Entrnal_eyes_data_5class_RVO_newNormal_resize_224_model

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0885
• Train Accuracy: 0.9332
• Train Top-3-accuracy: 0.9946
• Validation Loss: 0.2622
• Validation Accuracy: 0.9369
• Validation Top-3-accuracy: 0.9950
• 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': 777, '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
0.9273	0.5844	0.9067	0.5047	0.7651	0.9651	0
0.3467	0.8197	0.9763	0.3231	0.8519	0.9828	1
0.2263	0.8717	0.9862	0.3327	0.8846	0.9886	2
0.1624	0.8956	0.9902	0.2742	0.9047	0.9914	3
0.1247	0.9124	0.9923	0.2696	0.9190	0.9931	4
0.1000	0.9243	0.9937	0.2560	0.9292	0.9942	5
0.0885	0.9332	0.9946	0.2622	0.9369	0.9950	6

Framework versions

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