Entrnal_eyes_data_6class_allNew_not_other_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: 0.0917
• Train Accuracy: 0.9468
• Train Top-3-accuracy: 0.9954
• Validation Loss: 0.2431
• Validation Accuracy: 0.9496
• Validation Top-3-accuracy: 0.9957
• 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': 917, '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
0.9132	0.6556	0.9035	0.4997	0.8161	0.9711	0
0.3301	0.8571	0.9805	0.3293	0.8811	0.9856	1
0.2152	0.8971	0.9883	0.2990	0.9090	0.9902	2
0.1612	0.9176	0.9915	0.2913	0.9244	0.9926	3
0.1231	0.9302	0.9933	0.2531	0.9354	0.9940	4
0.1020	0.9397	0.9945	0.2420	0.9436	0.9950	5
0.0917	0.9468	0.9954	0.2431	0.9496	0.9957	6

Framework versions

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