readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imagefolder
  metrics:
  - accuracy
  - f1
  - recall
  - precision
  model-index:
  - name: Brain_Tumor_Detector_swin
    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: 0.9981308411214953
      - name: F1
        type: f1
        value: 0.9985111662531018
      - name: Recall
        type: recall
        value: 0.9990069513406157
      - name: Precision
        type: precision
        value: 0.998015873015873
  ---
  
  <!-- 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. -->
  
  # Brain_Tumor_Detector_swin
  
  This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0054
  - Accuracy: 0.9981
  - F1: 0.9985
  - Recall: 0.9990
  - Precision: 0.9980
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
  | 0.079         | 1.0   | 113  | 0.0283          | 0.9882   | 0.9906 | 0.9930 | 0.9881    |
  | 0.0575        | 2.0   | 226  | 0.0121          | 0.9956   | 0.9965 | 0.9950 | 0.9980    |
  | 0.0312        | 3.0   | 339  | 0.0054          | 0.9981   | 0.9985 | 0.9990 | 0.9980    |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  