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# Vit_Guava

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: 0.0036
- 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 OptimizerNames.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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1092        | 0.4651 | 100  | 0.0675          | 0.9918   |
| 0.0334        | 0.9302 | 200  | 0.0861          | 0.9785   |
| 0.0188        | 1.3953 | 300  | 0.0506          | 0.9847   |
| 0.0074        | 1.8605 | 400  | 0.0236          | 0.9949   |
| 0.016         | 2.3256 | 500  | 0.0092          | 0.9980   |
| 0.0041        | 2.7907 | 600  | 0.0044          | 1.0      |
| 0.0038        | 3.2558 | 700  | 0.0039          | 1.0      |
| 0.0035        | 3.7209 | 800  | 0.0036          | 1.0      |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0

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