Understanding outputs for new texcat model

Hi, I recently updated to the newest version of prodigy and I'm very confused with how the results of the models are presented.

From a previous entry I know that:

  • "E" refers to the number of epochs that you've trained, with one epoch representing one pass over all the data.

But I don't understand what # is then. I haven't been able to find documentation on how to read the results. Is score the F-score? How do I get the usual Accuracy, Precision, Recall or F1? If I could be directed to documentation on this new format It'd be very helpful.

Thanks.

Hi! The E refers to the epochs and # is the number of steps (iterations). Also see here: Unclear what the column 'E' is outputting in the console output during training · Discussion #7731 · explosion/spaCy · GitHub

The score is the combined weighted score and you can read more about it here: https://spacy.io/usage/training#metrics If you're only training one component, this is typically identical to the main score reported by the component (e.g. F-score). If you're training multiple components, you can use the score weights to define what to prioritise (e.g. best text classifier + NER recall combination, and so on).

You can also use the [training.score_weights] block to define the scores shown in the table. The scores set by the individual components are available in the code via the @Language.factory decorator: https://spacy.io/api/textcategorizer

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