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: 1.3899
Accuracy: 0.55

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: 16
eval_batch_size: 16
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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5061	1.0	40	1.5316	0.4875
0.4361	2.0	80	1.4641	0.5125
0.2775	3.0	120	1.4056	0.5375

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1

asaaitika/vit-emotion

vit-emotion

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

asaaitika/
vit-emotion