---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-brain-tumor-type-classification
  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-brain-tumor-type-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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2978
- Accuracy: 0.9081

## 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.4824        | 1.0   | 21   | 2.2558          | 0.2420   |
| 2.1213        | 2.0   | 42   | 1.8165          | 0.4170   |
| 1.6613        | 3.0   | 63   | 1.3678          | 0.5671   |
| 1.3237        | 4.0   | 84   | 1.1940          | 0.6060   |
| 1.1543        | 5.0   | 105  | 0.9205          | 0.7049   |
| 0.9317        | 6.0   | 126  | 0.8121          | 0.7314   |
| 0.7891        | 7.0   | 147  | 0.6553          | 0.7986   |
| 0.6812        | 8.0   | 168  | 0.5720          | 0.8180   |
| 0.6348        | 9.0   | 189  | 0.5364          | 0.8180   |
| 0.5488        | 10.0  | 210  | 0.4780          | 0.8428   |
| 0.505         | 11.0  | 231  | 0.4540          | 0.8569   |
| 0.4758        | 12.0  | 252  | 0.3992          | 0.8852   |
| 0.4306        | 13.0  | 273  | 0.4280          | 0.8675   |
| 0.3952        | 14.0  | 294  | 0.4019          | 0.8781   |
| 0.3726        | 15.0  | 315  | 0.3794          | 0.8763   |
| 0.3191        | 16.0  | 336  | 0.3482          | 0.8958   |
| 0.3014        | 17.0  | 357  | 0.3372          | 0.8940   |
| 0.2785        | 18.0  | 378  | 0.3472          | 0.8993   |
| 0.2948        | 19.0  | 399  | 0.3246          | 0.9064   |
| 0.2618        | 20.0  | 420  | 0.3060          | 0.9081   |
| 0.2705        | 21.0  | 441  | 0.3122          | 0.9046   |
| 0.2479        | 22.0  | 462  | 0.3061          | 0.9028   |
| 0.2411        | 23.0  | 483  | 0.3040          | 0.9099   |
| 0.2556        | 24.0  | 504  | 0.2990          | 0.9099   |
| 0.2413        | 25.0  | 525  | 0.2978          | 0.9081   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0