keras

Keras

The directory contains code to run the models with a Keras implementation and a Tensorlow backend. Code for both single and multitask models are given. For single tasks, one model for each of the three tasks will be computed by running the python script main_threeTasks.py. The multitask learning model can be computed with the script main_multiTaskLearning.py.

The data is expected to be in a dataset folder, in the main repository directory, with three files inside it: clean_train.txt for the training dataset, clean_test.txt for the testing dataset, and clean_valid.txt for the validation dataset. Inside the dataset folder, a pretrained_vectors folder is expected, with two files inside it: vecs_100.txt and vecs_300.txt.

The results will be stored into the model_results folder, with one directory created for each model.

python main_threeTasks.py
python main_multiTaskLearning.py

Contents

• README.md this file.
• code/
  • models code to create, train and validated NN models.
  • utils utility functions to run the models.
• main_multiTaskLearning python script to run the multi-task model.
• main_threeTasks python script to train one NN model for each task.

Dependencies

• Keras : version 2.1.1
• TensorFlow: 1.4.0
• Numpy: 1.13.3
• Keras contrib Keras contrib : 0.0.2
• Sklearn : 0.19.1
• Sklearn crfsuite Sklearn crfsuite : 0.3.6
• Python 3.5