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distilBert-keypoint-matching
NLP-Debater-Project/distilBert-keypoint-matching
distilBert-keypoint-matching is a machine learning model from NLP-Debater-Project. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This model predicts whether an argument is correctly matched (Apparié) or not (Non-Apparié) with a given key point.
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At a glance
- Model type
- distilbert
- Access
- Public
- Created
- Nov 18, 2025
- Updated
- Nov 19, 2025
- SHA
- 3b59c330
Model card
From the Hugging Face model README
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-Apparié1— 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
- Type
- distilbert
- Created
- Nov 18, 2025
- Updated
- Nov 19, 2025