Specifically, this model is a
mbart-large-50 model that was fine-tuned on JW300 Yorùbá corpus and
Menyo-20k. The model was trained using Swahili(sw_KE) as the language since the pre-trained model does not initially support Yorùbá. Thus, you need to use the sw_KE for language code when evaluating the model.
This model is limited by its training dataset. This may not generalize well for all use cases in different domains.
This model was fine-tuned on on JW300 corpus and
Menyo-20k dataset
Fine-tuning mbarr50-large achieves
13.39 BLEU on
Menyo-20k test set while mt5-base achieves 9.82