---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: SW2-DMAE-2
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6739130434782609
---

<!-- 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. -->

# SW2-DMAE-2

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: 1.0510
- Accuracy: 0.6739

## 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: 1.5e-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
- num_epochs: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.86  | 3    | 1.6269          | 0.1087   |
| No log        | 2.0   | 7    | 1.6078          | 0.1087   |
| 1.618         | 2.86  | 10   | 1.5852          | 0.1087   |
| 1.618         | 4.0   | 14   | 1.5398          | 0.1087   |
| 1.618         | 4.86  | 17   | 1.4948          | 0.1087   |
| 1.5162        | 6.0   | 21   | 1.4344          | 0.1087   |
| 1.5162        | 6.86  | 24   | 1.3879          | 0.1087   |
| 1.5162        | 8.0   | 28   | 1.3288          | 0.1739   |
| 1.3459        | 8.86  | 31   | 1.2926          | 0.4565   |
| 1.3459        | 10.0  | 35   | 1.2562          | 0.4565   |
| 1.3459        | 10.86 | 38   | 1.2384          | 0.4565   |
| 1.2384        | 12.0  | 42   | 1.2205          | 0.4565   |
| 1.2384        | 12.86 | 45   | 1.2174          | 0.4565   |
| 1.2384        | 14.0  | 49   | 1.2131          | 0.4565   |
| 1.2049        | 14.86 | 52   | 1.2104          | 0.4565   |
| 1.2049        | 16.0  | 56   | 1.2086          | 0.4565   |
| 1.2049        | 16.86 | 59   | 1.2076          | 0.4565   |
| 1.1815        | 18.0  | 63   | 1.2052          | 0.4565   |
| 1.1815        | 18.86 | 66   | 1.2049          | 0.4565   |
| 1.1826        | 20.0  | 70   | 1.2019          | 0.4565   |
| 1.1826        | 20.86 | 73   | 1.1960          | 0.4565   |
| 1.1826        | 22.0  | 77   | 1.1927          | 0.4565   |
| 1.1647        | 22.86 | 80   | 1.1928          | 0.4565   |
| 1.1647        | 24.0  | 84   | 1.1924          | 0.4565   |
| 1.1647        | 24.86 | 87   | 1.1903          | 0.4565   |
| 1.1568        | 26.0  | 91   | 1.1879          | 0.4565   |
| 1.1568        | 26.86 | 94   | 1.1913          | 0.4565   |
| 1.1568        | 28.0  | 98   | 1.2046          | 0.4783   |
| 1.1432        | 28.86 | 101  | 1.1934          | 0.4783   |
| 1.1432        | 30.0  | 105  | 1.1665          | 0.4783   |
| 1.1432        | 30.86 | 108  | 1.1601          | 0.4783   |
| 1.1112        | 32.0  | 112  | 1.1624          | 0.5      |
| 1.1112        | 32.86 | 115  | 1.1664          | 0.5217   |
| 1.1112        | 34.0  | 119  | 1.1692          | 0.5      |
| 1.1132        | 34.86 | 122  | 1.1513          | 0.5435   |
| 1.1132        | 36.0  | 126  | 1.1384          | 0.5870   |
| 1.1132        | 36.86 | 129  | 1.1274          | 0.6087   |
| 1.0642        | 38.0  | 133  | 1.1443          | 0.5870   |
| 1.0642        | 38.86 | 136  | 1.1651          | 0.5      |
| 1.0439        | 40.0  | 140  | 1.1493          | 0.5      |
| 1.0439        | 40.86 | 143  | 1.1331          | 0.5217   |
| 1.0439        | 42.0  | 147  | 1.1032          | 0.5870   |
| 1.0362        | 42.86 | 150  | 1.0988          | 0.6304   |
| 1.0362        | 44.0  | 154  | 1.1093          | 0.5870   |
| 1.0362        | 44.86 | 157  | 1.1101          | 0.5870   |
| 1.0177        | 46.0  | 161  | 1.0903          | 0.6304   |
| 1.0177        | 46.86 | 164  | 1.0691          | 0.6522   |
| 1.0177        | 48.0  | 168  | 1.0510          | 0.6739   |
| 1.0           | 48.86 | 171  | 1.0451          | 0.6522   |
| 1.0           | 50.0  | 175  | 1.0425          | 0.6522   |
| 1.0           | 50.86 | 178  | 1.0512          | 0.6087   |
| 0.9636        | 52.0  | 182  | 1.0441          | 0.6304   |
| 0.9636        | 52.86 | 185  | 1.0402          | 0.6522   |
| 0.9636        | 54.0  | 189  | 1.0161          | 0.6522   |
| 0.9744        | 54.86 | 192  | 1.0073          | 0.6522   |
| 0.9744        | 56.0  | 196  | 1.0048          | 0.6522   |
| 0.9744        | 56.86 | 199  | 0.9993          | 0.6522   |
| 0.9233        | 58.0  | 203  | 0.9939          | 0.6522   |
| 0.9233        | 58.86 | 206  | 0.9939          | 0.6522   |
| 0.9452        | 60.0  | 210  | 0.9975          | 0.6522   |
| 0.9452        | 60.86 | 213  | 0.9981          | 0.6087   |
| 0.9452        | 62.0  | 217  | 0.9985          | 0.6087   |
| 0.9183        | 62.86 | 220  | 0.9969          | 0.6087   |
| 0.9183        | 64.0  | 224  | 0.9958          | 0.6304   |
| 0.9183        | 64.86 | 227  | 0.9928          | 0.6087   |
| 0.9449        | 66.0  | 231  | 0.9906          | 0.6087   |
| 0.9449        | 66.86 | 234  | 0.9893          | 0.6304   |
| 0.9449        | 68.0  | 238  | 0.9881          | 0.6522   |
| 0.9154        | 68.57 | 240  | 0.9880          | 0.6522   |


### Framework versions

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