the reproduction code of the paper "Learning to Extract Attribute Value from Product via Question Answering: A Multi-task Approach"
Use the following command to run the train.py or test.py
python train.py --device=cuda
The model would run in 1 GPU in defualt, to change the setting, change the number in find_gpus in train.py and test.py
Put the aepub dataset in the ./dataset folder as an txt file (./dataset/publish_data.txt), and the processed dataset would be save to './dataset/aePub'
Use the ae_pub.py to generate and preprocess the dataset.
Modify the config.json to set the parameter and the dataset path.
The training.py would automatically go through the training and testing pipeline and generate the training and testing dataset
After training, the training accuracy would be stored in the training_metric.json at the root directory.
Python 3.7
scikit-learn
torch 1.11.0
transformer 4.18.0
You may find other packages in the requirement.txt and requirement_conda.txt for pip and conda environment.