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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV6

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: 1.0899
- Accuracy: 0.5962

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.65          | 1.0   | 12   | 1.5637          | 0.3462   |
| 1.5819        | 2.0   | 24   | 1.4962          | 0.3269   |
| 1.4527        | 3.0   | 36   | 1.3413          | 0.4615   |
| 1.2853        | 4.0   | 48   | 1.2034          | 0.4423   |
| 1.0185        | 5.0   | 60   | 1.1204          | 0.4808   |
| 0.8102        | 6.0   | 72   | 1.1004          | 0.4808   |
| 0.7477        | 7.0   | 84   | 1.1705          | 0.4808   |
| 0.6684        | 8.0   | 96   | 1.0245          | 0.5192   |
| 0.6297        | 9.0   | 108  | 1.0010          | 0.5577   |
| 0.5453        | 10.0  | 120  | 1.1905          | 0.4808   |
| 0.5496        | 11.0  | 132  | 1.1227          | 0.4808   |
| 0.4993        | 12.0  | 144  | 0.9619          | 0.5577   |
| 0.4297        | 13.0  | 156  | 1.0743          | 0.5192   |
| 0.4459        | 14.0  | 168  | 1.0195          | 0.5577   |
| 0.4219        | 15.0  | 180  | 1.0888          | 0.5      |
| 0.3742        | 16.0  | 192  | 1.0123          | 0.5769   |
| 0.4603        | 17.0  | 204  | 1.0503          | 0.5192   |
| 0.3607        | 18.0  | 216  | 1.1305          | 0.5577   |
| 0.3399        | 19.0  | 228  | 1.1327          | 0.5385   |
| 0.3422        | 20.0  | 240  | 1.1125          | 0.5192   |
| 0.3254        | 21.0  | 252  | 1.0243          | 0.5769   |
| 0.3363        | 22.0  | 264  | 1.0753          | 0.5577   |
| 0.3203        | 23.0  | 276  | 1.0778          | 0.5577   |
| 0.3248        | 24.0  | 288  | 1.1100          | 0.5385   |
| 0.2446        | 25.0  | 300  | 1.0773          | 0.5577   |
| 0.3058        | 26.0  | 312  | 1.0875          | 0.5769   |
| 0.254         | 27.0  | 324  | 1.0673          | 0.5769   |
| 0.2644        | 28.0  | 336  | 1.1026          | 0.5769   |
| 0.2962        | 29.0  | 348  | 1.0899          | 0.5962   |
| 0.2579        | 30.0  | 360  | 1.0816          | 0.5962   |


### 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