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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV18

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: 1.4318
- Accuracy: 0.6731

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 3.3548        | 1.0     | 22   | 1.5527          | 0.3077   |
| 3.2091        | 2.0     | 44   | 1.5476          | 0.3077   |
| 2.9355        | 3.0     | 66   | 1.3747          | 0.4808   |
| 2.3577        | 4.0     | 88   | 1.3003          | 0.4231   |
| 1.4766        | 5.0     | 110  | 1.1989          | 0.4808   |
| 1.3704        | 6.0     | 132  | 1.0006          | 0.6538   |
| 1.118         | 7.0     | 154  | 1.0605          | 0.6154   |
| 1.0178        | 8.0     | 176  | 0.9814          | 0.5962   |
| 0.8974        | 9.0     | 198  | 1.0096          | 0.6538   |
| 0.672         | 10.0    | 220  | 1.1785          | 0.6154   |
| 0.6533        | 11.0    | 242  | 1.3520          | 0.5577   |
| 0.4788        | 12.0    | 264  | 0.9816          | 0.75     |
| 0.5707        | 13.0    | 286  | 1.0714          | 0.6538   |
| 0.424         | 14.0    | 308  | 1.2733          | 0.6923   |
| 0.4466        | 15.0    | 330  | 1.1687          | 0.7115   |
| 0.4284        | 16.0    | 352  | 1.1879          | 0.6731   |
| 0.4528        | 17.0    | 374  | 1.1845          | 0.6346   |
| 0.3062        | 18.0    | 396  | 1.2126          | 0.7115   |
| 0.2953        | 19.0    | 418  | 1.4019          | 0.6154   |
| 0.3169        | 20.0    | 440  | 1.3913          | 0.6538   |
| 0.3235        | 21.0    | 462  | 1.1455          | 0.6346   |
| 0.3069        | 22.0    | 484  | 1.4152          | 0.6538   |
| 0.2402        | 23.0    | 506  | 1.1008          | 0.7115   |
| 0.2055        | 24.0    | 528  | 1.2535          | 0.6538   |
| 0.265         | 25.0    | 550  | 1.3737          | 0.6538   |
| 0.2097        | 26.0    | 572  | 1.4048          | 0.6923   |
| 0.2185        | 27.0    | 594  | 1.3243          | 0.6923   |
| 0.1778        | 28.0    | 616  | 1.3771          | 0.6346   |
| 0.1815        | 29.0    | 638  | 1.3688          | 0.5769   |
| 0.2201        | 30.0    | 660  | 1.3827          | 0.6346   |
| 0.1808        | 31.0    | 682  | 1.3749          | 0.6731   |
| 0.2013        | 32.0    | 704  | 1.4271          | 0.6538   |
| 0.1822        | 33.0    | 726  | 1.4023          | 0.6923   |
| 0.1602        | 34.0    | 748  | 1.3908          | 0.6731   |
| 0.1303        | 35.0    | 770  | 1.4396          | 0.6731   |
| 0.1848        | 36.0    | 792  | 1.4828          | 0.6923   |
| 0.0982        | 37.0    | 814  | 1.4231          | 0.6923   |
| 0.1267        | 38.0    | 836  | 1.4148          | 0.6731   |
| 0.1467        | 39.0    | 858  | 1.3743          | 0.6731   |
| 0.0891        | 40.0    | 880  | 1.4194          | 0.6923   |
| 0.1252        | 41.0    | 902  | 1.4187          | 0.6923   |
| 0.1189        | 42.0    | 924  | 1.4043          | 0.6346   |
| 0.1328        | 43.0    | 946  | 1.4175          | 0.6731   |
| 0.172         | 44.0    | 968  | 1.4249          | 0.6731   |
| 0.1324        | 45.0    | 990  | 1.4320          | 0.6731   |
| 0.1363        | 46.0    | 1012 | 1.4320          | 0.6731   |
| 0.125         | 47.0    | 1034 | 1.4318          | 0.6731   |
| 0.1122        | 47.7442 | 1050 | 1.4318          | 0.6731   |


### Framework versions

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

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