readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imagefolder
  metrics:
  - accuracy
  model-index:
  - name: swin-tiny-patch4-window7-224-finetuned-woody
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: imagefolder
        type: imagefolder
        config: default
        split: train
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.7927272727272727
  ---
  
  <!-- 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-tiny-patch4-window7-224-finetuned-woody
  
  This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4349
  - Accuracy: 0.7927
  
  ## 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: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.632         | 1.0   | 58   | 0.5883          | 0.6836   |
  | 0.6067        | 2.0   | 116  | 0.6017          | 0.6848   |
  | 0.5865        | 3.0   | 174  | 0.5695          | 0.7042   |
  | 0.553         | 4.0   | 232  | 0.5185          | 0.7515   |
  | 0.5468        | 5.0   | 290  | 0.5108          | 0.7430   |
  | 0.5473        | 6.0   | 348  | 0.4882          | 0.7648   |
  | 0.5381        | 7.0   | 406  | 0.4800          | 0.7588   |
  | 0.5468        | 8.0   | 464  | 0.5056          | 0.7358   |
  | 0.5191        | 9.0   | 522  | 0.4784          | 0.7673   |
  | 0.5318        | 10.0  | 580  | 0.4762          | 0.7636   |
  | 0.5079        | 11.0  | 638  | 0.4859          | 0.7673   |
  | 0.5216        | 12.0  | 696  | 0.4691          | 0.7697   |
  | 0.515         | 13.0  | 754  | 0.4857          | 0.7624   |
  | 0.5186        | 14.0  | 812  | 0.4685          | 0.7733   |
  | 0.4748        | 15.0  | 870  | 0.4536          | 0.7818   |
  | 0.4853        | 16.0  | 928  | 0.4617          | 0.7770   |
  | 0.4868        | 17.0  | 986  | 0.4622          | 0.7782   |
  | 0.4572        | 18.0  | 1044 | 0.4583          | 0.7770   |
  | 0.4679        | 19.0  | 1102 | 0.4590          | 0.7733   |
  | 0.4508        | 20.0  | 1160 | 0.4576          | 0.7903   |
  | 0.4663        | 21.0  | 1218 | 0.4542          | 0.7891   |
  | 0.4533        | 22.0  | 1276 | 0.4428          | 0.7903   |
  | 0.4892        | 23.0  | 1334 | 0.4372          | 0.7867   |
  | 0.4704        | 24.0  | 1392 | 0.4414          | 0.7903   |
  | 0.4304        | 25.0  | 1450 | 0.4430          | 0.7988   |
  | 0.4411        | 26.0  | 1508 | 0.4348          | 0.7818   |
  | 0.4604        | 27.0  | 1566 | 0.4387          | 0.7927   |
  | 0.441         | 28.0  | 1624 | 0.4378          | 0.7964   |
  | 0.442         | 29.0  | 1682 | 0.4351          | 0.7915   |
  | 0.4585        | 30.0  | 1740 | 0.4349          | 0.7927   |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.0
  - Tokenizers 0.13.1
  