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---
license: mit
language:
- en
---
# 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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