ansilmbabl/vit-base-patch16-224-in21k-Cards

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: 0.0861
• Train Accuracy: 0.9775
• Train Top-3-accuracy: 0.9991
• Validation Loss: 0.6749
• Validation Accuracy: 0.8113
• Validation Top-3-accuracy: 0.9740
• 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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 53200, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
• training_precision: mixed_float16

Training results

Train Loss	Train Accuracy	Train Top-3-accuracy	Validation Loss	Validation Accuracy	Validation Top-3-accuracy	Epoch
1.3188	0.6043	0.8822	0.8883	0.7130	0.9537	0
0.6864	0.7853	0.9705	0.6807	0.7647	0.9650	1
0.3966	0.8815	0.9896	0.5364	0.8120	0.9777	2
0.2310	0.9338	0.9964	0.4965	0.8427	0.9817	3
0.1333	0.9649	0.9981	0.4799	0.8513	0.9837	4
0.0861	0.9775	0.9991	0.6749	0.8113	0.9740	5

Framework versions

• Transformers 4.41.2
• TensorFlow 2.14.0
• Datasets 2.19.1
• Tokenizers 0.19.1