NLP-Debater-Project/distilBert-keypoint-matching

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/NLP-Debater-Project/destlibert-keypoint-matching}}}}
}

License

MIT License