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# vit-plant-classification

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0182
- Accuracy: 0.9933

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0529        | 1.0   | 476  | 0.0660          | 0.9816   |
| 0.0609        | 2.0   | 952  | 0.0229          | 0.9939   |
| 0.0012        | 3.0   | 1428 | 0.0205          | 0.9951   |
| 0.0007        | 4.0   | 1904 | 0.0126          | 0.9969   |
| 0.0006        | 5.0   | 2380 | 0.0122          | 0.9969   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0

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