中文多分類 BERT

直接把本身的工做文檔導入的，因爲是在外企工做，因此都是英文寫的

Steps:

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

         

   2. add the processor in main function

         

   

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:

      

      

      

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/