lm-eval-output/SmerkyG/rwkv6-world-1b6/medqa_4options/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json

{
  "results": {
    "medqa_4options": {
      "acc,none": 0.24901806755695208,
      "acc_stderr,none": 0.012125135984037815,
      "acc_norm,none": 0.24901806755695208,
      "acc_norm_stderr,none": 0.012125135984037815,
      "alias": "medqa_4options"
    }
  },
  "configs": {
    "medqa_4options": {
      "task": "medqa_4options",
      "dataset_path": "GBaker/MedQA-USMLE-4-options-hf",
      "training_split": "train",
      "validation_split": "validation",
      "test_split": "test",
      "doc_to_text": "def doc_to_text(doc) -> str:\n    option_choices = {'A': doc[\"ending0\"], 'B': doc[\"ending1\"], 'C': doc[\"ending2\"], 'D': doc[\"ending3\"]}\n    answers = \"\".join((f\"{k}. {v}\\n\") for k, v in option_choices.items())\n    return f\"Question: {doc['sent1']}\\n{answers}Answer:\"\n",
      "doc_to_target": "def doc_to_target(doc) -> int:\n    return doc[\"label\"]\n",
      "doc_to_choice": [
        "A",
        "B",
        "C",
        "D"
      ],
      "description": "",
      "target_delimiter": " ",
      "fewshot_delimiter": "\n\n",
      "metric_list": [
        {
          "metric": "acc",
          "aggregation": "mean",
          "higher_is_better": true
        },
        {
          "metric": "acc_norm",
          "aggregation": "mean",
          "higher_is_better": true
        }
      ],
      "output_type": "multiple_choice",
      "repeats": 1,
      "should_decontaminate": false
    }
  },
  "versions": {
    "medqa_4options": "Yaml"
  },
  "n-shot": {
    "medqa_4options": 0
  },
  "config": {
    "model": "hf",
    "model_args": "pretrained=SmerkyG/rwkv6-world-1b6,dtype=bfloat16,trust_remote_code=True",
    "batch_size": "auto",
    "batch_sizes": [
      32
    ],
    "device": null,
    "use_cache": null,
    "limit": null,
    "bootstrap_iters": 100000,
    "gen_kwargs": null
  },
  "git_hash": "bff08d1"
}