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# swin-tiny-patch4-window7-224-lcbsi-wbc-new

This model is a fine-tuned version of [polejowska/swin-tiny-patch4-window7-224-lcbsi-wbc](https://huggingface.co/polejowska/swin-tiny-patch4-window7-224-lcbsi-wbc) on the WBC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0457
- Accuracy: 0.992
- Precision: 0.9920
- Recall: 0.992
- F1: 0.9920

## 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: 0.0002562
- 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0936        | 0.98  | 27   | 0.0724          | 0.984    | 0.9841    | 0.984  | 0.9840 |
| 0.0276        | 1.98  | 54   | 0.0768          | 0.984    | 0.9841    | 0.984  | 0.9839 |
| 0.0133        | 2.98  | 81   | 0.0457          | 0.992    | 0.9920    | 0.992  | 0.9920 |


### Framework versions

- Transformers 4.25.1
- Pytorch 2.0.0.dev20230107
- Datasets 2.8.0
- Tokenizers 0.13.2

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