Remote-Sensing-UAV-image-classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an jonathan-roberts1/RSSCN7 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0593
- Accuracy: 0.9907
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
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 |
|---|---|---|---|---|
| 0.3922 | 0.71 | 100 | 0.4227 | 0.8821 |
| 0.2986 | 1.43 | 200 | 0.3142 | 0.9089 |
| 0.1109 | 2.14 | 300 | 0.2056 | 0.9518 |
| 0.0864 | 2.86 | 400 | 0.2472 | 0.9375 |
| 0.0193 | 3.57 | 500 | 0.0593 | 0.9907 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1