O guia definitivo para roberta pires
O guia definitivo para roberta pires
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RoBERTa has almost similar architecture as compare to BERT, but in order to improve the results on BERT architecture, the authors made some simple design changes in its architecture and training procedure. These changes are:
The problem with the original implementation is the fact that chosen tokens for masking for a given text sequence across different batches are sometimes the same.
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The authors experimented with removing/adding of NSP loss to different versions and concluded that removing the NSP loss matches or slightly improves downstream task performance
model. Initializing with a config file does not load the weights associated with the model, only the configuration.
As researchers found, it is slightly better to use dynamic masking meaning that masking is generated uniquely every time a sequence is passed to BERT. Overall, this results in less duplicated data during the training giving an opportunity for a model to work with more various data and masking patterns.
The authors of the paper conducted research for finding an optimal way to model the next sentence prediction task. As a consequence, they found several valuable insights:
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model. Initializing with a config file does not load the weights associated with the model, only the configuration.
A partir desse instante, a carreira do Roberta decolou e seu nome passou a ser sinônimo de música sertaneja por habilidade.
Ultimately, for the final RoBERTa implementation, the authors chose to keep the first two aspects and omit the third one. Despite the observed Saiba mais improvement behind the third insight, researchers did not not proceed with it because otherwise, it would have made the comparison between previous implementations more problematic.
A mulher nasceu utilizando todos os requisitos de modo a ser vencedora. Só precisa tomar conhecimento do valor de que representa a coragem de querer.
This is useful if you want more control over how to convert input_ids indices into associated vectors