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If you choose this second option, there are three possibilities you can use to gather all the input Tensors

Nevertheless, in the vocabulary size growth in RoBERTa allows to encode almost any word or subword without using the unknown token, compared to BERT. This gives a considerable advantage to RoBERTa as the model can now more fully understand complex texts containing rare words.

It happens due to the fact that reaching the document boundary and stopping there means that an input sequence will contain less than 512 tokens. For having a similar number of tokens across all batches, the batch size in such cases needs to be augmented. This leads to variable batch size and more complex comparisons which researchers wanted to avoid.

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model. Initializing with a config file does not load the weights associated with the model, only the configuration.

model. Initializing with a config file does not load the weights associated with the model, only the configuration.

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:

A Bastante virada em sua própria carreira veio em 1986, quando conseguiu gravar seu primeiro disco, “Roberta Miranda”.

Recent advancements in NLP showed that increase of the batch size with the appropriate decrease of the learning rate and the number of training steps usually tends to improve the model’s performance.

This is useful if you want more control over how to convert input_ids indices into associated vectors

Attentions weights after the attention softmax, used to compute the weighted Veja mais average in the self-attention

a dictionary with one or several input Tensors associated to the input names given in the docstring:

Throughout this article, we will be referring to the official RoBERTa paper which contains in-depth information about the model. In simple words, RoBERTa consists of several independent improvements over the original BERT model — all of the other principles including the architecture stay the same. All of the advancements will be covered and explained in this article.