Entrenal_eyes_5clasess_withOther_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: 0.0845
• Train Accuracy: 0.9283
• Train Top-3-accuracy: 0.9936
• Validation Loss: 0.4386
• Validation Accuracy: 0.9313
• Validation Top-3-accuracy: 0.9940
• 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': 847, '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
0.8358	0.6703	0.9165	0.5139	0.7995	0.9693	0
0.3540	0.8366	0.9783	0.4737	0.8589	0.9835	1
0.2235	0.8749	0.9862	0.3874	0.8876	0.9884	2
0.1607	0.8972	0.9898	0.4559	0.9045	0.9908	3
0.1204	0.9109	0.9914	0.4410	0.9163	0.9921	4
0.0961	0.9208	0.9927	0.4393	0.9246	0.9932	5
0.0845	0.9283	0.9936	0.4386	0.9313	0.9940	6

Framework versions

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