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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV22

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: 1.0386
- Accuracy: 0.6346

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 0.3
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 3.1723        | 1.0     | 22   | 1.6164          | 0.1923   |
| 2.8734        | 2.0     | 44   | 1.4347          | 0.3846   |
| 2.1553        | 3.0     | 66   | 1.1520          | 0.4808   |
| 1.6674        | 4.0     | 88   | 1.0921          | 0.4808   |
| 1.1204        | 5.0     | 110  | 0.9091          | 0.5962   |
| 1.0373        | 6.0     | 132  | 0.8185          | 0.6923   |
| 0.9181        | 7.0     | 154  | 0.9377          | 0.6731   |
| 0.7475        | 8.0     | 176  | 0.8407          | 0.6731   |
| 0.6679        | 9.0     | 198  | 0.9488          | 0.6923   |
| 0.4914        | 10.0    | 220  | 0.8699          | 0.7115   |
| 0.4421        | 11.0    | 242  | 1.1132          | 0.6538   |
| 0.3759        | 12.0    | 264  | 0.9250          | 0.7115   |
| 0.4317        | 13.0    | 286  | 0.9220          | 0.6731   |
| 0.4137        | 14.0    | 308  | 1.0225          | 0.7115   |
| 0.3451        | 15.0    | 330  | 1.0872          | 0.6538   |
| 0.3482        | 16.0    | 352  | 1.0129          | 0.6731   |
| 0.3346        | 17.0    | 374  | 1.0314          | 0.6538   |
| 0.3105        | 18.0    | 396  | 1.0348          | 0.6538   |
| 0.252         | 19.0    | 418  | 1.0386          | 0.6346   |
| 0.317         | 19.0930 | 420  | 1.0386          | 0.6346   |


### Framework versions

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

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