imb_pipe.py

model = make_pipeline(TfidfVectorizer(), MultinomialNB())
model.fit(X_train, y_train)
y_pred = model.predict(X_test)

print(classification_report(y_test,y_pred))
 
  #precision    recall  f1-score   support

  #         0       0.67      0.94      0.79       319
  #         1       0.96      0.92      0.94       389
  #         2       0.87      0.98      0.92       394
  #         3       0.97      0.36      0.52       251

  #  accuracy                           0.84      1353
  # macro avg       0.87      0.80      0.79      1353
#weighted avg       0.87      0.84      0.82      1353