mT5_base_yor_eng_mt is a machine translation model from Yorùbá language to English language based on a fine-tuned mT5-base model. It establishes a strong baseline for automatically translating texts from Yorùbá to English.
Specifically, this model is a mT5_base model that was fine-tuned on JW300 Yorùbá corpus and Menyo-20k
You can use this model with Transformers pipeline for MT.
from transformers import MT5ForConditionalGeneration, T5Tokenizer model = MT5ForConditionalGeneration.from_pretrained("Davlan/mt5_base_yor_eng_mt") tokenizer = T5Tokenizer.from_pretrained("google/mt5-base") input_string = "Akọni ajìjàgbara obìnrin tó sun àtìmalé torí owó orí" inputs = tokenizer.encode(input_string, return_tensors="pt") generated_tokens = model.generate(inputs) results = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True) print(results)
This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains.
This model was fine-tuned on on JW300 Yorùbá corpus and Menyo-20k dataset
This model was trained on a single NVIDIA V100 GPU
15.57 BLEU on Menyo-20k test set
By David Adelani
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