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: 1.3024
Accuracy: 0.5563

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: 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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	80	1.6229	0.4625
No log	2.0	160	1.3527	0.5062
No log	3.0	240	1.2950	0.5312
No log	4.0	320	1.2573	0.525
No log	5.0	400	1.2715	0.5375
No log	6.0	480	1.3024	0.5563
0.8888	7.0	560	1.3340	0.5375
0.8888	8.0	640	1.3683	0.525
0.8888	9.0	720	1.3806	0.5437
0.8888	10.0	800	1.3851	0.5375

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1

hfzdzakii/REA_Transfer_Learning

REA_Transfer_Learning

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hfzdzakii/
REA_Transfer_Learning