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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV58

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: 0.8236
- Accuracy: 0.7308

## 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: 45
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.8421  | 4    | 1.5015          | 0.4423   |
| No log        | 1.8421  | 8    | 1.4596          | 0.4231   |
| 1.7006        | 2.8421  | 12   | 1.3454          | 0.5192   |
| 1.7006        | 3.8421  | 16   | 1.2081          | 0.5577   |
| 1.7006        | 4.8421  | 20   | 1.0746          | 0.5577   |
| 1.3198        | 5.8421  | 24   | 0.9099          | 0.5962   |
| 1.3198        | 6.8421  | 28   | 0.8862          | 0.6346   |
| 1.3198        | 7.8421  | 32   | 0.8236          | 0.7308   |
| 0.86          | 8.8421  | 36   | 0.8757          | 0.6154   |
| 0.86          | 9.8421  | 40   | 0.8234          | 0.7115   |
| 0.86          | 10.8421 | 44   | 0.8238          | 0.7115   |
| 0.6765        | 11.8421 | 48   | 0.9140          | 0.6538   |
| 0.6765        | 12.8421 | 52   | 0.8608          | 0.6731   |
| 0.6765        | 13.8421 | 56   | 0.8913          | 0.6538   |
| 0.5549        | 14.8421 | 60   | 0.8184          | 0.7115   |
| 0.5549        | 15.8421 | 64   | 0.8233          | 0.7308   |
| 0.5549        | 16.8421 | 68   | 0.8051          | 0.7308   |
| 0.4803        | 17.8421 | 72   | 0.8256          | 0.7115   |
| 0.4803        | 18.8421 | 76   | 0.8907          | 0.6731   |
| 0.4803        | 19.8421 | 80   | 0.9122          | 0.7115   |
| 0.3757        | 20.8421 | 84   | 0.8812          | 0.7115   |
| 0.3757        | 21.8421 | 88   | 0.9496          | 0.7308   |
| 0.3757        | 22.8421 | 92   | 0.9228          | 0.7115   |
| 0.3166        | 23.8421 | 96   | 0.9533          | 0.6538   |
| 0.3166        | 24.8421 | 100  | 0.9486          | 0.6731   |
| 0.3166        | 25.8421 | 104  | 0.9961          | 0.6731   |
| 0.2869        | 26.8421 | 108  | 0.9953          | 0.6538   |
| 0.2869        | 27.8421 | 112  | 0.9716          | 0.7308   |
| 0.2869        | 28.8421 | 116  | 0.9851          | 0.7115   |
| 0.2901        | 29.8421 | 120  | 1.0567          | 0.6731   |
| 0.2901        | 30.8421 | 124  | 1.0905          | 0.7308   |
| 0.2901        | 31.8421 | 128  | 1.0009          | 0.6731   |
| 0.2548        | 32.8421 | 132  | 1.0158          | 0.6538   |
| 0.2548        | 33.8421 | 136  | 1.0908          | 0.7308   |
| 0.2548        | 34.8421 | 140  | 1.0802          | 0.6538   |
| 0.2359        | 35.8421 | 144  | 1.0642          | 0.6346   |
| 0.2359        | 36.8421 | 148  | 1.1139          | 0.6538   |
| 0.2359        | 37.8421 | 152  | 1.0740          | 0.6731   |
| 0.2295        | 38.8421 | 156  | 1.0772          | 0.7115   |
| 0.2295        | 39.8421 | 160  | 1.0724          | 0.6731   |
| 0.2295        | 40.8421 | 164  | 1.0859          | 0.6731   |
| 0.2234        | 41.8421 | 168  | 1.0928          | 0.6923   |
| 0.2234        | 42.8421 | 172  | 1.0850          | 0.6923   |
| 0.2234        | 43.8421 | 176  | 1.0761          | 0.6923   |
| 0.2086        | 44.8421 | 180  | 1.0766          | 0.6731   |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0

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