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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV67

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2829
- Accuracy: 0.92

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 45
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.103         | 1.0     | 18   | 1.0588          | 0.4      |
| 0.9007        | 2.0     | 36   | 0.5651          | 0.8229   |
| 0.497         | 3.0     | 54   | 0.3559          | 0.8743   |
| 0.4178        | 4.0     | 72   | 0.4171          | 0.7886   |
| 0.4303        | 5.0     | 90   | 0.6884          | 0.7314   |
| 0.485         | 6.0     | 108  | 0.3255          | 0.8629   |
| 0.3345        | 7.0     | 126  | 0.2631          | 0.9029   |
| 0.3058        | 8.0     | 144  | 0.3533          | 0.8343   |
| 0.35          | 9.0     | 162  | 0.2853          | 0.8686   |
| 0.2535        | 10.0    | 180  | 0.2529          | 0.9143   |
| 0.21          | 11.0    | 198  | 0.3806          | 0.84     |
| 0.2414        | 12.0    | 216  | 0.2829          | 0.92     |
| 0.1978        | 13.0    | 234  | 0.3011          | 0.9143   |
| 0.1683        | 14.0    | 252  | 0.2486          | 0.9086   |
| 0.2351        | 15.0    | 270  | 0.3612          | 0.8629   |
| 0.264         | 16.0    | 288  | 0.3643          | 0.88     |
| 0.1714        | 17.0    | 306  | 0.2481          | 0.9086   |
| 0.1714        | 18.0    | 324  | 0.3479          | 0.8914   |
| 0.1886        | 19.0    | 342  | 0.2644          | 0.9029   |
| 0.1522        | 20.0    | 360  | 0.2587          | 0.8971   |
| 0.1468        | 21.0    | 378  | 0.2832          | 0.9029   |
| 0.1364        | 22.0    | 396  | 0.2830          | 0.9029   |
| 0.1294        | 23.0    | 414  | 0.2954          | 0.8914   |
| 0.122         | 24.0    | 432  | 0.3801          | 0.8743   |
| 0.1114        | 25.0    | 450  | 0.3375          | 0.9029   |
| 0.12          | 26.0    | 468  | 0.3696          | 0.8743   |
| 0.121         | 27.0    | 486  | 0.3460          | 0.8857   |
| 0.1056        | 28.0    | 504  | 0.3296          | 0.9029   |
| 0.0941        | 29.0    | 522  | 0.3977          | 0.8971   |
| 0.0882        | 30.0    | 540  | 0.3436          | 0.8914   |
| 0.1131        | 31.0    | 558  | 0.3397          | 0.8914   |
| 0.0959        | 32.0    | 576  | 0.3420          | 0.8971   |
| 0.1058        | 33.0    | 594  | 0.3312          | 0.8971   |
| 0.0707        | 34.0    | 612  | 0.3917          | 0.8857   |
| 0.0885        | 35.0    | 630  | 0.3855          | 0.88     |
| 0.0788        | 36.0    | 648  | 0.3519          | 0.8857   |
| 0.112         | 37.0    | 666  | 0.3473          | 0.8914   |
| 0.0588        | 38.0    | 684  | 0.3718          | 0.9029   |
| 0.0963        | 39.0    | 702  | 0.4022          | 0.88     |
| 0.0681        | 40.0    | 720  | 0.3574          | 0.8971   |
| 0.0841        | 41.0    | 738  | 0.3621          | 0.88     |
| 0.0739        | 42.0    | 756  | 0.3782          | 0.8914   |
| 0.0649        | 42.5217 | 765  | 0.3766          | 0.8914   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1

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