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Multi-label Classification:
Accurate prediction of at least one label in an issue across issues: ~87%
Accuracy in predicting all labels in an issue (i.e. an exact match of all labels to an issue) across issues: ~20%

How was the data collected:

The labels below were These were labels chosen for prediction initially by the model. Only the issues which are specific to these labels are what is being tested on, in other words

either the specific label being tested on was predicted by the model or the specific label was the actual label on the issue. This score 

Results in accurately predicting a label – Meaning the model predicted a label and that was one of the actual labels in the repo:

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