readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imagefolder
  metrics:
  - accuracy
  model-index:
  - name: swin-tiny-patch4-window7-224-finetuned-woody_130epochs
    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: 0.8921212121212121
  ---
  
  <!-- 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_130epochs
  
  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: 0.4550
  - Accuracy: 0.8921
  
  ## 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: 130
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6694        | 1.0   | 58   | 0.6370          | 0.6594   |
  | 0.6072        | 2.0   | 116  | 0.5813          | 0.7030   |
  | 0.6048        | 3.0   | 174  | 0.5646          | 0.7030   |
  | 0.5849        | 4.0   | 232  | 0.5778          | 0.6970   |
  | 0.5671        | 5.0   | 290  | 0.5394          | 0.7236   |
  | 0.5575        | 6.0   | 348  | 0.5212          | 0.7382   |
  | 0.568         | 7.0   | 406  | 0.5218          | 0.7358   |
  | 0.5607        | 8.0   | 464  | 0.5183          | 0.7527   |
  | 0.5351        | 9.0   | 522  | 0.5138          | 0.7467   |
  | 0.5459        | 10.0  | 580  | 0.5290          | 0.7394   |
  | 0.5454        | 11.0  | 638  | 0.5212          | 0.7345   |
  | 0.5291        | 12.0  | 696  | 0.5130          | 0.7576   |
  | 0.5378        | 13.0  | 754  | 0.5372          | 0.7503   |
  | 0.5264        | 14.0  | 812  | 0.6089          | 0.6861   |
  | 0.4909        | 15.0  | 870  | 0.4852          | 0.7636   |
  | 0.5591        | 16.0  | 928  | 0.4817          | 0.76     |
  | 0.4966        | 17.0  | 986  | 0.5673          | 0.6933   |
  | 0.4988        | 18.0  | 1044 | 0.5131          | 0.7418   |
  | 0.5339        | 19.0  | 1102 | 0.4998          | 0.7394   |
  | 0.4804        | 20.0  | 1160 | 0.4655          | 0.7733   |
  | 0.503         | 21.0  | 1218 | 0.4554          | 0.7685   |
  | 0.4859        | 22.0  | 1276 | 0.4713          | 0.7770   |
  | 0.504         | 23.0  | 1334 | 0.4545          | 0.7721   |
  | 0.478         | 24.0  | 1392 | 0.4658          | 0.7830   |
  | 0.4759        | 25.0  | 1450 | 0.4365          | 0.8012   |
  | 0.4686        | 26.0  | 1508 | 0.4452          | 0.7855   |
  | 0.4668        | 27.0  | 1566 | 0.4427          | 0.7879   |
  | 0.4615        | 28.0  | 1624 | 0.4439          | 0.7685   |
  | 0.4588        | 29.0  | 1682 | 0.4378          | 0.7830   |
  | 0.4588        | 30.0  | 1740 | 0.4229          | 0.7988   |
  | 0.4296        | 31.0  | 1798 | 0.4188          | 0.7976   |
  | 0.4208        | 32.0  | 1856 | 0.4316          | 0.7891   |
  | 0.4481        | 33.0  | 1914 | 0.4331          | 0.7891   |
  | 0.4253        | 34.0  | 1972 | 0.4524          | 0.7879   |
  | 0.4117        | 35.0  | 2030 | 0.4570          | 0.7952   |
  | 0.4405        | 36.0  | 2088 | 0.4307          | 0.7927   |
  | 0.4154        | 37.0  | 2146 | 0.4257          | 0.8024   |
  | 0.3962        | 38.0  | 2204 | 0.5077          | 0.7818   |
  | 0.414         | 39.0  | 2262 | 0.4602          | 0.8012   |
  | 0.3937        | 40.0  | 2320 | 0.4741          | 0.7770   |
  | 0.4186        | 41.0  | 2378 | 0.4250          | 0.8      |
  | 0.4076        | 42.0  | 2436 | 0.4353          | 0.7988   |
  | 0.3777        | 43.0  | 2494 | 0.4442          | 0.7879   |
  | 0.3968        | 44.0  | 2552 | 0.4525          | 0.7879   |
  | 0.377         | 45.0  | 2610 | 0.4198          | 0.7988   |
  | 0.378         | 46.0  | 2668 | 0.4297          | 0.8097   |
  | 0.3675        | 47.0  | 2726 | 0.4435          | 0.8085   |
  | 0.3562        | 48.0  | 2784 | 0.4477          | 0.7952   |
  | 0.381         | 49.0  | 2842 | 0.4206          | 0.8255   |
  | 0.3603        | 50.0  | 2900 | 0.4136          | 0.8109   |
  | 0.3331        | 51.0  | 2958 | 0.4141          | 0.8230   |
  | 0.3471        | 52.0  | 3016 | 0.4253          | 0.8109   |
  | 0.346         | 53.0  | 3074 | 0.5203          | 0.8048   |
  | 0.3481        | 54.0  | 3132 