| --- |
| language: |
| - en |
| license: apache-2.0 |
| pretty_name: MedMCQA |
| size_categories: |
| - 10K<n<100K |
| source_datasets: |
| - openlifescienceai/medmcqa |
| task_categories: |
| - question-answering |
| - multiple-choice |
| tags: |
| - medical |
| - medmcqa |
| dataset_info: |
| - config_name: sft |
| features: |
| - name: prompt |
| dtype: string |
| - name: answer |
| dtype: string |
| splits: |
| - name: train |
| num_examples: 20000 |
| - name: validation |
| num_examples: 200 |
| - config_name: train |
| splits: |
| - name: train |
| num_examples: 20000 |
| - config_name: validation |
| splits: |
| - name: validation |
| num_examples: 200 |
| - config_name: mia_members |
| splits: |
| - name: train |
| num_examples: 2000 |
| - config_name: mia_nonmembers |
| splits: |
| - name: train |
| num_examples: 2000 |
| - config_name: filtered |
| splits: |
| - name: train |
| num_examples: 84403 |
| configs: |
| - config_name: sft |
| data_files: |
| - split: train |
| path: sft/sft_train_20000.jsonl |
| - split: validation |
| path: sft/sft_validation_200.jsonl |
| - config_name: train |
| data_files: |
| - split: train |
| path: train_20000.jsonl |
| - config_name: validation |
| data_files: |
| - split: validation |
| path: validation_200.jsonl |
| - config_name: mia_members |
| data_files: |
| - split: train |
| path: mia_members_2000.jsonl |
| - config_name: mia_nonmembers |
| data_files: |
| - split: train |
| path: mia_nonmembers_2000.jsonl |
| - config_name: filtered |
| data_files: |
| - split: train |
| path: medmcqa_filtered.parquet |
| --- |
| |
| # MedMCQA |
|
|
| 由 [openlifescienceai/medmcqa](https://huggingface.co/datasets/openlifescienceai/medmcqa) 的 train split 清洗、去重后划分得到。上游许可证为 Apache-2.0。 |
|
|
| 默认配置 `sft` 可直接用于监督微调。`answer` 是完整解答加正确选项字母，不是单独的选项标签。 |
|
|
| ```python |
| from datasets import load_dataset |
| |
| sft = load_dataset("HaolinRPI/medmcqa", "sft") |
| train = load_dataset("HaolinRPI/medmcqa", "train", split="train") |
| validation = load_dataset("HaolinRPI/medmcqa", "validation", split="validation") |
| members = load_dataset("HaolinRPI/medmcqa", "mia_members", split="train") |
| nonmembers = load_dataset("HaolinRPI/medmcqa", "mia_nonmembers", split="train") |
| filtered = load_dataset("HaolinRPI/medmcqa", "filtered", split="train") |
| ``` |
|
|
| ## 划分 |
|
|
| Training、MIA Non-member 和 Validation 的规范化 Question 互不重叠。MIA Member 是 Training 的子集。随机种子是 42。完整统计见 `split_manifest.json`。 |
|
|
| | 文件 | 条数 | 用途 | |
| |---|---:|---| |
| | `sft/sft_train_20000.jsonl` | 20,000 | SFT 训练集，只含 `prompt` 和 `answer` | |
| | `sft/sft_validation_200.jsonl` | 200 | SFT 验证集，只含 `prompt` 和 `answer` | |
| | `train_20000.jsonl` | 20,000 | 训练样本，保留原始字段 | |
| | `mia_members_2000.jsonl` | 2,000 | Training 内部的 MIA Member | |
| | `mia_nonmembers_2000.jsonl` | 2,000 | 不参与训练的 MIA Non-member | |
| | `validation_200.jsonl` | 200 | 独立验证样本 | |
| | `medmcqa_filtered.parquet` | 84,403 | 全部合格记录，含未使用样本 | |
|
|
| ## SFT 文本 |
|
|
| `prompt` 由题干、A–D 选项和指令 “Answer with the letter of the correct option.” 组成。`answer` 由解释和正确选项字母组成，字母单独占最后一行。 |
|
|
