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Chens7/Qwen2.5-7B-ReasonMed-response-123k
Qwen2.5-7B-ReasonMed-response-123k is a text generation model from Chens7. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
Full fine-tune of Qwen/Qwen2.5-7B on the ResponseMed variant of ReasonMed — direct answers without chain-of-thought reasoning. 123K samples (1/3 of full dataset) × 3 epochs.
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From the Hugging Face model README
Full fine-tune of Qwen/Qwen2.5-7B on the ResponseMed variant of ReasonMed — direct answers without chain-of-thought reasoning. 123K samples (1/3 of full dataset) × 3 epochs.
Training code: https://github.com/Chen-Jie7/NLP_project
lingshu-medical-mllm/ReasonMed — ResponseMed.json variant. Outputs are direct answers only.
All three models trained with identical hyperparameters on 123K samples. Evaluated via loglikelihood MCQ scoring.
| Variant | Output format | Total acc |
|---|---|---|
| reason | <think>CoT</think>Response | 65.8 |
| cot | CoT without tags | 65.0 |
| response (this model) | Direct answer only | 63.8 |
| Benchmark | Ours (123K) | Paper (370K) |
|---|---|---|
| MedQA | 60.7 | 66.9 |
| MedMCQA (val) | 60.0 | 65.1 |
| PubMedQA | 72.3 | 82.0 |
| MMLU-Anatomy | 72.6 | 75.6 |
| MMLU-Clinical-Knowledge | 73.6 | 79.3 |
| MMLU-College-Biology | 80.6 | 79.2 |
| MMLU-College-Medicine | 67.6 | 73.4 |
| MMLU-Medical-Genetics | 80.0 | 85.0 |
| MMLU-Professional-Medicine | 74.6 | 80.9 |
| Total | 63.8 | 69.6 |