https://github.com/chaoscodes/untl
EMNLP'2022: Unsupervised Non-transferable Text Classification
Science Score: 10.0%
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Low similarity (6.4%) to scientific vocabulary
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Repository
EMNLP'2022: Unsupervised Non-transferable Text Classification
Basic Info
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Metadata Files
README.md
Unsupervised-Non-transferable-Text-Classification
This repository is for our EMNLP' 22 paper:
Unsupervised Non-transferable Text Classification ArXiv
Overview
We propose a novel unsupervised non-transferable learning method for the text classification task that does not require annotated target domain data. We further introduce a secret key component in our approach for recovering the access to the target domain, where we design both an explicit (prompt secret key) and an implicit method (adapter secret key) for doing so.
Install dependencies
Run the following scripts to install the dependencies.
shell
pip install -r requirements.txt
Training
Create a directory outputs for storing the checkpoints by:
shell
mkdir outputs
Run the scripts to train the UNTL model.
shell
python UNTL.py
As for the secret key based methods, run the following scripts to train the models
- Train the prompt secret key based model
sh
python UNTL_with_prefix.py
- Train the adapter secret key based model
sh
python UNTL_with_adapter.py
Evaluatoin
After finishing training, run the following scripts for evaluating the model.
- Evaluate the UNTL model
shell
python predict.py
- Evaluate the prompt secret key based model
sh
python predict_prefix.py
- Evaluate the adapter secret key based model
shell
python predict_adapter.py
Reference
@inproceedings{zeng2022unsupervised,
author = {Guangtao Zeng and Wei Lu},
title = {Unsupervised Non-transferable Text Classification},
booktitle = {Proceedings of EMNLP},
year = {2022}
}
Owner
- Login: ChaosCodes
- Kind: user
- Repositories: 23
- Profile: https://github.com/ChaosCodes
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