| { |
| "results": { |
| "unde-laudantium_lsat-rc_base": { |
| "acc,none": 0.30111524163568776, |
| "acc_stderr,none": 0.028022169587612226, |
| "alias": "unde-laudantium_lsat-rc_base" |
| }, |
| "unde-laudantium_lsat-lr_base": { |
| "acc,none": 0.23529411764705882, |
| "acc_stderr,none": 0.018801558887410304, |
| "alias": "unde-laudantium_lsat-lr_base" |
| }, |
| "unde-laudantium_lsat-ar_base": { |
| "acc,none": 0.20869565217391303, |
| "acc_stderr,none": 0.026854108265439675, |
| "alias": "unde-laudantium_lsat-ar_base" |
| }, |
| "unde-laudantium_logiqa_base": { |
| "acc,none": 0.26996805111821087, |
| "acc_stderr,none": 0.017757716181700637, |
| "alias": "unde-laudantium_logiqa_base" |
| }, |
| "unde-laudantium_logiqa2_base": { |
| "acc,none": 0.3256997455470738, |
| "acc_stderr,none": 0.011823533300939599, |
| "alias": "unde-laudantium_logiqa2_base" |
| }, |
| "temporibus-illo_lsat-rc_base": { |
| "acc,none": 0.26394052044609667, |
| "acc_stderr,none": 0.02692415564390256, |
| "alias": "temporibus-illo_lsat-rc_base" |
| }, |
| "temporibus-illo_lsat-lr_base": { |
| "acc,none": 0.21568627450980393, |
| "acc_stderr,none": 0.018230445049830818, |
| "alias": "temporibus-illo_lsat-lr_base" |
| }, |
| "temporibus-illo_lsat-ar_base": { |
| "acc,none": 0.1826086956521739, |
| "acc_stderr,none": 0.025530421952734174, |
| "alias": "temporibus-illo_lsat-ar_base" |
| }, |
| "temporibus-illo_logiqa_base": { |
| "acc,none": 0.26996805111821087, |
| "acc_stderr,none": 0.017757716181700637, |
| "alias": "temporibus-illo_logiqa_base" |
| }, |
| "temporibus-illo_logiqa2_base": { |
| "acc,none": 0.3187022900763359, |
| "acc_stderr,none": 0.011756362373408389, |
| "alias": "temporibus-illo_logiqa2_base" |
| }, |
| "quo-non_lsat-rc_base": { |
| "acc,none": 0.24907063197026022, |
| "acc_stderr,none": 0.02641760298057974, |
| "alias": "quo-non_lsat-rc_base" |
| }, |
| "quo-non_lsat-lr_base": { |
| "acc,none": 0.2411764705882353, |
| "acc_stderr,none": 0.018961774215004727, |
| "alias": "quo-non_lsat-lr_base" |
| }, |
| "quo-non_lsat-ar_base": { |
| "acc,none": 0.20434782608695654, |
| "acc_stderr,none": 0.026645808150011344, |
| "alias": "quo-non_lsat-ar_base" |
| }, |
| "quo-non_logiqa_base": { |
| "acc,none": 0.25878594249201275, |
| "acc_stderr,none": 0.01751871129783383, |
| "alias": "quo-non_logiqa_base" |
| }, |
| "quo-non_logiqa2_base": { |
| "acc,none": 0.30279898218829515, |
| "acc_stderr,none": 0.011592260158888737, |
| "alias": "quo-non_logiqa2_base" |
| }, |
| "magni-excepturi_lsat-rc_base": { |
| "acc,none": 0.26022304832713755, |
| "acc_stderr,none": 0.02680130130545777, |
| "alias": "magni-excepturi_lsat-rc_base" |
| }, |
| "magni-excepturi_lsat-lr_base": { |
| "acc,none": 0.22745098039215686, |
| "acc_stderr,none": 0.018580099622603333, |
| "alias": "magni-excepturi_lsat-lr_base" |
| }, |
| "magni-excepturi_lsat-ar_base": { |
| "acc,none": 0.17391304347826086, |
| "acc_stderr,none": 0.02504731738604972, |
| "alias": "magni-excepturi_lsat-ar_base" |
| }, |
| "magni-excepturi_logiqa_base": { |
| "acc,none": 0.25878594249201275, |
| "acc_stderr,none": 0.01751871129783383, |
| "alias": "magni-excepturi_logiqa_base" |
| }, |
| "magni-excepturi_logiqa2_base": { |
| "acc,none": 0.30725190839694655, |
| "acc_stderr,none": 0.011639836259579924, |
| "alias": "magni-excepturi_logiqa2_base" |
| }, |
| "laboriosam-numquam_lsat-rc_base": { |
| "acc,none": 0.27137546468401486, |
| "acc_stderr,none": 0.027162503089239523, |
| "alias": "laboriosam-numquam_lsat-rc_base" |
| }, |
| "laboriosam-numquam_lsat-lr_base": { |
| "acc,none": 0.21372549019607842, |
| "acc_stderr,none": 0.01817006027631824, |
| "alias": "laboriosam-numquam_lsat-lr_base" |
| }, |
| "laboriosam-numquam_lsat-ar_base": { |
| "acc,none": 0.21304347826086956, |
| "acc_stderr,none": 0.027057754389936177, |
| "alias": "laboriosam-numquam_lsat-ar_base" |
| }, |
| "laboriosam-numquam_logiqa_base": { |
| "acc,none": 0.25559105431309903, |
| "acc_stderr,none": 0.01744771697469749, |
| "alias": "laboriosam-numquam_logiqa_base" |
| }, |
| "laboriosam-numquam_logiqa2_base": { |
| "acc,none": 0.30725190839694655, |
| "acc_stderr,none": 0.011639836259579922, |
| "alias": "laboriosam-numquam_logiqa2_base" |
| }, |
| "dolore-possimus_lsat-rc_base": { |
| "acc,none": 0.2862453531598513, |
| "acc_stderr,none": 0.027610628966374826, |
| "alias": "dolore-possimus_lsat-rc_base" |
| }, |
| "dolore-possimus_lsat-lr_base": { |
| "acc,none": 0.2196078431372549, |
| "acc_stderr,none": 0.01834938361142324, |
| "alias": "dolore-possimus_lsat-lr_base" |
| }, |
| "dolore-possimus_lsat-ar_base": { |
| "acc,none": 0.2217391304347826, |
| "acc_stderr,none": 0.027451496604058916, |
| "alias": "dolore-possimus_lsat-ar_base" |
| }, |
| "dolore-possimus_logiqa_base": { |
| "acc,none": 0.2763578274760383, |
| "acc_stderr,none": 0.01788783625456192, |
| "alias": "dolore-possimus_logiqa_base" |
| }, |
| "dolore-possimus_logiqa2_base": { |
| "acc,none": 0.2989821882951654, |
| "acc_stderr,none": 0.011550454987784068, |
| "alias": "dolore-possimus_logiqa2_base" |
| } |
| }, |
| "configs": { |
| "dolore-possimus_logiqa2_base": { |
| "task": "dolore-possimus_logiqa2_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "dolore-possimus-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 |
| } |
| }, |
| "dolore-possimus_logiqa_base": { |
| "task": "dolore-possimus_logiqa_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "dolore-possimus-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 |
| } |
| }, |
| "dolore-possimus_lsat-ar_base": { |
| "task": "dolore-possimus_lsat-ar_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "dolore-possimus-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 |
| } |
| }, |
| "dolore-possimus_lsat-lr_base": { |
| "task": "dolore-possimus_lsat-lr_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "dolore-possimus-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 |
| } |
| }, |
| "dolore-possimus_lsat-rc_base": { |
| "task": "dolore-possimus_lsat-rc_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "dolore-possimus-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-numquam_logiqa2_base": { |
| "task": "laboriosam-numquam_logiqa2_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "laboriosam-numquam-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-numquam_logiqa_base": { |
| "task": "laboriosam-numquam_logiqa_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "laboriosam-numquam-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-numquam_lsat-ar_base": { |
| "task": "laboriosam-numquam_lsat-ar_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "laboriosam-numquam-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-numquam_lsat-lr_base": { |
| "task": "laboriosam-numquam_lsat-lr_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "laboriosam-numquam-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-numquam_lsat-rc_base": { |
| "task": "laboriosam-numquam_lsat-rc_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "laboriosam-numquam-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 |
| } |
| }, |
| "magni-excepturi_logiqa2_base": { |
| "task": "magni-excepturi_logiqa2_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "magni-excepturi-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 |
| } |
| }, |
| "magni-excepturi_logiqa_base": { |
| "task": "magni-excepturi_logiqa_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "magni-excepturi-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 |
| } |
| }, |
| "magni-excepturi_lsat-ar_base": { |
| "task": "magni-excepturi_lsat-ar_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "magni-excepturi-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 |
| } |
| }, |
| "magni-excepturi_lsat-lr_base": { |
| "task": "magni-excepturi_lsat-lr_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "magni-excepturi-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 |
| } |
| }, |
| "magni-excepturi_lsat-rc_base": { |
| "task": "magni-excepturi_lsat-rc_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "magni-excepturi-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 |
| } |
| }, |
| "quo-non_logiqa2_base": { |
| "task": "quo-non_logiqa2_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "quo-non-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 |
| } |
| }, |
| "quo-non_logiqa_base": { |
| "task": "quo-non_logiqa_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "quo-non-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 |
| } |
| }, |
| "quo-non_lsat-ar_base": { |
| "task": "quo-non_lsat-ar_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "quo-non-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 |
| } |
| }, |
| "quo-non_lsat-lr_base": { |
| "task": "quo-non_lsat-lr_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "quo-non-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 |
| } |
| }, |
| "quo-non_lsat-rc_base": { |
| "task": "quo-non_lsat-rc_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "quo-non-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 |
| } |
| }, |
| "temporibus-illo_logiqa2_base": { |
| "task": "temporibus-illo_logiqa2_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "temporibus-illo-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 |
| } |
| }, |
| "temporibus-illo_logiqa_base": { |
| "task": "temporibus-illo_logiqa_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "temporibus-illo-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 |
| } |
| }, |
| "temporibus-illo_lsat-ar_base": { |
| "task": "temporibus-illo_lsat-ar_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "temporibus-illo-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 |
| } |
| }, |
| "temporibus-illo_lsat-lr_base": { |
| "task": "temporibus-illo_lsat-lr_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "temporibus-illo-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 |
| } |
| }, |
| "temporibus-illo_lsat-rc_base": { |
| "task": "temporibus-illo_lsat-rc_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "temporibus-illo-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 |
| } |
| }, |
| "unde-laudantium_logiqa2_base": { |
| "task": "unde-laudantium_logiqa2_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "unde-laudantium-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 |
| } |
| }, |
| "unde-laudantium_logiqa_base": { |
| "task": "unde-laudantium_logiqa_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "unde-laudantium-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 |
| } |
| }, |
| "unde-laudantium_lsat-ar_base": { |
| "task": "unde-laudantium_lsat-ar_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "unde-laudantium-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 |
| } |
| }, |
| "unde-laudantium_lsat-lr_base": { |
| "task": "unde-laudantium_lsat-lr_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "unde-laudantium-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 |
| } |
| }, |
| "unde-laudantium_lsat-rc_base": { |
| "task": "unde-laudantium_lsat-rc_base", |
| "group": "logikon-bench", |
| "dataset_path": "logikon/cot-eval-traces", |
| "dataset_kwargs": { |
| "data_files": { |
| "test": "unde-laudantium-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": { |
| "dolore-possimus_logiqa2_base": 0.0, |
| "dolore-possimus_logiqa_base": 0.0, |
| "dolore-possimus_lsat-ar_base": 0.0, |
| "dolore-possimus_lsat-lr_base": 0.0, |
| "dolore-possimus_lsat-rc_base": 0.0, |
| "laboriosam-numquam_logiqa2_base": 0.0, |
| "laboriosam-numquam_logiqa_base": 0.0, |
| "laboriosam-numquam_lsat-ar_base": 0.0, |
| "laboriosam-numquam_lsat-lr_base": 0.0, |
| "laboriosam-numquam_lsat-rc_base": 0.0, |
| "magni-excepturi_logiqa2_base": 0.0, |
| "magni-excepturi_logiqa_base": 0.0, |
| "magni-excepturi_lsat-ar_base": 0.0, |
| "magni-excepturi_lsat-lr_base": 0.0, |
| "magni-excepturi_lsat-rc_base": 0.0, |
| "quo-non_logiqa2_base": 0.0, |
| "quo-non_logiqa_base": 0.0, |
| "quo-non_lsat-ar_base": 0.0, |
| "quo-non_lsat-lr_base": 0.0, |
| "quo-non_lsat-rc_base": 0.0, |
| "temporibus-illo_logiqa2_base": 0.0, |
| "temporibus-illo_logiqa_base": 0.0, |
| "temporibus-illo_lsat-ar_base": 0.0, |
| "temporibus-illo_lsat-lr_base": 0.0, |
| "temporibus-illo_lsat-rc_base": 0.0, |
| "unde-laudantium_logiqa2_base": 0.0, |
| "unde-laudantium_logiqa_base": 0.0, |
| "unde-laudantium_lsat-ar_base": 0.0, |
| "unde-laudantium_lsat-lr_base": 0.0, |
| "unde-laudantium_lsat-rc_base": 0.0 |
| }, |
| "n-shot": { |
| "dolore-possimus_logiqa2_base": 0, |
| "dolore-possimus_logiqa_base": 0, |
| "dolore-possimus_lsat-ar_base": 0, |
| "dolore-possimus_lsat-lr_base": 0, |
| "dolore-possimus_lsat-rc_base": 0, |
| "laboriosam-numquam_logiqa2_base": 0, |
| "laboriosam-numquam_logiqa_base": 0, |
| "laboriosam-numquam_lsat-ar_base": 0, |
| "laboriosam-numquam_lsat-lr_base": 0, |
| "laboriosam-numquam_lsat-rc_base": 0, |
| "magni-excepturi_logiqa2_base": 0, |
| "magni-excepturi_logiqa_base": 0, |
| "magni-excepturi_lsat-ar_base": 0, |
| "magni-excepturi_lsat-lr_base": 0, |
| "magni-excepturi_lsat-rc_base": 0, |
| "quo-non_logiqa2_base": 0, |
| "quo-non_logiqa_base": 0, |
| "quo-non_lsat-ar_base": 0, |
| "quo-non_lsat-lr_base": 0, |
| "quo-non_lsat-rc_base": 0, |
| "temporibus-illo_logiqa2_base": 0, |
| "temporibus-illo_logiqa_base": 0, |
| "temporibus-illo_lsat-ar_base": 0, |
| "temporibus-illo_lsat-lr_base": 0, |
| "temporibus-illo_lsat-rc_base": 0, |
| "unde-laudantium_logiqa2_base": 0, |
| "unde-laudantium_logiqa_base": 0, |
| "unde-laudantium_lsat-ar_base": 0, |
| "unde-laudantium_lsat-lr_base": 0, |
| "unde-laudantium_lsat-rc_base": 0 |
| }, |
| "config": { |
| "model": "vllm", |
| "model_args": "pretrained=mistralai/Mistral-7B-v0.1,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" |
| } |
