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System Development & Application
|
212-216

Question answering model based on self-distillation and self-ensemble

Wang Tongjie
Li Ye
School of Optical-Electrical & Computer Engineering, University of Shanghai for Science & Technology, Shanghai 200093, China

Abstract

Knowledge distillation combined with pre-trained language models is one of the primary methods for constructing question-answering models. However, these methods suffer from inefficiencies in knowledge transfer, time-consuming teacher model training, and mismatched capabilities between teacher and student models. To address these issues, this paper proposed a question-answering model based on self-distillation and self-ensemble, named SD-SE-BERT. The self-ensemble mechanism was designed based on a sliding window; the student model used BERT; the teacher model was derived from a weighted average combination of several student models during the training process, based on their performance on the validation set. The loss function used the output of the ensemble and the true labels to guide the training of the student model in the current round. Experimental results on the SQuAD1.1 dataset show that the EM and F1 scores of SD-SE-BERT are respectively 7.5 and 4.9 higher than those of the BERT model, and the model's performance surpasses other representative single models and distillation models. Compared to the fine-tuning results of the large-scale language model ChatGLM-6B, the EM score was improved by 4.5, and the F1 score by 2.5. It proves that SD-SE-BERT can leverage the model's supervision information to enhance the model's capacity to combine different text data features, eliminating the need for complex teacher-model training and avoiding the problem of mismatch between teacher and student models.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.05.0281
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 1
Section: System Development & Application
Pages: 212-216
Serial Number: 1001-3695(2024)01-032-0212-05

Publish History

[2023-10-07] Accepted Paper
[2024-01-05] Printed Article

Cite This Article

王同结, 李烨. 基于自蒸馏与自集成的问答模型 [J]. 计算机应用研究, 2024, 41 (1): 212-216. (Wang Tongjie, Li Ye. Question answering model based on self-distillation and self-ensemble [J]. Application Research of Computers, 2024, 41 (1): 212-216. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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