{ "results": { "mmlu": { "acc,none": 0.7060959977211223, "acc_stderr,none": 0.0036419117884613442, "alias": "mmlu" }, "mmlu_humanities": { "alias": " - humanities", "acc,none": 0.6561105207226355, "acc_stderr,none": 0.006537667125056556 }, "mmlu_formal_logic": { "alias": " - formal_logic", "acc,none": 0.5793650793650794, "acc_stderr,none": 0.04415438226743745 }, "mmlu_high_school_european_history": { "alias": " - high_school_european_history", "acc,none": 0.8181818181818182, "acc_stderr,none": 0.030117688929503582 }, "mmlu_high_school_us_history": { "alias": " - high_school_us_history", "acc,none": 0.8627450980392157, "acc_stderr,none": 0.024152225962801577 }, "mmlu_high_school_world_history": { "alias": " - high_school_world_history", "acc,none": 0.8565400843881856, "acc_stderr,none": 0.022818291821017012 }, "mmlu_international_law": { "alias": " - international_law", "acc,none": 0.8512396694214877, "acc_stderr,none": 0.03248470083807195 }, "mmlu_jurisprudence": { "alias": " - jurisprudence", "acc,none": 0.8518518518518519, "acc_stderr,none": 0.03434300243631002 }, "mmlu_logical_fallacies": { "alias": " - logical_fallacies", "acc,none": 0.7975460122699386, "acc_stderr,none": 0.031570650789119 }, "mmlu_moral_disputes": { "alias": " - moral_disputes", "acc,none": 0.7947976878612717, "acc_stderr,none": 0.021742519835276274 }, "mmlu_moral_scenarios": { "alias": " - moral_scenarios", "acc,none": 0.4983240223463687, "acc_stderr,none": 0.016722407608296398 }, "mmlu_philosophy": { "alias": " - philosophy", "acc,none": 0.7942122186495176, "acc_stderr,none": 0.022961339906764234 }, "mmlu_prehistory": { "alias": " - prehistory", "acc,none": 0.7993827160493827, "acc_stderr,none": 0.0222823139497749 }, "mmlu_professional_law": { "alias": " - professional_law", "acc,none": 0.516297262059974, "acc_stderr,none": 0.012763450734699812 }, "mmlu_world_religions": { "alias": " - world_religions", "acc,none": 0.9122807017543859, "acc_stderr,none": 0.021696383943889223 }, "mmlu_other": { "alias": " - other", "acc,none": 0.7608625683939492, "acc_stderr,none": 0.007354391095553756 }, "mmlu_business_ethics": { "alias": " - business_ethics", "acc,none": 0.77, "acc_stderr,none": 0.04229525846816506 }, "mmlu_clinical_knowledge": { "alias": " - clinical_knowledge", "acc,none": 0.7735849056603774, "acc_stderr,none": 0.025757559893106758 }, "mmlu_college_medicine": { "alias": " - college_medicine", "acc,none": 0.7398843930635838, "acc_stderr,none": 0.033450369167889904 }, "mmlu_global_facts": { "alias": " - global_facts", "acc,none": 0.45, "acc_stderr,none": 0.05 }, "mmlu_human_aging": { "alias": " - human_aging", "acc,none": 0.7533632286995515, "acc_stderr,none": 0.028930413120910874 }, "mmlu_management": { "alias": " - management", "acc,none": 0.8543689320388349, "acc_stderr,none": 0.0349260647662379 }, "mmlu_marketing": { "alias": " - marketing", "acc,none": 0.9145299145299145, "acc_stderr,none": 0.01831589168562584 }, "mmlu_medical_genetics": { "alias": " - medical_genetics", "acc,none": 0.77, "acc_stderr,none": 0.042295258468165065 }, "mmlu_miscellaneous": { "alias": " - miscellaneous", "acc,none": 0.8518518518518519, "acc_stderr,none": 0.012703598899445173 }, "mmlu_nutrition": { "alias": " - nutrition", "acc,none": 0.7908496732026143, "acc_stderr,none": 0.02328768531233481 }, "mmlu_professional_accounting": { "alias": " - professional_accounting", "acc,none": 0.5319148936170213, "acc_stderr,none": 0.029766675075873866 }, "mmlu_professional_medicine": { "alias": " - professional_medicine", "acc,none": 0.7794117647058824, "acc_stderr,none": 0.02518778666022727 }, "mmlu_virology": { "alias": " - virology", "acc,none": 0.5481927710843374, "acc_stderr,none": 0.038743715565879536 }, "mmlu_social_sciences": { "alias": " - social_sciences", "acc,none": 0.8059798505037374, "acc_stderr,none": 0.007000549787458337 }, "mmlu_econometrics": { "alias": " - econometrics", "acc,none": 0.6052631578947368, "acc_stderr,none": 0.04598188057816542 }, "mmlu_high_school_geography": { "alias": " - high_school_geography", "acc,none": 0.8636363636363636, "acc_stderr,none": 0.024450155973189835 }, "mmlu_high_school_government_and_politics": { "alias": " - high_school_government_and_politics", "acc,none": 0.9378238341968912, "acc_stderr,none": 0.017426974154240514 }, "mmlu_high_school_macroeconomics": { "alias": " - high_school_macroeconomics", "acc,none": 0.7230769230769231, "acc_stderr,none": 0.022688042352424994 }, "mmlu_high_school_microeconomics": { "alias": " - high_school_microeconomics", "acc,none": 0.8109243697478992, "acc_stderr,none": 0.02543511943810537 }, "mmlu_high_school_psychology": { "alias": " - high_school_psychology", "acc,none": 0.8844036697247707, "acc_stderr,none": 0.013708749534172636 }, "mmlu_human_sexuality": { "alias": " - human_sexuality", "acc,none": 0.7709923664122137, "acc_stderr,none": 0.036853466317118506 }, "mmlu_professional_psychology": { "alias": " - professional_psychology", "acc,none": 0.7532679738562091, "acc_stderr,none": 0.0174408203674025 }, "mmlu_public_relations": { "alias": " - public_relations", "acc,none": 0.7363636363636363, "acc_stderr,none": 0.04220224692971987 }, "mmlu_security_studies": { "alias": " - security_studies", "acc,none": 0.7877551020408163, "acc_stderr,none": 0.026176967197866767 }, "mmlu_sociology": { "alias": " - sociology", "acc,none": 0.8756218905472637, "acc_stderr,none": 0.023335401790166327 }, "mmlu_us_foreign_policy": { "alias": " - us_foreign_policy", "acc,none": 0.9, "acc_stderr,none": 0.030151134457776348 }, "mmlu_stem": { "alias": " - stem", "acc,none": 0.6292419917538852, "acc_stderr,none": 0.00828854335131971 }, "mmlu_abstract_algebra": { "alias": " - abstract_algebra", "acc,none": 0.4, "acc_stderr,none": 0.049236596391733084 }, "mmlu_anatomy": { "alias": " - anatomy", "acc,none": 0.6518518518518519, "acc_stderr,none": 0.041153246103369526 }, "mmlu_astronomy": { "alias": " - astronomy", "acc,none": 0.8026315789473685, "acc_stderr,none": 0.03238981601699397 }, "mmlu_college_biology": { "alias": " - college_biology", "acc,none": 0.8402777777777778, "acc_stderr,none": 0.030635578972093278 }, "mmlu_college_chemistry": { "alias": " - college_chemistry", "acc,none": 0.5, "acc_stderr,none": 0.050251890762960605 }, "mmlu_college_computer_science": { "alias": " - college_computer_science", "acc,none": 0.64, "acc_stderr,none": 0.04824181513244218 }, "mmlu_college_mathematics": { "alias": " - college_mathematics", "acc,none": 0.47, "acc_stderr,none": 0.050161355804659205 }, "mmlu_college_physics": { "alias": " - college_physics", "acc,none": 0.49019607843137253, "acc_stderr,none": 0.04974229460422817 }, "mmlu_computer_security": { "alias": " - computer_security", "acc,none": 0.8, "acc_stderr,none": 0.040201512610368445 }, "mmlu_conceptual_physics": { "alias": " - conceptual_physics", "acc,none": 0.6978723404255319, "acc_stderr,none": 0.030017554471880557 }, "mmlu_electrical_engineering": { "alias": " - electrical_engineering", "acc,none": 0.6827586206896552, "acc_stderr,none": 0.03878352372138622 }, "mmlu_elementary_mathematics": { "alias": " - elementary_mathematics", "acc,none": 0.5582010582010583, "acc_stderr,none": 0.025576257061253833 }, "mmlu_high_school_biology": { "alias": " - high_school_biology", "acc,none": 0.8064516129032258, "acc_stderr,none": 0.02247525852553606 }, "mmlu_high_school_chemistry": { "alias": " - high_school_chemistry", "acc,none": 0.5566502463054187, "acc_stderr,none": 0.03495334582162933 }, "mmlu_high_school_computer_science": { "alias": " - high_school_computer_science", "acc,none": 0.8, "acc_stderr,none": 0.04020151261036846 }, "mmlu_high_school_mathematics": { "alias": " - high_school_mathematics", "acc,none": 0.44074074074074077, "acc_stderr,none": 0.030270671157284074 }, "mmlu_high_school_physics": { "alias": " - high_school_physics", "acc,none": 0.4768211920529801, "acc_stderr,none": 0.04078093859163084 }, "mmlu_high_school_statistics": { "alias": " - high_school_statistics", "acc,none": 0.6898148148148148, "acc_stderr,none": 0.03154696285656629 }, "mmlu_machine_learning": { "alias": " - machine_learning", "acc,none": 0.5803571428571429, "acc_stderr,none": 0.04684099321077106 } }, "groups": { "mmlu": { "acc,none": 0.7060959977211223, "acc_stderr,none": 0.0036419117884613442, "alias": "mmlu" }, "mmlu_humanities": { "alias": " - humanities", "acc,none": 0.6561105207226355, "acc_stderr,none": 0.006537667125056556 }, "mmlu_other": { "alias": " - other", "acc,none": 0.7608625683939492, "acc_stderr,none": 0.007354391095553756 }, "mmlu_social_sciences": { "alias": " - social_sciences", "acc,none": 0.8059798505037374, "acc_stderr,none": 0.007000549787458337 }, "mmlu_stem": { "alias": " - stem", "acc,none": 0.6292419917538852, "acc_stderr,none": 0.00828854335131971 } }, "group_subtasks": { "mmlu_stem": [ "mmlu_college_computer_science", "mmlu_high_school_physics", "mmlu_college_chemistry", "mmlu_college_biology", "mmlu_high_school_mathematics", "mmlu_high_school_computer_science", "mmlu_electrical_engineering", "mmlu_college_physics", "mmlu_anatomy", "mmlu_college_mathematics", "mmlu_elementary_mathematics", "mmlu_high_school_chemistry", "mmlu_machine_learning", "mmlu_abstract_algebra", "mmlu_astronomy", "mmlu_computer_security", "mmlu_high_school_biology", "mmlu_high_school_statistics", "mmlu_conceptual_physics" ], "mmlu_other": [ "mmlu_business_ethics", "mmlu_virology", "mmlu_nutrition", "mmlu_management", "mmlu_clinical_knowledge", "mmlu_marketing", "mmlu_college_medicine", "mmlu_professional_medicine", "mmlu_medical_genetics", "mmlu_human_aging", "mmlu_professional_accounting", "mmlu_miscellaneous", "mmlu_global_facts" ], "mmlu_social_sciences": [ "mmlu_high_school_government_and_politics", "mmlu_human_sexuality", "mmlu_high_school_microeconomics", "mmlu_high_school_macroeconomics", "mmlu_public_relations", "mmlu_sociology", "mmlu_professional_psychology", "mmlu_high_school_psychology", "mmlu_econometrics", "mmlu_high_school_geography", "mmlu_us_foreign_policy", "mmlu_security_studies" ], "mmlu_humanities": [ "mmlu_high_school_european_history", "mmlu_high_school_world_history", "mmlu_professional_law", "mmlu_logical_fallacies", "mmlu_high_school_us_history", "mmlu_world_religions", "mmlu_prehistory", "mmlu_jurisprudence", "mmlu_moral_scenarios", "mmlu_formal_logic", "mmlu_philosophy", "mmlu_international_law", "mmlu_moral_disputes" ], "mmlu": [ "mmlu_humanities", "mmlu_social_sciences", "mmlu_other", "mmlu_stem" ] }, "configs": { "mmlu_abstract_algebra": { "task": "mmlu_abstract_algebra", "task_alias": "abstract_algebra", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "abstract_algebra", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_anatomy": { "task": "mmlu_anatomy", "task_alias": "anatomy", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "anatomy", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about anatomy.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_astronomy": { "task": "mmlu_astronomy", "task_alias": "astronomy", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "astronomy", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about astronomy.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_business_ethics": { "task": "mmlu_business_ethics", "task_alias": "business_ethics", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "business_ethics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about business ethics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_clinical_knowledge": { "task": "mmlu_clinical_knowledge", "task_alias": "clinical_knowledge", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "clinical_knowledge", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_college_biology": { "task": "mmlu_college_biology", "task_alias": "college_biology", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_biology", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college biology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_college_chemistry": { "task": "mmlu_college_chemistry", "task_alias": "college_chemistry", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_chemistry", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_college_computer_science": { "task": "mmlu_college_computer_science", "task_alias": "college_computer_science", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_computer_science", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college computer science.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_college_mathematics": { "task": "mmlu_college_mathematics", "task_alias": "college_mathematics", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_mathematics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_college_medicine": { "task": "mmlu_college_medicine", "task_alias": "college_medicine", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_medicine", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college medicine.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_college_physics": { "task": "mmlu_college_physics", "task_alias": "college_physics", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_physics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college physics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_computer_security": { "task": "mmlu_computer_security", "task_alias": "computer_security", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "computer_security", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about computer security.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_conceptual_physics": { "task": "mmlu_conceptual_physics", "task_alias": "conceptual_physics", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "conceptual_physics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_econometrics": { "task": "mmlu_econometrics", "task_alias": "econometrics", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "econometrics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about econometrics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_electrical_engineering": { "task": "mmlu_electrical_engineering", "task_alias": "electrical_engineering", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "electrical_engineering", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_elementary_mathematics": { "task": "mmlu_elementary_mathematics", "task_alias": "elementary_mathematics", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "elementary_mathematics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_formal_logic": { "task": "mmlu_formal_logic", "task_alias": "formal_logic", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "formal_logic", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about formal logic.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_global_facts": { "task": "mmlu_global_facts", "task_alias": "global_facts", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "global_facts", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about global facts.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_biology": { "task": "mmlu_high_school_biology", "task_alias": "high_school_biology", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_biology", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school biology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_chemistry": { "task": "mmlu_high_school_chemistry", "task_alias": "high_school_chemistry", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_chemistry", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_computer_science": { "task": "mmlu_high_school_computer_science", "task_alias": "high_school_computer_science", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_computer_science", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_european_history": { "task": "mmlu_high_school_european_history", "task_alias": "high_school_european_history", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_european_history", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school european history.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_geography": { "task": "mmlu_high_school_geography", "task_alias": "high_school_geography", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_geography", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school geography.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_government_and_politics": { "task": "mmlu_high_school_government_and_politics", "task_alias": "high_school_government_and_politics", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_government_and_politics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_macroeconomics": { "task": "mmlu_high_school_macroeconomics", "task_alias": "high_school_macroeconomics", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_macroeconomics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_mathematics": { "task": "mmlu_high_school_mathematics", "task_alias": "high_school_mathematics", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_mathematics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_microeconomics": { "task": "mmlu_high_school_microeconomics", "task_alias": "high_school_microeconomics", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_microeconomics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_physics": { "task": "mmlu_high_school_physics", "task_alias": "high_school_physics", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_physics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school physics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_psychology": { "task": "mmlu_high_school_psychology", "task_alias": "high_school_psychology", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_psychology", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_statistics": { "task": "mmlu_high_school_statistics", "task_alias": "high_school_statistics", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_statistics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_us_history": { "task": "mmlu_high_school_us_history", "task_alias": "high_school_us_history", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_us_history", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school us history.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_high_school_world_history": { "task": "mmlu_high_school_world_history", "task_alias": "high_school_world_history", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_world_history", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school world history.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_human_aging": { "task": "mmlu_human_aging", "task_alias": "human_aging", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "human_aging", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about human aging.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_human_sexuality": { "task": "mmlu_human_sexuality", "task_alias": "human_sexuality", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "human_sexuality", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_international_law": { "task": "mmlu_international_law", "task_alias": "international_law", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "international_law", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about international law.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_jurisprudence": { "task": "mmlu_jurisprudence", "task_alias": "jurisprudence", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "jurisprudence", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_logical_fallacies": { "task": "mmlu_logical_fallacies", "task_alias": "logical_fallacies", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "logical_fallacies", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_machine_learning": { "task": "mmlu_machine_learning", "task_alias": "machine_learning", "group": "mmlu_stem", "group_alias": "stem", "dataset_path": "hails/mmlu_no_train", "dataset_name": "machine_learning", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about machine learning.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_management": { "task": "mmlu_management", "task_alias": "management", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "management", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about management.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_marketing": { "task": "mmlu_marketing", "task_alias": "marketing", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "marketing", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about marketing.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_medical_genetics": { "task": "mmlu_medical_genetics", "task_alias": "medical_genetics", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "medical_genetics", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_miscellaneous": { "task": "mmlu_miscellaneous", "task_alias": "miscellaneous", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "miscellaneous", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_moral_disputes": { "task": "mmlu_moral_disputes", "task_alias": "moral_disputes", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "moral_disputes", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_moral_scenarios": { "task": "mmlu_moral_scenarios", "task_alias": "moral_scenarios", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "moral_scenarios", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_nutrition": { "task": "mmlu_nutrition", "task_alias": "nutrition", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "nutrition", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about nutrition.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_philosophy": { "task": "mmlu_philosophy", "task_alias": "philosophy", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "philosophy", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about philosophy.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_prehistory": { "task": "mmlu_prehistory", "task_alias": "prehistory", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "prehistory", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about prehistory.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_professional_accounting": { "task": "mmlu_professional_accounting", "task_alias": "professional_accounting", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "professional_accounting", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_professional_law": { "task": "mmlu_professional_law", "task_alias": "professional_law", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "professional_law", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about professional law.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_professional_medicine": { "task": "mmlu_professional_medicine", "task_alias": "professional_medicine", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "professional_medicine", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_professional_psychology": { "task": "mmlu_professional_psychology", "task_alias": "professional_psychology", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "professional_psychology", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_public_relations": { "task": "mmlu_public_relations", "task_alias": "public_relations", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "public_relations", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about public relations.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_security_studies": { "task": "mmlu_security_studies", "task_alias": "security_studies", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "security_studies", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about security studies.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_sociology": { "task": "mmlu_sociology", "task_alias": "sociology", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "sociology", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about sociology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_us_foreign_policy": { "task": "mmlu_us_foreign_policy", "task_alias": "us_foreign_policy", "group": "mmlu_social_sciences", "group_alias": "social_sciences", "dataset_path": "hails/mmlu_no_train", "dataset_name": "us_foreign_policy", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_virology": { "task": "mmlu_virology", "task_alias": "virology", "group": "mmlu_other", "group_alias": "other", "dataset_path": "hails/mmlu_no_train", "dataset_name": "virology", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about virology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } }, "mmlu_world_religions": { "task": "mmlu_world_religions", "task_alias": "world_religions", "group": "mmlu_humanities", "group_alias": "humanities", "dataset_path": "hails/mmlu_no_train", "dataset_name": "world_religions", "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about world religions.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 5, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 0.0 } } }, "versions": { "mmlu_abstract_algebra": 0.0, "mmlu_anatomy": 0.0, "mmlu_astronomy": 0.0, "mmlu_business_ethics": 0.0, "mmlu_clinical_knowledge": 0.0, "mmlu_college_biology": 0.0, "mmlu_college_chemistry": 0.0, "mmlu_college_computer_science": 0.0, "mmlu_college_mathematics": 0.0, "mmlu_college_medicine": 0.0, "mmlu_college_physics": 0.0, "mmlu_computer_security": 0.0, "mmlu_conceptual_physics": 0.0, "mmlu_econometrics": 0.0, "mmlu_electrical_engineering": 0.0, "mmlu_elementary_mathematics": 0.0, "mmlu_formal_logic": 0.0, "mmlu_global_facts": 0.0, "mmlu_high_school_biology": 0.0, "mmlu_high_school_chemistry": 0.0, "mmlu_high_school_computer_science": 0.0, "mmlu_high_school_european_history": 0.0, "mmlu_high_school_geography": 0.0, "mmlu_high_school_government_and_politics": 0.0, "mmlu_high_school_macroeconomics": 0.0, "mmlu_high_school_mathematics": 0.0, "mmlu_high_school_microeconomics": 0.0, "mmlu_high_school_physics": 0.0, "mmlu_high_school_psychology": 0.0, "mmlu_high_school_statistics": 0.0, "mmlu_high_school_us_history": 0.0, "mmlu_high_school_world_history": 0.0, "mmlu_human_aging": 0.0, "mmlu_human_sexuality": 0.0, "mmlu_international_law": 0.0, "mmlu_jurisprudence": 0.0, "mmlu_logical_fallacies": 0.0, "mmlu_machine_learning": 0.0, "mmlu_management": 0.0, "mmlu_marketing": 0.0, "mmlu_medical_genetics": 0.0, "mmlu_miscellaneous": 0.0, "mmlu_moral_disputes": 0.0, "mmlu_moral_scenarios": 0.0, "mmlu_nutrition": 0.0, "mmlu_philosophy": 0.0, "mmlu_prehistory": 0.0, "mmlu_professional_accounting": 0.0, "mmlu_professional_law": 0.0, "mmlu_professional_medicine": 0.0, "mmlu_professional_psychology": 0.0, "mmlu_public_relations": 0.0, "mmlu_security_studies": 0.0, "mmlu_sociology": 0.0, "mmlu_us_foreign_policy": 0.0, "mmlu_virology": 0.0, "mmlu_world_religions": 0.0 }, "n-shot": { "mmlu": 0, "mmlu_abstract_algebra": 5, "mmlu_anatomy": 5, "mmlu_astronomy": 5, "mmlu_business_ethics": 5, "mmlu_clinical_knowledge": 5, "mmlu_college_biology": 5, "mmlu_college_chemistry": 5, "mmlu_college_computer_science": 5, "mmlu_college_mathematics": 5, "mmlu_college_medicine": 5, "mmlu_college_physics": 5, "mmlu_computer_security": 5, "mmlu_conceptual_physics": 5, "mmlu_econometrics": 5, "mmlu_electrical_engineering": 5, "mmlu_elementary_mathematics": 5, "mmlu_formal_logic": 5, "mmlu_global_facts": 5, "mmlu_high_school_biology": 5, "mmlu_high_school_chemistry": 5, "mmlu_high_school_computer_science": 5, "mmlu_high_school_european_history": 5, "mmlu_high_school_geography": 5, "mmlu_high_school_government_and_politics": 5, "mmlu_high_school_macroeconomics": 5, "mmlu_high_school_mathematics": 5, "mmlu_high_school_microeconomics": 5, "mmlu_high_school_physics": 5, "mmlu_high_school_psychology": 5, "mmlu_high_school_statistics": 5, "mmlu_high_school_us_history": 5, "mmlu_high_school_world_history": 5, "mmlu_human_aging": 5, "mmlu_human_sexuality": 5, "mmlu_humanities": 5, "mmlu_international_law": 5, "mmlu_jurisprudence": 5, "mmlu_logical_fallacies": 5, "mmlu_machine_learning": 5, "mmlu_management": 5, "mmlu_marketing": 5, "mmlu_medical_genetics": 5, "mmlu_miscellaneous": 5, "mmlu_moral_disputes": 5, "mmlu_moral_scenarios": 5, "mmlu_nutrition": 5, "mmlu_other": 5, "mmlu_philosophy": 5, "mmlu_prehistory": 5, "mmlu_professional_accounting": 5, "mmlu_professional_law": 5, "mmlu_professional_medicine": 5, "mmlu_professional_psychology": 5, "mmlu_public_relations": 5, "mmlu_security_studies": 5, "mmlu_social_sciences": 5, "mmlu_sociology": 5, "mmlu_stem": 5, "mmlu_us_foreign_policy": 5, "mmlu_virology": 5, "mmlu_world_religions": 5 }, "higher_is_better": { "mmlu": { "acc": true }, "mmlu_abstract_algebra": { "acc": true }, "mmlu_anatomy": { "acc": true }, "mmlu_astronomy": { "acc": true }, "mmlu_business_ethics": { "acc": true }, "mmlu_clinical_knowledge": { "acc": true }, "mmlu_college_biology": { "acc": true }, "mmlu_college_chemistry": { "acc": true }, "mmlu_college_computer_science": { "acc": true }, "mmlu_college_mathematics": { "acc": true }, "mmlu_college_medicine": { "acc": true }, "mmlu_college_physics": { "acc": true }, "mmlu_computer_security": { "acc": true }, "mmlu_conceptual_physics": { "acc": true }, "mmlu_econometrics": { "acc": true }, "mmlu_electrical_engineering": { "acc": true }, "mmlu_elementary_mathematics": { "acc": true }, "mmlu_formal_logic": { "acc": true }, "mmlu_global_facts": { "acc": true }, "mmlu_high_school_biology": { "acc": true }, "mmlu_high_school_chemistry": { "acc": true }, "mmlu_high_school_computer_science": { "acc": true }, "mmlu_high_school_european_history": { "acc": true }, "mmlu_high_school_geography": { "acc": true }, "mmlu_high_school_government_and_politics": { "acc": true }, "mmlu_high_school_macroeconomics": { "acc": true }, "mmlu_high_school_mathematics": { "acc": true }, "mmlu_high_school_microeconomics": { "acc": true }, "mmlu_high_school_physics": { "acc": true }, "mmlu_high_school_psychology": { "acc": true }, "mmlu_high_school_statistics": { "acc": true }, "mmlu_high_school_us_history": { "acc": true }, "mmlu_high_school_world_history": { "acc": true }, "mmlu_human_aging": { "acc": true }, "mmlu_human_sexuality": { "acc": true }, "mmlu_humanities": { "acc": true }, "mmlu_international_law": { "acc": true }, "mmlu_jurisprudence": { "acc": true }, "mmlu_logical_fallacies": { "acc": true }, "mmlu_machine_learning": { "acc": true }, "mmlu_management": { "acc": true }, "mmlu_marketing": { "acc": true }, "mmlu_medical_genetics": { "acc": true }, "mmlu_miscellaneous": { "acc": true }, "mmlu_moral_disputes": { "acc": true }, "mmlu_moral_scenarios": { "acc": true }, "mmlu_nutrition": { "acc": true }, "mmlu_other": { "acc": true }, "mmlu_philosophy": { "acc": true }, "mmlu_prehistory": { "acc": true }, "mmlu_professional_accounting": { "acc": true }, "mmlu_professional_law": { "acc": true }, "mmlu_professional_medicine": { "acc": true }, "mmlu_professional_psychology": { "acc": true }, "mmlu_public_relations": { "acc": true }, "mmlu_security_studies": { "acc": true }, "mmlu_social_sciences": { "acc": true }, "mmlu_sociology": { "acc": true }, "mmlu_stem": { "acc": true }, "mmlu_us_foreign_policy": { "acc": true }, "mmlu_virology": { "acc": true }, "mmlu_world_religions": { "acc": true } }, "n-samples": { "mmlu_high_school_european_history": { "original": 165, "effective": 165 }, "mmlu_high_school_world_history": { "original": 237, "effective": 237 }, "mmlu_professional_law": { "original": 1534, "effective": 1534 }, "mmlu_logical_fallacies": { "original": 163, "effective": 163 }, "mmlu_high_school_us_history": { "original": 204, "effective": 204 }, "mmlu_world_religions": { "original": 171, "effective": 171 }, "mmlu_prehistory": { "original": 324, "effective": 324 }, "mmlu_jurisprudence": { "original": 108, "effective": 108 }, "mmlu_moral_scenarios": { "original": 895, "effective": 895 }, "mmlu_formal_logic": { "original": 126, "effective": 126 }, "mmlu_philosophy": { "original": 311, "effective": 311 }, "mmlu_international_law": { "original": 121, "effective": 121 }, "mmlu_moral_disputes": { "original": 346, "effective": 346 }, "mmlu_high_school_government_and_politics": { "original": 193, "effective": 193 }, "mmlu_human_sexuality": { "original": 131, "effective": 131 }, "mmlu_high_school_microeconomics": { "original": 238, "effective": 238 }, "mmlu_high_school_macroeconomics": { "original": 390, "effective": 390 }, "mmlu_public_relations": { "original": 110, "effective": 110 }, "mmlu_sociology": { "original": 201, "effective": 201 }, "mmlu_professional_psychology": { "original": 612, "effective": 612 }, "mmlu_high_school_psychology": { "original": 545, "effective": 545 }, "mmlu_econometrics": { "original": 114, "effective": 114 }, "mmlu_high_school_geography": { "original": 198, "effective": 198 }, "mmlu_us_foreign_policy": { "original": 100, "effective": 100 }, "mmlu_security_studies": { "original": 245, "effective": 245 }, "mmlu_business_ethics": { "original": 100, "effective": 100 }, "mmlu_virology": { "original": 166, "effective": 166 }, "mmlu_nutrition": { "original": 306, "effective": 306 }, "mmlu_management": { "original": 103, "effective": 103 }, "mmlu_clinical_knowledge": { "original": 265, "effective": 265 }, "mmlu_marketing": { "original": 234, "effective": 234 }, "mmlu_college_medicine": { "original": 173, "effective": 173 }, "mmlu_professional_medicine": { "original": 272, "effective": 272 }, "mmlu_medical_genetics": { "original": 100, "effective": 100 }, "mmlu_human_aging": { "original": 223, "effective": 223 }, "mmlu_professional_accounting": { "original": 282, "effective": 282 }, "mmlu_miscellaneous": { "original": 783, "effective": 783 }, "mmlu_global_facts": { "original": 100, "effective": 100 }, "mmlu_college_computer_science": { "original": 100, "effective": 100 }, "mmlu_high_school_physics": { "original": 151, "effective": 151 }, "mmlu_college_chemistry": { "original": 100, "effective": 100 }, "mmlu_college_biology": { "original": 144, "effective": 144 }, "mmlu_high_school_mathematics": { "original": 270, "effective": 270 }, "mmlu_high_school_computer_science": { "original": 100, "effective": 100 }, "mmlu_electrical_engineering": { "original": 145, "effective": 145 }, "mmlu_college_physics": { "original": 102, "effective": 102 }, "mmlu_anatomy": { "original": 135, "effective": 135 }, "mmlu_college_mathematics": { "original": 100, "effective": 100 }, "mmlu_elementary_mathematics": { "original": 378, "effective": 378 }, "mmlu_high_school_chemistry": { "original": 203, "effective": 203 }, "mmlu_machine_learning": { "original": 112, "effective": 112 }, "mmlu_abstract_algebra": { "original": 100, "effective": 100 }, "mmlu_astronomy": { "original": 152, "effective": 152 }, "mmlu_computer_security": { "original": 100, "effective": 100 }, "mmlu_high_school_biology": { "original": 310, "effective": 310 }, "mmlu_high_school_statistics": { "original": 216, "effective": 216 }, "mmlu_conceptual_physics": { "original": 235, "effective": 235 } }, "config": { "model": "vllm", "model_args": "pretrained=/home/mlr/models/Mixtral-8x22B-Instruct-v0.1-FP8,tensor_parallel_size=4,dtype=auto,add_bos_token=True,gpu_memory_utilization=0.8,data_parallel_size=1", "batch_size": "auto", "batch_sizes": [], "device": "cuda", "use_cache": null, "limit": null, "bootstrap_iters": 100000, "gen_kwargs": null, "random_seed": 0, "numpy_seed": 1234, "torch_seed": 1234, "fewshot_seed": 1234 }, "git_hash": "f2843b2f", "date": 1717759668.7806425, "pretty_env_info": "PyTorch version: 2.3.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.4 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.29.3\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.19.0-1010-nvidia-lowlatency-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.5.40\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA H100 NVL\nGPU 1: NVIDIA H100 NVL\nGPU 2: NVIDIA H100 NVL\nGPU 3: NVIDIA H100 NVL\nGPU 4: NVIDIA H100 NVL\nGPU 5: NVIDIA H100 NVL\nGPU 6: NVIDIA H100 NVL\nGPU 7: NVIDIA H100 NVL\n\nNvidia driver version: 555.42.02\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture: x86_64\nCPU op-mode(s): 32-bit, 64-bit\nAddress sizes: 46 bits physical, 57 bits virtual\nByte Order: Little Endian\nCPU(s): 144\nOn-line CPU(s) list: 0-143\nVendor ID: GenuineIntel\nModel name: Intel(R) Xeon(R) Platinum 8452Y\nCPU family: 6\nModel: 143\nThread(s) per core: 2\nCore(s) per socket: 36\nSocket(s): 2\nStepping: 8\nFrequency boost: enabled\nCPU max MHz: 2001.0000\nCPU min MHz: 800.0000\nBogoMIPS: 4000.00\nFlags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hfi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities\nVirtualization: VT-x\nL1d cache: 3.4 MiB (72 instances)\nL1i cache: 2.3 MiB (72 instances)\nL2 cache: 144 MiB (72 instances)\nL3 cache: 135 MiB (2 instances)\nNUMA node(s): 2\nNUMA node0 CPU(s): 0-35,72-107\nNUMA node1 CPU(s): 36-71,108-143\nVulnerability Itlb multihit: Not affected\nVulnerability L1tf: Not affected\nVulnerability Mds: Not affected\nVulnerability Meltdown: Not affected\nVulnerability Mmio stale data: Not affected\nVulnerability Retbleed: Not affected\nVulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl\nVulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence\nVulnerability Srbds: Not affected\nVulnerability Tsx async abort: Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.4\n[pip3] torch==2.3.0\n[pip3] triton==2.3.0\n[conda] Could not collect", "transformers_version": "4.41.2", "upper_git_hash": "f2843b2fd64df799179808ce2428b7a8dbc403de", "task_hashes": {}, "model_source": "vllm", "model_name": "/home/mlr/models/Mixtral-8x22B-Instruct-v0.1-FP8", "model_name_sanitized": "__home__mlr__models__Mixtral-8x22B-Instruct-v0.1-FP8", "system_instruction": null, "system_instruction_sha": null, "chat_template": null, "chat_template_sha": null, "start_time": 829948.992005701, "end_time": 847093.177875013, "total_evaluation_time_seconds": "17144.18586931203" }