Update README.md

README.md

@@ -23,7 +23,57 @@ The Phi-4 Medical QA Model is a fine-tuned version of the "unsloth/phi-4" langua
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+Model Description
+
+The Phi-4 Medical QA Model builds upon the robust foundation provided by the "unsloth/phi-4" pre-trained language model. Fine-tuned on the PubMedQA dataset, it is specifically designed to answer complex medical questions by integrating domain-specific knowledge and language understanding capabilities.
+
+The model employs several advanced techniques:
+
+LoRA Fine-Tuning: Low-Rank Adaptation (LoRA) enhances parameter efficiency, allowing domain adaptation with minimal compute.
+
+4-Bit Quantization: Memory usage is significantly reduced, making the model deployable on resource-constrained systems.
+
+Cyclic Attention and Gradient Checkpointing: Further optimizations for handling long sequences and reducing GPU memory usage.
+
+The model is trained using the SFTTrainer library from the trl package, with parameters optimized for accuracy and resource efficiency.
+
+Model Architecture
+
+Base Model: "unsloth/phi-4"
+
+Tokenization: Custom tokenizer from the unsloth framework
+
+Fine-Tuning Techniques:
+
+Targeted modules: q_proj, k_proj, v_proj, and others
+
+LoRA Rank: 16
+
+LoRA Alpha: 16
+
+Dropout: 0 (optimized for this use case)
+
+Training Dataset: PubMedQA (labeled fold0 source)
+
+Hardware Used: NVIDIA A100 GPUs
+
+Intended Use
+
+This model is intended for:
+
+Answering medical and healthcare-related questions.
+
+Supporting healthcare professionals and students with evidence-based insights.
+
+Enhancing patient care via interactive QA systems.
+
+Limitations
+
+Domain Restriction: The model performs best on medical questions and may not generalize well to other domains.
+
+Bias and Fairness: The model inherits biases from the PubMedQA dataset.
+
+Hallucination Risks: As with all large language models, responses should be validated by professionals before application in critical scenarios.
 
 
 ## How to Use