| Hugging Face's logo | |
| --- | |
| language: | |
| - yo | |
| - en | |
| datasets: | |
| - JW300 + [Menyo-20k](https://huggingface.co/datasets/menyo20k_mt) | |
| --- | |
| # mbart50-large-eng-yor-mt | |
| ## Model description | |
| **mbart50-large-eng-yor-mt** is a **machine translation** model from English language to Yorùbá language based on a fine-tuned facebook/mbart-large-50 model. It establishes a **strong baseline** for automatically translating texts from English to Yorùbá. | |
| Specifically, this model is a *mbart-large-50* model that was fine-tuned on JW300 Yorùbá corpus and [Menyo-20k](https://huggingface.co/datasets/menyo20k_mt). 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. | |
| #### Limitations and bias | |
| This model is limited by its training dataset. This may not generalize well for all use cases in different domains. | |
| ## Training data | |
| This model was fine-tuned on on JW300 corpus and [Menyo-20k](https://huggingface.co/datasets/menyo20k_mt) dataset | |
| ## Training procedure | |
| This model was trained on NVIDIA V100 GPU | |
| ## Eval results on Test set (BLEU score) | |
| Fine-tuning mbarr50-large achieves **13.39 BLEU** on [Menyo-20k test set](https://arxiv.org/abs/2103.08647) while mt5-base achieves 9.82 | |
| ### BibTeX entry and citation info | |
| By David Adelani | |
| ``` | |
| ``` | |