Performance of two French BERT models for French language on verbatim transcripts and online posts
Résumé
Pre-trained models based on the Transformer architecture have achieved notable performances in various language processing tasks. This article presents a comparison of two pretrained versions for French in a three-class classification task. The datasets used are of two types: a set of annotated verbatim transcripts from face-to-face interviews conducted during a market study and a set of online posts extracted from a community platform. Little work has been done in these two areas with transcribed oral corpora and online posts in French.
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