{ "results": { "mmlu": { "acc,none": 0.8439680957128615, "acc_stderr,none": 0.0029499711040394372, "alias": "mmlu" }, "mmlu_humanities": { "alias": " - humanities", "acc,none": 0.8146652497343252, "acc_stderr,none": 0.005505402478774841 }, "mmlu_formal_logic": { "alias": " - formal_logic", "acc,none": 0.7301587301587301, "acc_stderr,none": 0.03970158273235173 }, "mmlu_high_school_european_history": { "alias": " - high_school_european_history", "acc,none": 0.8909090909090909, "acc_stderr,none": 0.02434383813514564 }, "mmlu_high_school_us_history": { "alias": " - high_school_us_history", "acc,none": 0.9509803921568627, "acc_stderr,none": 0.01515383934021267 }, "mmlu_high_school_world_history": { "alias": " - high_school_world_history", "acc,none": 0.9409282700421941, "acc_stderr,none": 0.01534659746388869 }, "mmlu_international_law": { "alias": " - international_law", "acc,none": 0.9173553719008265, "acc_stderr,none": 0.025135382356604227 }, "mmlu_jurisprudence": { "alias": " - jurisprudence", "acc,none": 0.8796296296296297, "acc_stderr,none": 0.031457038543062525 }, "mmlu_logical_fallacies": { "alias": " - logical_fallacies", "acc,none": 0.901840490797546, "acc_stderr,none": 0.023376180231059605 }, "mmlu_moral_disputes": { "alias": " - moral_disputes", "acc,none": 0.869942196531792, "acc_stderr,none": 0.01810939152822133 }, "mmlu_moral_scenarios": { "alias": " - moral_scenarios", "acc,none": 0.829050279329609, "acc_stderr,none": 0.012590873868789222 }, "mmlu_philosophy": { "alias": " - philosophy", "acc,none": 0.8713826366559485, "acc_stderr,none": 0.01901399630412152 }, "mmlu_prehistory": { "alias": " - prehistory", "acc,none": 0.9104938271604939, "acc_stderr,none": 0.015884141073937555 }, "mmlu_professional_law": { "alias": " - professional_law", "acc,none": 0.6929595827900913, "acc_stderr,none": 0.011780959114513764 }, "mmlu_world_religions": { "alias": " - world_religions", "acc,none": 0.8888888888888888, "acc_stderr,none": 0.024103384202072864 }, "mmlu_other": { "alias": " - other", "acc,none": 0.8625683939491471, "acc_stderr,none": 0.005895325056685939 }, "mmlu_business_ethics": { "alias": " - business_ethics", "acc,none": 0.78, "acc_stderr,none": 0.04163331998932263 }, "mmlu_clinical_knowledge": { "alias": " - clinical_knowledge", "acc,none": 0.8716981132075472, "acc_stderr,none": 0.02058247568799185 }, "mmlu_college_medicine": { "alias": " - college_medicine", "acc,none": 0.8323699421965318, "acc_stderr,none": 0.028481963032143395 }, "mmlu_global_facts": { "alias": " - global_facts", "acc,none": 0.61, "acc_stderr,none": 0.04902071300001975 }, "mmlu_human_aging": { "alias": " - human_aging", "acc,none": 0.8565022421524664, "acc_stderr,none": 0.0235293712696182 }, "mmlu_management": { "alias": " - management", "acc,none": 0.9223300970873787, "acc_stderr,none": 0.026501440784762766 }, "mmlu_marketing": { "alias": " - marketing", "acc,none": 0.9487179487179487, "acc_stderr,none": 0.014450181176872726 }, "mmlu_medical_genetics": { "alias": " - medical_genetics", "acc,none": 0.9, "acc_stderr,none": 0.030151134457776348 }, "mmlu_miscellaneous": { "alias": " - miscellaneous", "acc,none": 0.9501915708812261, "acc_stderr,none": 0.0077795348866793465 }, "mmlu_nutrition": { "alias": " - nutrition", "acc,none": 0.9019607843137255, "acc_stderr,none": 0.017027222935582193 }, "mmlu_professional_accounting": { "alias": " - professional_accounting", "acc,none": 0.75177304964539, "acc_stderr,none": 0.025770015644290392 }, "mmlu_professional_medicine": { "alias": " - professional_medicine", "acc,none": 0.8897058823529411, "acc_stderr,none": 0.019028947191474497 }, "mmlu_virology": { "alias": " - virology", "acc,none": 0.5662650602409639, "acc_stderr,none": 0.03858158940685517 }, "mmlu_social_sciences": { "alias": " - social_sciences", "acc,none": 0.9038024049398765, "acc_stderr,none": 0.005221504585802578 }, "mmlu_econometrics": { "alias": " - econometrics", "acc,none": 0.7280701754385965, "acc_stderr,none": 0.041857744240220554 }, "mmlu_high_school_geography": { "alias": " - high_school_geography", "acc,none": 0.9393939393939394, "acc_stderr,none": 0.016999994927421606 }, "mmlu_high_school_government_and_politics": { "alias": " - high_school_government_and_politics", "acc,none": 0.9896373056994818, "acc_stderr,none": 0.007308424386792201 }, "mmlu_high_school_macroeconomics": { "alias": " - high_school_macroeconomics", "acc,none": 0.8897435897435897, "acc_stderr,none": 0.015880331261056115 }, "mmlu_high_school_microeconomics": { "alias": " - high_school_microeconomics", "acc,none": 0.9411764705882353, "acc_stderr,none": 0.015283995352038402 }, "mmlu_high_school_psychology": { "alias": " - high_school_psychology", "acc,none": 0.9357798165137615, "acc_stderr,none": 0.010510494713201424 }, "mmlu_human_sexuality": { "alias": " - human_sexuality", "acc,none": 0.9083969465648855, "acc_stderr,none": 0.025300035578642965 }, "mmlu_professional_psychology": { "alias": " - professional_psychology", "acc,none": 0.8970588235294118, "acc_stderr,none": 0.012293751200845176 }, "mmlu_public_relations": { "alias": " - public_relations", "acc,none": 0.7454545454545455, "acc_stderr,none": 0.041723430387053825 }, "mmlu_security_studies": { "alias": " - security_studies", "acc,none": 0.8408163265306122, "acc_stderr,none": 0.023420972069166365 }, "mmlu_sociology": { "alias": " - sociology", "acc,none": 0.945273631840796, "acc_stderr,none": 0.016082815796263254 }, "mmlu_us_foreign_policy": { "alias": " - us_foreign_policy", "acc,none": 0.94, "acc_stderr,none": 0.02386832565759419 }, "mmlu_stem": { "alias": " - stem", "acc,none": 0.8109736758642563, "acc_stderr,none": 0.0067376135296805745 }, "mmlu_abstract_algebra": { "alias": " - abstract_algebra", "acc,none": 0.66, "acc_stderr,none": 0.04760952285695237 }, "mmlu_anatomy": { "alias": " - anatomy", "acc,none": 0.7925925925925926, "acc_stderr,none": 0.03502553170678317 }, "mmlu_astronomy": { "alias": " - astronomy", "acc,none": 0.9276315789473685, "acc_stderr,none": 0.021085011261884112 }, "mmlu_college_biology": { "alias": " - college_biology", "acc,none": 0.9444444444444444, "acc_stderr,none": 0.01915507853243362 }, "mmlu_college_chemistry": { "alias": " - college_chemistry", "acc,none": 0.58, "acc_stderr,none": 0.049604496374885836 }, "mmlu_college_computer_science": { "alias": " - college_computer_science", "acc,none": 0.8, "acc_stderr,none": 0.040201512610368445 }, "mmlu_college_mathematics": { "alias": " - college_mathematics", "acc,none": 0.63, "acc_stderr,none": 0.04852365870939099 }, "mmlu_college_physics": { "alias": " - college_physics", "acc,none": 0.6470588235294118, "acc_stderr,none": 0.04755129616062947 }, "mmlu_computer_security": { "alias": " - computer_security", "acc,none": 0.83, "acc_stderr,none": 0.0377525168068637 }, "mmlu_conceptual_physics": { "alias": " - conceptual_physics", "acc,none": 0.8893617021276595, "acc_stderr,none": 0.020506145099008433 }, "mmlu_electrical_engineering": { "alias": " - electrical_engineering", "acc,none": 0.8275862068965517, "acc_stderr,none": 0.03147830790259575 }, "mmlu_elementary_mathematics": { "alias": " - elementary_mathematics", "acc,none": 0.8888888888888888, "acc_stderr,none": 0.01618571201620511 }, "mmlu_high_school_biology": { "alias": " - high_school_biology", "acc,none": 0.9419354838709677, "acc_stderr,none": 0.01330413811280927 }, "mmlu_high_school_chemistry": { "alias": " - high_school_chemistry", "acc,none": 0.7980295566502463, "acc_stderr,none": 0.028247350122180243 }, "mmlu_high_school_computer_science": { "alias": " - high_school_computer_science", "acc,none": 0.91, "acc_stderr,none": 0.028762349126466115 }, "mmlu_high_school_mathematics": { "alias": " - high_school_mathematics", "acc,none": 0.6777777777777778, "acc_stderr,none": 0.028493465091028597 }, "mmlu_high_school_physics": { "alias": " - high_school_physics", "acc,none": 0.7284768211920529, "acc_stderr,none": 0.03631329803969654 }, "mmlu_high_school_statistics": { "alias": " - high_school_statistics", "acc,none": 0.7824074074074074, "acc_stderr,none": 0.028139689444859676 }, "mmlu_machine_learning": { "alias": " - machine_learning", "acc,none": 0.7589285714285714, "acc_stderr,none": 0.04059867246952685 } }, "groups": { "mmlu": { "acc,none": 0.8439680957128615, "acc_stderr,none": 0.0029499711040394372, "alias": "mmlu" }, "mmlu_humanities": { "alias": " - humanities", "acc,none": 0.8146652497343252, "acc_stderr,none": 0.005505402478774841 }, "mmlu_other": { "alias": " - other", "acc,none": 0.8625683939491471, "acc_stderr,none": 0.005895325056685939 }, "mmlu_social_sciences": { "alias": " - social_sciences", "acc,none": 0.9038024049398765, "acc_stderr,none": 0.005221504585802578 }, "mmlu_stem": { "alias": " - stem", "acc,none": 0.8109736758642563, "acc_stderr,none": 0.0067376135296805745 } }, "group_subtasks": { "mmlu_stem": [ "mmlu_college_biology", "mmlu_high_school_computer_science", "mmlu_elementary_mathematics", "mmlu_astronomy", "mmlu_machine_learning", "mmlu_high_school_mathematics", "mmlu_electrical_engineering", "mmlu_college_chemistry", "mmlu_college_mathematics", "mmlu_high_school_statistics", "mmlu_high_school_biology", "mmlu_abstract_algebra", "mmlu_college_physics", "mmlu_conceptual_physics", "mmlu_computer_security", "mmlu_anatomy", "mmlu_college_computer_science", "mmlu_high_school_physics", "mmlu_high_school_chemistry" ], "mmlu_other": [ "mmlu_marketing", "mmlu_professional_accounting", "mmlu_clinical_knowledge", "mmlu_college_medicine", "mmlu_miscellaneous", "mmlu_virology", "mmlu_business_ethics", "mmlu_professional_medicine", "mmlu_global_facts", "mmlu_nutrition", "mmlu_human_aging", "mmlu_management", "mmlu_medical_genetics" ], "mmlu_social_sciences": [ "mmlu_high_school_psychology", "mmlu_high_school_geography", "mmlu_high_school_macroeconomics", "mmlu_public_relations", "mmlu_security_studies", "mmlu_high_school_microeconomics", "mmlu_human_sexuality", "mmlu_sociology", "mmlu_professional_psychology", "mmlu_econometrics", "mmlu_us_foreign_policy", "mmlu_high_school_government_and_politics" ], "mmlu_humanities": [ "mmlu_moral_scenarios", "mmlu_high_school_us_history", "mmlu_high_school_world_history", "mmlu_world_religions", "mmlu_formal_logic", "mmlu_moral_disputes", "mmlu_prehistory", "mmlu_international_law", "mmlu_logical_fallacies", "mmlu_professional_law", "mmlu_philosophy", "mmlu_high_school_european_history", "mmlu_jurisprudence" ], "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_moral_scenarios": { "original": 895, "effective": 895 }, "mmlu_high_school_us_history": { "original": 204, "effective": 204 }, "mmlu_high_school_world_history": { "original": 237, "effective": 237 }, "mmlu_world_religions": { "original": 171, "effective": 171 }, "mmlu_formal_logic": { "original": 126, "effective": 126 }, "mmlu_moral_disputes": { "original": 346, "effective": 346 }, "mmlu_prehistory": { "original": 324, "effective": 324 }, "mmlu_international_law": { "original": 121, "effective": 121 }, "mmlu_logical_fallacies": { "original": 163, "effective": 163 }, "mmlu_professional_law": { "original": 1534, "effective": 1534 }, "mmlu_philosophy": { "original": 311, "effective": 311 }, "mmlu_high_school_european_history": { "original": 165, "effective": 165 }, "mmlu_jurisprudence": { "original": 108, "effective": 108 }, "mmlu_high_school_psychology": { "original": 545, "effective": 545 }, "mmlu_high_school_geography": { "original": 198, "effective": 198 }, "mmlu_high_school_macroeconomics": { "original": 390, "effective": 390 }, "mmlu_public_relations": { "original": 110, "effective": 110 }, "mmlu_security_studies": { "original": 245, "effective": 245 }, "mmlu_high_school_microeconomics": { "original": 238, "effective": 238 }, "mmlu_human_sexuality": { "original": 131, "effective": 131 }, "mmlu_sociology": { "original": 201, "effective": 201 }, "mmlu_professional_psychology": { "original": 612, "effective": 612 }, "mmlu_econometrics": { "original": 114, "effective": 114 }, "mmlu_us_foreign_policy": { "original": 100, "effective": 100 }, "mmlu_high_school_government_and_politics": { "original": 193, "effective": 193 }, "mmlu_marketing": { "original": 234, "effective": 234 }, "mmlu_professional_accounting": { "original": 282, "effective": 282 }, "mmlu_clinical_knowledge": { "original": 265, "effective": 265 }, "mmlu_college_medicine": { "original": 173, "effective": 173 }, "mmlu_miscellaneous": { "original": 783, "effective": 783 }, "mmlu_virology": { "original": 166, "effective": 166 }, "mmlu_business_ethics": { "original": 100, "effective": 100 }, "mmlu_professional_medicine": { "original": 272, "effective": 272 }, "mmlu_global_facts": { "original": 100, "effective": 100 }, "mmlu_nutrition": { "original": 306, "effective": 306 }, "mmlu_human_aging": { "original": 223, "effective": 223 }, "mmlu_management": { "original": 103, "effective": 103 }, "mmlu_medical_genetics": { "original": 100, "effective": 100 }, "mmlu_college_biology": { "original": 144, "effective": 144 }, "mmlu_high_school_computer_science": { "original": 100, "effective": 100 }, "mmlu_elementary_mathematics": { "original": 378, "effective": 378 }, "mmlu_astronomy": { "original": 152, "effective": 152 }, "mmlu_machine_learning": { "original": 112, "effective": 112 }, "mmlu_high_school_mathematics": { "original": 270, "effective": 270 }, "mmlu_electrical_engineering": { "original": 145, "effective": 145 }, "mmlu_college_chemistry": { "original": 100, "effective": 100 }, "mmlu_college_mathematics": { "original": 100, "effective": 100 }, "mmlu_high_school_statistics": { "original": 216, "effective": 216 }, "mmlu_high_school_biology": { "original": 310, "effective": 310 }, "mmlu_abstract_algebra": { "original": 100, "effective": 100 }, "mmlu_college_physics": { "original": 102, "effective": 102 }, "mmlu_conceptual_physics": { "original": 235, "effective": 235 }, "mmlu_computer_security": { "original": 100, "effective": 100 }, "mmlu_anatomy": { "original": 135, "effective": 135 }, "mmlu_college_computer_science": { "original": 100, "effective": 100 }, "mmlu_high_school_physics": { "original": 151, "effective": 151 }, "mmlu_high_school_chemistry": { "original": 203, "effective": 203 } }, "config": { "model": "hf", "model_args": "pretrained=/home/migel/Tess-v2.5-qwen2-72B-safetensors,parallelize=True", "model_num_parameters": 72706203648, "model_dtype": "torch.float16", "model_revision": "main", "model_sha": "", "batch_size": "8", "batch_sizes": [], "device": null, "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": "b3e4c49a", "date": 1718167288.656124, "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 20.04.6 LTS (x86_64)\nGCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0\nClang version: Could not collect\nCMake version: version 3.29.3\nLibc version: glibc-2.31\n\nPython version: 3.10.14 (main, Apr 6 2024, 18:45:05) [GCC 9.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-1050-azure-x86_64-with-glibc2.31\nIs CUDA available: True\nCUDA runtime version: 12.1.105\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100 80GB PCIe\nGPU 1: NVIDIA A100 80GB PCIe\nGPU 2: NVIDIA A100 80GB PCIe\nGPU 3: NVIDIA A100 80GB PCIe\n\nNvidia driver version: 530.30.02\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\nByte Order: Little Endian\nAddress sizes: 48 bits physical, 48 bits virtual\nCPU(s): 96\nOn-line CPU(s) list: 0-95\nThread(s) per core: 1\nCore(s) per socket: 48\nSocket(s): 2\nNUMA node(s): 4\nVendor ID: AuthenticAMD\nCPU family: 25\nModel: 1\nModel name: AMD EPYC 7V13 64-Core Processor\nStepping: 1\nCPU MHz: 2445.435\nBogoMIPS: 4890.87\nHypervisor vendor: Microsoft\nVirtualization type: full\nL1d cache: 3 MiB\nL1i cache: 3 MiB\nL2 cache: 48 MiB\nL3 cache: 384 MiB\nNUMA node0 CPU(s): 0-23\nNUMA node1 CPU(s): 24-47\nNUMA node2 CPU(s): 48-71\nNUMA node3 CPU(s): 72-95\nVulnerability Gather data sampling: Not affected\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 rstack overflow: Mitigation; safe RET, no microcode\nVulnerability Spec store bypass: Vulnerable\nVulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2: Mitigation; Retpolines, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected\nVulnerability Srbds: Not affected\nVulnerability Tsx async abort: Not affected\nFlags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext perfctr_core invpcid_single vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves clzero xsaveerptr rdpru arat umip vaes vpclmulqdq rdpid fsrm\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] magma-cuda117 2.6.1 1 pytorch\n[conda] mkl 2022.2.1 pypi_0 pypi\n[conda] mkl-include 2022.2.1 pypi_0 pypi\n[conda] numpy 1.24.4 pypi_0 pypi\n[conda] pytorch-lightning 1.9.5 pypi_0 pypi\n[conda] torch 2.0.1 pypi_0 pypi\n[conda] torch-nebula 0.16.10 pypi_0 pypi\n[conda] torch-ort 1.17.0 pypi_0 pypi\n[conda] torchaudio 2.0.2+cu117 pypi_0 pypi\n[conda] torchdata 0.6.1 pypi_0 pypi\n[conda] torchmetrics 1.2.0 pypi_0 pypi\n[conda] torchsnapshot 0.1.0 pypi_0 pypi\n[conda] torchvision 0.15.2+cu117 pypi_0 pypi\n[conda] triton 2.0.0 pypi_0 pypi", "transformers_version": "4.41.1", "upper_git_hash": null, "task_hashes": {}, "model_source": "hf", "model_name": "/home/migel/Tess-v2.5-qwen2-72B-safetensors", "model_name_sanitized": "__home__migel__Tess-v2.5-qwen2-72B-safetensors", "system_instruction": null, "system_instruction_sha": null, "chat_template": null, "chat_template_sha": null, "start_time": 380863.826540975, "end_time": 388726.503174757, "total_evaluation_time_seconds": "7862.676633781986" }