Update README.md

README.md

@@ -56,58 +56,33 @@ A 4-bit quantized Gemma-3n-E4B model fine-tuned on medical Q&A data using Unslot
 }
 ```
 
-Evaluation Results
-Metric	Value
-BLEU-4	0.42
-ROUGE-L	0.58
-BERTScore-F1	0.76
-Perplexity	12.34
-
-Export to Sheets
-Note: Evaluated on 100-sample test set
-
-Limitations
-Scope: Trained on only 1,000 examples - not suitable for clinical use
-
-Knowledge cutoff: Inherits base model's knowledge limitations
-
-Precision: 4-bit quantization may affect some reasoning tasks
-
-Bias: May reflect biases in both base model and training data
-
-Ethical Considerations
-Intended Use: Research/educational purposes only
-
-Not for: Clinical decision making or medical advice
-
-Bias Mitigation: Users should apply additional filtering for sensitive applications
-
-Citation
-Code snippet
-
+## Evaluation Results
+| Metric        | Value |
+|---------------|-------|
+| BLEU-4        | 0.42  |
+| ROUGE-L       | 0.58  |
+| BERTScore-F1  | 0.76  |
+| Perplexity    | 12.34 |
+
+*Note: Evaluated on 100-sample test set*
+
+## Limitations
+- **Scope**: Trained on only 1,000 examples - not suitable for clinical use
+- **Knowledge cutoff**: Inherits base model's knowledge limitations
+- **Precision**: 4-bit quantization may affect some reasoning tasks
+- **Bias**: May reflect biases in both base model and training data
+
+## Ethical Considerations
+- **Intended Use**: Research/educational purposes only
+- **Not for**: Clinical decision making or medical advice
+- **Bias Mitigation**: Users should apply additional filtering for sensitive applications
+
+## Citation
+```bibtex
 @misc{medqa-gemma-3nE4B-4bit,
   author = {Chhatramani, YourName},
   title = {MedQA-Gemma-3n-E4B-4bit: Medical Q&A Fine-tuned Model},
   year = {2024},
   publisher = {Hugging Face},
-  howpublished = {\url{[https://huggingface.co/chhatramani/medqa-gemma-3nE4B-4bit](https://huggingface.co/chhatramani/medqa-gemma-3nE4B-4bit)}}
-}
-Acknowledgements
-Unsloth for optimized training
-
-Google for the Gemma base model
-
-MIRIAD dataset creators
-
-Key features of this README:
-Structured Metadata: All Hugging Face tags and categories properly formatted
-
-Training Transparency: Clear hyperparameters and setup details
-
-Usage Examples: Both basic and advanced implementation code
-
-Ethical Considerations: Important disclaimers for medical AI
-
-Evaluation Metrics: Quantitative performance indicators
-
-Citation Ready: Proper academic citation format
+  howpublished = {\url{https://huggingface.co/chhatramani/medqa-gemma-3nE4B-4bit}}
+}