--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_keras_callback model-index: - name: Entrnal_eyes_data_4class_resize_224_model results: [] --- # 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