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ALLaM-7B-Instruct-preview/evaluations/en/jais-family-30b-16k-chat/mmlu_0_shot.json
ModelHub XC 3e4c694337 初始化项目，由ModelHub XC社区提供模型 
Model: lanawwas/ALLaM-7B-Instruct-preview
Source: Original Platform
2026-04-22 10:54:04 +08:00

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{
"results": {
"mmlu": {
"acc,none": 0.5850306224184589,
"acc_stderr,none": 0.003945772740763423,
"alias": "mmlu"
},
"mmlu_humanities": {
"acc,none": 0.5540913921360255,
"acc_stderr,none": 0.006741645211476788,
"alias": " - humanities"
},
"mmlu_formal_logic": {
"alias": " - formal_logic",
"acc,none": 0.38095238095238093,
"acc_stderr,none": 0.04343525428949098
},
"mmlu_high_school_european_history": {
"alias": " - high_school_european_history",
"acc,none": 0.8363636363636363,
"acc_stderr,none": 0.02888787239548795
},
"mmlu_high_school_us_history": {
"alias": " - high_school_us_history",
"acc,none": 0.803921568627451,
"acc_stderr,none": 0.027865942286639325
},
"mmlu_high_school_world_history": {
"alias": " - high_school_world_history",
"acc,none": 0.8354430379746836,
"acc_stderr,none": 0.024135736240566922
},
"mmlu_international_law": {
"alias": " - international_law",
"acc,none": 0.743801652892562,
"acc_stderr,none": 0.03984979653302871
},
"mmlu_jurisprudence": {
"alias": " - jurisprudence",
"acc,none": 0.7129629629629629,
"acc_stderr,none": 0.043733130409147614
},
"mmlu_logical_fallacies": {
"alias": " - logical_fallacies",
"acc,none": 0.7668711656441718,
"acc_stderr,none": 0.03322015795776741
},
"mmlu_moral_disputes": {
"alias": " - moral_disputes",
"acc,none": 0.6994219653179191,
"acc_stderr,none": 0.024685316867257803
},
"mmlu_moral_scenarios": {
"alias": " - moral_scenarios",
"acc,none": 0.30502793296089387,
"acc_stderr,none": 0.015398723510916716
},
"mmlu_philosophy": {
"alias": " - philosophy",
"acc,none": 0.6430868167202572,
"acc_stderr,none": 0.027210420375934016
},
"mmlu_prehistory": {
"alias": " - prehistory",
"acc,none": 0.6512345679012346,
"acc_stderr,none": 0.02651759772446501
},
"mmlu_professional_law": {
"alias": " - professional_law",
"acc,none": 0.4556714471968709,
"acc_stderr,none": 0.012719949543032207
},
"mmlu_world_religions": {
"alias": " - world_religions",
"acc,none": 0.8304093567251462,
"acc_stderr,none": 0.02878210810540171
},
"mmlu_other": {
"acc,none": 0.6562600579336981,
"acc_stderr,none": 0.008305273406237188,
"alias": " - other"
},
"mmlu_business_ethics": {
"alias": " - business_ethics",
"acc,none": 0.58,
"acc_stderr,none": 0.049604496374885836
},
"mmlu_clinical_knowledge": {
"alias": " - clinical_knowledge",
"acc,none": 0.6113207547169811,
"acc_stderr,none": 0.030000485448675986
},
"mmlu_college_medicine": {
"alias": " - college_medicine",
"acc,none": 0.6069364161849711,
"acc_stderr,none": 0.0372424959581773
},
"mmlu_global_facts": {
"alias": " - global_facts",
"acc,none": 0.46,
"acc_stderr,none": 0.05009082659620332
},
"mmlu_human_aging": {
"alias": " - human_aging",
"acc,none": 0.6591928251121076,
"acc_stderr,none": 0.03181149747055359
},
"mmlu_management": {
"alias": " - management",
"acc,none": 0.7669902912621359,
"acc_stderr,none": 0.04185832598928315
},
"mmlu_marketing": {
"alias": " - marketing",
"acc,none": 0.8290598290598291,
"acc_stderr,none": 0.024662496845209814
},
"mmlu_medical_genetics": {
"alias": " - medical_genetics",
"acc,none": 0.68,
"acc_stderr,none": 0.04688261722621504
},
"mmlu_miscellaneous": {
"alias": " - miscellaneous",
"acc,none": 0.7701149425287356,
"acc_stderr,none": 0.01504630184669183
},
"mmlu_nutrition": {
"alias": " - nutrition",
"acc,none": 0.6470588235294118,
"acc_stderr,none": 0.027363593284684972
},
"mmlu_professional_accounting": {
"alias": " - professional_accounting",
"acc,none": 0.4645390070921986,
"acc_stderr,none": 0.029752389657427054
},
"mmlu_professional_medicine": {
"alias": " - professional_medicine",
"acc,none": 0.5698529411764706,
"acc_stderr,none": 0.030074971917302875
},
"mmlu_virology": {
"alias": " - virology",
"acc,none": 0.5602409638554217,
"acc_stderr,none": 0.03864139923699121
},
"mmlu_social_sciences": {
"acc,none": 0.6561585960350991,
"acc_stderr,none": 0.008289290873417059,
"alias": " - social sciences"
},
"mmlu_econometrics": {
"alias": " - econometrics",
"acc,none": 0.3157894736842105,
"acc_stderr,none": 0.04372748290278007
},
"mmlu_high_school_geography": {
"alias": " - high_school_geography",
"acc,none": 0.7575757575757576,
"acc_stderr,none": 0.030532892233932036
},
"mmlu_high_school_government_and_politics": {
"alias": " - high_school_government_and_politics",
"acc,none": 0.7823834196891192,
"acc_stderr,none": 0.029778663037752964
},
"mmlu_high_school_macroeconomics": {
"alias": " - high_school_macroeconomics",
"acc,none": 0.5384615384615384,
"acc_stderr,none": 0.025275892070240637
},
"mmlu_high_school_microeconomics": {
"alias": " - high_school_microeconomics",
"acc,none": 0.5714285714285714,
"acc_stderr,none": 0.032145368597886394
},
"mmlu_high_school_psychology": {
"alias": " - high_school_psychology",
"acc,none": 0.7798165137614679,
"acc_stderr,none": 0.017765978652327544
},
"mmlu_human_sexuality": {
"alias": " - human_sexuality",
"acc,none": 0.7022900763358778,
"acc_stderr,none": 0.04010358942462203
},
"mmlu_professional_psychology": {
"alias": " - professional_psychology",
"acc,none": 0.5571895424836601,
"acc_stderr,none": 0.020095083154577354
},
"mmlu_public_relations": {
"alias": " - public_relations",
"acc,none": 0.6818181818181818,
"acc_stderr,none": 0.044612721759105085
},
"mmlu_security_studies": {
"alias": " - security_studies",
"acc,none": 0.6693877551020408,
"acc_stderr,none": 0.030116426296540617
},
"mmlu_sociology": {
"alias": " - sociology",
"acc,none": 0.7711442786069652,
"acc_stderr,none": 0.02970528405677243
},
"mmlu_us_foreign_policy": {
"alias": " - us_foreign_policy",
"acc,none": 0.84,
"acc_stderr,none": 0.03684529491774708
},
"mmlu_stem": {
"acc,none": 0.4915953060577228,
"acc_stderr,none": 0.008671090807177336,
"alias": " - stem"
},
"mmlu_abstract_algebra": {
"alias": " - abstract_algebra",
"acc,none": 0.36,
"acc_stderr,none": 0.048241815132442176
},
"mmlu_anatomy": {
"alias": " - anatomy",
"acc,none": 0.5111111111111111,
"acc_stderr,none": 0.04318275491977976
},
"mmlu_astronomy": {
"alias": " - astronomy",
"acc,none": 0.6842105263157895,
"acc_stderr,none": 0.037827289808654685
},
"mmlu_college_biology": {
"alias": " - college_biology",
"acc,none": 0.6458333333333334,
"acc_stderr,none": 0.039994111357535424
},
"mmlu_college_chemistry": {
"alias": " - college_chemistry",
"acc,none": 0.39,
"acc_stderr,none": 0.04902071300001975
},
"mmlu_college_computer_science": {
"alias": " - college_computer_science",
"acc,none": 0.5,
"acc_stderr,none": 0.050251890762960605
},
"mmlu_college_mathematics": {
"alias": " - college_mathematics",
"acc,none": 0.36,
"acc_stderr,none": 0.04824181513244218
},
"mmlu_college_physics": {
"alias": " - college_physics",
"acc,none": 0.4117647058823529,
"acc_stderr,none": 0.048971049527263666
},
"mmlu_computer_security": {
"alias": " - computer_security",
"acc,none": 0.67,
"acc_stderr,none": 0.04725815626252607
},
"mmlu_conceptual_physics": {
"alias": " - conceptual_physics",
"acc,none": 0.4851063829787234,
"acc_stderr,none": 0.03267151848924777
},
"mmlu_electrical_engineering": {
"alias": " - electrical_engineering",
"acc,none": 0.5310344827586206,
"acc_stderr,none": 0.04158632762097828
},
"mmlu_elementary_mathematics": {
"alias": " - elementary_mathematics",
"acc,none": 0.41005291005291006,
"acc_stderr,none": 0.025331202438944447
},
"mmlu_high_school_biology": {
"alias": " - high_school_biology",
"acc,none": 0.7,
"acc_stderr,none": 0.026069362295335134
},
"mmlu_high_school_chemistry": {
"alias": " - high_school_chemistry",
"acc,none": 0.4433497536945813,
"acc_stderr,none": 0.03495334582162933
},
"mmlu_high_school_computer_science": {
"alias": " - high_school_computer_science",
"acc,none": 0.66,
"acc_stderr,none": 0.04760952285695237
},
"mmlu_high_school_mathematics": {
"alias": " - high_school_mathematics",
"acc,none": 0.37407407407407406,
"acc_stderr,none": 0.02950286112895529
},
"mmlu_high_school_physics": {
"alias": " - high_school_physics",
"acc,none": 0.3708609271523179,
"acc_stderr,none": 0.03943966699183629
},
"mmlu_high_school_statistics": {
"alias": " - high_school_statistics",
"acc,none": 0.44907407407407407,
"acc_stderr,none": 0.03392238405321616
},
"mmlu_machine_learning": {
"alias": " - machine_learning",
"acc,none": 0.36607142857142855,
"acc_stderr,none": 0.04572372358737431
}
},
"groups": {
"mmlu": {
"acc,none": 0.5850306224184589,
"acc_stderr,none": 0.003945772740763423,
"alias": "mmlu"
},
"mmlu_humanities": {
"acc,none": 0.5540913921360255,
"acc_stderr,none": 0.006741645211476788,
"alias": " - humanities"
},
"mmlu_other": {
"acc,none": 0.6562600579336981,
"acc_stderr,none": 0.008305273406237188,
"alias": " - other"
},
"mmlu_social_sciences": {
"acc,none": 0.6561585960350991,
"acc_stderr,none": 0.008289290873417059,
"alias": " - social sciences"
},
"mmlu_stem": {
"acc,none": 0.4915953060577228,
"acc_stderr,none": 0.008671090807177336,
"alias": " - stem"
}
},
"group_subtasks": {
"mmlu_humanities": [
"mmlu_world_religions",
"mmlu_moral_disputes",
"mmlu_logical_fallacies",
"mmlu_prehistory",
"mmlu_professional_law",
"mmlu_philosophy",
"mmlu_moral_scenarios",
"mmlu_jurisprudence",
"mmlu_international_law",
"mmlu_high_school_european_history",
"mmlu_formal_logic",
"mmlu_high_school_us_history",
"mmlu_high_school_world_history"
],
"mmlu_social_sciences": [
"mmlu_high_school_government_and_politics",
"mmlu_public_relations",
"mmlu_high_school_microeconomics",
"mmlu_us_foreign_policy",
"mmlu_high_school_psychology",
"mmlu_high_school_geography",
"mmlu_professional_psychology",
"mmlu_high_school_macroeconomics",
"mmlu_security_studies",
"mmlu_sociology",
"mmlu_human_sexuality",
"mmlu_econometrics"
],
"mmlu_other": [
"mmlu_virology",
"mmlu_management",
"mmlu_global_facts",
"mmlu_clinical_knowledge",
"mmlu_professional_medicine",
"mmlu_business_ethics",
"mmlu_nutrition",
"mmlu_professional_accounting",
"mmlu_college_medicine",
"mmlu_medical_genetics",
"mmlu_miscellaneous",
"mmlu_human_aging",
"mmlu_marketing"
],
"mmlu_stem": [
"mmlu_college_biology",
"mmlu_astronomy",
"mmlu_high_school_computer_science",
"mmlu_college_computer_science",
"mmlu_college_mathematics",
"mmlu_computer_security",
"mmlu_machine_learning",
"mmlu_high_school_physics",
"mmlu_college_physics",
"mmlu_elementary_mathematics",
"mmlu_high_school_mathematics",
"mmlu_high_school_statistics",
"mmlu_conceptual_physics",
"mmlu_high_school_biology",
"mmlu_college_chemistry",
"mmlu_abstract_algebra",
"mmlu_high_school_chemistry",
"mmlu_electrical_engineering",
"mmlu_anatomy"
],
"mmlu": [
"mmlu_stem",
"mmlu_other",
"mmlu_social_sciences",
"mmlu_humanities"
]
},
"configs": {
"mmlu_abstract_algebra": {
"task": "mmlu_abstract_algebra",
"task_alias": "abstract_algebra",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "abstract_algebra",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_anatomy": {
"task": "mmlu_anatomy",
"task_alias": "anatomy",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "anatomy",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_astronomy": {
"task": "mmlu_astronomy",
"task_alias": "astronomy",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "astronomy",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_business_ethics": {
"task": "mmlu_business_ethics",
"task_alias": "business_ethics",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "business_ethics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_clinical_knowledge": {
"task": "mmlu_clinical_knowledge",
"task_alias": "clinical_knowledge",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "clinical_knowledge",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_college_biology": {
"task": "mmlu_college_biology",
"task_alias": "college_biology",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "college_biology",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_college_chemistry": {
"task": "mmlu_college_chemistry",
"task_alias": "college_chemistry",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "college_chemistry",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_college_computer_science": {
"task": "mmlu_college_computer_science",
"task_alias": "college_computer_science",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "college_computer_science",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_college_mathematics": {
"task": "mmlu_college_mathematics",
"task_alias": "college_mathematics",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "college_mathematics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_college_medicine": {
"task": "mmlu_college_medicine",
"task_alias": "college_medicine",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "college_medicine",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_college_physics": {
"task": "mmlu_college_physics",
"task_alias": "college_physics",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "college_physics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_computer_security": {
"task": "mmlu_computer_security",
"task_alias": "computer_security",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "computer_security",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_conceptual_physics": {
"task": "mmlu_conceptual_physics",
"task_alias": "conceptual_physics",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "conceptual_physics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_econometrics": {
"task": "mmlu_econometrics",
"task_alias": "econometrics",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "econometrics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_electrical_engineering": {
"task": "mmlu_electrical_engineering",
"task_alias": "electrical_engineering",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "electrical_engineering",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_elementary_mathematics": {
"task": "mmlu_elementary_mathematics",
"task_alias": "elementary_mathematics",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "elementary_mathematics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_formal_logic": {
"task": "mmlu_formal_logic",
"task_alias": "formal_logic",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "formal_logic",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_global_facts": {
"task": "mmlu_global_facts",
"task_alias": "global_facts",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "global_facts",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_biology": {
"task": "mmlu_high_school_biology",
"task_alias": "high_school_biology",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_biology",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_chemistry": {
"task": "mmlu_high_school_chemistry",
"task_alias": "high_school_chemistry",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_chemistry",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_computer_science": {
"task": "mmlu_high_school_computer_science",
"task_alias": "high_school_computer_science",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_computer_science",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_european_history": {
"task": "mmlu_high_school_european_history",
"task_alias": "high_school_european_history",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_european_history",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_geography": {
"task": "mmlu_high_school_geography",
"task_alias": "high_school_geography",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_geography",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_government_and_politics": {
"task": "mmlu_high_school_government_and_politics",
"task_alias": "high_school_government_and_politics",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_government_and_politics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_macroeconomics": {
"task": "mmlu_high_school_macroeconomics",
"task_alias": "high_school_macroeconomics",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_macroeconomics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_mathematics": {
"task": "mmlu_high_school_mathematics",
"task_alias": "high_school_mathematics",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_mathematics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_microeconomics": {
"task": "mmlu_high_school_microeconomics",
"task_alias": "high_school_microeconomics",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_microeconomics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_physics": {
"task": "mmlu_high_school_physics",
"task_alias": "high_school_physics",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_physics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_psychology": {
"task": "mmlu_high_school_psychology",
"task_alias": "high_school_psychology",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_psychology",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_statistics": {
"task": "mmlu_high_school_statistics",
"task_alias": "high_school_statistics",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_statistics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_us_history": {
"task": "mmlu_high_school_us_history",
"task_alias": "high_school_us_history",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_us_history",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_high_school_world_history": {
"task": "mmlu_high_school_world_history",
"task_alias": "high_school_world_history",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "high_school_world_history",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_human_aging": {
"task": "mmlu_human_aging",
"task_alias": "human_aging",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "human_aging",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_human_sexuality": {
"task": "mmlu_human_sexuality",
"task_alias": "human_sexuality",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "human_sexuality",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_international_law": {
"task": "mmlu_international_law",
"task_alias": "international_law",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "international_law",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_jurisprudence": {
"task": "mmlu_jurisprudence",
"task_alias": "jurisprudence",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "jurisprudence",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_logical_fallacies": {
"task": "mmlu_logical_fallacies",
"task_alias": "logical_fallacies",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "logical_fallacies",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_machine_learning": {
"task": "mmlu_machine_learning",
"task_alias": "machine_learning",
"tag": "mmlu_stem_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "machine_learning",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_management": {
"task": "mmlu_management",
"task_alias": "management",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "management",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_marketing": {
"task": "mmlu_marketing",
"task_alias": "marketing",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "marketing",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_medical_genetics": {
"task": "mmlu_medical_genetics",
"task_alias": "medical_genetics",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "medical_genetics",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_miscellaneous": {
"task": "mmlu_miscellaneous",
"task_alias": "miscellaneous",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "miscellaneous",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_moral_disputes": {
"task": "mmlu_moral_disputes",
"task_alias": "moral_disputes",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "moral_disputes",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_moral_scenarios": {
"task": "mmlu_moral_scenarios",
"task_alias": "moral_scenarios",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "moral_scenarios",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_nutrition": {
"task": "mmlu_nutrition",
"task_alias": "nutrition",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "nutrition",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_philosophy": {
"task": "mmlu_philosophy",
"task_alias": "philosophy",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "philosophy",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_prehistory": {
"task": "mmlu_prehistory",
"task_alias": "prehistory",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "prehistory",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_professional_accounting": {
"task": "mmlu_professional_accounting",
"task_alias": "professional_accounting",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "professional_accounting",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_professional_law": {
"task": "mmlu_professional_law",
"task_alias": "professional_law",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "professional_law",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_professional_medicine": {
"task": "mmlu_professional_medicine",
"task_alias": "professional_medicine",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "professional_medicine",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_professional_psychology": {
"task": "mmlu_professional_psychology",
"task_alias": "professional_psychology",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "professional_psychology",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_public_relations": {
"task": "mmlu_public_relations",
"task_alias": "public_relations",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "public_relations",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_security_studies": {
"task": "mmlu_security_studies",
"task_alias": "security_studies",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "security_studies",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_sociology": {
"task": "mmlu_sociology",
"task_alias": "sociology",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "sociology",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_us_foreign_policy": {
"task": "mmlu_us_foreign_policy",
"task_alias": "us_foreign_policy",
"tag": "mmlu_social_sciences_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "us_foreign_policy",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_virology": {
"task": "mmlu_virology",
"task_alias": "virology",
"tag": "mmlu_other_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "virology",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
},
"mmlu_world_religions": {
"task": "mmlu_world_religions",
"task_alias": "world_religions",
"tag": "mmlu_humanities_tasks",
"dataset_path": "hails/mmlu_no_train",
"dataset_name": "world_religions",
"dataset_kwargs": {
"trust_remote_code": true
},
"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": 0,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": false,
"metadata": {
"version": 1.0
}
}
},
"versions": {
"mmlu": 2,
"mmlu_abstract_algebra": 1.0,
"mmlu_anatomy": 1.0,
"mmlu_astronomy": 1.0,
"mmlu_business_ethics": 1.0,
"mmlu_clinical_knowledge": 1.0,
"mmlu_college_biology": 1.0,
"mmlu_college_chemistry": 1.0,
"mmlu_college_computer_science": 1.0,
"mmlu_college_mathematics": 1.0,
"mmlu_college_medicine": 1.0,
"mmlu_college_physics": 1.0,
"mmlu_computer_security": 1.0,
"mmlu_conceptual_physics": 1.0,
"mmlu_econometrics": 1.0,
"mmlu_electrical_engineering": 1.0,
"mmlu_elementary_mathematics": 1.0,
"mmlu_formal_logic": 1.0,
"mmlu_global_facts": 1.0,
"mmlu_high_school_biology": 1.0,
"mmlu_high_school_chemistry": 1.0,
"mmlu_high_school_computer_science": 1.0,
"mmlu_high_school_european_history": 1.0,
"mmlu_high_school_geography": 1.0,
"mmlu_high_school_government_and_politics": 1.0,
"mmlu_high_school_macroeconomics": 1.0,
"mmlu_high_school_mathematics": 1.0,
"mmlu_high_school_microeconomics": 1.0,
"mmlu_high_school_physics": 1.0,
"mmlu_high_school_psychology": 1.0,
"mmlu_high_school_statistics": 1.0,
"mmlu_high_school_us_history": 1.0,
"mmlu_high_school_world_history": 1.0,
"mmlu_human_aging": 1.0,
"mmlu_human_sexuality": 1.0,
"mmlu_humanities": 2,
"mmlu_international_law": 1.0,
"mmlu_jurisprudence": 1.0,
"mmlu_logical_fallacies": 1.0,
"mmlu_machine_learning": 1.0,
"mmlu_management": 1.0,
"mmlu_marketing": 1.0,
"mmlu_medical_genetics": 1.0,
"mmlu_miscellaneous": 1.0,
"mmlu_moral_disputes": 1.0,
"mmlu_moral_scenarios": 1.0,
"mmlu_nutrition": 1.0,
"mmlu_other": 2,
"mmlu_philosophy": 1.0,
"mmlu_prehistory": 1.0,
"mmlu_professional_accounting": 1.0,
"mmlu_professional_law": 1.0,
"mmlu_professional_medicine": 1.0,
"mmlu_professional_psychology": 1.0,
"mmlu_public_relations": 1.0,
"mmlu_security_studies": 1.0,
"mmlu_social_sciences": 2,
"mmlu_sociology": 1.0,
"mmlu_stem": 2,
"mmlu_us_foreign_policy": 1.0,
"mmlu_virology": 1.0,
"mmlu_world_religions": 1.0
},
"n-shot": {
"mmlu_abstract_algebra": 0,
"mmlu_anatomy": 0,
"mmlu_astronomy": 0,
"mmlu_business_ethics": 0,
"mmlu_clinical_knowledge": 0,
"mmlu_college_biology": 0,
"mmlu_college_chemistry": 0,
"mmlu_college_computer_science": 0,
"mmlu_college_mathematics": 0,
"mmlu_college_medicine": 0,
"mmlu_college_physics": 0,
"mmlu_computer_security": 0,
"mmlu_conceptual_physics": 0,
"mmlu_econometrics": 0,
"mmlu_electrical_engineering": 0,
"mmlu_elementary_mathematics": 0,
"mmlu_formal_logic": 0,
"mmlu_global_facts": 0,
"mmlu_high_school_biology": 0,
"mmlu_high_school_chemistry": 0,
"mmlu_high_school_computer_science": 0,
"mmlu_high_school_european_history": 0,
"mmlu_high_school_geography": 0,
"mmlu_high_school_government_and_politics": 0,
"mmlu_high_school_macroeconomics": 0,
"mmlu_high_school_mathematics": 0,
"mmlu_high_school_microeconomics": 0,
"mmlu_high_school_physics": 0,
"mmlu_high_school_psychology": 0,
"mmlu_high_school_statistics": 0,
"mmlu_high_school_us_history": 0,
"mmlu_high_school_world_history": 0,
"mmlu_human_aging": 0,
"mmlu_human_sexuality": 0,
"mmlu_international_law": 0,
"mmlu_jurisprudence": 0,
"mmlu_logical_fallacies": 0,
"mmlu_machine_learning": 0,
"mmlu_management": 0,
"mmlu_marketing": 0,
"mmlu_medical_genetics": 0,
"mmlu_miscellaneous": 0,
"mmlu_moral_disputes": 0,
"mmlu_moral_scenarios": 0,
"mmlu_nutrition": 0,
"mmlu_philosophy": 0,
"mmlu_prehistory": 0,
"mmlu_professional_accounting": 0,
"mmlu_professional_law": 0,
"mmlu_professional_medicine": 0,
"mmlu_professional_psychology": 0,
"mmlu_public_relations": 0,
"mmlu_security_studies": 0,
"mmlu_sociology": 0,
"mmlu_us_foreign_policy": 0,
"mmlu_virology": 0,
"mmlu_world_religions": 0
},
"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_college_biology": {
"original": 144,
"effective": 144
},
"mmlu_astronomy": {
"original": 152,
"effective": 152
},
"mmlu_high_school_computer_science": {
"original": 100,
"effective": 100
},
"mmlu_college_computer_science": {
"original": 100,
"effective": 100
},
"mmlu_college_mathematics": {
"original": 100,
"effective": 100
},
"mmlu_computer_security": {
"original": 100,
"effective": 100
},
"mmlu_machine_learning": {
"original": 112,
"effective": 112
},
"mmlu_high_school_physics": {
"original": 151,
"effective": 151
},
"mmlu_college_physics": {
"original": 102,
"effective": 102
},
"mmlu_elementary_mathematics": {
"original": 378,
"effective": 378
},
"mmlu_high_school_mathematics": {
"original": 270,
"effective": 270
},
"mmlu_high_school_statistics": {
"original": 216,
"effective": 216
},
"mmlu_conceptual_physics": {
"original": 235,
"effective": 235
},
"mmlu_high_school_biology": {
"original": 310,
"effective": 310
},
"mmlu_college_chemistry": {
"original": 100,
"effective": 100
},
"mmlu_abstract_algebra": {
"original": 100,
"effective": 100
},
"mmlu_high_school_chemistry": {
"original": 203,
"effective": 203
},
"mmlu_electrical_engineering": {
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"effective": 145
},
"mmlu_anatomy": {
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"effective": 135
},
"mmlu_virology": {
"original": 166,
"effective": 166
},
"mmlu_management": {
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"effective": 103
},
"mmlu_global_facts": {
"original": 100,
"effective": 100
},
"mmlu_clinical_knowledge": {
"original": 265,
"effective": 265
},
"mmlu_professional_medicine": {
"original": 272,
"effective": 272
},
"mmlu_business_ethics": {
"original": 100,
"effective": 100
},
"mmlu_nutrition": {
"original": 306,
"effective": 306
},
"mmlu_professional_accounting": {
"original": 282,
"effective": 282
},
"mmlu_college_medicine": {
"original": 173,
"effective": 173
},
"mmlu_medical_genetics": {
"original": 100,
"effective": 100
},
"mmlu_miscellaneous": {
"original": 783,
"effective": 783
},
"mmlu_human_aging": {
"original": 223,
"effective": 223
},
"mmlu_marketing": {
"original": 234,
"effective": 234
},
"mmlu_high_school_government_and_politics": {
"original": 193,
"effective": 193
},
"mmlu_public_relations": {
"original": 110,
"effective": 110
},
"mmlu_high_school_microeconomics": {
"original": 238,
"effective": 238
},
"mmlu_us_foreign_policy": {
"original": 100,
"effective": 100
},
"mmlu_high_school_psychology": {
"original": 545,
"effective": 545
},
"mmlu_high_school_geography": {
"original": 198,
"effective": 198
},
"mmlu_professional_psychology": {
"original": 612,
"effective": 612
},
"mmlu_high_school_macroeconomics": {
"original": 390,
"effective": 390
},
"mmlu_security_studies": {
"original": 245,
"effective": 245
},
"mmlu_sociology": {
"original": 201,
"effective": 201
},
"mmlu_human_sexuality": {
"original": 131,
"effective": 131
},
"mmlu_econometrics": {
"original": 114,
"effective": 114
},
"mmlu_world_religions": {
"original": 171,
"effective": 171
},
"mmlu_moral_disputes": {
"original": 346,
"effective": 346
},
"mmlu_logical_fallacies": {
"original": 163,
"effective": 163
},
"mmlu_prehistory": {
"original": 324,
"effective": 324
},
"mmlu_professional_law": {
"original": 1534,
"effective": 1534
},
"mmlu_philosophy": {
"original": 311,
"effective": 311
},
"mmlu_moral_scenarios": {
"original": 895,
"effective": 895
},
"mmlu_jurisprudence": {
"original": 108,
"effective": 108
},
"mmlu_international_law": {
"original": 121,
"effective": 121
},
"mmlu_high_school_european_history": {
"original": 165,
"effective": 165
},
"mmlu_formal_logic": {
"original": 126,
"effective": 126
},
"mmlu_high_school_us_history": {
"original": 204,
"effective": 204
},
"mmlu_high_school_world_history": {
"original": 237,
"effective": 237
}
},
"config": {
"model": "hf",
"model_args": "parallelize=True,pretrained=inceptionai/jais-family-30b-16k-chat,trust_remote_code=True,mm=False,trust_remote_code=True",
"model_num_parameters": 30208489464,
"model_dtype": "torch.float32",
"model_revision": "main",
"model_sha": "369f88eeee4d313155f1b1dca4ebec90f9f9f2a4",
"batch_size": 1,
"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": "3127d82f",
"date": 1731336782.934575,
"pretty_env_info": "PyTorch version: 2.1.0a0+29c30b1\nIs debug build: False\nCUDA used to build PyTorch: 12.2\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.3 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.27.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-1064-azure-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.128\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Probably one of the following:\n/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.4\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: 48 bits physical, 48 bits virtual\nByte Order: Little Endian\nCPU(s): 96\nOn-line CPU(s) list: 0-95\nVendor ID: AuthenticAMD\nModel name: AMD EPYC 7V12 64-Core Processor\nCPU family: 23\nModel: 49\nThread(s) per core: 1\nCore(s) per socket: 48\nSocket(s): 2\nStepping: 0\nBogoMIPS: 4890.87\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 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 ssbd vmmcall fsgsbase bmi1 avx2 smep bmi2 rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 clzero xsaveerptr rdpru arat umip rdpid\nHypervisor vendor: Microsoft\nVirtualization type: full\nL1d cache: 3 MiB (96 instances)\nL1i cache: 3 MiB (96 instances)\nL2 cache: 48 MiB (96 instances)\nL3 cache: 384 MiB (24 instances)\nNUMA node(s): 4\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: Mitigation; untrained return thunk; SMT disabled\nVulnerability Spec rstack overflow: Mitigation; safe RET, no microcode\nVulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2: Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected\nVulnerability Srbds: Not affected\nVulnerability Tsx async abort: Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.22.2\n[pip3] pytorch-lightning==2.0.7\n[pip3] pytorch-quantization==2.1.2\n[pip3] torch==2.1.0a0+29c30b1\n[pip3] torch-tensorrt==2.0.0.dev0\n[pip3] torchaudio==2.1.0\n[pip3] torchdata==0.7.0a0\n[pip3] torchmetrics==1.2.0\n[pip3] torchvision==0.16.0a0\n[pip3] triton==2.0.0.dev20221202\n[conda] Could not collect",
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"tokenizer_pad_token": [
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],
"tokenizer_eos_token": [
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],
"tokenizer_bos_token": [
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],
"eot_token_id": 0,
"max_length": 16384,
"task_hashes": {},
"model_source": "hf",
"model_name": "inceptionai/jais-family-30b-16k-chat",
"model_name_sanitized": "inceptionai__jais-family-30b-16k-chat",
"system_instruction": null,
"system_instruction_sha": null,
"fewshot_as_multiturn": false,
"chat_template": null,
"chat_template_sha": null,
"start_time": 148924.409827349,
"end_time": 154552.998906196,
"total_evaluation_time_seconds": "5628.589078846999"
}
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