Before revision:  On these datasets, we also show that by using pre-trained models and paraphrases from iNLTK, we can achieve more than 95\% of the previous best performance by using less than 10\% of the training data. iNLTK is already being widely used by the community and has 40,000+ downloads, 600+ stars and 100+ forks on GitHub.
After revision:  On these datasets, we also show that by using pre-trained models and data augmentation from iNLTK, we can achieve more than 95\% of the previous best performance by using less than 10\% of the training data. iNLTK is already being widely used by the community and has 40,000+ downloads, 600+ stars and 100+ forks on GitHub.