# Translation Experiments
A suite of translation experiments across a variety of models and datasets, focused on African languages. We believe synthetic data is a powerful tool for improving model performance on low-resource languages, and machine translation is a critical part of that pipeline. We hope these results will help the community understand the strengths and weaknesses of different models and approaches to translation.
## Ablations
- Baseline results on the following datasets:
- AfriDocMT (Health, Tech domain)
- openlanguagedata/flores_plus
- SFT with different model and dataset mixture combinations
- GRPO on base instruction-tuned models and SFT models
- SDPO on base instruction-tuned models and SFT models