julenalvaro/Perros-VS-gatos-con-vit-base-patch16-224-in21k

vit-base-patch16-224-in21k

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1026
• Accuracy: 0.982

Model description

This model is a fine-tuned version of google/vit-base-patch16-224-in21k which discriminates cats from dogs.

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.177	0.5	500	0.2100	0.9435
0.1515	1.0	1000	0.0710	0.975
0.0443	1.5	1500	0.2043	0.9535
0.0625	2.0	2000	0.0898	0.9745
0.0181	2.5	2500	0.0961	0.9805
0.0091	3.0	3000	0.1049	0.982
0.0016	3.5	3500	0.1066	0.981
0.0015	4.0	4000	0.1026	0.982

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu116
• Datasets 2.8.0
• Tokenizers 0.13.2