EA-HS: East Africa Hate Speech Classifier v3

Multilingual hate speech classifier for East African languages, built for conflict monitoring and peacebuilding applications.

Model Details

• Base model: Davlan/afro-xlmr-base (Africa-focused XLM-RoBERTa)
• Fine-tuned on: AfriHate (7 African languages) + HatEval (Arabic) + HateXplain (English)
• Labels: 0 (not hate), 1 (hate), 2 (offensive)
• Languages: Swahili, Somali, Amharic, Oromo, Tigrinya, Kinyarwanda, Nigerian Pidgin, Arabic, English

Performance

Version	Base Model	Accuracy	F1
v3 (current)	afro-xlmr-base	77.10%	76.87%
v2	xlm-roberta-base	76.18%	75.99%

Usage

from transformers import pipeline
classifier = pipeline('text-classification', model='KSvendsen/EA-HS')
result = classifier('This is a test sentence')

Training

• 5 epochs, batch size 16, learning rate 2e-5
• Class-weighted loss + minority upsampling
• ~95k training samples across 9 languages

Developed by

MERLx / RIKO - AI-augmented conflict monitoring