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

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: 0.1240
- Train Accuracy: 0.9989
- Train Top-3-accuracy: 1.0
- Validation Loss: 0.2638
- Validation Accuracy: 0.9568
- Validation Top-3-accuracy: 0.9892
- Epoch: 10

## 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': 8200, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 2.2501     | 0.3937         | 0.6346               | 1.8763          | 0.5551              | 0.8035                    | 0     |
| 1.5448     | 0.6808         | 0.8732               | 1.3666          | 0.7127              | 0.8812                    | 1     |
| 1.0471     | 0.8324         | 0.9439               | 0.9732          | 0.8402              | 0.9568                    | 2     |
| 0.7074     | 0.9385         | 0.9828               | 0.7078          | 0.9266              | 0.9849                    | 3     |
| 0.4854     | 0.9748         | 0.9924               | 0.5190          | 0.9374              | 0.9892                    | 4     |
| 0.3465     | 0.9905         | 0.9962               | 0.4126          | 0.9482              | 0.9935                    | 5     |
| 0.2571     | 0.9950         | 0.9981               | 0.3267          | 0.9719              | 0.9957                    | 6     |
| 0.2031     | 0.9962         | 0.9992               | 0.2788          | 0.9741              | 0.9957                    | 7     |
| 0.1667     | 0.9985         | 1.0                  | 0.2484          | 0.9698              | 0.9957                    | 8     |
| 0.1398     | 0.9992         | 1.0                  | 0.2225          | 0.9719              | 0.9957                    | 9     |
| 0.1240     | 0.9989         | 1.0                  | 0.2638          | 0.9568              | 0.9892                    | 10    |


### Framework versions

- Transformers 4.35.0
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1

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