Imene/vit-base-patch16-224-in21k-iiii

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: 2.8947
• Train Accuracy: 0.5439
• Train Top-3-accuracy: 0.7916
• Validation Loss: 3.0482
• Validation Accuracy: 0.3907
• Validation Top-3-accuracy: 0.6302
• Epoch: 4

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': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 540, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, '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
3.8068	0.0843	0.2108	3.6116	0.1721	0.3593	0
3.4497	0.2735	0.4840	3.3654	0.2779	0.4953	1
3.1913	0.3991	0.6314	3.1839	0.3512	0.5977	2
3.0017	0.4878	0.7311	3.0867	0.3872	0.6233	3
2.8947	0.5439	0.7916	3.0482	0.3907	0.6302	4

Framework versions

• Transformers 4.21.2
• TensorFlow 2.8.2
• Datasets 2.4.0
• Tokenizers 0.12.1