readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: swin-tiny-patch4-window7-224-finetuned-fluro_cls
    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. -->
  
  # swin-tiny-patch4-window7-224-finetuned-fluro_cls
  
  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 None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0000
  - 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: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 0.67  | 1    | 0.7112          | 0.5238   |
  | No log        | 1.67  | 2    | 0.5591          | 0.8571   |
  | 0.811         | 2.67  | 3    | 0.3781          | 0.9524   |
  | 0.811         | 3.67  | 4    | 0.1995          | 1.0      |
  | 0.811         | 4.67  | 5    | 0.1215          | 1.0      |
  | 0.3531        | 5.67  | 6    | 0.0578          | 1.0      |
  | 0.3531        | 6.67  | 7    | 0.0195          | 1.0      |
  | 0.3531        | 7.67  | 8    | 0.0072          | 1.0      |
  | 0.0618        | 8.67  | 9    | 0.0030          | 1.0      |
  | 0.0618        | 9.67  | 10   | 0.0012          | 1.0      |
  | 0.0618        | 10.67 | 11   | 0.0005          | 1.0      |
  | 0.0079        | 11.67 | 12   | 0.0003          | 1.0      |
  | 0.0079        | 12.67 | 13   | 0.0001          | 1.0      |
  | 0.0079        | 13.67 | 14   | 0.0001          | 1.0      |
  | 0.0051        | 14.67 | 15   | 0.0001          | 1.0      |
  | 0.0051        | 15.67 | 16   | 0.0000          | 1.0      |
  | 0.0051        | 16.67 | 17   | 0.0000          | 1.0      |
  | 0.0017        | 17.67 | 18   | 0.0000          | 1.0      |
  | 0.0017        | 18.67 | 19   | 0.0000          | 1.0      |
  | 0.0017        | 19.67 | 20   | 0.0000          | 1.0      |
  | 0.0004        | 20.67 | 21   | 0.0000          | 1.0      |
  | 0.0004        | 21.67 | 22   | 0.0000          | 1.0      |
  | 0.0004        | 22.67 | 23   | 0.0000          | 1.0      |
  | 0.0022        | 23.67 | 24   | 0.0000          | 1.0      |
  | 0.0022        | 24.67 | 25   | 0.0000          | 1.0      |
  | 0.0022        | 25.67 | 26   | 0.0000          | 1.0      |
  | 0.001         | 26.67 | 27   | 0.0000          | 1.0      |
  | 0.001         | 27.67 | 28   | 0.0000          | 1.0      |
  | 0.001         | 28.67 | 29   | 0.0000          | 1.0      |
  | 0.0013        | 29.67 | 30   | 0.0000          | 1.0      |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.10.2+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  