Multi-Label Text Topic Classification

I have a huge dataset of messages/comments classified with topics. The dataset consists of 1kk records and have a total of 90 topics, like this:

text         topic1     topic2  ....   topic90
comment        1          0               1
comment        0          1               0

I want to use a supervised method as I have already labeled all comments. I want to know what are the recommended approach to tackle this problem. The topics are quite unbalanced.

Topic supervised-learning topic-model nlp

Category Data Science

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