SOTAVerified

BARThez: a Skilled Pretrained French Sequence-to-Sequence Model

2020-10-23EMNLP 2021Code Available1· sign in to hype

Moussa Kamal Eddine, Antoine J. -P. Tixier, Michalis Vazirgiannis

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

Inductive transfer learning has taken the entire NLP field by storm, with models such as BERT and BART setting new state of the art on countless NLU tasks. However, most of the available models and research have been conducted for English. In this work, we introduce BARThez, the first large-scale pretrained seq2seq model for French. Being based on BART, BARThez is particularly well-suited for generative tasks. We evaluate BARThez on five discriminative tasks from the FLUE benchmark and two generative tasks from a novel summarization dataset, OrangeSum, that we created for this research. We show BARThez to be very competitive with state-of-the-art BERT-based French language models such as CamemBERT and FlauBERT. We also continue the pretraining of a multilingual BART on BARThez' corpus, and show our resulting model, mBARThez, to significantly boost BARThez' generative performance. Code, data and models are publicly available.

Tasks

Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
OrangeSummBARThez (OrangeSum abstract)ROUGE-132.67Unverified
OrangeSumBARThez (OrangeSum abstract)ROUGE-131.44Unverified

Reproductions