This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cats_vs_dogs dataset. It achieves the following results on the evaluation set:

Loss: 0.0202
Accuracy: 0.9935

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: 0.0002
train_batch_size: 64
eval_batch_size: 64
seed: 1337
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.064	1.0	311	0.0483	0.9849
0.0622	2.0	622	0.0275	0.9903
0.0366	3.0	933	0.0262	0.9917
0.0294	4.0	1244	0.0219	0.9932
0.0161	5.0	1555	0.0202	0.9935

Framework versions

Transformers 4.8.1
Pytorch 1.9.0+cu102
Datasets 1.11.1.dev0
Tokenizers 0.10.3

nateraw/vit-base-cats-vs-dogs

vit-base-cats-vs-dogs

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

nateraw/
vit-base-cats-vs-dogs