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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV63

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: 0.2824
- Accuracy: 0.9029

## 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: 5e-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: linear
- 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        | 1.0   | 5    | 1.0434          | 0.4743   |
| 1.0715        | 2.0   | 10   | 1.0274          | 0.4571   |
| 1.0715        | 3.0   | 15   | 0.9232          | 0.5714   |
| 0.9224        | 4.0   | 20   | 0.7760          | 0.7257   |
| 0.9224        | 5.0   | 25   | 0.6111          | 0.7314   |
| 0.659         | 6.0   | 30   | 0.4303          | 0.8514   |
| 0.659         | 7.0   | 35   | 0.3456          | 0.8743   |
| 0.4725        | 8.0   | 40   | 0.4387          | 0.8      |
| 0.4725        | 9.0   | 45   | 0.3622          | 0.8286   |
| 0.4171        | 10.0  | 50   | 0.3593          | 0.8686   |
| 0.4171        | 11.0  | 55   | 0.3262          | 0.8629   |
| 0.3615        | 12.0  | 60   | 0.3256          | 0.8571   |
| 0.3615        | 13.0  | 65   | 0.3205          | 0.8743   |
| 0.3094        | 14.0  | 70   | 0.3051          | 0.8743   |
| 0.3094        | 15.0  | 75   | 0.2948          | 0.8857   |
| 0.2784        | 16.0  | 80   | 0.3237          | 0.8857   |
| 0.2784        | 17.0  | 85   | 0.2920          | 0.88     |
| 0.2849        | 18.0  | 90   | 0.2824          | 0.9029   |
| 0.2849        | 19.0  | 95   | 0.3579          | 0.8743   |
| 0.2772        | 20.0  | 100  | 0.2966          | 0.8857   |
| 0.2772        | 21.0  | 105  | 0.3484          | 0.8743   |
| 0.2135        | 22.0  | 110  | 0.3230          | 0.88     |
| 0.2135        | 23.0  | 115  | 0.3591          | 0.8686   |
| 0.2067        | 24.0  | 120  | 0.3292          | 0.8743   |
| 0.2067        | 25.0  | 125  | 0.3496          | 0.88     |
| 0.165         | 26.0  | 130  | 0.3628          | 0.88     |
| 0.165         | 27.0  | 135  | 0.3345          | 0.8914   |
| 0.1888        | 28.0  | 140  | 0.3596          | 0.88     |
| 0.1888        | 29.0  | 145  | 0.3567          | 0.8914   |
| 0.1473        | 30.0  | 150  | 0.3824          | 0.8743   |
| 0.1473        | 31.0  | 155  | 0.3685          | 0.88     |
| 0.1472        | 32.0  | 160  | 0.3488          | 0.8971   |
| 0.1472        | 33.0  | 165  | 0.3895          | 0.8857   |
| 0.1568        | 34.0  | 170  | 0.3929          | 0.8914   |
| 0.1568        | 35.0  | 175  | 0.3803          | 0.8857   |
| 0.129         | 36.0  | 180  | 0.3954          | 0.8743   |
| 0.129         | 37.0  | 185  | 0.3920          | 0.8743   |
| 0.1295        | 38.0  | 190  | 0.3945          | 0.8971   |
| 0.1295        | 39.0  | 195  | 0.3836          | 0.8857   |
| 0.1322        | 40.0  | 200  | 0.4102          | 0.8743   |
| 0.1322        | 41.0  | 205  | 0.4226          | 0.8686   |
| 0.1124        | 42.0  | 210  | 0.3939          | 0.88     |
| 0.1124        | 43.0  | 215  | 0.3911          | 0.8857   |
| 0.1162        | 44.0  | 220  | 0.3986          | 0.8914   |
| 0.1162        | 45.0  | 225  | 0.4015          | 0.8857   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1

avanzada avanzada humeda no dmae