MMLU_PROΒΆ

NAME = MMLU_PRO
DATASET_PATH = TIGER-Lab/MMLU-Pro
SAMPLE_SPLIT = test
FEWSHOT_SPLIT = test
RESPONSE_TYPE = LOGLIKELIHOODS
METRICS = [AccuracyLoglikelihood, AccuracyNormLoglikelihood]
SUBJECTS = ['engineering', 'physics', 'psychology', 'chemistry', 'biology', 'law', 'philosophy', 'computer science', 'other', 'economics', 'business', 'history', 'math', 'health']
LANGUAGE = <Language.ENG: 'English'>

More detailed documentation, with prompt examples and ground truth completions, can be generated with uv run -m eval_framework.utils.generate_task_docs --add-prompt-examples --only-tasks "MMLU_PRO".