data/OpenBuddy/openbuddy-mistral2-7b-v20.2-32k/orig/results_24-04-08-13:02:28.json

{
  "results": {
    "logiqa2_base": {
      "acc,none": 0.2436386768447837,
      "acc_stderr,none": 0.010830529261905954,
      "alias": "logiqa2_base"
    },
    "logiqa_base": {
      "acc,none": 0.26198083067092653,
      "acc_stderr,none": 0.017588490556356362,
      "alias": "logiqa_base"
    },
    "lsat-ar_base": {
      "acc,none": 0.2,
      "acc_stderr,none": 0.026432744018203547,
      "alias": "lsat-ar_base"
    },
    "lsat-lr_base": {
      "acc,none": 0.17450980392156862,
      "acc_stderr,none": 0.016823137090491495,
      "alias": "lsat-lr_base"
    },
    "lsat-rc_base": {
      "acc,none": 0.2342007434944238,
      "acc_stderr,none": 0.02586927204182962,
      "alias": "lsat-rc_base"
    }
  },
  "configs": {
    "logiqa2_base": {
      "task": "logiqa2_base",
      "group": "logikon-bench",
      "dataset_path": "logikon/logikon-bench",
      "dataset_name": "logiqa2",
      "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
      }
    },
    "logiqa_base": {
      "task": "logiqa_base",
      "group": "logikon-bench",
      "dataset_path": "logikon/logikon-bench",
      "dataset_name": "logiqa",
      "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
      }
    },
    "lsat-ar_base": {
      "task": "lsat-ar_base",
      "group": "logikon-bench",
      "dataset_path": "logikon/logikon-bench",
      "dataset_name": "lsat-ar",
      "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
      }
    },
    "lsat-lr_base": {
      "task": "lsat-lr_base",
      "group": "logikon-bench",
      "dataset_path": "logikon/logikon-bench",
      "dataset_name": "lsat-lr",
      "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
      }
    },
    "lsat-rc_base": {
      "task": "lsat-rc_base",
      "group": "logikon-bench",
      "dataset_path": "logikon/logikon-bench",
      "dataset_name": "lsat-rc",
      "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": {
    "logiqa2_base": 0.0,
    "logiqa_base": 0.0,
    "lsat-ar_base": 0.0,
    "lsat-lr_base": 0.0,
    "lsat-rc_base": 0.0
  },
  "n-shot": {
    "logiqa2_base": 0,
    "logiqa_base": 0,
    "lsat-ar_base": 0,
    "lsat-lr_base": 0,
    "lsat-rc_base": 0
  },
  "config": {
    "model": "vllm",
    "model_args": "pretrained=OpenBuddy/openbuddy-mistral2-7b-v20.2-32k,revision=main,dtype=bfloat16,tensor_parallel_size=1,gpu_memory_utilization=0.8,trust_remote_code=true,max_length=2048",
    "batch_size": "auto",
    "batch_sizes": [],
    "device": null,
    "use_cache": null,
    "limit": null,
    "bootstrap_iters": 100000,
    "gen_kwargs": null
  },
  "git_hash": "741db1c"
}