GitLab

* feat: initial commit with templates for evalita evaluation

* fix: change rule for generate_until

* feat: modified yaml to use reduced version of NER test datasets

* feat: added templates to use reduced dataset for summarization (fanpage and ilpost)

* Add Six Prompts for Each Multiple-Choice Task

* fix: fastest eval for summarization

* chore: linted with ruff

* chore: linted with ruff

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Co-authored-by: rzanoli <zanoli@fbk.eu>

Signed-off-by: Lu Fang <lufang@fb.com>

* add subtask scores

* pacify pre-commit

* Add JSON schema benchmark

* Update lm_eval/tasks/jsonschema_bench/metrics.py

Thanks for catching this
Co-authored-by: Baber Abbasi <92168766+baberabb@users.noreply.github.com>

* run pre-commit

* add description to task catalogue readme

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Co-authored-by: Baber Abbasi <92168766+baberabb@users.noreply.github.com>

* sync with leaderboard

* also output old metric

* wrap old extraction in try except

* better log

* llama-style MMLU CoT

* Refactor MMLU CoT template YAML to simplify 'until' structure

* Add GSM8K task configuration for LLaMA3 with few-shot examples

* Fix missing newline at end of MMLU CoT YAML file

* Add ARC-Challenge task configuration and processing utility

* Add additional MMLU and ARC-Challenge task variants to README

* Update README with notes on arc_challenge_llama dataset preprocessing

* Changed default max_length from 2048 to 8192 and max_gen_toks from 256 to 2048 fro MMLU Pro tasks.

* Update lm_eval/tasks/mmlu_pro/_default_template_yaml

* pre-commit

* nit

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* add Darija tasks

* fix multiple groups issue in darijammlu

* add MT to the description of the Darija tasks

* Update README.md

nit

* fix the recursion error caused by the darija_summarization task

* use a custom filter instead of the decorator for the strip function

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Co-authored-by: Baber Abbasi <92168766+baberabb@users.noreply.github.com>

* Adding acpbench task

* adding ACPBench in Tasks readme.

* running precommit

* Multilingual MMLU

* Refactor process_docs function calls for clarity and consistency

I haven't had time to review the library that's replacing tj-actions or whether this change breaks anything, but the vulnerability is quite severe and I would rather the functionality be broken than risk compromise.

**to do:** review this later

* update mmlu_prox configs

* update tasks/README

* correct hyphon to underline in task/README

* update pre-commit codes

* Update generation_kwargs in default template to include additional end tokens

* Update filter_list in MMLU Pro configuration to use strict_match

* Update _default_template_yaml

* Add markdown linter to pre-commit hooks

* Reformat existing markdown (excluding lm_eval/tasks/*.md)

* Update continuation template YAML for MMLU task with new generation and filtering options

* Refactor filter_list structure in continuation template YAML for improved readability

* Add 'take_first' function to filter_list in continuation template YAML

* Update filter_list in continuation template YAML to use 'strict_match' and modify filtering functions

* Add 'do_sample' option to generation_kwargs in MMLU template YAML

* Allow writing confing to wandb

* set defaults

* Update help

* Update help

* add changelog to readme template

* add readme

* add to task list

* add min_pixels, max_pixels

* fix

suport for longcontext (and other synthetic tasks)
* add ruler
* add longbench
* pass `metadata` to TaskConfig

* add MastermindEval benchmark

* fill out checklist

* Add cocoteros_va dataset

* Fix format in cocoteros_va.yml

* Undo newline added

* Execute pre-commit to fix format errors

* Update catalan_bench.yaml version and add Changelog section into Readme.md

* add __version__

* add version consistency check to publish action

* Add support for token-based auth for watsonx models

* Fix lint

* Move dotenv import to inner scope

* Improve readability of _verify_credentials

* Add INCLUDE tasks

* pacify pre-commit

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Co-authored-by: Baber <baber@hey.com>

* Update openllm.yaml to use train fewshot split for arc

* Implementation of Winogender

* Minor fixes README.md

* Add winogender

* Clean winogender utils.py

* Change dataset to one containing All subsets

* Flesh out README for BBQ task

* Add missing tasks for BBQ

* Add simple cooccurrence bias task

* Fix wrong mask for ambiguated context+rename metrics

* Made generate_until evaluation (following PALM paper) default

Also moved separate config files per category to separate metrics using custom function.
Created config file for multiple_choice way of evaluating BBQ.

* Add missing version metadata

* Add missing versionmetadata for bbq multiple choice

* Fix metrics and address edge cases

* Made BBQ multiple choice the default version

* Added settings following winogrande

* Add num_fewshot to simple_cooccurrence_bias

* Fixes for bbq (multiple choice)

* Fix wrong dataset

* CrowS-Pairs: make it easier to use another dataset by removing dataset_name from the subsets.

* Use simplest prompt possible without description

* Merge

* BBQ: Fix np.NaN related bug

* BBQ: Fix wrong aggregation method for disamb accuracy

* BBQ: Make it possible to only evaluate on (dis)ambiguous subset (needed for few shot eval)

* BBQ: fix showing one target in case of few-shot evals

* BBQ: Fix few-shot example for bbq_generate

* BBQ: simplify subtasks

* BBQ: Minimize number of UNK variations to reduce inference time

* BBQ: Add extra UNK keywords for the generate task

* Add a generate_until version of simple_cooccurrence_bias

* Change system/description prompt to include few-shot examples

* Group agg rework

* Run pre-commit

* add tasks to readme table

* remove trailing space from simple_cooccurrence_bias_gen.yaml `doc_to_text`

* fix

* fix

* fix version

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Co-authored-by: Baber <baber@hey.com>