vit-cropped-faces

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

• Loss: 0.0109
• 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: 0.0002
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 20
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0254	3.125	100	0.0136	1.0
0.0053	6.25	200	0.0109	1.0
0.0033	9.375	300	0.0139	1.0
0.0025	12.5	400	0.0128	1.0
0.0021	15.625	500	0.0122	1.0
0.0019	18.75	600	0.0120	1.0

Framework versions

• Transformers 4.48.3
• Pytorch 2.5.1+cu124
• Datasets 3.3.2
• Tokenizers 0.21.0