Text Summarization with Pretrained Encoders
Table 5: Model perplexity (CNN/DailyMail; validation set) under different combinations of encoder and decoder learning rates.
['~ [ITALIC] lrE~ [ITALIC] lrD', '1', '0.1', '0.01', '0.001']
Specifically, we report model perplexity on the CNN/DailyMail validation set for varying encoder/decoder learning rates. We can see that the model performs best with ~lrE=2e−3 and ~lrD=0.1.