glacoma_andOther_model1

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: 0.0575
• Train Accuracy: 0.9403
• Train Top-3-accuracy: 0.9984
• Validation Loss: 0.2329
• Validation Accuracy: 0.9442
• Validation Top-3-accuracy: 0.9985
• Epoch: 5

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': 1266, '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
0.5871	0.7237	0.9808	0.3574	0.8358	0.9916	0
0.2606	0.8643	0.9942	0.2785	0.8821	0.9958	1
0.1643	0.8966	0.9966	0.2490	0.9077	0.9971	2
0.1114	0.9168	0.9975	0.2644	0.9239	0.9978	3
0.0797	0.9301	0.9980	0.2345	0.9353	0.9982	4
0.0575	0.9403	0.9984	0.2329	0.9442	0.9985	5

Framework versions

• Transformers 4.44.2
• TensorFlow 2.15.0
• Datasets 2.21.0
• Tokenizers 0.19.1