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

Will BFN be effective on discrete dataset with large vocabulary? #1

Open
LtECoD opened this issue Aug 23, 2024 · 0 comments
Open

Will BFN be effective on discrete dataset with large vocabulary? #1

LtECoD opened this issue Aug 23, 2024 · 0 comments

Comments

@LtECoD
Copy link

LtECoD commented Aug 23, 2024

Hi,
The discrete BFN presented in the paper has demonstrated competitive performance on the text8 dataset. However, the vocabulary size of text8, which stands at a mere 27, is considerably limited for most NLP tasks. Have you experimented with training discrete BFN models on datasets with a larger vocabulary? Could you provide some insights into the model's architecture, settings of hyper parameters, and the performance achieved?
Thanks!

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

1 participant