MultiWord Expression Detection : MWE detection using transformers based models

Transformers based approach for multiword expressions detection.

Installation

First you need to install PyTorch. The recommended PyTorch version is 1.11.0 Please refer to PyTorch installation page for more details specifically for the platforms.

When PyTorch has been installed, you can install requirements from source by cloning the repository and running:

git clone https://github.com/DamithDR/MultiwordExpressions.git
cd MultiwordExpressions
pip install -r requirements.txt

Experiment Results

You can easily run experiments using following command and altering the parameters as you wish

python -m examples.mwe.en.run --model xlm-roberta-base

To run using docker, you need to have docker installed in your machine. Please use Docker installation Guide to install docker based on your operating system.

Once you successfully installed docker in your system, you can simply use following command to execute the experiments.

docker run damithpremasiri/transformer-based-mwe:V1.0 --model xlm-roberta-base

Parameters

Please find the detailed descriptions of the parameters

--model               : The name of the model you want to experiment with

Model Names supported

xlm-roberta-base
xlnet-base-cased
roberta-base
bert-base-multilingual-cased
bert-base-multilingual-uncased
bert-base-uncased
bert-base-cased
google/electra-base-discriminator