readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imagefolder
  metrics:
  - accuracy
  - f1
  - recall
  - precision
  model-index:
  - name: Brain_Tumor_Classification
    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: 0.9646761984861227
      - name: F1
        type: f1
        value: 0.9646761984861227
      - name: Recall
        type: recall
        value: 0.9646761984861227
      - name: Precision
        type: precision
        value: 0.9646761984861227
  ---
  
  <!-- 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_Classification
  
  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: 0.1012
  - Accuracy: 0.9647
  - F1: 0.9647
  - Recall: 0.9647
  - Precision: 0.9647
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
  | 0.4856        | 0.99  | 83   | 0.3771          | 0.8444   | 0.8444 | 0.8444 | 0.8444    |
  | 0.3495        | 1.99  | 166  | 0.2608          | 0.8949   | 0.8949 | 0.8949 | 0.8949    |
  | 0.252         | 2.99  | 249  | 0.1445          | 0.9487   | 0.9487 | 0.9487 | 0.9487    |
  | 0.2364        | 3.99  | 332  | 0.1029          | 0.9588   | 0.9588 | 0.9588 | 0.9588    |
  | 0.2178        | 4.99  | 415  | 0.1012          | 0.9647   | 0.9647 | 0.9647 | 0.9647    |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  