Learning to Create and Reuse Words in Open-Vocabulary Neural Language Modeling
Table 4: Results on PTB Corpus (bits-per-character). HCLM augmented with a cache obtains the best results among models which have approximately the same numbers of parameter as single layer LSTM with 1,000 hidden units.
['Method', 'Dev', 'Test']
Ptb Tab. Our baseline HCLM model achieved 1.276 bpc which is better performance than the LSTM with Zoneout regularization Krueger et al. And HCLM with cache outperformed the baseline model with 1.247 bpc and achieved competitive results with state-of-the-art models with regularization on recurrence weights, which was not used in our experiments.