Universal Language Model Fine-tuning for Text Classification
Table 3: Test error rates (%) on text classification datasets used by johnson2017deep.
['[EMPTY]', 'AG', 'DBpedia', 'Yelp-bi', 'Yelp-full']
Our method again outperforms the state-of-the-art significantly. On AG, we observe a similarly dramatic error reduction by 23.7% compared to the state-of-the-art. On DBpedia, Yelp-bi, and Yelp-full, we reduce the error by 4.8%, 18.2%, 2.0% respectively.