README.md

---
language:
- english
---

# bert-base-cased-conversational

Conversational BERT \(English, cased, 12-layer, 768-hidden, 12-heads, 110M parameters\) was trained
on the English part of Twitter, Reddit, DailyDialogues\[1\], OpenSubtitles\[2\], Debates\[3\], Blogs\[4\],
Facebook News Comments. We used this training data to build the vocabulary of English subtokens and took
English cased version of BERT-base as an initialization for English Conversational BERT.


\[1\]: Yanran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, and Shuzi Niu. DailyDialog: A Manually Labelled
Multi-turn Dialogue Dataset. IJCNLP 2017.

\[2\]: P. Lison and J. Tiedemann, 2016, OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles.
In Proceedings of the 10th International Conference on Language Resources and Evaluation \(LREC 2016\)

\[3\]: Justine Zhang, Ravi Kumar, Sujith Ravi, Cristian Danescu-Niculescu-Mizil. Proceedings of NAACL, 2016.

\[4\]: J. Schler, M. Koppel, S. Argamon and J. Pennebaker \(2006\). Effects of Age and Gender on Blogging
in Proceedings of 2006 AAAI Spring Symposium on Computational Approaches for Analyzing Weblogs.