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: 0.7362
Accuracy: 0.608
F1: 0.5096

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
3.2255	5.0	20	1.9574	0.512	0.3083
1.3773	10.0	40	0.8854	0.584	0.4617
0.869	15.0	60	0.7880	0.608	0.4795
0.7966	20.0	80	0.7732	0.6	0.4846
0.8458	25.0	100	0.7795	0.576	0.4112
0.8135	30.0	120	0.7362	0.608	0.5096

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.1

arpanl/Fine-Tuned_Model3

Fine-Tuned_Model3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

arpanl/
Fine-Tuned_Model3