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采用nlp-architect实现rasa-nlu中文意图提取和槽填充

Python 93.47% Perl 6.52% Shell 0.01%
rasa-nlu intent-extraction slot-filling nlp-architect chinese rasa-core policy rasa

rasa-nlp-architect's Introduction

介绍

这个repository主要是实现了intel的nlp-architect的intent和slot的提取,两个model

  • mtl
  • seq2seq

然后配合提供一个rasa-nlu的server,配合rasa-core使用。

Train mtl model

python train_mtl_model.py --dataset_path rasa_data/rasa_nlu_data/ -b 100 -e 10

Train seq2seq model

python train_seq2seq_model.py --dataset_path rasa_data/rasa_nlu_data/ -b 100 -e 10

Interactive

python interactive.py --model_path models/mtl/model.h5 --dataset_path rasa_data/rasa_nlu_data/

or

python interactive.py --model_path models/seq2seq/model.h5 --dataset_path rasa_data/rasa_nlu_data/

Provide a server

python server.py -m models/mtl/model.h5 -i models/mtl/model_info.dat

or

python server.py -m models/seq2seq/model.h5 -i models/seq2seq/model_info.dat

TODO

现阶段Intent只返回了概率最大的,后续需要做intent ranking.

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rasa-nlp-architect's Issues

验证集效果太差

大神你好,按readme中写的步骤训练网络,我发现模型在训练集上逐渐收敛,但在验证集上效果很差,几乎没有任何效果,这可能是什么原因?

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