3283 lines
96 KiB
JSON
3283 lines
96 KiB
JSON
{
|
|
"results": {
|
|
"mmlu": {
|
|
"acc,none": 0.819897450505626,
|
|
"acc_stderr,none": 0.0031087150831215155,
|
|
"alias": "mmlu"
|
|
},
|
|
"mmlu_humanities": {
|
|
"acc,none": 0.8104144527098831,
|
|
"acc_stderr,none": 0.005519815358782114,
|
|
"alias": " - humanities"
|
|
},
|
|
"mmlu_formal_logic": {
|
|
"alias": " - formal_logic",
|
|
"acc,none": 0.6746031746031746,
|
|
"acc_stderr,none": 0.04190596438871136
|
|
},
|
|
"mmlu_high_school_european_history": {
|
|
"alias": " - high_school_european_history",
|
|
"acc,none": 0.8424242424242424,
|
|
"acc_stderr,none": 0.02845038880528436
|
|
},
|
|
"mmlu_high_school_us_history": {
|
|
"alias": " - high_school_us_history",
|
|
"acc,none": 0.946078431372549,
|
|
"acc_stderr,none": 0.015852465281106908
|
|
},
|
|
"mmlu_high_school_world_history": {
|
|
"alias": " - high_school_world_history",
|
|
"acc,none": 0.9240506329113924,
|
|
"acc_stderr,none": 0.017244633251065695
|
|
},
|
|
"mmlu_international_law": {
|
|
"alias": " - international_law",
|
|
"acc,none": 0.8925619834710744,
|
|
"acc_stderr,none": 0.028268812192540627
|
|
},
|
|
"mmlu_jurisprudence": {
|
|
"alias": " - jurisprudence",
|
|
"acc,none": 0.8611111111111112,
|
|
"acc_stderr,none": 0.03343270062869622
|
|
},
|
|
"mmlu_logical_fallacies": {
|
|
"alias": " - logical_fallacies",
|
|
"acc,none": 0.8895705521472392,
|
|
"acc_stderr,none": 0.024624937788941318
|
|
},
|
|
"mmlu_moral_disputes": {
|
|
"alias": " - moral_disputes",
|
|
"acc,none": 0.8583815028901735,
|
|
"acc_stderr,none": 0.018771138684059014
|
|
},
|
|
"mmlu_moral_scenarios": {
|
|
"alias": " - moral_scenarios",
|
|
"acc,none": 0.8737430167597765,
|
|
"acc_stderr,none": 0.01110838193631582
|
|
},
|
|
"mmlu_philosophy": {
|
|
"alias": " - philosophy",
|
|
"acc,none": 0.8681672025723473,
|
|
"acc_stderr,none": 0.019214654265652387
|
|
},
|
|
"mmlu_prehistory": {
|
|
"alias": " - prehistory",
|
|
"acc,none": 0.904320987654321,
|
|
"acc_stderr,none": 0.016366973744175266
|
|
},
|
|
"mmlu_professional_law": {
|
|
"alias": " - professional_law",
|
|
"acc,none": 0.6734028683181226,
|
|
"acc_stderr,none": 0.011977676704715999
|
|
},
|
|
"mmlu_world_religions": {
|
|
"alias": " - world_religions",
|
|
"acc,none": 0.9122807017543859,
|
|
"acc_stderr,none": 0.02169638394388924
|
|
},
|
|
"mmlu_other": {
|
|
"acc,none": 0.8419697457354361,
|
|
"acc_stderr,none": 0.006258463660583839,
|
|
"alias": " - other"
|
|
},
|
|
"mmlu_business_ethics": {
|
|
"alias": " - business_ethics",
|
|
"acc,none": 0.81,
|
|
"acc_stderr,none": 0.03942772444036625
|
|
},
|
|
"mmlu_clinical_knowledge": {
|
|
"alias": " - clinical_knowledge",
|
|
"acc,none": 0.8415094339622642,
|
|
"acc_stderr,none": 0.022476528710167712
|
|
},
|
|
"mmlu_college_medicine": {
|
|
"alias": " - college_medicine",
|
|
"acc,none": 0.7572254335260116,
|
|
"acc_stderr,none": 0.0326926380614177
|
|
},
|
|
"mmlu_global_facts": {
|
|
"alias": " - global_facts",
|
|
"acc,none": 0.61,
|
|
"acc_stderr,none": 0.04902071300001975
|
|
},
|
|
"mmlu_human_aging": {
|
|
"alias": " - human_aging",
|
|
"acc,none": 0.820627802690583,
|
|
"acc_stderr,none": 0.025749819569192804
|
|
},
|
|
"mmlu_management": {
|
|
"alias": " - management",
|
|
"acc,none": 0.9029126213592233,
|
|
"acc_stderr,none": 0.02931596291881347
|
|
},
|
|
"mmlu_marketing": {
|
|
"alias": " - marketing",
|
|
"acc,none": 0.9273504273504274,
|
|
"acc_stderr,none": 0.017004368568132366
|
|
},
|
|
"mmlu_medical_genetics": {
|
|
"alias": " - medical_genetics",
|
|
"acc,none": 0.9,
|
|
"acc_stderr,none": 0.030151134457776334
|
|
},
|
|
"mmlu_miscellaneous": {
|
|
"alias": " - miscellaneous",
|
|
"acc,none": 0.929757343550447,
|
|
"acc_stderr,none": 0.009138646868032285
|
|
},
|
|
"mmlu_nutrition": {
|
|
"alias": " - nutrition",
|
|
"acc,none": 0.8954248366013072,
|
|
"acc_stderr,none": 0.017521808294174466
|
|
},
|
|
"mmlu_professional_accounting": {
|
|
"alias": " - professional_accounting",
|
|
"acc,none": 0.6808510638297872,
|
|
"acc_stderr,none": 0.027807990141320196
|
|
},
|
|
"mmlu_professional_medicine": {
|
|
"alias": " - professional_medicine",
|
|
"acc,none": 0.9117647058823529,
|
|
"acc_stderr,none": 0.017229707781039032
|
|
},
|
|
"mmlu_virology": {
|
|
"alias": " - virology",
|
|
"acc,none": 0.572289156626506,
|
|
"acc_stderr,none": 0.038515976837185335
|
|
},
|
|
"mmlu_social_sciences": {
|
|
"acc,none": 0.8813779655508612,
|
|
"acc_stderr,none": 0.005724484350303844,
|
|
"alias": " - social sciences"
|
|
},
|
|
"mmlu_econometrics": {
|
|
"alias": " - econometrics",
|
|
"acc,none": 0.7017543859649122,
|
|
"acc_stderr,none": 0.04303684033537315
|
|
},
|
|
"mmlu_high_school_geography": {
|
|
"alias": " - high_school_geography",
|
|
"acc,none": 0.9393939393939394,
|
|
"acc_stderr,none": 0.016999994927421613
|
|
},
|
|
"mmlu_high_school_government_and_politics": {
|
|
"alias": " - high_school_government_and_politics",
|
|
"acc,none": 0.9740932642487047,
|
|
"acc_stderr,none": 0.011464523356953176
|
|
},
|
|
"mmlu_high_school_macroeconomics": {
|
|
"alias": " - high_school_macroeconomics",
|
|
"acc,none": 0.8615384615384616,
|
|
"acc_stderr,none": 0.017511651708913754
|
|
},
|
|
"mmlu_high_school_microeconomics": {
|
|
"alias": " - high_school_microeconomics",
|
|
"acc,none": 0.9033613445378151,
|
|
"acc_stderr,none": 0.019192520709708723
|
|
},
|
|
"mmlu_high_school_psychology": {
|
|
"alias": " - high_school_psychology",
|
|
"acc,none": 0.9412844036697248,
|
|
"acc_stderr,none": 0.010079470534014019
|
|
},
|
|
"mmlu_human_sexuality": {
|
|
"alias": " - human_sexuality",
|
|
"acc,none": 0.8549618320610687,
|
|
"acc_stderr,none": 0.030884661089515382
|
|
},
|
|
"mmlu_professional_psychology": {
|
|
"alias": " - professional_psychology",
|
|
"acc,none": 0.8545751633986928,
|
|
"acc_stderr,none": 0.014261782879481027
|
|
},
|
|
"mmlu_public_relations": {
|
|
"alias": " - public_relations",
|
|
"acc,none": 0.7363636363636363,
|
|
"acc_stderr,none": 0.04220224692971987
|
|
},
|
|
"mmlu_security_studies": {
|
|
"alias": " - security_studies",
|
|
"acc,none": 0.8163265306122449,
|
|
"acc_stderr,none": 0.024789071332007626
|
|
},
|
|
"mmlu_sociology": {
|
|
"alias": " - sociology",
|
|
"acc,none": 0.9203980099502488,
|
|
"acc_stderr,none": 0.019139685633503815
|
|
},
|
|
"mmlu_us_foreign_policy": {
|
|
"alias": " - us_foreign_policy",
|
|
"acc,none": 0.93,
|
|
"acc_stderr,none": 0.025643239997624294
|
|
},
|
|
"mmlu_stem": {
|
|
"acc,none": 0.7522993973993023,
|
|
"acc_stderr,none": 0.007389783284914271,
|
|
"alias": " - stem"
|
|
},
|
|
"mmlu_abstract_algebra": {
|
|
"alias": " - abstract_algebra",
|
|
"acc,none": 0.6,
|
|
"acc_stderr,none": 0.04923659639173309
|
|
},
|
|
"mmlu_anatomy": {
|
|
"alias": " - anatomy",
|
|
"acc,none": 0.8296296296296296,
|
|
"acc_stderr,none": 0.03247781185995593
|
|
},
|
|
"mmlu_astronomy": {
|
|
"alias": " - astronomy",
|
|
"acc,none": 0.9078947368421053,
|
|
"acc_stderr,none": 0.02353268597044349
|
|
},
|
|
"mmlu_college_biology": {
|
|
"alias": " - college_biology",
|
|
"acc,none": 0.9166666666666666,
|
|
"acc_stderr,none": 0.023112508176051233
|
|
},
|
|
"mmlu_college_chemistry": {
|
|
"alias": " - college_chemistry",
|
|
"acc,none": 0.59,
|
|
"acc_stderr,none": 0.04943110704237102
|
|
},
|
|
"mmlu_college_computer_science": {
|
|
"alias": " - college_computer_science",
|
|
"acc,none": 0.67,
|
|
"acc_stderr,none": 0.04725815626252607
|
|
},
|
|
"mmlu_college_mathematics": {
|
|
"alias": " - college_mathematics",
|
|
"acc,none": 0.55,
|
|
"acc_stderr,none": 0.05
|
|
},
|
|
"mmlu_college_physics": {
|
|
"alias": " - college_physics",
|
|
"acc,none": 0.6470588235294118,
|
|
"acc_stderr,none": 0.04755129616062947
|
|
},
|
|
"mmlu_computer_security": {
|
|
"alias": " - computer_security",
|
|
"acc,none": 0.84,
|
|
"acc_stderr,none": 0.03684529491774707
|
|
},
|
|
"mmlu_conceptual_physics": {
|
|
"alias": " - conceptual_physics",
|
|
"acc,none": 0.8297872340425532,
|
|
"acc_stderr,none": 0.0245680965612607
|
|
},
|
|
"mmlu_electrical_engineering": {
|
|
"alias": " - electrical_engineering",
|
|
"acc,none": 0.7655172413793103,
|
|
"acc_stderr,none": 0.035306258743465914
|
|
},
|
|
"mmlu_elementary_mathematics": {
|
|
"alias": " - elementary_mathematics",
|
|
"acc,none": 0.7592592592592593,
|
|
"acc_stderr,none": 0.02201908001221789
|
|
},
|
|
"mmlu_high_school_biology": {
|
|
"alias": " - high_school_biology",
|
|
"acc,none": 0.9129032258064517,
|
|
"acc_stderr,none": 0.01604110074169668
|
|
},
|
|
"mmlu_high_school_chemistry": {
|
|
"alias": " - high_school_chemistry",
|
|
"acc,none": 0.7536945812807881,
|
|
"acc_stderr,none": 0.030315099285617732
|
|
},
|
|
"mmlu_high_school_computer_science": {
|
|
"alias": " - high_school_computer_science",
|
|
"acc,none": 0.92,
|
|
"acc_stderr,none": 0.027265992434429086
|
|
},
|
|
"mmlu_high_school_mathematics": {
|
|
"alias": " - high_school_mathematics",
|
|
"acc,none": 0.5370370370370371,
|
|
"acc_stderr,none": 0.03040178640610151
|
|
},
|
|
"mmlu_high_school_physics": {
|
|
"alias": " - high_school_physics",
|
|
"acc,none": 0.6225165562913907,
|
|
"acc_stderr,none": 0.0395802723112157
|
|
},
|
|
"mmlu_high_school_statistics": {
|
|
"alias": " - high_school_statistics",
|
|
"acc,none": 0.7546296296296297,
|
|
"acc_stderr,none": 0.029346665094372948
|
|
},
|
|
"mmlu_machine_learning": {
|
|
"alias": " - machine_learning",
|
|
"acc,none": 0.6785714285714286,
|
|
"acc_stderr,none": 0.04432804055291519
|
|
}
|
|
},
|
|
"groups": {
|
|
"mmlu": {
|
|
"acc,none": 0.819897450505626,
|
|
"acc_stderr,none": 0.0031087150831215155,
|
|
"alias": "mmlu"
|
|
},
|
|
"mmlu_humanities": {
|
|
"acc,none": 0.8104144527098831,
|
|
"acc_stderr,none": 0.005519815358782114,
|
|
"alias": " - humanities"
|
|
},
|
|
"mmlu_other": {
|
|
"acc,none": 0.8419697457354361,
|
|
"acc_stderr,none": 0.006258463660583839,
|
|
"alias": " - other"
|
|
},
|
|
"mmlu_social_sciences": {
|
|
"acc,none": 0.8813779655508612,
|
|
"acc_stderr,none": 0.005724484350303844,
|
|
"alias": " - social sciences"
|
|
},
|
|
"mmlu_stem": {
|
|
"acc,none": 0.7522993973993023,
|
|
"acc_stderr,none": 0.007389783284914271,
|
|
"alias": " - stem"
|
|
}
|
|
},
|
|
"group_subtasks": {
|
|
"mmlu_humanities": [
|
|
"mmlu_moral_scenarios",
|
|
"mmlu_formal_logic",
|
|
"mmlu_high_school_european_history",
|
|
"mmlu_high_school_world_history",
|
|
"mmlu_high_school_us_history",
|
|
"mmlu_international_law",
|
|
"mmlu_professional_law",
|
|
"mmlu_logical_fallacies",
|
|
"mmlu_prehistory",
|
|
"mmlu_moral_disputes",
|
|
"mmlu_world_religions",
|
|
"mmlu_philosophy",
|
|
"mmlu_jurisprudence"
|
|
],
|
|
"mmlu_social_sciences": [
|
|
"mmlu_econometrics",
|
|
"mmlu_public_relations",
|
|
"mmlu_security_studies",
|
|
"mmlu_professional_psychology",
|
|
"mmlu_sociology",
|
|
"mmlu_us_foreign_policy",
|
|
"mmlu_human_sexuality",
|
|
"mmlu_high_school_government_and_politics",
|
|
"mmlu_high_school_macroeconomics",
|
|
"mmlu_high_school_geography",
|
|
"mmlu_high_school_psychology",
|
|
"mmlu_high_school_microeconomics"
|
|
],
|
|
"mmlu_other": [
|
|
"mmlu_human_aging",
|
|
"mmlu_miscellaneous",
|
|
"mmlu_professional_medicine",
|
|
"mmlu_college_medicine",
|
|
"mmlu_clinical_knowledge",
|
|
"mmlu_marketing",
|
|
"mmlu_business_ethics",
|
|
"mmlu_global_facts",
|
|
"mmlu_professional_accounting",
|
|
"mmlu_virology",
|
|
"mmlu_nutrition",
|
|
"mmlu_management",
|
|
"mmlu_medical_genetics"
|
|
],
|
|
"mmlu_stem": [
|
|
"mmlu_college_mathematics",
|
|
"mmlu_college_chemistry",
|
|
"mmlu_college_physics",
|
|
"mmlu_high_school_biology",
|
|
"mmlu_astronomy",
|
|
"mmlu_college_computer_science",
|
|
"mmlu_conceptual_physics",
|
|
"mmlu_high_school_chemistry",
|
|
"mmlu_high_school_statistics",
|
|
"mmlu_electrical_engineering",
|
|
"mmlu_abstract_algebra",
|
|
"mmlu_high_school_mathematics",
|
|
"mmlu_high_school_physics",
|
|
"mmlu_high_school_computer_science",
|
|
"mmlu_machine_learning",
|
|
"mmlu_anatomy",
|
|
"mmlu_elementary_mathematics",
|
|
"mmlu_college_biology",
|
|
"mmlu_computer_security"
|
|
],
|
|
"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_mathematics": {
|
|
"original": 100,
|
|
"effective": 100
|
|
},
|
|
"mmlu_college_chemistry": {
|
|
"original": 100,
|
|
"effective": 100
|
|
},
|
|
"mmlu_college_physics": {
|
|
"original": 102,
|
|
"effective": 102
|
|
},
|
|
"mmlu_high_school_biology": {
|
|
"original": 310,
|
|
"effective": 310
|
|
},
|
|
"mmlu_astronomy": {
|
|
"original": 152,
|
|
"effective": 152
|
|
},
|
|
"mmlu_college_computer_science": {
|
|
"original": 100,
|
|
"effective": 100
|
|
},
|
|
"mmlu_conceptual_physics": {
|
|
"original": 235,
|
|
"effective": 235
|
|
},
|
|
"mmlu_high_school_chemistry": {
|
|
"original": 203,
|
|
"effective": 203
|
|
},
|
|
"mmlu_high_school_statistics": {
|
|
"original": 216,
|
|
"effective": 216
|
|
},
|
|
"mmlu_electrical_engineering": {
|
|
"original": 145,
|
|
"effective": 145
|
|
},
|
|
"mmlu_abstract_algebra": {
|
|
"original": 100,
|
|
"effective": 100
|
|
},
|
|
"mmlu_high_school_mathematics": {
|
|
"original": 270,
|
|
"effective": 270
|
|
},
|
|
"mmlu_high_school_physics": {
|
|
"original": 151,
|
|
"effective": 151
|
|
},
|
|
"mmlu_high_school_computer_science": {
|
|
"original": 100,
|
|
"effective": 100
|
|
},
|
|
"mmlu_machine_learning": {
|
|
"original": 112,
|
|
"effective": 112
|
|
},
|
|
"mmlu_anatomy": {
|
|
"original": 135,
|
|
"effective": 135
|
|
},
|
|
"mmlu_elementary_mathematics": {
|
|
"original": 378,
|
|
"effective": 378
|
|
},
|
|
"mmlu_college_biology": {
|
|
"original": 144,
|
|
"effective": 144
|
|
},
|
|
"mmlu_computer_security": {
|
|
"original": 100,
|
|
"effective": 100
|
|
},
|
|
"mmlu_human_aging": {
|
|
"original": 223,
|
|
"effective": 223
|
|
},
|
|
"mmlu_miscellaneous": {
|
|
"original": 783,
|
|
"effective": 783
|
|
},
|
|
"mmlu_professional_medicine": {
|
|
"original": 272,
|
|
"effective": 272
|
|
},
|
|
"mmlu_college_medicine": {
|
|
"original": 173,
|
|
"effective": 173
|
|
},
|
|
"mmlu_clinical_knowledge": {
|
|
"original": 265,
|
|
"effective": 265
|
|
},
|
|
"mmlu_marketing": {
|
|
"original": 234,
|
|
"effective": 234
|
|
},
|
|
"mmlu_business_ethics": {
|
|
"original": 100,
|
|
"effective": 100
|
|
},
|
|
"mmlu_global_facts": {
|
|
"original": 100,
|
|
"effective": 100
|
|
},
|
|
"mmlu_professional_accounting": {
|
|
"original": 282,
|
|
"effective": 282
|
|
},
|
|
"mmlu_virology": {
|
|
"original": 166,
|
|
"effective": 166
|
|
},
|
|
"mmlu_nutrition": {
|
|
"original": 306,
|
|
"effective": 306
|
|
},
|
|
"mmlu_management": {
|
|
"original": 103,
|
|
"effective": 103
|
|
},
|
|
"mmlu_medical_genetics": {
|
|
"original": 100,
|
|
"effective": 100
|
|
},
|
|
"mmlu_econometrics": {
|
|
"original": 114,
|
|
"effective": 114
|
|
},
|
|
"mmlu_public_relations": {
|
|
"original": 110,
|
|
"effective": 110
|
|
},
|
|
"mmlu_security_studies": {
|
|
"original": 245,
|
|
"effective": 245
|
|
},
|
|
"mmlu_professional_psychology": {
|
|
"original": 612,
|
|
"effective": 612
|
|
},
|
|
"mmlu_sociology": {
|
|
"original": 201,
|
|
"effective": 201
|
|
},
|
|
"mmlu_us_foreign_policy": {
|
|
"original": 100,
|
|
"effective": 100
|
|
},
|
|
"mmlu_human_sexuality": {
|
|
"original": 131,
|
|
"effective": 131
|
|
},
|
|
"mmlu_high_school_government_and_politics": {
|
|
"original": 193,
|
|
"effective": 193
|
|
},
|
|
"mmlu_high_school_macroeconomics": {
|
|
"original": 390,
|
|
"effective": 390
|
|
},
|
|
"mmlu_high_school_geography": {
|
|
"original": 198,
|
|
"effective": 198
|
|
},
|
|
"mmlu_high_school_psychology": {
|
|
"original": 545,
|
|
"effective": 545
|
|
},
|
|
"mmlu_high_school_microeconomics": {
|
|
"original": 238,
|
|
"effective": 238
|
|
},
|
|
"mmlu_moral_scenarios": {
|
|
"original": 895,
|
|
"effective": 895
|
|
},
|
|
"mmlu_formal_logic": {
|
|
"original": 126,
|
|
"effective": 126
|
|
},
|
|
"mmlu_high_school_european_history": {
|
|
"original": 165,
|
|
"effective": 165
|
|
},
|
|
"mmlu_high_school_world_history": {
|
|
"original": 237,
|
|
"effective": 237
|
|
},
|
|
"mmlu_high_school_us_history": {
|
|
"original": 204,
|
|
"effective": 204
|
|
},
|
|
"mmlu_international_law": {
|
|
"original": 121,
|
|
"effective": 121
|
|
},
|
|
"mmlu_professional_law": {
|
|
"original": 1534,
|
|
"effective": 1534
|
|
},
|
|
"mmlu_logical_fallacies": {
|
|
"original": 163,
|
|
"effective": 163
|
|
},
|
|
"mmlu_prehistory": {
|
|
"original": 324,
|
|
"effective": 324
|
|
},
|
|
"mmlu_moral_disputes": {
|
|
"original": 346,
|
|
"effective": 346
|
|
},
|
|
"mmlu_world_religions": {
|
|
"original": 171,
|
|
"effective": 171
|
|
},
|
|
"mmlu_philosophy": {
|
|
"original": 311,
|
|
"effective": 311
|
|
},
|
|
"mmlu_jurisprudence": {
|
|
"original": 108,
|
|
"effective": 108
|
|
}
|
|
},
|
|
"config": {
|
|
"model": "vllm",
|
|
"model_args": "pretrained=meta-llama/Llama-3.3-70B-Instruct,tensor_parallel_size=4,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": "150ae04f",
|
|
"date": 1737585757.4256392,
|
|
"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-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==1.26.4\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": "086919bd66f4e15fdcd4b792a7b27a698c1ba091",
|
|
"tokenizer_pad_token": [
|
|
"<|finetune_right_pad_id|>",
|
|
"128004"
|
|
],
|
|
"tokenizer_eos_token": [
|
|
"<|eot_id|>",
|
|
"128009"
|
|
],
|
|
"tokenizer_bos_token": [
|
|
"<|begin_of_text|>",
|
|
"128000"
|
|
],
|
|
"eot_token_id": 128009,
|
|
"max_length": 131072,
|
|
"task_hashes": {},
|
|
"model_source": "vllm",
|
|
"model_name": "meta-llama/Llama-3.3-70B-Instruct",
|
|
"model_name_sanitized": "meta-llama__Llama-3.3-70B-Instruct",
|
|
"system_instruction": null,
|
|
"system_instruction_sha": null,
|
|
"fewshot_as_multiturn": false,
|
|
"chat_template": null,
|
|
"chat_template_sha": null,
|
|
"start_time": 127778.472369656,
|
|
"end_time": 128825.949499582,
|
|
"total_evaluation_time_seconds": "1047.4771299260028"
|
|
} |