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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV21

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: 0.8631
- Accuracy: 0.7308

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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: 42

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9302  | 10   | 1.5510          | 0.3462   |
| 6.5929        | 1.9302  | 20   | 1.4802          | 0.2692   |
| 5.6252        | 2.9302  | 30   | 1.1115          | 0.4038   |
| 3.874         | 3.9302  | 40   | 0.9996          | 0.5577   |
| 2.7168        | 4.9302  | 50   | 0.8436          | 0.6538   |
| 2.2435        | 5.9302  | 60   | 0.9320          | 0.6154   |
| 2.2435        | 6.9302  | 70   | 0.8412          | 0.6346   |
| 1.9334        | 7.9302  | 80   | 0.8622          | 0.6731   |
| 1.6303        | 8.9302  | 90   | 0.9152          | 0.7115   |
| 1.2748        | 9.9302  | 100  | 0.9721          | 0.6731   |
| 1.0945        | 10.9302 | 110  | 1.0827          | 0.6538   |
| 0.8395        | 11.9302 | 120  | 0.9153          | 0.7115   |
| 0.8395        | 12.9302 | 130  | 0.8631          | 0.7308   |
| 0.8587        | 13.9302 | 140  | 1.1039          | 0.6538   |
| 0.8574        | 14.9302 | 150  | 1.0463          | 0.6923   |
| 0.7096        | 15.9302 | 160  | 0.9991          | 0.7115   |
| 0.6606        | 16.9302 | 170  | 1.0519          | 0.6731   |
| 0.5513        | 17.9302 | 180  | 1.0865          | 0.7115   |
| 0.5513        | 18.9302 | 190  | 1.1140          | 0.6731   |
| 0.61          | 19.9302 | 200  | 1.0290          | 0.6731   |
| 0.5278        | 20.9302 | 210  | 1.1003          | 0.6923   |
| 0.4639        | 21.9302 | 220  | 1.2472          | 0.6538   |
| 0.4719        | 22.9302 | 230  | 1.1546          | 0.6923   |
| 0.4212        | 23.9302 | 240  | 1.1084          | 0.7308   |
| 0.4212        | 24.9302 | 250  | 1.2953          | 0.6731   |
| 0.4109        | 25.9302 | 260  | 1.1868          | 0.7308   |
| 0.4236        | 26.9302 | 270  | 1.2560          | 0.6346   |
| 0.3638        | 27.9302 | 280  | 1.2161          | 0.7115   |
| 0.3944        | 28.9302 | 290  | 1.1582          | 0.7308   |
| 0.3621        | 29.9302 | 300  | 1.2993          | 0.6923   |
| 0.3621        | 30.9302 | 310  | 1.1401          | 0.7115   |
| 0.3203        | 31.9302 | 320  | 1.3228          | 0.7115   |
| 0.3014        | 32.9302 | 330  | 1.2813          | 0.6923   |
| 0.3464        | 33.9302 | 340  | 1.4768          | 0.6538   |
| 0.2891        | 34.9302 | 350  | 1.2304          | 0.7308   |
| 0.3153        | 35.9302 | 360  | 1.3096          | 0.6923   |
| 0.3153        | 36.9302 | 370  | 1.3565          | 0.7115   |
| 0.2762        | 37.9302 | 380  | 1.2931          | 0.6923   |
| 0.3191        | 38.9302 | 390  | 1.2441          | 0.7308   |
| 0.3009        | 39.9302 | 400  | 1.2110          | 0.7308   |
| 0.2645        | 40.9302 | 410  | 1.2433          | 0.7115   |
| 0.2497        | 41.9302 | 420  | 1.2461          | 0.6923   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0

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