Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Question about EC downstream task #3

Open
Heisenburger2020 opened this issue Dec 23, 2023 · 1 comment
Open

Question about EC downstream task #3

Heisenburger2020 opened this issue Dec 23, 2023 · 1 comment

Comments

@Heisenburger2020
Copy link

Dear Sir/Madam,

Thank you for such a great repo, but I am confused by the result for EC downstream task result. The result of multiview contrast in paper "PROTEIN REPRESENTATION LEARNING BY GEOMETRIC STRUCTURE PRETRAINING" is 0.874. However, in this paper it is 0.857, and AUPR is 0.875. Why is this happening?

Yours Sincerely,
JialeZhao

@Oxer11
Copy link
Collaborator

Oxer11 commented Dec 28, 2023

Thanks for carefully reading our work! The difference lies in the number of epochs for fine-tuning. In SiamDiff, we only use 50 epochs for fine-tuning on EC (see Sec. 5.1, training and evaluation); while in GearNet paper, we use 200 epochs for fine-tuning.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants