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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV64

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: 0.2871
- Accuracy: 0.9371

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1417        | 1.0   | 15   | 1.0312          | 0.5429   |
| 0.9163        | 2.0   | 30   | 0.7115          | 0.7943   |
| 0.7042        | 3.0   | 45   | 0.4227          | 0.8343   |
| 0.4976        | 4.0   | 60   | 0.3409          | 0.8686   |
| 0.4469        | 5.0   | 75   | 0.3059          | 0.8971   |
| 0.3746        | 6.0   | 90   | 0.2957          | 0.8914   |
| 0.3667        | 7.0   | 105  | 0.3036          | 0.8686   |
| 0.3026        | 8.0   | 120  | 0.2555          | 0.9086   |
| 0.2732        | 9.0   | 135  | 0.3009          | 0.9029   |
| 0.2518        | 10.0  | 150  | 0.2463          | 0.9029   |
| 0.2029        | 11.0  | 165  | 0.2345          | 0.9086   |
| 0.2698        | 12.0  | 180  | 0.2969          | 0.9029   |
| 0.2228        | 13.0  | 195  | 0.2966          | 0.9086   |
| 0.2213        | 14.0  | 210  | 0.4314          | 0.8514   |
| 0.1974        | 15.0  | 225  | 0.3352          | 0.8971   |
| 0.1865        | 16.0  | 240  | 0.2836          | 0.9086   |
| 0.157         | 17.0  | 255  | 0.2436          | 0.9086   |
| 0.1588        | 18.0  | 270  | 0.2618          | 0.88     |
| 0.1533        | 19.0  | 285  | 0.2315          | 0.92     |
| 0.1424        | 20.0  | 300  | 0.2358          | 0.9143   |
| 0.1278        | 21.0  | 315  | 0.2752          | 0.9086   |
| 0.1328        | 22.0  | 330  | 0.2196          | 0.92     |
| 0.124         | 23.0  | 345  | 0.2491          | 0.9143   |
| 0.1116        | 24.0  | 360  | 0.2085          | 0.92     |
| 0.1235        | 25.0  | 375  | 0.2379          | 0.92     |
| 0.1746        | 26.0  | 390  | 0.2749          | 0.9257   |
| 0.1143        | 27.0  | 405  | 0.2813          | 0.92     |
| 0.1256        | 28.0  | 420  | 0.3038          | 0.9086   |
| 0.0773        | 29.0  | 435  | 0.2903          | 0.9314   |
| 0.0981        | 30.0  | 450  | 0.2928          | 0.92     |
| 0.0717        | 31.0  | 465  | 0.3073          | 0.9086   |
| 0.1143        | 32.0  | 480  | 0.3466          | 0.8914   |
| 0.0821        | 33.0  | 495  | 0.3079          | 0.9257   |
| 0.0582        | 34.0  | 510  | 0.2845          | 0.9314   |
| 0.1015        | 35.0  | 525  | 0.3610          | 0.9029   |
| 0.075         | 36.0  | 540  | 0.2871          | 0.9371   |
| 0.0783        | 37.0  | 555  | 0.2788          | 0.9257   |
| 0.0919        | 38.0  | 570  | 0.2926          | 0.9257   |
| 0.0863        | 39.0  | 585  | 0.2911          | 0.9086   |
| 0.0721        | 40.0  | 600  | 0.3360          | 0.9143   |
| 0.0994        | 41.0  | 615  | 0.2865          | 0.9086   |
| 0.0734        | 42.0  | 630  | 0.3155          | 0.9143   |
| 0.0935        | 43.0  | 645  | 0.3129          | 0.9086   |
| 0.0651        | 44.0  | 660  | 0.2924          | 0.9143   |
| 0.0732        | 45.0  | 675  | 0.2961          | 0.9143   |


### Framework versions

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

avanzada avanzada humeda no dmae