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# Entrnal_eyes_data_7class_allNew_withother_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: 0.0693
- Train Accuracy: 0.9107
- Train Top-3-accuracy: 0.9914
- Validation Loss: 0.4731
- Validation Accuracy: 0.9137
- Validation Top-3-accuracy: 0.9918
- Epoch: 9

## 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': 1580, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 1.1195     | 0.5630         | 0.8481               | 0.7181          | 0.7020              | 0.9377                    | 0     |
| 0.5314     | 0.7457         | 0.9559               | 0.5566          | 0.7758              | 0.9668                    | 1     |
| 0.3817     | 0.7982         | 0.9725               | 0.4695          | 0.8146              | 0.9767                    | 2     |
| 0.2853     | 0.8284         | 0.9795               | 0.4379          | 0.8405              | 0.9819                    | 3     |
| 0.2111     | 0.8515         | 0.9837               | 0.4234          | 0.8605              | 0.9852                    | 4     |
| 0.1475     | 0.8695         | 0.9864               | 0.4329          | 0.8767              | 0.9874                    | 5     |
| 0.1070     | 0.8835         | 0.9882               | 0.4625          | 0.8896              | 0.9890                    | 6     |
| 0.0847     | 0.8948         | 0.9896               | 0.4766          | 0.8993              | 0.9901                    | 7     |
| 0.0745     | 0.9035         | 0.9906               | 0.4688          | 0.9073              | 0.9910                    | 8     |
| 0.0693     | 0.9107         | 0.9914               | 0.4731          | 0.9137              | 0.9918                    | 9     |


### Framework versions

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

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