Zynovia/vit-base-patch16-224-in21k-wwwwii

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: 0.8976
• Train Accuracy: 0.8813
• Train Top-3-accuracy: 0.9721
• Validation Loss: 1.6144
• Validation Accuracy: 0.5845
• Validation Top-3-accuracy: 0.7845
• 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': 6e-05, 'decay_steps': 4122, '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': 0.001}}, '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
3.4972	0.1475	0.3067	3.0825	0.3240	0.5178	0
2.7352	0.4129	0.6613	2.4838	0.4543	0.6930	1
2.0429	0.6153	0.8315	1.9934	0.5690	0.7550	2
1.4246	0.7672	0.9166	1.6714	0.5876	0.8016	3
0.8976	0.8813	0.9721	1.6144	0.5845	0.7845	4

Framework versions

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