vit-base-patch16-224-finetuned-lora-oxford-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: 0.2708
- Accuracy: 0.9378
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 |
---|---|---|---|---|
0.0241 | 1.0 | 370 | 0.2456 | 0.9398 |
0.0064 | 2.0 | 740 | 0.2754 | 0.9337 |
0.0017 | 3.0 | 1110 | 0.2613 | 0.9391 |
0.0012 | 4.0 | 1480 | 0.2687 | 0.9378 |
0.001 | 5.0 | 1850 | 0.2708 | 0.9378 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.0
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Base model
google/vit-base-patch16-224