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

Weird training accuracy curve #7

Closed
gongliyu opened this issue May 15, 2018 · 2 comments
Closed

Weird training accuracy curve #7

gongliyu opened this issue May 15, 2018 · 2 comments

Comments

@gongliyu
Copy link

Hi,

I observed that the training accuracy is very low all the time during the training process. The values is around 50%. Although validation accuracy reaches around 83%, this is still weird. I tried Kipf's GCN code, it can reach above 90% training accuracy, which is much normal.

Does anybody notice this?

@PetarV-
Copy link
Owner

PetarV- commented May 15, 2018

Hi Liyu,

This is caused by the strong dropout on the alpha_ij values. It causes the network to mispredict more often during training, as the graph neighbourhoods get quite variable; however this makes it less prone to overfitting on small training datasets such as Cora.

(If you were to turn off dropout and evaluate the model on the training set at the end of each epoch, you would probably get much more normal progression of training accuracies.)

Hope that helps!

Thanks,
Petar

@PetarV- PetarV- closed this as completed May 15, 2018
@gongliyu
Copy link
Author

Hi Petar,

Got it. Thank you very much for the explanation.

Best,
Liyu

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