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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV70

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: 0.3655
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0983        | 1.0   | 15   | 1.0283          | 0.5371   |
| 0.8777        | 2.0   | 30   | 0.7419          | 0.7371   |
| 0.69          | 3.0   | 45   | 0.4895          | 0.8      |
| 0.4806        | 4.0   | 60   | 0.4128          | 0.8114   |
| 0.436         | 5.0   | 75   | 0.3188          | 0.8743   |
| 0.3499        | 6.0   | 90   | 0.3870          | 0.8286   |
| 0.3754        | 7.0   | 105  | 0.3523          | 0.8857   |
| 0.2954        | 8.0   | 120  | 0.3168          | 0.8686   |
| 0.3075        | 9.0   | 135  | 0.3359          | 0.8743   |
| 0.2405        | 10.0  | 150  | 0.3676          | 0.8514   |
| 0.2716        | 11.0  | 165  | 0.3715          | 0.8343   |
| 0.2414        | 12.0  | 180  | 0.3665          | 0.8971   |
| 0.2116        | 13.0  | 195  | 0.3554          | 0.88     |
| 0.2134        | 14.0  | 210  | 0.4033          | 0.8686   |
| 0.2058        | 15.0  | 225  | 0.4590          | 0.84     |
| 0.1925        | 16.0  | 240  | 0.4088          | 0.8457   |
| 0.2004        | 17.0  | 255  | 0.4399          | 0.8743   |
| 0.1541        | 18.0  | 270  | 0.3550          | 0.8686   |
| 0.2124        | 19.0  | 285  | 0.3603          | 0.8914   |
| 0.1975        | 20.0  | 300  | 0.3655          | 0.9029   |
| 0.15          | 21.0  | 315  | 0.3863          | 0.8971   |
| 0.1796        | 22.0  | 330  | 0.3288          | 0.9029   |
| 0.1307        | 23.0  | 345  | 0.3781          | 0.8857   |
| 0.1721        | 24.0  | 360  | 0.3938          | 0.9029   |
| 0.1161        | 25.0  | 375  | 0.4481          | 0.88     |
| 0.1096        | 26.0  | 390  | 0.4351          | 0.8686   |
| 0.1203        | 27.0  | 405  | 0.4337          | 0.8686   |
| 0.1481        | 28.0  | 420  | 0.5295          | 0.8457   |
| 0.1295        | 29.0  | 435  | 0.4443          | 0.8857   |
| 0.1234        | 30.0  | 450  | 0.4490          | 0.8914   |
| 0.1368        | 31.0  | 465  | 0.5945          | 0.8629   |
| 0.1024        | 32.0  | 480  | 0.5224          | 0.88     |
| 0.1255        | 33.0  | 495  | 0.4385          | 0.9029   |
| 0.1285        | 34.0  | 510  | 0.5272          | 0.8971   |
| 0.1316        | 35.0  | 525  | 0.4936          | 0.8971   |
| 0.1042        | 36.0  | 540  | 0.5399          | 0.8971   |
| 0.1028        | 37.0  | 555  | 0.5199          | 0.8857   |
| 0.0923        | 38.0  | 570  | 0.4813          | 0.9029   |
| 0.1           | 39.0  | 585  | 0.5702          | 0.8914   |
| 0.0943        | 40.0  | 600  | 0.5477          | 0.8971   |
| 0.1135        | 41.0  | 615  | 0.5281          | 0.8971   |
| 0.1021        | 42.0  | 630  | 0.5353          | 0.8971   |


### Framework versions

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

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