Comments (5)
Hello,
Thanks for reaching out to us. How many epochs were you running for? I think that this has been the most common issue.
We can also give an exact command line command, at least for PreActResNet18.
We also submitted a new draft to arxiv which makes the experimental setup clearer and now reports mean/standard deviation across 5 trials for these experiments.
Best,
Alex.
from manifold_mixup.
Hello,
Can you give us more details on what you ran?
Best,
Alex.
from manifold_mixup.
@wtqin382 if you can paste the output log, I can see what is going wrong.
"For example, the paper is vague on details such as initial learning rate, batchsize, Nesterov or not, and other settings." All these details are present in the Appendix of the paper (since the first version), except the Nesterov ( which is "True" by default in the code)
from manifold_mixup.
Hi @wtqin382, we have uploaded the new code with the command line argument to run each of the experiments in the paper. It will be great if you can try to reproduce the results and let us know if there is some issues.
from manifold_mixup.
@wtqin382 Hi there! were you able to reproduce the results?
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Related Issues (16)
- Error running Semi-supervised Manifold mixup for Cifar10 HOT 3
- More on Reproducing CIFAR10 supervised results HOT 10
- Could you please point out the core novel code? HOT 2
- Error in line 109 of models/resnet.py HOT 1
- Plot Code
- AttributeError: 'CIFAR100' object has no attribute 'targets'
- Does mixup process still work during eval? HOT 2
- Application error HOT 1
- DataParallel Usage HOT 1
- Cannot reproduce CIFAR10 semi-supervised results HOT 26
- Dataparallel issue HOT 2
- Question about training epoch? HOT 2
- Question about BCE HOT 2
- Making the training process generic for custom models HOT 19
- Question about accuracy during Training HOT 1
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