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
Unanswered
Hi All. I Am Wondering How People Tend To Use Clearml With Cross-Validation. Do You Tend To Create Separate Experiments For Each Fold? And If So, Would You Then Create Another Experiment For The Aggregated Results?


One thought is to initialise a new clearML task in each fold to capture the iteration-level metrics, and then create another task/experiment at the end to capture the aggregated metrics across folds.

That is probably the easiest, and the most scalable.
BTW: with the mew reporting feature, you can integrate the comparison of the CV directly into your final report 🙂

  
  
Posted one year ago
166 Views
0 Answers
one year ago
one year ago