TunBERT

People in Tunisia use the Tunisian dialect in their daily communications, in most of their media (TV, radio, songs, etc), and on the internet (social media, forums). Yet, this dialect is not standardized which means there is no unique way for writing and speaking it. Added to that, it has its proper lexicon, phonetics, and morphological structures. The need for a robust language model for the Tunisian dialect has become crucial in order to develop NLP-based applications (translation, information retrieval, sentiment analysis, etc). This repository includes the code for fine-tuning TunBERT on the three downstream tasks: Sentiment Analysis (SA), Tunisian Dialect Identification (TDI) and Reading Comprehension Question-Answering (RCQA). This will help the community reproduce our work and collaborate continuously. We also released the two pre-trained new models: TunBERT Pytorch and TunBERT TensorFlow. Finally, we open source the fine-tuning datasets used for Tunisian Dialect Identification (TDI) and Reading Comprehension Question-Answering (RCQA)