| tags: | |
| - image-classification | |
| - wildfire-detection | |
| datasets: | |
| - your-dataset-name # Optional: Add the name of the dataset you used | |
| # ResNet50 Fine-tuned for Wildfire Detection | |
| This model is a ResNet50 fine-tuned on the [Wildfire Prediction Dataset](https://www.kaggle.com/datasets/abdelghaniaaba/wildfire-prediction-dataset) for image classification to detect wildfires. | |
| ## Model Details | |
| The model is a ResNet50 architecture with a custom classification head. It was trained in two phases: first with the backbone frozen, and then with full fine-tuning. | |
| ## Training | |
| The model was trained on the provided dataset with the following characteristics: | |
| - **Train samples:** 30250 | |
| - **Validation samples:** 6300 | |
| - **Batch size:** 16 | |
| - **Epochs (Phase 1 - Head):** 5 | |
| - **Epochs (Phase 2 - Full Fine-tuning):** 3 | |
| ## Performance | |
| (Add details about the model's performance metrics, e.g., accuracy, loss, etc. from your training output) | |
| ## Usage | |
| (Provide code examples on how to load and use the model for inference) | |