readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: vit-base-patch16-224-in21k-shiba-inu-detector
    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-patch16-224-in21k-shiba-inu-detector
  
  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on dataset with 4 dog types including Shiba Inu.
  
  It achieves the following results on the evaluation set:
  - Loss: 0.6511
  - Accuracy: 1.0
  
  ## 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: 5e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 0.94  | 4    | 1.3875          | 0.1667   |
  | No log        | 1.94  | 8    | 1.2712          | 0.7833   |
  | 1.4176        | 2.94  | 12   | 1.0972          | 0.9      |
  | 1.4176        | 3.94  | 16   | 0.9365          | 0.95     |
  | 1.0144        | 4.94  | 20   | 0.7836          | 0.9833   |
  | 1.0144        | 5.94  | 24   | 0.6511          | 1.0      |
  | 1.0144        | 6.94  | 28   | 0.5329          | 1.0      |
  | 0.6329        | 7.94  | 32   | 0.4403          | 1.0      |
  | 0.6329        | 8.94  | 36   | 0.3777          | 1.0      |
  | 0.3821        | 9.94  | 40   | 0.3273          | 1.0      |
  | 0.3821        | 10.94 | 44   | 0.2886          | 1.0      |
  | 0.3821        | 11.94 | 48   | 0.2622          | 1.0      |
  | 0.2655        | 12.94 | 52   | 0.2397          | 1.0      |
  | 0.2655        | 13.94 | 56   | 0.2250          | 1.0      |
  | 0.202         | 14.94 | 60   | 0.2152          | 1.0      |
  | 0.202         | 15.94 | 64   | 0.2074          | 1.0      |
  | 0.202         | 16.94 | 68   | 0.2003          | 1.0      |
  | 0.1785        | 17.94 | 72   | 0.1960          | 1.0      |
  | 0.1785        | 18.94 | 76   | 0.1936          | 1.0      |
  | 0.1618        | 19.94 | 80   | 0.1930          | 1.0      |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  