Entrnal_eyes_data_4class_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: 0.0823
• 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