ernie-csc's Introduction

ERNIE for Chinese Spelling Correction

简介

本文主要用PyTorch实现了百度在ACL 2021上提出结合拼音特征的Softmask策略的中文错别字纠错的下游任务网络，并提供预训练模型，模型结构如下：

"Correcting Chinese Spelling Errors with Phonetic Pre-training"非官方实现。

注：论文中暂未开源融合字音特征的预训练模型参数(即MLM-phonetics)，所以本文提供的纠错模型是在ERNIE-1.0的参数上进行Finetune，纠错模型结构与论文保持一致。

训练数据

该模型在SIGHAN简体版数据集以及Automatic Corpus Generation生成的中文纠错数据集上进行Finetune训练。本仓库已经把原始的语料进行处理，即可以直接用本仓库提供的语料进行训练。

单卡训练

python main.py --batch_size 32 --logging_steps 100 --epochs 10 --learning_rate 5e-5  --max_seq_length 192

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