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---
license: mit
---

# VGGWildFireModel for Wildfire Classification

## Model Details

- **Model Architecture:** VGG-16 (Modified)  
- **Framework:** PyTorch  
- **Input Shape:** 3-channel RGB images  
- **Number of Parameters:** ~ (Based on VGG-16)  
- **Output:** Binary classification (wildfire presence)  

## Model Description

This model is a **fine-tuned VGG-16** for wildfire classification. The pretrained **VGG-16** backbone is used with its feature extractor **frozen**, while only the **final classification layer** is trained. The last fully connected layer has been replaced with a **single output neuron** for binary classification.

## Training Details

- **Optimizer:** Adam  
- **Batch Size:** 32  
- **Loss Function:** Binary Cross-Entropy  
- **Number of Epochs:** 10  
- **Dataset:** [Wildfire Detection Image Data](https://www.kaggle.com/datasets/brsdincer/wildfire-detection-image-data)  

### Losses Per Epoch

| Epoch | Training Loss | Validation Loss |
|-------|--------------|----------------|
| 1     | 0.2571       | 0.3858         |
| 2     | 0.0846       | 0.1935         |
| 3     | 0.0165       | 0.1573         |
| 4     | 0.0013       | 0.1204         |
| 5     | 0.0001       | 0.1243         |
| 6     | 0.0000       | 0.1247         |
| 7     | 0.0000       | 0.1244         |
| 8     | 0.0000       | 0.1242         |
| 9     | 0.0000       | 0.1240         |
| 10    | 0.0000       | 0.1236         |

## License

This model is released under the **MIT License**.

---