| { | |
| "results": { | |
| "mmlu_pro": { | |
| "exact_match,custom-extract": 0.5244348404255319, | |
| "exact_match_stderr,custom-extract": 0.004361486625586025, | |
| "alias": "mmlu_pro" | |
| }, | |
| "mmlu_pro_biology": { | |
| "alias": " - biology", | |
| "exact_match,custom-extract": 0.7670850767085077, | |
| "exact_match_stderr,custom-extract": 0.015796610634606297 | |
| }, | |
| "mmlu_pro_business": { | |
| "alias": " - business", | |
| "exact_match,custom-extract": 0.5690747782002535, | |
| "exact_match_stderr,custom-extract": 0.017640972260771548 | |
| }, | |
| "mmlu_pro_chemistry": { | |
| "alias": " - chemistry", | |
| "exact_match,custom-extract": 0.27385159010600707, | |
| "exact_match_stderr,custom-extract": 0.013259862675787527 | |
| }, | |
| "mmlu_pro_computer_science": { | |
| "alias": " - computer_science", | |
| "exact_match,custom-extract": 0.5487804878048781, | |
| "exact_match_stderr,custom-extract": 0.024605467021746173 | |
| }, | |
| "mmlu_pro_economics": { | |
| "alias": " - economics", | |
| "exact_match,custom-extract": 0.6848341232227488, | |
| "exact_match_stderr,custom-extract": 0.01600105078446331 | |
| }, | |
| "mmlu_pro_engineering": { | |
| "alias": " - engineering", | |
| "exact_match,custom-extract": 0.32507739938080493, | |
| "exact_match_stderr,custom-extract": 0.01505506709517795 | |
| }, | |
| "mmlu_pro_health": { | |
| "alias": " - health", | |
| "exact_match,custom-extract": 0.6075794621026895, | |
| "exact_match_stderr,custom-extract": 0.017083088022054806 | |
| }, | |
| "mmlu_pro_history": { | |
| "alias": " - history", | |
| "exact_match,custom-extract": 0.5800524934383202, | |
| "exact_match_stderr,custom-extract": 0.02531858056501443 | |
| }, | |
| "mmlu_pro_law": { | |
| "alias": " - law", | |
| "exact_match,custom-extract": 0.38419618528610355, | |
| "exact_match_stderr,custom-extract": 0.014665651784719584 | |
| }, | |
| "mmlu_pro_math": { | |
| "alias": " - math", | |
| "exact_match,custom-extract": 0.53960029607698, | |
| "exact_match_stderr,custom-extract": 0.01356552865963102 | |
| }, | |
| "mmlu_pro_other": { | |
| "alias": " - other", | |
| "exact_match,custom-extract": 0.6233766233766234, | |
| "exact_match_stderr,custom-extract": 0.015948801100999506 | |
| }, | |
| "mmlu_pro_philosophy": { | |
| "alias": " - philosophy", | |
| "exact_match,custom-extract": 0.5410821643286573, | |
| "exact_match_stderr,custom-extract": 0.022329778044085976 | |
| }, | |
| "mmlu_pro_physics": { | |
| "alias": " - physics", | |
| "exact_match,custom-extract": 0.45573518090839105, | |
| "exact_match_stderr,custom-extract": 0.013823692447181207 | |
| }, | |
| "mmlu_pro_psychology": { | |
| "alias": " - psychology", | |
| "exact_match,custom-extract": 0.7205513784461153, | |
| "exact_match_stderr,custom-extract": 0.015894771970426862 | |
| } | |
| }, | |
| "groups": { | |
| "mmlu_pro": { | |
| "exact_match,custom-extract": 0.5244348404255319, | |
| "exact_match_stderr,custom-extract": 0.004361486625586025, | |
| "alias": "mmlu_pro" | |
| } | |
| }, | |
| "group_subtasks": { | |
| "mmlu_pro": [ | |
| "mmlu_pro_biology", | |
| "mmlu_pro_business", | |
| "mmlu_pro_chemistry", | |
| "mmlu_pro_computer_science", | |
| "mmlu_pro_economics", | |
| "mmlu_pro_engineering", | |
| "mmlu_pro_health", | |
| "mmlu_pro_history", | |
| "mmlu_pro_law", | |
| "mmlu_pro_math", | |
| "mmlu_pro_other", | |
| "mmlu_pro_philosophy", | |
| "mmlu_pro_physics", | |
| "mmlu_pro_psychology" | |
| ] | |
| }, | |
| "configs": { | |
| "mmlu_pro_biology": { | |
| "task": "mmlu_pro_biology", | |
| "task_alias": "biology", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd67edfc0>, subject='biology')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ee830>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about biology. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67eda20>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_business": { | |
| "task": "mmlu_pro_business", | |
| "task_alias": "business", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd6af3760>, subject='business')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ee0e0>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about business. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ed630>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_chemistry": { | |
| "task": "mmlu_pro_chemistry", | |
| "task_alias": "chemistry", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd6af3c70>, subject='chemistry')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67edc60>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about chemistry. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ef130>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_computer_science": { | |
| "task": "mmlu_pro_computer_science", | |
| "task_alias": "computer_science", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd6af3b50>, subject='computer science')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af2b00>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about computer science. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ec700>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_economics": { | |
| "task": "mmlu_pro_economics", | |
| "task_alias": "economics", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd67ed480>, subject='economics')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ed510>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about economics. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ecaf0>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_engineering": { | |
| "task": "mmlu_pro_engineering", | |
| "task_alias": "engineering", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd67ef6d0>, subject='engineering')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ec8b0>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about engineering. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ec790>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_health": { | |
| "task": "mmlu_pro_health", | |
| "task_alias": "health", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd6af28c0>, subject='health')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af2560>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about health. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af24d0>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_history": { | |
| "task": "mmlu_pro_history", | |
| "task_alias": "history", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd6af36d0>, subject='history')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af3f40>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about history. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af39a0>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_law": { | |
| "task": "mmlu_pro_law", | |
| "task_alias": "law", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd6af23b0>, subject='law')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af2d40>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about law. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af2a70>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_math": { | |
| "task": "mmlu_pro_math", | |
| "task_alias": "math", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd67ed990>, subject='math')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ee5f0>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about math. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ee4d0>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_other": { | |
| "task": "mmlu_pro_other", | |
| "task_alias": "other", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd67ec0d0>, subject='other')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ec040>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about other. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd67ec1f0>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_philosophy": { | |
| "task": "mmlu_pro_philosophy", | |
| "task_alias": "philosophy", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd6af3400>, subject='philosophy')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af3520>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about philosophy. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af2cb0>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_physics": { | |
| "task": "mmlu_pro_physics", | |
| "task_alias": "physics", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd6af3250>, subject='physics')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af3d00>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about physics. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6af32e0>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| }, | |
| "mmlu_pro_psychology": { | |
| "task": "mmlu_pro_psychology", | |
| "task_alias": "psychology", | |
| "dataset_path": "TIGER-Lab/MMLU-Pro", | |
| "test_split": "test", | |
| "fewshot_split": "validation", | |
| "process_docs": "functools.partial(<function process_docs at 0x147dd6a0e5f0>, subject='psychology')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x1480b6ee2710>, including_answer=False)", | |
| "doc_to_target": "answer", | |
| "description": "The following are multiple choice questions (with answers) about psychology. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\n", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "fewshot_config": { | |
| "sampler": "first_n", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x147dd6a0c430>, including_answer=True)", | |
| "doc_to_target": "" | |
| }, | |
| "num_fewshot": 5, | |
| "metric_list": [ | |
| { | |
| "metric": "exact_match", | |
| "aggregation": "mean", | |
| "higher_is_better": true, | |
| "ignore_case": true, | |
| "ignore_punctuation": true | |
| } | |
| ], | |
| "output_type": "generate_until", | |
| "generation_kwargs": { | |
| "until": [ | |
| "</s>", | |
| "Q:", | |
| "<|im_end|>" | |
| ], | |
| "do_sample": false, | |
| "temperature": 0.0 | |
| }, | |
| "repeats": 1, | |
| "filter_list": [ | |
| { | |
| "name": "custom-extract", | |
| "filter": [ | |
| { | |
| "function": "regex", | |
| "regex_pattern": "answer is \\(?([ABCDEFGHIJ])\\)?" | |
| }, | |
| { | |
| "function": "take_first" | |
| } | |
| ] | |
| } | |
| ], | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 1.0 | |
| } | |
| } | |
| }, | |
| "versions": { | |
| "mmlu_pro": 2.0, | |
| "mmlu_pro_biology": 1.0, | |
| "mmlu_pro_business": 1.0, | |
| "mmlu_pro_chemistry": 1.0, | |
| "mmlu_pro_computer_science": 1.0, | |
| "mmlu_pro_economics": 1.0, | |
| "mmlu_pro_engineering": 1.0, | |
| "mmlu_pro_health": 1.0, | |
| "mmlu_pro_history": 1.0, | |
| "mmlu_pro_law": 1.0, | |
| "mmlu_pro_math": 1.0, | |
| "mmlu_pro_other": 1.0, | |
| "mmlu_pro_philosophy": 1.0, | |
| "mmlu_pro_physics": 1.0, | |
| "mmlu_pro_psychology": 1.0 | |
| }, | |
| "n-shot": { | |
| "mmlu_pro_biology": 5, | |
| "mmlu_pro_business": 5, | |
| "mmlu_pro_chemistry": 5, | |
| "mmlu_pro_computer_science": 5, | |
| "mmlu_pro_economics": 5, | |
| "mmlu_pro_engineering": 5, | |
| "mmlu_pro_health": 5, | |
| "mmlu_pro_history": 5, | |
| "mmlu_pro_law": 5, | |
| "mmlu_pro_math": 5, | |
| "mmlu_pro_other": 5, | |
| "mmlu_pro_philosophy": 5, | |
| "mmlu_pro_physics": 5, | |
| "mmlu_pro_psychology": 5 | |
| }, | |
| "higher_is_better": { | |
| "mmlu_pro": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_biology": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_business": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_chemistry": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_computer_science": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_economics": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_engineering": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_health": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_history": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_law": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_math": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_other": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_philosophy": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_physics": { | |
| "exact_match": true | |
| }, | |
| "mmlu_pro_psychology": { | |
| "exact_match": true | |
| } | |
| }, | |
| "n-samples": { | |
| "mmlu_pro_biology": { | |
| "original": 717, | |
| "effective": 717 | |
| }, | |
| "mmlu_pro_business": { | |
| "original": 789, | |
| "effective": 789 | |
| }, | |
| "mmlu_pro_chemistry": { | |
| "original": 1132, | |
| "effective": 1132 | |
| }, | |
| "mmlu_pro_computer_science": { | |
| "original": 410, | |
| "effective": 410 | |
| }, | |
| "mmlu_pro_economics": { | |
| "original": 844, | |
| "effective": 844 | |
| }, | |
| "mmlu_pro_engineering": { | |
| "original": 969, | |
| "effective": 969 | |
| }, | |
| "mmlu_pro_health": { | |
| "original": 818, | |
| "effective": 818 | |
| }, | |
| "mmlu_pro_history": { | |
| "original": 381, | |
| "effective": 381 | |
| }, | |
| "mmlu_pro_law": { | |
| "original": 1101, | |
| "effective": 1101 | |
| }, | |
| "mmlu_pro_math": { | |
| "original": 1351, | |
| "effective": 1351 | |
| }, | |
| "mmlu_pro_other": { | |
| "original": 924, | |
| "effective": 924 | |
| }, | |
| "mmlu_pro_philosophy": { | |
| "original": 499, | |
| "effective": 499 | |
| }, | |
| "mmlu_pro_physics": { | |
| "original": 1299, | |
| "effective": 1299 | |
| }, | |
| "mmlu_pro_psychology": { | |
| "original": 798, | |
| "effective": 798 | |
| } | |
| }, | |
| "config": { | |
| "model": "vllm", | |
| "model_args": "pretrained=Qwen/Qwen2.5-14B-Instruct,tensor_parallel_size=4,data_parallel_size=2,download_dir=/tmp", | |
| "batch_size": 1, | |
| "batch_sizes": [], | |
| "device": null, | |
| "use_cache": null, | |
| "limit": null, | |
| "bootstrap_iters": 100000, | |
| "gen_kwargs": null, | |
| "random_seed": 0, | |
| "numpy_seed": 1234, | |
| "torch_seed": 1234, | |
| "fewshot_seed": 1234 | |
| }, | |
| "git_hash": "788a3672", | |
| "date": 1738828783.141779, | |
| "pretty_env_info": "PyTorch version: 2.4.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.3 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.27.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-1064-azure-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.128\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA H100 80GB HBM3\nGPU 1: NVIDIA H100 80GB HBM3\nGPU 2: NVIDIA H100 80GB HBM3\nGPU 3: NVIDIA H100 80GB HBM3\nGPU 4: NVIDIA H100 80GB HBM3\nGPU 5: NVIDIA H100 80GB HBM3\nGPU 6: NVIDIA H100 80GB HBM3\nGPU 7: NVIDIA H100 80GB HBM3\n\nNvidia driver version: 535.161.08\ncuDNN version: Probably one of the following:\n/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.4\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture: x86_64\nCPU op-mode(s): 32-bit, 64-bit\nAddress sizes: 46 bits physical, 57 bits virtual\nByte Order: Little Endian\nCPU(s): 96\nOn-line CPU(s) list: 0-95\nVendor ID: GenuineIntel\nModel name: Intel(R) Xeon(R) Platinum 8480C\nCPU family: 6\nModel: 143\nThread(s) per core: 1\nCore(s) per socket: 48\nSocket(s): 2\nStepping: 8\nBogoMIPS: 4000.00\nFlags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology tsc_reliable nonstop_tsc cpuid aperfmperf pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx_vnni avx512_bf16 avx512vbmi umip waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid cldemote movdiri movdir64b fsrm serialize amx_bf16 avx512_fp16 amx_tile amx_int8 arch_capabilities\nHypervisor vendor: Microsoft\nVirtualization type: full\nL1d cache: 4.5 MiB (96 instances)\nL1i cache: 3 MiB (96 instances)\nL2 cache: 192 MiB (96 instances)\nL3 cache: 210 MiB (2 instances)\nNUMA node(s): 2\nNUMA node0 CPU(s): 0-47\nNUMA node1 CPU(s): 48-95\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit: Not affected\nVulnerability L1tf: Not affected\nVulnerability Mds: Not affected\nVulnerability Meltdown: Not affected\nVulnerability Mmio stale data: Unknown: No mitigations\nVulnerability Retbleed: Vulnerable\nVulnerability Spec rstack overflow: Not affected\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 Retpoline\nVulnerability Srbds: Not affected\nVulnerability Tsx async abort: Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.4\n[pip3] onnx==1.14.0\n[pip3] pytorch-lightning==2.0.7\n[pip3] pytorch-quantization==2.1.2\n[pip3] torch==2.4.0\n[pip3] torch-tensorrt==2.0.0.dev0\n[pip3] torchaudio==2.1.0\n[pip3] torchdata==0.7.0a0\n[pip3] torchmetrics==1.2.0\n[pip3] torchvision==0.19.0\n[pip3] triton==3.0.0\n[conda] Could not collect", | |
| "transformers_version": "4.48.2", | |
| "upper_git_hash": null, | |
| "tokenizer_pad_token": [ | |
| "<|endoftext|>", | |
| "151643" | |
| ], | |
| "tokenizer_eos_token": [ | |
| "<|im_end|>", | |
| "151645" | |
| ], | |
| "tokenizer_bos_token": [ | |
| null, | |
| "None" | |
| ], | |
| "eot_token_id": 151645, | |
| "max_length": 32768, | |
| "task_hashes": { | |
| "mmlu_pro_biology": "78a27f3d4ea386dd0f7b5045f25bf654ba560ee9feac7b22eab763c73b4c37b9", | |
| "mmlu_pro_business": "9d10f8702f23d8d5aa9546ebf453e9333a6998a272450bc468b8f74bca8a1824", | |
| "mmlu_pro_chemistry": "0e3a8823fed7bd895e42f5053851f12b125f62edfcb36809e4c0aebec80f4506", | |
| "mmlu_pro_computer_science": "26e8d9026807a7552684e4ddd1a373873449548e0f0ac8abeada18f32cc5f685", | |
| "mmlu_pro_economics": "427580d476e69dc8f095f487f3081cbff1dbfdd3a05a4c13c024ae5bd6907262", | |
| "mmlu_pro_engineering": "66bc34b22bf2c19eab04a753e65e8aea2e6834544b27516a6aa2769a9be0b9e5", | |
| "mmlu_pro_health": "62edd914028ea5b83013192e458af0d22b843d25ce0ac6e280244d819615cdc4", | |
| "mmlu_pro_history": "8295796e4901f2a6b42a2bd8b6e888f2e64ae24ce451f8ecef70db6351f3583d", | |
| "mmlu_pro_law": "6969a0ecb6ac565ee29e658094231ddcf1016237aff3d903f5d219dd68a2e5dd", | |
| "mmlu_pro_math": "eb48989afd83cb45e2dfd8c769fbe986927de9eb06ac775a7237e939150f20ec", | |
| "mmlu_pro_other": "82e12fde3ce84ca4d478ce4623e9dd3877b8bd46c7fc1346c3d9e534df9cbba3", | |
| "mmlu_pro_philosophy": "1cd86d5d342a6029560af9a2d51e397df4f537d81d4e6249a0917267c91073e1", | |
| "mmlu_pro_physics": "dce786711af6f503b9b1463ca9e245de515859363f4ee7f0aa94656c3357a288", | |
| "mmlu_pro_psychology": "526f25dba79a26df39f911b7d6010990c8e21d7c473c89a94e4298566d7cdeda" | |
| }, | |
| "model_source": "vllm", | |
| "model_name": "Qwen/Qwen2.5-14B-Instruct", | |
| "model_name_sanitized": "Qwen__Qwen2.5-14B-Instruct", | |
| "system_instruction": null, | |
| "system_instruction_sha": null, | |
| "fewshot_as_multiturn": false, | |
| "chat_template": null, | |
| "chat_template_sha": null, | |
| "start_time": 629513.139791946, | |
| "end_time": 630076.356428782, | |
| "total_evaluation_time_seconds": "563.2166368359467" | |
| } |