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

This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-large-patch4-window12-192-22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7669
- Accuracy: 0.8233

## 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: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.4602        | 0.9825  | 14   | 1.7254          | 0.4318   |
| 1.7105        | 1.9649  | 28   | 0.8579          | 0.7047   |
| 0.6096        | 2.9474  | 42   | 0.7268          | 0.7562   |
| 0.3983        | 4.0     | 57   | 0.6706          | 0.7852   |
| 0.1083        | 4.9825  | 71   | 0.7051          | 0.7897   |
| 0.0952        | 5.9649  | 85   | 0.8423          | 0.7696   |
| 0.1106        | 6.9474  | 99   | 0.6406          | 0.8121   |
| 0.0357        | 8.0     | 114  | 0.8410          | 0.7897   |
| 0.0522        | 8.9825  | 128  | 0.8197          | 0.7987   |
| 0.0274        | 9.9649  | 142  | 0.8788          | 0.8098   |
| 0.0203        | 10.9474 | 156  | 0.8037          | 0.8233   |
| 0.0361        | 12.0    | 171  | 0.7932          | 0.8076   |
| 0.0204        | 12.9825 | 185  | 0.7503          | 0.8210   |
| 0.0165        | 13.9649 | 199  | 0.7416          | 0.8098   |
| 0.0129        | 14.9474 | 213  | 0.8474          | 0.8277   |
| 0.0062        | 16.0    | 228  | 0.7788          | 0.8233   |
| 0.0028        | 16.9825 | 242  | 0.7687          | 0.8255   |
| 0.001         | 17.9649 | 256  | 0.7730          | 0.8255   |
| 0.0019        | 18.9474 | 270  | 0.7681          | 0.8255   |
| 0.0014        | 19.6491 | 280  | 0.7669          | 0.8233   |


### Framework versions

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

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