saiwaiyanyu / Bi Lstm Crf Ner Tf2.0
Named Entity Recognition (NER) task using Bi-LSTM-CRF model implemented in Tensorflow 2.0(tensorflow2.0 +)
Stars: ✭ 93
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bi-lstm-crf-ner-tf2.0
Named Entity Recognition (NER) task using Bi-LSTM-CRF model implemented in Tensorflow2.0.
Requirements
- python >3.6
- tensorflow==2.0.0
- tensorflow-addons==0.6.0
data
data example
１ B-TIME
９ I-TIME
９ I-TIME
７ I-TIME
年 E-TIME
， O
是 O
中 B-LOC
国 E-LOC
发 O
展 O
历 O
史 O
上 O
非 O
常 O
重 O
要 O
的 O
很 O
不 O
平 O
凡 O
的 O
一 O
年 O
。 O
end
Usage
train
$ # pip install requirement.txt
$ python3 train.py
...
[-INFO-] 2019-12-05 21:11:15,037 24300 epoch 1, step 575, loss 5.0533 , accuracy --
[-INFO-] 2019-12-05 21:11:34,002 24300 epoch 1, step 576, loss 6.2023 , accuracy --
[-INFO-] 2019-12-05 21:11:52,543 24300 epoch 1, step 577, loss 4.3899 , accuracy --
[-INFO-] 2019-12-05 21:12:11,175 24300 epoch 1, step 578, loss 3.1313 , accuracy --
[-INFO-] 2019-12-05 21:12:29,661 24300 epoch 1, step 579, loss 6.4625 , accuracy --
[-INFO-] 2019-12-05 21:12:48,233 24300 epoch 1, step 580, loss 5.5159 , accuracy --
[-INFO-] 2019-12-05 21:12:48,325 24300 model saved
...
predict
$ python3 predict.py
input: 中共中央总书记、国家主席江泽民发表１９９８年新年讲话
[
{
"end": 4,
"words": "中共中央",
"type": "ORG",
"begin": 1
},
{
"end": 15,
"words": "江泽民",
"type": "PER",
"begin": 13
},
{
"end": 22,
"words": "１９９８年",
"type": "TIME",
"begin": 18
}
]
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