In this post I show how to leverage BERT, a transformer-based language representation model, in order to identify the personality type of users based on their writing style and the content of their posts, according to the Myers-Briggs indicator (MBTI).
In what follows, I'll show how to fine-tune a BERT classifier, using Huggingface and Keras+Tensorflow, for dealing with two different text classification problems. The first consists in detecting the sentiment (*negative* or *positive*) of a movie review, while the second is related to the classification of a comment based on different types of toxicity, such as *toxic*, *severe toxic*, *obscene*, *threat*, *insult* and *identity hate*.