vit-base-oxford-iiit-pets
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: 0.2197
- Accuracy: 0.9283
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3702 | 1.0 | 370 | 0.2809 | 0.9350 |
| 0.2176 | 2.0 | 740 | 0.2133 | 0.9432 |
| 0.1556 | 3.0 | 1110 | 0.1965 | 0.9486 |
| 0.1443 | 4.0 | 1480 | 0.1872 | 0.9499 |
| 0.1294 | 5.0 | 1850 | 0.1843 | 0.9486 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for adnananouzla/vit-base-oxford-iiit-pets
Base model
google/vit-base-patch16-224