chinese macbert base EU AI Act Compliance Profile

Please use 'Bert' related functions to load this model!

This repository contains the resources in our paper "Revisiting Pre-trained Models for Chinese Natural Language Processing", which will be published in "Findings of EMNLP". You can read our camera-ready paper through ACL Anthology or arXiv pre-print.

Revisiting Pre-trained Models for Chinese Natural Language Processing
Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Shijin Wang, Guoping Hu

You may also interested in,

• Chinese BERT series: https://github.com/ymcui/Chinese-BERT-wwm
• Chinese ELECTRA: https://github.com/ymcui/Chinese-ELECTRA
• Chinese XLNet: https://github.com/ymcui/Chinese-XLNet
• Knowledge Distillation Toolkit - TextBrewer: https://github.com/airaria/TextBrewer

More resources by HFL: https://github.com/ymcui/HFL-Anthology

Introduction

MacBERT is an improved BERT with novel MLM as correction pre-training task, which mitigates the discrepancy of pre-training and fine-tuning.

Instead of masking with [MASK] token, which never appears in the fine-tuning stage, we propose to use similar words for the masking purpose. A similar word is obtained by using Synonyms toolkit (Wang and Hu, 2017), which is based on word2vec (Mikolov et al., 2013) similarity calculations. If an N-gram is selected to mask, we will find similar words individually. In rare cases, when there is no similar word, we will degrade to use random word replacement.

Here is an example of our pre-training task. |

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