We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
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
Hi, alquraishi
I tried to train the model using CASP12 tfrecord data download from proteinnet: https://sharehost.hms.harvard.edu/sysbio/alquraishi/proteinnet/tfrecords/casp12.tar.gz I found the training_90 data is different from pretrained model (CASP12) RGN12/runs/CASP12/ProteinNet12Thinning90 https://sharehost.hms.harvard.edu/sysbio/alquraishi/rgn_models/RGN12.tar.gz
may I know which data is better? Using proteinnet data , I found numEvoEntries change to 21 instead of 42, and the training loss always nan.
numEvoEntries
Looking forward to hearing from you. Thank you
The text was updated successfully, but these errors were encountered:
No branches or pull requests
Hi, alquraishi
I tried to train the model using CASP12 tfrecord data download from proteinnet: https://sharehost.hms.harvard.edu/sysbio/alquraishi/proteinnet/tfrecords/casp12.tar.gz
I found the training_90 data is different from pretrained model (CASP12)
RGN12/runs/CASP12/ProteinNet12Thinning90
https://sharehost.hms.harvard.edu/sysbio/alquraishi/rgn_models/RGN12.tar.gz
may I know which data is better?
Using proteinnet data , I found
numEvoEntries
change to 21 instead of 42, and the training loss always nan.Looking forward to hearing from you.
Thank you
The text was updated successfully, but these errors were encountered: