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# vit-base-beans

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: 0.0013
- 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1405        | 0.3448 | 100  | 0.0269          | 0.9981   |
| 0.0862        | 0.6897 | 200  | 0.0432          | 0.9865   |
| 0.0058        | 1.0345 | 300  | 0.0057          | 1.0      |
| 0.0038        | 1.3793 | 400  | 0.0037          | 1.0      |
| 0.0028        | 1.7241 | 500  | 0.0028          | 1.0      |
| 0.0022        | 2.0690 | 600  | 0.0022          | 1.0      |
| 0.0019        | 2.4138 | 700  | 0.0018          | 1.0      |
| 0.0016        | 2.7586 | 800  | 0.0016          | 1.0      |
| 0.0015        | 3.1034 | 900  | 0.0015          | 1.0      |
| 0.0014        | 3.4483 | 1000 | 0.0014          | 1.0      |
| 0.0013        | 3.7931 | 1100 | 0.0013          | 1.0      |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0

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