Update README.md

README.md

@@ -220,22 +220,6 @@ for i, (obj_pred, obj_conf, mat_pred, mat_conf) in enumerate(zip(preds_obj, conf
     print(f"  Material: {mat_name} ({mat_conf:.3f})")
 ```
 
-### Custom Dataset Evaluation
-
-```python
-from datasets import load_dataset
-from main import load_model
-import json
-
-# Load your custom dataset
-dataset = load_dataset("your-dataset", split="test")
-
-# Load model
-model, label_mappings = load_model("model/v2/best_model.pth")
-
-# Run evaluation (modify main.py evaluation logic as needed)
-# ... evaluation code ...
-```
 
 ## Troubleshooting
 
@@ -261,7 +245,6 @@ model, label_mappings = load_model("model/v2/best_model.pth")
 
 - Use GPU for faster inference
 - Process images in batches for efficiency
-- Use the best_model.pth for production use
 - Consider model quantization for deployment
 
 ## Model Limitations
@@ -270,15 +253,3 @@ model, label_mappings = load_model("model/v2/best_model.pth")
 - May not generalize well to artifacts from other cultures/regions
 - Performance depends on image quality and lighting
 - Multi-output nature may have trade-offs between object and material accuracy
-
-## Contributing
-
-To improve the model:
-1. Use the training script with different hyperparameters
-2. Experiment with different backbones
-3. Add more advanced augmentations
-4. Fine-tune on additional datasets
-
-## License
-
-This model is part of the artifact identification project. Check the main project license for usage terms.