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# vit4fruveg

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0004
- Accuracy: 1.0

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0488        | 0.8   | 100  | 0.0470          | 1.0      |
| 0.0174        | 1.6   | 200  | 0.0173          | 1.0      |
| 0.0074        | 2.4   | 300  | 0.0075          | 1.0      |
| 0.0035        | 3.2   | 400  | 0.0035          | 1.0      |
| 0.0018        | 4.0   | 500  | 0.0023          | 1.0      |
| 0.001         | 4.8   | 600  | 0.0011          | 1.0      |
| 0.0006        | 5.6   | 700  | 0.0007          | 1.0      |
| 0.0005        | 6.4   | 800  | 0.0005          | 1.0      |
| 0.0004        | 7.2   | 900  | 0.0004          | 1.0      |
| 0.0003        | 8.0   | 1000 | 0.0004          | 1.0      |


### Framework versions

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

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