# Nested named entity recognition

**URL:** </static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fnested-named-entity-recognition%2F75376%3E%5C
**Category:** Intermediate\
**Created:** [February 29, 2024, 6:52pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fnested-named-entity-recognition%2F75376 "2024-02-29T18:52:25Z")\
**Posts on this page:** 1\
**Showing post:** 2

<div class="post-metadata">

**Author:** ![stulcrad](https://avatars.discourse-cdn.com/v4/letter/s/4bbf92/32.png) [@stulcrad](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fstulcrad)%5C
**Post date:** [March 19, 2024, 1:39am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fnested-named-entity-recognition%2F75376%2F2 "2024-03-19T01:39:52Z")

</div>

If anyone reading this would be interested, I solved it using this discussion

> [@Multi-label token classification](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fmulti-label-token-classification%2F16509)%3A
>
> Hi! I am trying to solve a token classification problem in a multi-label setup. So far I haven’t found the best path to do it. Unlike AutoModelForSequenceClassification, AutoModelForTokenClassification lacks the problem\_type parameter, where you can specify that you’re working with multi-label. Should I deepen into logits and create a custom loss or is there a more straightforward solution? Thanks!

---

_[View the full topic](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fnested-named-entity-recognition%2F75376)._