AMP: Adversarial Mixing Policy for Relaxing Locally Linear Constraints in Mixup
This is the code for the paper "Adversarial Mixing Policy for Relaxing Locally Linear Constraints in Mixup" accepted at EMNLP'21
Install requirements
pip install -r requeriments.txt
Preparing data sets
Download link and unzip all the datasets into data fold.
Download pre-trained bert model and Glove embeddings
Create fold bert-base-uncased and enter the fold. Download
pytorch_model.bin
config.json
vocab.txt
Enter the project root directory. Download GloVe embeddings glove.840B.300d.zip from link
Run
Detailed descriptions of arguments are provided in run_main.py
. For run the default parameters,
python run_main.py
License
MIT License