[ { "title": "Accuracy", "header": [ { "value": "Model", "markdown": false, "metadata": {} }, { "value": "MMLU All Subjects - EM", "description": "The Massive Multitask Language Understanding (MMLU) benchmark for knowledge-intensive question answering across 57 domains [(Hendrycks et al., 2021)](https://arxiv.org/pdf/2009.03300.pdf).\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "MMLU All Subjects" } }, { "value": "Abstract Algebra - EM", "description": "The abstract algebra subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Abstract Algebra" } }, { "value": "Anatomy - EM", "description": "The anatomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Anatomy" } }, { "value": "College Chemistry - EM", "description": "The college chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "College Chemistry" } }, { "value": "Computer Security - EM", "description": "The computer security subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Computer Security" } }, { "value": "Econometrics - EM", "description": "The econometrics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Econometrics" } }, { "value": "Global Facts - EM", "description": "The global facts subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Global Facts" } }, { "value": "Jurisprudence - EM", "description": "The jurisprudence subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Jurisprudence" } }, { "value": "Philosophy - EM", "description": "The philosophy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Philosophy" } }, { "value": "Professional Medicine - EM", "description": "The professional medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Professional Medicine" } }, { "value": "Us Foreign Policy - EM", "description": "The us foreign policy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Us Foreign Policy" } }, { "value": "Astronomy - EM", "description": "The astronomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Astronomy" } }, { "value": "Business Ethics - EM", "description": "The business ethics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Business Ethics" } }, { "value": "Clinical Knowledge - EM", "description": "The clinical knowledge subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Clinical Knowledge" } }, { "value": "College Biology - EM", "description": "The college biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "College Biology" } }, { "value": "College Computer Science - EM", "description": "The college computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "College Computer Science" } }, { "value": "College Mathematics - EM", "description": "The college mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "College Mathematics" } }, { "value": "College Medicine - EM", "description": "The college medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "College Medicine" } }, { "value": "College Physics - EM", "description": "The college physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "College Physics" } }, { "value": "Conceptual Physics - EM", "description": "The conceptual physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Conceptual Physics" } }, { "value": "Electrical Engineering - EM", "description": "The electrical engineering subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Electrical Engineering" } }, { "value": "Elementary Mathematics - EM", "description": "The elementary mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Elementary Mathematics" } }, { "value": "Formal Logic - EM", "description": "The formal logic subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Formal Logic" } }, { "value": "High School Biology - EM", "description": "The high school biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Biology" } }, { "value": "High School Chemistry - EM", "description": "The high school chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Chemistry" } }, { "value": "High School Computer Science - EM", "description": "The high school computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Computer Science" } }, { "value": "High School European History - EM", "description": "The high school european history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School European History" } }, { "value": "High School Geography - EM", "description": "The high school geography subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Geography" } }, { "value": "High School Government And Politics - EM", "description": "The high school government and politics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Government And Politics" } }, { "value": "High School Macroeconomics - EM", "description": "The high school macroeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Macroeconomics" } }, { "value": "High School Mathematics - EM", "description": "The high school mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Mathematics" } }, { "value": "High School Microeconomics - EM", "description": "The high school microeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Microeconomics" } }, { "value": "High School Physics - EM", "description": "The high school physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Physics" } }, { "value": "High School Psychology - EM", "description": "The high school psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Psychology" } }, { "value": "High School Statistics - EM", "description": "The high school statistics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School Statistics" } }, { "value": "High School US History - EM", "description": "The high school us history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School US History" } }, { "value": "High School World History - EM", "description": "The high school world history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "High School World History" } }, { "value": "Human Aging - EM", "description": "The human aging subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Human Aging" } }, { "value": "Human Sexuality - EM", "description": "The human sexuality subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Human Sexuality" } }, { "value": "International Law - EM", "description": "The international law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "International Law" } }, { "value": "Logical Fallacies - EM", "description": "The logical fallacies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Logical Fallacies" } }, { "value": "Machine Learning - EM", "description": "The machine learning subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Machine Learning" } }, { "value": "Management - EM", "description": "The management subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Management" } }, { "value": "Marketing - EM", "description": "The marketing subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Marketing" } }, { "value": "Medical Genetics - EM", "description": "The medical genetics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Medical Genetics" } }, { "value": "Miscellaneous - EM", "description": "The miscellaneous subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Miscellaneous" } }, { "value": "Moral Disputes - EM", "description": "The moral disputes subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Moral Disputes" } }, { "value": "Moral Scenarios - EM", "description": "The moral scenarios subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Moral Scenarios" } }, { "value": "Nutrition - EM", "description": "The nutrition subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Nutrition" } }, { "value": "Prehistory - EM", "description": "The prehistory subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Prehistory" } }, { "value": "Professional Accounting - EM", "description": "The professional accounting subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Professional Accounting" } }, { "value": "Professional Law - EM", "description": "The professional law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Professional Law" } }, { "value": "Professional Psychology - EM", "description": "The professional psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Professional Psychology" } }, { "value": "Public Relations - EM", "description": "The public relations subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Public Relations" } }, { "value": "Security Studies - EM", "description": "The security studies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Security Studies" } }, { "value": "Sociology - EM", "description": "The sociology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Sociology" } }, { "value": "Virology - EM", "description": "The virology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "Virology" } }, { "value": "World Religions - EM", "description": "The world religions subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nExact match: Fraction of instances that the predicted output matches a correct reference exactly.", "markdown": false, "lower_is_better": false, "metadata": { "metric": "EM", "run_group": "World Religions" } } ], "rows": [ [ { "value": "Gemma 2 (27B)", "description": "", "markdown": false }, { "value": 0.757043394397764, "description": "min=0.394, mean=0.757, max=0.979, sum=86.303 (114)", "style": {}, "markdown": false, "run_spec_names": [ "mmlu:subject=abstract_algebra,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_abstract_algebra", "mmlu:subject=anatomy,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_anatomy", "mmlu:subject=astronomy,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_astronomy", "mmlu:subject=business_ethics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_business_ethics", "mmlu:subject=clinical_knowledge,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_clinical_knowledge", "mmlu:subject=college_biology,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_biology", "mmlu:subject=college_chemistry,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_chemistry", "mmlu:subject=college_computer_science,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_computer_science", "mmlu:subject=college_mathematics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_mathematics", "mmlu:subject=college_medicine,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_medicine", "mmlu:subject=college_physics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_physics", "mmlu:subject=computer_security,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_computer_security", "mmlu:subject=conceptual_physics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_conceptual_physics", "mmlu:subject=econometrics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_econometrics", "mmlu:subject=electrical_engineering,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_electrical_engineering", "mmlu:subject=elementary_mathematics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_elementary_mathematics", "mmlu:subject=formal_logic,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_formal_logic", "mmlu:subject=global_facts,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_global_facts", "mmlu:subject=high_school_biology,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_biology", "mmlu:subject=high_school_chemistry,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_chemistry", "mmlu:subject=high_school_computer_science,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_computer_science", "mmlu:subject=high_school_european_history,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_european_history", "mmlu:subject=high_school_geography,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_geography", "mmlu:subject=high_school_government_and_politics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_government_and_politics", "mmlu:subject=high_school_macroeconomics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_macroeconomics", "mmlu:subject=high_school_mathematics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_mathematics", "mmlu:subject=high_school_microeconomics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_microeconomics", "mmlu:subject=high_school_physics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_physics", "mmlu:subject=high_school_psychology,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_psychology", "mmlu:subject=high_school_statistics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_statistics", "mmlu:subject=high_school_us_history,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_us_history", "mmlu:subject=high_school_world_history,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_high_school_world_history", "mmlu:subject=human_aging,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_human_aging", "mmlu:subject=human_sexuality,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_human_sexuality", "mmlu:subject=international_law,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_international_law", "mmlu:subject=jurisprudence,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_jurisprudence", 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columns).", "markdown": false, "lower_is_better": false, "metadata": {} }, { "value": "MMLU All Subjects - Observed inference time (s)", "description": "The Massive Multitask Language Understanding (MMLU) benchmark for knowledge-intensive question answering across 57 domains [(Hendrycks et al., 2021)](https://arxiv.org/pdf/2009.03300.pdf).\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "MMLU All Subjects" } }, { "value": "Abstract Algebra - Observed inference time (s)", "description": "The abstract algebra subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Abstract Algebra" } }, { "value": "Anatomy - Observed inference time (s)", "description": "The anatomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Anatomy" } }, { "value": "College Chemistry - Observed inference time (s)", "description": "The college chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "College Chemistry" } }, { "value": "Computer Security - Observed inference time (s)", "description": "The computer security subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Computer Security" } }, { "value": "Econometrics - Observed inference time (s)", "description": "The econometrics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Econometrics" } }, { "value": "Global Facts - Observed inference time (s)", "description": "The global facts subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Global Facts" } }, { "value": "Jurisprudence - Observed inference time (s)", "description": "The jurisprudence subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Jurisprudence" } }, { "value": "Philosophy - Observed inference time (s)", "description": "The philosophy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Philosophy" } }, { "value": "Professional Medicine - Observed inference time (s)", "description": "The professional medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Professional Medicine" } }, { "value": "Us Foreign Policy - Observed inference time (s)", "description": "The us foreign policy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Us Foreign Policy" } }, { "value": "Astronomy - Observed inference time (s)", "description": "The astronomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Astronomy" } }, { "value": "Business Ethics - Observed inference time (s)", "description": "The business ethics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Business Ethics" } }, { "value": "Clinical Knowledge - Observed inference time (s)", "description": "The clinical knowledge subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Clinical Knowledge" } }, { "value": "College Biology - Observed inference time (s)", "description": "The college biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "College Biology" } }, { "value": "College Computer Science - Observed inference time (s)", "description": "The college computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "College Computer Science" } }, { "value": "College Mathematics - Observed inference time (s)", "description": "The college mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "College Mathematics" } }, { "value": "College Medicine - Observed inference time (s)", "description": "The college medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "College Medicine" } }, { "value": "College Physics - Observed inference time (s)", "description": "The college physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "College Physics" } }, { "value": "Conceptual Physics - Observed inference time (s)", "description": "The conceptual physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Conceptual Physics" } }, { "value": "Electrical Engineering - Observed inference time (s)", "description": "The electrical engineering subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Electrical Engineering" } }, { "value": "Elementary Mathematics - Observed inference time (s)", "description": "The elementary mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Elementary Mathematics" } }, { "value": "Formal Logic - Observed inference time (s)", "description": "The formal logic subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Formal Logic" } }, { "value": "High School Biology - Observed inference time (s)", "description": "The high school biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Biology" } }, { "value": "High School Chemistry - Observed inference time (s)", "description": "The high school chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Chemistry" } }, { "value": "High School Computer Science - Observed inference time (s)", "description": "The high school computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Computer Science" } }, { "value": "High School European History - Observed inference time (s)", "description": "The high school european history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School European History" } }, { "value": "High School Geography - Observed inference time (s)", "description": "The high school geography subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Geography" } }, { "value": "High School Government And Politics - Observed inference time (s)", "description": "The high school government and politics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Government And Politics" } }, { "value": "High School Macroeconomics - Observed inference time (s)", "description": "The high school macroeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Macroeconomics" } }, { "value": "High School Mathematics - Observed inference time (s)", "description": "The high school mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Mathematics" } }, { "value": "High School Microeconomics - Observed inference time (s)", "description": "The high school microeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Microeconomics" } }, { "value": "High School Physics - Observed inference time (s)", "description": "The high school physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Physics" } }, { "value": "High School Psychology - Observed inference time (s)", "description": "The high school psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Psychology" } }, { "value": "High School Statistics - Observed inference time (s)", "description": "The high school statistics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School Statistics" } }, { "value": "High School US History - Observed inference time (s)", "description": "The high school us history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School US History" } }, { "value": "High School World History - Observed inference time (s)", "description": "The high school world history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "High School World History" } }, { "value": "Human Aging - Observed inference time (s)", "description": "The human aging subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Human Aging" } }, { "value": "Human Sexuality - Observed inference time (s)", "description": "The human sexuality subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Human Sexuality" } }, { "value": "International Law - Observed inference time (s)", "description": "The international law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "International Law" } }, { "value": "Logical Fallacies - Observed inference time (s)", "description": "The logical fallacies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Logical Fallacies" } }, { "value": "Machine Learning - Observed inference time (s)", "description": "The machine learning subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Machine Learning" } }, { "value": "Management - Observed inference time (s)", "description": "The management subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Management" } }, { "value": "Marketing - Observed inference time (s)", "description": "The marketing subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Marketing" } }, { "value": "Medical Genetics - Observed inference time (s)", "description": "The medical genetics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Medical Genetics" } }, { "value": "Miscellaneous - Observed inference time (s)", "description": "The miscellaneous subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Miscellaneous" } }, { "value": "Moral Disputes - Observed inference time (s)", "description": "The moral disputes subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Moral Disputes" } }, { "value": "Moral Scenarios - Observed inference time (s)", "description": "The moral scenarios subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Moral Scenarios" } }, { "value": "Nutrition - Observed inference time (s)", "description": "The nutrition subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Nutrition" } }, { "value": "Prehistory - Observed inference time (s)", "description": "The prehistory subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Prehistory" } }, { "value": "Professional Accounting - Observed inference time (s)", "description": "The professional accounting subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Professional Accounting" } }, { "value": "Professional Law - Observed inference time (s)", "description": "The professional law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Professional Law" } }, { "value": "Professional Psychology - Observed inference time (s)", "description": "The professional psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Professional Psychology" } }, { "value": "Public Relations - Observed inference time (s)", "description": "The public relations subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Public Relations" } }, { "value": "Security Studies - Observed inference time (s)", "description": "The security studies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Security Studies" } }, { "value": "Sociology - Observed inference time (s)", "description": "The sociology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Sociology" } }, { "value": "Virology - Observed inference time (s)", "description": "The virology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "Virology" } }, { "value": "World Religions - Observed inference time (s)", "description": "The world religions subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\nObserved inference runtime (s): Average observed time to process a request to the model (via an API, and thus depends on particular deployment).", "markdown": false, "lower_is_better": true, "metadata": { "metric": "Observed inference time (s)", "run_group": "World Religions" } } ], "rows": [ [ { "value": "Gemma 2 (27B)", "description": "", "markdown": false }, { "value": 0.05017683465959328, "markdown": false }, { "value": 2.7443855864562217, "description": "min=1.169, mean=2.744, max=12.207, sum=312.86 (114)", "style": {}, "markdown": false, "run_spec_names": [ "mmlu:subject=abstract_algebra,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_abstract_algebra", "mmlu:subject=anatomy,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_anatomy", "mmlu:subject=astronomy,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_astronomy", "mmlu:subject=business_ethics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_business_ethics", "mmlu:subject=clinical_knowledge,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_clinical_knowledge", "mmlu:subject=college_biology,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_biology", "mmlu:subject=college_chemistry,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_chemistry", "mmlu:subject=college_computer_science,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_computer_science", "mmlu:subject=college_mathematics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_mathematics", "mmlu:subject=college_medicine,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_medicine", "mmlu:subject=college_physics,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_college_physics", "mmlu:subject=computer_security,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_computer_security", 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Algebra" } }, { "value": "Abstract Algebra - # output tokens", "description": "The abstract algebra subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Abstract Algebra" } }, { "value": "Anatomy - # eval", "description": "The anatomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Anatomy" } }, { "value": "Anatomy - # train", "description": "The anatomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Anatomy" } }, { "value": "Anatomy - truncated", "description": "The anatomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Anatomy" } }, { "value": "Anatomy - # prompt tokens", "description": "The anatomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Anatomy" } }, { "value": "Anatomy - # output tokens", "description": "The anatomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Anatomy" } }, { "value": "College Chemistry - # eval", "description": "The college chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "College Chemistry" } }, { "value": "College Chemistry - # train", "description": "The college chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "College Chemistry" } }, { "value": "College Chemistry - truncated", "description": "The college chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "College Chemistry" } }, { "value": "College Chemistry - # prompt tokens", "description": "The college chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "College Chemistry" } }, { "value": "College Chemistry - # output tokens", "description": "The college chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "College Chemistry" } }, { "value": "Computer Security - # eval", "description": "The computer security subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Computer Security" } }, { "value": "Computer Security - # train", "description": "The computer security subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Computer Security" } }, { "value": "Computer Security - truncated", "description": "The computer security subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Computer Security" } }, { "value": "Computer Security - # prompt tokens", "description": "The computer security subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Computer Security" } }, { "value": "Computer Security - # output tokens", "description": "The computer security subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Computer Security" } }, { "value": "Econometrics - # eval", "description": "The econometrics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Econometrics" } }, { "value": "Econometrics - # train", "description": "The econometrics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Econometrics" } }, { "value": "Econometrics - truncated", "description": "The econometrics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Econometrics" } }, { "value": "Econometrics - # prompt tokens", "description": "The econometrics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Econometrics" } }, { "value": "Econometrics - # output tokens", "description": "The econometrics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Econometrics" } }, { "value": "Global Facts - # eval", "description": "The global facts subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Global Facts" } }, { "value": "Global Facts - # train", "description": "The global facts subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Global Facts" } }, { "value": "Global Facts - truncated", "description": "The global facts subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Global Facts" } }, { "value": "Global Facts - # prompt tokens", "description": "The global facts subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Global Facts" } }, { "value": "Global Facts - # output tokens", "description": "The global facts subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Global Facts" } }, { "value": "Jurisprudence - # eval", "description": "The jurisprudence subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Jurisprudence" } }, { "value": "Jurisprudence - # train", "description": "The jurisprudence subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Jurisprudence" } }, { "value": "Jurisprudence - truncated", "description": "The jurisprudence subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Jurisprudence" } }, { "value": "Jurisprudence - # prompt tokens", "description": "The jurisprudence subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Jurisprudence" } }, { "value": "Jurisprudence - # output tokens", "description": "The jurisprudence subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Jurisprudence" } }, { "value": "Philosophy - # eval", "description": "The philosophy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Philosophy" } }, { "value": "Philosophy - # train", "description": "The philosophy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Philosophy" } }, { "value": "Philosophy - truncated", "description": "The philosophy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Philosophy" } }, { "value": "Philosophy - # prompt tokens", "description": "The philosophy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Philosophy" } }, { "value": "Philosophy - # output tokens", "description": "The philosophy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Philosophy" } }, { "value": "Professional Medicine - # eval", "description": "The professional medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Professional Medicine" } }, { "value": "Professional Medicine - # train", "description": "The professional medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Professional Medicine" } }, { "value": "Professional Medicine - truncated", "description": "The professional medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Professional Medicine" } }, { "value": "Professional Medicine - # prompt tokens", "description": "The professional medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Professional Medicine" } }, { "value": "Professional Medicine - # output tokens", "description": "The professional medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Professional Medicine" } }, { "value": "Us Foreign Policy - # eval", "description": "The us foreign policy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Us Foreign Policy" } }, { "value": "Us Foreign Policy - # train", "description": "The us foreign policy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Us Foreign Policy" } }, { "value": "Us Foreign Policy - truncated", "description": "The us foreign policy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Us Foreign Policy" } }, { "value": "Us Foreign Policy - # prompt tokens", "description": "The us foreign policy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Us Foreign Policy" } }, { "value": "Us Foreign Policy - # output tokens", "description": "The us foreign policy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Us Foreign Policy" } }, { "value": "Astronomy - # eval", "description": "The astronomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Astronomy" } }, { "value": "Astronomy - # train", "description": "The astronomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Astronomy" } }, { "value": "Astronomy - truncated", "description": "The astronomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Astronomy" } }, { "value": "Astronomy - # prompt tokens", "description": "The astronomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Astronomy" } }, { "value": "Astronomy - # output tokens", "description": "The astronomy subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Astronomy" } }, { "value": "Business Ethics - # eval", "description": "The business ethics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Business Ethics" } }, { "value": "Business Ethics - # train", "description": "The business ethics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Business Ethics" } }, { "value": "Business Ethics - truncated", "description": "The business ethics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Business Ethics" } }, { "value": "Business Ethics - # prompt tokens", "description": "The business ethics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Business Ethics" } }, { "value": "Business Ethics - # output tokens", "description": "The business ethics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Business Ethics" } }, { "value": "Clinical Knowledge - # eval", "description": "The clinical knowledge subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Clinical Knowledge" } }, { "value": "Clinical Knowledge - # train", "description": "The clinical knowledge subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Clinical Knowledge" } }, { "value": "Clinical Knowledge - truncated", "description": "The clinical knowledge subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Clinical Knowledge" } }, { "value": "Clinical Knowledge - # prompt tokens", "description": "The clinical knowledge subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Clinical Knowledge" } }, { "value": "Clinical Knowledge - # output tokens", "description": "The clinical knowledge subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Clinical Knowledge" } }, { "value": "College Biology - # eval", "description": "The college biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "College Biology" } }, { "value": "College Biology - # train", "description": "The college biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "College Biology" } }, { "value": "College Biology - truncated", "description": "The college biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "College Biology" } }, { "value": "College Biology - # prompt tokens", "description": "The college biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "College Biology" } }, { "value": "College Biology - # output tokens", "description": "The college biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "College Biology" } }, { "value": "College Computer Science - # eval", "description": "The college computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "College Computer Science" } }, { "value": "College Computer Science - # train", "description": "The college computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "College Computer Science" } }, { "value": "College Computer Science - truncated", "description": "The college computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "College Computer Science" } }, { "value": "College Computer Science - # prompt tokens", "description": "The college computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "College Computer Science" } }, { "value": "College Computer Science - # output tokens", "description": "The college computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "College Computer Science" } }, { "value": "College Mathematics - # eval", "description": "The college mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "College Mathematics" } }, { "value": "College Mathematics - # train", "description": "The college mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "College Mathematics" } }, { "value": "College Mathematics - truncated", "description": "The college mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "College Mathematics" } }, { "value": "College Mathematics - # prompt tokens", "description": "The college mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "College Mathematics" } }, { "value": "College Mathematics - # output tokens", "description": "The college mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "College Mathematics" } }, { "value": "College Medicine - # eval", "description": "The college medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "College Medicine" } }, { "value": "College Medicine - # train", "description": "The college medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "College Medicine" } }, { "value": "College Medicine - truncated", "description": "The college medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "College Medicine" } }, { "value": "College Medicine - # prompt tokens", "description": "The college medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "College Medicine" } }, { "value": "College Medicine - # output tokens", "description": "The college medicine subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "College Medicine" } }, { "value": "College Physics - # eval", "description": "The college physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "College Physics" } }, { "value": "College Physics - # train", "description": "The college physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "College Physics" } }, { "value": "College Physics - truncated", "description": "The college physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "College Physics" } }, { "value": "College Physics - # prompt tokens", "description": "The college physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "College Physics" } }, { "value": "College Physics - # output tokens", "description": "The college physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "College Physics" } }, { "value": "Conceptual Physics - # eval", "description": "The conceptual physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Conceptual Physics" } }, { "value": "Conceptual Physics - # train", "description": "The conceptual physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Conceptual Physics" } }, { "value": "Conceptual Physics - truncated", "description": "The conceptual physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Conceptual Physics" } }, { "value": "Conceptual Physics - # prompt tokens", "description": "The conceptual physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Conceptual Physics" } }, { "value": "Conceptual Physics - # output tokens", "description": "The conceptual physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Conceptual Physics" } }, { "value": "Electrical Engineering - # eval", "description": "The electrical engineering subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Electrical Engineering" } }, { "value": "Electrical Engineering - # train", "description": "The electrical engineering subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Electrical Engineering" } }, { "value": "Electrical Engineering - truncated", "description": "The electrical engineering subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Electrical Engineering" } }, { "value": "Electrical Engineering - # prompt tokens", "description": "The electrical engineering subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Electrical Engineering" } }, { "value": "Electrical Engineering - # output tokens", "description": "The electrical engineering subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Electrical Engineering" } }, { "value": "Elementary Mathematics - # eval", "description": "The elementary mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Elementary Mathematics" } }, { "value": "Elementary Mathematics - # train", "description": "The elementary mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Elementary Mathematics" } }, { "value": "Elementary Mathematics - truncated", "description": "The elementary mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Elementary Mathematics" } }, { "value": "Elementary Mathematics - # prompt tokens", "description": "The elementary mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Elementary Mathematics" } }, { "value": "Elementary Mathematics - # output tokens", "description": "The elementary mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Elementary Mathematics" } }, { "value": "Formal Logic - # eval", "description": "The formal logic subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Formal Logic" } }, { "value": "Formal Logic - # train", "description": "The formal logic subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Formal Logic" } }, { "value": "Formal Logic - truncated", "description": "The formal logic subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Formal Logic" } }, { "value": "Formal Logic - # prompt tokens", "description": "The formal logic subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Formal Logic" } }, { "value": "Formal Logic - # output tokens", "description": "The formal logic subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Formal Logic" } }, { "value": "High School Biology - # eval", "description": "The high school biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Biology" } }, { "value": "High School Biology - # train", "description": "The high school biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Biology" } }, { "value": "High School Biology - truncated", "description": "The high school biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Biology" } }, { "value": "High School Biology - # prompt tokens", "description": "The high school biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Biology" } }, { "value": "High School Biology - # output tokens", "description": "The high school biology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Biology" } }, { "value": "High School Chemistry - # eval", "description": "The high school chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Chemistry" } }, { "value": "High School Chemistry - # train", "description": "The high school chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Chemistry" } }, { "value": "High School Chemistry - truncated", "description": "The high school chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Chemistry" } }, { "value": "High School Chemistry - # prompt tokens", "description": "The high school chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Chemistry" } }, { "value": "High School Chemistry - # output tokens", "description": "The high school chemistry subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Chemistry" } }, { "value": "High School Computer Science - # eval", "description": "The high school computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Computer Science" } }, { "value": "High School Computer Science - # train", "description": "The high school computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Computer Science" } }, { "value": "High School Computer Science - truncated", "description": "The high school computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Computer Science" } }, { "value": "High School Computer Science - # prompt tokens", "description": "The high school computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Computer Science" } }, { "value": "High School Computer Science - # output tokens", "description": "The high school computer science subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Computer Science" } }, { "value": "High School European History - # eval", "description": "The high school european history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School European History" } }, { "value": "High School European History - # train", "description": "The high school european history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School European History" } }, { "value": "High School European History - truncated", "description": "The high school european history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School European History" } }, { "value": "High School European History - # prompt tokens", "description": "The high school european history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School European History" } }, { "value": "High School European History - # output tokens", "description": "The high school european history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School European History" } }, { "value": "High School Geography - # eval", "description": "The high school geography subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Geography" } }, { "value": "High School Geography - # train", "description": "The high school geography subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Geography" } }, { "value": "High School Geography - truncated", "description": "The high school geography subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Geography" } }, { "value": "High School Geography - # prompt tokens", "description": "The high school geography subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Geography" } }, { "value": "High School Geography - # output tokens", "description": "The high school geography subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Geography" } }, { "value": "High School Government And Politics - # eval", "description": "The high school government and politics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Government And Politics" } }, { "value": "High School Government And Politics - # train", "description": "The high school government and politics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Government And Politics" } }, { "value": "High School Government And Politics - truncated", "description": "The high school government and politics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Government And Politics" } }, { "value": "High School Government And Politics - # prompt tokens", "description": "The high school government and politics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Government And Politics" } }, { "value": "High School Government And Politics - # output tokens", "description": "The high school government and politics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Government And Politics" } }, { "value": "High School Macroeconomics - # eval", "description": "The high school macroeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Macroeconomics" } }, { "value": "High School Macroeconomics - # train", "description": "The high school macroeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Macroeconomics" } }, { "value": "High School Macroeconomics - truncated", "description": "The high school macroeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Macroeconomics" } }, { "value": "High School Macroeconomics - # prompt tokens", "description": "The high school macroeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Macroeconomics" } }, { "value": "High School Macroeconomics - # output tokens", "description": "The high school macroeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Macroeconomics" } }, { "value": "High School Mathematics - # eval", "description": "The high school mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Mathematics" } }, { "value": "High School Mathematics - # train", "description": "The high school mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Mathematics" } }, { "value": "High School Mathematics - truncated", "description": "The high school mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Mathematics" } }, { "value": "High School Mathematics - # prompt tokens", "description": "The high school mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Mathematics" } }, { "value": "High School Mathematics - # output tokens", "description": "The high school mathematics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Mathematics" } }, { "value": "High School Microeconomics - # eval", "description": "The high school microeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Microeconomics" } }, { "value": "High School Microeconomics - # train", "description": "The high school microeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Microeconomics" } }, { "value": "High School Microeconomics - truncated", "description": "The high school microeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Microeconomics" } }, { "value": "High School Microeconomics - # prompt tokens", "description": "The high school microeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Microeconomics" } }, { "value": "High School Microeconomics - # output tokens", "description": "The high school microeconomics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Microeconomics" } }, { "value": "High School Physics - # eval", "description": "The high school physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Physics" } }, { "value": "High School Physics - # train", "description": "The high school physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Physics" } }, { "value": "High School Physics - truncated", "description": "The high school physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Physics" } }, { "value": "High School Physics - # prompt tokens", "description": "The high school physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Physics" } }, { "value": "High School Physics - # output tokens", "description": "The high school physics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Physics" } }, { "value": "High School Psychology - # eval", "description": "The high school psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Psychology" } }, { "value": "High School Psychology - # train", "description": "The high school psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Psychology" } }, { "value": "High School Psychology - truncated", "description": "The high school psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Psychology" } }, { "value": "High School Psychology - # prompt tokens", "description": "The high school psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Psychology" } }, { "value": "High School Psychology - # output tokens", "description": "The high school psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Psychology" } }, { "value": "High School Statistics - # eval", "description": "The high school statistics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School Statistics" } }, { "value": "High School Statistics - # train", "description": "The high school statistics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School Statistics" } }, { "value": "High School Statistics - truncated", "description": "The high school statistics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School Statistics" } }, { "value": "High School Statistics - # prompt tokens", "description": "The high school statistics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School Statistics" } }, { "value": "High School Statistics - # output tokens", "description": "The high school statistics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School Statistics" } }, { "value": "High School US History - # eval", "description": "The high school us history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School US History" } }, { "value": "High School US History - # train", "description": "The high school us history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School US History" } }, { "value": "High School US History - truncated", "description": "The high school us history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School US History" } }, { "value": "High School US History - # prompt tokens", "description": "The high school us history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School US History" } }, { "value": "High School US History - # output tokens", "description": "The high school us history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School US History" } }, { "value": "High School World History - # eval", "description": "The high school world history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "High School World History" } }, { "value": "High School World History - # train", "description": "The high school world history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "High School World History" } }, { "value": "High School World History - truncated", "description": "The high school world history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "High School World History" } }, { "value": "High School World History - # prompt tokens", "description": "The high school world history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "High School World History" } }, { "value": "High School World History - # output tokens", "description": "The high school world history subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "High School World History" } }, { "value": "Human Aging - # eval", "description": "The human aging subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Human Aging" } }, { "value": "Human Aging - # train", "description": "The human aging subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Human Aging" } }, { "value": "Human Aging - truncated", "description": "The human aging subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Human Aging" } }, { "value": "Human Aging - # prompt tokens", "description": "The human aging subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Human Aging" } }, { "value": "Human Aging - # output tokens", "description": "The human aging subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Human Aging" } }, { "value": "Human Sexuality - # eval", "description": "The human sexuality subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Human Sexuality" } }, { "value": "Human Sexuality - # train", "description": "The human sexuality subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Human Sexuality" } }, { "value": "Human Sexuality - truncated", "description": "The human sexuality subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Human Sexuality" } }, { "value": "Human Sexuality - # prompt tokens", "description": "The human sexuality subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Human Sexuality" } }, { "value": "Human Sexuality - # output tokens", "description": "The human sexuality subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Human Sexuality" } }, { "value": "International Law - # eval", "description": "The international law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "International Law" } }, { "value": "International Law - # train", "description": "The international law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "International Law" } }, { "value": "International Law - truncated", "description": "The international law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "International Law" } }, { "value": "International Law - # prompt tokens", "description": "The international law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "International Law" } }, { "value": "International Law - # output tokens", "description": "The international law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "International Law" } }, { "value": "Logical Fallacies - # eval", "description": "The logical fallacies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Logical Fallacies" } }, { "value": "Logical Fallacies - # train", "description": "The logical fallacies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Logical Fallacies" } }, { "value": "Logical Fallacies - truncated", "description": "The logical fallacies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Logical Fallacies" } }, { "value": "Logical Fallacies - # prompt tokens", "description": "The logical fallacies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Logical Fallacies" } }, { "value": "Logical Fallacies - # output tokens", "description": "The logical fallacies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Logical Fallacies" } }, { "value": "Machine Learning - # eval", "description": "The machine learning subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Machine Learning" } }, { "value": "Machine Learning - # train", "description": "The machine learning subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Machine Learning" } }, { "value": "Machine Learning - truncated", "description": "The machine learning subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Machine Learning" } }, { "value": "Machine Learning - # prompt tokens", "description": "The machine learning subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Machine Learning" } }, { "value": "Machine Learning - # output tokens", "description": "The machine learning subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Machine Learning" } }, { "value": "Management - # eval", "description": "The management subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Management" } }, { "value": "Management - # train", "description": "The management subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Management" } }, { "value": "Management - truncated", "description": "The management subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Management" } }, { "value": "Management - # prompt tokens", "description": "The management subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Management" } }, { "value": "Management - # output tokens", "description": "The management subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Management" } }, { "value": "Marketing - # eval", "description": "The marketing subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Marketing" } }, { "value": "Marketing - # train", "description": "The marketing subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Marketing" } }, { "value": "Marketing - truncated", "description": "The marketing subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Marketing" } }, { "value": "Marketing - # prompt tokens", "description": "The marketing subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Marketing" } }, { "value": "Marketing - # output tokens", "description": "The marketing subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Marketing" } }, { "value": "Medical Genetics - # eval", "description": "The medical genetics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Medical Genetics" } }, { "value": "Medical Genetics - # train", "description": "The medical genetics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Medical Genetics" } }, { "value": "Medical Genetics - truncated", "description": "The medical genetics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Medical Genetics" } }, { "value": "Medical Genetics - # prompt tokens", "description": "The medical genetics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Medical Genetics" } }, { "value": "Medical Genetics - # output tokens", "description": "The medical genetics subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Medical Genetics" } }, { "value": "Miscellaneous - # eval", "description": "The miscellaneous subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Miscellaneous" } }, { "value": "Miscellaneous - # train", "description": "The miscellaneous subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Miscellaneous" } }, { "value": "Miscellaneous - truncated", "description": "The miscellaneous subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Miscellaneous" } }, { "value": "Miscellaneous - # prompt tokens", "description": "The miscellaneous subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Miscellaneous" } }, { "value": "Miscellaneous - # output tokens", "description": "The miscellaneous subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Miscellaneous" } }, { "value": "Moral Disputes - # eval", "description": "The moral disputes subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Moral Disputes" } }, { "value": "Moral Disputes - # train", "description": "The moral disputes subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Moral Disputes" } }, { "value": "Moral Disputes - truncated", "description": "The moral disputes subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Moral Disputes" } }, { "value": "Moral Disputes - # prompt tokens", "description": "The moral disputes subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Moral Disputes" } }, { "value": "Moral Disputes - # output tokens", "description": "The moral disputes subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Moral Disputes" } }, { "value": "Moral Scenarios - # eval", "description": "The moral scenarios subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Moral Scenarios" } }, { "value": "Moral Scenarios - # train", "description": "The moral scenarios subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Moral Scenarios" } }, { "value": "Moral Scenarios - truncated", "description": "The moral scenarios subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Moral Scenarios" } }, { "value": "Moral Scenarios - # prompt tokens", "description": "The moral scenarios subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Moral Scenarios" } }, { "value": "Moral Scenarios - # output tokens", "description": "The moral scenarios subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Moral Scenarios" } }, { "value": "Nutrition - # eval", "description": "The nutrition subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Nutrition" } }, { "value": "Nutrition - # train", "description": "The nutrition subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Nutrition" } }, { "value": "Nutrition - truncated", "description": "The nutrition subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Nutrition" } }, { "value": "Nutrition - # prompt tokens", "description": "The nutrition subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Nutrition" } }, { "value": "Nutrition - # output tokens", "description": "The nutrition subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Nutrition" } }, { "value": "Prehistory - # eval", "description": "The prehistory subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Prehistory" } }, { "value": "Prehistory - # train", "description": "The prehistory subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Prehistory" } }, { "value": "Prehistory - truncated", "description": "The prehistory subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Prehistory" } }, { "value": "Prehistory - # prompt tokens", "description": "The prehistory subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Prehistory" } }, { "value": "Prehistory - # output tokens", "description": "The prehistory subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Prehistory" } }, { "value": "Professional Accounting - # eval", "description": "The professional accounting subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Professional Accounting" } }, { "value": "Professional Accounting - # train", "description": "The professional accounting subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Professional Accounting" } }, { "value": "Professional Accounting - truncated", "description": "The professional accounting subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Professional Accounting" } }, { "value": "Professional Accounting - # prompt tokens", "description": "The professional accounting subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Professional Accounting" } }, { "value": "Professional Accounting - # output tokens", "description": "The professional accounting subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Professional Accounting" } }, { "value": "Professional Law - # eval", "description": "The professional law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Professional Law" } }, { "value": "Professional Law - # train", "description": "The professional law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Professional Law" } }, { "value": "Professional Law - truncated", "description": "The professional law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Professional Law" } }, { "value": "Professional Law - # prompt tokens", "description": "The professional law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Professional Law" } }, { "value": "Professional Law - # output tokens", "description": "The professional law subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Professional Law" } }, { "value": "Professional Psychology - # eval", "description": "The professional psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Professional Psychology" } }, { "value": "Professional Psychology - # train", "description": "The professional psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Professional Psychology" } }, { "value": "Professional Psychology - truncated", "description": "The professional psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Professional Psychology" } }, { "value": "Professional Psychology - # prompt tokens", "description": "The professional psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Professional Psychology" } }, { "value": "Professional Psychology - # output tokens", "description": "The professional psychology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Professional Psychology" } }, { "value": "Public Relations - # eval", "description": "The public relations subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Public Relations" } }, { "value": "Public Relations - # train", "description": "The public relations subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Public Relations" } }, { "value": "Public Relations - truncated", "description": "The public relations subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Public Relations" } }, { "value": "Public Relations - # prompt tokens", "description": "The public relations subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Public Relations" } }, { "value": "Public Relations - # output tokens", "description": "The public relations subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Public Relations" } }, { "value": "Security Studies - # eval", "description": "The security studies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Security Studies" } }, { "value": "Security Studies - # train", "description": "The security studies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Security Studies" } }, { "value": "Security Studies - truncated", "description": "The security studies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Security Studies" } }, { "value": "Security Studies - # prompt tokens", "description": "The security studies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Security Studies" } }, { "value": "Security Studies - # output tokens", "description": "The security studies subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Security Studies" } }, { "value": "Sociology - # eval", "description": "The sociology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Sociology" } }, { "value": "Sociology - # train", "description": "The sociology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Sociology" } }, { "value": "Sociology - truncated", "description": "The sociology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Sociology" } }, { "value": "Sociology - # prompt tokens", "description": "The sociology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Sociology" } }, { "value": "Sociology - # output tokens", "description": "The sociology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Sociology" } }, { "value": "Virology - # eval", "description": "The virology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "Virology" } }, { "value": "Virology - # train", "description": "The virology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "Virology" } }, { "value": "Virology - truncated", "description": "The virology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "Virology" } }, { "value": "Virology - # prompt tokens", "description": "The virology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "Virology" } }, { "value": "Virology - # output tokens", "description": "The virology subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "Virology" } }, { "value": "World Religions - # eval", "description": "The world religions subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# eval: Number of evaluation instances.", "markdown": false, "metadata": { "metric": "# eval", "run_group": "World Religions" } }, { "value": "World Religions - # train", "description": "The world religions subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# train: Number of training instances (e.g., in-context examples).", "markdown": false, "metadata": { "metric": "# train", "run_group": "World Religions" } }, { "value": "World Religions - truncated", "description": "The world religions subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", "markdown": false, "metadata": { "metric": "truncated", "run_group": "World Religions" } }, { "value": "World Religions - # prompt tokens", "description": "The world religions subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# prompt tokens: Number of tokens in the prompt.", "markdown": false, "metadata": { "metric": "# prompt tokens", "run_group": "World Religions" } }, { "value": "World Religions - # output tokens", "description": "The world religions subject in the Massive Multitask Language Understanding (MMLU) benchmark.\n\n# output tokens: Actual number of output tokens.", "markdown": false, "metadata": { "metric": "# output tokens", "run_group": "World Religions" } } ], "rows": [ [ { "value": "Gemma 2 (27B)", "description": "", "markdown": false }, { "value": 246.35087719298247, "description": "min=100, mean=246.351, max=1534, sum=28084 (114)", "style": {}, "markdown": false, "run_spec_names": [ "mmlu:subject=abstract_algebra,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_abstract_algebra", "mmlu:subject=anatomy,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_anatomy", "mmlu:subject=astronomy,method=multiple_choice_joint,model=google_gemma-2-27b,eval_split=test,groups=mmlu_astronomy", 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