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# Entrenal_eyes_5clasess_withOther_model

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: 0.0845
- Train Accuracy: 0.9283
- Train Top-3-accuracy: 0.9936
- Validation Loss: 0.4386
- Validation Accuracy: 0.9313
- Validation Top-3-accuracy: 0.9940
- 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': 847, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 0.8358     | 0.6703         | 0.9165               | 0.5139          | 0.7995              | 0.9693                    | 0     |
| 0.3540     | 0.8366         | 0.9783               | 0.4737          | 0.8589              | 0.9835                    | 1     |
| 0.2235     | 0.8749         | 0.9862               | 0.3874          | 0.8876              | 0.9884                    | 2     |
| 0.1607     | 0.8972         | 0.9898               | 0.4559          | 0.9045              | 0.9908                    | 3     |
| 0.1204     | 0.9109         | 0.9914               | 0.4410          | 0.9163              | 0.9921                    | 4     |
| 0.0961     | 0.9208         | 0.9927               | 0.4393          | 0.9246              | 0.9932                    | 5     |
| 0.0845     | 0.9283         | 0.9936               | 0.4386          | 0.9313              | 0.9940                    | 6     |


### Framework versions

- Transformers 4.44.2
- TensorFlow 2.15.1
- Datasets 3.0.0
- Tokenizers 0.19.1

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