MedInjection-FR
/

QWEN-4B-NAT-SYN

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 ---
 library_name: transformers
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 ---
 library_name: transformers
+tags:
+- medical
+license: mit
+datasets:
+- MedInjection-FR/Native
+- MedInjection-FR/Translated
+language:
+- fr
+- en
+base_model:
+- Qwen/Qwen3-4B-Instruct-2507
 ---
+# 🩺 QWEN-4B-NAT-SYN
+**QWEN-4B-NAT-SYN** is a fine-tuned version of **Qwen-4B-Instruct** trained on the [MedInjection-FR](https://huggingface.co/MedInjection-FR) dataset, a French biomedical instruction corpus combining *native, synthetic, and translated* medical question–answer pairs.
+This model was fine-tuned using **Supervised Fine-Tuning (SFT)** with **DoRA adapters**, designed to study how the origin of supervision data influences model adaptation.
+---
+## 🧠 Model overview
+| Property | Description |
+|-----------|--------------|
+| **Base model** | Qwen3-4B-Instruct-2507 |
+| **Fine-tuning method** | DoRA (Weight-Decomposed Low-Rank Adaptation) |
+| **Architecture size** | ~4B parameters |
+| **Language** | French 🇫🇷 |
+| **Domain** | Biomedical, Clinical, Health |
+| **Intended use** | Research on instruction tuning and domain adaptation |
+| **Caution** | Not for clinical or diagnostic use |
+---
+## ⚙️ Training setup
+Fine-tuning was performed on **30k multiple-choice (MCQ and MCQU)** examples for each configuration, using:
+- 10 epochs
+- Batch size: 12
+- Learning rate: 1e-4
+- Gradient accumulation: 8
+- Cosine scheduler with 5% warmup
+- LoRA rank: 16, α = 16, dropout = 0.05
+- Adapters applied to: `q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj`
+All runs used identical hyperparameters to isolate the effect of **data provenance**.
+---
+## 📊 Evaluation summary
+Evaluation was conducted on French biomedical benchmarks (MCQ, MCQU, OEQ).
+Metrics include **Exact Match (EM)** and **Hamming Score** for multiple-choice tasks, and **BLEU/ROUGE/BERTScore + LLM-as-a-judge** for open-ended QA.
+> See [MedInjection-FR GitHub](https://github.com/yourusername/MedInjection-FR) for full results and plots.
+## 📚 Citation
+If you use this model, please cite:
+```bibtex
+```