
<!-- 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-DAV56

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: 0.8748
- Accuracy: 0.7308

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 45
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.8421  | 4    | 1.5618          | 0.3269   |
| No log        | 1.8421  | 8    | 1.5396          | 0.4423   |
| 1.7209        | 2.8421  | 12   | 1.5124          | 0.3077   |
| 1.7209        | 3.8421  | 16   | 1.4679          | 0.3269   |
| 1.7209        | 4.8421  | 20   | 1.4130          | 0.3462   |
| 1.5864        | 5.8421  | 24   | 1.3107          | 0.5385   |
| 1.5864        | 6.8421  | 28   | 1.2112          | 0.5385   |
| 1.5864        | 7.8421  | 32   | 1.1194          | 0.5962   |
| 1.2629        | 8.8421  | 36   | 1.0422          | 0.5962   |
| 1.2629        | 9.8421  | 40   | 0.9706          | 0.6538   |
| 1.2629        | 10.8421 | 44   | 0.9638          | 0.6538   |
| 0.951         | 11.8421 | 48   | 0.9906          | 0.6154   |
| 0.951         | 12.8421 | 52   | 0.9890          | 0.5962   |
| 0.951         | 13.8421 | 56   | 0.9110          | 0.6538   |
| 0.7947        | 14.8421 | 60   | 0.9282          | 0.6731   |
| 0.7947        | 15.8421 | 64   | 0.9315          | 0.6538   |
| 0.7947        | 16.8421 | 68   | 0.9230          | 0.6154   |
| 0.7143        | 17.8421 | 72   | 0.9068          | 0.6538   |
| 0.7143        | 18.8421 | 76   | 0.8997          | 0.6154   |
| 0.7143        | 19.8421 | 80   | 0.8648          | 0.6923   |
| 0.6329        | 20.8421 | 84   | 0.8624          | 0.6538   |
| 0.6329        | 21.8421 | 88   | 0.8737          | 0.6154   |
| 0.6329        | 22.8421 | 92   | 0.8636          | 0.6731   |
| 0.5508        | 23.8421 | 96   | 0.8545          | 0.6538   |
| 0.5508        | 24.8421 | 100  | 0.8617          | 0.6731   |
| 0.5508        | 25.8421 | 104  | 0.8635          | 0.6346   |
| 0.5009        | 26.8421 | 108  | 0.8650          | 0.6346   |
| 0.5009        | 27.8421 | 112  | 0.8638          | 0.6538   |
| 0.5009        | 28.8421 | 116  | 0.8730          | 0.6538   |
| 0.5286        | 29.8421 | 120  | 0.8886          | 0.6346   |
| 0.5286        | 30.8421 | 124  | 0.8827          | 0.6538   |
| 0.5286        | 31.8421 | 128  | 0.8748          | 0.7308   |
| 0.4559        | 32.8421 | 132  | 0.8671          | 0.7115   |
| 0.4559        | 33.8421 | 136  | 0.8727          | 0.6731   |
| 0.4559        | 34.8421 | 140  | 0.8755          | 0.7115   |
| 0.4704        | 35.8421 | 144  | 0.8760          | 0.7308   |
| 0.4704        | 36.8421 | 148  | 0.8786          | 0.7308   |
| 0.4704        | 37.8421 | 152  | 0.8781          | 0.7308   |
| 0.4582        | 38.8421 | 156  | 0.8771          | 0.7308   |
| 0.4582        | 39.8421 | 160  | 0.8754          | 0.7308   |
| 0.4582        | 40.8421 | 164  | 0.8741          | 0.7308   |
| 0.4538        | 41.8421 | 168  | 0.8742          | 0.7308   |
| 0.4538        | 42.8421 | 172  | 0.8740          | 0.7308   |
| 0.4538        | 43.8421 | 176  | 0.8740          | 0.7308   |
| 0.4476        | 44.8421 | 180  | 0.8741          | 0.7308   |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0

avanzada avanzada humeda leve moderada no dmae