Code to reproduce the results in the FAIR research papers "Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples" https://arxiv.org/abs/2104.13963 and "Supervision Accelerates Pre-training in Contrastive Semi-Supervised Learning of Visual Representations" https://arxiv.org/abs/2006.10803
Hi! Thanks for sharing your work :)
Shouldn't the accuracy rate of training on PAWS with labeled dataset A and unlabeled dataset B be higher than that of full supervised learning with labeled dataset A alone? I can achieve an accuracy of 90% on Resnet using a self built labeled dataset. Why did I add unlabeled data into this dataset and only achieve an accuracy of over 50% using Paws? It's strange.
Hi! Thanks for sharing your work :) Shouldn't the accuracy rate of training on PAWS with labeled dataset A and unlabeled dataset B be higher than that of full supervised learning with labeled dataset A alone? I can achieve an accuracy of 90% on Resnet using a self built labeled dataset. Why did I add unlabeled data into this dataset and only achieve an accuracy of over 50% using Paws? It's strange.