Skip to content
three-hierarchy multiclassification for desensitization text, using LSTM model
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.

What's this

This is the code about 种子杯, a small chinese text multi-classification contest

It shows how to build word embedding by gensim and use torchtext to process the data, and, finally training a Attention-Based BLSTM model in pytorch.

project feature

  • around 300 lines
  • only has basic function
  • shared for educational purpose
  • f1_score(...,'macro')==86.42 in semi-final, ranked in the 6th echelone


  1. mainRefer
  2. Attention-Based BLSTM


name means
df pandas.DataFrame

env prerequisite

  • OS: run on windows and linux
  • python 3.*(below are newest in 2018-10)
    • pandas
      • numpy
    • sklearn
    • pytorch(pytorch-cpu allowed)
      • torchtext
    • gensim

data view

dataset location

item_id title_characters title_words description_characters description_words cate1_id cate2_id cate3_id
a38b804b6eb25c6a39eef30e54060ce1 c51,c38,c48,c45,c10,c7,c288,c18,c15,c7,c255,c305,c18,c56,c762,c549,c1051,c18,c1051,c147,c955,c259,c18 w27,w12,w22,w215,w11,w875,w1242,w14391,w4018,w5656 c32,c540,c101,c275,c613,c61,c92,c54,c467,c354,c361,c61,c154,c183,c247,c71,c398,c21,c31,c2,c32,c23,c135,c229,c1175,c61,c76,c23,c135,c982,c71,c2,c1175,c633,c195,c61,c62,c197,c61,c14,c1163,c166,c31 w8,w295,w2132,w13,w86,w1830,w3009,w13,w167,w395,w1499,w4,w7,w8,w87,w3584,w13,w93,w87,w2014,w3843,w13,w111,w13,w14,w2867,w7 2 13 13

*one catej_id corresponding only one catei_id, for j>i*

directory structure

├── data                
│   ├── test_w.tsv      
│   ├── train_w.tsv     
│   ├── val_w.tsv       
│   └── w300.txt        gensim model saved
├──       preprocess data
├── model\              model usaged
├── doc\                context explain and report
├── raw\                here put data provided
├──            support model train
├──             support data process
└── ...                 other files

how to run

generate processed data in data/ (need data in raw/)


suppose you want to save model in abc dir

py abc

finally it will generate predicate txt for raw\test_b.txt

load model and train


change para LAST_EPOCH ; and LOADMODEL to where the model saved

py abc

modify answer manual

use ipython to run

after run

ans = util.get_pred_list(model, test_iter, use_pandas=True)

you will get a df ans

model parameters

name usage
MAX_EPOCH num of train epoch
MAX_SEQ_LEN=200 fixed and max length of word
NUM_LAYER=2 num of recurrent layers, stacking two LSTM together to form a stacked LSTM, with the second LSTM taking in outputs of the first LSTM and computing the final results.
DROPOUT dropout probability of Dropout layer
wei_criterion used to calculate total loss

others refer to

You can’t perform that action at this time.