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ALLaM-7B-Instruct-preview/evaluations/en/jais-family-13b-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": 0.5190856003418316,
"acc_stderr,none": 0.00402831164950512,
"alias": "mmlu"
},
"mmlu_humanities": {
"acc,none": 0.4862911795961743,
"acc_stderr,none": 0.00687259966449505,
"alias": " - humanities"
},
"mmlu_formal_logic": {
"alias": " - formal_logic",
"acc,none": 0.4126984126984127,
"acc_stderr,none": 0.04403438954768176
},
"mmlu_high_school_european_history": {
"alias": " - high_school_european_history",
"acc,none": 0.7151515151515152,
"acc_stderr,none": 0.0352439084451178
},
"mmlu_high_school_us_history": {
"alias": " - high_school_us_history",
"acc,none": 0.6862745098039216,
"acc_stderr,none": 0.03256685484460389
},
"mmlu_high_school_world_history": {
"alias": " - high_school_world_history",
"acc,none": 0.7679324894514767,
"acc_stderr,none": 0.02747974455080851
},
"mmlu_international_law": {
"alias": " - international_law",
"acc,none": 0.7024793388429752,
"acc_stderr,none": 0.04173349148083499
},
"mmlu_jurisprudence": {
"alias": " - jurisprudence",
"acc,none": 0.6203703703703703,
"acc_stderr,none": 0.04691521224077742
},
"mmlu_logical_fallacies": {
"alias": " - logical_fallacies",
"acc,none": 0.5828220858895705,
"acc_stderr,none": 0.038741028598180814
},
"mmlu_moral_disputes": {
"alias": " - moral_disputes",
"acc,none": 0.5722543352601156,
"acc_stderr,none": 0.026636539741116082
},
"mmlu_moral_scenarios": {
"alias": " - moral_scenarios",
"acc,none": 0.24022346368715083,
"acc_stderr,none": 0.014288343803925319
},
"mmlu_philosophy": {
"alias": " - philosophy",
"acc,none": 0.6205787781350482,
"acc_stderr,none": 0.027559949802347813
},
"mmlu_prehistory": {
"alias": " - prehistory",
"acc,none": 0.5895061728395061,
"acc_stderr,none": 0.027371350925124764
},
"mmlu_professional_law": {
"alias": " - professional_law",
"acc,none": 0.4067796610169492,
"acc_stderr,none": 0.01254632559656954
},
"mmlu_world_religions": {
"alias": " - world_religions",
"acc,none": 0.7485380116959064,
"acc_stderr,none": 0.033275044238468436
},
"mmlu_other": {
"acc,none": 0.5835210814290313,
"acc_stderr,none": 0.008561660886354683,
"alias": " - other"
},
"mmlu_business_ethics": {
"alias": " - business_ethics",
"acc,none": 0.53,
"acc_stderr,none": 0.05016135580465919
},
"mmlu_clinical_knowledge": {
"alias": " - clinical_knowledge",
"acc,none": 0.5773584905660377,
"acc_stderr,none": 0.030402331445769544
},
"mmlu_college_medicine": {
"alias": " - college_medicine",
"acc,none": 0.49710982658959535,
"acc_stderr,none": 0.038124005659748335
},
"mmlu_global_facts": {
"alias": " - global_facts",
"acc,none": 0.24,
"acc_stderr,none": 0.042923469599092816
},
"mmlu_human_aging": {
"alias": " - human_aging",
"acc,none": 0.6143497757847534,
"acc_stderr,none": 0.03266842214289201
},
"mmlu_management": {
"alias": " - management",
"acc,none": 0.6601941747572816,
"acc_stderr,none": 0.04689765937278135
},
"mmlu_marketing": {
"alias": " - marketing",
"acc,none": 0.7564102564102564,
"acc_stderr,none": 0.02812096650391438
},
"mmlu_medical_genetics": {
"alias": " - medical_genetics",
"acc,none": 0.66,
"acc_stderr,none": 0.04760952285695238
},
"mmlu_miscellaneous": {
"alias": " - miscellaneous",
"acc,none": 0.7126436781609196,
"acc_stderr,none": 0.0161824107306827
},
"mmlu_nutrition": {
"alias": " - nutrition",
"acc,none": 0.5522875816993464,
"acc_stderr,none": 0.02847293847803353
},
"mmlu_professional_accounting": {
"alias": " - professional_accounting",
"acc,none": 0.3900709219858156,
"acc_stderr,none": 0.029097675599463926
},
"mmlu_professional_medicine": {
"alias": " - professional_medicine",
"acc,none": 0.5073529411764706,
"acc_stderr,none": 0.030369552523902173
},
"mmlu_virology": {
"alias": " - virology",
"acc,none": 0.4457831325301205,
"acc_stderr,none": 0.03869543323472101
},
"mmlu_social_sciences": {
"acc,none": 0.5914852128696783,
"acc_stderr,none": 0.008614191331314497,
"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": 0.6515151515151515,
"acc_stderr,none": 0.033948539651564025
},
"mmlu_high_school_government_and_politics": {
"alias": " - high_school_government_and_politics",
"acc,none": 0.7357512953367875,
"acc_stderr,none": 0.03182155050916647
},
"mmlu_high_school_macroeconomics": {
"alias": " - high_school_macroeconomics",
"acc,none": 0.4564102564102564,
"acc_stderr,none": 0.02525448542479961
},
"mmlu_high_school_microeconomics": {
"alias": " - high_school_microeconomics",
"acc,none": 0.5042016806722689,
"acc_stderr,none": 0.03247734334448111
},
"mmlu_high_school_psychology": {
"alias": " - high_school_psychology",
"acc,none": 0.7009174311926606,
"acc_stderr,none": 0.019630417285415175
},
"mmlu_human_sexuality": {
"alias": " - human_sexuality",
"acc,none": 0.648854961832061,
"acc_stderr,none": 0.04186445163013751
},
"mmlu_professional_psychology": {
"alias": " - professional_psychology",
"acc,none": 0.5081699346405228,
"acc_stderr,none": 0.020225134343057265
},
"mmlu_public_relations": {
"alias": " - public_relations",
"acc,none": 0.5272727272727272,
"acc_stderr,none": 0.04782001791380062
},
"mmlu_security_studies": {
"alias": " - security_studies",
"acc,none": 0.6,
"acc_stderr,none": 0.03136250240935893
},
"mmlu_sociology": {
"alias": " - sociology",
"acc,none": 0.7711442786069652,
"acc_stderr,none": 0.029705284056772426
},
"mmlu_us_foreign_policy": {
"alias": " - us_foreign_policy",
"acc,none": 0.77,
"acc_stderr,none": 0.042295258468165065
},
"mmlu_stem": {
"acc,none": 0.43387250237868696,
"acc_stderr,none": 0.00865079641005906,
"alias": " - stem"
},
"mmlu_abstract_algebra": {
"alias": " - abstract_algebra",
"acc,none": 0.32,
"acc_stderr,none": 0.046882617226215034
},
"mmlu_anatomy": {
"alias": " - anatomy",
"acc,none": 0.4888888888888889,
"acc_stderr,none": 0.04318275491977976
},
"mmlu_astronomy": {
"alias": " - astronomy",
"acc,none": 0.618421052631579,
"acc_stderr,none": 0.03953173377749193
},
"mmlu_college_biology": {
"alias": " - college_biology",
"acc,none": 0.5069444444444444,
"acc_stderr,none": 0.04180806750294938
},
"mmlu_college_chemistry": {
"alias": " - college_chemistry",
"acc,none": 0.34,
"acc_stderr,none": 0.04760952285695236
},
"mmlu_college_computer_science": {
"alias": " - college_computer_science",
"acc,none": 0.39,
"acc_stderr,none": 0.04902071300001975
},
"mmlu_college_mathematics": {
"alias": " - college_mathematics",
"acc,none": 0.38,
"acc_stderr,none": 0.048783173121456316
},
"mmlu_college_physics": {
"alias": " - college_physics",
"acc,none": 0.3137254901960784,
"acc_stderr,none": 0.04617034827006718
},
"mmlu_computer_security": {
"alias": " - computer_security",
"acc,none": 0.62,
"acc_stderr,none": 0.04878317312145633
},
"mmlu_conceptual_physics": {
"alias": " - conceptual_physics",
"acc,none": 0.43829787234042555,
"acc_stderr,none": 0.03243618636108101
},
"mmlu_electrical_engineering": {
"alias": " - electrical_engineering",
"acc,none": 0.5172413793103449,
"acc_stderr,none": 0.04164188720169375
},
"mmlu_elementary_mathematics": {
"alias": " - elementary_mathematics",
"acc,none": 0.35714285714285715,
"acc_stderr,none": 0.024677862841332783
},
"mmlu_high_school_biology": {
"alias": " - high_school_biology",
"acc,none": 0.6193548387096774,
"acc_stderr,none": 0.02762171783290704
},
"mmlu_high_school_chemistry": {
"alias": " - high_school_chemistry",
"acc,none": 0.4236453201970443,
"acc_stderr,none": 0.03476725747649036
},
"mmlu_high_school_computer_science": {
"alias": " - high_school_computer_science",
"acc,none": 0.46,
"acc_stderr,none": 0.05009082659620333
},
"mmlu_high_school_mathematics": {
"alias": " - high_school_mathematics",
"acc,none": 0.32222222222222224,
"acc_stderr,none": 0.028493465091028593
},
"mmlu_high_school_physics": {
"alias": " - high_school_physics",
"acc,none": 0.32450331125827814,
"acc_stderr,none": 0.03822746937658753
},
"mmlu_high_school_statistics": {
"alias": " - high_school_statistics",
"acc,none": 0.3425925925925926,
"acc_stderr,none": 0.032365852526021574
},
"mmlu_machine_learning": {
"alias": " - machine_learning",
"acc,none": 0.45535714285714285,
"acc_stderr,none": 0.04726835553719099
}
},
"groups": {
"mmlu": {
"acc,none": 0.5190856003418316,
"acc_stderr,none": 0.00402831164950512,
"alias": "mmlu"
},
"mmlu_humanities": {
"acc,none": 0.4862911795961743,
"acc_stderr,none": 0.00687259966449505,
"alias": " - humanities"
},
"mmlu_other": {
"acc,none": 0.5835210814290313,
"acc_stderr,none": 0.008561660886354683,
"alias": " - other"
},
"mmlu_social_sciences": {
"acc,none": 0.5914852128696783,
"acc_stderr,none": 0.008614191331314497,
"alias": " - social sciences"
},
"mmlu_stem": {
"acc,none": 0.43387250237868696,
"acc_stderr,none": 0.00865079641005906,
"alias": " - stem"
}
},
"group_subtasks": {
"mmlu_humanities": [
"mmlu_moral_disputes",
"mmlu_high_school_world_history",
"mmlu_high_school_european_history",
"mmlu_moral_scenarios",
"mmlu_logical_fallacies",
"mmlu_philosophy",
"mmlu_formal_logic",
"mmlu_prehistory",
"mmlu_professional_law",
"mmlu_high_school_us_history",
"mmlu_jurisprudence",
"mmlu_international_law",
"mmlu_world_religions"
],
"mmlu_social_sciences": [
"mmlu_high_school_government_and_politics",
"mmlu_sociology",
"mmlu_public_relations",
"mmlu_security_studies",
"mmlu_high_school_geography",
"mmlu_human_sexuality",
"mmlu_high_school_psychology",
"mmlu_us_foreign_policy",
"mmlu_professional_psychology",
"mmlu_high_school_microeconomics",
"mmlu_econometrics",
"mmlu_high_school_macroeconomics"
],
"mmlu_other": [
"mmlu_clinical_knowledge",
"mmlu_marketing",
"mmlu_miscellaneous",
"mmlu_professional_medicine",
"mmlu_college_medicine",
"mmlu_nutrition",
"mmlu_business_ethics",
"mmlu_global_facts",
"mmlu_medical_genetics",
"mmlu_virology",
"mmlu_professional_accounting",
"mmlu_human_aging",
"mmlu_management"
],
"mmlu_stem": [
"mmlu_college_chemistry",
"mmlu_computer_security",
"mmlu_anatomy",
"mmlu_high_school_chemistry",
"mmlu_high_school_biology",
"mmlu_electrical_engineering",
"mmlu_college_mathematics",
"mmlu_high_school_physics",
"mmlu_machine_learning",
"mmlu_astronomy",
"mmlu_conceptual_physics",
"mmlu_college_biology",
"mmlu_abstract_algebra",
"mmlu_high_school_statistics",
"mmlu_college_physics",
"mmlu_elementary_mathematics",
"mmlu_high_school_mathematics",
"mmlu_college_computer_science",
"mmlu_high_school_computer_science"
],
"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_chemistry": {
"original": 100,
"effective": 100
},
"mmlu_computer_security": {
"original": 100,
"effective": 100
},
"mmlu_anatomy": {
"original": 135,
"effective": 135
},
"mmlu_high_school_chemistry": {
"original": 203,
"effective": 203
},
"mmlu_high_school_biology": {
"original": 310,
"effective": 310
},
"mmlu_electrical_engineering": {
"original": 145,
"effective": 145
},
"mmlu_college_mathematics": {
"original": 100,
"effective": 100
},
"mmlu_high_school_physics": {
"original": 151,
"effective": 151
},
"mmlu_machine_learning": {
"original": 112,
"effective": 112
},
"mmlu_astronomy": {
"original": 152,
"effective": 152
},
"mmlu_conceptual_physics": {
"original": 235,
"effective": 235
},
"mmlu_college_biology": {
"original": 144,
"effective": 144
},
"mmlu_abstract_algebra": {
"original": 100,
"effective": 100
},
"mmlu_high_school_statistics": {
"original": 216,
"effective": 216
},
"mmlu_college_physics": {
"original": 102,
"effective": 102
},
"mmlu_elementary_mathematics": {
"original": 378,
"effective": 378
},
"mmlu_high_school_mathematics": {
"original": 270,
"effective": 270
},
"mmlu_college_computer_science": {
"original": 100,
"effective": 100
},
"mmlu_high_school_computer_science": {
"original": 100,
"effective": 100
},
"mmlu_clinical_knowledge": {
"original": 265,
"effective": 265
},
"mmlu_marketing": {
"original": 234,
"effective": 234
},
"mmlu_miscellaneous": {
"original": 783,
"effective": 783
},
"mmlu_professional_medicine": {
"original": 272,
"effective": 272
},
"mmlu_college_medicine": {
"original": 173,
"effective": 173
},
"mmlu_nutrition": {
"original": 306,
"effective": 306
},
"mmlu_business_ethics": {
"original": 100,
"effective": 100
},
"mmlu_global_facts": {
"original": 100,
"effective": 100
},
"mmlu_medical_genetics": {
"original": 100,
"effective": 100
},
"mmlu_virology": {
"original": 166,
"effective": 166
},
"mmlu_professional_accounting": {
"original": 282,
"effective": 282
},
"mmlu_human_aging": {
"original": 223,
"effective": 223
},
"mmlu_management": {
"original": 103,
"effective": 103
},
"mmlu_high_school_government_and_politics": {
"original": 193,
"effective": 193
},
"mmlu_sociology": {
"original": 201,
"effective": 201
},
"mmlu_public_relations": {
"original": 110,
"effective": 110
},
"mmlu_security_studies": {
"original": 245,
"effective": 245
},
"mmlu_high_school_geography": {
"original": 198,
"effective": 198
},
"mmlu_human_sexuality": {
"original": 131,
"effective": 131
},
"mmlu_high_school_psychology": {
"original": 545,
"effective": 545
},
"mmlu_us_foreign_policy": {
"original": 100,
"effective": 100
},
"mmlu_professional_psychology": {
"original": 612,
"effective": 612
},
"mmlu_high_school_microeconomics": {
"original": 238,
"effective": 238
},
"mmlu_econometrics": {
"original": 114,
"effective": 114
},
"mmlu_high_school_macroeconomics": {
"original": 390,
"effective": 390
},
"mmlu_moral_disputes": {
"original": 346,
"effective": 346
},
"mmlu_high_school_world_history": {
"original": 237,
"effective": 237
},
"mmlu_high_school_european_history": {
"original": 165,
"effective": 165
},
"mmlu_moral_scenarios": {
"original": 895,
"effective": 895
},
"mmlu_logical_fallacies": {
"original": 163,
"effective": 163
},
"mmlu_philosophy": {
"original": 311,
"effective": 311
},
"mmlu_formal_logic": {
"original": 126,
"effective": 126
},
"mmlu_prehistory": {
"original": 324,
"effective": 324
},
"mmlu_professional_law": {
"original": 1534,
"effective": 1534
},
"mmlu_high_school_us_history": {
"original": 204,
"effective": 204
},
"mmlu_jurisprudence": {
"original": 108,
"effective": 108
},
"mmlu_international_law": {
"original": 121,
"effective": 121
},
"mmlu_world_religions": {
"original": 171,
"effective": 171
}
},
"config": {
"model": "vllm",
"model_args": "pretrained=inceptionai/jais-family-13b-chat,tensor_parallel_size=1,data_parallel_size=2,gpu_memory_utilization=0.9,download_dir=/tmp,enforce_eager=True",
"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": "788a3672",
"date": 1737539565.7477572,
"pretty_env_info": "PyTorch version: 2.4.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.3 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 80GB PCIe\nGPU 1: NVIDIA A100 80GB PCIe\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): 48\nOn-line CPU(s) list: 0-47\nVendor ID: AuthenticAMD\nModel name: AMD EPYC 7V13 64-Core Processor\nCPU family: 25\nModel: 1\nThread(s) per core: 1\nCore(s) per socket: 48\nSocket(s): 1\nStepping: 1\nBogoMIPS: 4890.86\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\nHypervisor vendor: Microsoft\nVirtualization type: full\nL1d cache: 1.5 MiB (48 instances)\nL1i cache: 1.5 MiB (48 instances)\nL2 cache: 24 MiB (48 instances)\nL3 cache: 192 MiB (6 instances)\nNUMA node(s): 2\nNUMA node0 CPU(s): 0-23\nNUMA node1 CPU(s): 24-47\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; BHI Not affected\nVulnerability Srbds: Not affected\nVulnerability Tsx async abort: Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.4\n[pip3] onnx==1.14.0\n[pip3] pytorch-lightning==2.0.7\n[pip3] pytorch-quantization==2.1.2\n[pip3] torch==2.4.0\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==0.19.0\n[pip3] triton==3.0.0\n[conda] Could not collect",
"transformers_version": "4.48.1",
"upper_git_hash": null,
"tokenizer_pad_token": [
"<|endoftext|>",
"0"
],
"tokenizer_eos_token": [
"<|endoftext|>",
"0"
],
"tokenizer_bos_token": [
"<|endoftext|>",
"0"
],
"eot_token_id": 0,
"max_length": 2048,
"task_hashes": {},
"model_source": "vllm",
"model_name": "inceptionai/jais-family-13b-chat",
"model_name_sanitized": "inceptionai__jais-family-13b-chat",
"system_instruction": null,
"system_instruction_sha": null,
"fewshot_as_multiturn": false,
"chat_template": null,
"chat_template_sha": null,
"start_time": 17378.186912084,
"end_time": 18143.24832748,
"total_evaluation_time_seconds": "765.0614153960014"
}
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