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# dwiedarioo/vit-base-patch16-224-in21k-datascience6

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:
- Train Loss: 0.0096
- Train Accuracy: 0.9996
- Train Top-3-accuracy: 1.0
- Validation Loss: 0.0214
- Validation Accuracy: 0.9966
- Validation Top-3-accuracy: 1.0
- Epoch: 4

## 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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 2880, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16

### Training results

| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 0.2948     | 0.9267         | 0.9948               | 0.0826          | 0.9859              | 0.9994                    | 0     |
| 0.0568     | 0.9896         | 0.9999               | 0.0408          | 0.9923              | 1.0                       | 1     |
| 0.0247     | 0.9967         | 1.0                  | 0.0383          | 0.9917              | 1.0                       | 2     |
| 0.0142     | 0.9986         | 1.0                  | 0.0274          | 0.9948              | 1.0                       | 3     |
| 0.0096     | 0.9996         | 1.0                  | 0.0214          | 0.9966              | 1.0                       | 4     |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0

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