BERT Models Fine-tuned on Algerian Dialect Sentiment Analysis

These are different BERT models (BERT Arabic models are initialized from AraBERT) fine-tuned on the Algerian Dialect Sentiment Analysis dataset. The dataset contains 50,016 comments from YouTube videos in Algerian dialect. The models are evaluated on the testing set:

Model Version No. of Parameters Training Time F1-Score Accuracy
LSTM ~4 M 3 min 0.7399 0.7445
Bi-LSTM ~4.3 M 6 min 35 s 0.7380 0.7437
BERT Base ~109.5 M 33 min 20 s 0.6979 0.7500
BERT Large ~335.1 M 1 h 50 min 0.6976 0.7484
BERT Arabic Mini ~11.6 M 2 min 40 s 0.7057 0.7527
BERT Arabic Medium ~42.1 M 11 min 25 s 0.7521 0.7860
BERT Arabic Base ~110.6 M 34 min 19 s 0.7688 0.8002
BERT Arabic Large ~336.7 M 1 h 53 min 0.7838 0.8174

Citation

If you find our work useful, please cite it as follows:

@article{2023,
  title={Sentiment Analysis on Algerian Dialect with Transformers},
  author={Zakaria Benmounah and Abdennour Boulesnane and Abdeladim Fadheli and Mustapha Khial},
  journal={Applied Sciences},
  volume={13},
  number={20},
  pages={11157},
  year={2023},
  month={Oct},
  publisher={MDPI AG},
  DOI={10.3390/app132011157},
  ISSN={2076-3417},
  url={http://dx.doi.org/10.3390/app132011157}
}
Downloads last month
19
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train Abdou/arabert-medium-algerian