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Revealing the Dark Secrets of BERT

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Figure

Figure 1: Typical self-attention classes used for training a neural network. Both axes on every image representBERT tokens of an input example, and colors denote absolute attention weights (darker colors stand for greaterweights)
Figure 5 shows that for all the tasks ex-
Figure 5: Per-head cosine similarity between pre-trained BERT’s and fine-tuned BERT’s self-attention maps foreach of the selected GLUE tasks, averaged over validation dataset examples
Figure 7: Per-task attention weights corresponding to the [CLS] token averaged over input sequences’ lengths andover dataset examples, and extracted from the final layer
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