Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning
使用谷歌的BERT模型在BLSTM-CRF模型上进行预训练用于中文命名实体识别的Tensorflow代码
The Chinese training data($PATH/NERdata/) from:https://github.com/zjy-ucas/ChineseNER
The CoNLL-2003 data($PATH/NERdata/ori/) from:https://github.com/kyzhouhzau/BERT-NER
The evaluation codes come from:https://github.com/guillaumegenthial/tf_metrics/blob/master/tf_metrics/__init__.py
Try to implement NER work based on google's BERT code and BiLSTM-CRF network!
python3 bert_lstm_ner.py \
--task_name="NER" \
--do_train=True \
--do_eval=True \
--do_predict=True
--data_dir=NERdata \
--vocab_file=checkpoint/vocab.txt \
--bert_config_file=checkpoint/bert_config.json \
--init_checkpoint=checkpoint/bert_model.ckpt \
--max_seq_length=128 \
--train_batch_size=32 \
--learning_rate=2e-5 \
--num_train_epochs=3.0 \
--output_dir=./output/result_dir/
####2. replace the BERT path and project path in BERT_NER.py
if os.name == 'nt':
bert_path = '{your BERT model path}'
root_path = '{project path}'
else:
bert_path = '{your BERT model path}'
root_path = '{project path}'
-
The evaluation codes come from:https://github.com/guillaumegenthial/tf_metrics/blob/master/tf_metrics/__init__.py
Any problem please email me([email protected])