Entrnal_eyes_data_6_true_agoiment211_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: 0.1455
• Train Accuracy: 0.9282
• Train Top-3-accuracy: 0.9908
• Validation Loss: 0.3319
• Validation Accuracy: 0.9322
• Validation Top-3-accuracy: 0.9914
• 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': 434, '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
1.1623	0.5608	0.8521	0.7419	0.7200	0.9394	0
0.5255	0.7824	0.9588	0.4509	0.8190	0.9701	1
0.3218	0.8454	0.9759	0.3839	0.8644	0.9803	2
0.2230	0.8794	0.9830	0.3494	0.8923	0.9852	3
0.1755	0.9022	0.9868	0.3445	0.9104	0.9882	4
0.1539	0.9173	0.9892	0.3343	0.9231	0.9901	5
0.1455	0.9282	0.9908	0.3319	0.9322	0.9914	6

Framework versions

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