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

Loss: 0.2073
Accuracy: 0.967

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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.1833	0.14	10	1.6004	0.626
1.3976	0.28	20	0.8484	0.909
0.9003	0.43	30	0.4514	0.946
0.6423	0.57	40	0.3037	0.96
0.5084	0.71	50	0.2468	0.96
0.47	0.85	60	0.2161	0.965
0.4753	0.99	70	0.2073	0.967

Framework versions

Transformers 4.35.0
Pytorch 2.1.1
Datasets 2.14.6
Tokenizers 0.14.1

phuong-tk-nguyen/vit-base-patch16-224-finetuned

vit-base-patch16-224-finetuned

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

phuong-tk-nguyen/
vit-base-patch16-224-finetuned