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# Rice-Plant-Disease-Detection-Model

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: 0.2929
- Accuracy: 0.8958
- F1: 0.8965

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5517        | 1.0   | 18   | 0.5222          | 0.875    | 0.8754 |
| 0.2996        | 2.0   | 36   | 0.3833          | 0.8542   | 0.8564 |
| 0.1529        | 3.0   | 54   | 0.3152          | 0.875    | 0.8763 |
| 0.0843        | 4.0   | 72   | 0.2929          | 0.8958   | 0.8965 |
| 0.0549        | 5.0   | 90   | 0.2756          | 0.875    | 0.8754 |
| 0.0402        | 6.0   | 108  | 0.2765          | 0.875    | 0.8754 |
| 0.0327        | 7.0   | 126  | 0.2875          | 0.875    | 0.8754 |
| 0.0277        | 8.0   | 144  | 0.2938          | 0.875    | 0.8754 |
| 0.0244        | 9.0   | 162  | 0.2992          | 0.875    | 0.8754 |
| 0.0222        | 10.0  | 180  | 0.2996          | 0.8958   | 0.8960 |
| 0.0203        | 11.0  | 198  | 0.3052          | 0.8958   | 0.8960 |
| 0.019         | 12.0  | 216  | 0.3087          | 0.8958   | 0.8960 |
| 0.018         | 13.0  | 234  | 0.3143          | 0.8958   | 0.8960 |
| 0.0171        | 14.0  | 252  | 0.3206          | 0.8958   | 0.8960 |
| 0.0164        | 15.0  | 270  | 0.3227          | 0.8958   | 0.8960 |
| 0.0158        | 16.0  | 288  | 0.3250          | 0.8958   | 0.8960 |
| 0.0155        | 17.0  | 306  | 0.3257          | 0.8958   | 0.8960 |
| 0.0152        | 18.0  | 324  | 0.3264          | 0.8958   | 0.8960 |
| 0.015         | 19.0  | 342  | 0.3276          | 0.8958   | 0.8960 |
| 0.0149        | 20.0  | 360  | 0.3275          | 0.8958   | 0.8960 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cpu
- Datasets 2.14.5
- Tokenizers 0.14.0

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