Wildfire classifier
This model is a fine-tuned version of google/vit-base-patch16-384 on the Kaggle Wildfire Dataset. It achieves the following results on the evaluation set:
- Loss: 0.2329
- Accuracy: 0.9202
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.1208 | 1.28 | 100 | 0.2329 | 0.9202 |
0.0261 | 2.56 | 200 | 0.2469 | 0.9316 |
0.0007 | 3.85 | 300 | 0.2358 | 0.9392 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
Aditional resources
- Downloads last month
- 26
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for arnaucas/wildfire-classifier
Base model
google/vit-base-patch16-384