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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}
}
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Dataset used to train Abdou/arabert-large-algerian