{ "results": { "arc_challenge": { "alias": "arc_challenge", "acc,none": 0.4104095563139932, "acc_stderr,none": 0.01437492219264266, "acc_norm,none": 0.3984641638225256, "acc_norm_stderr,none": 0.014306946052735565 }, "mmlu": { "acc,none": 0.2973935336846603, "acc_stderr,none": 0.0038396438372097657, "alias": "mmlu" }, "mmlu_humanities": { "acc,none": 0.32051009564293303, "acc_stderr,none": 0.006759141773447958, "alias": " - humanities" }, "mmlu_formal_logic": { "alias": " - formal_logic", "acc,none": 0.36507936507936506, "acc_stderr,none": 0.043062412591271554 }, "mmlu_high_school_european_history": { "alias": " - high_school_european_history", "acc,none": 0.3090909090909091, "acc_stderr,none": 0.036085410115739666 }, "mmlu_high_school_us_history": { "alias": " - high_school_us_history", "acc,none": 0.3235294117647059, "acc_stderr,none": 0.03283472056108567 }, "mmlu_high_school_world_history": { "alias": " - high_school_world_history", "acc,none": 0.45569620253164556, "acc_stderr,none": 0.03241920684693334 }, "mmlu_international_law": { "alias": " - international_law", "acc,none": 0.256198347107438, "acc_stderr,none": 0.03984979653302871 }, "mmlu_jurisprudence": { "alias": " - jurisprudence", "acc,none": 0.28703703703703703, "acc_stderr,none": 0.043733130409147614 }, "mmlu_logical_fallacies": { "alias": " - logical_fallacies", "acc,none": 0.3558282208588957, "acc_stderr,none": 0.03761521380046734 }, "mmlu_moral_disputes": { "alias": " - moral_disputes", "acc,none": 0.407514450867052, "acc_stderr,none": 0.0264545781469315 }, "mmlu_moral_scenarios": { "alias": " - moral_scenarios", "acc,none": 0.3642458100558659, "acc_stderr,none": 0.016094338768474596 }, "mmlu_philosophy": { "alias": " - philosophy", "acc,none": 0.3247588424437299, "acc_stderr,none": 0.026596782287697046 }, "mmlu_prehistory": { "alias": " - prehistory", "acc,none": 0.2777777777777778, "acc_stderr,none": 0.024922001168886335 }, "mmlu_professional_law": { "alias": " - professional_law", "acc,none": 0.26010430247718386, "acc_stderr,none": 0.011204382887823838 }, "mmlu_world_religions": { "alias": " - world_religions", "acc,none": 0.3508771929824561, "acc_stderr,none": 0.03660298834049164 }, "mmlu_other": { "acc,none": 0.2793691663984551, "acc_stderr,none": 0.008038833508038407, "alias": " - other" }, "mmlu_business_ethics": { "alias": " - business_ethics", "acc,none": 0.35, "acc_stderr,none": 0.04793724854411019 }, "mmlu_clinical_knowledge": { "alias": " - clinical_knowledge", "acc,none": 0.26037735849056604, "acc_stderr,none": 0.02700876609070809 }, "mmlu_college_medicine": { "alias": " - college_medicine", "acc,none": 0.2543352601156069, "acc_stderr,none": 0.0332055644308557 }, "mmlu_global_facts": { "alias": " - global_facts", "acc,none": 0.19, "acc_stderr,none": 0.039427724440366234 }, "mmlu_human_aging": { "alias": " - human_aging", "acc,none": 0.32286995515695066, "acc_stderr,none": 0.03138147637575498 }, "mmlu_management": { "alias": " - management", "acc,none": 0.1941747572815534, "acc_stderr,none": 0.03916667762822584 }, "mmlu_marketing": { "alias": " - marketing", "acc,none": 0.34615384615384615, "acc_stderr,none": 0.031166957367235903 }, "mmlu_medical_genetics": { "alias": " - medical_genetics", "acc,none": 0.29, "acc_stderr,none": 0.04560480215720683 }, "mmlu_miscellaneous": { "alias": " - miscellaneous", "acc,none": 0.28991060025542786, "acc_stderr,none": 0.01622501794477097 }, "mmlu_nutrition": { "alias": " - nutrition", "acc,none": 0.26143790849673204, "acc_stderr,none": 0.025160998214292456 }, "mmlu_professional_accounting": { "alias": " - professional_accounting", "acc,none": 0.28368794326241137, "acc_stderr,none": 0.02689170942834396 }, "mmlu_professional_medicine": { "alias": " - professional_medicine", "acc,none": 0.2426470588235294, "acc_stderr,none": 0.02604066247420127 }, "mmlu_virology": { "alias": " - virology", "acc,none": 0.27710843373493976, "acc_stderr,none": 0.03484331592680587 }, "mmlu_social_sciences": { "acc,none": 0.30321741956451087, "acc_stderr,none": 0.008259266274407914, "alias": " - social sciences" }, "mmlu_econometrics": { "alias": " - econometrics", "acc,none": 0.2807017543859649, "acc_stderr,none": 0.042270544512321984 }, "mmlu_high_school_geography": { "alias": " - high_school_geography", "acc,none": 0.20202020202020202, "acc_stderr,none": 0.02860620428922987 }, "mmlu_high_school_government_and_politics": { "alias": " - high_school_government_and_politics", "acc,none": 0.21761658031088082, "acc_stderr,none": 0.029778663037752964 }, "mmlu_high_school_macroeconomics": { "alias": " - high_school_macroeconomics", "acc,none": 0.28974358974358977, "acc_stderr,none": 0.023000628243687978 }, "mmlu_high_school_microeconomics": { "alias": " - high_school_microeconomics", "acc,none": 0.31932773109243695, "acc_stderr,none": 0.030283995525884396 }, "mmlu_high_school_psychology": { "alias": " - high_school_psychology", "acc,none": 0.3504587155963303, "acc_stderr,none": 0.020456077599824457 }, "mmlu_human_sexuality": { "alias": " - human_sexuality", "acc,none": 0.33587786259541985, "acc_stderr,none": 0.04142313771996665 }, "mmlu_professional_psychology": { "alias": " - professional_psychology", "acc,none": 0.3464052287581699, "acc_stderr,none": 0.019249785691717217 }, "mmlu_public_relations": { "alias": " - public_relations", "acc,none": 0.2636363636363636, "acc_stderr,none": 0.04220224692971987 }, "mmlu_security_studies": { "alias": " - security_studies", "acc,none": 0.2612244897959184, "acc_stderr,none": 0.028123429335142797 }, "mmlu_sociology": { "alias": " - sociology", "acc,none": 0.2935323383084577, "acc_stderr,none": 0.03220024104534204 }, "mmlu_us_foreign_policy": { "alias": " - us_foreign_policy", "acc,none": 0.31, "acc_stderr,none": 0.04648231987117316 }, "mmlu_stem": { "acc,none": 0.27497621313035203, "acc_stderr,none": 0.007934123391489032, "alias": " - stem" }, "mmlu_abstract_algebra": { "alias": " - abstract_algebra", "acc,none": 0.22, "acc_stderr,none": 0.04163331998932269 }, "mmlu_anatomy": { "alias": " - anatomy", "acc,none": 0.2518518518518518, "acc_stderr,none": 0.03749850709174021 }, "mmlu_astronomy": { "alias": " - astronomy", "acc,none": 0.24342105263157895, "acc_stderr,none": 0.034923496688842384 }, "mmlu_college_biology": { "alias": " - college_biology", "acc,none": 0.3680555555555556, "acc_stderr,none": 0.040329990539607195 }, "mmlu_college_chemistry": { "alias": " - college_chemistry", "acc,none": 0.26, "acc_stderr,none": 0.04408440022768077 }, "mmlu_college_computer_science": { "alias": " - college_computer_science", "acc,none": 0.29, "acc_stderr,none": 0.045604802157206845 }, "mmlu_college_mathematics": { "alias": " - college_mathematics", "acc,none": 0.21, "acc_stderr,none": 0.040936018074033256 }, "mmlu_college_physics": { "alias": " - college_physics", "acc,none": 0.29411764705882354, "acc_stderr,none": 0.04533838195929776 }, "mmlu_computer_security": { "alias": " - computer_security", "acc,none": 0.3, "acc_stderr,none": 0.046056618647183814 }, "mmlu_conceptual_physics": { "alias": " - conceptual_physics", "acc,none": 0.3276595744680851, "acc_stderr,none": 0.030683020843231008 }, "mmlu_electrical_engineering": { "alias": " - electrical_engineering", "acc,none": 0.2896551724137931, "acc_stderr,none": 0.03780019230438014 }, "mmlu_elementary_mathematics": { "alias": " - elementary_mathematics", "acc,none": 0.2962962962962963, "acc_stderr,none": 0.023517294335963286 }, "mmlu_high_school_biology": { "alias": " - high_school_biology", "acc,none": 0.2967741935483871, "acc_stderr,none": 0.025988500792411884 }, "mmlu_high_school_chemistry": { "alias": " - high_school_chemistry", "acc,none": 0.21182266009852216, "acc_stderr,none": 0.028748983689941072 }, "mmlu_high_school_computer_science": { "alias": " - high_school_computer_science", "acc,none": 0.35, "acc_stderr,none": 0.04793724854411018 }, "mmlu_high_school_mathematics": { "alias": " - high_school_mathematics", "acc,none": 0.21481481481481482, "acc_stderr,none": 0.025040443877000683 }, "mmlu_high_school_physics": { "alias": " - high_school_physics", "acc,none": 0.26490066225165565, "acc_stderr,none": 0.03603038545360384 }, "mmlu_high_school_statistics": { "alias": " - high_school_statistics", "acc,none": 0.22685185185185186, "acc_stderr,none": 0.028561650102422256 }, "mmlu_machine_learning": { "alias": " - machine_learning", "acc,none": 0.33035714285714285, "acc_stderr,none": 0.04464285714285713 } }, "groups": { "mmlu": { "acc,none": 0.2973935336846603, "acc_stderr,none": 0.0038396438372097657, "alias": "mmlu" }, "mmlu_humanities": { "acc,none": 0.32051009564293303, "acc_stderr,none": 0.006759141773447958, "alias": " - humanities" }, "mmlu_other": { "acc,none": 0.2793691663984551, "acc_stderr,none": 0.008038833508038407, "alias": " - other" }, "mmlu_social_sciences": { "acc,none": 0.30321741956451087, "acc_stderr,none": 0.008259266274407914, "alias": " - social sciences" }, "mmlu_stem": { "acc,none": 0.27497621313035203, "acc_stderr,none": 0.007934123391489032, "alias": " - stem" } }, "group_subtasks": { "arc_challenge": [], "mmlu_humanities": [ "mmlu_formal_logic", "mmlu_prehistory", "mmlu_world_religions", "mmlu_philosophy", "mmlu_high_school_world_history", "mmlu_professional_law", "mmlu_high_school_us_history", "mmlu_logical_fallacies", "mmlu_international_law", "mmlu_high_school_european_history", "mmlu_moral_disputes", "mmlu_moral_scenarios", "mmlu_jurisprudence" ], "mmlu_social_sciences": [ "mmlu_public_relations", "mmlu_sociology", "mmlu_security_studies", "mmlu_high_school_government_and_politics", "mmlu_high_school_psychology", "mmlu_human_sexuality", "mmlu_us_foreign_policy", "mmlu_high_school_microeconomics", "mmlu_econometrics", "mmlu_high_school_macroeconomics", "mmlu_high_school_geography", "mmlu_professional_psychology" ], "mmlu_other": [ "mmlu_medical_genetics", "mmlu_global_facts", "mmlu_marketing", "mmlu_college_medicine", "mmlu_human_aging", "mmlu_virology", "mmlu_business_ethics", "mmlu_clinical_knowledge", "mmlu_professional_medicine", "mmlu_nutrition", "mmlu_miscellaneous", "mmlu_professional_accounting", "mmlu_management" ], "mmlu_stem": [ "mmlu_conceptual_physics", "mmlu_high_school_chemistry", "mmlu_college_biology", "mmlu_college_chemistry", "mmlu_machine_learning", "mmlu_elementary_mathematics", "mmlu_abstract_algebra", "mmlu_astronomy", "mmlu_high_school_statistics", "mmlu_anatomy", "mmlu_college_mathematics", "mmlu_computer_security", "mmlu_college_computer_science", "mmlu_electrical_engineering", "mmlu_college_physics", "mmlu_high_school_computer_science", "mmlu_high_school_physics", "mmlu_high_school_biology", "mmlu_high_school_mathematics" ], "mmlu": [ "mmlu_stem", "mmlu_other", "mmlu_social_sciences", "mmlu_humanities" ] }, "configs": { "arc_challenge": { "task": "arc_challenge", "tag": [ "ai2_arc" ], "dataset_path": "allenai/ai2_arc", "dataset_name": "ARC-Challenge", "training_split": "train", "validation_split": "validation", "test_split": "test", "doc_to_text": "Question: {{question}}\nAnswer:", "doc_to_target": "{{choices.label.index(answerKey)}}", "doc_to_choice": "{{choices.text}}", "description": "", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true }, { "metric": "acc_norm", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": true, "doc_to_decontamination_query": "Question: {{question}}\nAnswer:", "metadata": { "version": 1.0 } }, "mmlu_abstract_algebra": { "task": "mmlu_abstract_algebra", "task_alias": "abstract_algebra", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "abstract_algebra", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_anatomy": { "task": "mmlu_anatomy", "task_alias": "anatomy", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "anatomy", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about anatomy.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_astronomy": { "task": "mmlu_astronomy", "task_alias": "astronomy", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "astronomy", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about astronomy.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_business_ethics": { "task": "mmlu_business_ethics", "task_alias": "business_ethics", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "business_ethics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about business ethics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_clinical_knowledge": { "task": "mmlu_clinical_knowledge", "task_alias": "clinical_knowledge", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "clinical_knowledge", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_college_biology": { "task": "mmlu_college_biology", "task_alias": "college_biology", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_biology", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college biology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_college_chemistry": { "task": "mmlu_college_chemistry", "task_alias": "college_chemistry", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_chemistry", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_college_computer_science": { "task": "mmlu_college_computer_science", "task_alias": "college_computer_science", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_computer_science", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college computer science.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_college_mathematics": { "task": "mmlu_college_mathematics", "task_alias": "college_mathematics", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_mathematics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_college_medicine": { "task": "mmlu_college_medicine", "task_alias": "college_medicine", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_medicine", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college medicine.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_college_physics": { "task": "mmlu_college_physics", "task_alias": "college_physics", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "college_physics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about college physics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_computer_security": { "task": "mmlu_computer_security", "task_alias": "computer_security", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "computer_security", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about computer security.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_conceptual_physics": { "task": "mmlu_conceptual_physics", "task_alias": "conceptual_physics", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "conceptual_physics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_econometrics": { "task": "mmlu_econometrics", "task_alias": "econometrics", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "econometrics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about econometrics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_electrical_engineering": { "task": "mmlu_electrical_engineering", "task_alias": "electrical_engineering", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "electrical_engineering", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_elementary_mathematics": { "task": "mmlu_elementary_mathematics", "task_alias": "elementary_mathematics", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "elementary_mathematics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_formal_logic": { "task": "mmlu_formal_logic", "task_alias": "formal_logic", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "formal_logic", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about formal logic.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_global_facts": { "task": "mmlu_global_facts", "task_alias": "global_facts", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "global_facts", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about global facts.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_biology": { "task": "mmlu_high_school_biology", "task_alias": "high_school_biology", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_biology", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school biology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_chemistry": { "task": "mmlu_high_school_chemistry", "task_alias": "high_school_chemistry", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_chemistry", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_computer_science": { "task": "mmlu_high_school_computer_science", "task_alias": "high_school_computer_science", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_computer_science", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_european_history": { "task": "mmlu_high_school_european_history", "task_alias": "high_school_european_history", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_european_history", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school european history.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_geography": { "task": "mmlu_high_school_geography", "task_alias": "high_school_geography", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_geography", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school geography.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_government_and_politics": { "task": "mmlu_high_school_government_and_politics", "task_alias": "high_school_government_and_politics", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_government_and_politics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_macroeconomics": { "task": "mmlu_high_school_macroeconomics", "task_alias": "high_school_macroeconomics", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_macroeconomics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_mathematics": { "task": "mmlu_high_school_mathematics", "task_alias": "high_school_mathematics", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_mathematics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_microeconomics": { "task": "mmlu_high_school_microeconomics", "task_alias": "high_school_microeconomics", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_microeconomics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_physics": { "task": "mmlu_high_school_physics", "task_alias": "high_school_physics", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_physics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school physics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_psychology": { "task": "mmlu_high_school_psychology", "task_alias": "high_school_psychology", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_psychology", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_statistics": { "task": "mmlu_high_school_statistics", "task_alias": "high_school_statistics", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_statistics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_us_history": { "task": "mmlu_high_school_us_history", "task_alias": "high_school_us_history", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_us_history", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school us history.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_high_school_world_history": { "task": "mmlu_high_school_world_history", "task_alias": "high_school_world_history", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "high_school_world_history", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about high school world history.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_human_aging": { "task": "mmlu_human_aging", "task_alias": "human_aging", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "human_aging", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about human aging.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_human_sexuality": { "task": "mmlu_human_sexuality", "task_alias": "human_sexuality", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "human_sexuality", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_international_law": { "task": "mmlu_international_law", "task_alias": "international_law", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "international_law", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about international law.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_jurisprudence": { "task": "mmlu_jurisprudence", "task_alias": "jurisprudence", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "jurisprudence", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_logical_fallacies": { "task": "mmlu_logical_fallacies", "task_alias": "logical_fallacies", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "logical_fallacies", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_machine_learning": { "task": "mmlu_machine_learning", "task_alias": "machine_learning", "tag": "mmlu_stem_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "machine_learning", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about machine learning.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_management": { "task": "mmlu_management", "task_alias": "management", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "management", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about management.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_marketing": { "task": "mmlu_marketing", "task_alias": "marketing", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "marketing", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about marketing.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_medical_genetics": { "task": "mmlu_medical_genetics", "task_alias": "medical_genetics", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "medical_genetics", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_miscellaneous": { "task": "mmlu_miscellaneous", "task_alias": "miscellaneous", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "miscellaneous", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_moral_disputes": { "task": "mmlu_moral_disputes", "task_alias": "moral_disputes", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "moral_disputes", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_moral_scenarios": { "task": "mmlu_moral_scenarios", "task_alias": "moral_scenarios", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "moral_scenarios", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_nutrition": { "task": "mmlu_nutrition", "task_alias": "nutrition", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "nutrition", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about nutrition.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_philosophy": { "task": "mmlu_philosophy", "task_alias": "philosophy", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "philosophy", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about philosophy.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_prehistory": { "task": "mmlu_prehistory", "task_alias": "prehistory", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "prehistory", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about prehistory.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_professional_accounting": { "task": "mmlu_professional_accounting", "task_alias": "professional_accounting", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "professional_accounting", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_professional_law": { "task": "mmlu_professional_law", "task_alias": "professional_law", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "professional_law", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about professional law.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_professional_medicine": { "task": "mmlu_professional_medicine", "task_alias": "professional_medicine", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "professional_medicine", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_professional_psychology": { "task": "mmlu_professional_psychology", "task_alias": "professional_psychology", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "professional_psychology", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_public_relations": { "task": "mmlu_public_relations", "task_alias": "public_relations", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "public_relations", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about public relations.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_security_studies": { "task": "mmlu_security_studies", "task_alias": "security_studies", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "security_studies", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about security studies.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_sociology": { "task": "mmlu_sociology", "task_alias": "sociology", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "sociology", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about sociology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_us_foreign_policy": { "task": "mmlu_us_foreign_policy", "task_alias": "us_foreign_policy", "tag": "mmlu_social_sciences_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "us_foreign_policy", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_virology": { "task": "mmlu_virology", "task_alias": "virology", "tag": "mmlu_other_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "virology", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about virology.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } }, "mmlu_world_religions": { "task": "mmlu_world_religions", "task_alias": "world_religions", "tag": "mmlu_humanities_tasks", "dataset_path": "hails/mmlu_no_train", "dataset_name": "world_religions", "dataset_kwargs": { "trust_remote_code": true }, "test_split": "test", "fewshot_split": "dev", "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", "doc_to_target": "answer", "doc_to_choice": [ "A", "B", "C", "D" ], "description": "The following are multiple choice questions (with answers) about world religions.\n\n", "target_delimiter": " ", "fewshot_delimiter": "\n\n", "fewshot_config": { "sampler": "first_n" }, "num_fewshot": 0, "metric_list": [ { "metric": "acc", "aggregation": "mean", "higher_is_better": true } ], "output_type": "multiple_choice", "repeats": 1, "should_decontaminate": false, "metadata": { "version": 1.0 } } }, "versions": { "arc_challenge": 1.0, "mmlu": 2, "mmlu_abstract_algebra": 1.0, "mmlu_anatomy": 1.0, "mmlu_astronomy": 1.0, "mmlu_business_ethics": 1.0, "mmlu_clinical_knowledge": 1.0, "mmlu_college_biology": 1.0, "mmlu_college_chemistry": 1.0, "mmlu_college_computer_science": 1.0, "mmlu_college_mathematics": 1.0, "mmlu_college_medicine": 1.0, "mmlu_college_physics": 1.0, "mmlu_computer_security": 1.0, "mmlu_conceptual_physics": 1.0, "mmlu_econometrics": 1.0, "mmlu_electrical_engineering": 1.0, "mmlu_elementary_mathematics": 1.0, "mmlu_formal_logic": 1.0, "mmlu_global_facts": 1.0, "mmlu_high_school_biology": 1.0, "mmlu_high_school_chemistry": 1.0, "mmlu_high_school_computer_science": 1.0, "mmlu_high_school_european_history": 1.0, "mmlu_high_school_geography": 1.0, "mmlu_high_school_government_and_politics": 1.0, "mmlu_high_school_macroeconomics": 1.0, "mmlu_high_school_mathematics": 1.0, "mmlu_high_school_microeconomics": 1.0, "mmlu_high_school_physics": 1.0, "mmlu_high_school_psychology": 1.0, "mmlu_high_school_statistics": 1.0, "mmlu_high_school_us_history": 1.0, "mmlu_high_school_world_history": 1.0, "mmlu_human_aging": 1.0, "mmlu_human_sexuality": 1.0, "mmlu_humanities": 2, "mmlu_international_law": 1.0, "mmlu_jurisprudence": 1.0, "mmlu_logical_fallacies": 1.0, "mmlu_machine_learning": 1.0, "mmlu_management": 1.0, "mmlu_marketing": 1.0, "mmlu_medical_genetics": 1.0, "mmlu_miscellaneous": 1.0, "mmlu_moral_disputes": 1.0, "mmlu_moral_scenarios": 1.0, "mmlu_nutrition": 1.0, "mmlu_other": 2, "mmlu_philosophy": 1.0, "mmlu_prehistory": 1.0, "mmlu_professional_accounting": 1.0, "mmlu_professional_law": 1.0, "mmlu_professional_medicine": 1.0, "mmlu_professional_psychology": 1.0, "mmlu_public_relations": 1.0, "mmlu_security_studies": 1.0, "mmlu_social_sciences": 2, "mmlu_sociology": 1.0, "mmlu_stem": 2, "mmlu_us_foreign_policy": 1.0, "mmlu_virology": 1.0, "mmlu_world_religions": 1.0 }, "n-shot": { "arc_challenge": 0, "mmlu_abstract_algebra": 0, "mmlu_anatomy": 0, "mmlu_astronomy": 0, "mmlu_business_ethics": 0, "mmlu_clinical_knowledge": 0, "mmlu_college_biology": 0, "mmlu_college_chemistry": 0, "mmlu_college_computer_science": 0, "mmlu_college_mathematics": 0, "mmlu_college_medicine": 0, "mmlu_college_physics": 0, "mmlu_computer_security": 0, "mmlu_conceptual_physics": 0, "mmlu_econometrics": 0, "mmlu_electrical_engineering": 0, "mmlu_elementary_mathematics": 0, "mmlu_formal_logic": 0, "mmlu_global_facts": 0, "mmlu_high_school_biology": 0, "mmlu_high_school_chemistry": 0, "mmlu_high_school_computer_science": 0, "mmlu_high_school_european_history": 0, "mmlu_high_school_geography": 0, "mmlu_high_school_government_and_politics": 0, "mmlu_high_school_macroeconomics": 0, "mmlu_high_school_mathematics": 0, "mmlu_high_school_microeconomics": 0, "mmlu_high_school_physics": 0, "mmlu_high_school_psychology": 0, "mmlu_high_school_statistics": 0, "mmlu_high_school_us_history": 0, "mmlu_high_school_world_history": 0, "mmlu_human_aging": 0, "mmlu_human_sexuality": 0, "mmlu_international_law": 0, "mmlu_jurisprudence": 0, "mmlu_logical_fallacies": 0, "mmlu_machine_learning": 0, "mmlu_management": 0, "mmlu_marketing": 0, "mmlu_medical_genetics": 0, "mmlu_miscellaneous": 0, "mmlu_moral_disputes": 0, "mmlu_moral_scenarios": 0, "mmlu_nutrition": 0, "mmlu_philosophy": 0, "mmlu_prehistory": 0, "mmlu_professional_accounting": 0, "mmlu_professional_law": 0, "mmlu_professional_medicine": 0, "mmlu_professional_psychology": 0, "mmlu_public_relations": 0, "mmlu_security_studies": 0, "mmlu_sociology": 0, "mmlu_us_foreign_policy": 0, "mmlu_virology": 0, "mmlu_world_religions": 0 }, "higher_is_better": { "arc_challenge": { "acc": true, "acc_norm": true }, "mmlu": { "acc": true }, "mmlu_abstract_algebra": { "acc": true }, "mmlu_anatomy": { "acc": true }, "mmlu_astronomy": { "acc": true }, "mmlu_business_ethics": { "acc": true }, "mmlu_clinical_knowledge": { "acc": true }, "mmlu_college_biology": { "acc": true }, "mmlu_college_chemistry": { "acc": true }, "mmlu_college_computer_science": { "acc": true }, "mmlu_college_mathematics": { "acc": true }, "mmlu_college_medicine": { "acc": true }, "mmlu_college_physics": { "acc": true }, "mmlu_computer_security": { "acc": true }, "mmlu_conceptual_physics": { "acc": true }, "mmlu_econometrics": { "acc": true }, "mmlu_electrical_engineering": { "acc": true }, "mmlu_elementary_mathematics": { "acc": true }, "mmlu_formal_logic": { "acc": true }, "mmlu_global_facts": { "acc": true }, "mmlu_high_school_biology": { "acc": true }, "mmlu_high_school_chemistry": { "acc": true }, "mmlu_high_school_computer_science": { "acc": true }, "mmlu_high_school_european_history": { "acc": true }, "mmlu_high_school_geography": { "acc": true }, "mmlu_high_school_government_and_politics": { "acc": true }, "mmlu_high_school_macroeconomics": { "acc": true }, "mmlu_high_school_mathematics": { "acc": true }, "mmlu_high_school_microeconomics": { "acc": true }, "mmlu_high_school_physics": { "acc": true }, "mmlu_high_school_psychology": { "acc": true }, "mmlu_high_school_statistics": { "acc": true }, "mmlu_high_school_us_history": { "acc": true }, "mmlu_high_school_world_history": { "acc": true }, "mmlu_human_aging": { "acc": true }, "mmlu_human_sexuality": { "acc": true }, "mmlu_humanities": { "acc": true }, "mmlu_international_law": { "acc": true }, "mmlu_jurisprudence": { "acc": true }, "mmlu_logical_fallacies": { "acc": true }, "mmlu_machine_learning": { "acc": true }, "mmlu_management": { "acc": true }, "mmlu_marketing": { "acc": true }, "mmlu_medical_genetics": { "acc": true }, "mmlu_miscellaneous": { "acc": true }, "mmlu_moral_disputes": { "acc": true }, "mmlu_moral_scenarios": { "acc": true }, "mmlu_nutrition": { "acc": true }, "mmlu_other": { "acc": true }, "mmlu_philosophy": { "acc": true }, "mmlu_prehistory": { "acc": true }, "mmlu_professional_accounting": { "acc": true }, "mmlu_professional_law": { "acc": true }, "mmlu_professional_medicine": { "acc": true }, "mmlu_professional_psychology": { "acc": true }, "mmlu_public_relations": { "acc": true }, "mmlu_security_studies": { "acc": true }, "mmlu_social_sciences": { "acc": true }, "mmlu_sociology": { "acc": true }, "mmlu_stem": { "acc": true }, "mmlu_us_foreign_policy": { "acc": true }, "mmlu_virology": { "acc": true }, "mmlu_world_religions": { "acc": true } }, "n-samples": { "mmlu_conceptual_physics": { "original": 235, "effective": 235 }, "mmlu_high_school_chemistry": { "original": 203, "effective": 203 }, "mmlu_college_biology": { "original": 144, "effective": 144 }, "mmlu_college_chemistry": { "original": 100, "effective": 100 }, "mmlu_machine_learning": { "original": 112, "effective": 112 }, "mmlu_elementary_mathematics": { "original": 378, "effective": 378 }, "mmlu_abstract_algebra": { "original": 100, "effective": 100 }, "mmlu_astronomy": { "original": 152, "effective": 152 }, "mmlu_high_school_statistics": { "original": 216, "effective": 216 }, "mmlu_anatomy": { "original": 135, "effective": 135 }, "mmlu_college_mathematics": { "original": 100, "effective": 100 }, "mmlu_computer_security": { "original": 100, "effective": 100 }, "mmlu_college_computer_science": { "original": 100, "effective": 100 }, "mmlu_electrical_engineering": { "original": 145, "effective": 145 }, "mmlu_college_physics": { "original": 102, "effective": 102 }, "mmlu_high_school_computer_science": { "original": 100, "effective": 100 }, "mmlu_high_school_physics": { "original": 151, "effective": 151 }, "mmlu_high_school_biology": { "original": 310, "effective": 310 }, "mmlu_high_school_mathematics": { "original": 270, "effective": 270 }, "mmlu_medical_genetics": { "original": 100, "effective": 100 }, "mmlu_global_facts": { "original": 100, "effective": 100 }, "mmlu_marketing": { "original": 234, "effective": 234 }, "mmlu_college_medicine": { "original": 173, "effective": 173 }, "mmlu_human_aging": { "original": 223, "effective": 223 }, "mmlu_virology": { "original": 166, "effective": 166 }, "mmlu_business_ethics": { "original": 100, "effective": 100 }, "mmlu_clinical_knowledge": { "original": 265, "effective": 265 }, "mmlu_professional_medicine": { "original": 272, "effective": 272 }, "mmlu_nutrition": { "original": 306, "effective": 306 }, "mmlu_miscellaneous": { "original": 783, "effective": 783 }, "mmlu_professional_accounting": { "original": 282, "effective": 282 }, "mmlu_management": { "original": 103, "effective": 103 }, "mmlu_public_relations": { "original": 110, "effective": 110 }, "mmlu_sociology": { "original": 201, "effective": 201 }, "mmlu_security_studies": { "original": 245, "effective": 245 }, "mmlu_high_school_government_and_politics": { "original": 193, "effective": 193 }, "mmlu_high_school_psychology": { "original": 545, "effective": 545 }, "mmlu_human_sexuality": { "original": 131, "effective": 131 }, "mmlu_us_foreign_policy": { "original": 100, "effective": 100 }, "mmlu_high_school_microeconomics": { "original": 238, "effective": 238 }, "mmlu_econometrics": { "original": 114, "effective": 114 }, "mmlu_high_school_macroeconomics": { "original": 390, "effective": 390 }, "mmlu_high_school_geography": { "original": 198, "effective": 198 }, "mmlu_professional_psychology": { "original": 612, "effective": 612 }, "mmlu_formal_logic": { "original": 126, "effective": 126 }, "mmlu_prehistory": { "original": 324, "effective": 324 }, "mmlu_world_religions": { "original": 171, "effective": 171 }, "mmlu_philosophy": { "original": 311, "effective": 311 }, "mmlu_high_school_world_history": { "original": 237, "effective": 237 }, "mmlu_professional_law": { "original": 1534, "effective": 1534 }, "mmlu_high_school_us_history": { "original": 204, "effective": 204 }, "mmlu_logical_fallacies": { "original": 163, "effective": 163 }, "mmlu_international_law": { "original": 121, "effective": 121 }, "mmlu_high_school_european_history": { "original": 165, "effective": 165 }, "mmlu_moral_disputes": { "original": 346, "effective": 346 }, "mmlu_moral_scenarios": { "original": 895, "effective": 895 }, "mmlu_jurisprudence": { "original": 108, "effective": 108 }, "arc_challenge": { "original": 1172, "effective": 1172 } }, "config": { "model": "hf", "model_args": "pretrained=DeepSeek-R1-Distill-Qwen-32B-gptq-4bit,gptqmodel=True", "model_num_parameters": 5736502272, "model_dtype": "torch.float16", "model_revision": "main", "model_sha": "", "batch_size": 1, "batch_sizes": [], "device": null, "use_cache": null, "limit": null, "bootstrap_iters": 100000, "gen_kwargs": null, "random_seed": 0, "numpy_seed": 1234, "torch_seed": 1234, "fewshot_seed": 1234 }, "git_hash": "b1f7295", "date": 1739700827.6612206, "pretty_env_info": "PyTorch version: 2.5.0+cu124\nIs debug build: False\nCUDA used to build PyTorch: 12.4\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 24.04.1 LTS (x86_64)\nGCC version: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0\nClang version: Could not collect\nCMake version: Could not collect\nLibc version: glibc-2.39\n\nPython version: 3.10.16 | packaged by conda-forge | (main, Dec 5 2024, 14:16:10) [GCC 13.3.0] (64-bit runtime)\nPython platform: Linux-6.8.0-1021-azure-x86_64-with-glibc2.39\nIs CUDA available: True\nCUDA runtime version: 12.0.140\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: GPU 0: NVIDIA A100 80GB PCIe\nNvidia driver version: 550.54.14\ncuDNN version: Could not collect\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture: x86_64\nCPU op-mode(s): 32-bit, 64-bit\nAddress sizes: 48 bits physical, 48 bits virtual\nByte Order: Little Endian\nCPU(s): 24\nOn-line CPU(s) list: 0-23\nVendor ID: AuthenticAMD\nModel name: AMD EPYC 7V13 64-Core Processor\nCPU family: 25\nModel: 1\nThread(s) per core: 1\nCore(s) per socket: 24\nSocket(s): 1\nStepping: 1\nBogoMIPS: 4890.87\nFlags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext perfctr_core vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves user_shstk clzero xsaveerptr rdpru arat umip vaes vpclmulqdq rdpid fsrm\nHypervisor vendor: Microsoft\nVirtualization type: full\nL1d cache: 768 KiB (24 instances)\nL1i cache: 768 KiB (24 instances)\nL2 cache: 12 MiB (24 instances)\nL3 cache: 96 MiB (3 instances)\nNUMA node(s): 1\nNUMA node0 CPU(s): 0-23\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit: Not affected\nVulnerability L1tf: Not affected\nVulnerability Mds: Not affected\nVulnerability Meltdown: Not affected\nVulnerability Mmio stale data: Not affected\nVulnerability Reg file data sampling: Not affected\nVulnerability Retbleed: Not affected\nVulnerability Spec rstack overflow: Vulnerable: Safe RET, no microcode\nVulnerability Spec store bypass: Vulnerable\nVulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2: Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected\nVulnerability Srbds: Not affected\nVulnerability Tsx async abort: Not affected\n\nVersions of relevant libraries:\n[pip3] gptqmodel==1.7.4+cu124torch2.5\n[pip3] numpy==1.26.4\n[pip3] torch==2.5.0\n[pip3] torchaudio==2.5.0+cu124\n[pip3] torchvision==0.20.0\n[pip3] triton==3.1.0\n[conda] cudatoolkit 11.8.0 h4ba93d1_13 conda-forge\n[conda] gptqmodel 1.7.4+cu124torch2.5 pypi_0 pypi\n[conda] libtorch 2.5.1 cpu_generic_h90be84d_11 conda-forge\n[conda] nomkl 1.0 h5ca1d4c_0 conda-forge\n[conda] numpy 1.26.4 pypi_0 pypi\n[conda] torch 2.5.0 pypi_0 pypi\n[conda] torchaudio 2.5.0+cu124 pypi_0 pypi\n[conda] torchvision 0.20.0 pypi_0 pypi\n[conda] triton 3.1.0 pypi_0 pypi", "transformers_version": "4.48.2", "upper_git_hash": null, "tokenizer_pad_token": [ "", "128244" ], "tokenizer_eos_token": [ "<｜end▁of▁sentence｜>", "151643" ], "tokenizer_bos_token": [ "<｜begin▁of▁sentence｜>", "151646" ], "eot_token_id": 151643, "max_length": 131072, "task_hashes": { "mmlu_conceptual_physics": "e44e160e9de59b66b27f9845286798fa84b1f978d47fab83916947fdce9d558a", "mmlu_high_school_chemistry": "7b0aa278f3d736a17f8272ffebfb731297b2ef07665fa775a01b48a98584e63d", "mmlu_college_biology": "67badf9a8a9eadf4793aed211c6114416aac791dfa1e2b3b1a2b2d0418fe83d9", "mmlu_college_chemistry": "7cf7bbde59ef7d3ac36ad6a1f09823c10151aaa37313c53909a9249820ac42a7", "mmlu_machine_learning": "5d44d6f9356eea8613bccda3f7c0de4abe0652a7087e3cc8ed5ad0a54601b4aa", "mmlu_elementary_mathematics": "e61d9026fa8be2b227195ed796ff07c3a609225ef081bcb98ae6c5e4dd85dc9c", "mmlu_abstract_algebra": "9af9d070b9cf616053d53513d6b61870f758da004979b1d2a5f5237fda624bc2", "mmlu_astronomy": "d1158c2b8a534c85e29a0ef6dbf97f76d80d2a2b8ed6dfd4ea46f97bd7650652", "mmlu_high_school_statistics": "251d2d800b0c4b41d4cd68ca9b7b7e1003f02a56da68113d1bf6777da34a15c3", "mmlu_anatomy": "bcff5e29b7522dd3a9e38abad9ed23138347ffbdb5c56d4d0a9a0e7f8d1b781c", "mmlu_college_mathematics": "7de9fea1cc7d1df17e55653035838e0e9251e16df8d23fe9905feb3f52c2d295", "mmlu_computer_security": "bcf86d055731822d43b9ea71e361a44b2a1e884f74790e189256e69e1154437b", "mmlu_college_computer_science": "7e6c0169773451f5a3e224fc9da2c21e0f218283d8176a75d9a44f1ec37fbce1", "mmlu_electrical_engineering": "d64db9707012d81e0924fa3a785ff419b53faf7e9a13781be3596287aa7f6f28", "mmlu_college_physics": "7ceeb19eb9785b4372c4facb61eb51e4d9a199a249c6576796bd7e77147f96d4", "mmlu_high_school_computer_science": "feafcc88c4efe7b7d2d4058672c4895b985bf0947f983055a771da137827f467", "mmlu_high_school_physics": "fd4e84b9f983621e61e4f4efd6833659bad4c1dd4ec5e11669dc620cd11124a7", "mmlu_high_school_biology": "788524572d0bad43c502d0377893abeba647f95d7bbfda03ac0c170f3c2ebe3d", "mmlu_high_school_mathematics": "3498bee9814d09ea3c4785a8ff7e059122902d599fe669f20b548832eee5a210", "mmlu_medical_genetics": "38c379b96a9b5dad162fc3ca02bd6860720931228c1bbdb563444676aa560d8b", "mmlu_global_facts": "6a24ab3772264f824d644148a9e594c9311a9abb832e2e01ebb8e30295f21a73", "mmlu_marketing": "3c35ab45fe954b4a99c49a1371de508eb804a1d404755ed579700f8b07339eb3", "mmlu_college_medicine": "a99f25347c639f44d59f14688e63b372d410c6fdeda20460e6da0887b58a08dc", "mmlu_human_aging": "2d3b53f216e855735c554601d17806d772cc0aa32c6e0a3ad56be0b596c10597", "mmlu_virology": "e37defad93a8fed48d1cd444617c16cec31a4654b01bd3b5865248a278355cb0", "mmlu_business_ethics": "f43c4f96059d3dd1223e3a2b5f7bef9c0e8c934d48174bfc067207642614683e", "mmlu_clinical_knowledge": "bbfbeaaf991677c9abf8a2542c73858a18d762cead9d0c5fde817657edc3e0bb", "mmlu_professional_medicine": "d9d3810d35fda320ed3acf4bd62f08e82cda46317d211255a1685f32995de66f", "mmlu_nutrition": "ee22165a7e6e52d891002d0c3f96577cb970623135cb95c5ccd70a498beacd11", "mmlu_miscellaneous": "7318105f736493ead94ab2560f0741a3c281478c46068a525bbb5644c30cf883", "mmlu_professional_accounting": "1f81d684d03a3c64557a8f17b21d0b6db31e3652708c5cfa2de01cdbfd1fba64", "mmlu_management": "b86f3b3e03c37b74eb84b97c410c9e591cc30283bad42b3310cb1667f4d6c496", "mmlu_public_relations": "cd4b6c1cf0e2535103be225017caac7de8d0629aa2852428df5a44e1979ee8ed", "mmlu_sociology": "41ca5f38e3c2da34027eddf39502da75b70cbaf1f4875b0db40c672c2a7c9e77", "mmlu_security_studies": "9090d84bb431ed36c63d72c46ab14c8c831ef37d3721656d9619c08817a272e8", "mmlu_high_school_government_and_politics": "2c9006d3e6a17d51db851e5a08687293b4160d9448d14b89589f2de669fdb3f3", "mmlu_high_school_psychology": "3fb17b0fa3d98fada697e70060bfd231d4e78e1af47a0cfa2ea27a67dfe6ec5e", "mmlu_human_sexuality": "4e3e5f3c9f9c77c24553cfd398f4c132c9dbe05588ddda82d614e53ab09132a8", "mmlu_us_foreign_policy": "a9ca53568f3daa8c23e5c3746ba889ad65eb69d3f0add04f880edeb6f968eee5", "mmlu_high_school_microeconomics": "b2d3b5f2ea56678868b043b83da826713bf4faa330f612bdbd7a8a0a264737f9", "mmlu_econometrics": "1bc2e20960800cabc5871cfeb1273faebf7135cdf422b4584cf4df229f6c7796", "mmlu_high_school_macroeconomics": "af91dcb4b4f0fdd03f1aa2400e00a85515f4cc3d78921c9344192de60512511a", "mmlu_high_school_geography": "e2b10ea70273ee1ea3067d2e2d0b01227a4e845f348b966caa83344e0587d0b2", "mmlu_professional_psychology": "5df9d5c9d999c021a60f157a18403bcaf39f7187f9c28b7b21b04ed73f3e0efc", "mmlu_formal_logic": "904413b3c48c56c27d51a026467f86dd7ebb996e59b4a3547e5523b98e1ca76c", "mmlu_prehistory": "01ff8c2029d2e816a5c547cb11b06f16602f4cb9543e2d0ad3c7b7e7d4567930", "mmlu_world_religions": "362d75721ca689e2004dbaaa888f8f0733f15366aa2ebf4aa9ee7e33ee03003b", "mmlu_philosophy": "7d37dcd5c5a2fdb4783fb47aac7422f78f549b2dd699fd62ea7b43b2ed3fa9e4", "mmlu_high_school_world_history": "638f3897c2875cd8b74d8f860bfc0684e80f2ad05dfc3f10013635256ea14ba5", "mmlu_professional_law": "944247baa44b214a437996293db7462d35b8bd9e70ebb63a37e1d07215c5e3db", "mmlu_high_school_us_history": "4dd38134bf4919c2b7efffd8740c0ea47a7ae26fa4415ea58be296e698ac119c", "mmlu_logical_fallacies": "2abf7f08f106c4f1d107b38934447d184962341f0424ec3473d2ae53f775919d", "mmlu_international_law": "03942fc6ba90528f4cf7d9c9ea7ad11af33ce40043dd4eaed9504c5d3d740de2", "mmlu_high_school_european_history": "d296775eca79ec0a144615e167665255e0db747c166c0baebc63e0cef2bce142", "mmlu_moral_disputes": "9df8fb79547677e18eb458a8e05119b70144f617a09383c04fce8827a90f4778", "mmlu_moral_scenarios": "de57e5892ade37f040a28c23608285fbbaf33bf9b1dd123382611f4de1528fd0", "mmlu_jurisprudence": "a03927ba52301ee52619a8d2c0a270945d6f1b5a84b3a23678595bb8b1bcf9c1", "arc_challenge": "84e51e80f164ae698e98637454ad407407ccc6ed14441621fe4a5e7f399d1907" }, "model_source": "hf", "model_name": "DeepSeek-R1-Distill-Qwen-32B-gptq-4bit", "model_name_sanitized": "DeepSeek-R1-Distill-Qwen-32B-gptq-4bit", "system_instruction": null, "system_instruction_sha": null, "fewshot_as_multiturn": false, "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '' in content %}{% set content = content.split('')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜>\\n'}}{% endif %}", "chat_template_sha": "56a1447ad31926fdc21fb07e56e5642bd9c850c4f52d8c8af7bbe5f079a84f5f", "start_time": 567333.679121267, "end_time": 569114.181343909, "total_evaluation_time_seconds": "1780.5022226419533" }