Service Quality Ai-based System is a cutting-edge platform designed to enhance customer service and support in various industries specifically in Arabic language.
- Topic classification
- Sentiment Analysis
- Solution Generation
This is the repository accompanying our project [ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic]. In the paper, we:
- introduce
ARBERT
andMARBERT
, two powerful Transformer-based language models for Arabic; - introduce
ArBench
, a multi-domain, multi-variety benchmark for Arabic naturaal language understanding based on 41 datasets across 5 different tasks and task clusters; - evaluate ARBERT and MARBERT on ArBench and compare against available language models.
Our model establish new state-of-the-art (SOTA) on all 5 tasks/task clusters on 37 out of the 41 datasets. Our language models are publicaly available for research (see below). The rest of this repository provides more information about our new language models, benchmark, and experiments.
You can use ARBERT and MARBERT with Hugging Face's Transformers library as follow.
from transformers import AutoTokenizer, AutoModel
#load AEBERT model from huggingface
ARBERT_tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/ARBERT")
ARBERT_model = AutoModel.from_pretrained("UBC-NLP/ARBERT")
#load MAEBERT model from huggingface
MARBERT_tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/MARBERT")
MARBERT_model = AutoModel.from_pretrained("UBC-NLP/MARBERT")
MARBERT Fine-Tuning demo with PyTorch checkpoint for Sentiment Analysis on the AJGT dataset