yuhaofanuzh/mt-exercise-4

MT Exercise 4: Layer Normalization for Transformer Models

This repo is a collection of scripts showing how to install JoeyNMT, download data and train & evaluate models, as well as the necessary data for training your own model

Requirements

• This only works on a Unix-like system, with bash.

• Python 3.10 must be installed on your system, i.e. the command python3 must be available

• Make sure virtualenv is installed on your system. To install, e.g.

  pip install virtualenv

Steps

Clone this repository or your fork thereof in the desired place:

git clone https://github.com/yuhaofanUZH/mt-exercise-4

Create a new virtualenv that uses Python 3. Please make sure to run this command outside of any virtual Python environment:

./scripts/make_virtualenv.sh

Important: Then activate the env by executing the source command that is output by the shell script above.

Make sure to install the exact software versions specified in the the exercise sheet before continuing.

Download Moses for post-processing:

./scripts/download_moses.sh

In your current venv, clone the joeynmt directory

git clone https://github.com/yuhaofanUZH/joeynmt

Change directory

cd joeynmt

Install JoeyNMT in editable mode

pip install -e .

Then navigate back to mt-exercise-4 directory!

cd your_path/mt-exercise-4

And train two models:

./scripts/train.sh deen_transformer_pre_norm
./scripts/train.sh deen_transformer_post_norm

log the perplexity of the model and visualize it:

python3 log_ppl.py
python3 plot.py

The training process can be interrupted at any time, and the best checkpoint will always be saved. It is also possible to continue training from there later on.