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hatemnoaman/bert-base-arabic-finetuned-emotion

sourceHugging Faceupdated 3y agoView on Hugging Face
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bert-base-arabic-finetuned-emotion

This model is a fine-tuned version of asafaya/bert-base-arabic on the emotone_ar dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8965
  • Accuracy: 0.7416
  • F1: 0.7406

Cite this model

-Noaman, H. (2023). Improved Emotion Detection Framework for Arabic Text using Transformer Models.
Advanced Engineering Technology and Application, 12(2), 1-11.

@article{noaman2023improved,
  title={Improved Emotion Detection Framework for Arabic Text using Transformer Models},
  author={Noaman, Hatem},
  journal={Advanced Engineering Technology and Application},
  volume={12},
  number={2},
  pages={1--11},
  year={2023},
  publisher={Fayoum University}
}

Load Pretrained Model

You can use this model by

python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("hatemnoaman/bert-base-arabic-finetuned-emotion")
model = AutoModel.from_pretrained("hatemnoaman/bert-base-arabic-finetuned-emotion")

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • trainbatchsize: 64
  • evalbatchsize: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 6

Training results

Training LossEpochStepValidation LossAccuracyF1
1.34761.01420.89110.70080.6812
0.82042.02840.81750.72760.7212
0.62273.04260.83920.73760.7302
0.48164.05680.85310.74350.7404
0.3785.07100.88170.73960.7388
0.31346.08520.89650.74160.7406

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2