---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-DMAE-da2-4e-5
  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: 0.6521739130434783
---

<!-- 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. -->

# swinv2-tiny-patch4-window8-256-DMAE-da2-4e-5

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: 0.8252
- Accuracy: 0.6522

## 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: 1
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 6.6265        | 0.96  | 11   | 7.9417          | 0.1087   |
| 6.1679        | 2.0   | 23   | 7.9339          | 0.1087   |
| 6.8561        | 2.96  | 34   | 7.9149          | 0.1087   |
| 6.399         | 4.0   | 46   | 7.8629          | 0.1087   |
| 6.7961        | 4.96  | 57   | 7.7408          | 0.1087   |
| 6.5019        | 6.0   | 69   | 7.4856          | 0.1087   |
| 6.085         | 6.96  | 80   | 7.1388          | 0.1087   |
| 6.014         | 8.0   | 92   | 6.7124          | 0.1087   |
| 5.6147        | 8.96  | 103  | 6.2444          | 0.1087   |
| 5.2206        | 10.0  | 115  | 5.6953          | 0.1087   |
| 4.9027        | 10.96 | 126  | 5.1300          | 0.1087   |
| 4.4278        | 12.0  | 138  | 4.4629          | 0.1087   |
| 4.0841        | 12.96 | 149  | 3.8089          | 0.1087   |
| 3.0004        | 14.0  | 161  | 3.0893          | 0.1087   |
| 2.5654        | 14.96 | 172  | 2.4630          | 0.1087   |
| 2.094         | 16.0  | 184  | 1.8911          | 0.1087   |
| 1.8348        | 16.96 | 195  | 1.5454          | 0.1087   |
| 1.5383        | 18.0  | 207  | 1.4124          | 0.1087   |
| 1.4068        | 18.96 | 218  | 1.4348          | 0.1087   |
| 1.379         | 20.0  | 230  | 1.4207          | 0.1522   |
| 1.3552        | 20.96 | 241  | 1.3786          | 0.3478   |
| 1.262         | 22.0  | 253  | 1.3580          | 0.4783   |
| 1.2235        | 22.96 | 264  | 1.4413          | 0.3696   |
| 1.2065        | 24.0  | 276  | 1.3013          | 0.1957   |
| 1.2196        | 24.96 | 287  | 1.3489          | 0.2609   |
| 1.1815        | 26.0  | 299  | 1.3158          | 0.3043   |
| 1.0469        | 26.96 | 310  | 1.2959          | 0.4565   |
| 0.9854        | 28.0  | 322  | 1.4712          | 0.5217   |
| 0.9443        | 28.96 | 333  | 1.2061          | 0.3261   |
| 0.9168        | 30.0  | 345  | 1.0655          | 0.4348   |
| 0.8138        | 30.96 | 356  | 1.0981          | 0.5435   |
| 0.8066        | 32.0  | 368  | 1.0023          | 0.6304   |
| 0.8035        | 32.96 | 379  | 0.9529          | 0.5652   |
| 0.7693        | 34.0  | 391  | 1.0104          | 0.5      |
| 0.6773        | 34.96 | 402  | 1.0684          | 0.5      |
| 0.6726        | 36.0  | 414  | 0.8252          | 0.6522   |
| 0.5859        | 36.96 | 425  | 0.8158          | 0.6304   |
| 0.6204        | 38.0  | 437  | 0.8518          | 0.6087   |
| 0.5921        | 38.26 | 440  | 0.8757          | 0.5870   |


### Framework versions

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