---
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-abnormalities-classification-fold2
  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-abnormalities-classification-fold2

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: 0.0893
- Accuracy: 0.9688

## 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: 15

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.9549        | 0.9714  | 17   | 0.7206          | 0.7236   |
| 0.5426        | 2.0     | 35   | 0.3207          | 0.8686   |
| 0.3933        | 2.9714  | 52   | 0.2391          | 0.8970   |
| 0.2881        | 4.0     | 70   | 0.2387          | 0.8943   |
| 0.2524        | 4.9714  | 87   | 0.1485          | 0.9444   |
| 0.1997        | 6.0     | 105  | 0.1185          | 0.9566   |
| 0.1746        | 6.9714  | 122  | 0.1188          | 0.9553   |
| 0.1589        | 8.0     | 140  | 0.0990          | 0.9621   |
| 0.1369        | 8.9714  | 157  | 0.1044          | 0.9593   |
| 0.1281        | 10.0    | 175  | 0.0957          | 0.9675   |
| 0.1211        | 10.9714 | 192  | 0.1026          | 0.9607   |
| 0.1233        | 12.0    | 210  | 0.1258          | 0.9499   |
| 0.1141        | 12.9714 | 227  | 0.0861          | 0.9729   |
| 0.1021        | 14.0    | 245  | 0.0945          | 0.9648   |
| 0.1102        | 14.5714 | 255  | 0.0893          | 0.9688   |


### Framework versions

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