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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV3

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: 0.2067
- Accuracy: 0.9589

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 0.05
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 3.9845        | 1.0     | 21   | 1.6832          | 0.3425   |
| 2.4369        | 2.0     | 42   | 1.1981          | 0.4384   |
| 1.7752        | 3.0     | 63   | 0.8412          | 0.6301   |
| 1.3772        | 4.0     | 84   | 0.7895          | 0.7123   |
| 1.1556        | 5.0     | 105  | 0.7385          | 0.7808   |
| 1.0059        | 6.0     | 126  | 0.6626          | 0.8082   |
| 0.8598        | 7.0     | 147  | 0.5403          | 0.7808   |
| 0.8724        | 8.0     | 168  | 0.5520          | 0.8219   |
| 0.7096        | 9.0     | 189  | 0.5182          | 0.8356   |
| 0.5038        | 10.0    | 210  | 0.4133          | 0.8493   |
| 0.4951        | 11.0    | 231  | 0.3548          | 0.8767   |
| 0.4692        | 12.0    | 252  | 0.3845          | 0.8493   |
| 0.5339        | 13.0    | 273  | 0.3178          | 0.8904   |
| 0.4536        | 14.0    | 294  | 0.3252          | 0.8904   |
| 0.4369        | 15.0    | 315  | 0.2785          | 0.8904   |
| 0.3941        | 16.0    | 336  | 0.2900          | 0.9041   |
| 0.4363        | 17.0    | 357  | 0.3426          | 0.8630   |
| 0.2819        | 18.0    | 378  | 0.2839          | 0.9041   |
| 0.361         | 19.0    | 399  | 0.2223          | 0.9041   |
| 0.1857        | 20.0    | 420  | 0.2522          | 0.9178   |
| 0.3161        | 21.0    | 441  | 0.2164          | 0.9178   |
| 0.3273        | 22.0    | 462  | 0.2224          | 0.9315   |
| 0.3458        | 23.0    | 483  | 0.2199          | 0.9452   |
| 0.337         | 24.0    | 504  | 0.2377          | 0.9315   |
| 0.1801        | 25.0    | 525  | 0.2067          | 0.9589   |
| 0.3283        | 26.0    | 546  | 0.2401          | 0.9315   |
| 0.2211        | 27.0    | 567  | 0.2167          | 0.9315   |
| 0.1783        | 28.0    | 588  | 0.2180          | 0.9315   |
| 0.2783        | 28.5854 | 600  | 0.2223          | 0.9315   |


### Framework versions

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

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