Dice Loss for NLP Tasks with python
Dice Loss for NLP Tasks
This repository contains code for Dice Loss for Data-imbalanced NLP Tasks at ACL2020.
Setup
- Install Package Dependencies
The code was tested in Python 3.6.9+ and Pytorch 1.7.1. If you are working on ubuntu GPU machine with CUDA 10.1, please run the following command to setup environment.
$ virtualenv -p /usr/bin/python3.6 venv
$ source venv/bin/activate
$ pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
$ pip install -r requirements.txt
- Download BERT Model Checkpoints
Before running the repo you must download the BERT-Base and BERT-Large checkpoints from here and unzip it to some directory $BERT_DIR. Then convert original TensorFlow checkpoints for BERT to a PyTorch saved file by running bash scripts/prepare_ckpt.sh .
Apply Dice-Loss to NLP Tasks
In this repository, we apply