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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV45

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: 0.7812
- Accuracy: 0.7841

## 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 42

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 6.1945        | 1.0     | 20   | 1.2588          | 0.4545   |
| 4.5836        | 2.0     | 40   | 0.9658          | 0.7159   |
| 2.9056        | 3.0     | 60   | 0.7737          | 0.7273   |
| 2.8061        | 4.0     | 80   | 0.6738          | 0.7727   |
| 1.9405        | 5.0     | 100  | 0.6261          | 0.7614   |
| 1.4425        | 6.0     | 120  | 0.8127          | 0.75     |
| 1.3554        | 7.0     | 140  | 0.7812          | 0.7841   |
| 1.2975        | 8.0     | 160  | 0.8405          | 0.75     |
| 0.812         | 9.0     | 180  | 1.0777          | 0.7159   |
| 0.7984        | 10.0    | 200  | 0.9404          | 0.7159   |
| 0.7895        | 11.0    | 220  | 1.0902          | 0.7045   |
| 0.7333        | 12.0    | 240  | 1.0998          | 0.75     |
| 0.6073        | 13.0    | 260  | 1.2734          | 0.7386   |
| 0.6548        | 14.0    | 280  | 1.3034          | 0.7159   |
| 0.5538        | 15.0    | 300  | 1.1890          | 0.75     |
| 0.556         | 16.0    | 320  | 1.3662          | 0.75     |
| 0.5273        | 17.0    | 340  | 1.2833          | 0.7273   |
| 0.3863        | 18.0    | 360  | 1.2976          | 0.7159   |
| 0.5185        | 19.0    | 380  | 1.2461          | 0.7386   |
| 0.475         | 20.0    | 400  | 1.2543          | 0.7386   |
| 0.3021        | 21.0    | 420  | 1.3143          | 0.7727   |
| 0.3334        | 22.0    | 440  | 1.2873          | 0.75     |
| 0.3773        | 23.0    | 460  | 1.3992          | 0.7386   |
| 0.2606        | 24.0    | 480  | 1.5181          | 0.7159   |
| 0.3344        | 25.0    | 500  | 1.4330          | 0.7614   |
| 0.3349        | 26.0    | 520  | 1.4165          | 0.7841   |
| 0.3246        | 27.0    | 540  | 1.3634          | 0.7614   |
| 0.3395        | 28.0    | 560  | 1.3985          | 0.7614   |
| 0.2606        | 29.0    | 580  | 1.3866          | 0.7614   |
| 0.2212        | 30.0    | 600  | 1.4849          | 0.75     |
| 0.2266        | 31.0    | 620  | 1.4230          | 0.7727   |
| 0.2525        | 32.0    | 640  | 1.4288          | 0.7727   |
| 0.2241        | 33.0    | 660  | 1.4497          | 0.7614   |
| 0.1816        | 34.0    | 680  | 1.4347          | 0.7614   |
| 0.2529        | 35.0    | 700  | 1.4278          | 0.75     |
| 0.189         | 36.0    | 720  | 1.4290          | 0.75     |
| 0.2491        | 37.0    | 740  | 1.4449          | 0.7614   |
| 0.2562        | 38.0    | 760  | 1.4514          | 0.75     |
| 0.1872        | 39.0    | 780  | 1.4522          | 0.75     |
| 0.223         | 39.9351 | 798  | 1.4527          | 0.75     |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0

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