| { | |
| "results": { | |
| "mmlu_pro": { | |
| "exact_match,custom-extract": 0.331781914893617, | |
| "exact_match_stderr,custom-extract": 0.004148145764333384, | |
| "alias": "mmlu_pro" | |
| }, | |
| "mmlu_pro_biology": { | |
| "alias": " - biology", | |
| "exact_match,custom-extract": 0.596931659693166, | |
| "exact_match_stderr,custom-extract": 0.01833137910755257 | |
| }, | |
| "mmlu_pro_business": { | |
| "alias": " - business", | |
| "exact_match,custom-extract": 0.302915082382763, | |
| "exact_match_stderr,custom-extract": 0.016369679755239445 | |
| }, | |
| "mmlu_pro_chemistry": { | |
| "alias": " - chemistry", | |
| "exact_match,custom-extract": 0.1784452296819788, | |
| "exact_match_stderr,custom-extract": 0.011385167638750223 | |
| }, | |
| "mmlu_pro_computer_science": { | |
| "alias": " - computer_science", | |
| "exact_match,custom-extract": 0.348780487804878, | |
| "exact_match_stderr,custom-extract": 0.023565580300378107 | |
| }, | |
| "mmlu_pro_economics": { | |
| "alias": " - economics", | |
| "exact_match,custom-extract": 0.4561611374407583, | |
| "exact_match_stderr,custom-extract": 0.017154595168203345 | |
| }, | |
| "mmlu_pro_engineering": { | |
| "alias": " - engineering", | |
| "exact_match,custom-extract": 0.2084623323013416, | |
| "exact_match_stderr,custom-extract": 0.013056053198289154 | |
| }, | |
| "mmlu_pro_health": { | |
| "alias": " - health", | |
| "exact_match,custom-extract": 0.4193154034229829, | |
| "exact_match_stderr,custom-extract": 0.017263527180628145 | |
| }, | |
| "mmlu_pro_history": { | |
| "alias": " - history", | |
| "exact_match,custom-extract": 0.3674540682414698, | |
| "exact_match_stderr,custom-extract": 0.024731802239981133 | |
| }, | |
| "mmlu_pro_law": { | |
| "alias": " - law", | |
| "exact_match,custom-extract": 0.23160762942779292, | |
| "exact_match_stderr,custom-extract": 0.012719545997423476 | |
| }, | |
| "mmlu_pro_math": { | |
| "alias": " - math", | |
| "exact_match,custom-extract": 0.23316062176165803, | |
| "exact_match_stderr,custom-extract": 0.011508346285981068 | |
| }, | |
| "mmlu_pro_other": { | |
| "alias": " - other", | |
| "exact_match,custom-extract": 0.4090909090909091, | |
| "exact_match_stderr,custom-extract": 0.016183386248098043 | |
| }, | |
| "mmlu_pro_philosophy": { | |
| "alias": " - philosophy", | |
| "exact_match,custom-extract": 0.37675350701402804, | |
| "exact_match_stderr,custom-extract": 0.02171420342667759 | |
| }, | |
| "mmlu_pro_physics": { | |
| "alias": " - physics", | |
| "exact_match,custom-extract": 0.2702078521939954, | |
| "exact_match_stderr,custom-extract": 0.012325689684529193 | |
| }, | |
| "mmlu_pro_psychology": { | |
| "alias": " - psychology", | |
| "exact_match,custom-extract": 0.5300751879699248, | |
| "exact_match_stderr,custom-extract": 0.017678840007925144 | |
| } | |
| }, | |
| "groups": { | |
| "mmlu_pro": { | |
| "exact_match,custom-extract": 0.331781914893617, | |
| "exact_match_stderr,custom-extract": 0.004148145764333384, | |
| "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 0x1524595d0af0>, subject='biology')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x1524595d3880>, 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 0x1524595d3760>, 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 0x1524595d0160>, subject='business')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x1524595d3490>, 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 0x1524595d3370>, 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 0x1524595d0670>, subject='chemistry')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x1524595d30a0>, 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 0x1524595d2f80>, 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 0x1524595d0430>, subject='computer science')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x1524595d2cb0>, 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 0x1524595d2b90>, 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 0x1524595d0b80>, subject='economics')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x1524595d28c0>, 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 0x1524595d27a0>, 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 0x1524595d01f0>, subject='engineering')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x1524595d2440>, 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 0x1524595d2320>, 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 0x1524595d1cf0>, subject='health')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x1524595d2050>, 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 0x1524595d1f30>, 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 0x1524595d15a0>, subject='history')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x1524595d1a20>, 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 0x1524595d1900>, 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 0x152459377130>, subject='law')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x152459376c20>, 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 0x152459377010>, 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 0x1524595d0700>, subject='math')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x152459377b50>, 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 0x152459376f80>, 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 0x152459377370>, subject='other')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x152459377d90>, 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 0x152459376e60>, 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 0x1524593775b0>, subject='philosophy')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x15245acd2c20>, 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 0x152459377f40>, 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 0x152459377520>, subject='physics')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x15245acd2d40>, 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 0x1524593777f0>, 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 0x15245acd3010>, subject='psychology')", | |
| "doc_to_text": "functools.partial(<function format_cot_example at 0x15245acd3520>, 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 0x15245acd2950>, 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": "hf", | |
| "model_args": "pretrained=mistralai/Mistral-7B-Instruct-v0.3,trust_remote_code=True,cache_dir=/tmp,parallelize=False", | |
| "model_num_parameters": 7248023552, | |
| "model_dtype": "torch.bfloat16", | |
| "model_revision": "main", | |
| "model_sha": "e0bc86c23ce5aae1db576c8cca6f06f1f73af2db", | |
| "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": "112b79143", | |
| "date": 1739601765.3763208, | |
| "pretty_env_info": "PyTorch version: 2.4.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.3 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.27.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-1064-azure-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.128\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Probably one of the following:\n/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.4\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture: x86_64\nCPU op-mode(s): 32-bit, 64-bit\nAddress sizes: 48 bits physical, 48 bits virtual\nByte Order: Little Endian\nCPU(s): 96\nOn-line CPU(s) list: 0-95\nVendor ID: AuthenticAMD\nModel name: AMD EPYC 7V12 64-Core Processor\nCPU family: 23\nModel: 49\nThread(s) per core: 1\nCore(s) per socket: 48\nSocket(s): 2\nStepping: 0\nBogoMIPS: 4890.88\nFlags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext perfctr_core ssbd vmmcall fsgsbase bmi1 avx2 smep bmi2 rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 clzero xsaveerptr rdpru arat umip rdpid\nHypervisor vendor: Microsoft\nVirtualization type: full\nL1d cache: 3 MiB (96 instances)\nL1i cache: 3 MiB (96 instances)\nL2 cache: 48 MiB (96 instances)\nL3 cache: 384 MiB (24 instances)\nNUMA node(s): 4\nNUMA node0 CPU(s): 0-23\nNUMA node1 CPU(s): 24-47\nNUMA node2 CPU(s): 48-71\nNUMA node3 CPU(s): 72-95\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit: Not affected\nVulnerability L1tf: Not affected\nVulnerability Mds: Not affected\nVulnerability Meltdown: Not affected\nVulnerability Mmio stale data: Not affected\nVulnerability Retbleed: Mitigation; untrained return thunk; SMT disabled\nVulnerability Spec rstack overflow: Mitigation; safe RET, no microcode\nVulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2: Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected\nVulnerability Srbds: Not affected\nVulnerability Tsx async abort: Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.4\n[pip3] onnx==1.14.0\n[pip3] pytorch-lightning==2.0.7\n[pip3] pytorch-quantization==2.1.2\n[pip3] torch==2.4.0\n[pip3] torch-tensorrt==2.0.0.dev0\n[pip3] torchaudio==2.1.0\n[pip3] torchdata==0.7.0a0\n[pip3] torchmetrics==1.2.0\n[pip3] torchvision==0.19.0\n[pip3] triton==3.0.0\n[conda] Could not collect", | |
| "transformers_version": "4.48.3", | |
| "upper_git_hash": null, | |
| "tokenizer_pad_token": [ | |
| "<unk>", | |
| "0" | |
| ], | |
| "tokenizer_eos_token": [ | |
| "</s>", | |
| "2" | |
| ], | |
| "tokenizer_bos_token": [ | |
| "<s>", | |
| "1" | |
| ], | |
| "eot_token_id": 2, | |
| "max_length": 32768, | |
| "task_hashes": {}, | |
| "model_source": "hf", | |
| "model_name": "mistralai/Mistral-7B-Instruct-v0.3", | |
| "model_name_sanitized": "mistralai__Mistral-7B-Instruct-v0.3", | |
| "system_instruction": null, | |
| "system_instruction_sha": null, | |
| "fewshot_as_multiturn": false, | |
| "chat_template": null, | |
| "chat_template_sha": null, | |
| "start_time": 1712199.299923685, | |
| "end_time": 1800173.808858755, | |
| "total_evaluation_time_seconds": "87974.50893507013" | |
| } |