readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  
  widget:
    - src: >-
        https://huggingface.co/julenalvaro/Perros-VS-gatos-con-vit-base-patch16-224-in21k/resolve/main/dog.jpeg
      example_title: dog
    - src: >-
        https://huggingface.co/julenalvaro/Perros-VS-gatos-con-vit-base-patch16-224-in21k/resolve/main/cat.jpeg
      example_title: cat
  
  model-index:
  - name: vit-base-patch16-224-in21k
    results: []
  ---
  
  # vit-base-patch16-224-in21k
  
  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: 0.1026
  - Accuracy: 0.982
  
  ## Model description
  
  This model is a fine-tuned version of google/vit-base-patch16-224-in21k which discriminates cats from dogs. 
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.177         | 0.5   | 500  | 0.2100          | 0.9435   |
  | 0.1515        | 1.0   | 1000 | 0.0710          | 0.975    |
  | 0.0443        | 1.5   | 1500 | 0.2043          | 0.9535   |
  | 0.0625        | 2.0   | 2000 | 0.0898          | 0.9745   |
  | 0.0181        | 2.5   | 2500 | 0.0961          | 0.9805   |
  | 0.0091        | 3.0   | 3000 | 0.1049          | 0.982    |
  | 0.0016        | 3.5   | 3500 | 0.1066          | 0.981    |
  | 0.0015        | 4.0   | 4000 | 0.1026          | 0.982    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  