The mask token in BERT is a special token used to replace a certain percentage of words in the input text during the pre-training phase. This strategy aims to help the model learn to infer the masked words based on the context, thus improving its performance on downstream tasks. Typically, 15% of the tokens are chosen for masking, with 80% of those replaced by the [MASK] token, 10% replaced by random tokens, and the remaining 10% kept unchanged.
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Alessandro
Thu Mar 20 2025
This special token is frequently incorporated into transformer-based models.
Stefano
Thu Mar 20 2025
One notable example of such models is BERT (Bidirectional Encoder Representations from Transformers).
GinsengBoostPower
Thu Mar 20 2025
In BERT and similar architectures, the mask token helps handle missing word prediction tasks.
PhoenixRising
Thu Mar 20 2025
Mask token ([MASK]) plays a crucial role in machine learning and artificial intelligence models.
CryptoAlchemy
Thu Mar 20 2025
Specifically, it is utilized for language modeling and text prediction tasks.