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README.md

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-license: mit
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+---
+license: mit
+---
+
+# 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**.
+
+---