The Effect of Domain and Diacritics in Yorùbá-English Neural Machine Translation
Paper • 2103.08647 • Published
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language: - yo - en datasets: - JW300 + Menyo-20k
m2m100_418M-eng-yor-mt
Model description
m2m100_418M-yor-eng-mt is a machine translation model from Yorùbá language to English language based on a fine-tuned facebook/m2m100_418M model. It establishes a strong baseline for automatically translating texts from Yorùbá to English.
Specifically, this model is a facebook/m2m100_418M model that was fine-tuned on JW300 Yorùbá corpus and Menyo-20k.
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 JW300 corpus and Menyo-20k dataset
Training procedure
This model was trained on NVIDIA V100 GPU
Eval results on Test set (BLEU score)
Fine-tuning m2m100_418M achieves 16.76 BLEU on Menyo-20k test set while mt5-base achieves 15.57
BibTeX entry and citation info
By David Adelani
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# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Davlan/m2m100_418M-yor-eng-mt") model = AutoModelForSeq2SeqLM.from_pretrained("Davlan/m2m100_418M-yor-eng-mt", device_map="auto")