vit-base-patch16-224-cifar10

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

• Loss: 0.0506
• Accuracy: 0.9906

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: 128
• eval_batch_size: 64
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 0.1
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0405	1.2788	500	0.0684	0.9801
0.0211	2.5575	1000	0.0913	0.9763
0.0107	3.8363	1500	0.0541	0.9864
0.0045	5.1151	2000	0.0534	0.9883
0.0022	6.3939	2500	0.0522	0.989
0.0009	7.6726	3000	0.0506	0.9906
0.0012	8.9514	3500	0.0487	0.9905

Framework versions

• Transformers 5.3.0
• Pytorch 2.6.0+cu124
• Datasets 4.8.3
• Tokenizers 0.22.2