We are trying to solve a problem where we need to classify the articles into the right categories.

Currently, using a FastText to train a model with 100,000 articles categorized into 600 categories. The loss seems to be converging but the precision is not going up, another thing that requires clarification is that can we use pre-trained Wikipedia English embeddings to categorize text.

What would you recommend using FastText or some other algorithm/approach towards this problem?

Any suggestion/ideas would be appreciated.

Thanks.