|
{ |
|
"results": { |
|
"mmlu": { |
|
"acc,none": 0.5959977211223473, |
|
"acc_stderr,none": 0.003940274143686019, |
|
"alias": "mmlu" |
|
}, |
|
"mmlu_humanities": { |
|
"alias": " - humanities", |
|
"acc,none": 0.5598299681190223, |
|
"acc_stderr,none": 0.006857746834862335 |
|
}, |
|
"mmlu_formal_logic": { |
|
"alias": " - formal_logic", |
|
"acc,none": 0.40476190476190477, |
|
"acc_stderr,none": 0.043902592653775614 |
|
}, |
|
"mmlu_high_school_european_history": { |
|
"alias": " - high_school_european_history", |
|
"acc,none": 0.7272727272727273, |
|
"acc_stderr,none": 0.0347769116216366 |
|
}, |
|
"mmlu_high_school_us_history": { |
|
"alias": " - high_school_us_history", |
|
"acc,none": 0.7794117647058824, |
|
"acc_stderr,none": 0.029102254389674093 |
|
}, |
|
"mmlu_high_school_world_history": { |
|
"alias": " - high_school_world_history", |
|
"acc,none": 0.7679324894514767, |
|
"acc_stderr,none": 0.02747974455080852 |
|
}, |
|
"mmlu_international_law": { |
|
"alias": " - international_law", |
|
"acc,none": 0.7933884297520661, |
|
"acc_stderr,none": 0.03695980128098824 |
|
}, |
|
"mmlu_jurisprudence": { |
|
"alias": " - jurisprudence", |
|
"acc,none": 0.7314814814814815, |
|
"acc_stderr,none": 0.042844679680521934 |
|
}, |
|
"mmlu_logical_fallacies": { |
|
"alias": " - logical_fallacies", |
|
"acc,none": 0.7177914110429447, |
|
"acc_stderr,none": 0.03536117886664743 |
|
}, |
|
"mmlu_moral_disputes": { |
|
"alias": " - moral_disputes", |
|
"acc,none": 0.684971098265896, |
|
"acc_stderr,none": 0.0250093137900697 |
|
}, |
|
"mmlu_moral_scenarios": { |
|
"alias": " - moral_scenarios", |
|
"acc,none": 0.3888268156424581, |
|
"acc_stderr,none": 0.01630389953079613 |
|
}, |
|
"mmlu_philosophy": { |
|
"alias": " - philosophy", |
|
"acc,none": 0.6913183279742765, |
|
"acc_stderr,none": 0.026236965881153256 |
|
}, |
|
"mmlu_prehistory": { |
|
"alias": " - prehistory", |
|
"acc,none": 0.6851851851851852, |
|
"acc_stderr,none": 0.025842248700902175 |
|
}, |
|
"mmlu_professional_law": { |
|
"alias": " - professional_law", |
|
"acc,none": 0.4335071707953064, |
|
"acc_stderr,none": 0.012656810383983964 |
|
}, |
|
"mmlu_world_religions": { |
|
"alias": " - world_religions", |
|
"acc,none": 0.8362573099415205, |
|
"acc_stderr,none": 0.028380919596145866 |
|
}, |
|
"mmlu_other": { |
|
"alias": " - other", |
|
"acc,none": 0.657547473447055, |
|
"acc_stderr,none": 0.008223099667026796 |
|
}, |
|
"mmlu_business_ethics": { |
|
"alias": " - business_ethics", |
|
"acc,none": 0.56, |
|
"acc_stderr,none": 0.04988876515698589 |
|
}, |
|
"mmlu_clinical_knowledge": { |
|
"alias": " - clinical_knowledge", |
|
"acc,none": 0.660377358490566, |
|
"acc_stderr,none": 0.02914690474779833 |
|
}, |
|
"mmlu_college_medicine": { |
|
"alias": " - college_medicine", |
|
"acc,none": 0.5895953757225434, |
|
"acc_stderr,none": 0.03750757044895536 |
|
}, |
|
"mmlu_global_facts": { |
|
"alias": " - global_facts", |
|
"acc,none": 0.37, |
|
"acc_stderr,none": 0.048523658709391 |
|
}, |
|
"mmlu_human_aging": { |
|
"alias": " - human_aging", |
|
"acc,none": 0.6098654708520179, |
|
"acc_stderr,none": 0.03273766725459156 |
|
}, |
|
"mmlu_management": { |
|
"alias": " - management", |
|
"acc,none": 0.7378640776699029, |
|
"acc_stderr,none": 0.04354631077260595 |
|
}, |
|
"mmlu_marketing": { |
|
"alias": " - marketing", |
|
"acc,none": 0.8589743589743589, |
|
"acc_stderr,none": 0.022801382534597518 |
|
}, |
|
"mmlu_medical_genetics": { |
|
"alias": " - medical_genetics", |
|
"acc,none": 0.67, |
|
"acc_stderr,none": 0.04725815626252607 |
|
}, |
|
"mmlu_miscellaneous": { |
|
"alias": " - miscellaneous", |
|
"acc,none": 0.7752234993614304, |
|
"acc_stderr,none": 0.014927447101937157 |
|
}, |
|
"mmlu_nutrition": { |
|
"alias": " - nutrition", |
|
"acc,none": 0.6928104575163399, |
|
"acc_stderr,none": 0.026415601914389002 |
|
}, |
|
"mmlu_professional_accounting": { |
|
"alias": " - professional_accounting", |
|
"acc,none": 0.4432624113475177, |
|
"acc_stderr,none": 0.029634838473766006 |
|
}, |
|
"mmlu_professional_medicine": { |
|
"alias": " - professional_medicine", |
|
"acc,none": 0.6102941176470589, |
|
"acc_stderr,none": 0.02962466358115969 |
|
}, |
|
"mmlu_virology": { |
|
"alias": " - virology", |
|
"acc,none": 0.5, |
|
"acc_stderr,none": 0.03892494720807614 |
|
}, |
|
"mmlu_social_sciences": { |
|
"alias": " - social_sciences", |
|
"acc,none": 0.693532661683458, |
|
"acc_stderr,none": 0.008120210287270358 |
|
}, |
|
"mmlu_econometrics": { |
|
"alias": " - econometrics", |
|
"acc,none": 0.40350877192982454, |
|
"acc_stderr,none": 0.046151869625837026 |
|
}, |
|
"mmlu_high_school_geography": { |
|
"alias": " - high_school_geography", |
|
"acc,none": 0.7626262626262627, |
|
"acc_stderr,none": 0.030313710538198892 |
|
}, |
|
"mmlu_high_school_government_and_politics": { |
|
"alias": " - high_school_government_and_politics", |
|
"acc,none": 0.8393782383419689, |
|
"acc_stderr,none": 0.02649905770139744 |
|
}, |
|
"mmlu_high_school_macroeconomics": { |
|
"alias": " - high_school_macroeconomics", |
|
"acc,none": 0.5666666666666667, |
|
"acc_stderr,none": 0.025124653525885124 |
|
}, |
|
"mmlu_high_school_microeconomics": { |
|
"alias": " - high_school_microeconomics", |
|
"acc,none": 0.6470588235294118, |
|
"acc_stderr,none": 0.031041941304059278 |
|
}, |
|
"mmlu_high_school_psychology": { |
|
"alias": " - high_school_psychology", |
|
"acc,none": 0.7926605504587156, |
|
"acc_stderr,none": 0.017381415563608667 |
|
}, |
|
"mmlu_human_sexuality": { |
|
"alias": " - human_sexuality", |
|
"acc,none": 0.7480916030534351, |
|
"acc_stderr,none": 0.03807387116306086 |
|
}, |
|
"mmlu_professional_psychology": { |
|
"alias": " - professional_psychology", |
|
"acc,none": 0.6290849673202614, |
|
"acc_stderr,none": 0.01954210156485412 |
|
}, |
|
"mmlu_public_relations": { |
|
"alias": " - public_relations", |
|
"acc,none": 0.7272727272727273, |
|
"acc_stderr,none": 0.04265792110940588 |
|
}, |
|
"mmlu_security_studies": { |
|
"alias": " - security_studies", |
|
"acc,none": 0.710204081632653, |
|
"acc_stderr,none": 0.02904308868330433 |
|
}, |
|
"mmlu_sociology": { |
|
"alias": " - sociology", |
|
"acc,none": 0.736318407960199, |
|
"acc_stderr,none": 0.031157150869355568 |
|
}, |
|
"mmlu_us_foreign_policy": { |
|
"alias": " - us_foreign_policy", |
|
"acc,none": 0.83, |
|
"acc_stderr,none": 0.0377525168068637 |
|
}, |
|
"mmlu_stem": { |
|
"alias": " - stem", |
|
"acc,none": 0.4941325721535046, |
|
"acc_stderr,none": 0.008646286993166217 |
|
}, |
|
"mmlu_abstract_algebra": { |
|
"alias": " - abstract_algebra", |
|
"acc,none": 0.3, |
|
"acc_stderr,none": 0.046056618647183814 |
|
}, |
|
"mmlu_anatomy": { |
|
"alias": " - anatomy", |
|
"acc,none": 0.5777777777777777, |
|
"acc_stderr,none": 0.04266763404099582 |
|
}, |
|
"mmlu_astronomy": { |
|
"alias": " - astronomy", |
|
"acc,none": 0.6381578947368421, |
|
"acc_stderr,none": 0.03910525752849724 |
|
}, |
|
"mmlu_college_biology": { |
|
"alias": " - college_biology", |
|
"acc,none": 0.6805555555555556, |
|
"acc_stderr,none": 0.03899073687357335 |
|
}, |
|
"mmlu_college_chemistry": { |
|
"alias": " - college_chemistry", |
|
"acc,none": 0.41, |
|
"acc_stderr,none": 0.049431107042371025 |
|
}, |
|
"mmlu_college_computer_science": { |
|
"alias": " - college_computer_science", |
|
"acc,none": 0.51, |
|
"acc_stderr,none": 0.05024183937956912 |
|
}, |
|
"mmlu_college_mathematics": { |
|
"alias": " - college_mathematics", |
|
"acc,none": 0.42, |
|
"acc_stderr,none": 0.04960449637488584 |
|
}, |
|
"mmlu_college_physics": { |
|
"alias": " - college_physics", |
|
"acc,none": 0.38235294117647056, |
|
"acc_stderr,none": 0.04835503696107224 |
|
}, |
|
"mmlu_computer_security": { |
|
"alias": " - computer_security", |
|
"acc,none": 0.67, |
|
"acc_stderr,none": 0.04725815626252609 |
|
}, |
|
"mmlu_conceptual_physics": { |
|
"alias": " - conceptual_physics", |
|
"acc,none": 0.5404255319148936, |
|
"acc_stderr,none": 0.03257901482099835 |
|
}, |
|
"mmlu_electrical_engineering": { |
|
"alias": " - electrical_engineering", |
|
"acc,none": 0.5862068965517241, |
|
"acc_stderr,none": 0.04104269211806232 |
|
}, |
|
"mmlu_elementary_mathematics": { |
|
"alias": " - elementary_mathematics", |
|
"acc,none": 0.3915343915343915, |
|
"acc_stderr,none": 0.025138091388851112 |
|
}, |
|
"mmlu_high_school_biology": { |
|
"alias": " - high_school_biology", |
|
"acc,none": 0.6709677419354839, |
|
"acc_stderr,none": 0.026729499068349954 |
|
}, |
|
"mmlu_high_school_chemistry": { |
|
"alias": " - high_school_chemistry", |
|
"acc,none": 0.5221674876847291, |
|
"acc_stderr,none": 0.035145285621750094 |
|
}, |
|
"mmlu_high_school_computer_science": { |
|
"alias": " - high_school_computer_science", |
|
"acc,none": 0.57, |
|
"acc_stderr,none": 0.049756985195624284 |
|
}, |
|
"mmlu_high_school_mathematics": { |
|
"alias": " - high_school_mathematics", |
|
"acc,none": 0.2962962962962963, |
|
"acc_stderr,none": 0.027840811495871927 |
|
}, |
|
"mmlu_high_school_physics": { |
|
"alias": " - high_school_physics", |
|
"acc,none": 0.33774834437086093, |
|
"acc_stderr,none": 0.03861557546255169 |
|
}, |
|
"mmlu_high_school_statistics": { |
|
"alias": " - high_school_statistics", |
|
"acc,none": 0.4861111111111111, |
|
"acc_stderr,none": 0.03408655867977748 |
|
}, |
|
"mmlu_machine_learning": { |
|
"alias": " - machine_learning", |
|
"acc,none": 0.42857142857142855, |
|
"acc_stderr,none": 0.04697113923010213 |
|
} |
|
}, |
|
"groups": { |
|
"mmlu": { |
|
"acc,none": 0.5959977211223473, |
|
"acc_stderr,none": 0.003940274143686019, |
|
"alias": "mmlu" |
|
}, |
|
"mmlu_humanities": { |
|
"alias": " - humanities", |
|
"acc,none": 0.5598299681190223, |
|
"acc_stderr,none": 0.006857746834862335 |
|
}, |
|
"mmlu_other": { |
|
"alias": " - other", |
|
"acc,none": 0.657547473447055, |
|
"acc_stderr,none": 0.008223099667026796 |
|
}, |
|
"mmlu_social_sciences": { |
|
"alias": " - social_sciences", |
|
"acc,none": 0.693532661683458, |
|
"acc_stderr,none": 0.008120210287270358 |
|
}, |
|
"mmlu_stem": { |
|
"alias": " - stem", |
|
"acc,none": 0.4941325721535046, |
|
"acc_stderr,none": 0.008646286993166217 |
|
} |
|
}, |
|
"configs": { |
|
"mmlu_abstract_algebra": { |
|
"task": "mmlu_abstract_algebra", |
|
"task_alias": "abstract_algebra", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "abstract_algebra", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_anatomy": { |
|
"task": "mmlu_anatomy", |
|
"task_alias": "anatomy", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "anatomy", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about anatomy.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_astronomy": { |
|
"task": "mmlu_astronomy", |
|
"task_alias": "astronomy", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "astronomy", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about astronomy.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_business_ethics": { |
|
"task": "mmlu_business_ethics", |
|
"task_alias": "business_ethics", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "business_ethics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about business ethics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_clinical_knowledge": { |
|
"task": "mmlu_clinical_knowledge", |
|
"task_alias": "clinical_knowledge", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "clinical_knowledge", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_college_biology": { |
|
"task": "mmlu_college_biology", |
|
"task_alias": "college_biology", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "college_biology", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about college biology.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_college_chemistry": { |
|
"task": "mmlu_college_chemistry", |
|
"task_alias": "college_chemistry", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "college_chemistry", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about college chemistry.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_college_computer_science": { |
|
"task": "mmlu_college_computer_science", |
|
"task_alias": "college_computer_science", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "college_computer_science", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about college computer science.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_college_mathematics": { |
|
"task": "mmlu_college_mathematics", |
|
"task_alias": "college_mathematics", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "college_mathematics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about college mathematics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_college_medicine": { |
|
"task": "mmlu_college_medicine", |
|
"task_alias": "college_medicine", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "college_medicine", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about college medicine.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_college_physics": { |
|
"task": "mmlu_college_physics", |
|
"task_alias": "college_physics", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "college_physics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about college physics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_computer_security": { |
|
"task": "mmlu_computer_security", |
|
"task_alias": "computer_security", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "computer_security", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about computer security.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_conceptual_physics": { |
|
"task": "mmlu_conceptual_physics", |
|
"task_alias": "conceptual_physics", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "conceptual_physics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_econometrics": { |
|
"task": "mmlu_econometrics", |
|
"task_alias": "econometrics", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "econometrics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about econometrics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_electrical_engineering": { |
|
"task": "mmlu_electrical_engineering", |
|
"task_alias": "electrical_engineering", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "electrical_engineering", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_elementary_mathematics": { |
|
"task": "mmlu_elementary_mathematics", |
|
"task_alias": "elementary_mathematics", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "elementary_mathematics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_formal_logic": { |
|
"task": "mmlu_formal_logic", |
|
"task_alias": "formal_logic", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "formal_logic", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about formal logic.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_global_facts": { |
|
"task": "mmlu_global_facts", |
|
"task_alias": "global_facts", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "global_facts", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about global facts.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_biology": { |
|
"task": "mmlu_high_school_biology", |
|
"task_alias": "high_school_biology", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_biology", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school biology.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_chemistry": { |
|
"task": "mmlu_high_school_chemistry", |
|
"task_alias": "high_school_chemistry", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_chemistry", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_computer_science": { |
|
"task": "mmlu_high_school_computer_science", |
|
"task_alias": "high_school_computer_science", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_computer_science", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school computer science.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_european_history": { |
|
"task": "mmlu_high_school_european_history", |
|
"task_alias": "high_school_european_history", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_european_history", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school european history.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_geography": { |
|
"task": "mmlu_high_school_geography", |
|
"task_alias": "high_school_geography", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_geography", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school geography.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_government_and_politics": { |
|
"task": "mmlu_high_school_government_and_politics", |
|
"task_alias": "high_school_government_and_politics", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_government_and_politics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_macroeconomics": { |
|
"task": "mmlu_high_school_macroeconomics", |
|
"task_alias": "high_school_macroeconomics", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_macroeconomics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_mathematics": { |
|
"task": "mmlu_high_school_mathematics", |
|
"task_alias": "high_school_mathematics", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_mathematics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_microeconomics": { |
|
"task": "mmlu_high_school_microeconomics", |
|
"task_alias": "high_school_microeconomics", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_microeconomics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_physics": { |
|
"task": "mmlu_high_school_physics", |
|
"task_alias": "high_school_physics", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_physics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school physics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_psychology": { |
|
"task": "mmlu_high_school_psychology", |
|
"task_alias": "high_school_psychology", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_psychology", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school psychology.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_statistics": { |
|
"task": "mmlu_high_school_statistics", |
|
"task_alias": "high_school_statistics", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_statistics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school statistics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_us_history": { |
|
"task": "mmlu_high_school_us_history", |
|
"task_alias": "high_school_us_history", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_us_history", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school us history.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_high_school_world_history": { |
|
"task": "mmlu_high_school_world_history", |
|
"task_alias": "high_school_world_history", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "high_school_world_history", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about high school world history.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_human_aging": { |
|
"task": "mmlu_human_aging", |
|
"task_alias": "human_aging", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "human_aging", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about human aging.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_human_sexuality": { |
|
"task": "mmlu_human_sexuality", |
|
"task_alias": "human_sexuality", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "human_sexuality", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about human sexuality.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_international_law": { |
|
"task": "mmlu_international_law", |
|
"task_alias": "international_law", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "international_law", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about international law.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_jurisprudence": { |
|
"task": "mmlu_jurisprudence", |
|
"task_alias": "jurisprudence", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "jurisprudence", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_logical_fallacies": { |
|
"task": "mmlu_logical_fallacies", |
|
"task_alias": "logical_fallacies", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "logical_fallacies", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_machine_learning": { |
|
"task": "mmlu_machine_learning", |
|
"task_alias": "machine_learning", |
|
"group": "mmlu_stem", |
|
"group_alias": "stem", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "machine_learning", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about machine learning.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_management": { |
|
"task": "mmlu_management", |
|
"task_alias": "management", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "management", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about management.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_marketing": { |
|
"task": "mmlu_marketing", |
|
"task_alias": "marketing", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "marketing", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about marketing.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_medical_genetics": { |
|
"task": "mmlu_medical_genetics", |
|
"task_alias": "medical_genetics", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "medical_genetics", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about medical genetics.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_miscellaneous": { |
|
"task": "mmlu_miscellaneous", |
|
"task_alias": "miscellaneous", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "miscellaneous", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_moral_disputes": { |
|
"task": "mmlu_moral_disputes", |
|
"task_alias": "moral_disputes", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "moral_disputes", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about moral disputes.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_moral_scenarios": { |
|
"task": "mmlu_moral_scenarios", |
|
"task_alias": "moral_scenarios", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "moral_scenarios", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_nutrition": { |
|
"task": "mmlu_nutrition", |
|
"task_alias": "nutrition", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "nutrition", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about nutrition.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_philosophy": { |
|
"task": "mmlu_philosophy", |
|
"task_alias": "philosophy", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "philosophy", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about philosophy.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_prehistory": { |
|
"task": "mmlu_prehistory", |
|
"task_alias": "prehistory", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "prehistory", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about prehistory.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_professional_accounting": { |
|
"task": "mmlu_professional_accounting", |
|
"task_alias": "professional_accounting", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "professional_accounting", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about professional accounting.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_professional_law": { |
|
"task": "mmlu_professional_law", |
|
"task_alias": "professional_law", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "professional_law", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about professional law.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_professional_medicine": { |
|
"task": "mmlu_professional_medicine", |
|
"task_alias": "professional_medicine", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "professional_medicine", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about professional medicine.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_professional_psychology": { |
|
"task": "mmlu_professional_psychology", |
|
"task_alias": "professional_psychology", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "professional_psychology", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about professional psychology.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_public_relations": { |
|
"task": "mmlu_public_relations", |
|
"task_alias": "public_relations", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "public_relations", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about public relations.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_security_studies": { |
|
"task": "mmlu_security_studies", |
|
"task_alias": "security_studies", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "security_studies", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about security studies.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_sociology": { |
|
"task": "mmlu_sociology", |
|
"task_alias": "sociology", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "sociology", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about sociology.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_us_foreign_policy": { |
|
"task": "mmlu_us_foreign_policy", |
|
"task_alias": "us_foreign_policy", |
|
"group": "mmlu_social_sciences", |
|
"group_alias": "social_sciences", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "us_foreign_policy", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_virology": { |
|
"task": "mmlu_virology", |
|
"task_alias": "virology", |
|
"group": "mmlu_other", |
|
"group_alias": "other", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "virology", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about virology.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"mmlu_world_religions": { |
|
"task": "mmlu_world_religions", |
|
"task_alias": "world_religions", |
|
"group": "mmlu_humanities", |
|
"group_alias": "humanities", |
|
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/mmlu_no_train", |
|
"dataset_name": "world_religions", |
|
"test_split": "test", |
|
"fewshot_split": "dev", |
|
"doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", |
|
"doc_to_target": "answer", |
|
"doc_to_choice": [ |
|
"A", |
|
"B", |
|
"C", |
|
"D" |
|
], |
|
"description": "The following are multiple choice questions (with answers) about world religions.\n\n", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"fewshot_config": { |
|
"sampler": "first_n" |
|
}, |
|
"num_fewshot": 5, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
} |
|
}, |
|
"versions": { |
|
"mmlu": "N/A", |
|
"mmlu_abstract_algebra": 0.0, |
|
"mmlu_anatomy": 0.0, |
|
"mmlu_astronomy": 0.0, |
|
"mmlu_business_ethics": 0.0, |
|
"mmlu_clinical_knowledge": 0.0, |
|
"mmlu_college_biology": 0.0, |
|
"mmlu_college_chemistry": 0.0, |
|
"mmlu_college_computer_science": 0.0, |
|
"mmlu_college_mathematics": 0.0, |
|
"mmlu_college_medicine": 0.0, |
|
"mmlu_college_physics": 0.0, |
|
"mmlu_computer_security": 0.0, |
|
"mmlu_conceptual_physics": 0.0, |
|
"mmlu_econometrics": 0.0, |
|
"mmlu_electrical_engineering": 0.0, |
|
"mmlu_elementary_mathematics": 0.0, |
|
"mmlu_formal_logic": 0.0, |
|
"mmlu_global_facts": 0.0, |
|
"mmlu_high_school_biology": 0.0, |
|
"mmlu_high_school_chemistry": 0.0, |
|
"mmlu_high_school_computer_science": 0.0, |
|
"mmlu_high_school_european_history": 0.0, |
|
"mmlu_high_school_geography": 0.0, |
|
"mmlu_high_school_government_and_politics": 0.0, |
|
"mmlu_high_school_macroeconomics": 0.0, |
|
"mmlu_high_school_mathematics": 0.0, |
|
"mmlu_high_school_microeconomics": 0.0, |
|
"mmlu_high_school_physics": 0.0, |
|
"mmlu_high_school_psychology": 0.0, |
|
"mmlu_high_school_statistics": 0.0, |
|
"mmlu_high_school_us_history": 0.0, |
|
"mmlu_high_school_world_history": 0.0, |
|
"mmlu_human_aging": 0.0, |
|
"mmlu_human_sexuality": 0.0, |
|
"mmlu_humanities": "N/A", |
|
"mmlu_international_law": 0.0, |
|
"mmlu_jurisprudence": 0.0, |
|
"mmlu_logical_fallacies": 0.0, |
|
"mmlu_machine_learning": 0.0, |
|
"mmlu_management": 0.0, |
|
"mmlu_marketing": 0.0, |
|
"mmlu_medical_genetics": 0.0, |
|
"mmlu_miscellaneous": 0.0, |
|
"mmlu_moral_disputes": 0.0, |
|
"mmlu_moral_scenarios": 0.0, |
|
"mmlu_nutrition": 0.0, |
|
"mmlu_other": "N/A", |
|
"mmlu_philosophy": 0.0, |
|
"mmlu_prehistory": 0.0, |
|
"mmlu_professional_accounting": 0.0, |
|
"mmlu_professional_law": 0.0, |
|
"mmlu_professional_medicine": 0.0, |
|
"mmlu_professional_psychology": 0.0, |
|
"mmlu_public_relations": 0.0, |
|
"mmlu_security_studies": 0.0, |
|
"mmlu_social_sciences": "N/A", |
|
"mmlu_sociology": 0.0, |
|
"mmlu_stem": "N/A", |
|
"mmlu_us_foreign_policy": 0.0, |
|
"mmlu_virology": 0.0, |
|
"mmlu_world_religions": 0.0 |
|
}, |
|
"n-shot": { |
|
"mmlu": 0, |
|
"mmlu_abstract_algebra": 5, |
|
"mmlu_anatomy": 5, |
|
"mmlu_astronomy": 5, |
|
"mmlu_business_ethics": 5, |
|
"mmlu_clinical_knowledge": 5, |
|
"mmlu_college_biology": 5, |
|
"mmlu_college_chemistry": 5, |
|
"mmlu_college_computer_science": 5, |
|
"mmlu_college_mathematics": 5, |
|
"mmlu_college_medicine": 5, |
|
"mmlu_college_physics": 5, |
|
"mmlu_computer_security": 5, |
|
"mmlu_conceptual_physics": 5, |
|
"mmlu_econometrics": 5, |
|
"mmlu_electrical_engineering": 5, |
|
"mmlu_elementary_mathematics": 5, |
|
"mmlu_formal_logic": 5, |
|
"mmlu_global_facts": 5, |
|
"mmlu_high_school_biology": 5, |
|
"mmlu_high_school_chemistry": 5, |
|
"mmlu_high_school_computer_science": 5, |
|
"mmlu_high_school_european_history": 5, |
|
"mmlu_high_school_geography": 5, |
|
"mmlu_high_school_government_and_politics": 5, |
|
"mmlu_high_school_macroeconomics": 5, |
|
"mmlu_high_school_mathematics": 5, |
|
"mmlu_high_school_microeconomics": 5, |
|
"mmlu_high_school_physics": 5, |
|
"mmlu_high_school_psychology": 5, |
|
"mmlu_high_school_statistics": 5, |
|
"mmlu_high_school_us_history": 5, |
|
"mmlu_high_school_world_history": 5, |
|
"mmlu_human_aging": 5, |
|
"mmlu_human_sexuality": 5, |
|
"mmlu_humanities": 5, |
|
"mmlu_international_law": 5, |
|
"mmlu_jurisprudence": 5, |
|
"mmlu_logical_fallacies": 5, |
|
"mmlu_machine_learning": 5, |
|
"mmlu_management": 5, |
|
"mmlu_marketing": 5, |
|
"mmlu_medical_genetics": 5, |
|
"mmlu_miscellaneous": 5, |
|
"mmlu_moral_disputes": 5, |
|
"mmlu_moral_scenarios": 5, |
|
"mmlu_nutrition": 5, |
|
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}, |
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"config": { |
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"model": "vllm", |
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"model_args": "pretrained=/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Voyage-dpo-1,tensor_parallel_size=1,dtype=auto,gpu_memory_utilization=0.9,data_parallel_size=1,max_model_len=4096", |
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"batch_size": "auto:128", |
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"device": "cuda", |
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}, |
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"git_hash": null |
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} |