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# swin-large-patch4-window7-224-in22k-limb

This model is a fine-tuned version of [microsoft/swin-large-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-large-patch4-window7-224-in22k) on the c14kevincardenas/beta_caller_284 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9104
- Accuracy: 0.6153

## 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: 2014
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.005

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.381         | 1.0   | 215  | 1.3791          | 0.2784   |
| 1.2719        | 2.0   | 430  | 1.2902          | 0.3435   |
| 1.2584        | 3.0   | 645  | 1.1300          | 0.4423   |
| 1.1503        | 4.0   | 860  | 1.0864          | 0.5049   |
| 1.0337        | 5.0   | 1075 | 1.1408          | 0.5239   |
| 1.0062        | 6.0   | 1290 | 1.0178          | 0.5428   |
| 0.9712        | 7.0   | 1505 | 0.9268          | 0.5906   |
| 0.9287        | 8.0   | 1720 | 0.9192          | 0.5939   |
| 0.8887        | 9.0   | 1935 | 0.9256          | 0.6161   |
| 0.845         | 10.0  | 2150 | 0.9255          | 0.6096   |
| 0.8045        | 11.0  | 2365 | 0.9433          | 0.6269   |
| 0.8685        | 12.0  | 2580 | 0.9104          | 0.6153   |
| 0.806         | 13.0  | 2795 | 0.9112          | 0.6285   |
| 0.7729        | 14.0  | 3010 | 0.9369          | 0.6483   |
| 0.7582        | 15.0  | 3225 | 1.0296          | 0.6244   |
| 0.77          | 16.0  | 3440 | 0.9607          | 0.6367   |
| 0.7218        | 17.0  | 3655 | 1.0158          | 0.6326   |
| 0.7389        | 18.0  | 3870 | 0.9320          | 0.6433   |
| 0.6532        | 19.0  | 4085 | 0.9733          | 0.6639   |
| 0.6812        | 20.0  | 4300 | 1.0518          | 0.6516   |
| 0.6697        | 21.0  | 4515 | 1.0159          | 0.6409   |
| 0.6968        | 22.0  | 4730 | 1.0112          | 0.6483   |
| 0.6087        | 23.0  | 4945 | 1.0446          | 0.6639   |
| 0.6268        | 24.0  | 5160 | 1.0730          | 0.6656   |
| 0.6092        | 25.0  | 5375 | 1.0707          | 0.6680   |
| 0.5765        | 26.0  | 5590 | 1.0561          | 0.6573   |
| 0.6332        | 27.0  | 5805 | 1.0880          | 0.6614   |
| 0.6267        | 28.0  | 6020 | 1.1181          | 0.6474   |
| 0.6283        | 29.0  | 6235 | 1.0807          | 0.6507   |
| 0.5614        | 30.0  | 6450 | 1.0881          | 0.6524   |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1

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