| { | |
| "results": { | |
| "mmlu": { | |
| "acc,none": 0.6396524711579548, | |
| "acc_stderr,none": 0.0038282718412418733, | |
| "alias": "mmlu" | |
| }, | |
| "mmlu_humanities": { | |
| "alias": " - humanities", | |
| "acc,none": 0.6, | |
| "acc_stderr,none": 0.006778341124606213 | |
| }, | |
| "mmlu_formal_logic": { | |
| "alias": " - formal_logic", | |
| "acc,none": 0.4444444444444444, | |
| "acc_stderr,none": 0.04444444444444449 | |
| }, | |
| "mmlu_high_school_european_history": { | |
| "alias": " - high_school_european_history", | |
| "acc,none": 0.7696969696969697, | |
| "acc_stderr,none": 0.0328766675860349 | |
| }, | |
| "mmlu_high_school_us_history": { | |
| "alias": " - high_school_us_history", | |
| "acc,none": 0.8480392156862745, | |
| "acc_stderr,none": 0.025195658428931792 | |
| }, | |
| "mmlu_high_school_world_history": { | |
| "alias": " - high_school_world_history", | |
| "acc,none": 0.8016877637130801, | |
| "acc_stderr,none": 0.02595502084162111 | |
| }, | |
| "mmlu_international_law": { | |
| "alias": " - international_law", | |
| "acc,none": 0.7768595041322314, | |
| "acc_stderr,none": 0.03800754475228733 | |
| }, | |
| "mmlu_jurisprudence": { | |
| "alias": " - jurisprudence", | |
| "acc,none": 0.7685185185185185, | |
| "acc_stderr,none": 0.04077494709252627 | |
| }, | |
| "mmlu_logical_fallacies": { | |
| "alias": " - logical_fallacies", | |
| "acc,none": 0.7668711656441718, | |
| "acc_stderr,none": 0.033220157957767414 | |
| }, | |
| "mmlu_moral_disputes": { | |
| "alias": " - moral_disputes", | |
| "acc,none": 0.7283236994219653, | |
| "acc_stderr,none": 0.023948512905468348 | |
| }, | |
| "mmlu_moral_scenarios": { | |
| "alias": " - moral_scenarios", | |
| "acc,none": 0.4681564245810056, | |
| "acc_stderr,none": 0.016688553415612213 | |
| }, | |
| "mmlu_philosophy": { | |
| "alias": " - philosophy", | |
| "acc,none": 0.707395498392283, | |
| "acc_stderr,none": 0.02583989833487798 | |
| }, | |
| "mmlu_prehistory": { | |
| "alias": " - prehistory", | |
| "acc,none": 0.7438271604938271, | |
| "acc_stderr,none": 0.0242885336377261 | |
| }, | |
| "mmlu_professional_law": { | |
| "alias": " - professional_law", | |
| "acc,none": 0.4556714471968709, | |
| "acc_stderr,none": 0.012719949543032204 | |
| }, | |
| "mmlu_world_religions": { | |
| "alias": " - world_religions", | |
| "acc,none": 0.8421052631578947, | |
| "acc_stderr,none": 0.027966785859160872 | |
| }, | |
| "mmlu_other": { | |
| "alias": " - other", | |
| "acc,none": 0.7051818474412617, | |
| "acc_stderr,none": 0.00782572992790983 | |
| }, | |
| "mmlu_business_ethics": { | |
| "alias": " - business_ethics", | |
| "acc,none": 0.65, | |
| "acc_stderr,none": 0.047937248544110196 | |
| }, | |
| "mmlu_clinical_knowledge": { | |
| "alias": " - clinical_knowledge", | |
| "acc,none": 0.7169811320754716, | |
| "acc_stderr,none": 0.027724236492700918 | |
| }, | |
| "mmlu_college_medicine": { | |
| "alias": " - college_medicine", | |
| "acc,none": 0.6589595375722543, | |
| "acc_stderr,none": 0.036146654241808254 | |
| }, | |
| "mmlu_global_facts": { | |
| "alias": " - global_facts", | |
| "acc,none": 0.32, | |
| "acc_stderr,none": 0.046882617226215034 | |
| }, | |
| "mmlu_human_aging": { | |
| "alias": " - human_aging", | |
| "acc,none": 0.695067264573991, | |
| "acc_stderr,none": 0.03089861088247752 | |
| }, | |
| "mmlu_management": { | |
| "alias": " - management", | |
| "acc,none": 0.7864077669902912, | |
| "acc_stderr,none": 0.04058042015646034 | |
| }, | |
| "mmlu_marketing": { | |
| "alias": " - marketing", | |
| "acc,none": 0.8846153846153846, | |
| "acc_stderr,none": 0.020930193185179333 | |
| }, | |
| "mmlu_medical_genetics": { | |
| "alias": " - medical_genetics", | |
| "acc,none": 0.72, | |
| "acc_stderr,none": 0.04512608598542127 | |
| }, | |
| "mmlu_miscellaneous": { | |
| "alias": " - miscellaneous", | |
| "acc,none": 0.8314176245210728, | |
| "acc_stderr,none": 0.013387895731543602 | |
| }, | |
| "mmlu_nutrition": { | |
| "alias": " - nutrition", | |
| "acc,none": 0.7222222222222222, | |
| "acc_stderr,none": 0.02564686309713791 | |
| }, | |
| "mmlu_professional_accounting": { | |
| "alias": " - professional_accounting", | |
| "acc,none": 0.4645390070921986, | |
| "acc_stderr,none": 0.029752389657427054 | |
| }, | |
| "mmlu_professional_medicine": { | |
| "alias": " - professional_medicine", | |
| "acc,none": 0.6654411764705882, | |
| "acc_stderr,none": 0.02866199620233531 | |
| }, | |
| "mmlu_virology": { | |
| "alias": " - virology", | |
| "acc,none": 0.5481927710843374, | |
| "acc_stderr,none": 0.03874371556587953 | |
| }, | |
| "mmlu_social_sciences": { | |
| "alias": " - social_sciences", | |
| "acc,none": 0.745206369840754, | |
| "acc_stderr,none": 0.0076970085276856625 | |
| }, | |
| "mmlu_econometrics": { | |
| "alias": " - econometrics", | |
| "acc,none": 0.5087719298245614, | |
| "acc_stderr,none": 0.04702880432049615 | |
| }, | |
| "mmlu_high_school_geography": { | |
| "alias": " - high_school_geography", | |
| "acc,none": 0.7929292929292929, | |
| "acc_stderr,none": 0.02886977846026707 | |
| }, | |
| "mmlu_high_school_government_and_politics": { | |
| "alias": " - high_school_government_and_politics", | |
| "acc,none": 0.8808290155440415, | |
| "acc_stderr,none": 0.023381935348121437 | |
| }, | |
| "mmlu_high_school_macroeconomics": { | |
| "alias": " - high_school_macroeconomics", | |
| "acc,none": 0.6743589743589744, | |
| "acc_stderr,none": 0.02375966576741229 | |
| }, | |
| "mmlu_high_school_microeconomics": { | |
| "alias": " - high_school_microeconomics", | |
| "acc,none": 0.6932773109243697, | |
| "acc_stderr,none": 0.029953823891887037 | |
| }, | |
| "mmlu_high_school_psychology": { | |
| "alias": " - high_school_psychology", | |
| "acc,none": 0.8422018348623853, | |
| "acc_stderr,none": 0.01563002297009244 | |
| }, | |
| "mmlu_human_sexuality": { | |
| "alias": " - human_sexuality", | |
| "acc,none": 0.7862595419847328, | |
| "acc_stderr,none": 0.0359546161177469 | |
| }, | |
| "mmlu_professional_psychology": { | |
| "alias": " - professional_psychology", | |
| "acc,none": 0.6715686274509803, | |
| "acc_stderr,none": 0.018999707383162662 | |
| }, | |
| "mmlu_public_relations": { | |
| "alias": " - public_relations", | |
| "acc,none": 0.6545454545454545, | |
| "acc_stderr,none": 0.04554619617541054 | |
| }, | |
| "mmlu_security_studies": { | |
| "alias": " - security_studies", | |
| "acc,none": 0.7387755102040816, | |
| "acc_stderr,none": 0.028123429335142787 | |
| }, | |
| "mmlu_sociology": { | |
| "alias": " - sociology", | |
| "acc,none": 0.8507462686567164, | |
| "acc_stderr,none": 0.025196929874827093 | |
| }, | |
| "mmlu_us_foreign_policy": { | |
| "alias": " - us_foreign_policy", | |
| "acc,none": 0.83, | |
| "acc_stderr,none": 0.0377525168068637 | |
| }, | |
| "mmlu_stem": { | |
| "alias": " - stem", | |
| "acc,none": 0.5312400888043134, | |
| "acc_stderr,none": 0.00851347107140647 | |
| }, | |
| "mmlu_abstract_algebra": { | |
| "alias": " - abstract_algebra", | |
| "acc,none": 0.3, | |
| "acc_stderr,none": 0.046056618647183814 | |
| }, | |
| "mmlu_anatomy": { | |
| "alias": " - anatomy", | |
| "acc,none": 0.6444444444444445, | |
| "acc_stderr,none": 0.04135176749720386 | |
| }, | |
| "mmlu_astronomy": { | |
| "alias": " - astronomy", | |
| "acc,none": 0.6907894736842105, | |
| "acc_stderr,none": 0.03761070869867479 | |
| }, | |
| "mmlu_college_biology": { | |
| "alias": " - college_biology", | |
| "acc,none": 0.7291666666666666, | |
| "acc_stderr,none": 0.03716177437566017 | |
| }, | |
| "mmlu_college_chemistry": { | |
| "alias": " - college_chemistry", | |
| "acc,none": 0.45, | |
| "acc_stderr,none": 0.049999999999999996 | |
| }, | |
| "mmlu_college_computer_science": { | |
| "alias": " - college_computer_science", | |
| "acc,none": 0.55, | |
| "acc_stderr,none": 0.04999999999999999 | |
| }, | |
| "mmlu_college_mathematics": { | |
| "alias": " - college_mathematics", | |
| "acc,none": 0.32, | |
| "acc_stderr,none": 0.04688261722621505 | |
| }, | |
| "mmlu_college_physics": { | |
| "alias": " - college_physics", | |
| "acc,none": 0.4411764705882353, | |
| "acc_stderr,none": 0.049406356306056595 | |
| }, | |
| "mmlu_computer_security": { | |
| "alias": " - computer_security", | |
| "acc,none": 0.76, | |
| "acc_stderr,none": 0.04292346959909282 | |
| }, | |
| "mmlu_conceptual_physics": { | |
| "alias": " - conceptual_physics", | |
| "acc,none": 0.6042553191489362, | |
| "acc_stderr,none": 0.03196758697835362 | |
| }, | |
| "mmlu_electrical_engineering": { | |
| "alias": " - electrical_engineering", | |
| "acc,none": 0.5586206896551724, | |
| "acc_stderr,none": 0.04137931034482757 | |
| }, | |
| "mmlu_elementary_mathematics": { | |
| "alias": " - elementary_mathematics", | |
| "acc,none": 0.41798941798941797, | |
| "acc_stderr,none": 0.02540255550326091 | |
| }, | |
| "mmlu_high_school_biology": { | |
| "alias": " - high_school_biology", | |
| "acc,none": 0.7741935483870968, | |
| "acc_stderr,none": 0.023785577884181012 | |
| }, | |
| "mmlu_high_school_chemistry": { | |
| "alias": " - high_school_chemistry", | |
| "acc,none": 0.4975369458128079, | |
| "acc_stderr,none": 0.03517945038691063 | |
| }, | |
| "mmlu_high_school_computer_science": { | |
| "alias": " - high_school_computer_science", | |
| "acc,none": 0.68, | |
| "acc_stderr,none": 0.04688261722621504 | |
| }, | |
| "mmlu_high_school_mathematics": { | |
| "alias": " - high_school_mathematics", | |
| "acc,none": 0.362962962962963, | |
| "acc_stderr,none": 0.029318203645206865 | |
| }, | |
| "mmlu_high_school_physics": { | |
| "alias": " - high_school_physics", | |
| "acc,none": 0.36423841059602646, | |
| "acc_stderr,none": 0.03929111781242741 | |
| }, | |
| "mmlu_high_school_statistics": { | |
| "alias": " - high_school_statistics", | |
| "acc,none": 0.5, | |
| "acc_stderr,none": 0.034099716973523674 | |
| }, | |
| "mmlu_machine_learning": { | |
| "alias": " - machine_learning", | |
| "acc,none": 0.39285714285714285, | |
| "acc_stderr,none": 0.04635550135609976 | |
| } | |
| }, | |
| "groups": { | |
| "mmlu": { | |
| "acc,none": 0.6396524711579548, | |
| "acc_stderr,none": 0.0038282718412418733, | |
| "alias": "mmlu" | |
| }, | |
| "mmlu_humanities": { | |
| "alias": " - humanities", | |
| "acc,none": 0.6, | |
| "acc_stderr,none": 0.006778341124606213 | |
| }, | |
| "mmlu_other": { | |
| "alias": " - other", | |
| "acc,none": 0.7051818474412617, | |
| "acc_stderr,none": 0.00782572992790983 | |
| }, | |
| "mmlu_social_sciences": { | |
| "alias": " - social_sciences", | |
| "acc,none": 0.745206369840754, | |
| "acc_stderr,none": 0.0076970085276856625 | |
| }, | |
| "mmlu_stem": { | |
| "alias": " - stem", | |
| "acc,none": 0.5312400888043134, | |
| "acc_stderr,none": 0.00851347107140647 | |
| } | |
| }, | |
| "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, | |
| "mmlu_other": 5, | |
| "mmlu_philosophy": 5, | |
| "mmlu_prehistory": 5, | |
| "mmlu_professional_accounting": 5, | |
| "mmlu_professional_law": 5, | |
| "mmlu_professional_medicine": 5, | |
| "mmlu_professional_psychology": 5, | |
| "mmlu_public_relations": 5, | |
| "mmlu_security_studies": 5, | |
| "mmlu_social_sciences": 5, | |
| "mmlu_sociology": 5, | |
| "mmlu_stem": 5, | |
| "mmlu_us_foreign_policy": 5, | |
| "mmlu_virology": 5, | |
| "mmlu_world_religions": 5 | |
| }, | |
| "config": { | |
| "model": "vllm", | |
| "model_args": "pretrained=/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Oasis,tensor_parallel_size=1,dtype=auto,gpu_memory_utilization=0.9,data_parallel_size=1,max_model_len=4096", | |
| "batch_size": "auto:128", | |
| "batch_sizes": [], | |
| "device": "cuda", | |
| "use_cache": "/lustre07/scratch/gagan30/arocr/cache/", | |
| "limit": null, | |
| "bootstrap_iters": 100000, | |
| "gen_kwargs": null | |
| }, | |
| "git_hash": null | |
| } |