readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - cifar100
  metrics:
  - accuracy
  model-index:
  - name: swin-small-finetuned-cifar100
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: cifar100
        type: cifar100
        args: cifar100
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8938
  ---
  
  <!-- 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. -->
  
  # swin-small-finetuned-cifar100
  
  This model is a fine-tuned version of [microsoft/swin-small-patch4-window7-224](https://huggingface.co/microsoft/swin-small-patch4-window7-224) on the cifar100 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6281
  - Accuracy: 0.8938
  
  ## 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: 4e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.72          | 1.0   | 781   | 0.6691          | 0.8077   |
  | 0.6944        | 2.0   | 1562  | 0.4797          | 0.8495   |
  | 0.2794        | 3.0   | 2343  | 0.4338          | 0.869    |
  | 0.2569        | 4.0   | 3124  | 0.4263          | 0.879    |
  | 0.1417        | 5.0   | 3905  | 0.4385          | 0.8819   |
  | 0.0961        | 6.0   | 4686  | 0.4720          | 0.8854   |
  | 0.0584        | 7.0   | 5467  | 0.4941          | 0.885    |
  | 0.0351        | 8.0   | 6248  | 0.5253          | 0.885    |
  | 0.0107        | 9.0   | 7029  | 0.5598          | 0.8887   |
  | 0.0118        | 10.0  | 7810  | 0.5998          | 0.8858   |
  | 0.0097        | 11.0  | 8591  | 0.5957          | 0.8941   |
  | 0.0044        | 12.0  | 9372  | 0.6237          | 0.8912   |
  | 0.0013        | 13.0  | 10153 | 0.6286          | 0.8929   |
  | 0.0102        | 14.0  | 10934 | 0.6281          | 0.8938   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  