# Create a classifier learner using the dataloader defined above
learn_clf = text_classifier_learner(dls_clf, 
                                    # Specify a model architecture for the learner
                                    AWD_LSTM, 
                                    # Specify the % in dropout layer for regularization
                                    drop_mult=0.5,
                                    # Specify a metric to evaluate performance while training
                                    metrics = accuracy_multi).to_fp16()

# Load the embeddings from the finetuned language model in our learner object
learn_clf = learn_clf.load_encoder("finetuned_language_model_encoder")