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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV57

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: 0.8727
- 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: cosine_with_restarts
- 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    | 1.5807          | 0.2885   |
| No log        | 1.8421  | 8    | 1.4549          | 0.4423   |
| 1.6981        | 2.8421  | 12   | 1.3224          | 0.4231   |
| 1.6981        | 3.8421  | 16   | 1.2079          | 0.5      |
| 1.6981        | 4.8421  | 20   | 1.0541          | 0.5769   |
| 1.2915        | 5.8421  | 24   | 0.9398          | 0.6346   |
| 1.2915        | 6.8421  | 28   | 0.9887          | 0.5577   |
| 1.2915        | 7.8421  | 32   | 0.8991          | 0.6538   |
| 0.8599        | 8.8421  | 36   | 0.9379          | 0.5577   |
| 0.8599        | 9.8421  | 40   | 0.8260          | 0.6923   |
| 0.8599        | 10.8421 | 44   | 0.9418          | 0.6731   |
| 0.6803        | 11.8421 | 48   | 0.9368          | 0.5769   |
| 0.6803        | 12.8421 | 52   | 0.9148          | 0.5962   |
| 0.6803        | 13.8421 | 56   | 0.9135          | 0.6346   |
| 0.5562        | 14.8421 | 60   | 0.8477          | 0.6731   |
| 0.5562        | 15.8421 | 64   | 0.8730          | 0.5962   |
| 0.5562        | 16.8421 | 68   | 0.8420          | 0.6923   |
| 0.4696        | 17.8421 | 72   | 0.9168          | 0.5962   |
| 0.4696        | 18.8421 | 76   | 0.9373          | 0.6538   |
| 0.4696        | 19.8421 | 80   | 0.8634          | 0.6538   |
| 0.3975        | 20.8421 | 84   | 0.8695          | 0.6538   |
| 0.3975        | 21.8421 | 88   | 0.8958          | 0.6923   |
| 0.3975        | 22.8421 | 92   | 0.8914          | 0.6731   |
| 0.3185        | 23.8421 | 96   | 0.8727          | 0.7308   |
| 0.3185        | 24.8421 | 100  | 0.9820          | 0.6923   |
| 0.3185        | 25.8421 | 104  | 0.9263          | 0.6923   |
| 0.2758        | 26.8421 | 108  | 1.0548          | 0.5962   |
| 0.2758        | 27.8421 | 112  | 0.9833          | 0.6731   |
| 0.2758        | 28.8421 | 116  | 0.9492          | 0.6923   |
| 0.2667        | 29.8421 | 120  | 0.9466          | 0.6346   |
| 0.2667        | 30.8421 | 124  | 0.9828          | 0.6923   |
| 0.2667        | 31.8421 | 128  | 1.1056          | 0.6923   |
| 0.2396        | 32.8421 | 132  | 1.0083          | 0.6731   |
| 0.2396        | 33.8421 | 136  | 1.0040          | 0.6923   |
| 0.2396        | 34.8421 | 140  | 1.0727          | 0.6731   |
| 0.2173        | 35.8421 | 144  | 1.0953          | 0.6923   |
| 0.2173        | 36.8421 | 148  | 1.0802          | 0.6538   |
| 0.2173        | 37.8421 | 152  | 1.0446          | 0.6923   |
| 0.2313        | 38.8421 | 156  | 1.0331          | 0.7115   |
| 0.2313        | 39.8421 | 160  | 1.0334          | 0.6923   |
| 0.2313        | 40.8421 | 164  | 1.0364          | 0.6923   |
| 0.2129        | 41.8421 | 168  | 1.0413          | 0.6731   |
| 0.2129        | 42.8421 | 172  | 1.0407          | 0.6731   |
| 0.2129        | 43.8421 | 176  | 1.0405          | 0.6731   |
| 0.2026        | 44.8421 | 180  | 1.0401          | 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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