I have a labeled dataset that I have ingested into a dataframe. It consists of news articles,
>>> df.columns Index(['title', 'headline', 'byline', 'dateline', 'text', 'copyright', 'country', 'industry', 'topic', 'file'], dtype='object')
where the text column contains the body (text) of the article and the topic column contains a list of associated topics.
I want to train a model from this dataset to predict the article topics. I was considering using transformers (https://huggingface.co/transformers/index.html) to do this, along with tensorflow, but I from what I know of transformers, it's not really good for this.
What would be the best NLP library to perform this task with high accuracy?