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dmn-pytorch's Introduction

Dynamic Memory Networks (PyTorch)

PyTorch implementation of the paper,

Ask Me Anything: Dynamic Memory Networks for Natural Language Processing
Kumar et al., 2016 arxiv

Requirements

Datasets

  • bAQbI Tasks v1.2 data downloaded from here
  • Place files in en-valid-10k under (home)/datasets/babi/en directory.
  • Place a pretrained GloVe under (home)/datasets/glove directory.
# Preprocessing dataset. This will create ./data/babi(tmp).pkl
$ python dataset.py

Run experiments

# Train and test with default settings
$ python main.py

# Train with different number of hidden units, epochs, and QA sets
$ python main.py --s_rnn_hdim 200 --epoch 20 --set_num 5

Model Overview

Dynamic Memory Networks

Experimental Results (bAbI)

Task Accuracy Task Accuracy
1 100% 11 100%
2 99.51% 12 100%
3 88.28% 13 95.21%
4 100% 14 100%
5 99.51% 15 100%
6 99.51% 16 100%
7 98.93% 17 57.13%
8 95.41% 18 99.41%
9 99.90% 19 82.52%
10 99.90% 20 100 %
Mean 95.76%

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