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relevant-comment-detector
Chaima-KHENAFIF/relevant-comment-detector
relevant-comment-detector is a text classification model from Chaima-KHENAFIF. Use it when you need a label for a piece of text. The card lists the license as mit.
A fine-tuned xlm-roberta-base model that classifies social media comments as relevant or irrelevant to the topic they were posted under.
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At a glance
- Task
- Text Classification
- License
- mit
- Access
- Public
- Created
- Aug 21, 2026
- Updated
- Aug 21, 2026
- SHA
- 30b18041
Try a prompt
Base models
Model card
From the Hugging Face model README
Relevant / Irrelevant Comment Classifier
A fine-tuned xlm-roberta-base model that classifies social media comments as relevant or irrelevant to the topic they were posted under.
Trained on real-world telecom customer comments (French, Darija, and Arabic), where "irrelevant" covers off-topic chatter, spam, or unrelated remarks mixed in with genuine customer feedback.
Usage
from transformers import pipeline
classifier = pipeline("text-classification", model="Chaima-KHENAFIF/relevant-comment-detector")
classifier("la connexion est très lente")
Training
Fine-tuned on ~2,000 labeled comments scraped from telecom operator social media pages, covering French, Darija (Latin and Arabic script), and Arabic.
Training results
| Epoch | Train Loss | Val Loss | Val Accuracy |
|---|---|---|---|
| 1 | 0.5005 | 0.2117 | 93.56% |
| 2 | 0.2171 | 0.1577 | 95.05% |
| 3 | 0.1743 | 0.1530 | 94.06% |
| 4 | 0.1322 | 0.1546 | 93.56% |
Best validation accuracy of 95.05% reached at epoch 2.
Links
- Full code and training pipeline: GitHub repo
- Task
- Text Classification
- License
- mit
- Languages
- ar, fr, en
- Created
- Aug 21, 2026
- Updated
- Aug 21, 2026