While all the data is from the CNN-DM train dataset in the supervised setups, for the unsupervised setups, we set the proportion of unsupervised data to 50% (either CNN-DM VAL, CNN-DM TEST for in-domain or TL;DR for out-of-domain data).
for 50% of the data, the model has access only to the QA conf and QA f score reward signals, since the ROUGE-L reward can only be computed on supervised batches.