binli123
commented
2 years ago https://drive.google.com/drive/folders/1_mumfTU3GJRtjfcJK_M0fWm048sYYFqi There are several model weights trained using only the training data. I also tested using both the training set and the testing set for SimCLR, the difference in the results is minor. What is the batch size you used? Please make sure the batch size is at least 512 and train for enough iterations in order to get an actual useful embedder from SimCLR, as pointed out in their paper. Bigger batch size and longer training time lead to better embedder and they have quite a big impact on the performance of the downstream task. The best embedder we obtained was trained for 2 months because of the large number of patches.
Plus, we are not the only ones who had luck with self-supervised learning on Camelyon16, https://arxiv.org/pdf/2012.03583.pdf where they showed that very high results can be obtained.
yangsenwxy
raycaohmu
GeorgeBatch
PiumiDS
I have a question, your simlr is pre-training, does it include all the data of camelyon16 (training set and test set)? Because I found that your feature extractor is faulty, you leaked the information of the test set, I tried, only pre-trained on the training set, there is no such high result, I think you should check this problem carefully, resulting in your result is too high