kawchar85/image-classification

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