transformers pytorch mbart text2text-generation arxiv:2103.08647 autotrain_compatible endpoints_compatible region:us
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Hugging Face's logo
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language: 
- yo
- en
datasets:
- JW300 + [Menyo-20k](https://huggingface.co/datasets/menyo20k_mt)
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# mbart50-large-yor-eng-mt
## Model description
**mbart50-large-yor-eng-mt** is a **machine translation** model from Yorùbá language to English language based on a fine-tuned   facebook/mbart-large-50 model.  It establishes a **strong baseline** for automatically translating texts from Yorùbá to English.  

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 mbart50-large achieves **15.88 BLEU** on [Menyo-20k test set](https://arxiv.org/abs/2103.08647) while mt5-base achieves 15.57

### BibTeX entry and citation info
By David Adelani
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