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

Saving weights after each epoch #14

Open
2 tasks
nikos-kekatos opened this issue May 6, 2020 · 0 comments
Open
2 tasks

Saving weights after each epoch #14

nikos-kekatos opened this issue May 6, 2020 · 0 comments

Comments

@nikos-kekatos
Copy link
Owner

It does not seem to exist a default option with Deep Learning Toolbox in Matlab.

Workaround
One way to see the weights after every epoch is to set the network to only train one epoch at a time, and then to use the 'getwb' command.

Caveat
We will not get the same performance as N_epochs=100 and N_loop=1 since the method train reinitialises internal training parameters at each call.

  • Look at checkpointPath.
  • Check references: [1],[2],[3]
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