dousery

This is a fine-tuned version of openai/gpt-oss-20b specifically optimized for medical reasoning and clinical decision-making. The model has been trained on high-quality medical reasoning datasets to provide accurate and thoughtful responses to medical queries. - Medical Expertise: Specialized in medical reasoning, diagnosis, and clinical decision-making - Complex Reasoning: Uses chain-of-thought reasoning for medical problems - Adapter-Only Training: Only LoRA layers are trained, base model remains frozen - Efficient: Lightweight fine-tuning, smaller storage footprint - Ready-to-Use: Requires base model + adapter for inference Training Data - Dataset: Freedomintelligence/medical-o1-reasoning-SFT - Language: English - Size: 19,704 medical reasoning examples - Format: Question-Answer pairs with complex chain-of-thought reasoning Training Configuration - Base Model: unsloth/gpt-oss-20b (20B parameters) - Training Method: LoRA (adapter-only fine-tuning) - LoRA Rank: 8 - Learning Rate: 5e-5 - Batch Size: 4 per device, gradientaccumulationsteps=4 - Epochs: 2 - Max Sequence Length: 2048 - LR Scheduler: Cosine, warmupratio=0.05 - Final Training Loss: 1.22 Model Architecture - Parameters: 20.9 billion - Architecture: GPT-OSS (Transformer-based) - Context Length: 2.048 tokens - Trainable Parameters: 3.98M (0.02% of total) Primary Use Cases - Medical Education: Explaining medical concepts and procedures - Clinical Reasoning: Analyzing symptoms and differential diagnosis - Research Support: Assisting in medical research and literature review - Decision Support: Providing reasoning for clinical decisions (with human oversight) - Not a Medical Device: This model is for educational and research purposes only - Human Oversight Required: All medical decisions should involve qualified healthcare professionals - Accuracy Not Guaranteed: Model outputs should be verified against current medical literature - Regional Variations: Training data may not reflect all regional medical practices The model demonstrates strong performance in: - Medical concept explanation - Differential diagnosis reasoning - Treatment option analysis - Pathophysiology understanding Note: Comprehensive clinical evaluation is ongoing. Always validate outputs with current medical guidelines. Minimum Requirements - GPU Memory: 16GB+ VRAM recommended - RAM: 32GB+ system memory - Storage: 40GB+ free space This model is released under the Apache 2.0 license. Please review the license terms before commercial use. - Base Model: openai/gpt-oss-20b - Adapter/Training: [dousery/medical-reasoning-gpt-oss-20b]() - Dataset: Freedomintelligence - Infrastructure: Modal Labs for GPU compute For questions, issues, or collaboration opportunities, please reach out through the HuggingFace community discussions or my Linkedin account : Linkedin