nontree-arg-mining

Implementation of the argument mining system from Towards Better Non-Tree Argument Mining: Proposition-Level Biaffine Parsing with Task-Specific Parameterization.

Code heavy inspired by the SuPar repository.

Setup

Please install libraries in the requirements.txt file using the following command:

pip install -r requirements.txt

Use of virtual environments is optional but recommended. For GPU support refer to the comments in the requirements.txt file.

After installing the libraries from the requirements.txt file also run the following command to install the correct spacy pipeline:

python3 -m spacy download en_core_web_sm

Then change the PATH_TO_DATASET variable in the run.py file to the directory containing the CDCP dataset with transitive closure performed. This dataset is also available here.

Running the model

Please run the following command for information on the command line arguments:

python3 run.py -h

An example command for a training run using the validation set:

python3 run.py --epochs 50 --lr 12e-4 --elmo_embedding --glove_embedding --device 0 --save_dir ./morio-model-runs/ -train

An example command for evaluating on the test set:

python3 run.py --cpu --checkpoint_path ./morio-model-runs/example.pt -test

Repo structure

The model.py file contains all the PyTorch modules needed to construct the model while the run.py file consists of methods for loading, training, and evaluating, all orchestrated in main().

Issues

For any issues or comments please feel free to contact Ting Chen

Notes

• If you run into a 500 error from huggingface just wait a couple minutes and rerun it