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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV7

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: 0.9241
- Accuracy: 0.6923

## 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: 2e-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: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6286        | 1.0   | 12   | 1.5624          | 0.2692   |
| 1.5581        | 2.0   | 24   | 1.4706          | 0.5192   |
| 1.4708        | 3.0   | 36   | 1.2967          | 0.5385   |
| 1.3022        | 4.0   | 48   | 1.1556          | 0.4615   |
| 0.9735        | 5.0   | 60   | 1.0354          | 0.5385   |
| 0.7914        | 6.0   | 72   | 1.1014          | 0.4423   |
| 0.7376        | 7.0   | 84   | 1.1087          | 0.4808   |
| 0.692         | 8.0   | 96   | 0.9630          | 0.6346   |
| 0.6586        | 9.0   | 108  | 0.9429          | 0.6346   |
| 0.5799        | 10.0  | 120  | 0.9332          | 0.6346   |
| 0.5557        | 11.0  | 132  | 1.1712          | 0.5192   |
| 0.5233        | 12.0  | 144  | 1.0447          | 0.5577   |
| 0.4427        | 13.0  | 156  | 0.8928          | 0.6538   |
| 0.5043        | 14.0  | 168  | 1.0120          | 0.5962   |
| 0.4167        | 15.0  | 180  | 0.9241          | 0.6923   |
| 0.4601        | 16.0  | 192  | 0.8848          | 0.6538   |
| 0.4619        | 17.0  | 204  | 0.9239          | 0.6923   |
| 0.3822        | 18.0  | 216  | 0.9208          | 0.6731   |
| 0.3707        | 19.0  | 228  | 1.0374          | 0.5769   |
| 0.365         | 20.0  | 240  | 0.9900          | 0.6538   |
| 0.3412        | 21.0  | 252  | 1.0541          | 0.6538   |
| 0.3265        | 22.0  | 264  | 0.9913          | 0.6731   |
| 0.3096        | 23.0  | 276  | 1.0355          | 0.6346   |
| 0.3603        | 24.0  | 288  | 0.9986          | 0.6538   |
| 0.2924        | 25.0  | 300  | 1.0046          | 0.6731   |
| 0.3489        | 26.0  | 312  | 1.0560          | 0.6346   |
| 0.2974        | 27.0  | 324  | 1.0076          | 0.6538   |
| 0.2924        | 28.0  | 336  | 1.0164          | 0.6538   |
| 0.3369        | 29.0  | 348  | 1.0260          | 0.6346   |
| 0.2884        | 30.0  | 360  | 1.0293          | 0.6346   |


### Framework versions

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

avanzada avanzada humeda leve moderada no dmae