D-RNN

RNN model incorporating Development process

1. Dataset

This dataset contains movie reviews along with their associated binary sentiment polarity labels.

1.1 Data organization

The dataset contains 50,000 reviews split evenly into 25000 train and 25000 test sets. Dataset also include an additional 50,000 unlabeled documents for unsupervised learning.

1.2 Download

http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz

1.3 Publications Using the Dataset

http://ai.stanford.edu/~amaas/papers/wvSent_acl2011.pdf

2. Training

2.1 Using Tensorboard

./tbrun.sh

This shell script do things below.

1. Check if Tensorboard is running in the background.
2. If there is no running Tensorboard process, make Tensorboard run and disown it.
3. Runs python triain.py in the background, and disown it.

2.2 Without Tensorboard

python train.py

2.3 Running Tensorboard without Training

./tbrun.sh no