ResNet50 Fine-tuned for Wildfire Detection

This model is a ResNet50 fine-tuned on the 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)

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support