readme: ---
  license: apache-2.0
  tags:
  - image-classification
  - generated_from_trainer
  datasets:
  - imagefolder
  widget:
    - src: https://huggingface.co/alkzar90/croupier-creature-classifier/resolve/main/examples/crusader_peco_peco.png
      example_title: Crusader-Rangarok-Online
    - src: https://huggingface.co/alkzar90/croupier-creature-classifier/resolve/main/examples/goblin_wow.png
      example_title: Goblin-WoW
    - src: https://huggingface.co/alkzar90/croupier-creature-classifier/resolve/main/examples/dobby_harry_potter.jpg
      example_title: Dobby-Harry-Potter
    - src: https://huggingface.co/alkzar90/croupier-creature-classifier/resolve/main/examples/resident_evil_nemesis.jpeg
      example_title: Nemesis-Resident-Evil
  metrics:
  - accuracy
  model-index:
  - name: croupier-creature-classifier
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: croupier-mtg-dataset
        type: imagefolder
        config: alkzar90--croupier-mtg-dataset
        split: train
        args: alkzar90--croupier-mtg-dataset
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.7471264367816092
  ---
  
  <!-- 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. -->
  
  # croupier-creature-classifier
  
  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 croupier-mtg-dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7583
  - Accuracy: 0.7471
  
  ## 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: 0.0002
  - train_batch_size: 16
  - eval_batch_size: 8
  - 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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6663        | 1.1   | 100  | 1.0179          | 0.5941   |
  | 0.4924        | 2.2   | 200  | 0.7036          | 0.7529   |
  | 0.4552        | 3.3   | 300  | 0.6123          | 0.7824   |
  | 0.2355        | 4.4   | 400  | 0.5748          | 0.7647   |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  