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# vit-base-beans_50

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1514
- Accuracy: 0.9439

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 468  | 0.1514          | 0.9439   |
| 0.2863        | 2.0   | 936  | 0.1917          | 0.9303   |
| 0.2377        | 3.0   | 1404 | 0.1725          | 0.9333   |
| 0.2142        | 4.0   | 1872 | 0.1782          | 0.9288   |
| 0.2058        | 5.0   | 2340 | 0.1788          | 0.9273   |
| 0.1899        | 6.0   | 2808 | 0.1824          | 0.9318   |
| 0.1838        | 7.0   | 3276 | 0.1879          | 0.9333   |
| 0.1757        | 8.0   | 3744 | 0.2391          | 0.9333   |
| 0.1852        | 9.0   | 4212 | 0.1725          | 0.9409   |
| 0.1634        | 10.0  | 4680 | 0.1762          | 0.9394   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

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