|
{ |
|
"results": { |
|
"soluta-magni-5240_logiqa2_cot": { |
|
"acc,none": 0.3702290076335878, |
|
"acc_stderr,none": 0.012182557094147298, |
|
"alias": "soluta-magni-5240_logiqa2_cot" |
|
}, |
|
"soluta-magni-5240_logiqa_cot": { |
|
"acc,none": 0.3242811501597444, |
|
"acc_stderr,none": 0.018724225412478573, |
|
"alias": "soluta-magni-5240_logiqa_cot" |
|
}, |
|
"soluta-magni-5240_lsat-ar_cot": { |
|
"acc,none": 0.26521739130434785, |
|
"acc_stderr,none": 0.02917176407847257, |
|
"alias": "soluta-magni-5240_lsat-ar_cot" |
|
}, |
|
"soluta-magni-5240_lsat-lr_cot": { |
|
"acc,none": 0.2980392156862745, |
|
"acc_stderr,none": 0.020273757152422762, |
|
"alias": "soluta-magni-5240_lsat-lr_cot" |
|
}, |
|
"soluta-magni-5240_lsat-rc_cot": { |
|
"acc,none": 0.4052044609665427, |
|
"acc_stderr,none": 0.029988418521912058, |
|
"alias": "soluta-magni-5240_lsat-rc_cot" |
|
} |
|
}, |
|
"configs": { |
|
"soluta-magni-5240_logiqa2_cot": { |
|
"task": "soluta-magni-5240_logiqa2_cot", |
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"group": "logikon-bench", |
|
"dataset_path": "cot-leaderboard/cot-eval-traces", |
|
"dataset_kwargs": { |
|
"data_files": { |
|
"test": "soluta-magni-5240-logiqa2/test-00000-of-00001.parquet" |
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} |
|
}, |
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"test_split": "test", |
|
"doc_to_text": "def doc_to_text_cot(doc) -> str:\n \"\"\"\n Answer the following question about the given passage. [Base your answer on the reasoning below.]\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n [Reasoning: <reasoning>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage. Base your answer on the reasoning below.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"\\n\"\n prompt += \"Reasoning: \" + doc[\"reasoning_trace\"] + \"\\n\\n\" \n prompt += \"Answer:\"\n return prompt\n", |
|
"doc_to_target": "{{answer}}", |
|
"doc_to_choice": "{{options}}", |
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"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"num_fewshot": 0, |
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"metric_list": [ |
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{ |
|
"metric": "acc", |
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"aggregation": "mean", |
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"higher_is_better": true |
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} |
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], |
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"output_type": "multiple_choice", |
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"repeats": 1, |
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"should_decontaminate": false, |
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"metadata": { |
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"version": 0.0 |
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} |
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}, |
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"soluta-magni-5240_logiqa_cot": { |
|
"task": "soluta-magni-5240_logiqa_cot", |
|
"group": "logikon-bench", |
|
"dataset_path": "cot-leaderboard/cot-eval-traces", |
|
"dataset_kwargs": { |
|
"data_files": { |
|
"test": "soluta-magni-5240-logiqa/test-00000-of-00001.parquet" |
|
} |
|
}, |
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"test_split": "test", |
|
"doc_to_text": "def doc_to_text_cot(doc) -> str:\n \"\"\"\n Answer the following question about the given passage. [Base your answer on the reasoning below.]\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n [Reasoning: <reasoning>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage. Base your answer on the reasoning below.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"\\n\"\n prompt += \"Reasoning: \" + doc[\"reasoning_trace\"] + \"\\n\\n\" \n prompt += \"Answer:\"\n return prompt\n", |
|
"doc_to_target": "{{answer}}", |
|
"doc_to_choice": "{{options}}", |
|
"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
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"num_fewshot": 0, |
|
"metric_list": [ |
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{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
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"higher_is_better": true |
|
} |
|
], |
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"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"soluta-magni-5240_lsat-ar_cot": { |
|
"task": "soluta-magni-5240_lsat-ar_cot", |
|
"group": "logikon-bench", |
|
"dataset_path": "cot-leaderboard/cot-eval-traces", |
|
"dataset_kwargs": { |
|
"data_files": { |
|
"test": "soluta-magni-5240-lsat-ar/test-00000-of-00001.parquet" |
|
} |
|
}, |
|
"test_split": "test", |
|
"doc_to_text": "def doc_to_text_cot(doc) -> str:\n \"\"\"\n Answer the following question about the given passage. [Base your answer on the reasoning below.]\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n [Reasoning: <reasoning>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage. Base your answer on the reasoning below.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"\\n\"\n prompt += \"Reasoning: \" + doc[\"reasoning_trace\"] + \"\\n\\n\" \n prompt += \"Answer:\"\n return prompt\n", |
|
"doc_to_target": "{{answer}}", |
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"doc_to_choice": "{{options}}", |
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"description": "", |
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"target_delimiter": " ", |
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"fewshot_delimiter": "\n\n", |
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"num_fewshot": 0, |
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"metric_list": [ |
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{ |
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"metric": "acc", |
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"aggregation": "mean", |
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"higher_is_better": true |
|
} |
|
], |
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"output_type": "multiple_choice", |
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"repeats": 1, |
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"should_decontaminate": false, |
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"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"soluta-magni-5240_lsat-lr_cot": { |
|
"task": "soluta-magni-5240_lsat-lr_cot", |
|
"group": "logikon-bench", |
|
"dataset_path": "cot-leaderboard/cot-eval-traces", |
|
"dataset_kwargs": { |
|
"data_files": { |
|
"test": "soluta-magni-5240-lsat-lr/test-00000-of-00001.parquet" |
|
} |
|
}, |
|
"test_split": "test", |
|
"doc_to_text": "def doc_to_text_cot(doc) -> str:\n \"\"\"\n Answer the following question about the given passage. [Base your answer on the reasoning below.]\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n [Reasoning: <reasoning>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage. Base your answer on the reasoning below.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"\\n\"\n prompt += \"Reasoning: \" + doc[\"reasoning_trace\"] + \"\\n\\n\" \n prompt += \"Answer:\"\n return prompt\n", |
|
"doc_to_target": "{{answer}}", |
|
"doc_to_choice": "{{options}}", |
|
"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
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"num_fewshot": 0, |
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"metric_list": [ |
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{ |
|
"metric": "acc", |
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"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"soluta-magni-5240_lsat-rc_cot": { |
|
"task": "soluta-magni-5240_lsat-rc_cot", |
|
"group": "logikon-bench", |
|
"dataset_path": "cot-leaderboard/cot-eval-traces", |
|
"dataset_kwargs": { |
|
"data_files": { |
|
"test": "soluta-magni-5240-lsat-rc/test-00000-of-00001.parquet" |
|
} |
|
}, |
|
"test_split": "test", |
|
"doc_to_text": "def doc_to_text_cot(doc) -> str:\n \"\"\"\n Answer the following question about the given passage. [Base your answer on the reasoning below.]\n \n Passage: <passage>\n \n Question: <question>\n A. <choice1>\n B. <choice2>\n C. <choice3>\n D. <choice4>\n [E. <choice5>]\n \n [Reasoning: <reasoning>]\n \n Answer:\n \"\"\"\n k = len(doc[\"options\"])\n choices = [\"a\", \"b\", \"c\", \"d\", \"e\"][:k]\n prompt = \"Answer the following question about the given passage. Base your answer on the reasoning below.\\n\\n\"\n prompt = \"Passage: \" + doc[\"passage\"] + \"\\n\\n\"\n prompt += \"Question: \" + doc[\"question\"] + \"\\n\"\n for choice, option in zip(choices, doc[\"options\"]):\n prompt += f\"{choice.upper()}. {option}\\n\"\n prompt += \"\\n\"\n prompt += \"Reasoning: \" + doc[\"reasoning_trace\"] + \"\\n\\n\" \n prompt += \"Answer:\"\n return prompt\n", |
|
"doc_to_target": "{{answer}}", |
|
"doc_to_choice": "{{options}}", |
|
"description": "", |
|
"target_delimiter": " ", |
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"fewshot_delimiter": "\n\n", |
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"num_fewshot": 0, |
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"metric_list": [ |
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{ |
|
"metric": "acc", |
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"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
} |
|
}, |
|
"versions": { |
|
"soluta-magni-5240_logiqa2_cot": 0.0, |
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"soluta-magni-5240_logiqa_cot": 0.0, |
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"soluta-magni-5240_lsat-ar_cot": 0.0, |
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"soluta-magni-5240_lsat-lr_cot": 0.0, |
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"soluta-magni-5240_lsat-rc_cot": 0.0 |
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}, |
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"n-shot": { |
|
"soluta-magni-5240_logiqa2_cot": 0, |
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"soluta-magni-5240_logiqa_cot": 0, |
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"soluta-magni-5240_lsat-ar_cot": 0, |
|
"soluta-magni-5240_lsat-lr_cot": 0, |
|
"soluta-magni-5240_lsat-rc_cot": 0 |
|
}, |
|
"config": { |
|
"model": "vllm", |
|
"model_args": "pretrained=microsoft/Orca-2-7b,revision=main,dtype=float16,tensor_parallel_size=1,gpu_memory_utilization=0.7,trust_remote_code=true,max_length=2048", |
|
"batch_size": "auto", |
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"batch_sizes": [], |
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"device": null, |
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"use_cache": null, |
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"limit": null, |
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"bootstrap_iters": 100000, |
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"gen_kwargs": null |
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}, |
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"git_hash": "741db1c" |
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} |