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# Entrnal_eyes_data_6_true_agoiment211_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: 0.1455
- Train Accuracy: 0.9282
- Train Top-3-accuracy: 0.9908
- Validation Loss: 0.3319
- Validation Accuracy: 0.9322
- Validation Top-3-accuracy: 0.9914
- 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': 434, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 1.1623     | 0.5608         | 0.8521               | 0.7419          | 0.7200              | 0.9394                    | 0     |
| 0.5255     | 0.7824         | 0.9588               | 0.4509          | 0.8190              | 0.9701                    | 1     |
| 0.3218     | 0.8454         | 0.9759               | 0.3839          | 0.8644              | 0.9803                    | 2     |
| 0.2230     | 0.8794         | 0.9830               | 0.3494          | 0.8923              | 0.9852                    | 3     |
| 0.1755     | 0.9022         | 0.9868               | 0.3445          | 0.9104              | 0.9882                    | 4     |
| 0.1539     | 0.9173         | 0.9892               | 0.3343          | 0.9231              | 0.9901                    | 5     |
| 0.1455     | 0.9282         | 0.9908               | 0.3319          | 0.9322              | 0.9914                    | 6     |


### Framework versions

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

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