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# vit-base-beans

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 beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0226
- Accuracy: 0.9925

## 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: 0.0002
- 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3365        | 0.38  | 50   | 0.2455          | 0.9323   |
| 0.1728        | 0.77  | 100  | 0.1544          | 0.9549   |
| 0.1519        | 1.15  | 150  | 0.1072          | 0.9624   |
| 0.0209        | 1.54  | 200  | 0.1594          | 0.9624   |
| 0.0206        | 1.92  | 250  | 0.0913          | 0.9699   |
| 0.0135        | 2.31  | 300  | 0.1488          | 0.9624   |
| 0.0079        | 2.69  | 350  | 0.0226          | 0.9925   |
| 0.0074        | 3.08  | 400  | 0.0582          | 0.9925   |
| 0.0064        | 3.46  | 450  | 0.0984          | 0.9774   |
| 0.0061        | 3.85  | 500  | 0.1151          | 0.9699   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3

angular_leaf_spot bean_rust healthy