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Ralph Tang
7957dc7638
* Tweak conv-rnn model - Fix misplaced zero_grad() - Tweak model hyperparams and optimization algorithm * Fix typo * Add new results * Clean up extraneous code
Convolutional RNN
Implementation based on [1].
Usage
Run ./getData.sh to fetch the data. The project structure should now look like this:
├── conv_rnn/
│ ├── data/
│ ├── saves/
│ └── *.*
You may then run python train.py and python test.py for training and testing, respectively. For more options, add the -h switch.
Empirical results
| Best dev | Test |
|---|---|
| 52.04359673024523 | 50.85972850678733 |
References
[1] Chenglong Wang, Feijun Jiang, and Hongxia Yang. 2017. A Hybrid Framework for Text Modeling with Convolutional RNN. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '17).