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yh 9529f89abd | 5 years ago | |
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model | 5 years ago | |
README.md | 5 years ago | |
__init__.py | 5 years ago | |
train_bert.py | 5 years ago | |
train_cnn_lstm_crf_conll2003.py | 5 years ago | |
train_idcnn.py | 5 years ago | |
train_ontonote.py | 5 years ago |
这里使用fastNLP复现经典的BiLSTM-CNN的NER任务的模型,旨在达到与论文中相符的性能。
论文链接Named Entity Recognition with Bidirectional LSTM-CNNs
使用fastNLP复现的结果vs论文汇报结果(/前为fastNLP实现,后面为论文报道)
model name | Conll2003 | Ontonotes |
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BiLSTM-CNN | 91.17/90.91 | 86.47/86.35 |
一款轻量级的自然语言处理(NLP)工具包,目标是减少用户项目中的工程型代码,例如数据处理循环、训练循环、多卡运行等
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