検索に戻る
案件記録

TRAINING A MULTI-DOMAIN LANGUAGE MODEL FOR CONTENT MODERATION

発明審査中
2閲覧数
20請求項 · 3 独立
§ Ⅰ

案件概要

発明者

Tharathorn Rimchala; Runhua Zhao

IPC分類

G6N 20/

CPC分類

G6N20/

A method including receiving a multi-domain language model having a number of base layers, a number of domain general adapter layers, and a set of domain specific adapter layers. The method also includes training the base layers on an unlabeled training dataset. The method also includes training the domain general adapter layers on a domain general labeled dataset generated from the unlabeled training dataset. Training the domain general adapter layers excludes updating the set of domain specific adapter layers. The method also includes training the set of domain specific adapter layers on a domain specific labeled dataset generated from the unlabeled training dataset. Training the set of domain specific adapter layers excludes updating the domain general adapter layers. The method also includes returning, as a trained multi-domain language model, the updated base layers, the updated domain general adapter layers, and the updated set of domain specific adapter layers.

原文(中国語)

A method including receiving a multi-domain language model having a number of base layers, a number of domain general adapter layers, and a set of domain specific adapter layers. The method also includes training the base layers on an unlabeled training dataset. The method also includes training the domain general adapter layers on a domain general labeled dataset generated from the unlabeled training dataset. Training the domain general adapter layers excludes updating the set of domain specific adapter layers. The method also includes training the set of domain specific adapter layers on a domain specific labeled dataset generated from the unlabeled training dataset. Training the set of domain specific adapter layers excludes updating the domain general adapter layers. The method also includes returning, as a trained multi-domain language model, the updated base layers, the updated domain general adapter layers, and the updated set of domain specific adapter layers.

外部リソース