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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV77

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: 0.3654
- Accuracy: 0.8914

## 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.1317        | 0.9524  | 15   | 1.0850          | 0.3657   |
| 1.0134        | 1.9524  | 30   | 1.0048          | 0.56     |
| 0.9444        | 2.9524  | 45   | 0.7731          | 0.7371   |
| 0.6457        | 3.9524  | 60   | 0.5598          | 0.7486   |
| 0.5593        | 4.9524  | 75   | 0.4836          | 0.7771   |
| 0.4781        | 5.9524  | 90   | 0.4486          | 0.7829   |
| 0.4769        | 6.9524  | 105  | 0.4365          | 0.8114   |
| 0.4366        | 7.9524  | 120  | 0.5434          | 0.7657   |
| 0.4248        | 8.9524  | 135  | 0.3744          | 0.8457   |
| 0.3298        | 9.9524  | 150  | 0.3618          | 0.8343   |
| 0.342         | 10.9524 | 165  | 0.3661          | 0.8629   |
| 0.3033        | 11.9524 | 180  | 0.3753          | 0.8343   |
| 0.3106        | 12.9524 | 195  | 0.4607          | 0.8229   |
| 0.264         | 13.9524 | 210  | 0.3623          | 0.8457   |
| 0.2407        | 14.9524 | 225  | 0.3982          | 0.8343   |
| 0.2758        | 15.9524 | 240  | 0.3694          | 0.8514   |
| 0.2719        | 16.9524 | 255  | 0.5112          | 0.8171   |
| 0.2311        | 17.9524 | 270  | 0.3977          | 0.8571   |
| 0.246         | 18.9524 | 285  | 0.4087          | 0.8629   |
| 0.2193        | 19.9524 | 300  | 0.4239          | 0.8343   |
| 0.2419        | 20.9524 | 315  | 0.3980          | 0.8514   |
| 0.2084        | 21.9524 | 330  | 0.4278          | 0.8686   |
| 0.1973        | 22.9524 | 345  | 0.3654          | 0.8914   |
| 0.1807        | 23.9524 | 360  | 0.4050          | 0.8629   |
| 0.1693        | 24.9524 | 375  | 0.5299          | 0.8229   |
| 0.1594        | 25.9524 | 390  | 0.4832          | 0.8514   |
| 0.1876        | 26.9524 | 405  | 0.5069          | 0.84     |
| 0.1514        | 27.9524 | 420  | 0.5056          | 0.8571   |
| 0.1818        | 28.9524 | 435  | 0.5403          | 0.8286   |
| 0.1682        | 29.9524 | 450  | 0.5058          | 0.84     |
| 0.1681        | 30.9524 | 465  | 0.5187          | 0.8114   |
| 0.1394        | 31.9524 | 480  | 0.5843          | 0.8629   |
| 0.1659        | 32.9524 | 495  | 0.4707          | 0.8629   |
| 0.1753        | 33.9524 | 510  | 0.5603          | 0.8229   |
| 0.1884        | 34.9524 | 525  | 0.5372          | 0.8343   |
| 0.1399        | 35.9524 | 540  | 0.5559          | 0.8629   |
| 0.1603        | 36.9524 | 555  | 0.6177          | 0.8629   |
| 0.1353        | 37.9524 | 570  | 0.5262          | 0.8457   |
| 0.0874        | 38.9524 | 585  | 0.4945          | 0.8629   |
| 0.1054        | 39.9524 | 600  | 0.6391          | 0.8629   |
| 0.1156        | 40.9524 | 615  | 0.6080          | 0.8514   |
| 0.1247        | 41.9524 | 630  | 0.6483          | 0.8114   |
| 0.1396        | 42.9524 | 645  | 0.5377          | 0.8457   |
| 0.117         | 43.9524 | 660  | 0.5460          | 0.8629   |
| 0.1403        | 44.9524 | 675  | 0.6856          | 0.84     |
| 0.1089        | 45.9524 | 690  | 0.6401          | 0.8514   |
| 0.1022        | 46.9524 | 705  | 0.6795          | 0.8514   |
| 0.09          | 47.9524 | 720  | 0.6025          | 0.8457   |
| 0.0948        | 48.9524 | 735  | 0.6489          | 0.8514   |
| 0.1177        | 49.9524 | 750  | 0.6105          | 0.8571   |
| 0.0797        | 50.9524 | 765  | 0.7485          | 0.8229   |
| 0.0872        | 51.9524 | 780  | 0.6390          | 0.84     |
| 0.1038        | 52.9524 | 795  | 0.6190          | 0.8743   |
| 0.1361        | 53.9524 | 810  | 0.6417          | 0.8457   |
| 0.1205        | 54.9524 | 825  | 0.6161          | 0.84     |
| 0.1026        | 55.9524 | 840  | 0.5836          | 0.8514   |
| 0.1059        | 56.9524 | 855  | 0.6865          | 0.8571   |
| 0.0999        | 57.9524 | 870  | 0.7455          | 0.8629   |
| 0.1075        | 58.9524 | 885  | 0.7018          | 0.8343   |
| 0.0952        | 59.9524 | 900  | 0.6851          | 0.8286   |
| 0.0796        | 60.9524 | 915  | 0.6301          | 0.8514   |
| 0.0952        | 61.9524 | 930  | 0.6734          | 0.8343   |
| 0.1041        | 62.9524 | 945  | 0.6475          | 0.8514   |
| 0.0961        | 63.9524 | 960  | 0.7369          | 0.8229   |
| 0.0897        | 64.9524 | 975  | 0.7261          | 0.84     |
| 0.0591        | 65.9524 | 990  | 0.7303          | 0.8286   |
| 0.106         | 66.9524 | 1005 | 0.6512          | 0.84     |
| 0.0817        | 67.9524 | 1020 | 0.6835          | 0.8229   |
| 0.0653        | 68.9524 | 1035 | 0.7211          | 0.8514   |
| 0.0801        | 69.9524 | 1050 | 0.7762          | 0.8343   |
| 0.0754        | 70.9524 | 1065 | 0.7669          | 0.8571   |
| 0.067         | 71.9524 | 1080 | 0.8578          | 0.8457   |
| 0.0896        | 72.9524 | 1095 | 0.8271          | 0.84     |
| 0.0622        | 73.9524 | 1110 | 0.7458          | 0.8286   |
| 0.0741        | 74.9524 | 1125 | 0.7236          | 0.84     |
| 0.0687        | 75.9524 | 1140 | 0.7986          | 0.84     |
| 0.0877        | 76.9524 | 1155 | 0.7999          | 0.8286   |
| 0.1034        | 77.9524 | 1170 | 0.7840          | 0.8286   |
| 0.0716        | 78.9524 | 1185 | 0.7871          | 0.8343   |
| 0.0659        | 79.9524 | 1200 | 0.7860          | 0.8571   |
| 0.0844        | 80.9524 | 1215 | 0.8366          | 0.8514   |
| 0.0858        | 81.9524 | 1230 | 0.8152          | 0.8629   |
| 0.0531        | 82.9524 | 1245 | 0.7717          | 0.8286   |
| 0.075         | 83.9524 | 1260 | 0.8578          | 0.8171   |
| 0.059         | 84.9524 | 1275 | 0.8240          | 0.8229   |
| 0.0896        | 85.9524 | 1290 | 0.8907          | 0.8343   |
| 0.0741        | 86.9524 | 1305 | 0.8814          | 0.84     |
| 0.0697        | 87.9524 | 1320 | 0.9080          | 0.8286   |
| 0.0552        | 88.9524 | 1335 | 0.8345          | 0.8343   |
| 0.0576        | 89.9524 | 1350 | 0.8746          | 0.8229   |
| 0.0729        | 90.9524 | 1365 | 0.8196          | 0.8343   |
| 0.0782        | 91.9524 | 1380 | 0.8073          | 0.8343   |
| 0.0584        | 92.9524 | 1395 | 0.8011          | 0.8286   |
| 0.0471        | 93.9524 | 1410 | 0.8076          | 0.8286   |
| 0.0544        | 94.9524 | 1425 | 0.8390          | 0.8229   |
| 0.0576        | 95.9524 | 1440 | 0.8575          | 0.8286   |
| 0.0608        | 96.9524 | 1455 | 0.8392          | 0.8229   |
| 0.064         | 97.9524 | 1470 | 0.8266          | 0.8286   |
| 0.0742        | 98.9524 | 1485 | 0.8311          | 0.8286   |
| 0.0471        | 99.9524 | 1500 | 0.8333          | 0.8286   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.19.0
- Tokenizers 0.21.1

avanzada avanzada humeda no dmae