This model is a fine-tuned version of google/vit-base-patch16-224 on the maurice-fp/stanford-dogs dataset. It achieves the following results on the evaluation set:

Loss: 0.6323
Accuracy: 0.8416

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: 6e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.7839	1.0	1029	1.6492	0.7988
0.765	2.0	2058	0.7655	0.8411
0.6504	3.0	3087	0.6558	0.8426
0.6054	4.0	4116	0.6601	0.8319
0.6279	5.0	5145	0.6133	0.8435

Framework versions

Transformers 4.52.4
Pytorch 2.7.0
Datasets 3.6.0
Tokenizers 0.21.1

Flogoro/vit-base-maurice-fp-stanford-dogs

vit-base-maurice-fp-stanford-dogs

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Flogoro/
vit-base-maurice-fp-stanford-dogs