US 12,204,851 B2
Method for generating pre-trained language model, electronic device and storage medium
Tongyang Liu, Beijing (CN); Shu Wang, Beijing (CN); Wanli Chang, Beijing (CN); Wei Zheng, Beijing (CN); Zhifan Feng, Beijing (CN); Chunguang Chai, Beijing (CN); and Yong Zhu, Beijing (CN)
Assigned to BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD., Beijing (CN)
Filed by BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD., Beijing (CN)
Filed on Jul. 14, 2022, as Appl. No. 17/864,636.
Claims priority of application No. 202110931911.6 (CN), filed on Aug. 13, 2021.
Prior Publication US 2022/0350965 A1, Nov. 3, 2022
Int. Cl. G06F 40/211 (2020.01); G06F 40/109 (2020.01); G06F 40/30 (2020.01); G06N 3/08 (2023.01)
CPC G06F 40/211 (2020.01) [G06F 40/109 (2020.01); G06F 40/30 (2020.01); G06N 3/08 (2013.01)] 18 Claims
OG exemplary drawing
 
7. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory is configured to store instructions executable by the at least one processor, when the instructions are executed by the at least one processor, the at least one processor is enabled to perform:
obtaining sample files;
obtaining typography structure information and text information of the sample files by parsing the sample files;
obtaining a plurality of task models of a pre-trained language model, wherein the plurality of task models comprise a first prediction model, a masked language model and a second prediction model;
obtaining a trained pre-trained language model by jointly training the pre-trained language model and the plurality of task models according to the typography structure information and the text information; and
generating a target pre-trained language model by fine-tuning the trained pre-trained language model according to the typography structure information and the text information.