Cross-Lingual Ability of Multilingual BERT: An Empirical Study
Table 1: The Effect of Word-piece Overlap and of Structural Similarity For different pairs of B-BERT languages, and for two tasks (XNLI and NER), we show the contribution of word-pieces to the success of the model. In every two consecutive rows, we show results for a pair (e.g., English-Spanish) and then for the corresponding pair after mapping English to a disjoint set of word-pieces. The gap between the performance in each group of two rows indicates the loss due to completely eliminating the word-piece contribution. We add an asterisk to the number for NER when the results are statistically significant at the 0.05 level.
['[BOLD] B-BERT', '[BOLD] Train', '[BOLD] Test', '[BOLD] XNLI  [BOLD] Accuracy', '[BOLD] XNLI  [BOLD] Word-piece Contribution', '[BOLD] NER  [BOLD] F{}_{1}-Score']
We measure the contribution of word-piece overlap as the drop in performance when the word-piece overlap is removed.