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# Entrnal_eyes_data_4class_resize_224_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: 0.0823
- Train Accuracy: 0.9261
- Train Top-3-accuracy: 0.9972
- Validation Loss: 0.2588
- Validation Accuracy: 0.9299
- Validation Top-3-accuracy: 0.9974
- 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': 651, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 0.7993     | 0.6130         | 0.9518               | 0.5184          | 0.7611              | 0.9833                    | 0     |
| 0.3482     | 0.8052         | 0.9881               | 0.3126          | 0.8382              | 0.9913                    | 1     |
| 0.2260     | 0.8597         | 0.9929               | 0.2990          | 0.8739              | 0.9942                    | 2     |
| 0.1576     | 0.8861         | 0.9949               | 0.2597          | 0.8954              | 0.9956                    | 3     |
| 0.1191     | 0.9041         | 0.9960               | 0.2642          | 0.9106              | 0.9964                    | 4     |
| 0.0933     | 0.9167         | 0.9967               | 0.2598          | 0.9216              | 0.9970                    | 5     |
| 0.0823     | 0.9261         | 0.9972               | 0.2588          | 0.9299              | 0.9974                    | 6     |


### Framework versions

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

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