This is what I'm seeing the > is the title - series relation. I'm not 100% clear why the iteration is a problem, could you elaborate?
this is the selection from the column setting menu
AgitatedDove14 all I did was to cerate this metric as "last" and then turned on the "max" and "min" and then turned them off
I can't reproduce it now but:
I restarted the services and it didn't help I deleted the columns, and created them again after a while and it helped
Yes, I have a metric I want to monitor so I will be able to sort my experiments by it. It is logged in this manner
logger.report_scalar(title='Mean Top 4 Accuracy', series=ARGS.model, iteration=0, value=results['top_4_acc'].mean())
When looking at my dashboard this is how it looks
It would, but it would get the trick. you can update the iteration 0 value and you'll be able to see it in the table. or do you mean you ONLY want to see it in the table and not in the scalars tab?
what's the value of ARGS.model? is it "4"?
By the examples I figured out this ould appear as a scatter plot with X and Y axis and one point only.. Does it avoid that?
You can just use report_scalar:from trains import Logger Logger.current_logger().report_scalar("title", "series", iteration=0, value=1337)Then you can select it as a metric in the experiment tale.
Could be, my message is that in general, the ability to attach a named scalar (without iteration/series dimension) to an experiment is valuable and basic when looking to track a metric over different experiments
I'm using iteration = 0 at the moment, and I "choose" the max and it shows as a column... But the column is not the scalar name (because it cuts it and puts the > sign to signal max).
For the sake of comparing and sorting, it makes sense to log a scalar with a given name without the iteration dimension
Just to make sure, if you change the title to "mean top four accuracy" it should work OK
I...Think it's a UI bug? I'll confirm 🙂