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metadata
annotations_creators:
  - no-annotation
language_creators:
  - expert-generated
language:
  - en
license:
  - mit
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - question-answering
task_ids:
  - multiple-choice-qa
paperswithcode_id: mmlu
pretty_name: Measuring Massive Multitask Language Understanding
language_bcp47:
  - en-US
dataset_info:
  - config_name: abstract_algebra
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  - config_name: all
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  - config_name: anatomy
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  - config_name: astronomy
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  - config_name: business_ethics
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  - config_name: clinical_knowledge
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  - config_name: college_biology
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  - config_name: college_chemistry
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  - config_name: college_computer_science
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  - config_name: college_mathematics
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  - config_name: college_medicine
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  - config_name: college_physics
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  - config_name: computer_security
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  - config_name: conceptual_physics
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  - config_name: econometrics
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  - config_name: electrical_engineering
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  - config_name: elementary_mathematics
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  - config_name: formal_logic
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  - config_name: high_school_biology
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  - config_name: high_school_chemistry
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  - config_name: high_school_computer_science
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  - config_name: high_school_european_history
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  - config_name: high_school_geography
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  - config_name: high_school_government_and_politics
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  - config_name: high_school_macroeconomics
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  - config_name: high_school_mathematics
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  - config_name: high_school_microeconomics
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  - config_name: high_school_psychology
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  - config_name: high_school_statistics
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  - config_name: high_school_us_history
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  - config_name: human_aging
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      - name: subject
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      - name: test
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        num_examples: 223
      - name: validation
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        num_examples: 23
      - name: dev
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        num_examples: 5
    download_size: 47203557
    dataset_size: 161056167
  - config_name: human_sexuality
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      - name: question
        dtype: string
      - name: choices
        sequence: string
      - name: answer
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        num_examples: 99842
      - name: test
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        num_examples: 131
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        num_examples: 12
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        num_examples: 5
    download_size: 166184960
    dataset_size: 160636985
  - config_name: international_law
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      - name: question
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        num_examples: 121
      - name: validation
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    download_size: 166184960
    dataset_size: 160663799
  - config_name: jurisprudence
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      - name: question
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      - name: choices
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        num_examples: 99842
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    download_size: 166184960
    dataset_size: 160640395
  - config_name: logical_fallacies
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        num_examples: 163
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    download_size: 166184960
    dataset_size: 160658170
  - config_name: machine_learning
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      - name: question
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        num_examples: 99842
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        num_examples: 112
      - name: validation
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        num_examples: 11
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    download_size: 166184960
    dataset_size: 160640812
  - config_name: management
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        num_examples: 99842
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        num_examples: 103
      - name: validation
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    download_size: 166184960
    dataset_size: 160624097
  - config_name: marketing
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      - name: choices
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        num_examples: 99842
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      - name: validation
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    download_size: 166184960
    dataset_size: 160673277
  - config_name: medical_genetics
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        num_examples: 100
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    download_size: 166184960
    dataset_size: 160626335
  - config_name: miscellaneous
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    download_size: 166184960
    dataset_size: 160764110
  - config_name: moral_disputes
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        num_examples: 99842
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        num_examples: 346
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        num_examples: 38
      - name: dev
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    download_size: 166184960
    dataset_size: 160723370
  - config_name: moral_scenarios
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      - name: choices
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        num_examples: 100
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    download_size: 166184960
    dataset_size: 161019799
  - config_name: nutrition
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        num_examples: 99842
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        num_examples: 306
      - name: validation
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    download_size: 166184960
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  - config_name: philosophy
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        num_examples: 311
      - name: validation
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      - name: dev
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    download_size: 166184960
    dataset_size: 160691622
  - config_name: prehistory
    features:
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      - name: choices
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    download_size: 166184960
    dataset_size: 160703134
  - config_name: professional_accounting
    features:
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      - name: choices
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        num_examples: 99842
      - name: test
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        num_examples: 282
      - name: validation
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        num_examples: 31
      - name: dev
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        num_examples: 5
    download_size: 166184960
    dataset_size: 160742447
  - config_name: professional_law
    features:
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      - name: choices
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        num_examples: 170
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    download_size: 166184960
    dataset_size: 162703268
  - config_name: professional_medicine
    features:
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      - name: choices
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        num_examples: 99842
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        num_examples: 31
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    download_size: 166184960
    dataset_size: 160846592
  - config_name: professional_psychology
    features:
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      - name: choices
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        num_examples: 99842
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        num_examples: 612
      - name: validation
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        num_examples: 69
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    download_size: 166184960
    dataset_size: 160858644
  - config_name: public_relations
    features:
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      - name: choices
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        num_examples: 99842
      - name: test
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        num_examples: 110
      - name: validation
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    download_size: 166184960
    dataset_size: 160636199
  - config_name: security_studies
    features:
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              '3': D
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        num_examples: 99842
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        num_examples: 245
      - name: validation
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        num_examples: 27
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    download_size: 166184960
    dataset_size: 160834193
  - config_name: sociology
    features:
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        dtype: string
      - name: choices
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        num_examples: 99842
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        num_examples: 201
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    download_size: 166184960
    dataset_size: 160676417
  - config_name: us_foreign_policy
    features:
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      - name: choices
        sequence: string
      - name: answer
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        num_examples: 99842
      - name: test
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        num_examples: 100
      - name: validation
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        num_examples: 11
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        num_examples: 5
    download_size: 166184960
    dataset_size: 160634695
  - config_name: virology
    features:
      - name: question
        dtype: string
      - name: choices
        sequence: string
      - name: answer
        dtype:
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    splits:
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        num_examples: 99842
      - name: test
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      - name: validation
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    download_size: 166184960
    dataset_size: 160646695
  - config_name: world_religions
    features:
      - name: question
        dtype: string
      - name: choices
        sequence: string
      - name: answer
        dtype:
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            names:
              '0': A
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              '2': C
              '3': D
    splits:
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        num_examples: 99842
      - name: test
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        num_examples: 171
      - name: validation
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        num_examples: 19
      - name: dev
        num_bytes: 670
        num_examples: 5
    download_size: 166184960
    dataset_size: 160630086
configs:
  - config_name: abstract_algebra
    data_files:
      - split: auxiliary_train
        path: abstract_algebra/auxiliary_train-*
      - split: test
        path: abstract_algebra/test-*
      - split: validation
        path: abstract_algebra/validation-*
      - split: dev
        path: abstract_algebra/dev-*
  - config_name: all
    data_files:
      - split: auxiliary_train
        path: all/auxiliary_train-*
      - split: test
        path: all/test-*
      - split: validation
        path: all/validation-*
      - split: dev
        path: all/dev-*
  - config_name: anatomy
    data_files:
      - split: auxiliary_train
        path: anatomy/auxiliary_train-*
      - split: test
        path: anatomy/test-*
      - split: validation
        path: anatomy/validation-*
      - split: dev
        path: anatomy/dev-*
  - config_name: astronomy
    data_files:
      - split: auxiliary_train
        path: astronomy/auxiliary_train-*
      - split: test
        path: astronomy/test-*
      - split: validation
        path: astronomy/validation-*
      - split: dev
        path: astronomy/dev-*
  - config_name: business_ethics
    data_files:
      - split: auxiliary_train
        path: business_ethics/auxiliary_train-*
      - split: test
        path: business_ethics/test-*
      - split: validation
        path: business_ethics/validation-*
      - split: dev
        path: business_ethics/dev-*
  - config_name: clinical_knowledge
    data_files:
      - split: auxiliary_train
        path: clinical_knowledge/auxiliary_train-*
      - split: test
        path: clinical_knowledge/test-*
      - split: validation
        path: clinical_knowledge/validation-*
      - split: dev
        path: clinical_knowledge/dev-*
  - config_name: college_biology
    data_files:
      - split: auxiliary_train
        path: college_biology/auxiliary_train-*
      - split: test
        path: college_biology/test-*
      - split: validation
        path: college_biology/validation-*
      - split: dev
        path: college_biology/dev-*
  - config_name: college_chemistry
    data_files:
      - split: auxiliary_train
        path: college_chemistry/auxiliary_train-*
      - split: test
        path: college_chemistry/test-*
      - split: validation
        path: college_chemistry/validation-*
      - split: dev
        path: college_chemistry/dev-*
  - config_name: college_computer_science
    data_files:
      - split: auxiliary_train
        path: college_computer_science/auxiliary_train-*
      - split: test
        path: college_computer_science/test-*
      - split: validation
        path: college_computer_science/validation-*
      - split: dev
        path: college_computer_science/dev-*
  - config_name: college_mathematics
    data_files:
      - split: auxiliary_train
        path: college_mathematics/auxiliary_train-*
      - split: test
        path: college_mathematics/test-*
      - split: validation
        path: college_mathematics/validation-*
      - split: dev
        path: college_mathematics/dev-*
  - config_name: college_medicine
    data_files:
      - split: auxiliary_train
        path: college_medicine/auxiliary_train-*
      - split: test
        path: college_medicine/test-*
      - split: validation
        path: college_medicine/validation-*
      - split: dev
        path: college_medicine/dev-*
  - config_name: college_physics
    data_files:
      - split: auxiliary_train
        path: college_physics/auxiliary_train-*
      - split: test
        path: college_physics/test-*
      - split: validation
        path: college_physics/validation-*
      - split: dev
        path: college_physics/dev-*
  - config_name: computer_security
    data_files:
      - split: auxiliary_train
        path: computer_security/auxiliary_train-*
      - split: test
        path: computer_security/test-*
      - split: validation
        path: computer_security/validation-*
      - split: dev
        path: computer_security/dev-*
  - config_name: conceptual_physics
    data_files:
      - split: auxiliary_train
        path: conceptual_physics/auxiliary_train-*
      - split: test
        path: conceptual_physics/test-*
      - split: validation
        path: conceptual_physics/validation-*
      - split: dev
        path: conceptual_physics/dev-*
  - config_name: econometrics
    data_files:
      - split: auxiliary_train
        path: econometrics/auxiliary_train-*
      - split: test
        path: econometrics/test-*
      - split: validation
        path: econometrics/validation-*
      - split: dev
        path: econometrics/dev-*
  - config_name: electrical_engineering
    data_files:
      - split: auxiliary_train
        path: electrical_engineering/auxiliary_train-*
      - split: test
        path: electrical_engineering/test-*
      - split: validation
        path: electrical_engineering/validation-*
      - split: dev
        path: electrical_engineering/dev-*
  - config_name: elementary_mathematics
    data_files:
      - split: auxiliary_train
        path: elementary_mathematics/auxiliary_train-*
      - split: test
        path: elementary_mathematics/test-*
      - split: validation
        path: elementary_mathematics/validation-*
      - split: dev
        path: elementary_mathematics/dev-*
  - config_name: formal_logic
    data_files:
      - split: auxiliary_train
        path: formal_logic/auxiliary_train-*
      - split: test
        path: formal_logic/test-*
      - split: validation
        path: formal_logic/validation-*
      - split: dev
        path: formal_logic/dev-*
  - config_name: global_facts
    data_files:
      - split: auxiliary_train
        path: global_facts/auxiliary_train-*
      - split: test
        path: global_facts/test-*
      - split: validation
        path: global_facts/validation-*
      - split: dev
        path: global_facts/dev-*
  - config_name: high_school_biology
    data_files:
      - split: auxiliary_train
        path: high_school_biology/auxiliary_train-*
      - split: test
        path: high_school_biology/test-*
      - split: validation
        path: high_school_biology/validation-*
      - split: dev
        path: high_school_biology/dev-*
  - config_name: high_school_chemistry
    data_files:
      - split: auxiliary_train
        path: high_school_chemistry/auxiliary_train-*
      - split: test
        path: high_school_chemistry/test-*
      - split: validation
        path: high_school_chemistry/validation-*
      - split: dev
        path: high_school_chemistry/dev-*
  - config_name: high_school_computer_science
    data_files:
      - split: auxiliary_train
        path: high_school_computer_science/auxiliary_train-*
      - split: test
        path: high_school_computer_science/test-*
      - split: validation
        path: high_school_computer_science/validation-*
      - split: dev
        path: high_school_computer_science/dev-*
  - config_name: high_school_european_history
    data_files:
      - split: auxiliary_train
        path: high_school_european_history/auxiliary_train-*
      - split: test
        path: high_school_european_history/test-*
      - split: validation
        path: high_school_european_history/validation-*
      - split: dev
        path: high_school_european_history/dev-*
  - config_name: high_school_geography
    data_files:
      - split: auxiliary_train
        path: high_school_geography/auxiliary_train-*
      - split: test
        path: high_school_geography/test-*
      - split: validation
        path: high_school_geography/validation-*
      - split: dev
        path: high_school_geography/dev-*
  - config_name: high_school_government_and_politics
    data_files:
      - split: auxiliary_train
        path: high_school_government_and_politics/auxiliary_train-*
      - split: test
        path: high_school_government_and_politics/test-*
      - split: validation
        path: high_school_government_and_politics/validation-*
      - split: dev
        path: high_school_government_and_politics/dev-*
  - config_name: high_school_macroeconomics
    data_files:
      - split: auxiliary_train
        path: high_school_macroeconomics/auxiliary_train-*
      - split: test
        path: high_school_macroeconomics/test-*
      - split: validation
        path: high_school_macroeconomics/validation-*
      - split: dev
        path: high_school_macroeconomics/dev-*
  - config_name: high_school_mathematics
    data_files:
      - split: auxiliary_train
        path: high_school_mathematics/auxiliary_train-*
      - split: test
        path: high_school_mathematics/test-*
      - split: validation
        path: high_school_mathematics/validation-*
      - split: dev
        path: high_school_mathematics/dev-*
  - config_name: high_school_microeconomics
    data_files:
      - split: auxiliary_train
        path: high_school_microeconomics/auxiliary_train-*
      - split: test
        path: high_school_microeconomics/test-*
      - split: validation
        path: high_school_microeconomics/validation-*
      - split: dev
        path: high_school_microeconomics/dev-*
  - config_name: high_school_physics
    data_files:
      - split: auxiliary_train
        path: high_school_physics/auxiliary_train-*
      - split: test
        path: high_school_physics/test-*
      - split: validation
        path: high_school_physics/validation-*
      - split: dev
        path: high_school_physics/dev-*
  - config_name: high_school_psychology
    data_files:
      - split: auxiliary_train
        path: high_school_psychology/auxiliary_train-*
      - split: test
        path: high_school_psychology/test-*
      - split: validation
        path: high_school_psychology/validation-*
      - split: dev
        path: high_school_psychology/dev-*
  - config_name: high_school_statistics
    data_files:
      - split: auxiliary_train
        path: high_school_statistics/auxiliary_train-*
      - split: test
        path: high_school_statistics/test-*
      - split: validation
        path: high_school_statistics/validation-*
      - split: dev
        path: high_school_statistics/dev-*
  - config_name: high_school_us_history
    data_files:
      - split: auxiliary_train
        path: high_school_us_history/auxiliary_train-*
      - split: test
        path: high_school_us_history/test-*
      - split: validation
        path: high_school_us_history/validation-*
      - split: dev
        path: high_school_us_history/dev-*
  - config_name: high_school_world_history
    data_files:
      - split: auxiliary_train
        path: high_school_world_history/auxiliary_train-*
      - split: test
        path: high_school_world_history/test-*
      - split: validation
        path: high_school_world_history/validation-*
      - split: dev
        path: high_school_world_history/dev-*
  - config_name: human_aging
    data_files:
      - split: auxiliary_train
        path: human_aging/auxiliary_train-*
      - split: test
        path: human_aging/test-*
      - split: validation
        path: human_aging/validation-*
      - split: dev
        path: human_aging/dev-*

Dataset Card for MMLU

Table of Contents

Dataset Description

Dataset Summary

Measuring Massive Multitask Language Understanding by Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt (ICLR 2021).

This is a massive multitask test consisting of multiple-choice questions from various branches of knowledge. The test spans subjects in the humanities, social sciences, hard sciences, and other areas that are important for some people to learn. This covers 57 tasks including elementary mathematics, US history, computer science, law, and more. To attain high accuracy on this test, models must possess extensive world knowledge and problem solving ability.

A complete list of tasks: ['abstract_algebra', 'anatomy', 'astronomy', 'business_ethics', 'clinical_knowledge', 'college_biology', 'college_chemistry', 'college_computer_science', 'college_mathematics', 'college_medicine', 'college_physics', 'computer_security', 'conceptual_physics', 'econometrics', 'electrical_engineering', 'elementary_mathematics', 'formal_logic', 'global_facts', 'high_school_biology', 'high_school_chemistry', 'high_school_computer_science', 'high_school_european_history', 'high_school_geography', 'high_school_government_and_politics', 'high_school_macroeconomics', 'high_school_mathematics', 'high_school_microeconomics', 'high_school_physics', 'high_school_psychology', 'high_school_statistics', 'high_school_us_history', 'high_school_world_history', 'human_aging', 'human_sexuality', 'international_law', 'jurisprudence', 'logical_fallacies', 'machine_learning', 'management', 'marketing', 'medical_genetics', 'miscellaneous', 'moral_disputes', 'moral_scenarios', 'nutrition', 'philosophy', 'prehistory', 'professional_accounting', 'professional_law', 'professional_medicine', 'professional_psychology', 'public_relations', 'security_studies', 'sociology', 'us_foreign_policy', 'virology', 'world_religions']

Supported Tasks and Leaderboards

Model Authors Humanities Social Science STEM Other Average
UnifiedQA Khashabi et al., 2020 45.6 56.6 40.2 54.6 48.9
GPT-3 (few-shot) Brown et al., 2020 40.8 50.4 36.7 48.8 43.9
GPT-2 Radford et al., 2019 32.8 33.3 30.2 33.1 32.4
Random Baseline N/A 25.0 25.0 25.0 25.0 25.0

Languages

English

Dataset Structure

Data Instances

An example from anatomy subtask looks as follows:

{
  "question": "What is the embryological origin of the hyoid bone?",
  "choices": ["The first pharyngeal arch", "The first and second pharyngeal arches", "The second pharyngeal arch", "The second and third pharyngeal arches"],
  "answer": "D"
}

Data Fields

  • question: a string feature
  • choices: a list of 4 string features
  • answer: a ClassLabel feature

Data Splits

  • auxiliary_train: auxiliary multiple-choice training questions from ARC, MC_TEST, OBQA, RACE, etc.
  • dev: 5 examples per subtask, meant for few-shot setting
  • test: there are at least 100 examples per subtask
auxiliary_train dev val test
TOTAL 99842 285 1531 14042

Dataset Creation

Curation Rationale

Transformer models have driven this recent progress by pretraining on massive text corpora, including all of Wikipedia, thousands of books, and numerous websites. These models consequently see extensive information about specialized topics, most of which is not assessed by existing NLP benchmarks. To bridge the gap between the wide-ranging knowledge that models see during pretraining and the existing measures of success, we introduce a new benchmark for assessing models across a diverse set of subjects that humans learn.

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

MIT License

Citation Information

If you find this useful in your research, please consider citing the test and also the ETHICS dataset it draws from:

    @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}
    }

Contributions

Thanks to @andyzoujm for adding this dataset.