# Text Classification Enhancement

The roberta_wwm_ext_large model trained on massive Chinese reading comprehension data shows significant improvement in tasks like reading comprehension and text classification.

AfriBERTa is a multilingual pretrained model supporting 11 African languages with 111 million parameters, suitable for tasks like text classification and named entity recognition.

This is a Hausa BERT model fine-tuned based on the multilingual BERT model, performing better than the original multilingual BERT in text classification and named entity recognition tasks.