task_learning.py

#Creating Classification Data
data_clas = TextClasDataBunch.from_df(path ="", train_df=train, valid_df =valid,  test_df=test_df, vocab=data_lm.train_ds.vocab, bs=32,label_cols = 'target')

# Creating Classifier Object
learn = text_classifier_learner(data_clas, AWD_LSTM, drop_mult=0.5)
# Add weights of finetuned Language model 
learn.load_encoder('ft_enc')
# Fitting Classifier Object
learn.fit_one_cycle(1, 1e-2)
# Fitting Classifier Object after freezing all but last 2 layers
learn.freeze_to(-2)
learn.fit_one_cycle(1, slice(5e-3/2., 5e-3))
# Fitting Classifier Object - discriminative learning
learn.unfreeze()
learn.fit_one_cycle(1, slice(2e-3/100, 2e-3))