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# beans-leaf-disease-detection

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: 0.0404
- Accuracy: 0.9925
- Precision: 0.9926
- Recall: 0.9925
- F1: 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0492        | 0.7692 | 50   | 0.1117          | 0.9774   | 0.9776    | 0.9774 | 0.9774 |
| 0.0432        | 1.5385 | 100  | 0.1428          | 0.9624   | 0.9650    | 0.9624 | 0.9620 |
| 0.0119        | 2.3077 | 150  | 0.0736          | 0.9850   | 0.9851    | 0.9850 | 0.9850 |
| 0.0038        | 3.0769 | 200  | 0.0404          | 0.9925   | 0.9926    | 0.9925 | 0.9925 |
| 0.0046        | 3.8462 | 250  | 0.0472          | 0.9850   | 0.9856    | 0.9850 | 0.9850 |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1

angular_leaf_spot bean_rust healthy