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# vit-base-patch16-224-5class224

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0115
- Train Accuracy: 0.9460
- Train Top-3-accuracy: 0.9911
- Validation Loss: 0.1621
- Validation Accuracy: 0.9490
- Validation Top-3-accuracy: 0.9916
- Epoch: 6

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 574, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 0.7725     | 0.6414         | 0.8898               | 0.3755          | 0.7636              | 0.9478                    | 0     |
| 0.2160     | 0.8219         | 0.9635               | 0.2372          | 0.8557              | 0.9726                    | 1     |
| 0.0696     | 0.8812         | 0.9780               | 0.2035          | 0.8989              | 0.9818                    | 2     |
| 0.0344     | 0.9108         | 0.9842               | 0.1715          | 0.9203              | 0.9860                    | 3     |
| 0.0194     | 0.9278         | 0.9875               | 0.1911          | 0.9337              | 0.9888                    | 4     |
| 0.0147     | 0.9381         | 0.9897               | 0.1651          | 0.9425              | 0.9904                    | 5     |
| 0.0115     | 0.9460         | 0.9911               | 0.1621          | 0.9490              | 0.9916                    | 6     |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1

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