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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV73

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: 0.3467
- Accuracy: 0.8914

## 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.1143        | 1.0     | 15   | 1.0550          | 0.5886   |
| 0.9057        | 2.0     | 30   | 0.7895          | 0.7314   |
| 0.7128        | 3.0     | 45   | 0.5484          | 0.76     |
| 0.491         | 4.0     | 60   | 0.4717          | 0.7829   |
| 0.4667        | 5.0     | 75   | 0.3817          | 0.8457   |
| 0.39          | 6.0     | 90   | 0.3647          | 0.88     |
| 0.3975        | 7.0     | 105  | 0.3604          | 0.8571   |
| 0.3496        | 8.0     | 120  | 0.3397          | 0.8457   |
| 0.3546        | 9.0     | 135  | 0.3968          | 0.84     |
| 0.2798        | 10.0    | 150  | 0.3983          | 0.8571   |
| 0.2813        | 11.0    | 165  | 0.3591          | 0.8571   |
| 0.2178        | 12.0    | 180  | 0.4332          | 0.8571   |
| 0.234         | 13.0    | 195  | 0.3892          | 0.8686   |
| 0.2539        | 14.0    | 210  | 0.3944          | 0.8743   |
| 0.2147        | 15.0    | 225  | 0.5366          | 0.8286   |
| 0.2045        | 16.0    | 240  | 0.3467          | 0.8914   |
| 0.1826        | 17.0    | 255  | 0.4077          | 0.8629   |
| 0.1703        | 18.0    | 270  | 0.4043          | 0.8743   |
| 0.1928        | 19.0    | 285  | 0.4470          | 0.88     |
| 0.1853        | 20.0    | 300  | 0.4742          | 0.8857   |
| 0.1503        | 21.0    | 315  | 0.5047          | 0.8743   |
| 0.1692        | 22.0    | 330  | 0.4166          | 0.8686   |
| 0.1436        | 23.0    | 345  | 0.4770          | 0.8686   |
| 0.1715        | 24.0    | 360  | 0.4240          | 0.8514   |
| 0.1449        | 25.0    | 375  | 0.4297          | 0.8743   |
| 0.1051        | 26.0    | 390  | 0.5423          | 0.8743   |
| 0.1055        | 27.0    | 405  | 0.5705          | 0.8743   |
| 0.1407        | 28.0    | 420  | 0.5883          | 0.8743   |
| 0.1463        | 29.0    | 435  | 0.4944          | 0.8857   |
| 0.1413        | 30.0    | 450  | 0.5196          | 0.8914   |
| 0.1521        | 31.0    | 465  | 0.6213          | 0.8571   |
| 0.1318        | 32.0    | 480  | 0.7071          | 0.84     |
| 0.1357        | 33.0    | 495  | 0.5737          | 0.8743   |
| 0.1182        | 34.0    | 510  | 0.5457          | 0.88     |
| 0.1382        | 35.0    | 525  | 0.5622          | 0.8743   |
| 0.1108        | 36.0    | 540  | 0.5403          | 0.88     |
| 0.0948        | 37.0    | 555  | 0.6038          | 0.8629   |
| 0.0964        | 38.0    | 570  | 0.6299          | 0.8743   |
| 0.1035        | 39.0    | 585  | 0.5474          | 0.8857   |
| 0.0892        | 40.0    | 600  | 0.5423          | 0.8914   |
| 0.1121        | 41.0    | 615  | 0.5783          | 0.8686   |
| 0.1119        | 42.0    | 630  | 0.6223          | 0.8743   |
| 0.1103        | 43.0    | 645  | 0.6355          | 0.88     |
| 0.0934        | 44.0    | 660  | 0.5847          | 0.88     |
| 0.0861        | 45.0    | 675  | 0.6008          | 0.88     |
| 0.0933        | 46.0    | 690  | 0.6066          | 0.88     |
| 0.0909        | 46.6780 | 700  | 0.6084          | 0.88     |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.19.0
- Tokenizers 0.21.1

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