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ALLaM-7B-Instruct-preview/evaluations/en/jais-adapted-13b-chat/mmlu_pro_5_shot.json

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初始化项目，由ModelHub XC社区提供模型 Model: lanawwas/ALLaM-7B-Instruct-preview Source: Original Platform
2026-04-22 10:54:04 +08:00
{
"results": {
"mmlu_pro": {
"exact_match,custom-extract": 0.2628823138297872,
"exact_match_stderr,custom-extract": 0.003918934360900739,
"alias": "mmlu_pro"
},
"mmlu_pro_biology": {
"alias": " - biology",
"exact_match,custom-extract": 0.4714086471408647,
"exact_match_stderr,custom-extract": 0.01865530218568491
},
"mmlu_pro_business": {
"alias": " - business",
"exact_match,custom-extract": 0.27629911280101394,
"exact_match_stderr,custom-extract": 0.015929648357222322
},
"mmlu_pro_chemistry": {
"alias": " - chemistry",
"exact_match,custom-extract": 0.11837455830388692,
"exact_match_stderr,custom-extract": 0.009605941567355314
},
"mmlu_pro_computer_science": {
"alias": " - computer_science",
"exact_match,custom-extract": 0.275609756097561,
"exact_match_stderr,custom-extract": 0.022093877192384963
},
"mmlu_pro_economics": {
"alias": " - economics",
"exact_match,custom-extract": 0.3518957345971564,
"exact_match_stderr,custom-extract": 0.016448096825135112
},
"mmlu_pro_engineering": {
"alias": " - engineering",
"exact_match,custom-extract": 0.15892672858617132,
"exact_match_stderr,custom-extract": 0.011751078002557013
},
"mmlu_pro_health": {
"alias": " - health",
"exact_match,custom-extract": 0.28973105134474325,
"exact_match_stderr,custom-extract": 0.01587076668876994
},
"mmlu_pro_history": {
"alias": " - history",
"exact_match,custom-extract": 0.29658792650918636,
"exact_match_stderr,custom-extract": 0.023430947167220318
},
"mmlu_pro_law": {
"alias": " - law",
"exact_match,custom-extract": 0.1807447774750227,
"exact_match_stderr,custom-extract": 0.011602354889908755
},
"mmlu_pro_math": {
"alias": " - math",
"exact_match,custom-extract": 0.24204293116210215,
"exact_match_stderr,custom-extract": 0.011657397925671434
},
"mmlu_pro_other": {
"alias": " - other",
"exact_match,custom-extract": 0.3365800865800866,
"exact_match_stderr,custom-extract": 0.015553839388265447
},
"mmlu_pro_philosophy": {
"alias": " - philosophy",
"exact_match,custom-extract": 0.2905811623246493,
"exact_match_stderr,custom-extract": 0.020345595934973294
},
"mmlu_pro_physics": {
"alias": " - physics",
"exact_match,custom-extract": 0.19168591224018475,
"exact_match_stderr,custom-extract": 0.010925663632033133
},
"mmlu_pro_psychology": {
"alias": " - psychology",
"exact_match,custom-extract": 0.41102756892230574,
"exact_match_stderr,custom-extract": 0.01742825071101031
}
},
"groups": {
"mmlu_pro": {
"exact_match,custom-extract": 0.2628823138297872,
"exact_match_stderr,custom-extract": 0.003918934360900739,
"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 0x1549a4362b00>, subject='biology')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a4360ca0>, 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 0x1549a43604c0>, 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 0x1549a55b0040>, subject='business')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a55b0f70>, 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 0x1549a55b1120>, 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 0x1549a4360430>, subject='chemistry')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a4363eb0>, 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 0x1549a4362560>, 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 0x1549a4363130>, subject='computer science')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a4360ee0>, 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 0x1549a4363b50>, 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 0x1549a4363be0>, subject='economics')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a4362ef0>, 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 0x1549a43639a0>, 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 0x1549a4363400>, subject='engineering')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a4362710>, 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 0x1549a4362830>, 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 0x1549a4361ab0>, subject='health')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a43609d0>, 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 0x1549a4361990>, 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 0x1549a43615a0>, subject='history')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a4361480>, 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 0x1549a4360f70>, 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 0x1549a4363640>, subject='law')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a43636d0>, 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 0x1549a4363d90>, 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 0x1549a4363a30>, subject='math')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a4361cf0>, 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 0x1549a4361bd0>, 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 0x1549a43605e0>, subject='other')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x1549a43613f0>, 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 0x1549a4360af0>, 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 0x154fc0913d00>, subject='philosophy')",
"doc_to_text": "functools.partial(<function format_cot_example at 0x154fc0913eb0>, 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 0x154fc0910dc0>, including_answer=True)",
"doc_to_target": ""
},
"num_fewshot": 5,
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},
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],
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"mmlu_pro_psychology": {
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"doc_to_text": "functools.partial(<function format_cot_example at 0x154fc09f7400>, including_answer=False)",
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"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",
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},
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"mmlu_pro_engineering": {
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"mmlu_pro_health": {
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"mmlu_pro_law": {
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"mmlu_pro_math": {
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"mmlu_pro_other": {
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"mmlu_pro_philosophy": {
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"mmlu_pro_physics": {
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},
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"effective": 717
},
"mmlu_pro_business": {
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"effective": 789
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"mmlu_pro_chemistry": {
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"effective": 1132
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"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": {
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"effective": 1101
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"mmlu_pro_math": {
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"effective": 1351
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"mmlu_pro_other": {
"original": 924,
"effective": 924
},
"mmlu_pro_philosophy": {
"original": 499,
"effective": 499
},
"mmlu_pro_physics": {
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"effective": 1299
},
"mmlu_pro_psychology": {
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"effective": 798
}
},
"config": {
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"model_args": "parallelize=False,pretrained=inceptionai/jais-adapted-13b-chat,trust_remote_code=True,mm=False",
"model_num_parameters": 13343544320,
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"device": null,
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"limit": null,
"bootstrap_iters": 100000,
"gen_kwargs": null,
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},
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"date": 1730985220.2037723,
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"model_name_sanitized": "inceptionai__jais-adapted-13b-chat",
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"system_instruction_sha": null,
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"chat_template": null,
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"end_time": 168425.436540462,
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}
Reference in New Issue Copy Permalink