-
Notifications
You must be signed in to change notification settings - Fork 731
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
LoRA matrices dropout #1398
Comments
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Hi everyone,
recently has been proposed to apply the dropout directly on the LoRA weight matrices A and B: this favors sparsity which improve generalization and reduce overfitting. The dropout is only applied on input/output dimension to avoid reducing the matrices rank.
If you guys think that this could be helpful I can submit a PR with the feature.
Thanks
The text was updated successfully, but these errors were encountered: