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: 1.5853
Accuracy: 0.4625

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	20	1.9252	0.2938
No log	2.0	40	1.7439	0.4562
No log	3.0	60	1.6389	0.425
No log	4.0	80	1.5862	0.475
No log	5.0	100	1.5477	0.4188
No log	6.0	120	1.5441	0.4437

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cpu
Datasets 2.17.0
Tokenizers 0.15.2

aldidwiputra9/emotion_classification

emotion_classification

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

aldidwiputra9/
emotion_classification