---
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-fold1
  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-fold1

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: 0.1102
- Accuracy: 0.9607

## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.9214        | 0.9714  | 17   | 0.7237          | 0.7249   |
| 0.5441        | 2.0     | 35   | 0.3606          | 0.8523   |
| 0.3592        | 2.9714  | 52   | 0.2474          | 0.9024   |
| 0.2732        | 4.0     | 70   | 0.2265          | 0.9173   |
| 0.2283        | 4.9714  | 87   | 0.1731          | 0.9404   |
| 0.1865        | 6.0     | 105  | 0.1808          | 0.9309   |
| 0.185         | 6.9714  | 122  | 0.1703          | 0.9201   |
| 0.1597        | 8.0     | 140  | 0.1262          | 0.9485   |
| 0.1545        | 8.9714  | 157  | 0.1375          | 0.9472   |
| 0.1237        | 10.0    | 175  | 0.1133          | 0.9580   |
| 0.1165        | 10.9714 | 192  | 0.1299          | 0.9512   |
| 0.1086        | 12.0    | 210  | 0.1118          | 0.9634   |
| 0.1129        | 12.9714 | 227  | 0.1101          | 0.9580   |
| 0.0898        | 14.0    | 245  | 0.1089          | 0.9607   |
| 0.0811        | 14.5714 | 255  | 0.1102          | 0.9607   |


### Framework versions

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