Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)

Chinese NER using Bert

BERT for Chinese NER.

dataset list

1. cner: datasets/cner
2. CLUENER: https://github.com/CLUEbenchmark/CLUENER

model list

1. BERT+Softmax
2. BERT+CRF
3. BERT+Span

requirement

1. 1.1.0 =< PyTorch < 1.5.0
2. cuda=9.0
3. python3.6+

input format

Input format (prefer BIOS tag scheme), with each character its label for one line. Sentences are splited with a null line.

美	B-LOC
国	I-LOC
的	O
华	B-PER
莱	I-PER
士	I-PER

我	O
跟	O
他	O

run the code

1. Modify the configuration information in run_ner_xxx.py or run_ner_xxx.sh .
2. sh scripts/run_ner_xxx.sh

note: file structure of the model

├── prev_trained_model
|  └── bert_base
|  |  └── pytorch_model.bin
|  |  └── config.json
|  |  └── vocab.txt
|  |  └── ......

CLUENER result

The overall performance of BERT on dev:

ALBERT for CLUENER

The overall performance of ALBERT on dev:

Cner result

The overall performance of BERT on dev(test):