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Pronoun disambiguation (Winograd Schema Challenge): RoBERTa can be used to disambiguate pronouns. First install spaCy and download the English-language model: pip install spacy. python -m spacy download en_core_web_lg. Next load the roberta.large.wsc model and call the disambiguate_pronoun function.
RoBERTa builds on BERT’s language masking strategy and modifies key hyperparameters in BERT, including removing BERT’s next-sentence pretraining objective, and training with much larger mini-batches and learning rates. RoBERTa was also trained on an order of magnitude more data than BERT, for a longer amount of time.
RoBERTa is an extension of BERT with changes to the pretraining procedure. The modifications include: training the model longer, with bigger batches, over more data removing the next sentence prediction objective training on longer sequences dynamically changing the masking pattern applied to the training data. The authors also collect a large new dataset ($\text{CC-News}$) of comparable size ...
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu∗§ Myle Ott∗§ Naman Goyal∗§ Jingfei Du∗§ Mandar Joshi† Danqi Chen§ Omer Levy§ Mike Lewis§ Luke Zettlemoyer†§ Veselin Stoyanov§ † Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA {mandar90,lsz}@cs.washington.edu ...
RoBERTa中文预训练模型: RoBERTa for Chinese . Contribute to brightmart/roberta_zh development by creating an account on GitHub.
29 de jul. de 2019 · RoBERTa, which was implemented in PyTorch, modifies key hyperparameters in BERT, including removing BERT’s next-sentence pretraining objective, and training with much larger mini-batches and learning rates. This allows RoBERTa to improve on the masked language modeling objective compared with BERT and leads to better downstream task performance.
Overview. The RoBERTa model was proposed in RoBERTa: A Robustly Optimized BERT Pretraining Approach by Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, Veselin Stoyanov.It is based on Google’s BERT model released in 2018. It builds on BERT and modifies key hyperparameters, removing the next-sentence pretraining objective and ...
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