Nlp Course 2nd Project

Second homework of the NLP course at Sapienza University of Rome (course info).

GitHub Repo

• Prof: Roberto Navigli)
• Teaching assistants: Cesare Campagnano and Pere-Lluís Huguet Cabot

Requirements

• Ubuntu distribution 19.10 or the current LTS are perfectly fine.
• conda, a package and environment management system particularly used for Python in the ML community

Setup Environment

1. Install Docker
2. Setup a client
3. Download glove.6B.50d.txt embeddings from this page and put it inside model/embeddings

For those interested, test.sh essentially setups a server exposing your model through a REST Api and then queries this server, evaluating your model.

Install Docker

curl -fsSL get.docker.com -o get-docker.sh
sudo sh get-docker.sh
rm get-docker.sh
sudo usermod -aG docker $USER

Logout and re-login (important); then:

newgrp docker
sudo service docker restart

Setup Client

Your model will be exposed through a REST server. In order to call it, we need a client. The client has already been written (the evaluation script) but it needs some dependecies to run. We will be using conda to create the environment for this client.

conda create -n nlp2021-hw1 python=3.7
conda activate nlp2021-hw1
pip install -r requirements.txt

Run

test.sh is a simple bash script. To run it:

conda activate nlp2021-hw1
bash test.sh data/dev.jsonl

Actually, you can replace data/dev.jsonl to point to a different file, as far as the target file has the same format.

If you hadn’t changed hw1/stud/model.py yet when you run test.sh, the scores you just saw describe how a random baseline.