# Multilabel+multiclass classification

**URL:** <https://discuss.huggingface.co/t/multilabel-multiclass-classification/18807>\
**Category:** Beginners\
**Created:** [June 7, 2022, 8:24am UTC](https://discuss.huggingface.co/t/multilabel-multiclass-classification/18807 "2022-06-07T08:24:20Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![kyaneos](https://avatars.discourse-cdn.com/v4/letter/k/ba8739/32.png) [@kyaneos](https://discuss.huggingface.co/u/kyaneos)\
**Post date:** [June 7, 2022, 8:24am UTC](https://discuss.huggingface.co/t/multilabel-multiclass-classification/18807/1 "2022-06-07T08:24:20Z")

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Hi,  
I am interested in solving a multilabel+multiclass classification problem, i. e. I have 9 labels and each of these 9 labels can have more than 2 classes.  
I attempted to build 9 classification heads and calculate the loss by averaging the loss of all 9 heads.  
My labels are stored in a list containing 9 elements with the labels for every head. However, the DataCollatorForTokenClassification does not seem to support lists, and I can’t figure out how I can make my data compatible with a DataCollator.  
Is it possible to create a custom DataCollator for this purpose? Or did I miss something which solves my problem?  
Thank you very much in advance.