batch_size=None, device=None,
no_cache=False, limit=None, bootstrap_iters=100000, no_cache=False, limit=None, bootstrap_iters=100000,
description_dict=None, decontamination_ngrams_path=None): description_dict=None, check_integrity=False,
decontamination_ngrams_path=None):
"""Instantiate and evaluate a model on a list of tasks. """Instantiate and evaluate a model on a list of tasks.
:param model: Union[str, LM] :param model: Union[str, LM]
...@@ -37,6 +40,8 @@ def simple_evaluate(model, model_args=None, tasks=[], ...@@ -37,6 +40,8 @@ def simple_evaluate(model, model_args=None, tasks=[],
Number of iterations for bootstrap statistics Number of iterations for bootstrap statistics
:param description_dict: dict[str, str] :param description_dict: dict[str, str]
Dictionary of custom task descriptions of the form: `task_name: description` Dictionary of custom task descriptions of the form: `task_name: description`
:param check_integrity: bool
Whether to run the relevant part of the test suite for the tasks
:return :return
Dictionary of results Dictionary of results
""" """
...@@ -61,6 +66,9 @@ def simple_evaluate(model, model_args=None, tasks=[], ...@@ -61,6 +66,9 @@ def simple_evaluate(model, model_args=None, tasks=[],
task_dict = lm_eval.tasks.get_task_dict(tasks) task_dict = lm_eval.tasks.get_task_dict(tasks)
if check_integrity:
run_task_tests(task_list=tasks)
results = evaluate( results = evaluate(
lm=lm, lm=lm,
task_dict=task_dict, task_dict=task_dict,
......
lm_eval/models/dummy.py
View file @ bf19a7a1
...@@ -7,30 +7,30 @@ class DummyLM(LM): ...@@ -7,30 +7,30 @@ class DummyLM(LM):
pass pass
@classmethod @classmethod
def create_from_arg_string(cls, arg_string): def create_from_arg_string(cls, arg_string, additional_config=None):
return cls() return cls()
def loglikelihood(self, requests): def loglikelihood(self, requests):
res = [] res = []
for _ in requests: for _ in requests:
res.append((-random.random(), False)) res.append((-random.random(), False))
return res return res
def greedy_until(self, requests): def greedy_until(self, requests):
res = [] res = []
for ctx, _ in requests: for ctx, _ in requests:
res.append("lol") res.append("lol")
assert ctx.strip() != '' assert ctx.strip() != ""
return res return res
def loglikelihood_rolling(self, requests): def loglikelihood_rolling(self, requests):
res = [] res = []
for _ in requests: for _ in requests:
res.append(-random.random()) res.append(-random.random())
return res return res
\ No newline at end of file
lm_eval/models/gpt3.py
View file @ bf19a7a1
...@@ -46,6 +46,8 @@ def oa_completion(**kwargs): ...@@ -46,6 +46,8 @@ def oa_completion(**kwargs):
try: try:
return openai.Completion.create(**kwargs) return openai.Completion.create(**kwargs)
except openai.error.OpenAIError: except openai.error.OpenAIError:
import traceback
traceback.print_exc()
time.sleep(backoff_time) time.sleep(backoff_time)
backoff_time *= 1.5 backoff_time *= 1.5
......
lm_eval/tasks/__init__.py
View file @ bf19a7a1
...@@ -29,6 +29,7 @@ from . import triviaqa ...@@ -29,6 +29,7 @@ from . import triviaqa
from . import pubmedqa from . import pubmedqa
from . import sciq from . import sciq
from . import webqs from . import webqs
from . import qasper
from . import qa4mre from . import qa4mre
from . import translation from . import translation
from . import headqa from . import headqa
...@@ -48,6 +49,7 @@ from . import mutual ...@@ -48,6 +49,7 @@ from . import mutual
from . import truthfulqa from . import truthfulqa
from . import blimp from . import blimp
from . import asdiv from . import asdiv
from . import gsm8k
######################################## ########################################
# Translation tasks # Translation tasks
...@@ -121,6 +123,8 @@ TASK_REGISTRY = { ...@@ -121,6 +123,8 @@ TASK_REGISTRY = {
"pubmedqa" : pubmedqa.Pubmed_QA, "pubmedqa" : pubmedqa.Pubmed_QA,
"sciq" : sciq.SciQ, "sciq" : sciq.SciQ,
"qasper": qasper.QASPER,
"qa4mre_2011" : qa4mre.QA4MRE_2011, "qa4mre_2011" : qa4mre.QA4MRE_2011,
"qa4mre_2012" : qa4mre.QA4MRE_2012, "qa4mre_2012" : qa4mre.QA4MRE_2012,
"qa4mre_2013" : qa4mre.QA4MRE_2013, "qa4mre_2013" : qa4mre.QA4MRE_2013,
...@@ -170,6 +174,7 @@ TASK_REGISTRY = { ...@@ -170,6 +174,7 @@ TASK_REGISTRY = {
"math_prealgebra": hendrycks_math.MathPrealgebra, "math_prealgebra": hendrycks_math.MathPrealgebra,
"math_precalc": hendrycks_math.MathPrecalculus, "math_precalc": hendrycks_math.MathPrecalculus,
"math_asdiv": asdiv.Asdiv, "math_asdiv": asdiv.Asdiv,
"gsm8k": gsm8k.GradeSchoolMath8K,
# arithmetic # arithmetic
"arithmetic_2da": arithmetic.Arithmetic2DPlus, "arithmetic_2da": arithmetic.Arithmetic2DPlus,
......
lm_eval/tasks/gsm8k.py 0 → 100644
View file @ bf19a7a1
"""
"Training Verifiers to Solve Math Word Problems"
https://arxiv.org/abs/2110.14168
@misc{cobbe2021training,
title={Training Verifiers to Solve Math Word Problems},
author={Karl Cobbe and Vineet Kosaraju and Mohammad Bavarian and Jacob Hilton and Reiichiro Nakano and Christopher Hesse and John Schulman},
year={2021},
eprint={2110.14168},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
NOTE: See the official implementation of the task:
https://github.com/openai/grade-school-math/blob/master/grade_school_math/calculator.py
for how to make use of the dataset's calculator annotations in your language
model's sample/generation function.
"""
import json
import re
from best_download import download_file
from pathlib import Path
from lm_eval.base import Task, rf
from lm_eval.metrics import mean
ANS_RE = re.compile(r"#### (\-?[0-9\.\,]+)")
INVALID_ANS = "[invalid]"
class GradeSchoolMath8K(Task):
VERSION = 0
DATASET_PATH = Path('data/gsm8k')
def download(self):
if self.DATASET_PATH.exists():
return
Path.mkdir(self.DATASET_PATH, parents=True)
base_url = "https://raw.githubusercontent.com/openai/grade-school-math/master/grade_school_math/data"
splits = [
{"name": "train", "checksum": "17f347dc51477c50d4efb83959dbb7c56297aba886e5544ee2aaed3024813465"},
{"name": "test", "checksum": "3730d312f6e3440559ace48831e51066acaca737f6eabec99bccb9e4b3c39d14"},
]
for split in splits:
file = self.DATASET_PATH / f"{split['name']}.jsonl"
download_file(f"{base_url}/{split['name']}.jsonl", str(file), split["checksum"])
def has_training_docs(self):
return True
def has_validation_docs(self):
return False
def has_test_docs(self):
return True
def _load_docs(self, file):
return (json.loads(line) for line in open(file).read().splitlines())
def training_docs(self):
return self._load_docs(self.DATASET_PATH / "train.jsonl")
def validation_docs(self):
raise NotImplementedError
def test_docs(self):
return self._load_docs(self.DATASET_PATH / "test.jsonl")
def doc_to_text(self, doc):
return "Question: " + doc['question'] + '\nAnswer:'
def doc_to_target(self, doc):
return " " + doc['answer']
def construct_requests(self, doc, ctx):
""" Uses RequestFactory to construct Requests and returns an iterable of
Requests which will be sent to the LM.
:param doc:
The document as returned from training_docs, validation_docs, or test_docs.
:param ctx: str
The context string, generated by fewshot_context. This includes the natural
language description, as well as the few shot examples, and the question
part of the document for `doc`.
"""
# NOTE: The paper implements "verifiers" that assign a score to multiple
# solutions and output the highest ranked solution.
completion = rf.greedy_until(ctx, ['\n'])
return completion
def _extract_answer(self, completion):
match = ANS_RE.search(completion)
if match:
match_str = match.group(1).strip()
match_str = match_str.replace(",", "")
return match_str
else:
return INVALID_ANS
def _is_correct(self, completion, answer):
gold = self._extract_answer(answer)
assert gold != INVALID_ANS, "No ground truth answer found in the document."
return self._extract_answer(completion) == gold
def process_results(self, doc, results):
"""Take a single document and the LM results and evaluates, returning a
dict where keys are the names of submetrics and values are the values of
the metric for that one document
:param doc:
The document as returned from training_docs, validation_docs, or test_docs.
:param results:
The results of the requests created in construct_requests.
"""
completion = results[0]
answer = doc["answer"]
return {
"acc": self._is_correct(completion, answer)
}
def aggregation(self):
"""
:returns: {str: [float] -> float}
A dictionary where keys are the names of submetrics and values are
functions that aggregate a list of metrics
"""
return {
"acc": mean
}
def higher_is_better(self):
"""
:returns: {str: bool}
A dictionary where keys are the names of submetrics and values are
whether a higher value of the submetric is better
"""
return {
"acc": True
}
lm_eval/tasks/hendrycks_math.py
View file @ bf19a7a1
...@@ -18,7 +18,7 @@ class Math(Task): ...@@ -18,7 +18,7 @@ class Math(Task):
def download(self): def download(self):
if not (self.DATASET_PATH / 'test').exists() or not (self.DATASET_PATH / 'done').exists(): if not (self.DATASET_PATH / 'test').exists() or not (self.DATASET_PATH / 'done').exists():
sh(f"mkdir -p {self.DATASET_PATH}") sh(f"mkdir -p {self.DATASET_PATH}")
download_file("https://people.eecs.berkeley.edu/~hendrycks/MATH.tar", local_file=f"{self.DATASET_PATH}.tar", expected_checksum="01256fd7cd5430596fdf07e6e6a5827111b5235b7ffed679c662a12f898932da") download_file("https://people.eecs.berkeley.edu/~hendrycks/MATH.tar", local_file=f"{self.DATASET_PATH}.tar", expected_checksum="0fbe4fad0df66942db6c221cdcc95b298cc7f4595a2f0f518360cce84e90d9ac")
sh(f""" sh(f"""
tar -xf {self.DATASET_PATH}.tar -C data/ && touch {self.DATASET_PATH / 'done'} tar -xf {self.DATASET_PATH}.tar -C data/ && touch {self.DATASET_PATH / 'done'}
rm {self.DATASET_PATH}.tar rm {self.DATASET_PATH}.tar
...@@ -291,42 +291,42 @@ class Math(Task): ...@@ -291,42 +291,42 @@ class Math(Task):
class MathAlgebra(Math): class MathAlgebra(Math):
VERSION = 0 VERSION = 1
def get_file_info(self): def get_file_info(self):
return 'algebra' return 'algebra'
class MathCountingAndProbability(Math): class MathCountingAndProbability(Math):
VERSION = 0 VERSION = 1
def get_file_info(self): def get_file_info(self):
return 'counting_and_probability' return 'counting_and_probability'
class MathGeometry(Math): class MathGeometry(Math):
VERSION = 0 VERSION = 1
def get_file_info(self): def get_file_info(self):
return 'geometry' return 'geometry'
class MathIntermediateAlgebra(Math): class MathIntermediateAlgebra(Math):
VERSION = 0 VERSION = 1
def get_file_info(self): def get_file_info(self):
return 'intermediate_algebra' return 'intermediate_algebra'
class MathNumberTheory(Math): class MathNumberTheory(Math):
VERSION = 0 VERSION = 1
def get_file_info(self): def get_file_info(self):
return 'number_theory' return 'number_theory'
class MathPrealgebra(Math): class MathPrealgebra(Math):
VERSION = 0 VERSION = 1
def get_file_info(self): def get_file_info(self):
return 'prealgebra' return 'prealgebra'
class MathPrecalculus(Math): class MathPrecalculus(Math):
VERSION = 0 VERSION = 1
def get_file_info(self): def get_file_info(self):
return 'precalculus' return 'precalculus'
lm_eval/tasks/qasper.py 0 → 100644
View file @ bf19a7a1
"""
A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers
https://arxiv.org/abs/2105.03011
@article{DBLP:journals/corr/abs-2105-03011,
author = {Pradeep Dasigi and
Kyle Lo and
Iz Beltagy and
Arman Cohan and
Noah A. Smith and
Matt Gardner},
title = {A Dataset of Information-Seeking Questions and Answers Anchored in
Research Papers},
journal = {CoRR},
volume = {abs/2105.03011},
year = {2021},
url = {https://arxiv.org/abs/2105.03011},
eprinttype = {arXiv},
eprint = {2105.03011},
timestamp = {Fri, 14 May 2021 12:13:30 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2105-03011.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
"""
from collections import Counter
from math import exp
import random
import re
import string
from lm_eval.base import rf
from lm_eval.metrics import f1_score, mean
from .common import HFTask
def normalize_answer(s):
"""
Taken from the official evaluation script for v1.1 of the SQuAD dataset.
Lower text and remove punctuation, articles and extra whitespace.
"""
def remove_articles(text):
return re.sub(r"\b(a|an|the)\b", " ", text)
def white_space_fix(text):
return " ".join(text.split())
def remove_punc(text):
exclude = set(string.punctuation)
return "".join(ch for ch in text if ch not in exclude)
def lower(text):
return text.lower()
return white_space_fix(remove_articles(remove_punc(lower(s))))
def categorise_answer(answer_blob):
if answer_blob["unanswerable"]:
answer = "unanswerable"
answer_type = "unanswerable"
return answer, answer_type
elif answer_blob["yes_no"]:
answer = "yes"
answer_type = "bool"
return answer, answer_type
elif answer_blob["free_form_answer"]:
answer = answer_blob["free_form_answer"]
answer_type = "free form answer"
return answer, answer_type
elif answer_blob["extractive_spans"]:
answer = answer_blob["extractive_spans"]
answer_type = "extractive_spans"
return answer, answer_type
elif answer_blob["yes_no"] is False:
answer = "no"
answer_type = "bool"
return answer, answer_type
def token_f1_score(prediction, ground_truth):
"""
Taken from the official evaluation script for v1.1 of the SQuAD dataset.
"""
prediction_tokens = normalize_answer(prediction).split()
ground_truth_tokens = normalize_answer(ground_truth).split()
common = Counter(prediction_tokens) & Counter(ground_truth_tokens)
num_same = sum(common.values())
if num_same == 0:
return 0
precision = 1.0 * num_same / len(prediction_tokens)
recall = 1.0 * num_same / len(ground_truth_tokens)
f1 = (2 * precision * recall) / (precision + recall)
return f1
class QASPER(HFTask):
VERSION = 0
DATASET_PATH = "qasper"
DATASET_NAME = None
def doc_to_text(self, doc):
return (
"TITLE: "
+ doc["title"]
+ "\n"
+ "ABSTRACT: "
+ doc["abstract"]
+ "\n\n"
+ "Q: "
+ doc["question"]
+ "\n\n"
+ "A:"
)
def doc_to_target(self, doc):
answer = doc["answer"]
if isinstance(answer, list):
answer = ", ".join(answer)
return " " + answer
def training_docs(self):
for doc in self.data["train"]:
yield from self.process_doc(doc)
def validation_docs(self):
for doc in self.data["train"]:
yield from self.process_doc(doc)
def process_doc(self, doc):
"""Given a `doc`, flatten it out so that each JSON blob
contains exactly one question and one answer. Logic taken from
the reference implementation available at
https://github.com/allenai/qasper-led-baseline/blob/main/scripts/evaluator.py
"""
obs_list = []
for question, answer_list in zip(doc["qas"]["question"], doc["qas"]["answers"]):
for answer_blob in answer_list["answer"]:
answer, answer_type = categorise_answer(answer_blob)
obs_list.append(
{
"title": doc["title"],
"abstract": doc["abstract"],
"question": question,
"answer": answer,
"answer_type": answer_type,
}
)
return obs_list
def process_results(self, doc, results):
# TODO: Calculate a score for extractive spans once a request type for generating
# extractive spans is available
if not results:
return {}
elif len(results) == 1:
[res] = results
elif len(results) == 2:
[ll_yes, ll_no] = results
# TODO: Handle unanswerability first
# unanswerable_gold = doc["answer_type"] == "unanswerable"
# unanswerable_pred = exp(logprob_unanswerable)
# res_dict["f1_unanswerable"] = (unanswerable_gold, unanswerable_pred)
res_dict = {}
# Handle yes/no questions
if doc["answer_type"] == "bool":
gold = 1 if doc["answer"] == "yes" else 0
pred = ll_yes > ll_no
res_dict["f1_yesno"] = (gold, pred)
# Handle completions
if doc["answer_type"] == "free form answer":
res_dict["f1_abstractive"] = token_f1_score(res, doc["answer"])
# TODO: Handle extraction
# if doc["answer_type"] == "extractive_spans":
# res_dict["f1_extractive"] = 0
return res_dict
def aggregation(self):
return {
"f1_yesno": f1_score,
"f1_abstractive": mean,
}
def construct_requests(self, doc, ctx):
"""Uses RequestFactory to construct Requests and returns an iterable of
Requests which will be sent to the LM.
:param doc:
The document as returned from training_docs, validation_docs, or test_docs.
:param ctx: str
The context string, generated by fewshot_context. This includes the natural
language description, as well as the few shot examples, and the question
part of the document for `doc`.
"""
# unanswerable = rf.loglikelihood(ctx, " " + "unanswerable")
if doc["answer_type"] in ("free form answer"):
return [rf.greedy_until(ctx, ["\n"])]
elif doc["answer_type"] in ("bool"):
ll_yes, _ = rf.loglikelihood(ctx, " yes")
ll_no, _ = rf.loglikelihood(ctx, " no")
return [ll_yes, ll_no]
else:
return []
def higher_is_better(self):
"""
:returns: {str: bool}
A dictionary where keys are the names of submetrics and values are
whether a higher value of the submetric is better
"""
return {
"f1_yesno": True,
"f1_abstractive": True,
}
lm_eval/utils.py
View file @ bf19a7a1
import os import os
import pathlib
import re import re
import collections import collections
import functools import functools
import inspect import inspect
import sys
import pytest
from typing import List
class ExitCodeError(Exception): class ExitCodeError(Exception):
...@@ -155,3 +159,32 @@ def positional_deprecated(fn): ...@@ -155,3 +159,32 @@ def positional_deprecated(fn):
"lm-evaluation-harness!") "lm-evaluation-harness!")
return fn(*args, **kwargs) return fn(*args, **kwargs)
return _wrapper return _wrapper
@positional_deprecated
def find_test_root(start_path: pathlib.Path) -> pathlib.Path:
"""
Search upward in the directory tree to a maximum of three layers
to find and return the package root (containing the 'tests' folder)
"""
cur_path = start_path.resolve()
max_layers = 3
for _ in range(max_layers):
if (cur_path / 'tests' / 'test_version_stable.py').exists():
return cur_path
else:
cur_path = cur_path.parent.resolve()
raise FileNotFoundError(f"Unable to find package root within {max_layers} upwards" +\
f"of {start_path}")
@positional_deprecated
def run_task_tests(task_list: List[str]):
"""
Find the package root and run the tests for the given tasks
"""
package_root = find_test_root(start_path=pathlib.Path(__file__))
task_string = ' or '.join(task_list)
args = [f'{package_root}/tests/test_version_stable.py', f'--rootdir={package_root}', '-k', f'{task_string}']
sys.path.append(str(package_root))
pytest_return_val = pytest.main(args)
if pytest_return_val:
raise ValueError(f"Not all tests for the specified tasks ({task_list}) ran successfully! Error code: {pytest_return_val}")
\ No newline at end of file
main.py
View file @ bf19a7a1
...@@ -38,7 +38,8 @@ def parse_args(): ...@@ -38,7 +38,8 @@ def parse_args():
parser.add_argument('--decontaminate', action="store_true") parser.add_argument('--decontaminate', action="store_true")
parser.add_argument('--decontaminate_ngrams_path', default=None) parser.add_argument('--decontaminate_ngrams_path', default=None)
parser.add_argument('--decontaminate_ngrams_n_size', type=int, default=None) parser.add_argument('--decontaminate_ngrams_n_size', type=int, default=None)
parser.add_argument('--description_dict_path', default=None) parser.add_argument('--description_dict_path', default=None)
parser.add_argument('--check_integrity', action="store_true")
return parser.parse_args() return parser.parse_args()
...@@ -98,6 +99,7 @@ def main(): ...@@ -98,6 +99,7 @@ def main():
decontaminate=args.decontaminate, decontaminate=args.decontaminate,
decontaminate_ngrams_path=args.decontaminate_ngrams_path, decontaminate_ngrams_path=args.decontaminate_ngrams_path,
decontaminate_ngrams_n_size=args.decontaminate_ngrams_n_size decontaminate_ngrams_n_size=args.decontaminate_ngrams_n_size
check_integrity=args.check_integrity
) )
dumped = json.dumps(results, indent=2) dumped = json.dumps(results, indent=2)
......
setup.py
View file @ bf19a7a1
...@@ -21,7 +21,7 @@ setuptools.setup( ...@@ -21,7 +21,7 @@ setuptools.setup(
python_requires='>=3.6', python_requires='>=3.6',
install_requires=[ install_requires=[
"black", "black",
"best_download>=0.0.6", "best_download==0.0.9",
"datasets==1.15.1", "datasets==1.15.1",
"click>=7.1", "click>=7.1",
"scikit-learn>=0.24.1", "scikit-learn>=0.24.1",
......
tests/testdata/gsm8k-v0-greedy_until 0 → 100644
View file @ bf19a7a1
e7292dbdd7fd8419ba954f2e0701e04c8d0e8842fe053dbf2fe47d926630e35e
\ No newline at end of file
tests/testdata/gsm8k-v0-res.json 0 → 100644
View file @ bf19a7a1
{"results": {"gsm8k": {"acc": 0.0, "acc_stderr": 0.0}}, "versions": {"gsm8k": 0}}
\ No newline at end of file
tests/testdata/math_algebra-v1-greedy_until 0 → 100644
View file @ bf19a7a1
f19182ce697a2c095d9e5b56ee6659dc38c93994b69ca75d7c3d3f5fd87572b4
\ No newline at end of file
tests/testdata/math_algebra-v1-res.json 0 → 100644
View file @ bf19a7a1
{"results": {"math_algebra": {"acc": 0.0, "acc_stderr": 0.0}}, "versions": {"math_algebra": 1}}
\ No newline at end of file
tests/testdata/math_counting_and_prob-v1-greedy_until 0 → 100644
View file @ bf19a7a1
2aa9ae43ee9dbb2457525247d7b65358632c5eaa9cbfc40cf95a4f17f5d942ad
\ No newline at end of file
tests/testdata/math_counting_and_prob-v1-res.json 0 → 100644
View file @ bf19a7a1
{"results": {"math_counting_and_prob": {"acc": 0.0, "acc_stderr": 0.0}}, "versions": {"math_counting_and_prob": 1}}
\ No newline at end of file
tests/testdata/math_geometry-v1-greedy_until 0 → 100644
View file @ bf19a7a1
46bc4cb219b6903397da782699a684bdbb982c0c954ff82e6beeed5c84878f42
\ No newline at end of file
tests/testdata/math_geometry-v1-res.json 0 → 100644
View file @ bf19a7a1
{"results": {"math_geometry": {"acc": 0.0, "acc_stderr": 0.0}}, "versions": {"math_geometry": 1}}
\ No newline at end of file
tests/testdata/math_intermediate_algebra-v1-greedy_until 0 → 100644
View file @ bf19a7a1
d53c699de272d517ed7ad783b4e692302be9f9f97a8d4ac7a6541e538a7cabe0
\ No newline at end of file
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