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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV19

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: 1.4438
- 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: 7e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- 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: 0.3
- num_epochs: 42

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6103        | 1.0   | 22   | 1.6051          | 0.2885   |
| 1.4727        | 2.0   | 44   | 1.4581          | 0.4808   |
| 1.0885        | 3.0   | 66   | 1.1148          | 0.5385   |
| 0.8317        | 4.0   | 88   | 1.1753          | 0.4808   |
| 0.5767        | 5.0   | 110  | 1.0842          | 0.5192   |
| 0.4983        | 6.0   | 132  | 0.9595          | 0.5769   |
| 0.4392        | 7.0   | 154  | 0.9108          | 0.6538   |
| 0.38          | 8.0   | 176  | 0.7973          | 0.6923   |
| 0.367         | 9.0   | 198  | 0.8772          | 0.6346   |
| 0.2892        | 10.0  | 220  | 0.9240          | 0.6346   |
| 0.2627        | 11.0  | 242  | 1.1102          | 0.6154   |
| 0.1956        | 12.0  | 264  | 0.8497          | 0.7115   |
| 0.2529        | 13.0  | 286  | 0.9588          | 0.6923   |
| 0.1933        | 14.0  | 308  | 1.4496          | 0.5962   |
| 0.2023        | 15.0  | 330  | 1.2467          | 0.6346   |
| 0.1725        | 16.0  | 352  | 1.1693          | 0.6731   |
| 0.1604        | 17.0  | 374  | 1.1374          | 0.6346   |
| 0.1909        | 18.0  | 396  | 0.9065          | 0.7115   |
| 0.1577        | 19.0  | 418  | 1.1488          | 0.6538   |
| 0.1323        | 20.0  | 440  | 1.3994          | 0.6923   |
| 0.1342        | 21.0  | 462  | 1.1350          | 0.6731   |
| 0.1024        | 22.0  | 484  | 1.2422          | 0.6538   |
| 0.1054        | 23.0  | 506  | 1.0670          | 0.75     |
| 0.0809        | 24.0  | 528  | 1.2367          | 0.6731   |
| 0.0856        | 25.0  | 550  | 1.1758          | 0.7308   |
| 0.0781        | 26.0  | 572  | 1.1735          | 0.6731   |
| 0.1136        | 27.0  | 594  | 1.5008          | 0.6923   |
| 0.0784        | 28.0  | 616  | 1.2966          | 0.7308   |
| 0.0648        | 29.0  | 638  | 1.2018          | 0.7115   |
| 0.0941        | 30.0  | 660  | 1.0879          | 0.6731   |
| 0.0654        | 31.0  | 682  | 1.2646          | 0.7115   |
| 0.0967        | 32.0  | 704  | 1.0537          | 0.75     |
| 0.0717        | 33.0  | 726  | 1.4332          | 0.7115   |
| 0.0715        | 34.0  | 748  | 1.2683          | 0.7308   |
| 0.0773        | 35.0  | 770  | 1.3363          | 0.6731   |
| 0.0767        | 36.0  | 792  | 1.3192          | 0.6731   |
| 0.0343        | 37.0  | 814  | 1.2926          | 0.7115   |
| 0.0524        | 38.0  | 836  | 1.4072          | 0.7115   |
| 0.052         | 39.0  | 858  | 1.4377          | 0.6923   |
| 0.0247        | 40.0  | 880  | 1.4420          | 0.6923   |
| 0.0256        | 41.0  | 902  | 1.4403          | 0.7115   |
| 0.0384        | 42.0  | 924  | 1.4438          | 0.7308   |


### Framework versions

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

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