Solution of DeBERTaV3 on CommonsenseQA

TL;DR

This paper demonstrates that DeBERTaV3 achieves new state-of-the-art results on CommonsenseQA by leveraging its natural language inference capabilities, using a straightforward text classification approach without external knowledge.

Contribution

The paper shows that DeBERTaV3's natural language inference ability can be effectively utilized for commonsense question answering, setting new benchmarks without external data.

Findings

DeBERTaV3 achieves state-of-the-art performance on CommonsenseQA.

Single and ensemble models outperform previous methods.

No external knowledge is needed for top performance.

Abstract

We report the performance of DeBERTaV3 on CommonsenseQA in this report. We simply formalize the answer selection as a text classification for DeBERTaV3. The strong natural language inference ability of DeBERTaV3 helps its single and ensemble model set the new (w/o external knowledge) state-of-the-art on CommonsenseQA.