TensorBoard - Plot training and validation losses on the same graph?

machine-learning tensorflow tensorboard
golmschenk picture golmschenk · May 10, 2016 · Viewed 23.5k times · Source

Is there a way to plot both the training losses and validation losses on the same graph?

It's easy to have two separate scalar summaries for each of them individually, but this puts them on separate graphs. If both are displayed in the same graph it's much easier to see the gap between them and whether or not they have begin to diverge due to overfitting.

Is there a built in way to do this? If not, a work around way? Thank you much!

Answer

Lifu Huang picture Lifu Huang · May 11, 2016

The work-around I have been doing is to use two SummaryWriter with different log dir for training set and cross-validation set respectively. And you will see something like this:

enter image description here

Related questions

How can I run Tensorboard on a remote server?

I'm new to Tensorflow and would greatly benefit from some visualizations of what I'm doing. I understand that Tensorboard is a useful visualization tool, but how do I run it on my remote Ubuntu machine?

Read More
Unable to open Tensorboard in browser

I am following google cloud machine learning tutorial and I am unable to Launch TensorBoard I've followed the steps in the above tutorial (also set up my environment using docker container) until typing the below command in the terminal tensorboard …

Read More
Show training and validation accuracy in TensorFlow using same graph

I have a TensorFlow model, and one part of this model evaluates the accuracy. The accuracy is just another node in the tensorflow graph, that takes in logits and labels. When I want to plot the training accuracy, this is …

Read More