readme: ---
  tags:
  - image-classification
  metrics:
  - accuracy
  
  model-index:
  - name: vit-base-patch16-224-in21k-image-classification-sagemaker
  ---
  
  <!-- 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-patch16-224-in21k-image-classification-sagemaker
  
  This model is a fine-tuned version of [vit-base-patch16-224-in21k](https://huggingface.co/vit-base-patch16-224-in21k) on the cifar10 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3033
  - Accuracy: 0.972
  
  ## 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: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 313  | 1.4603          | 0.936    |
  | 1.6548        | 2.0   | 626  | 0.4451          | 0.966    |
  | 1.6548        | 3.0   | 939  | 0.3033          | 0.972    |
  
  
  ### Framework versions
  
  - Transformers 4.6.1
  - Pytorch 1.7.1
  - Datasets 1.6.2
  - Tokenizers 0.10.3
  