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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV76

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: 0.4077
- Accuracy: 0.88

## 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.1017        | 0.9524  | 15   | 1.0955          | 0.3143   |
| 0.9212        | 1.9524  | 30   | 0.8475          | 0.6743   |
| 0.7117        | 2.9524  | 45   | 0.6980          | 0.6171   |
| 0.5496        | 3.9524  | 60   | 0.4957          | 0.8      |
| 0.5051        | 4.9524  | 75   | 0.4578          | 0.7714   |
| 0.4331        | 5.9524  | 90   | 0.3767          | 0.8457   |
| 0.4324        | 6.9524  | 105  | 0.4334          | 0.8229   |
| 0.3664        | 7.9524  | 120  | 0.4469          | 0.7829   |
| 0.335         | 8.9524  | 135  | 0.3407          | 0.8743   |
| 0.2977        | 9.9524  | 150  | 0.3569          | 0.84     |
| 0.2978        | 10.9524 | 165  | 0.3858          | 0.8686   |
| 0.2983        | 11.9524 | 180  | 0.3657          | 0.8571   |
| 0.2539        | 12.9524 | 195  | 0.3979          | 0.8514   |
| 0.2215        | 13.9524 | 210  | 0.3755          | 0.8514   |
| 0.2474        | 14.9524 | 225  | 0.4143          | 0.8457   |
| 0.2245        | 15.9524 | 240  | 0.3954          | 0.8629   |
| 0.2427        | 16.9524 | 255  | 0.4063          | 0.8743   |
| 0.2036        | 17.9524 | 270  | 0.4762          | 0.8343   |
| 0.2397        | 18.9524 | 285  | 0.4077          | 0.88     |
| 0.2157        | 19.9524 | 300  | 0.5519          | 0.8114   |
| 0.221         | 20.9524 | 315  | 0.5091          | 0.8114   |
| 0.1799        | 21.9524 | 330  | 0.4301          | 0.8629   |
| 0.1777        | 22.9524 | 345  | 0.4592          | 0.8743   |
| 0.1641        | 23.9524 | 360  | 0.4445          | 0.8686   |
| 0.1582        | 24.9524 | 375  | 0.4807          | 0.8571   |
| 0.1394        | 25.9524 | 390  | 0.4472          | 0.8743   |
| 0.16          | 26.9524 | 405  | 0.5020          | 0.8743   |
| 0.1826        | 27.9524 | 420  | 0.4834          | 0.8686   |
| 0.1648        | 28.9524 | 435  | 0.5368          | 0.8629   |
| 0.155         | 29.9524 | 450  | 0.5284          | 0.8514   |
| 0.1378        | 30.9524 | 465  | 0.4585          | 0.8743   |
| 0.1608        | 31.9524 | 480  | 0.4883          | 0.8686   |
| 0.1435        | 32.9524 | 495  | 0.5400          | 0.84     |
| 0.1444        | 33.9524 | 510  | 0.5379          | 0.8571   |
| 0.1504        | 34.9524 | 525  | 0.5876          | 0.8629   |
| 0.1108        | 35.9524 | 540  | 0.5414          | 0.8571   |
| 0.1392        | 36.9524 | 555  | 0.5801          | 0.8571   |
| 0.1065        | 37.9524 | 570  | 0.5940          | 0.8629   |
| 0.087         | 38.9524 | 585  | 0.6316          | 0.8571   |
| 0.127         | 39.9524 | 600  | 0.6509          | 0.8571   |
| 0.1198        | 40.9524 | 615  | 0.6311          | 0.8571   |
| 0.1255        | 41.9524 | 630  | 0.5793          | 0.8514   |
| 0.1317        | 42.9524 | 645  | 0.5860          | 0.8343   |
| 0.1016        | 43.9524 | 660  | 0.5839          | 0.8629   |
| 0.1249        | 44.9524 | 675  | 0.5763          | 0.8571   |
| 0.0762        | 45.9524 | 690  | 0.5853          | 0.8629   |
| 0.1075        | 46.9524 | 705  | 0.5967          | 0.8514   |
| 0.0792        | 47.9524 | 720  | 0.6012          | 0.8457   |
| 0.1033        | 48.9524 | 735  | 0.5989          | 0.8457   |
| 0.1115        | 49.9524 | 750  | 0.6030          | 0.8457   |


### Framework versions

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

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