# English Reading Comprehension

A question-answering model fine-tuned on the SQuAD dataset based on distilbert-base-uncased

This model is a fine-tuned version of distilbert-base-uncased on the SQuAD question answering dataset, suitable for QA tasks.

MobileBERT is a lightweight version of BERT_LARGE, featuring a bottleneck structure design that balances self-attention mechanisms and feed-forward networks. This model is fine-tuned on the SQuAD1.1 dataset and is suitable for question-answering tasks.

A Q&A model fine-tuned on the SQuAD v2 dataset based on the ALBERT base v2 architecture, excelling in reading comprehension tasks involving unanswerable questions

A question-answering model fine-tuned on the Squad V2 dataset based on the Mobile-Bert architecture, suitable for resource-limited devices

BERT-Small is a compact BERT model developed by Google Research, fine-tuned on the SQuAD 2.0 dataset, suitable for Q&A tasks in resource-constrained environments.

A QA model fine-tuned based on the lightweight MobileBERT architecture, specifically optimized for the SQuAD v2 dataset, capable of handling both answerable and unanswerable questions.