/VQUANDA-Baseline-Models

Sequence to sequence baseline models for VQuAnDa

Primary LanguagePythonMIT LicenseMIT

Baseline models for VQuAnDa

VQuAnDa Repository

Introduction

The repository contains sequence to sequence models for evaluating VQuAnDa.

The models we use are based on:

Experiments

Requirements and Setup

Python version >= 3.7

PyTorch version >= 1.3.0

# first download the dataset
git clone https://github.com/AskNowQA/VQUANDA.git
cd VQUANDA
# inside the dataset download the baseline models
git clone https://github.com/endrikacupaj/VQUANDA-Baseline-Models.git
cd VQUANDA-Baseline-Models
pip install -r requirements.txt

Run models

RNN-1 with Bahdanau attention:

python run.py --model rnn --attention bahdanau
# with covered entities
python run.py --model rnn --attention bahdanau --cover_entities
# query as input
python run.py --model rnn --attention bahdanau --input query
# query as input with covered entities
python run.py --model rnn --attention bahdanau --input query --cover_entities

RNN-2 with Luong attention:

python run.py --model rnn --attention luong
# with covered entities
python run.py --model rnn --attention luong --cover_entities
# query as input
python run.py --model rnn --attention luong --input query
# query as input with covered entities
python run.py --model rnn --attention luong --input query --cover_entities

CNN:

python run.py --model cnn
# with covered entities
python run.py --model cnn --cover_entities
# query as input
python run.py --model cnn --input query
# query as input with covered entities
python run.py --model cnn --input query --cover_entities

Transformer:

python run.py --model transformer
# with covered entities
python run.py --model transformer --cover_entities
# query as input
python run.py --model transformer --input query
# query as input with covered entities
python run.py --model transformer --input query --cover_entities

Results

License

The repository is under MIT License.

References

Links we considered for implementing the baseline models: