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license: mit
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# MobileNetWildFireModel for Wildfire Classification

## Model Details

- **Model Architecture:** MobileNetV2 (Modified)  
- **Framework:** PyTorch  
- **Input Shape:** 3-channel RGB images  
- **Number of Parameters:** ~3.4M (Based on MobileNetV2)  
- **Output:** Binary classification (wildfire presence)

## Model Description

This model is a **fine-tuned MobileNetV2** for wildfire classification. The pretrained **MobileNetV2** 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     | 0.0991        | 0.0255          |
| 2     | 0.0046        | 0.0269          |
| 3     | 0.0038        | 0.0290          |
| 4     | 0.0026        | 0.0227          |
| 5     | 0.0023        | 0.0229          |
| 6     | 0.0019        | 0.0291          |
| 7     | 0.0020        | 0.0269          |
| 8     | 0.0017        | 0.0230          |
| 9     | 0.0015        | 0.0243          |
| 10    | 0.0014        | 0.0241          |

## License

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

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