hiepnh137/VTCC-NLP-at-SemEval-2023-Task-6

2

stars

18

commits

Python

primary language

Jan 29, 2024

updated

README

VTCC-NLP-at-SemEval-2023-Task-6

This repository contains the source code for VTCC-NLP team's method for SemEval-2023 Task 6 “Rhetorical Roles Prediction”. Our method achieves the top 4 in the public leaderboard of the sub-task B. The model is described in the paper "VTCC-NLP at SemEval-2023 Task 6:Long-Text Representation Based on Graph Neural Network for Rhetorical Roles Prediction".

Install dependencies

  pip install -r requirements.txt

How to run the code

For training, you can run as the follows:

  bash lsp.sh
  bash train.sh

For inference, run this command:

python infer_new_graph.py custom_processed_input.json output_json_path model_path

Contributors

hiepnh137

18 commits

hiepnh137/VTCC-NLP-at-SemEval-2023-Task-6

2

stars

18

commits

Python

primary language

Jan 29, 2024

updated

README

VTCC-NLP-at-SemEval-2023-Task-6

This repository contains the source code for VTCC-NLP team's method for SemEval-2023 Task 6 “Rhetorical Roles Prediction”. Our method achieves the top 4 in the public leaderboard of the sub-task B. The model is described in the paper "VTCC-NLP at SemEval-2023 Task 6:Long-Text Representation Based on Graph Neural Network for Rhetorical Roles Prediction".

Install dependencies

  pip install -r requirements.txt

How to run the code

For training, you can run as the follows:

  bash lsp.sh
  bash train.sh

For inference, run this command:

python infer_new_graph.py custom_processed_input.json output_json_path model_path

Contributors

hiepnh137

18 commits

Languages

Python

92.4%

Jupyter Notebook

7.5%