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Auf unserer Open-Source-Plattform »Open Roberta Lab« erstellst du im Handumdrehen deine ersten Programme per drag and drop. Dabei hilft dir (NEPO), unsere grafische Programmiersprache.
RoBERTa has the same architecture as BERT, but uses a byte-level BPE as a tokenizer (same as GPT-2) and uses a different pretraining scheme. RoBERTa doesn’t have token_type_ids, you don’t need to indicate which token belongs to which segment.
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.
Open Roberta ist eine Entwicklung des Fraunhofer-Instituts für Intelligente Analyse- und Informationssysteme IAIS. Seit 2014 wird Open Roberta auf Servern des Fraunhofer IAIS in Sankt Augustin unter hohen Datenschutz-Maßnahmen gehostet und entwickelt.
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26 de jul. de 2019 · We 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.
RoBERTa Model transformer with a sequence classification/regression head on top (a linear layer on top of the pooled output) e.g. for GLUE tasks. This model is a PyTorch torch.nn.Module sub-class. Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage and behavior. Parameters
