直接把自己的工作文档导入的,由于是在外企工作,所以都是英文写的

  1. git clone https://github.com/google-research/bert
  2. prepare data, download pre-trained models
  3. modify code in run_classifier.py
    1. add a new processor

      中文多分类 BERT

         

    2. add the processor in main function

         

      中文多分类 BERT

   

Train and predict

  1. train

    python run_classifier.py \

    --task_name=multiclass \

    --do_train=true \

    --do_eval=true \

    --data_dir=/home/wxl/bertProject/bertTextClassification/data\

    --vocab_file=/home/wxl/bertProject/chinese_L-12_H-768_A-12/vocab.txt \

    --bert_config_file=/home/wxl/bertProject/chinese_L-12_H-768_A-12/bert_config.json \

    --init_checkpoint=/home/wxl/bertProject/chinese_L-12_H-768_A-12/bert_model.ckpt \

    --max_seq_length=128 \

    --train_batch_size=16 \

    --learning_rate=2e-5 \

    --num_train_epochs=100.0 \

    --output_dir=/home/wxl/bertProject/bertTextClassification/outputThree/

       

    you would get the following result if success:

    中文多分类 BERT

       

       

       

  2. predict

    python run_classifier.py \

    --task_name=multiclass \

    --do_predict=true \

    --data_dir=/home/wxl/bertProject/bertTextClassification/data\

    --vocab_file=/home/wxl/bertProject/chinese_L-12_H-768_A-12/vocab.txt \

    --bert_config_file=/home/wxl/bertProject/chinese_L-12_H-768_A-12/bert_config.json \

    --init_checkpoint=/home/wxl/bertProject/bertTextClassification/outputThreeV1 \

    --max_seq_length=128 \

    --output_dir=/home/wxl/bertProject/bertTextClassification/mulitiPredictThreeV1/

       

   

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