YKXBCi/vit-base-patch16-224-in21k-aidSat

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: 0.4026
• Train Accuracy: 0.9981
• Train Top-3-accuracy: 0.9998
• Validation Loss: 0.4715
• Validation Accuracy: 0.9796
• Validation Top-3-accuracy: 0.9980
• 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': 1325, '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
2.3544	0.7383	0.8687	1.5415	0.9266	0.9857	0
1.1313	0.9522	0.9942	0.8788	0.9613	0.9966	1
0.6741	0.9841	0.9985	0.6268	0.9640	0.9986	2
0.4785	0.9953	0.9995	0.5058	0.9755	0.9980	3
0.4026	0.9981	0.9998	0.4715	0.9796	0.9980	4

Framework versions

• Transformers 4.18.0
• TensorFlow 2.6.0
• Datasets 2.1.0
• Tokenizers 0.12.1