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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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Dynamically changing the masking pattern: In BERT architecture, the masking is performed once during data preprocessing, resulting in a single static mask. To avoid using the single static mask, training data is duplicated and masked 10 times, each time with a different mask strategy over quarenta epochs thus having 4 epochs with the same mask.
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A Colossal virada em sua própria carreira veio em 1986, quando conseguiu gravar seu primeiro disco, “Roberta Miranda”.
model. Initializing with a config file does not load the weights associated with the model, only the configuration.
This results in 15M and 20M additional parameters for BERT base and BERT large models respectively. The introduced encoding version in RoBERTa demonstrates slightly worse results than before.
model. Initializing with a config file does not Veja mais load the weights associated with the model, only the configuration.
If you choose this second option, there are three possibilities you can use to gather all the input Tensors
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