# BART for sequence classification

**URL:** </static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fbart-for-sequence-classification%2F2425%3E%5C
**Category:** 🤗Transformers\
**Created:** [December 2, 2020, 3:10pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fbart-for-sequence-classification%2F2425 "2020-12-02T15:10:36Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![shainaraza](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/shainaraza/32/2854_2.png) [@shainaraza](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fshainaraza)%5C
**Post date:** [December 2, 2020, 3:10pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fbart-for-sequence-classification%2F2425%2F1 "2020-12-02T15:10:36Z")

</div>

the facebook/bart-large-cnn is pre-trained on summarization task, is it possible to fine-tune it on a classification task?  
syntactically, it doesn’t cause any issue, but in terms of results.

---

<div class="post-metadata">

**Author:** ![Jung](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/jung/32/21989_2.png) [@Jung](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FJung)%5C
**Post date:** [December 3, 2020, 6:43am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fbart-for-sequence-classification%2F2425%2F2 "2020-12-03T06:43:30Z")

</div>

In [Google’s QUEST challenge](https://www.kaggle.com/c/google-quest-challenge) which is a “multi-label” classificatin competition , the 1st place winner uses (finetuned) pretrained Bart as one of their core model, so that might partially answer your question.