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language: yo datasets: - JW300 + Menyo-20k

mT5_base_yoruba_adr

Model description

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

Intended uses & limitations

How to use

You can use this model with Transformers pipeline for ADR.

from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline
tokenizer = AutoTokenizer.from_pretrained("")
model = AutoModelForTokenClassification.from_pretrained("")
nlp = pipeline("", model=model, tokenizer=tokenizer)
example = "Emir of Kano turban Zhang wey don spend 18 years for Nigeria"
ner_results = nlp(example)
print(ner_results)

Limitations and bias

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.

Training data

This model was fine-tuned on on JW300 Yorùbá corpus and Menyo-20k dataset

Training procedure

This model was trained on a single NVIDIA V100 GPU

Eval results on Test set (BLEU score)

15.57 BLEU on Menyo-20k test set

BibTeX entry and citation info

By David Adelani