---
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-PE
  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: 0.797979797979798
---

<!-- 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-PE

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: 0.4489
- Accuracy: 0.7980

## 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: 0.0025
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6872        | 1.0   | 11   | 0.6535          | 0.6061   |
| 0.7287        | 2.0   | 22   | 0.6601          | 0.6397   |
| 0.7212        | 3.0   | 33   | 0.6740          | 0.5657   |
| 0.6947        | 4.0   | 44   | 0.6531          | 0.6532   |
| 0.6783        | 5.0   | 55   | 0.6739          | 0.5724   |
| 0.6816        | 6.0   | 66   | 0.6274          | 0.6599   |
| 0.6428        | 7.0   | 77   | 0.6671          | 0.6330   |
| 0.6928        | 8.0   | 88   | 0.6380          | 0.6498   |
| 0.6767        | 9.0   | 99   | 0.6875          | 0.6061   |
| 0.6918        | 10.0  | 110  | 0.6859          | 0.5690   |
| 0.6845        | 11.0  | 121  | 0.6810          | 0.5657   |
| 0.6826        | 12.0  | 132  | 0.6919          | 0.5185   |
| 0.6877        | 13.0  | 143  | 0.6693          | 0.6061   |
| 0.6709        | 14.0  | 154  | 0.6660          | 0.5690   |
| 0.6707        | 15.0  | 165  | 0.6764          | 0.5690   |
| 0.6703        | 16.0  | 176  | 0.6467          | 0.6296   |
| 0.6629        | 17.0  | 187  | 0.6471          | 0.6431   |
| 0.6557        | 18.0  | 198  | 0.6597          | 0.6229   |
| 0.659         | 19.0  | 209  | 0.6451          | 0.6027   |
| 0.65          | 20.0  | 220  | 0.6638          | 0.6094   |
| 0.6453        | 21.0  | 231  | 0.6544          | 0.6162   |
| 0.6426        | 22.0  | 242  | 0.6565          | 0.5825   |
| 0.6339        | 23.0  | 253  | 0.6743          | 0.6296   |
| 0.6236        | 24.0  | 264  | 0.6669          | 0.5960   |
| 0.6427        | 25.0  | 275  | 0.6379          | 0.6532   |
| 0.6439        | 26.0  | 286  | 0.6361          | 0.6263   |
| 0.6212        | 27.0  | 297  | 0.6540          | 0.6465   |
| 0.6186        | 28.0  | 308  | 0.5925          | 0.6700   |
| 0.6162        | 29.0  | 319  | 0.6224          | 0.6734   |
| 0.6237        | 30.0  | 330  | 0.6018          | 0.6667   |
| 0.6061        | 31.0  | 341  | 0.5735          | 0.6801   |
| 0.6138        | 32.0  | 352  | 0.6425          | 0.6566   |
| 0.595         | 33.0  | 363  | 0.5827          | 0.6768   |
| 0.5869        | 34.0  | 374  | 0.5956          | 0.7172   |
| 0.577         | 35.0  | 385  | 0.5458          | 0.7003   |
| 0.5766        | 36.0  | 396  | 0.5603          | 0.6869   |
| 0.5726        | 37.0  | 407  | 0.5339          | 0.7340   |
| 0.5702        | 38.0  | 418  | 0.5577          | 0.7138   |
| 0.5762        | 39.0  | 429  | 0.5262          | 0.7374   |
| 0.5543        | 40.0  | 440  | 0.5091          | 0.7441   |
| 0.5339        | 41.0  | 451  | 0.5185          | 0.7542   |
| 0.5428        | 42.0  | 462  | 0.5023          | 0.7542   |
| 0.5349        | 43.0  | 473  | 0.5439          | 0.7306   |
| 0.5319        | 44.0  | 484  | 0.4745          | 0.7811   |
| 0.5294        | 45.0  | 495  | 0.5432          | 0.7172   |
| 0.5314        | 46.0  | 506  | 0.4511          | 0.7912   |
| 0.5073        | 47.0  | 517  | 0.4379          | 0.8047   |
| 0.5028        | 48.0  | 528  | 0.4487          | 0.7980   |
| 0.4985        | 49.0  | 539  | 0.4550          | 0.7946   |
| 0.4826        | 50.0  | 550  | 0.4489          | 0.7980   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3