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: 0.1992
Accuracy: 0.9391
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 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
0.3991
1.0
370
0.2804
0.9337
0.2286
2.0
740
0.2133
0.9445
0.1633
3.0
1110
0.2036
0.9418
0.1518
4.0
1480
0.1882
0.9418
0.1434
5.0
1850
0.1854
0.9432
Framework versions
Transformers 4.50.0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1
Zero Shot Resultate
Model used for Zero Shot: openai/clip-vit-large-patch14
