This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.4629
Accuracy: 0.9125

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: 0.0002
train_batch_size: 160
eval_batch_size: 32
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
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8836	1.1765	100	0.6595	0.8818
0.681	2.3529	200	0.5422	0.8965
0.5669	3.5294	300	0.4629	0.9125

Framework versions

Transformers 4.48.0.dev0
Pytorch 2.4.1
Datasets 3.2.0
Tokenizers 0.21.0

nguyenthethang1995/finetuned-bank-images

finetuned-bank-images

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nguyenthethang1995/
finetuned-bank-images