54 lines
1.6 KiB
Markdown
54 lines
1.6 KiB
Markdown
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---
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license: apache-2.0
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tags:
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- unsloth
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- trl
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- sft
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datasets:
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- suayptalha/Treatment-Instructions
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language:
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- en
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base_model:
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- Qwen/Qwen3-0.6B
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pipeline_tag: text-generation
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library_name: transformers
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---
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# Qwen3-0.6B-Treatment-Expert
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This project performs full fine-tuning on the **Qwen3-0.6B** language model to enhance its clinical treatment planning and reasoning capabilities. The model was optimized using the bfloat16 (bf16) data type.
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## Training Procedure
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1. **Dataset Preparation**
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* Dataset: Containing paired clinical diagnosis descriptions and corresponding step-by-step treatment plans.
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2. **Model Loading and Configuration**
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* Base model: **Qwen3-0.6B**, loaded with the `unsloth` library in bf16 precision.
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* Full fine-tuning (`full_finetuning=True`) applied to all layers to adapt the model for medical treatment tasks.
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3. **Supervised Fine-Tuning (SFT)**
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* Utilized the Hugging Face TRL library with the Supervised Fine-Tuning approach.
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* The model was trained to generate both intermediate reasoning steps and final treatment recommendations.
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* Training hyperparameters:
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* Epochs: 2
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* Learning rate: 2e-5
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* Batch size: 8
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## Purpose and Outcome
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* Significantly improved the model’s ability to interpret clinical diagnoses and propose structured treatment plans.
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## Evaluation
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* Performance was measured on a held-out validation set with the following metrics:
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* **Plan Fidelity:** 59.69% similarity with DeepSeek V3-0324.
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* **Reasoning Coherence:** Rated high by a panel of medical experts.
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## License
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This project is licensed under the Apache License 2.0. See the [LICENSE](./LICENSE) file for details.
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