---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: SW2-RHS-DA
  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: 0.8598130841121495
---

<!-- 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-RHS-DA

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: 0.4541
- Accuracy: 0.8598

## 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
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0538        | 0.99  | 35   | 1.2866          | 0.4112   |
| 0.7464        | 2.0   | 71   | 0.6780          | 0.5888   |
| 0.7061        | 2.99  | 106  | 0.6851          | 0.5888   |
| 0.6951        | 4.0   | 142  | 0.6742          | 0.5888   |
| 0.6928        | 4.99  | 177  | 0.6917          | 0.4486   |
| 0.683         | 6.0   | 213  | 0.6531          | 0.5794   |
| 0.7013        | 6.99  | 248  | 0.7000          | 0.4486   |
| 0.6921        | 8.0   | 284  | 0.7519          | 0.5514   |
| 0.6166        | 8.99  | 319  | 0.5947          | 0.6822   |
| 0.6128        | 10.0  | 355  | 0.5434          | 0.7850   |
| 0.5737        | 10.99 | 390  | 0.5533          | 0.7570   |
| 0.5376        | 12.0  | 426  | 0.5347          | 0.7103   |
| 0.5056        | 12.99 | 461  | 0.4949          | 0.7664   |
| 0.5396        | 14.0  | 497  | 0.5151          | 0.7477   |
| 0.4826        | 14.99 | 532  | 0.5669          | 0.7196   |
| 0.4269        | 16.0  | 568  | 0.4796          | 0.7570   |
| 0.5004        | 16.99 | 603  | 0.4489          | 0.8037   |
| 0.4116        | 18.0  | 639  | 0.4362          | 0.8224   |
| 0.3776        | 18.99 | 674  | 0.5300          | 0.7570   |
| 0.3646        | 20.0  | 710  | 0.4175          | 0.8037   |
| 0.3683        | 20.99 | 745  | 0.4700          | 0.8224   |
| 0.3277        | 22.0  | 781  | 0.4707          | 0.8131   |
| 0.3534        | 22.99 | 816  | 0.5240          | 0.8131   |
| 0.3083        | 24.0  | 852  | 0.5012          | 0.8131   |
| 0.2829        | 24.99 | 887  | 0.4421          | 0.8318   |
| 0.2564        | 26.0  | 923  | 0.4548          | 0.8224   |
| 0.3136        | 26.99 | 958  | 0.4374          | 0.8318   |
| 0.2443        | 28.0  | 994  | 0.5277          | 0.8131   |
| 0.258         | 28.99 | 1029 | 0.4601          | 0.8224   |
| 0.2673        | 30.0  | 1065 | 0.4520          | 0.8318   |
| 0.2233        | 30.99 | 1100 | 0.4541          | 0.8598   |
| 0.2276        | 32.0  | 1136 | 0.4247          | 0.8505   |
| 0.2653        | 32.99 | 1171 | 0.4091          | 0.8505   |
| 0.2007        | 34.0  | 1207 | 0.4719          | 0.8505   |
| 0.2082        | 34.99 | 1242 | 0.4624          | 0.8411   |
| 0.1794        | 36.0  | 1278 | 0.4856          | 0.8318   |
| 0.1987        | 36.99 | 1313 | 0.4904          | 0.8224   |
| 0.2066        | 38.0  | 1349 | 0.4741          | 0.8505   |
| 0.1972        | 38.99 | 1384 | 0.4530          | 0.8505   |
| 0.2319        | 39.44 | 1400 | 0.4536          | 0.8505   |


### Framework versions

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