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# vit-4-veggies

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 darthraider/fruit-ripeness-detection-dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0606
- Accuracy: 0.9879

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3154        | 0.6494 | 100  | 0.3098          | 0.9435   |
| 0.1446        | 1.2987 | 200  | 0.2217          | 0.9435   |
| 0.0814        | 1.9481 | 300  | 0.1310          | 0.9717   |
| 0.0438        | 2.5974 | 400  | 0.0875          | 0.9830   |
| 0.0212        | 3.2468 | 500  | 0.1199          | 0.9766   |
| 0.0212        | 3.8961 | 600  | 0.0606          | 0.9879   |
| 0.002         | 4.5455 | 700  | 0.0803          | 0.9863   |
| 0.0011        | 5.1948 | 800  | 0.0745          | 0.9871   |
| 0.0008        | 5.8442 | 900  | 0.0809          | 0.9879   |
| 0.0005        | 6.4935 | 1000 | 0.0861          | 0.9887   |
| 0.0005        | 7.1429 | 1100 | 0.0865          | 0.9879   |
| 0.0004        | 7.7922 | 1200 | 0.0788          | 0.9879   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0

damaged dried old ripe unripe