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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV17

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: 0.8543
- Accuracy: 0.7885

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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: 42

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9302  | 10   | 1.5864          | 0.2885   |
| 6.7245        | 1.9302  | 20   | 1.4466          | 0.4615   |
| 5.7484        | 2.9302  | 30   | 1.0303          | 0.5962   |
| 3.9879        | 3.9302  | 40   | 0.9820          | 0.5577   |
| 2.769         | 4.9302  | 50   | 0.8608          | 0.6538   |
| 2.3766        | 5.9302  | 60   | 0.8945          | 0.6923   |
| 2.3766        | 6.9302  | 70   | 0.7773          | 0.6346   |
| 1.9183        | 7.9302  | 80   | 0.8082          | 0.6346   |
| 1.4993        | 8.9302  | 90   | 0.9407          | 0.6923   |
| 1.3461        | 9.9302  | 100  | 0.9281          | 0.75     |
| 1.2085        | 10.9302 | 110  | 0.7563          | 0.7692   |
| 0.8413        | 11.9302 | 120  | 0.9108          | 0.7308   |
| 0.8413        | 12.9302 | 130  | 0.8543          | 0.7885   |
| 0.9607        | 13.9302 | 140  | 1.2058          | 0.6731   |
| 0.837         | 14.9302 | 150  | 0.9733          | 0.7115   |
| 0.7641        | 15.9302 | 160  | 1.0169          | 0.6538   |
| 0.7997        | 16.9302 | 170  | 0.8486          | 0.7308   |
| 0.6171        | 17.9302 | 180  | 0.9551          | 0.7885   |
| 0.6171        | 18.9302 | 190  | 1.0267          | 0.7308   |
| 0.6755        | 19.9302 | 200  | 1.1810          | 0.6923   |
| 0.6393        | 20.9302 | 210  | 1.0516          | 0.7308   |
| 0.573         | 21.9302 | 220  | 1.1029          | 0.7115   |
| 0.4657        | 22.9302 | 230  | 1.0257          | 0.7885   |
| 0.4626        | 23.9302 | 240  | 1.2266          | 0.6923   |
| 0.4626        | 24.9302 | 250  | 1.3491          | 0.6538   |
| 0.4899        | 25.9302 | 260  | 1.2055          | 0.7692   |
| 0.3991        | 26.9302 | 270  | 1.1633          | 0.6923   |
| 0.3778        | 27.9302 | 280  | 1.1751          | 0.7308   |
| 0.443         | 28.9302 | 290  | 1.1727          | 0.75     |
| 0.43          | 29.9302 | 300  | 1.3292          | 0.7115   |
| 0.43          | 30.9302 | 310  | 1.1873          | 0.7115   |
| 0.4425        | 31.9302 | 320  | 1.2326          | 0.6538   |
| 0.3098        | 32.9302 | 330  | 1.2379          | 0.7115   |
| 0.4086        | 33.9302 | 340  | 1.3020          | 0.6731   |
| 0.3046        | 34.9302 | 350  | 1.2686          | 0.7115   |
| 0.3503        | 35.9302 | 360  | 1.3006          | 0.6923   |
| 0.3503        | 36.9302 | 370  | 1.3207          | 0.6923   |
| 0.2985        | 37.9302 | 380  | 1.3626          | 0.7115   |
| 0.3445        | 38.9302 | 390  | 1.3689          | 0.7115   |
| 0.3017        | 39.9302 | 400  | 1.3523          | 0.7115   |
| 0.3446        | 40.9302 | 410  | 1.3447          | 0.7115   |
| 0.2799        | 41.9302 | 420  | 1.3395          | 0.7115   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0

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