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95 lines
2.9 KiB
ReStructuredText
95 lines
2.9 KiB
ReStructuredText
RoBERTa
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The RoBERTa model was proposed in `RoBERTa: A Robustly Optimized BERT Pretraining Approach <https://arxiv.org/abs/1907.11692>`_
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by Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer,
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Veselin Stoyanov. It is based on Google's BERT model released in 2018.
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It builds on BERT and modifies key hyperparameters, removing the next-sentence pretraining
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objective and training with much larger mini-batches and learning rates.
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The abstract from the paper is the following:
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*Language model pretraining has led to significant performance gains but careful comparison between different
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approaches is challenging. Training is computationally expensive, often done on private datasets of different sizes,
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and, as we will show, hyperparameter choices have significant impact on the final results. We present a replication
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study of BERT pretraining (Devlin et al., 2019) that carefully measures the impact of many key hyperparameters and
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training data size. We find that BERT was significantly undertrained, and can match or exceed the performance of
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every model published after it. Our best model achieves state-of-the-art results on GLUE, RACE and SQuAD. These
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results highlight the importance of previously overlooked design choices, and raise questions about the source
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of recently reported improvements. We release our models and code.*
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Tips:
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- This implementation is the same as :class:`~transformers.BertModel` with a tiny embeddings tweak as well as a
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setup for Roberta pretrained models.
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- `Camembert <./camembert.html>`__ is a wrapper around RoBERTa. Refer to this page for usage examples.
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RobertaConfig
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~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.RobertaConfig
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:members:
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RobertaTokenizer
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~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.RobertaTokenizer
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:members:
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RobertaModel
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~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.RobertaModel
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:members:
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RobertaForMaskedLM
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~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.RobertaForMaskedLM
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:members:
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RobertaForSequenceClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.RobertaForSequenceClassification
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:members:
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RobertaForTokenClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.RobertaForTokenClassification
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:members:
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TFRobertaModel
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~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFRobertaModel
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:members:
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TFRobertaForMaskedLM
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~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFRobertaForMaskedLM
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:members:
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TFRobertaForSequenceClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFRobertaForSequenceClassification
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:members:
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TFRobertaForTokenClassification
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.TFRobertaForTokenClassification
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:members:
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