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Update website/docs/api/spancategorizer.mdx

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Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
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@ -13,11 +13,11 @@ A span categorizer consists of two parts: a [suggester function](#suggesters)
that proposes candidate spans, which may or may not overlap, and a labeler model that proposes candidate spans, which may or may not overlap, and a labeler model
that predicts zero or more labels for each candidate. that predicts zero or more labels for each candidate.
This component comes in two forms: `spancat` and `spancat_singlelabel`. When you This component comes in two forms: `spancat` and `spancat_singlelabel` (added in spaCy v3.5.1). When you
need to perform multi-label classification on your spans, use `spancat`. The need to perform multi-label classification on your spans, use `spancat`. The
`spancat` component uses a `Logistic` layer where the output class probabilities `spancat` component uses a `Logistic` layer where the output class probabilities
are independent for each class. However, if you need to predict at most one true are independent for each class. However, if you need to predict at most one true
class for a span, then use `spancat_singlelabel` <Tag variant="new">3.5.1</Tag>. class for a span, then use `spancat_singlelabel`.
It uses a `Softmax` layer and treats the spans as a multi-class problem. It uses a `Softmax` layer and treats the spans as a multi-class problem.
Predicted spans will be saved in a [`SpanGroup`](/api/spangroup) on the doc. Predicted spans will be saved in a [`SpanGroup`](/api/spangroup) on the doc.