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# glacoma_andOther_model1

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: 0.0575
- Train Accuracy: 0.9403
- Train Top-3-accuracy: 0.9984
- Validation Loss: 0.2329
- Validation Accuracy: 0.9442
- Validation Top-3-accuracy: 0.9985
- Epoch: 5

## 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': 1266, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 0.5871     | 0.7237         | 0.9808               | 0.3574          | 0.8358              | 0.9916                    | 0     |
| 0.2606     | 0.8643         | 0.9942               | 0.2785          | 0.8821              | 0.9958                    | 1     |
| 0.1643     | 0.8966         | 0.9966               | 0.2490          | 0.9077              | 0.9971                    | 2     |
| 0.1114     | 0.9168         | 0.9975               | 0.2644          | 0.9239              | 0.9978                    | 3     |
| 0.0797     | 0.9301         | 0.9980               | 0.2345          | 0.9353              | 0.9982                    | 4     |
| 0.0575     | 0.9403         | 0.9984               | 0.2329          | 0.9442              | 0.9985                    | 5     |


### Framework versions

- Transformers 4.44.2
- TensorFlow 2.15.0
- Datasets 2.21.0
- Tokenizers 0.19.1

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