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

kawchar85/image-classification

Image Classification

Training procedure

Training hyperparameters

Training results

Framework versions

kawchar85/
image-classification