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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV61

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: 0.2449
- Accuracy: 0.9086

## 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: 4e-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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.1254        | 1.0     | 10   | 1.0551          | 0.48     |
| 0.967         | 2.0     | 20   | 0.9770          | 0.4571   |
| 0.8537        | 3.0     | 30   | 0.7128          | 0.7086   |
| 0.6489        | 4.0     | 40   | 0.5167          | 0.7371   |
| 0.567         | 5.0     | 50   | 0.3952          | 0.8      |
| 0.4724        | 6.0     | 60   | 0.3705          | 0.8571   |
| 0.4106        | 7.0     | 70   | 0.3076          | 0.8743   |
| 0.3853        | 8.0     | 80   | 0.3155          | 0.8914   |
| 0.3369        | 9.0     | 90   | 0.2908          | 0.8514   |
| 0.3345        | 10.0    | 100  | 0.3034          | 0.8457   |
| 0.3092        | 11.0    | 110  | 0.2575          | 0.88     |
| 0.3027        | 12.0    | 120  | 0.2486          | 0.8971   |
| 0.2945        | 13.0    | 130  | 0.2956          | 0.8629   |
| 0.254         | 14.0    | 140  | 0.2787          | 0.8971   |
| 0.2476        | 15.0    | 150  | 0.2594          | 0.9029   |
| 0.2058        | 16.0    | 160  | 0.3091          | 0.8971   |
| 0.2254        | 17.0    | 170  | 0.2778          | 0.8971   |
| 0.2165        | 18.0    | 180  | 0.3094          | 0.88     |
| 0.2501        | 19.0    | 190  | 0.2536          | 0.8914   |
| 0.2016        | 20.0    | 200  | 0.2652          | 0.9029   |
| 0.1791        | 21.0    | 210  | 0.2449          | 0.9086   |
| 0.1401        | 22.0    | 220  | 0.3205          | 0.8743   |
| 0.17          | 23.0    | 230  | 0.3446          | 0.8686   |
| 0.1665        | 24.0    | 240  | 0.3058          | 0.8743   |
| 0.1192        | 25.0    | 250  | 0.3537          | 0.8743   |
| 0.1249        | 26.0    | 260  | 0.2929          | 0.8743   |
| 0.143         | 27.0    | 270  | 0.3050          | 0.8743   |
| 0.1809        | 28.0    | 280  | 0.2964          | 0.8914   |
| 0.135         | 29.0    | 290  | 0.3047          | 0.8743   |
| 0.1235        | 30.0    | 300  | 0.3011          | 0.8971   |
| 0.1351        | 31.0    | 310  | 0.3147          | 0.8914   |
| 0.1124        | 32.0    | 320  | 0.3123          | 0.8857   |
| 0.1122        | 33.0    | 330  | 0.3289          | 0.8857   |
| 0.1163        | 34.0    | 340  | 0.3256          | 0.88     |
| 0.0885        | 35.0    | 350  | 0.3126          | 0.8971   |
| 0.097         | 36.0    | 360  | 0.3425          | 0.8857   |
| 0.1036        | 37.0    | 370  | 0.3221          | 0.8857   |
| 0.1107        | 38.0    | 380  | 0.3598          | 0.8971   |
| 0.0928        | 39.0    | 390  | 0.3355          | 0.8857   |
| 0.1104        | 40.0    | 400  | 0.3425          | 0.8857   |
| 0.1104        | 40.5128 | 405  | 0.3428          | 0.8857   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.0

avanzada avanzada humeda no dmae