Create README.md

README.md

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+---
+license: mit
+language:
+- en
+---
+
+# AlexNetWildFire for Wildfire Classification
+
+## Model Details
+
+- **Model Architecture:** AlexNet (Modified)  
+- **Framework:** PyTorch  
+- **Input Shape:** 3-channel RGB images  
+- **Number of Parameters:** ~ (Based on AlexNet)  
+- **Output:** Binary classification (wildfire presence)  
+
+## Model Description
+
+This model is a **fine-tuned AlexNet** for wildfire classification. The pretrained **AlexNet** 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.
+
+## Training Details
+
+- **Optimizer:** Adam  
+- **Batch Size:** 32  
+- **Loss Function:** Binary Cross-Entropy (assumed)  
+- **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     | 0.2161       | 0.2249         |
+| 2     | 0.1158       | 0.3618         |
+| 3     | 0.1004       | 0.3120         |
+| 4     | 0.0213       | 0.3541         |
+| 5     | 0.0299       | 0.2749         |
+| 6     | 0.0326       | 0.2352         |
+| 7     | 0.0032       | 0.2222         |
+| 8     | 0.0012       | 0.3360         |
+| 9     | 0.0001       | 0.3072         |
+| 10    | 0.0000       | 0.2819         |
+
+## License
+
+This model is released under the **MIT License**.
+
+---