# tfidf is the vector defined previously
#tfidf = TfidfVectorizer(ngram_range=(1,3), stop_words='english', lowercase=True)

# Transform train_lbl['content'] to vectorizer
X_train_vec_lbl = tfidf.fit_transform(train_lbl["content"])
# Size of X_train_vec_lbl and y_train_lbl
print(X_train_vec_lbl.shape)
print(y_train_lbl.shape)