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RoBERTa is trained on longer sequences than compared with BERT. BERT is trained via 1M steps with a batch size of 256 sequences. As Past work in Neural Machine Translation (NMT) has shown that training with very large mini-batches can both improve optimization speed and end-task performance.
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- Vinil do Velho
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10 de ene. de 2023 · RoBERTa (short for “Robustly Optimized BERT Approach”) is a variant of the BERT (Bidirectional Encoder Representations from Transformers) model, which was developed by researchers at Facebook AI. Like BERT, RoBERTa is a transformer-based language model that uses self-attention to process input sequences and generate contextualized ...
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27 de dic. de 2019 · In this article, a hands-on tutorial is provided to build RoBERTa (a robustly optimised BERT pre-trained approach) for NLP classification tasks. The problem of using latest/state-of-the-art models ...
