---
license: apache-2.0
base_model: microsoft/swin-small-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-small-patch4-window7-224-finetuned-piid
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: val
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.776255707762557
---

<!-- 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-small-patch4-window7-224-finetuned-piid

This model is a fine-tuned version of [microsoft/swin-small-patch4-window7-224](https://huggingface.co/microsoft/swin-small-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6168
- Accuracy: 0.7763

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2327        | 0.98  | 20   | 1.1687          | 0.5114   |
| 0.7354        | 2.0   | 41   | 0.7696          | 0.6712   |
| 0.602         | 2.98  | 61   | 0.7198          | 0.7078   |
| 0.5809        | 4.0   | 82   | 0.5824          | 0.7397   |
| 0.4989        | 4.98  | 102  | 0.5331          | 0.7489   |
| 0.4364        | 6.0   | 123  | 0.6137          | 0.7489   |
| 0.3321        | 6.98  | 143  | 0.5839          | 0.7717   |
| 0.3           | 8.0   | 164  | 0.5246          | 0.7763   |
| 0.3024        | 8.98  | 184  | 0.5557          | 0.7717   |
| 0.3433        | 10.0  | 205  | 0.5258          | 0.7900   |
| 0.258         | 10.98 | 225  | 0.6354          | 0.7489   |
| 0.1595        | 12.0  | 246  | 0.5492          | 0.8219   |
| 0.2295        | 12.98 | 266  | 0.5889          | 0.7900   |
| 0.1956        | 14.0  | 287  | 0.5670          | 0.7900   |
| 0.2028        | 14.98 | 307  | 0.5460          | 0.7900   |
| 0.1514        | 16.0  | 328  | 0.6587          | 0.7900   |
| 0.0934        | 16.98 | 348  | 0.6131          | 0.7945   |
| 0.1323        | 18.0  | 369  | 0.6615          | 0.7900   |
| 0.1213        | 18.98 | 389  | 0.6192          | 0.7671   |
| 0.1028        | 19.51 | 400  | 0.6168          | 0.7763   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1