Update README.md

README.md

@@ -1,3 +1,47 @@
----
-license: mit
----
+---
+license: mit
+---
+
+# 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**.
+
+---
+