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: 0.9525
Accuracy: 0.6667

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: 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
No log	1.0	3	1.5195	0.2
No log	2.0	6	1.4667	0.2
No log	3.0	9	1.4288	0.0
No log	4.0	12	1.4128	0.0
No log	5.0	15	1.4065	0.2

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cpu
Datasets 3.0.0
Tokenizers 0.19.1

Bang18/vit-base-oxford-iiit-pets

vit-base-oxford-iiit-pets

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Bang18/
vit-base-oxford-iiit-pets