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.

Sign up for GitHub

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

Jump to bottom

SplitcrossEntropy #10

Open

gslaller opened this issue Jan 3, 2020 · 1 comment

gslaller commented Jan 3, 2020

Can you provide any further information on the loss function you are using? Perhaps a reference to a paper?

munael commented Dec 27, 2020 •

edited

Loading

@gslaller - Seems to be from here: Efficient softmax approximation for GPUs

See: https://twitter.com/Smerity/status/1343159498081366017

The SHA-RNN paper itself only uses it as it was already part of AWD-LSTM. It's the adaptive softmax from linked FAIR paper. Almost all Facebook (FAIR) codebases use it. Essentially a computationally efficient hierarchical softmax. Hope that helps!
https://arxiv.org/abs/1609.04309

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment