Tensorflow implementation of Semi-supervised Sequence Learning (https://arxiv.org/abs/1511.01432)

Related tags

Deep Learning text-classification transfer-learning semi-supervised auto-encoder langauge-model
Overview

Transfer Learning for Text Classification with Tensorflow

Tensorflow implementation of Semi-supervised Sequence Learning(https://arxiv.org/abs/1511.01432).

Auto-encoder or language model is used as a pre-trained model to initialize LSTM text classification model.

  • SA-LSTM: Use auto-encoder as a pre-trained model.
  • LM-LSTM: Use language model as a pre-trained model.

Requirements

  • Python 3
  • Tensorflow
  • pip install -r requirements.txt

Usage

DBpedia dataset is used for pre-training and training.

Pre-train auto encoder or language model

$ python pre_train.py --model="<MODEL>"

(<Model>: auto_encoder | language_model)

Train LSTM text classification model

$ python train.py --pre_trained="<MODEL>"

(<Model>: none | auto_encoder | language_model)

Experimental Results

  • Orange lines: LSTM
  • Blue lines: SA-LSTM
  • Red lines: LM-LSTM

Loss

Accuracy

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Comments
  • CVE-2007-4559 Patch

    CVE-2007-4559 Patch

    Patching CVE-2007-4559

    Hi, we are security researchers from the Advanced Research Center at Trellix. We have began a campaign to patch a widespread bug named CVE-2007-4559. CVE-2007-4559 is a 15 year old bug in the Python tarfile package. By using extract() or extractall() on a tarfile object without sanitizing input, a maliciously crafted .tar file could perform a directory path traversal attack. We found at least one unsantized extractall() in your codebase and are providing a patch for you via pull request. The patch essentially checks to see if all tarfile members will be extracted safely and throws an exception otherwise. We encourage you to use this patch or your own solution to secure against CVE-2007-4559. Further technical information about the vulnerability can be found in this blog.

    If you have further questions you may contact us through this projects lead researcher Kasimir Schulz.

    opened by TrellixVulnTeam 0
  • Encoder and Decoder RNN

    Encoder and Decoder RNN

    The paper - Semi-supervised Sequence Learning(https://arxiv.org/abs/1511.01432) - states that for training of SA-LSTM, they used the same LSTM for both encoding and for decoding. However, this implementation uses 2 LSTMs - encoder_cell, and decoder_cell. Could you please clarify.

    Thanks, Shishir

    opened by ShishirPatil 1
Owner
DONGJUN LEE
DONGJUN LEE
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