Examples: query, "exact match", wildcard*, wild?ard, wild*rd
Fuzzy search: cake~ (finds cakes, bake)
Term boost: "red velvet"^4, chocolate^2
Field grouping: tags:(+work -"fun-stuff")
Escaping: Escape characters +-&|!(){}[]^"~*?:\ with \, e.g. \+
Range search: properties.timestamp:[1587729413488 TO *] (inclusive), properties.title:{A TO Z}(excluding A and Z)
Combinations: chocolate AND vanilla, chocolate OR vanilla, (chocolate OR vanilla) NOT "vanilla pudding"
Field search: properties.title:"The Title" AND text
Answered
Hello Everyone. I Would Like To Ask About The Rapid Decline In Acuracy Of Opportunity Learning. When I Run The Code For Learning Locally, It Is Fine, But When I Run It In Queue, The Accuracies Suddenly Drop. No Error Is Displayed And I Want To Find Out Th

Hello everyone.
I would like to ask about the rapid decline in acuracy of opportunity learning.
When I run the code for learning locally, it is fine, but when I run it in queue, the accuracies suddenly drop.
No error is displayed and I want to find out the cause. If you know the cause or know how to identify the cause, please advise me.

The agent on the server side to which it was assigned remained activated.
(6:14 PM is the end of the 100 epoch, so workers worked until the end.)

This script uses dataset (torchvision.datasets.CIFAR10) for a three-level classification model with pytorch.
Thank you!!
image
image
image

  
  
Posted 26 days ago
Votes Newest

Answers


Hi @<1761199244808556544:profile|SarcasticHare65> , and if you run locally for the same amount of iterations this does not happen?

  
  
Posted 24 days ago
73 Views
1 Answer
26 days ago
24 days ago
Tags