adversarial_training
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Pytorch implementation of the methods proposed in **Adversarial Training Methods for Semi-Supervised Text Classification** on IMDB dataset
Adversarial Training
Pytorch implementation of Adversarial Training Methods for Semi-Supervised Text Classification (sentiment analysis on IMDB dataset, only adversarial training done).
Based on
- Paper Adversarial training methods for semi-supervised text classification, ICLR 2017, Miyato T., Dai A., Goodfellow I. Only adversarial training has been implemented.
- Github repository Adversarial Training Methods. This is another implementation using tensorflow.
Requirements
This repository has been tested under python 3.6 and Pytorch 0.4.1 with GPU.
Usage
- Download preprocessed IMDB dataset for this repository (you can also find the URL in imdb/google_drive.txt). And then uncompressing these files into directory imdb. Of course, you can try to generate these files under the guidance of Adversarial Training Methods.
- Run the main function in at_pytorch/run.py:
$ cd ./at_pytorch
$ python3 run.py
Results
The running result can be seen in file at_pytorch/standard_result.txt, and brief description is as following:
Method | Seq. Length | Epochs | Accuracy |
---|---|---|---|
baseline | 400 | 10 | 0.854 |
adversarial | 400 | 10 | 0.871 |
We have not got the results reported by the original paper, but our result shows the effectiveness of adversarial training.