smilelab-fl / fedvocab

Code for paper "Federated Model Decomposition with Private Vocabulary for Text Classification"

FedeVocab

Code for paper "Federated Model Decomposition with Private Vocabulary for Text Classification". In this paper, we propose a fedrated model decomposition method that protects the privacy of vocabularies, shorted as FedeVocab.

Installation

Directory Structure

Before using our code, we recommend running FedeVocab according to the following directory structure:

├── workspace  
│   └── data   
|   |   └── fednlp_data  
│   ├── pretrain
│   │   └── cv  
│   ├── output  
│   └── code  
│       └── fedevocab

You can run the following command:

mkdir workspace  
cd workspace  
mkdir data  
mkdir code  
mkdir pretrained  
cd pretrained  
mkdir nlp  
cd ..  
cd code  

Requirement

The python version of the running environment is 3.7+ and the pytorch version is 1.10+.

git clone 
cd fedevocab  
pip install -r resquirements.txt  

How to run FedeVocab

Our code is built on FedNLP. To use our code, you must clone FedNLP.

Utility Experiments

bash run/detlm_alone/fedrun_sweep.sh sst_2 distilbert v100 2

Privacy Experiments

bash run/attack/dlg.sh /workspace {save_times} {model_type} {gpu_id} {batch_size}

Licence

Apache 2.0