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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV66

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: 0.2728
- Accuracy: 0.9086

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1391        | 1.0   | 15   | 1.0750          | 0.4057   |
| 0.9921        | 2.0   | 30   | 0.9329          | 0.6857   |
| 0.8345        | 3.0   | 45   | 0.5657          | 0.8229   |
| 0.5658        | 4.0   | 60   | 0.4445          | 0.8343   |
| 0.5066        | 5.0   | 75   | 0.4037          | 0.84     |
| 0.4016        | 6.0   | 90   | 0.3566          | 0.8629   |
| 0.4143        | 7.0   | 105  | 0.3347          | 0.8686   |
| 0.3599        | 8.0   | 120  | 0.3101          | 0.8743   |
| 0.3245        | 9.0   | 135  | 0.3187          | 0.88     |
| 0.3025        | 10.0  | 150  | 0.2728          | 0.9086   |
| 0.2546        | 11.0  | 165  | 0.2887          | 0.8743   |
| 0.2963        | 12.0  | 180  | 0.3797          | 0.8571   |
| 0.27          | 13.0  | 195  | 0.4297          | 0.84     |
| 0.2374        | 14.0  | 210  | 0.4063          | 0.8457   |
| 0.2626        | 15.0  | 225  | 0.3277          | 0.8914   |
| 0.2268        | 16.0  | 240  | 0.3114          | 0.8914   |
| 0.1787        | 17.0  | 255  | 0.3716          | 0.8571   |
| 0.2187        | 18.0  | 270  | 0.3290          | 0.88     |
| 0.1818        | 19.0  | 285  | 0.3367          | 0.9029   |
| 0.1822        | 20.0  | 300  | 0.3245          | 0.8857   |
| 0.1747        | 21.0  | 315  | 0.3293          | 0.88     |
| 0.1728        | 22.0  | 330  | 0.3330          | 0.88     |
| 0.1688        | 23.0  | 345  | 0.3699          | 0.8857   |
| 0.1953        | 24.0  | 360  | 0.3193          | 0.9029   |
| 0.1677        | 25.0  | 375  | 0.3689          | 0.8914   |
| 0.1658        | 26.0  | 390  | 0.3698          | 0.8971   |
| 0.147         | 27.0  | 405  | 0.3759          | 0.8914   |
| 0.1599        | 28.0  | 420  | 0.4673          | 0.8571   |
| 0.1165        | 29.0  | 435  | 0.4239          | 0.88     |
| 0.1235        | 30.0  | 450  | 0.4119          | 0.8857   |
| 0.098         | 31.0  | 465  | 0.4140          | 0.8914   |
| 0.1042        | 32.0  | 480  | 0.4382          | 0.88     |
| 0.1052        | 33.0  | 495  | 0.4593          | 0.8743   |
| 0.1021        | 34.0  | 510  | 0.5186          | 0.8629   |
| 0.1074        | 35.0  | 525  | 0.4545          | 0.88     |
| 0.0964        | 36.0  | 540  | 0.4612          | 0.88     |
| 0.1047        | 37.0  | 555  | 0.4607          | 0.8743   |
| 0.1218        | 38.0  | 570  | 0.4805          | 0.8629   |
| 0.1073        | 39.0  | 585  | 0.4456          | 0.8914   |
| 0.0948        | 40.0  | 600  | 0.4985          | 0.8743   |
| 0.1087        | 41.0  | 615  | 0.4687          | 0.8857   |
| 0.1055        | 42.0  | 630  | 0.4863          | 0.8857   |
| 0.1082        | 43.0  | 645  | 0.4663          | 0.8914   |
| 0.0829        | 44.0  | 660  | 0.4579          | 0.8857   |
| 0.0774        | 45.0  | 675  | 0.4660          | 0.8857   |


### Framework versions

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

avanzada avanzada humeda no dmae