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: 0.3168
Accuracy: 0.9432

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: 128
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.5136	1.0	47	1.1031	0.8430
0.5547	2.0	94	0.5232	0.9269
0.4111	3.0	141	0.3988	0.9310
0.3438	4.0	188	0.3553	0.9337
0.298	5.0	235	0.3448	0.9296

Framework versions

Transformers 4.39.2
Pytorch 2.1.2
Datasets 2.16.0
Tokenizers 0.15.2

OmAlve/vit-base-pets

vit-base-pets

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

OmAlve/
vit-base-pets