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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV65

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: 0.4432
- 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: 45
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1096        | 1.0   | 15   | 1.0206          | 0.48     |
| 0.7949        | 2.0   | 30   | 0.5637          | 0.8057   |
| 0.6305        | 3.0   | 45   | 0.3961          | 0.8457   |
| 0.4475        | 4.0   | 60   | 0.3464          | 0.8629   |
| 0.4342        | 5.0   | 75   | 0.3489          | 0.8629   |
| 0.3843        | 6.0   | 90   | 0.3304          | 0.8457   |
| 0.3059        | 7.0   | 105  | 0.3037          | 0.88     |
| 0.2993        | 8.0   | 120  | 0.3286          | 0.8686   |
| 0.2799        | 9.0   | 135  | 0.4499          | 0.8457   |
| 0.302         | 10.0  | 150  | 0.2965          | 0.8857   |
| 0.2445        | 11.0  | 165  | 0.2569          | 0.8857   |
| 0.2317        | 12.0  | 180  | 0.4269          | 0.8286   |
| 0.2189        | 13.0  | 195  | 0.4250          | 0.8514   |
| 0.2001        | 14.0  | 210  | 0.3725          | 0.8743   |
| 0.1924        | 15.0  | 225  | 0.3042          | 0.8571   |
| 0.1617        | 16.0  | 240  | 0.4525          | 0.8686   |
| 0.131         | 17.0  | 255  | 0.4021          | 0.8457   |
| 0.1491        | 18.0  | 270  | 0.3316          | 0.8571   |
| 0.1576        | 19.0  | 285  | 0.3288          | 0.8857   |
| 0.1189        | 20.0  | 300  | 0.3464          | 0.88     |
| 0.1384        | 21.0  | 315  | 0.3618          | 0.8857   |
| 0.1109        | 22.0  | 330  | 0.3548          | 0.8914   |
| 0.0985        | 23.0  | 345  | 0.3908          | 0.8857   |
| 0.1095        | 24.0  | 360  | 0.4517          | 0.8743   |
| 0.1007        | 25.0  | 375  | 0.5406          | 0.8743   |
| 0.192         | 26.0  | 390  | 0.5257          | 0.8686   |
| 0.093         | 27.0  | 405  | 0.4442          | 0.8686   |
| 0.1337        | 28.0  | 420  | 0.5376          | 0.8629   |
| 0.0737        | 29.0  | 435  | 0.4627          | 0.8686   |
| 0.0932        | 30.0  | 450  | 0.4371          | 0.8914   |
| 0.0638        | 31.0  | 465  | 0.4741          | 0.8971   |
| 0.0796        | 32.0  | 480  | 0.4220          | 0.88     |
| 0.0674        | 33.0  | 495  | 0.4432          | 0.9029   |
| 0.0466        | 34.0  | 510  | 0.4385          | 0.8914   |
| 0.0586        | 35.0  | 525  | 0.4614          | 0.8971   |
| 0.0634        | 36.0  | 540  | 0.4855          | 0.8857   |
| 0.0867        | 37.0  | 555  | 0.4716          | 0.88     |
| 0.0721        | 38.0  | 570  | 0.4353          | 0.8914   |
| 0.0572        | 39.0  | 585  | 0.4443          | 0.8914   |
| 0.0613        | 40.0  | 600  | 0.4655          | 0.8857   |
| 0.0911        | 41.0  | 615  | 0.4462          | 0.8971   |
| 0.0691        | 42.0  | 630  | 0.4922          | 0.88     |
| 0.0767        | 43.0  | 645  | 0.4702          | 0.8743   |
| 0.0763        | 44.0  | 660  | 0.4670          | 0.8743   |
| 0.055         | 45.0  | 675  | 0.4692          | 0.8686   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1

avanzada avanzada humeda no dmae