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# Entrnal_eyes_data_6_true_agoiment211_model2

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: 0.0883
- Train Accuracy: 0.9406
- Train Top-3-accuracy: 0.9940
- Validation Loss: 0.2930
- Validation Accuracy: 0.9430
- Validation Top-3-accuracy: 0.9943
- 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': 620, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 1.1642     | 0.5159         | 0.8895               | 0.8054          | 0.6679              | 0.9485                    | 0     |
| 0.5389     | 0.7360         | 0.9637               | 0.4377          | 0.7847              | 0.9737                    | 1     |
| 0.3063     | 0.8169         | 0.9788               | 0.3756          | 0.8425              | 0.9825                    | 2     |
| 0.2024     | 0.8607         | 0.9848               | 0.3307          | 0.8758              | 0.9868                    | 3     |
| 0.1515     | 0.8875         | 0.9882               | 0.3064          | 0.8976              | 0.9893                    | 4     |
| 0.1205     | 0.9058         | 0.9902               | 0.2965          | 0.9127              | 0.9909                    | 5     |
| 0.1071     | 0.9184         | 0.9916               | 0.2962          | 0.9234              | 0.9921                    | 6     |
| 0.0969     | 0.9277         | 0.9926               | 0.2831          | 0.9316              | 0.9930                    | 7     |
| 0.0948     | 0.9348         | 0.9934               | 0.2905          | 0.9379              | 0.9937                    | 8     |
| 0.0883     | 0.9406         | 0.9940               | 0.2930          | 0.9430              | 0.9943                    | 9     |


### Framework versions

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

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