Self-training with Noisy Student improves ImageNet classification

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Benchmark Model Rank Results
image-classification-on-imagenet-realEfficientNet-L2#19Accuracy: 90.55%Params: 480M
image-classification-on-imagenetNoisyStudent (EfficientNet-L2)#51Top 1 Accuracy: 88.4%Number of params: 480MHardware Burden: 51800G
image-classification-on-imagenetNoisyStudent (EfficientNet-B7)#122Top 1 Accuracy: 86.9%Number of params: 66MGFLOPs: 37
image-classification-on-imagenetNoisyStudent (EfficientNet-B6)#155Top 1 Accuracy: 86.4%Number of params: 43M
image-classification-on-imagenetNoisyStudent (EfficientNet-B5)#184Top 1 Accuracy: 86.1%Number of params: 30M
image-classification-on-imagenetNoisyStudent (EfficientNet-B4)#253Top 1 Accuracy: 85.3%Number of params: 19M
image-classification-on-imagenetNoisyStudent (EfficientNet-B3)#374Top 1 Accuracy: 84.1%Number of params: 12M
image-classification-on-imagenetNoisyStudent (EfficientNet-B2)#569Top 1 Accuracy: 82.4%Number of params: 9.2M
image-classification-on-imagenetNoisyStudent (EfficientNet-B1)#666Top 1 Accuracy: 81.5%Number of params: 7.8M
image-classification-on-imagenetNoisyStudent (EfficientNet-B0)#841Top 1 Accuracy: 78.8%Number of params: 5.3M

Rank counts only results with a code link.