
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV71

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: 0.5977
- Accuracy: 0.9029

## 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: 6e-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: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1246        | 1.0   | 15   | 1.0559          | 0.4171   |
| 0.8728        | 2.0   | 30   | 0.7460          | 0.6971   |
| 0.6663        | 3.0   | 45   | 0.4563          | 0.8057   |
| 0.4632        | 4.0   | 60   | 0.4076          | 0.8286   |
| 0.4278        | 5.0   | 75   | 0.3670          | 0.84     |
| 0.361         | 6.0   | 90   | 0.3624          | 0.8457   |
| 0.3742        | 7.0   | 105  | 0.3504          | 0.8629   |
| 0.3313        | 8.0   | 120  | 0.2962          | 0.8629   |
| 0.2977        | 9.0   | 135  | 0.3321          | 0.8686   |
| 0.2589        | 10.0  | 150  | 0.3425          | 0.8629   |
| 0.2477        | 11.0  | 165  | 0.3982          | 0.8457   |
| 0.2187        | 12.0  | 180  | 0.5954          | 0.8514   |
| 0.2342        | 13.0  | 195  | 0.3745          | 0.8514   |
| 0.2444        | 14.0  | 210  | 0.5220          | 0.8629   |
| 0.2067        | 15.0  | 225  | 0.4433          | 0.8457   |
| 0.1882        | 16.0  | 240  | 0.3937          | 0.8629   |
| 0.199         | 17.0  | 255  | 0.5103          | 0.8629   |
| 0.1565        | 18.0  | 270  | 0.3608          | 0.8857   |
| 0.2068        | 19.0  | 285  | 0.3679          | 0.88     |
| 0.194         | 20.0  | 300  | 0.5581          | 0.8457   |
| 0.1654        | 21.0  | 315  | 0.5074          | 0.8686   |
| 0.1986        | 22.0  | 330  | 0.4395          | 0.88     |
| 0.1257        | 23.0  | 345  | 0.4293          | 0.8686   |
| 0.1976        | 24.0  | 360  | 0.4932          | 0.8571   |
| 0.1563        | 25.0  | 375  | 0.4254          | 0.8857   |
| 0.0985        | 26.0  | 390  | 0.5097          | 0.8686   |
| 0.1238        | 27.0  | 405  | 0.7264          | 0.8514   |
| 0.1577        | 28.0  | 420  | 0.4827          | 0.8571   |
| 0.1271        | 29.0  | 435  | 0.5305          | 0.8686   |
| 0.1002        | 30.0  | 450  | 0.5888          | 0.8629   |
| 0.1268        | 31.0  | 465  | 0.6433          | 0.8571   |
| 0.1153        | 32.0  | 480  | 0.8394          | 0.8343   |
| 0.1191        | 33.0  | 495  | 0.7475          | 0.84     |
| 0.1184        | 34.0  | 510  | 0.4884          | 0.8743   |
| 0.1332        | 35.0  | 525  | 0.5834          | 0.8857   |
| 0.1071        | 36.0  | 540  | 0.6279          | 0.8571   |
| 0.0886        | 37.0  | 555  | 0.6999          | 0.8629   |
| 0.0744        | 38.0  | 570  | 0.7295          | 0.8686   |
| 0.1274        | 39.0  | 585  | 0.6137          | 0.8914   |
| 0.0795        | 40.0  | 600  | 0.5706          | 0.8743   |
| 0.0962        | 41.0  | 615  | 0.6100          | 0.8857   |
| 0.094         | 42.0  | 630  | 0.6149          | 0.8743   |
| 0.0945        | 43.0  | 645  | 0.5689          | 0.88     |
| 0.0584        | 44.0  | 660  | 0.7019          | 0.8743   |
| 0.0676        | 45.0  | 675  | 0.6934          | 0.88     |
| 0.0763        | 46.0  | 690  | 0.6047          | 0.8914   |
| 0.0762        | 47.0  | 705  | 0.6064          | 0.88     |
| 0.0696        | 48.0  | 720  | 0.7336          | 0.8686   |
| 0.0555        | 49.0  | 735  | 0.6599          | 0.8743   |
| 0.0572        | 50.0  | 750  | 0.5977          | 0.9029   |
| 0.0648        | 51.0  | 765  | 0.6257          | 0.88     |
| 0.0705        | 52.0  | 780  | 0.6654          | 0.8857   |
| 0.0646        | 53.0  | 795  | 0.6813          | 0.8686   |
| 0.0795        | 54.0  | 810  | 0.6209          | 0.8743   |
| 0.0828        | 55.0  | 825  | 0.6457          | 0.8743   |
| 0.0674        | 56.0  | 840  | 0.6521          | 0.88     |


### Framework versions

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

avanzada avanzada humeda no dmae