The notebook is the work I have done to compete in the kaggle Natural Language Processing Challenge : Jigsaw Toxic Comment Classification Challenge.
https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge
The task was to classify online comments into 6 categories: toxic, severve_toxic, obscene, threat, insult, identity_hate. The competition metric was the average of the individual AUCs of each predicted class.
The code achives a score of 0.9823 on the private Leaderbord.
I used the concatenation of two pre-trained embeddings : fastText crawl-300d-2M.vec and glove.840B.300d.txt.
The first can be found here: https://fasttext.cc/docs/en/english-vectors.html.
The second can be found here : https://nlp.stanford.edu/projects/glove/
You can download the data from kaggle here.