https://github.com/poteminr/ada-binder
Adaptive BI-encoder for Named Entity Recognition
https://github.com/poteminr/ada-binder
Last synced: 4 months ago
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Adaptive BI-encoder for Named Entity Recognition
- Host: GitHub
- URL: https://github.com/poteminr/ada-binder
- Owner: poteminr
- License: mit
- Created: 2024-03-29T12:44:36.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-06-05T11:07:41.000Z (about 1 year ago)
- Last Synced: 2024-12-29T07:17:11.098Z (6 months ago)
- Language: Python
- Size: 50.8 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Adaptive Bi-Encoder for Named Entity Recognition via Contrastive Learning
## Introduction
This is the repository for **ada-binder** - extended version of [**microsoft/binder**](https://openreview.net/forum?id=9EAQVEINuum).
## Reference
Check out [original microsoft/binder paper](https://openreview.net/forum?id=9EAQVEINuum) for the details.
[Original microsoft/binder repository](https://github.com/microsoft/binder)
```bib
@article{zhang-etal-2022-binder,
title={Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learning},
author={Zhang, Sheng and Cheng, Hao and Gao, Jianfeng and Poon, Hoifung},
journal={arXiv preprint arXiv:2208.14565},
year={2022}
}
```
## Quick Start
### 1. Data Preparation
Follow the instructions [README.md](https://github.com/microsoft/binder/blob/main/data_preproc/README.md) in the data_preproc folder of original repository [microsoft/binder](https://github.com/microsoft/binder).
### 2. Environment Setup
```bash
conda create -n binder -y python=3.9
conda activate binder
conda install pytorch==1.13 pytorch-cuda=11.6 -c pytorch -c nvidia
pip install transformers==4.24.0 datasets==2.6.1 wandb==0.13.5 seqeval==1.2.2
```
### 3. Experiment Run
Assuming you have prepared data for [Nerel-BIO](https://github.com/nerel-ds/NEREL-BIO/tree/master) and finished environment setup, below is the command to run an experiment:
```bash
python run_ner.py conf/nerel-bio.json
```
To run experiments on other datasets, simply change the config.