---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: SWv2-DMAE-H-5-p-clean-fix-U-40-Cross-3
  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: 0.8390804597701149
---

<!-- 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. -->

# SWv2-DMAE-H-5-p-clean-fix-U-40-Cross-3

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4952
- Accuracy: 0.8391

## 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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.609         | 0.96  | 13   | 1.6081          | 0.1954   |
| 1.6048        | 2.0   | 27   | 1.5943          | 0.1954   |
| 1.5299        | 2.96  | 40   | 1.5695          | 0.1954   |
| 1.4527        | 4.0   | 54   | 1.4408          | 0.2184   |
| 1.3442        | 4.96  | 67   | 1.1869          | 0.5632   |
| 1.114         | 6.0   | 81   | 0.9027          | 0.6897   |
| 0.9651        | 6.96  | 94   | 0.7102          | 0.7586   |
| 0.8893        | 8.0   | 108  | 0.8029          | 0.6322   |
| 0.7704        | 8.96  | 121  | 0.5880          | 0.7816   |
| 0.6737        | 10.0  | 135  | 0.5514          | 0.8161   |
| 0.6713        | 10.96 | 148  | 0.4952          | 0.8391   |
| 0.6927        | 12.0  | 162  | 0.5375          | 0.8046   |
| 0.6031        | 12.96 | 175  | 0.5099          | 0.7931   |
| 0.542         | 14.0  | 189  | 0.5453          | 0.8046   |
| 0.511         | 14.96 | 202  | 0.5673          | 0.7701   |
| 0.4901        | 16.0  | 216  | 0.6610          | 0.7931   |
| 0.4824        | 16.96 | 229  | 0.5610          | 0.8046   |
| 0.4685        | 18.0  | 243  | 0.5992          | 0.7931   |
| 0.4442        | 18.96 | 256  | 0.5958          | 0.8161   |
| 0.4676        | 20.0  | 270  | 0.5621          | 0.8391   |
| 0.4231        | 20.96 | 283  | 0.5877          | 0.8161   |
| 0.3795        | 22.0  | 297  | 0.6075          | 0.8046   |
| 0.3645        | 22.96 | 310  | 0.6449          | 0.8046   |
| 0.366         | 24.0  | 324  | 0.6480          | 0.8161   |
| 0.344         | 24.96 | 337  | 0.6409          | 0.8276   |
| 0.2833        | 26.0  | 351  | 0.6246          | 0.8161   |
| 0.326         | 26.96 | 364  | 0.6491          | 0.8276   |
| 0.3416        | 28.0  | 378  | 0.6778          | 0.8161   |
| 0.2942        | 28.96 | 391  | 0.6374          | 0.8276   |
| 0.2767        | 30.0  | 405  | 0.6426          | 0.8276   |
| 0.2569        | 30.96 | 418  | 0.6631          | 0.8276   |
| 0.2889        | 32.0  | 432  | 0.6818          | 0.8161   |
| 0.2701        | 32.96 | 445  | 0.6889          | 0.8046   |
| 0.2553        | 34.0  | 459  | 0.6986          | 0.8161   |
| 0.2401        | 34.96 | 472  | 0.6985          | 0.8046   |
| 0.2536        | 36.0  | 486  | 0.7015          | 0.8046   |
| 0.2738        | 36.96 | 499  | 0.6940          | 0.8046   |
| 0.2304        | 38.0  | 513  | 0.6951          | 0.8046   |
| 0.3081        | 38.52 | 520  | 0.6951          | 0.8046   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0