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# eyesCare_firstTryEntrnal_mix_model-1

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: 0.0066
- Train Accuracy: 0.8616
- Train Top-3-accuracy: 0.9785
- Validation Loss: 1.9942
- Validation Accuracy: 0.8627
- Validation Top-3-accuracy: 0.9787
- Epoch: 29

## 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': 4e-05, 'decay_steps': 4950, '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': 0.001}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 1.3981     | 0.3217         | 0.7428               | 1.1812          | 0.4135              | 0.8283                    | 0     |
| 1.1137     | 0.4540         | 0.8600               | 1.0974          | 0.4763              | 0.8802                    | 1     |
| 0.9296     | 0.5034         | 0.8955               | 1.0739          | 0.5231              | 0.9065                    | 2     |
| 0.7444     | 0.5473         | 0.9155               | 1.1126          | 0.5663              | 0.9225                    | 3     |
| 0.5534     | 0.5880         | 0.9285               | 1.1673          | 0.6076              | 0.9342                    | 4     |
| 0.4105     | 0.6261         | 0.9387               | 1.1547          | 0.6422              | 0.9428                    | 5     |
| 0.2830     | 0.6586         | 0.9462               | 1.3119          | 0.6729              | 0.9493                    | 6     |
| 0.1984     | 0.6874         | 0.9519               | 1.3821          | 0.6990              | 0.9540                    | 7     |
| 0.1224     | 0.7104         | 0.9559               | 1.4778          | 0.7213              | 0.9576                    | 8     |
| 0.1021     | 0.7313         | 0.9591               | 1.5426          | 0.7400              | 0.9603                    | 9     |
| 0.1017     | 0.7478         | 0.9615               | 1.6387          | 0.7545              | 0.9625                    | 10    |
| 0.0646     | 0.7613         | 0.9635               | 1.6226          | 0.7678              | 0.9644                    | 11    |
| 0.0500     | 0.7738         | 0.9654               | 1.6646          | 0.7793              | 0.9662                    | 12    |
| 0.0571     | 0.7843         | 0.9669               | 1.7492          | 0.7890              | 0.9675                    | 13    |
| 0.0248     | 0.7935         | 0.9682               | 1.6984          | 0.7978              | 0.9689                    | 14    |
| 0.0185     | 0.8020         | 0.9695               | 1.7302          | 0.8059              | 0.9701                    | 15    |
| 0.0145     | 0.8096         | 0.9707               | 1.7669          | 0.8129              | 0.9712                    | 16    |
| 0.0129     | 0.8163         | 0.9718               | 1.7972          | 0.8193              | 0.9722                    | 17    |
| 0.0116     | 0.8223         | 0.9727               | 1.8276          | 0.8251              | 0.9732                    | 18    |
| 0.0106     | 0.8277         | 0.9736               | 1.8544          | 0.8302              | 0.9739                    | 19    |
| 0.0098     | 0.8326         | 0.9743               | 1.8792          | 0.8348              | 0.9746                    | 20    |
| 0.0091     | 0.8370         | 0.9749               | 1.9012          | 0.8391              | 0.9752                    | 21    |
| 0.0085     | 0.8411         | 0.9755               | 1.9212          | 0.8430              | 0.9758                    | 22    |
| 0.0080     | 0.8448         | 0.9761               | 1.9391          | 0.8465              | 0.9763                    | 23    |
| 0.0076     | 0.8482         | 0.9766               | 1.9547          | 0.8498              | 0.9768                    | 24    |
| 0.0073     | 0.8513         | 0.9770               | 1.9682          | 0.8527              | 0.9772                    | 25    |
| 0.0070     | 0.8542         | 0.9774               | 1.9789          | 0.8555              | 0.9777                    | 26    |
| 0.0068     | 0.8568         | 0.9778               | 1.9871          | 0.8580              | 0.9780                    | 27    |
| 0.0067     | 0.8593         | 0.9782               | 1.9924          | 0.8605              | 0.9784                    | 28    |
| 0.0066     | 0.8616         | 0.9785               | 1.9942          | 0.8627              | 0.9787                    | 29    |


### Framework versions

- Transformers 4.44.2
- TensorFlow 2.15.0
- Datasets 2.21.0
- Tokenizers 0.19.1

mild moderate no_dr proliferative_dr severe