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Open Roberta ist eine Entwicklung des Fraunhofer-Instituts...
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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 ...
26 de jul. de 2019 · RoBERTa: A Robustly Optimized BERT Pretraining Approach. Language model pretraining has led to significant performance gains but careful comparison between different approaches is challenging.
- Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke...
- arXiv:1907.11692 [cs.CL]
- 2019
- Computation and Language (cs.CL)
RoBERTa is a transformers model pretrained on a large corpus of English data in a self-supervised fashion. This means it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts.
24 de sept. de 2023 · The total number of parameters of RoBERTa is 355M. RoBERTa is pretrained on a combination of five massive datasets resulting in a total of 160 GB of text data. In comparison, BERT large is pretrained only on 13 GB of data. Finally, the authors increase the number of training steps from 100K to 500K.
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