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# swinv2-base-patch4-window8-256-dmae-humeda-DAV14

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8478
- Accuracy: 0.7692

## 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.8421  | 4    | 1.6083          | 0.2115   |
| No log        | 1.8421  | 8    | 1.5519          | 0.3077   |
| 7.0606        | 2.8421  | 12   | 1.4896          | 0.3846   |
| 7.0606        | 3.8421  | 16   | 1.4160          | 0.3846   |
| 6.3113        | 4.8421  | 20   | 1.3599          | 0.3269   |
| 6.3113        | 5.8421  | 24   | 1.2338          | 0.3462   |
| 6.3113        | 6.8421  | 28   | 1.1538          | 0.4808   |
| 5.1603        | 7.8421  | 32   | 1.0931          | 0.5577   |
| 5.1603        | 8.8421  | 36   | 1.0510          | 0.5577   |
| 3.5688        | 9.8421  | 40   | 0.9583          | 0.5577   |
| 3.5688        | 10.8421 | 44   | 0.9648          | 0.5577   |
| 3.5688        | 11.8421 | 48   | 0.9486          | 0.6154   |
| 2.9736        | 12.8421 | 52   | 0.9201          | 0.5962   |
| 2.9736        | 13.8421 | 56   | 1.0203          | 0.5577   |
| 2.5257        | 14.8421 | 60   | 0.8558          | 0.6154   |
| 2.5257        | 15.8421 | 64   | 0.9309          | 0.5769   |
| 2.5257        | 16.8421 | 68   | 0.9707          | 0.5769   |
| 2.3819        | 17.8421 | 72   | 0.8505          | 0.6731   |
| 2.3819        | 18.8421 | 76   | 0.9245          | 0.6538   |
| 1.9541        | 19.8421 | 80   | 0.9093          | 0.6731   |
| 1.9541        | 20.8421 | 84   | 0.8463          | 0.7115   |
| 1.9541        | 21.8421 | 88   | 0.9135          | 0.6731   |
| 1.7643        | 22.8421 | 92   | 0.8720          | 0.7115   |
| 1.7643        | 23.8421 | 96   | 0.8631          | 0.7115   |
| 1.5146        | 24.8421 | 100  | 0.8862          | 0.6923   |
| 1.5146        | 25.8421 | 104  | 0.8584          | 0.75     |
| 1.5146        | 26.8421 | 108  | 0.9111          | 0.6923   |
| 1.4609        | 27.8421 | 112  | 0.8703          | 0.75     |
| 1.4609        | 28.8421 | 116  | 0.8478          | 0.7692   |
| 1.463         | 29.8421 | 120  | 0.8645          | 0.75     |
| 1.463         | 30.8421 | 124  | 0.9137          | 0.6731   |
| 1.463         | 31.8421 | 128  | 0.9311          | 0.6731   |
| 1.3699        | 32.8421 | 132  | 0.9070          | 0.7115   |
| 1.3699        | 33.8421 | 136  | 0.8930          | 0.7115   |
| 1.2756        | 34.8421 | 140  | 0.8930          | 0.7115   |
| 1.2756        | 35.8421 | 144  | 0.8935          | 0.7308   |
| 1.2756        | 36.8421 | 148  | 0.8960          | 0.7308   |
| 1.273         | 37.8421 | 152  | 0.8951          | 0.7308   |
| 1.273         | 38.8421 | 156  | 0.8955          | 0.7308   |
| 1.2626        | 39.8421 | 160  | 0.8954          | 0.7308   |


### 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