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Pytorch: Bi-LSTM Sequence-Labeling

Introduction

A simple sequence labeling with bi-lstm.
ATIS data is used and included.

Requirement

- Python 3.5+
- Pytorch 0.3+
- pytorchnlp

Tricks Included

- glove embedding
- mini-batch
- learning rate decay
- grad clip
- dropout
- sgd & adam

Usage

Train and run the model in the project dir.
python3 postagger.py  --train_and_test --train_path ./data/atis_train --dev_path ./data/atis_dev --test_path ./data/atis.test.txt --label_set_path ./data/atis_slot_names.txt --model ./model/ --output ./result/result.txt --script ./eval/conlleval.pl --gpu 0  --load_data_type conll