cnn-text-classification

An example of text classification using CNN

To use you must download the MR polarity dataset and put it in the path specified in the mr-dataset-path The dataset can be obtained here: https://github.com/yoonkim/CNN_sentence. The two files rt-polarity.neg and rt-polarity.pos must be put in a directory. For example, data/mr-data/rt-polarity.neg.

You also must download the glove word embeddings. The suggested one to use is the smaller 50 dimension one glove.6B.50d.txt which is contained in the download file here https://nlp.stanford.edu/projects/glove/

Usage

You can run through the repl with (train-convnet {:embedding-size 50 :batch-size 100 :test-size 100 :num-epoch 10 :max-examples 1000})

or JVM_OPTS="Xmx1g" lein run (cpu)

You can control the devices you run on by doing:

lein run :cpu 2 - This will run on 2 cpu devices lein run :gpu 1 - This will run on 1 gpu device lein run :gpu 2 - This will run on 2 gpu devices

The max-examples only loads 1000 each of the dataset to keep the time and memory down. To run all the examples, change the main to be (train-convnet {:embedding-size 50 :batch-size 100 :test-size 1000 :num-epoch 10)

and then run

• lein uberjar
• java -Xms1024m -Xmx2048m -jar target/cnn-text-classification-0.1.0-SNAPSHOT-standalone.jar