Anonymized BERT: An Augmentation Approachto the Gendered Pronoun Resolution Challenge
Table 2: Stage 1 results improvements in End2end model due to augmentation
['[BOLD] model', '[BOLD] uncased', '[BOLD] cased', '[BOLD] ensemble']
In both uncased and cased versions and their ensemble, stage 1 log loss improved by about 0.01 when augmentation is added in training but not inference. And another massive 0.05 and 0.04 improvement for the uncased and cased version respectively is achieved when TTA is used. For the ensemble, augmentation improved the score from 0.3470 to 0.3052.