language:
- en
- ha
- yo
- ig
- pcm
pipeline_tag: text-classification
datasets:
- manueltonneau/NaijaHate
NaijaXLM-T-base Hate
This is a NaijaXLM-T base model finetuned on Nigerian tweets annotated for hate speech detection. The model is described and evaluated in the reference paper and was developed by @pvcastro and @manueltonneau.
Model Details
Model Description
- Model type: xlm-roberta
- Language(s) (NLP): (Nigerian) English, Nigerian Pidgin, Hausa, Yoruba, Igbo
- Finetuned from model:
manueltonneau/naija-xlm-twitter-base
Model Sources [optional]
- Repository: https://github.com/manueltonneau/hate_speech_nigeria
- Paper: https://arxiv.org/abs/2403.19260
Training Details
Training Data
This model was finetuned on the stratified (dataset=='stratified') and active learning (dataset=='al') subset of NaijaHate.
Training Procedure and Evaluation
We perform a 90-10 train-test split and conduct a 5-fold cross-validation with 5 learning rates ranging from 1e-5 to 5e-5. Each fold is trained using 3 different seeds. The train-test split is repeated for 10 different seeds, and the evaluation metrics are averaged across the 10 seeds.
We evaluate model performance on three datasets: the holdout sample from the train-test splits as well as the top-scored sample (dataset=='eval') and the random sample (dataset=='random') from NaijaHate.
| Model | Holdout | Top-scored | Random |
|---|---|---|---|
| GPT-3.5, ZSL | - | 60.3±2.7 | 3.1±1.2 |
| Perspective API | - | 60.2±3.5 | 4.3±2.6 |
| XLM-T | 84.2 ± 0.6 | 51.8 ± 0.7 | 0.6 ± 0.1 |
| XLM-T | 62.0 ± 2.3 | 68.9 ± 0.8 | 3.3 ± 0.6 |
| XLM-T | 70.5 ± 3.7 | 63.7 ± 1.1 | 1.9 ± 0.5 |
| DeBERTaV3 | 82.3 ± 2.3 | 85.3 ± 0.8 | 29.7 ± 4.1 |
| XLM-R | 76.7 ± 2.5 | 83.6 ± 0.8 | 22.1 ± 3.7 |
| mDeBERTaV3 | 29.2 ± 2.0 | 49.6 ± 1.0 | 0.2 ± 0.0 |
| Conv. BERT | 79.2 ± 2.3 | 86.2 ± 0.8 | 22.6 ± 3.6 |
| BERTweet | 83.6 ± 2.0 | 88.5 ± 0.6 | 34.0 ± 4.4 |
| XLM-T | 79.0 ± 2.4 | 84.5 ± 0.9 | 22.5 ± 3.7 |
| AfriBERTa | 70.1 ± 2.7 | 80.1 ± 0.9 | 12.5 ± 2.8 |
| AfroXLM-R | 79.7 ± 2.3 | 86.1 ± 0.8 | 24.7 ± 4.0 |
| XLM-R Naija | 77.0 ± 2.5 | 83.5 ± 0.8 | 19.1 ± 3.4 |
| NaijaXLM-T | 83.4 ± 2.1 | 89.3 ± 0.7 | 33.7 ± 4.5 |
For more information on the evaluation, please read the reference paper.
BibTeX entry and citation information
Please cite the reference paper if you use this model.
@article{tonneau2024naijahate,
title={NaijaHate: Evaluating Hate Speech Detection on Nigerian Twitter Using Representative Data},
author={Tonneau, Manuel and de Castro, Pedro Vitor Quinta and Lasri, Karim and Farouq, Ibrahim and Subramanian, Lakshminarayanan and Orozco-Olvera, Victor and Fraiberger, Samuel},
journal={arXiv preprint arXiv:2403.19260},
year={2024}
}