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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV4

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: 0.9551
- Accuracy: 0.7115

## 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: 2
- total_train_batch_size: 32
- 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: 0.05
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.1112        | 1.0   | 23   | 1.4616          | 0.4423   |
| 2.4301        | 2.0   | 46   | 1.3378          | 0.3846   |
| 1.8107        | 3.0   | 69   | 1.1497          | 0.4423   |
| 1.3272        | 4.0   | 92   | 1.2177          | 0.5      |
| 1.2039        | 5.0   | 115  | 1.1250          | 0.5577   |
| 1.0311        | 6.0   | 138  | 1.0660          | 0.5577   |
| 1.0515        | 7.0   | 161  | 1.2242          | 0.5      |
| 0.8709        | 8.0   | 184  | 1.0952          | 0.5962   |
| 0.677         | 9.0   | 207  | 1.1033          | 0.5385   |
| 0.6763        | 10.0  | 230  | 0.9551          | 0.7115   |
| 0.5749        | 11.0  | 253  | 1.0428          | 0.6346   |
| 0.4896        | 12.0  | 276  | 1.0981          | 0.6538   |
| 0.4817        | 13.0  | 299  | 1.3429          | 0.4808   |
| 0.4264        | 14.0  | 322  | 1.3040          | 0.6154   |
| 0.5637        | 15.0  | 345  | 1.2592          | 0.4808   |
| 0.3846        | 16.0  | 368  | 1.1849          | 0.6154   |
| 0.5337        | 17.0  | 391  | 1.2025          | 0.6346   |
| 0.34          | 18.0  | 414  | 1.0894          | 0.6346   |
| 0.3511        | 19.0  | 437  | 1.2145          | 0.6346   |
| 0.2539        | 20.0  | 460  | 1.1755          | 0.6346   |
| 0.2683        | 21.0  | 483  | 1.2359          | 0.6731   |
| 0.3144        | 22.0  | 506  | 1.2633          | 0.6538   |
| 0.3249        | 23.0  | 529  | 1.2980          | 0.6346   |
| 0.2363        | 24.0  | 552  | 1.1872          | 0.6538   |
| 0.2876        | 25.0  | 575  | 1.2377          | 0.6923   |
| 0.2694        | 26.0  | 598  | 1.2695          | 0.6538   |
| 0.2307        | 27.0  | 621  | 1.2481          | 0.6731   |
| 0.2508        | 28.0  | 644  | 1.3112          | 0.6731   |
| 0.3558        | 29.0  | 667  | 1.3209          | 0.6731   |
| 0.2418        | 30.0  | 690  | 1.3233          | 0.6538   |


### 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