Reproducibility Issues

[entuo]

Hello, this is great work. Congratulations! But I have a question: when I run the code, I find that the experimental results for CIFAR-10-LT and CIFAR-100-LT do not reach the accuracy mentioned in your paper. What could be the possible reasons for this, and are there any details I might have overlooked? Thank you for your response.

[Keke921]

There may be some hyperparameters that need to be adjusted. For example, batch size, learning rate, and m. And I recently found that the PyTorch version and hardware environment also have a significant impact on the final performance. 在 2024年6月1日，17:39，entuo ***@***.***> 写道：  Hello, this is great work. Congratulations! But I have a question: when I run the code, I find that the experimental results for CIFAR-10-LT and CIFAR-100-LT do not reach the accuracy mentioned in your paper. What could be the possible reasons for this, and are there any details I might have overlooked? Thank you for your response. — Reply to this email directly, view it on GitHub<#1>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/ALDW7LFRI72X44ZE4JBDUL3ZFGJDHAVCNFSM6AAAAABIUAKUK6VHI2DSMVQWIX3LMV43ASLTON2WKOZSGMZDSMBTHE4TQOA>. You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>

[entuo]

Thank you for your answer. What you mean is that different devices have different intrinsically random seeds even though they have the same random seed number, which will have a big impact on the results.