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license: mit
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# EfficientNetWildFireModel for Wildfire Classification

## Model Details

- **Model Architecture:** EfficientNet-B0 (Modified)  
- **Framework:** PyTorch  
- **Input Shape:** 3-channel RGB images  
- **Number of Parameters:** ~5.3M (Based on EfficientNet-B0)  
- **Output:** Binary classification (wildfire presence)

## Model Description

This model is a **fine-tuned EfficientNet-B0** for wildfire classification. The pretrained **EfficientNet-B0** 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, predicting the presence of wildfire.

## Training Details

- **Optimizer:** Adam  
- **Batch Size:** 32  
- **Loss Function:** Binary Cross-Entropy (BCE)  
- **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     | 0.1859        | 0.0699          |
| 2     | 0.0553        | 0.0580          |
| 3     | 0.0263        | 0.0576          |
| 4     | 0.0146        | 0.0553          |
| 5     | 0.0105        | 0.0555          |
| 6     | 0.0080        | 0.0554          |
| 7     | 0.0062        | 0.0554          |
| 8     | 0.0052        | 0.0559          |
| 9     | 0.0043        | 0.0550          |
| 10    | 0.0037        | 0.0563          |

## License

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

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