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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV39

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: 0.9091
- Accuracy: 0.75

## 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: 0.0001
- 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: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 1.0     | 4    | 1.3890          | 0.4318   |
| No log        | 2.0     | 8    | 1.2016          | 0.5682   |
| 4.424         | 3.0     | 12   | 1.0279          | 0.6364   |
| 4.424         | 4.0     | 16   | 0.9227          | 0.6477   |
| 4.424         | 5.0     | 20   | 0.9294          | 0.6818   |
| 2.6292        | 6.0     | 24   | 0.9936          | 0.625    |
| 2.6292        | 7.0     | 28   | 0.9816          | 0.6705   |
| 2.6292        | 8.0     | 32   | 0.9091          | 0.75     |
| 1.5117        | 9.0     | 36   | 0.8995          | 0.7159   |
| 1.5117        | 10.0    | 40   | 1.0646          | 0.7045   |
| 1.5117        | 11.0    | 44   | 1.1826          | 0.6705   |
| 0.7053        | 12.0    | 48   | 1.2360          | 0.6932   |
| 0.7053        | 13.0    | 52   | 1.4215          | 0.6818   |
| 0.7053        | 14.0    | 56   | 1.3694          | 0.7045   |
| 0.2599        | 15.0    | 60   | 1.2998          | 0.7159   |
| 0.2599        | 16.0    | 64   | 1.3703          | 0.7159   |
| 0.2599        | 17.0    | 68   | 1.4626          | 0.7159   |
| 0.1282        | 18.0    | 72   | 1.5181          | 0.7159   |
| 0.1282        | 19.0    | 76   | 1.5692          | 0.7045   |
| 0.1282        | 20.0    | 80   | 1.5965          | 0.6932   |
| 0.0816        | 21.0    | 84   | 1.6018          | 0.7045   |
| 0.0816        | 22.0    | 88   | 1.6046          | 0.7045   |
| 0.0816        | 22.6154 | 90   | 1.6049          | 0.7045   |


### Framework versions

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

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