A distributed fine-tuning framework that applies RLHF with AfriCOMET as a reward model to improve machine translation for low-resource and under-resourced language pairs.
# West African Machine Translation with AfriCOMET-Guided RLHF
**A machine translation system for West African languages. It teaches a small language model to translate, then improves it using feedback from a quality-scoring model built for African languages. Work is still ongoing.**
| | |
|---|---|
| **Base model** | `google/gemma-3-270m-it` |
| **Published checkpoint** | `BeardedMonster/gemma-3-270m-translate-it` |
| **Training data** | `Aletheia-ng/tds-sft` |
| **Reward model** | `masakhane/africomet-stl` |
| **Evaluation benchmark** | `masakhane/mafand` (validation split) |
| **Languages** | Hausa, Igbo, Yoruba, Wolof, Ewe, Fon, Twi (+ Nigerian Pidgin in training data) |
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## Table of Contents
1. Problem Statement
2. Approach
3. How It Works
4. Evaluation
5. Related Academic Work
6. Quick Start
7. Multi-GPU Training
8. Project Layout
9. Tech Stack
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## 1. Problem Statement
Most translation tools work well for languages like English, French, and German — but **West African languages are underserved**. Hausa, Igbo, Yoruba, Wolof, and others have far less training data, and general-purpose AI models often produce weak translations for them.
Three challenges make this hard:
1. **Not enough data** — There are far fewer high-quality translation examples for these languages than for major world languages.
2. **Hard to measure quality** — Standard translation scores do not always reflect how good a translation actually sounds to speakers of the language.
3. **Training cost** — Improving a model on millions of examples, then refining it with quality feedback, takes real compute — even with a small model.
**What this project does:**
- Trains **Gemma 3 270M**, a compact Google language model, on `Aletheia-ng/tds-sft` (~11M translation examples).
- Runs a second training stage that **rewards better translations** using **AfriCOMET**, a quality scorer built for African languages.
- Supports **single-GPU or multi-GPU training** so the same pipeline works on a l …