Entrnal_eyes_data_5class_RVO_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: 0.0870
• Train Accuracy: 0.9372
• Train Top-3-accuracy: 0.9944
• Validation Loss: 0.2468
• Validation Accuracy: 0.9406
• Validation Top-3-accuracy: 0.9948
• 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': 784, '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
0.9323	0.6128	0.8870	0.4850	0.7838	0.9644	0
0.3507	0.8315	0.9758	0.3223	0.8593	0.9822	1
0.2174	0.8787	0.9858	0.2710	0.8925	0.9883	2
0.1573	0.9034	0.9899	0.3544	0.9108	0.9911	3
0.1231	0.9172	0.9920	0.2527	0.9235	0.9928	4
0.0963	0.9287	0.9934	0.2485	0.9333	0.9940	5
0.0870	0.9372	0.9944	0.2468	0.9406	0.9948	6

Framework versions

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