This model is a fine-tuned version of google/vit-base-patch16-224 on the image_folder dataset. It achieves the following results on the evaluation set:

Loss: 1.2569
Accuracy: 0.6296

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
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7934	0.99	58	1.2569	0.6296

Framework versions

Transformers 4.35.2
Pytorch 2.0.0+cpu
Datasets 2.1.0
Tokenizers 0.15.0

OkabeRintaro/vit-base-patch16-224-finetuned-imagegpt

vit-base-patch16-224-finetuned-imagegpt

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

OkabeRintaro/
vit-base-patch16-224-finetuned-imagegpt