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: 0.2774
Accuracy: 1.0

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: 5
eval_batch_size: 5
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 20
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.8	2	0.5778	0.6667
No log	2.0	5	0.2774	1.0
No log	2.4	6	0.2546	1.0

Framework versions

Transformers 4.35.2
Pytorch 2.1.1+cu121
Datasets 2.16.0
Tokenizers 0.15.0

stentorianvoice/vit-base-patch16-224

vit-base-patch16-224

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

stentorianvoice/
vit-base-patch16-224