Comments (2)
sangwoomo
commented on June 12, 2024
1
Hi @ASDen,
Thank you for noticing that. I think there was some bug at converting coarse labels. We didn't notice since only some coarse labels suffer the issue, and the reproduced results seemed okay.
We will update the results as soon as possible.
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gdwang08
commented on June 12, 2024
A very nice work! I am wondering if you have updated the results using the standard division of CIFAR100 super-class.
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Related Issues (20)
- Can you share the implementation detail for baseline?(Cross-Entropy) HOT 3
- Why did you do the rotation transformation firstly and then apply the simlcr_aug？ HOT 1
- batch size HOT 4
- The result of using the checkpoint of unlabeled ImageNet-30 HOT 3
- CSI/training/unsup/simclr_CSI.py HOT 1
- Error while running the training script. HOT 1
- GPU requirement for training ImageNet model HOT 1
- About how to get result for noise condition
- How to define the joint_labels
- ImportError: /lib64/libstdc++.so.6: version `GLIBCXX_3.4.21' not found HOT 1
- The hyper parmeter of Rot(resnet18) and Rot+Trans(resnet18)
- Reproducing results for Cifar100 ens multi-class
- How can i train it on my own dataset? HOT 10
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- Some questions about Supervised_NT_xent
- baseline code?
- cannot reach the results when removing the four-way rotation classifier
- why use the hfilp() function during training? What does it do?
- Model is provided extra arguments.
- Problem
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