# Multilabel text classification with more than 200 labels **URL:** \ **Category:** Uncategorized\ **Tags:** usage, textcat\ **Created:** [January 19, 2022, 11:13am UTC](https://support.prodi.gy/t/multilabel-text-classification-with-more-than-200-labels/5206 "2022-01-19T11:13:35Z")\ **Posts on this page:** 1\ **Showing post:** 2
**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\ **Post date:** [January 19, 2022, 5:49pm UTC](https://support.prodi.gy/t/multilabel-text-classification-with-more-than-200-labels/5206/2 "2022-01-19T17:49:17Z")
How are your labels structured, are they hierarchical? If you're annotating with this many labels, we'd usually recommend breaking up the task and start by annotating the top level categories first, since those are usually the most important. If at every step you have to think about 200+ decisions, this will slow down the process a lot and you'll probably end up with a lot of categories that are underrepresented (or not represented) in the data, which is also going to be difficult to fix with just agumentation. So if your categories are hierarchical, one approach would be to start with the top level, annotate those and run a first training experiment. You can then drill down into the individual categories and only select from the sub-labels if you know that the top level applies. This gives you fewer options to select from and makes annotation a lot faster. If your model trained on the top level categories is good, you can even use it to do the top-level selection for you later in the process. Here's an example of the UI you could put together for this mutli-step process: [Text Classification · Prodigy · An annotation tool for AI, Machine Learning & NLP](https://prodi.gy/docs/text-classification#large-label-sets) I've also shared some thoughts on textcat annotation with large label sets here: > [@Best way to customize choice interface to manage 200 labels](https://support.prodi.gy/t/best-way-to-customize-choice-interface-to-manage-200-labels/4357/2): > > Hi! You coud probably implement something similar using a HTML block with some JavaScript – however, if you really have that many labels, we typically recommend breaking up the task into a multi-step process, especially if your labels are hierarchical. Start off with the top level, and then have a separate step that drills down into the more fine-grained categories, given the top label that was selected. Asking the annotator to select from a dropdown of 200 labels for every single annotation ca… --- _[View the full topic](https://support.prodi.gy/t/multilabel-text-classification-with-more-than-200-labels/5206)._