---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_03
  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: 0.9758007117437723
---

<!-- 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-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_03

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: 0.0706
- Accuracy: 0.9758

## 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: 6e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2809        | 1.0   | 11   | 0.7111          | 0.7153   |
| 0.4554        | 2.0   | 22   | 0.2233          | 0.9139   |
| 0.2382        | 3.0   | 33   | 0.1730          | 0.9388   |
| 0.1453        | 4.0   | 44   | 0.1444          | 0.9509   |
| 0.1064        | 5.0   | 55   | 0.0900          | 0.9665   |
| 0.079         | 6.0   | 66   | 0.0866          | 0.9665   |
| 0.0606        | 7.0   | 77   | 0.1744          | 0.9402   |
| 0.0561        | 8.0   | 88   | 0.1116          | 0.9580   |
| 0.0406        | 9.0   | 99   | 0.0726          | 0.9730   |
| 0.0306        | 10.0  | 110  | 0.0706          | 0.9758   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3