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Bookmark or Share- FacebookAI/roberta-base - Hugging FaceRoBERTa base model Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in this paper and first released in this repository. This model is case-sensitive: it makes a difference between english and English.
- RoBERTa: A Robustly Optimized BERT Pretraining ApproachWe present a replication study of BERT pretraining (Devlin et al., 2019) that carefully measures the impact of many key hyperparameters and training data size. We find that BERT was significantly undertrained, and can match or exceed the performance of every model published after it.
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- RoBERTa中文预训练模型: RoBERTa for Chinese - GitHubRoBERTa, produces state-of-the-art results on the widely used NLP benchmark, General Language Understanding Evaluation (GLUE). The model delivered state-of-the-art performance on the MNLI, QNLI, RTE, STS-B, and RACE tasks and a sizable performance improvement on the GLUE benchmark.
- RoBERTa - Hugging FaceThe 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.
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