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README.md

@@ -1,27 +1,78 @@
 ---
-    license: apache-2.0
-    tags:
-      - computer-vision
-      - image-classification
-      - food101
-      - cnn-vit
-    ---
-
-    # Hybrid Food Image Classifier (CNN + DeiT)
-
-    This model combines ResNet50 (CNN) and DeiT-Base (ViT) with an adaptive fusion head.
-
-    ## Files
-    - best_model.pth: Trained PyTorch checkpoint
-    - real_class_mapping.json: Human-readable class names
-    - config.yaml: Project configuration
-    - food101_class_names.json: Original class names
-
-    ## Quick Usage
-    ```python
-    from huggingface_hub import hf_hub_download
-    ckpt = hf_hub_download(repo_id="codealchemist01/food-image-classifier-hybrid", filename="best_model.pth")
-    ```
-
-    ## Notes
-    Validation accuracy plateaued around ~82.5%. Use best_model for inference.
+license: apache-2.0
+tags:
+  - computer-vision
+  - image-classification
+  - food101
+  - cnn-vit
+  - hybrid
+datasets:
+  - food101
+metrics:
+  - accuracy
+library_name: pytorch
+---
+
+# 🍕 Hybrid Food Image Classifier (CNN + ViT)
+
+This model combines ResNet50 (CNN) and DeiT-Base (ViT) with an adaptive fusion module for state-of-the-art food image classification.
+
+## Model Architecture
+
+- **CNN Branch**: ResNet50 (pretrained on ImageNet)
+- **ViT Branch**: DeiT-Base Distilled (pretrained)
+- **Fusion Module**: Adaptive attention-based fusion with multi-head cross-attention
+- **Classes**: 101 food categories from Food-101 dataset
+
+## Performance
+
+- **Validation Accuracy**: ~82.5%
+- **Top-5 Accuracy**: >95%
+
+## Files
+
+- `best_model.pth`: Trained PyTorch checkpoint
+- `real_class_mapping.json`: Human-readable class names
+- `config.yaml`: Training configuration
+- `food101_class_names.json`: Original class names
+
+## Quick Usage
+
+```python
+from huggingface_hub import hf_hub_download
+import torch
+
+# Download model
+ckpt_path = hf_hub_download(
+    repo_id="codealchemist01/food-image-classifier-hybrid",
+    filename="best_model.pth"
+)
+
+# Load checkpoint
+checkpoint = torch.load(ckpt_path, map_location="cpu")
+```
+
+## Demo
+
+Try the live demo: [Food Classifier Space](https://huggingface.co/spaces/codealchemist01/food-classifier-space)
+
+## Training Details
+
+- **Dataset**: Food-101 (101,000 images across 101 categories)
+- **Framework**: PyTorch 2.0+
+- **Image Size**: 224x224
+- **Optimizer**: AdamW with cosine annealing warm restarts
+- **Augmentations**: Albumentations (flip, rotation, color jitter)
+- **Mixed Precision**: FP16 training
+
+## Citation
+
+```bibtex
+@misc{food-classifier-hybrid,
+  author = {codealchemist01},
+  title = {Hybrid Food Image Classifier},
+  year = {2025},
+  publisher = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/codealchemist01/food-image-classifier-hybrid}}
+}
+```