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

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
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Training results

Framework versions

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