Upload results for model mistralai/Mistral-7B-v0.1 (#2)

- Upload results for model mistralai/Mistral-7B-v0.1 (da38201918a6e2c8ee8ce8008e75edba78de5c97)

data/mistralai/Mistral-7B-v0.1/base/24-02-02-23:43:14.json

@@ -0,0 +1,1162 @@
+{
+  "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"
+}