Language Models are Few-Shot Learners
Brown et al., 2020, Language Models are Few-Shot Learners (Advances in Neural Information Processing Systems 33 (NeurIPS 2020))
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2.2 Training Dataset
- How was GPT-3’s training data built?Common Crawl filtered by similarity to high-quality reference corpora, fuzzy document-level deduplication (within and across data sets, protecting the validation set), plus high-quality corpora: an expanded WebText, two book corpora and English Wikipedia.
- Brown et al., 2020, Language Models are Few-Shot Learners (Advances in Neural Information Processing Systems 33 (NeurIPS 2020)), §2.2
Source
- Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever and Dario Amodei. 2020. Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems 33 (NeurIPS 2020). https://papers.nips.cc/paper/2020/hash/1457c0d6bfcb4967418bfb8ac142f64a-Abstract.html