readme: ---
  license: apache-2.0
  tags:
  - image-classification
  - generated_from_trainer
  model-index:
  - name: vit-base-cifar10
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # vit-base-cifar10
  
  This model is a fine-tuned version of [nateraw/vit-base-patch16-224-cifar10](https://huggingface.co/nateraw/vit-base-patch16-224-cifar10) on the cifar10-upside-down dataset.
  It achieves the following results on the evaluation set:
  - eval_loss: 0.2348
  - eval_accuracy: 0.9134
  - eval_runtime: 157.4172
  - eval_samples_per_second: 127.051
  - eval_steps_per_second: 1.988
  - epoch: 0.02
  - step: 26
  
  ## Model description
  
  Vision Transformer
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.0002
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  