Image Classification
This model is a fine-tuned version of google/vit-base-patch16-224 on the pcuenq/oxford-pets dataset. It achieves the following results on the evaluation set:
- Loss: 0.2031
- Accuracy: 0.9459
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3727 | 1.0 | 370 | 0.2756 | 0.9337 |
| 0.2145 | 2.0 | 740 | 0.2168 | 0.9378 |
| 0.1835 | 3.0 | 1110 | 0.1918 | 0.9459 |
| 0.147 | 4.0 | 1480 | 0.1857 | 0.9472 |
| 0.1315 | 5.0 | 1850 | 0.1818 | 0.9472 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
google/vit-base-patch16-224