Source code for our paper :
Cleaner Pretraining Corpus Curation with Neural Web Scraping
This is a work in progress, so please wait for our incremental improvements 😊
If you find this work useful, please cite our paper and give us a shining star 🌟
1️⃣ Clone from git
git clone https://github.com/OpenMatch/NeuScraper
cd NeuScraper
2️⃣ Data
ClueWeb22 is the newest in the Lemur Project's ClueWeb line of datasets that support research on information retrieval, natural language processing and related human language technologies.
The ClueWeb22 datasets are distributed by Carnegie Mellon University for research purposes only. A dataset may be obtained by signing a data license agreement with Carnegie Mellon University. For details on how to get it, please click the following link:
https://www.lemurproject.org/clueweb22/obtain.php
3️⃣ Environment
Install the torch
first :
pip install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
Install other packages :
pip install -r requirements.txt
1️⃣ Download checkpoint for NeuScraper
git lfs install
git clone https://huggingface.co/OpenMatch/neuscraper-v1-clueweb
2️⃣ Preprocess the test data, we use the en0001-01
as our test set.
python src/build_test.py --path /path/to/clueweb22
3️⃣ Scraping with NeuScraper
bash scripts/inference.sh
4️⃣ Test on en0001-01
python src/eval/run_eval.py
Note: Training NeuScraper from scratch needs to be done on a server equipped with 8 NVIDIA A100-40G GPUs and SSDs
1️⃣ We need to preprocess the pages in Clueweb22:
python src/build_train.py --path /path/to/clueweb22
This command will place the processed data in data/train
.
It need to slice some of them up and put them in data/val
.
2️⃣ Run the following script to start training
bash scripts/train.sh
The training process will run for 30 epochs and take about 40 hours.
Note: CommonCrawl support is still a beta version and it still needs to be more efficient. Besides, neuscraper-v1 only focuses on scraping in English web pages. We are still trying our best to develop the new version, and have opened the MIT license. So if you want to develop a better version, do what you want!
1️⃣ Preprocess the pages in CommonCrawl
python src/warc/build.py --path /path/to/commoncrawl/warc
2️⃣ Scraping by NeuScraper
python scripts/commoncrawl.sh
3️⃣ Get Text
python src/warc/get_text.py
@article{xu2024cleaner,
title={Cleaner Pretraining Corpus Curation with Neural Web Scraping},
author={Xu, Zhipeng and Liu, Zhenghao and Yan, Yukun and Liu, Zhiyuan and Xiong, Chenyan and Yu, Ge},
journal={arXiv preprint arXiv:2402.14652},
year={2024}
}
If you have questions, suggestions, and bug reports, please send a email to us, we will try our best to help you.
xuzhipeng@stumail.neu.edu.cn