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The PyTorch Implementation Of SummaRuNNer

License

Models

  1. RNN_RNN
  1. CNN_RNN
  1. Hierarchical Attention Networks

Setup

Requires pipenv. Use pip install pipenv if not installed.

pipenv install
pipenv shell

Usage

# train
python main.py -device 0 -batch_size 32 -model RNN_RNN -seed 1 -save_dir checkpoints/XXX.pt
# test
python main.py -device 0 -batch_size 1 -test -load_dir checkpoints/XXX.pt

pretrained models

  1. RNN_RNN(checkpoints/RNN_RNN_seed_1.pt)
  2. CNN_RNN(checkpoints/CNN_RNN_seed_1.pt)
  3. AttnRNN(checkpoints/AttnRNN_seed_1.pt)

Result

DailyMail(75 bytes)

model ROUGE-1 ROUGE-2 ROUGE-L
SummaRNNer(Nallapati) 26.2 10.8 14.4
RNN-RNN 26.0 11.5 13.8
CNN-RNN 25.8 11.3 13.8
Hierarchical Attn Net 26.0 11.4 13.8

Blog

Download Data:

Evaluation

Acknowledge

  • Thanks for @AlJohri's contribution

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The PyTorch Implementation of SummaRuNNer

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  • Jupyter Notebook 94.7%
  • Python 5.3%