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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV34

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: 1.3276
- Accuracy: 0.6333

## 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: 40

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.8889  | 6    | 1.4254          | 0.45     |
| 5.9772        | 1.8889  | 12   | 1.3083          | 0.45     |
| 5.9772        | 2.8889  | 18   | 1.3032          | 0.4667   |
| 5.1141        | 3.8889  | 24   | 1.1521          | 0.5667   |
| 5.1141        | 4.8889  | 30   | 1.2171          | 0.4667   |
| 3.8959        | 5.8889  | 36   | 1.1281          | 0.4833   |
| 3.8959        | 6.8889  | 42   | 0.9969          | 0.6167   |
| 2.9663        | 7.8889  | 48   | 0.9814          | 0.65     |
| 2.9663        | 8.8889  | 54   | 0.8797          | 0.6333   |
| 2.416         | 9.8889  | 60   | 0.8956          | 0.6667   |
| 2.416         | 10.8889 | 66   | 0.8364          | 0.7      |
| 1.9336        | 11.8889 | 72   | 0.9800          | 0.65     |
| 1.9336        | 12.8889 | 78   | 0.8707          | 0.6833   |
| 1.5631        | 13.8889 | 84   | 0.9331          | 0.6333   |
| 1.5631        | 14.8889 | 90   | 1.0113          | 0.6333   |
| 1.1295        | 15.8889 | 96   | 1.0988          | 0.6167   |
| 1.1295        | 16.8889 | 102  | 1.0197          | 0.6833   |
| 1.1454        | 17.8889 | 108  | 1.2170          | 0.6167   |
| 1.1454        | 18.8889 | 114  | 1.1182          | 0.6667   |
| 0.8852        | 19.8889 | 120  | 1.1026          | 0.6833   |
| 0.8852        | 20.8889 | 126  | 1.0868          | 0.6333   |
| 0.7881        | 21.8889 | 132  | 1.1674          | 0.6333   |
| 0.7881        | 22.8889 | 138  | 1.1763          | 0.6667   |
| 0.7913        | 23.8889 | 144  | 1.3433          | 0.6333   |
| 0.7913        | 24.8889 | 150  | 1.1228          | 0.7      |
| 0.667         | 25.8889 | 156  | 1.2828          | 0.6667   |
| 0.667         | 26.8889 | 162  | 1.2373          | 0.6833   |
| 0.6299        | 27.8889 | 168  | 1.2951          | 0.6667   |
| 0.6299        | 28.8889 | 174  | 1.3410          | 0.6333   |
| 0.5409        | 29.8889 | 180  | 1.1852          | 0.7      |
| 0.5409        | 30.8889 | 186  | 1.4286          | 0.6167   |
| 0.6085        | 31.8889 | 192  | 1.2376          | 0.65     |
| 0.6085        | 32.8889 | 198  | 1.2249          | 0.6667   |
| 0.562         | 33.8889 | 204  | 1.3640          | 0.6333   |
| 0.562         | 34.8889 | 210  | 1.4234          | 0.6333   |
| 0.4543        | 35.8889 | 216  | 1.3489          | 0.6333   |
| 0.4543        | 36.8889 | 222  | 1.3273          | 0.6333   |
| 0.4708        | 37.8889 | 228  | 1.3215          | 0.6333   |
| 0.4708        | 38.8889 | 234  | 1.3277          | 0.6333   |
| 0.5217        | 39.8889 | 240  | 1.3276          | 0.6333   |


### Framework versions

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

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