| { | |
| "results": { | |
| "veritatis-velit_lsat-rc_base": { | |
| "acc,none": 0.37174721189591076, | |
| "acc_stderr,none": 0.029520497706913982, | |
| "alias": "veritatis-velit_lsat-rc_base" | |
| }, | |
| "veritatis-velit_lsat-lr_base": { | |
| "acc,none": 0.25098039215686274, | |
| "acc_stderr,none": 0.0192179738903761, | |
| "alias": "veritatis-velit_lsat-lr_base" | |
| }, | |
| "veritatis-velit_lsat-ar_base": { | |
| "acc,none": 0.2217391304347826, | |
| "acc_stderr,none": 0.02745149660405891, | |
| "alias": "veritatis-velit_lsat-ar_base" | |
| }, | |
| "veritatis-velit_logiqa_base": { | |
| "acc,none": 0.29073482428115016, | |
| "acc_stderr,none": 0.018164056209177798, | |
| "alias": "veritatis-velit_logiqa_base" | |
| }, | |
| "veritatis-velit_logiqa2_base": { | |
| "acc,none": 0.36704834605597964, | |
| "acc_stderr,none": 0.01216070666440455, | |
| "alias": "veritatis-velit_logiqa2_base" | |
| }, | |
| "saepe-fuga_lsat-rc_base": { | |
| "acc,none": 0.34944237918215615, | |
| "acc_stderr,none": 0.02912482161970039, | |
| "alias": "saepe-fuga_lsat-rc_base" | |
| }, | |
| "saepe-fuga_lsat-lr_base": { | |
| "acc,none": 0.2823529411764706, | |
| "acc_stderr,none": 0.01995228875819785, | |
| "alias": "saepe-fuga_lsat-lr_base" | |
| }, | |
| "saepe-fuga_lsat-ar_base": { | |
| "acc,none": 0.17391304347826086, | |
| "acc_stderr,none": 0.025047317386049713, | |
| "alias": "saepe-fuga_lsat-ar_base" | |
| }, | |
| "saepe-fuga_logiqa_base": { | |
| "acc,none": 0.30670926517571884, | |
| "acc_stderr,none": 0.01844510522956535, | |
| "alias": "saepe-fuga_logiqa_base" | |
| }, | |
| "saepe-fuga_logiqa2_base": { | |
| "acc,none": 0.36323155216284986, | |
| "acc_stderr,none": 0.012133733683836157, | |
| "alias": "saepe-fuga_logiqa2_base" | |
| }, | |
| "nisi-sunt_lsat-rc_base": { | |
| "acc,none": 0.31226765799256506, | |
| "acc_stderr,none": 0.028307781204694345, | |
| "alias": "nisi-sunt_lsat-rc_base" | |
| }, | |
| "nisi-sunt_lsat-lr_base": { | |
| "acc,none": 0.26862745098039215, | |
| "acc_stderr,none": 0.019646519888599705, | |
| "alias": "nisi-sunt_lsat-lr_base" | |
| }, | |
| "nisi-sunt_lsat-ar_base": { | |
| "acc,none": 0.20869565217391303, | |
| "acc_stderr,none": 0.02685410826543969, | |
| "alias": "nisi-sunt_lsat-ar_base" | |
| }, | |
| "nisi-sunt_logiqa_base": { | |
| "acc,none": 0.3003194888178914, | |
| "acc_stderr,none": 0.018335874932123606, | |
| "alias": "nisi-sunt_logiqa_base" | |
| }, | |
| "nisi-sunt_logiqa2_base": { | |
| "acc,none": 0.37659033078880405, | |
| "acc_stderr,none": 0.01222456057756536, | |
| "alias": "nisi-sunt_logiqa2_base" | |
| }, | |
| "laboriosam-molestiae_lsat-rc_base": { | |
| "acc,none": 0.3308550185873606, | |
| "acc_stderr,none": 0.02874164221560224, | |
| "alias": "laboriosam-molestiae_lsat-rc_base" | |
| }, | |
| "laboriosam-molestiae_lsat-lr_base": { | |
| "acc,none": 0.28627450980392155, | |
| "acc_stderr,none": 0.020035401617079118, | |
| "alias": "laboriosam-molestiae_lsat-lr_base" | |
| }, | |
| "laboriosam-molestiae_lsat-ar_base": { | |
| "acc,none": 0.18695652173913044, | |
| "acc_stderr,none": 0.025763772398512335, | |
| "alias": "laboriosam-molestiae_lsat-ar_base" | |
| }, | |
| "laboriosam-molestiae_logiqa_base": { | |
| "acc,none": 0.3146964856230032, | |
| "acc_stderr,none": 0.018575795328740336, | |
| "alias": "laboriosam-molestiae_logiqa_base" | |
| }, | |
| "laboriosam-molestiae_logiqa2_base": { | |
| "acc,none": 0.3746819338422392, | |
| "acc_stderr,none": 0.012212196173823686, | |
| "alias": "laboriosam-molestiae_logiqa2_base" | |
| }, | |
| "iste-molestias_lsat-rc_base": { | |
| "acc,none": 0.36059479553903345, | |
| "acc_stderr,none": 0.029331239329958934, | |
| "alias": "iste-molestias_lsat-rc_base" | |
| }, | |
| "iste-molestias_lsat-lr_base": { | |
| "acc,none": 0.2549019607843137, | |
| "acc_stderr,none": 0.019316765480532974, | |
| "alias": "iste-molestias_lsat-lr_base" | |
| }, | |
| "iste-molestias_lsat-ar_base": { | |
| "acc,none": 0.20869565217391303, | |
| "acc_stderr,none": 0.026854108265439654, | |
| "alias": "iste-molestias_lsat-ar_base" | |
| }, | |
| "iste-molestias_logiqa_base": { | |
| "acc,none": 0.30670926517571884, | |
| "acc_stderr,none": 0.018445105229565353, | |
| "alias": "iste-molestias_logiqa_base" | |
| }, | |
| "iste-molestias_logiqa2_base": { | |
| "acc,none": 0.38549618320610685, | |
| "acc_stderr,none": 0.01227960059074116, | |
| "alias": "iste-molestias_logiqa2_base" | |
| }, | |
| "eum-saepe_lsat-rc_base": { | |
| "acc,none": 0.3643122676579926, | |
| "acc_stderr,none": 0.029396215063241374, | |
| "alias": "eum-saepe_lsat-rc_base" | |
| }, | |
| "eum-saepe_lsat-lr_base": { | |
| "acc,none": 0.24313725490196078, | |
| "acc_stderr,none": 0.01901408485181097, | |
| "alias": "eum-saepe_lsat-lr_base" | |
| }, | |
| "eum-saepe_lsat-ar_base": { | |
| "acc,none": 0.19130434782608696, | |
| "acc_stderr,none": 0.025991852462828487, | |
| "alias": "eum-saepe_lsat-ar_base" | |
| }, | |
| "eum-saepe_logiqa_base": { | |
| "acc,none": 0.3035143769968051, | |
| "acc_stderr,none": 0.01839101519560228, | |
| "alias": "eum-saepe_logiqa_base" | |
| }, | |
| "eum-saepe_logiqa2_base": { | |
| "acc,none": 0.3651399491094148, | |
| "acc_stderr,none": 0.01214732308367413, | |
| "alias": "eum-saepe_logiqa2_base" | |
| } | |
| }, | |
| "configs": { | |
| "eum-saepe_logiqa2_base": { | |
| "task": "eum-saepe_logiqa2_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "eum-saepe-logiqa2/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "eum-saepe_logiqa_base": { | |
| "task": "eum-saepe_logiqa_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "eum-saepe-logiqa/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "eum-saepe_lsat-ar_base": { | |
| "task": "eum-saepe_lsat-ar_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "eum-saepe-lsat-ar/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "eum-saepe_lsat-lr_base": { | |
| "task": "eum-saepe_lsat-lr_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "eum-saepe-lsat-lr/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "eum-saepe_lsat-rc_base": { | |
| "task": "eum-saepe_lsat-rc_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "eum-saepe-lsat-rc/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "iste-molestias_logiqa2_base": { | |
| "task": "iste-molestias_logiqa2_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "iste-molestias-logiqa2/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "iste-molestias_logiqa_base": { | |
| "task": "iste-molestias_logiqa_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "iste-molestias-logiqa/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "iste-molestias_lsat-ar_base": { | |
| "task": "iste-molestias_lsat-ar_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "iste-molestias-lsat-ar/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "iste-molestias_lsat-lr_base": { | |
| "task": "iste-molestias_lsat-lr_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "iste-molestias-lsat-lr/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "iste-molestias_lsat-rc_base": { | |
| "task": "iste-molestias_lsat-rc_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "iste-molestias-lsat-rc/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "laboriosam-molestiae_logiqa2_base": { | |
| "task": "laboriosam-molestiae_logiqa2_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "laboriosam-molestiae-logiqa2/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "laboriosam-molestiae_logiqa_base": { | |
| "task": "laboriosam-molestiae_logiqa_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "laboriosam-molestiae-logiqa/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "laboriosam-molestiae_lsat-ar_base": { | |
| "task": "laboriosam-molestiae_lsat-ar_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "laboriosam-molestiae-lsat-ar/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "laboriosam-molestiae_lsat-lr_base": { | |
| "task": "laboriosam-molestiae_lsat-lr_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "laboriosam-molestiae-lsat-lr/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "laboriosam-molestiae_lsat-rc_base": { | |
| "task": "laboriosam-molestiae_lsat-rc_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "laboriosam-molestiae-lsat-rc/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "nisi-sunt_logiqa2_base": { | |
| "task": "nisi-sunt_logiqa2_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "nisi-sunt-logiqa2/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "nisi-sunt_logiqa_base": { | |
| "task": "nisi-sunt_logiqa_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "nisi-sunt-logiqa/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "nisi-sunt_lsat-ar_base": { | |
| "task": "nisi-sunt_lsat-ar_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "nisi-sunt-lsat-ar/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "nisi-sunt_lsat-lr_base": { | |
| "task": "nisi-sunt_lsat-lr_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "nisi-sunt-lsat-lr/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "nisi-sunt_lsat-rc_base": { | |
| "task": "nisi-sunt_lsat-rc_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "nisi-sunt-lsat-rc/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "saepe-fuga_logiqa2_base": { | |
| "task": "saepe-fuga_logiqa2_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "saepe-fuga-logiqa2/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "saepe-fuga_logiqa_base": { | |
| "task": "saepe-fuga_logiqa_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "saepe-fuga-logiqa/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "saepe-fuga_lsat-ar_base": { | |
| "task": "saepe-fuga_lsat-ar_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "saepe-fuga-lsat-ar/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "saepe-fuga_lsat-lr_base": { | |
| "task": "saepe-fuga_lsat-lr_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "saepe-fuga-lsat-lr/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "saepe-fuga_lsat-rc_base": { | |
| "task": "saepe-fuga_lsat-rc_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "saepe-fuga-lsat-rc/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "veritatis-velit_logiqa2_base": { | |
| "task": "veritatis-velit_logiqa2_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "veritatis-velit-logiqa2/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "veritatis-velit_logiqa_base": { | |
| "task": "veritatis-velit_logiqa_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "veritatis-velit-logiqa/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "veritatis-velit_lsat-ar_base": { | |
| "task": "veritatis-velit_lsat-ar_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "veritatis-velit-lsat-ar/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "veritatis-velit_lsat-lr_base": { | |
| "task": "veritatis-velit_lsat-lr_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "veritatis-velit-lsat-lr/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| }, | |
| "veritatis-velit_lsat-rc_base": { | |
| "task": "veritatis-velit_lsat-rc_base", | |
| "group": "logikon-bench", | |
| "dataset_path": "logikon/cot-eval-traces", | |
| "dataset_kwargs": { | |
| "data_files": { | |
| "test": "veritatis-velit-lsat-rc/test-00000-of-00001.parquet" | |
| } | |
| }, | |
| "test_split": "test", | |
| "doc_to_text": "def doc_to_text(doc) -> str:\n \"\"\"\n Answer the following question about the given passage.\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 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.\\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 += \"Answer:\"\n return prompt\n", | |
| "doc_to_target": "{{answer}}", | |
| "doc_to_choice": "{{options}}", | |
| "description": "", | |
| "target_delimiter": " ", | |
| "fewshot_delimiter": "\n\n", | |
| "num_fewshot": 0, | |
| "metric_list": [ | |
| { | |
| "metric": "acc", | |
| "aggregation": "mean", | |
| "higher_is_better": true | |
| } | |
| ], | |
| "output_type": "multiple_choice", | |
| "repeats": 1, | |
| "should_decontaminate": false, | |
| "metadata": { | |
| "version": 0.0 | |
| } | |
| } | |
| }, | |
| "versions": { | |
| "eum-saepe_logiqa2_base": 0.0, | |
| "eum-saepe_logiqa_base": 0.0, | |
| "eum-saepe_lsat-ar_base": 0.0, | |
| "eum-saepe_lsat-lr_base": 0.0, | |
| "eum-saepe_lsat-rc_base": 0.0, | |
| "iste-molestias_logiqa2_base": 0.0, | |
| "iste-molestias_logiqa_base": 0.0, | |
| "iste-molestias_lsat-ar_base": 0.0, | |
| "iste-molestias_lsat-lr_base": 0.0, | |
| "iste-molestias_lsat-rc_base": 0.0, | |
| "laboriosam-molestiae_logiqa2_base": 0.0, | |
| "laboriosam-molestiae_logiqa_base": 0.0, | |
| "laboriosam-molestiae_lsat-ar_base": 0.0, | |
| "laboriosam-molestiae_lsat-lr_base": 0.0, | |
| "laboriosam-molestiae_lsat-rc_base": 0.0, | |
| "nisi-sunt_logiqa2_base": 0.0, | |
| "nisi-sunt_logiqa_base": 0.0, | |
| "nisi-sunt_lsat-ar_base": 0.0, | |
| "nisi-sunt_lsat-lr_base": 0.0, | |
| "nisi-sunt_lsat-rc_base": 0.0, | |
| "saepe-fuga_logiqa2_base": 0.0, | |
| "saepe-fuga_logiqa_base": 0.0, | |
| "saepe-fuga_lsat-ar_base": 0.0, | |
| "saepe-fuga_lsat-lr_base": 0.0, | |
| "saepe-fuga_lsat-rc_base": 0.0, | |
| "veritatis-velit_logiqa2_base": 0.0, | |
| "veritatis-velit_logiqa_base": 0.0, | |
| "veritatis-velit_lsat-ar_base": 0.0, | |
| "veritatis-velit_lsat-lr_base": 0.0, | |
| "veritatis-velit_lsat-rc_base": 0.0 | |
| }, | |
| "n-shot": { | |
| "eum-saepe_logiqa2_base": 0, | |
| "eum-saepe_logiqa_base": 0, | |
| "eum-saepe_lsat-ar_base": 0, | |
| "eum-saepe_lsat-lr_base": 0, | |
| "eum-saepe_lsat-rc_base": 0, | |
| "iste-molestias_logiqa2_base": 0, | |
| "iste-molestias_logiqa_base": 0, | |
| "iste-molestias_lsat-ar_base": 0, | |
| "iste-molestias_lsat-lr_base": 0, | |
| "iste-molestias_lsat-rc_base": 0, | |
| "laboriosam-molestiae_logiqa2_base": 0, | |
| "laboriosam-molestiae_logiqa_base": 0, | |
| "laboriosam-molestiae_lsat-ar_base": 0, | |
| "laboriosam-molestiae_lsat-lr_base": 0, | |
| "laboriosam-molestiae_lsat-rc_base": 0, | |
| "nisi-sunt_logiqa2_base": 0, | |
| "nisi-sunt_logiqa_base": 0, | |
| "nisi-sunt_lsat-ar_base": 0, | |
| "nisi-sunt_lsat-lr_base": 0, | |
| "nisi-sunt_lsat-rc_base": 0, | |
| "saepe-fuga_logiqa2_base": 0, | |
| "saepe-fuga_logiqa_base": 0, | |
| "saepe-fuga_lsat-ar_base": 0, | |
| "saepe-fuga_lsat-lr_base": 0, | |
| "saepe-fuga_lsat-rc_base": 0, | |
| "veritatis-velit_logiqa2_base": 0, | |
| "veritatis-velit_logiqa_base": 0, | |
| "veritatis-velit_lsat-ar_base": 0, | |
| "veritatis-velit_lsat-lr_base": 0, | |
| "veritatis-velit_lsat-rc_base": 0 | |
| }, | |
| "config": { | |
| "model": "vllm", | |
| "model_args": "pretrained=Deci/DeciLM-7B,revision=main,dtype=auto,tensor_parallel_size=1,gpu_memory_utilization=0.9,trust_remote_code=true,max_length=4096", | |
| "batch_size": "auto", | |
| "batch_sizes": [], | |
| "device": null, | |
| "use_cache": null, | |
| "limit": null, | |
| "bootstrap_iters": 100000, | |
| "gen_kwargs": null | |
| }, | |
| "git_hash": "5044cf9" | |
| } |