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: 0.1514
Accuracy: 0.9439

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	468	0.1514	0.9439
0.2863	2.0	936	0.1917	0.9303
0.2377	3.0	1404	0.1725	0.9333
0.2142	4.0	1872	0.1782	0.9288
0.2058	5.0	2340	0.1788	0.9273
0.1899	6.0	2808	0.1824	0.9318
0.1838	7.0	3276	0.1879	0.9333
0.1757	8.0	3744	0.2391	0.9333
0.1852	9.0	4212	0.1725	0.9409
0.1634	10.0	4680	0.1762	0.9394

Framework versions

Transformers 4.34.1
Pytorch 2.1.0
Datasets 2.14.6
Tokenizers 0.14.1

sarabi1005/vit-base-beans_50

vit-base-beans_50

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sarabi1005/
vit-base-beans_50