Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Input: Experiments ::: Results ::: Natural Language Inference: XNLI
On the XNLI benchmark, CamemBERT obtains improved performance over multilingual language models on the TRANSLATE-TRAIN setting (81.2 vs. 80.2 for XLM) while using less than half the parameters (110M vs. 250M). However, its performance still lags behind models trained on the original English training set in the TRANSLATE-TEST setting, 81.2 vs. 82.91 for RoBERTa. It should be noted that CamemBERT uses far fewer parameters than RoBERTa (110M vs. 355M parameters).
Question: Which tasks does CamemBERT not improve on?
Output:
its performance still lags behind models trained on the original English training set in the TRANSLATE-TEST setting, 81.2 vs. 82.91 for RoBERTa