Post #63

《Do Better ImageNet Models Transfer Better?》的第二版。 In v1, we used public checkpoints where the ResNet models were trained without regularizers, which is why they performed best in the fixed feature setting. In v2, we retrained everything. Surprisingly, for ImageNet training, the same hyperparameters work well for all models. In v2, we show that regularization settings for ImageNet training matter a lot for transfer learning on fixed features. ImageNet accuracy now correlates with transfer acc in all settings. https://arxiv.org/abs/1805.08974