CUNI System for the WMT19 Robustness Task
Table 2: BLEU scores of the baseline and CUNI models measured on several datasets.
['[EMPTY]', 'English-French WMT14', 'English-French WMT15', 'English-French MTNT', 'English-French blind', 'French-English WMT14', 'French-English WMT15', 'French-English MTNT', 'French-English blind']
The model that was used as a baseline for the Robustness Task was trained on the WMT15 parallel data. Additionally, simple fine-tuning using stochastic gradient descent on the MTNT data is shown to improve the translation quality by a large margin. The Transformer-based baseline outperforms the RNN-based MTNT baseline by a large margin on both WMT and MTNT test datasets.