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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV72

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: 0.7140
- Accuracy: 0.8743

## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.0851        | 1.0     | 15   | 1.0597          | 0.4857   |
| 0.9595        | 2.0     | 30   | 0.9427          | 0.64     |
| 0.8642        | 3.0     | 45   | 0.6913          | 0.7086   |
| 0.5836        | 4.0     | 60   | 0.5780          | 0.7257   |
| 0.5395        | 5.0     | 75   | 0.4822          | 0.7829   |
| 0.4215        | 6.0     | 90   | 0.4077          | 0.8229   |
| 0.4329        | 7.0     | 105  | 0.4352          | 0.8114   |
| 0.3695        | 8.0     | 120  | 0.3244          | 0.8743   |
| 0.3314        | 9.0     | 135  | 0.3186          | 0.8914   |
| 0.3176        | 10.0    | 150  | 0.3788          | 0.8514   |
| 0.3368        | 11.0    | 165  | 0.3458          | 0.8629   |
| 0.2558        | 12.0    | 180  | 0.4196          | 0.8457   |
| 0.2579        | 13.0    | 195  | 0.3485          | 0.8743   |
| 0.2413        | 14.0    | 210  | 0.4509          | 0.8629   |
| 0.2374        | 15.0    | 225  | 0.3904          | 0.8743   |
| 0.2214        | 16.0    | 240  | 0.3461          | 0.8514   |
| 0.2189        | 17.0    | 255  | 0.5986          | 0.8229   |
| 0.2458        | 18.0    | 270  | 0.3360          | 0.8914   |
| 0.2431        | 19.0    | 285  | 0.3475          | 0.8857   |
| 0.2136        | 20.0    | 300  | 0.3242          | 0.88     |
| 0.1871        | 21.0    | 315  | 0.4103          | 0.8857   |
| 0.1996        | 22.0    | 330  | 0.3606          | 0.9029   |
| 0.1367        | 23.0    | 345  | 0.4657          | 0.8629   |
| 0.1963        | 24.0    | 360  | 0.4267          | 0.8743   |
| 0.1519        | 25.0    | 375  | 0.4322          | 0.8686   |
| 0.1365        | 26.0    | 390  | 0.4214          | 0.88     |
| 0.1158        | 27.0    | 405  | 0.4472          | 0.8743   |
| 0.1621        | 28.0    | 420  | 0.4020          | 0.8743   |
| 0.1271        | 29.0    | 435  | 0.4054          | 0.8857   |
| 0.136         | 30.0    | 450  | 0.4286          | 0.9143   |
| 0.1386        | 31.0    | 465  | 0.5015          | 0.8857   |
| 0.1153        | 32.0    | 480  | 0.6675          | 0.8629   |
| 0.1139        | 33.0    | 495  | 0.5458          | 0.8971   |
| 0.144         | 34.0    | 510  | 0.5303          | 0.88     |
| 0.1542        | 35.0    | 525  | 0.5164          | 0.8914   |
| 0.1208        | 36.0    | 540  | 0.5690          | 0.88     |
| 0.1034        | 37.0    | 555  | 0.7427          | 0.8571   |
| 0.0889        | 38.0    | 570  | 0.9084          | 0.8286   |
| 0.1355        | 39.0    | 585  | 0.5977          | 0.8743   |
| 0.0895        | 40.0    | 600  | 0.5400          | 0.8914   |
| 0.1072        | 41.0    | 615  | 0.6018          | 0.8743   |
| 0.1356        | 42.0    | 630  | 0.5493          | 0.8743   |
| 0.0953        | 43.0    | 645  | 0.5350          | 0.8914   |
| 0.0781        | 44.0    | 660  | 0.5269          | 0.88     |
| 0.0854        | 45.0    | 675  | 0.5428          | 0.88     |
| 0.0983        | 46.0    | 690  | 0.4897          | 0.8857   |
| 0.0944        | 47.0    | 705  | 0.5177          | 0.8971   |
| 0.1152        | 48.0    | 720  | 0.6401          | 0.8629   |
| 0.0608        | 49.0    | 735  | 0.7380          | 0.8629   |
| 0.0898        | 50.0    | 750  | 0.4922          | 0.8971   |
| 0.0923        | 51.0    | 765  | 0.5427          | 0.8971   |
| 0.0743        | 52.0    | 780  | 0.9941          | 0.84     |
| 0.0753        | 53.0    | 795  | 0.5342          | 0.8857   |
| 0.0751        | 54.0    | 810  | 0.6452          | 0.88     |
| 0.1222        | 55.0    | 825  | 0.6297          | 0.8743   |
| 0.0786        | 56.0    | 840  | 0.6592          | 0.8629   |
| 0.134         | 57.0    | 855  | 0.6541          | 0.8686   |
| 0.092         | 58.0    | 870  | 0.6523          | 0.8571   |
| 0.1036        | 59.0    | 885  | 0.5562          | 0.8971   |
| 0.0825        | 60.0    | 900  | 0.6117          | 0.8743   |
| 0.0923        | 61.0    | 915  | 0.5778          | 0.8686   |
| 0.0909        | 62.0    | 930  | 0.5974          | 0.8686   |
| 0.0536        | 63.0    | 945  | 0.7557          | 0.8514   |
| 0.0572        | 64.0    | 960  | 0.6255          | 0.8857   |
| 0.0824        | 65.0    | 975  | 0.6768          | 0.8686   |
| 0.0773        | 66.0    | 990  | 0.5942          | 0.9029   |
| 0.0495        | 67.0    | 1005 | 0.7902          | 0.8571   |
| 0.0649        | 68.0    | 1020 | 0.6097          | 0.8914   |
| 0.0852        | 69.0    | 1035 | 0.6614          | 0.8914   |
| 0.0634        | 70.0    | 1050 | 0.6604          | 0.8914   |
| 0.0774        | 71.0    | 1065 | 0.7848          | 0.8514   |
| 0.0803        | 72.0    | 1080 | 0.6424          | 0.8914   |
| 0.0645        | 73.0    | 1095 | 0.7508          | 0.8857   |
| 0.0483        | 74.0    | 1110 | 0.7523          | 0.8629   |
| 0.0586        | 75.0    | 1125 | 0.8278          | 0.8629   |
| 0.1           | 76.0    | 1140 | 0.7503          | 0.8686   |
| 0.0434        | 77.0    | 1155 | 0.7820          | 0.8743   |
| 0.0792        | 78.0    | 1170 | 0.7016          | 0.88     |
| 0.055         | 79.0    | 1185 | 0.8635          | 0.8571   |
| 0.0666        | 80.0    | 1200 | 0.7208          | 0.8686   |
| 0.0563        | 81.0    | 1215 | 0.7606          | 0.8686   |
| 0.0535        | 82.0    | 1230 | 0.7329          | 0.88     |
| 0.0499        | 83.0    | 1245 | 0.7253          | 0.88     |
| 0.0418        | 84.0    | 1260 | 0.7429          | 0.8686   |
| 0.0736        | 85.0    | 1275 | 0.7621          | 0.8743   |
| 0.0593        | 86.0    | 1290 | 0.7970          | 0.8571   |
| 0.0658        | 87.0    | 1305 | 0.7211          | 0.8686   |
| 0.0531        | 88.0    | 1320 | 0.7420          | 0.8686   |
| 0.0604        | 89.0    | 1335 | 0.7151          | 0.8743   |
| 0.0661        | 90.0    | 1350 | 0.6881          | 0.8857   |
| 0.058         | 91.0    | 1365 | 0.7139          | 0.8686   |
| 0.0436        | 92.0    | 1380 | 0.7260          | 0.8686   |
| 0.0733        | 93.0    | 1395 | 0.7150          | 0.8743   |
| 0.0501        | 93.3390 | 1400 | 0.7140          | 0.8743   |


### Framework versions

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

avanzada avanzada humeda no dmae