---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-spa_saloon_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: 0.9798083504449008
---

<!-- 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-tiny-patch4-window7-224-spa_saloon_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: 0.0639
- Accuracy: 0.9798

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.337         | 1.0   | 205  | 0.2108          | 0.9175   |
| 0.196         | 2.0   | 411  | 0.1137          | 0.9620   |
| 0.1502        | 3.0   | 616  | 0.1030          | 0.9668   |
| 0.1476        | 4.0   | 822  | 0.0815          | 0.9736   |
| 0.1532        | 5.0   | 1027 | 0.0815          | 0.9760   |
| 0.1311        | 6.0   | 1233 | 0.0667          | 0.9805   |
| 0.1212        | 7.0   | 1438 | 0.0675          | 0.9805   |
| 0.1637        | 8.0   | 1644 | 0.0697          | 0.9798   |
| 0.116         | 9.0   | 1849 | 0.0638          | 0.9812   |
| 0.085         | 9.98  | 2050 | 0.0639          | 0.9798   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1