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# 0.50-200Train-100Test-swinv2-base

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1459
- Accuracy: 0.8183

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 17

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.7214        | 0.9931  | 36   | 1.0786          | 0.6515   |
| 0.6184        | 1.9862  | 72   | 0.7491          | 0.7651   |
| 0.357         | 2.9793  | 108  | 0.7632          | 0.7764   |
| 0.2085        | 4.0     | 145  | 0.8125          | 0.7860   |
| 0.1343        | 4.9931  | 181  | 0.7920          | 0.7974   |
| 0.0641        | 5.9862  | 217  | 0.8851          | 0.7860   |
| 0.0515        | 6.9793  | 253  | 1.0784          | 0.7817   |
| 0.041         | 8.0     | 290  | 1.0600          | 0.7965   |
| 0.0338        | 8.9931  | 326  | 1.0860          | 0.8131   |
| 0.013         | 9.9862  | 362  | 1.0956          | 0.8148   |
| 0.016         | 10.9793 | 398  | 1.2115          | 0.7991   |
| 0.0154        | 12.0    | 435  | 1.1470          | 0.8105   |
| 0.011         | 12.9931 | 471  | 1.1045          | 0.8105   |
| 0.0027        | 13.9862 | 507  | 1.1310          | 0.8096   |
| 0.0042        | 14.9793 | 543  | 1.1808          | 0.8227   |
| 0.0016        | 16.0    | 580  | 1.1575          | 0.8157   |
| 0.0007        | 16.8828 | 612  | 1.1459          | 0.8183   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1

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