  In this paper, we provide an overview of the WNUT-2020 shared task on the
identification of informative COVID-19 English Tweets. We describe how we
construct a corpus of 10K Tweets and organize the development and evaluation
phases for this task. In addition, we also present a brief summary of results
obtained from the final system evaluation submissions of 55 teams, finding that
(i) many systems obtain very high performance, up to 0.91 F1 score, (ii) the
majority of the submissions achieve substantially higher results than the
baseline fastText (Joulin et al., 2017), and (iii) fine-tuning pre-trained
language models on relevant language data followed by supervised training
performs well in this task.
