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# 0.50-500Train-100Test-swinv2-base

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9122
- Accuracy: 0.8166

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6786        | 0.9946 | 46   | 0.7632          | 0.7450   |
| 0.2976        | 1.9892 | 92   | 0.8048          | 0.7677   |
| 0.1158        | 2.9838 | 138  | 0.8201          | 0.7860   |
| 0.0738        | 4.0    | 185  | 0.9474          | 0.7878   |
| 0.0354        | 4.9946 | 231  | 0.9128          | 0.8      |
| 0.0129        | 5.9892 | 277  | 0.8934          | 0.8105   |
| 0.0106        | 6.9622 | 322  | 0.9122          | 0.8166   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1

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