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license: mit
language:
- en
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# LeNet for Wildfire Classification

## Model Details

- **Model Architecture:** LeNet (Modified)  
- **Framework:** PyTorch  
- **Input Shape:** 3-channel RGB images  
- **Number of Parameters:** ~ (Calculated based on input size)  
- **Output:** Binary classification (wildfire presence)  

## Model Description

This model is a modified version of the classic **LeNet** architecture, adapted for **wildfire classification**. It consists of two convolutional layers followed by three fully connected layers. The model was trained using **ReLU activations**, **max pooling**, and a **final linear layer** for binary classification.

## Training Details

- **Optimizer:** Adam
- **Loss Function:** Binary Cross-Entropy   
- **Batch Size:** 32
- **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     | 0.8609       | 0.3632         |
| 2     | 0.3368       | 0.3023         |
| 3     | 0.2723       | 0.2852         |
| 4     | 0.1966       | 0.1914         |
| 5     | 0.2889       | 0.2610         |
| 6     | 0.1914       | 0.2747         |
| 7     | 0.2148       | 0.2520         |
| 8     | 0.1643       | 0.1751         |
| 9     | 0.1938       | 0.1929         |
| 10    | 0.1130       | 0.2095         |

## License

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

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