readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: vit-for-kaggle-mayo-clinic
    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-for-kaggle-mayo-clinic
  
  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5538
  - Accuracy: 0.7616
  
  ## 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: 0.0003
  - 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: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 10   | 0.5944          | 0.7483   |
  | No log        | 2.0   | 20   | 0.5640          | 0.7483   |
  | No log        | 3.0   | 30   | 0.5582          | 0.7483   |
  | No log        | 4.0   | 40   | 0.5585          | 0.7483   |
  | No log        | 5.0   | 50   | 0.5598          | 0.7483   |
  | No log        | 6.0   | 60   | 0.5484          | 0.7483   |
  | No log        | 7.0   | 70   | 0.5524          | 0.7417   |
  | No log        | 8.0   | 80   | 0.5538          | 0.7616   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  