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Argument–Keypoint Matching with DistilBERT

This model predicts whether an argument is correctly matched (Apparié) or not (Non-Apparié) with a given key point.

Model Description

  • Base Model: DistilBERT (uncased)
  • Task: Binary text-pair classification
  • Training Data: IBM ArgKP-2023 dataset (~32,000 examples)
  • Labels:
    • 0 — Non-Apparié
    • 1 — Apparié
  • Input: (argument, key_point)
  • Output: Predicted class + probabilities

Performance

  • Strong accuracy and F1 score on evaluation data
  • Reliable predictions across both labels

Training

Trained on a balanced argument–keypoint dataset

Exported using save_pretrained

Citation

@misc{argument-keypoint-matching,
  author       = {Malek Messaoudi},
  title        = {Argument–Keypoint Matching with DistilBERT},
  year         = {2025},
  publisher    = {Hugging Face},
  howpublished = {{\\url{{https://huggingface.co/Malek-Messaoudi/Key-point-matching-argument}}}}
}

License

MIT License

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