Learning Paraphrastic Sentence Embeddingsfrom Back-Translated Bitext
Table 8: Results of reference/translation classification (accuracy×100). The highest score in each column is in boldface. Final two columns show accuracies of positive (reference) and negative classes, respectively.
['Model', 'Lang.', 'Data', 'Test Acc.', '+ Acc.', '- Acc.']
While performance varies greatly across data sources, the LSTM always outperforms the word averaging model. For our translation-reference classification, we note that our results can be further improved. We also trained models on 90,000 examples, essentially doubling the amount of data, and the results improved by about 2% absolute on each dataset on both the validation and testing data.