This model is a version of
bert-base-cased fine-tuned on a
dataset of African American Vernacular English (AAVE) which was published alongside
Jørgensen et al. 2016.
It achieves the following results on the evaluation set:
This model is intended to help close the gap in part-of-speech tagging performance between Standard American English (SAE) and African American English (AAVE) which differ liguistically in many
well-documented ways. It was fine-tuned on data gathered from Twitter, and is thus ingrained with what linguists call 'register bias'.
