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Preserving Generalization of LLMs in Few-shot Continual Relation Extraction (FCRE)

Overview

This repository provides the implementation for "Preserving Generalization of Language Models in Few-shot Continual Relation Extraction." Our approach leverages underutilized language model heads with mutual information maximization to maintain pre-trained knowledge and enhance few-shot continual learning for relation extraction.

Requirements

To run the code, please install the following dependencies:

transformers==4.20.0
wordninja
wandb
scikit-learn
tqdm
numpy==1.23.0
peft
accelerate
sentencepiece
protobuf

Datasets

We perform experiments using two publicly available relation extraction datasets:

  • FewRel: A large-scale few-shot relation extraction dataset.
  • TACRED: A widely-used dataset for relation classification.

Training

BERT-based Models

TACRED

To train BERT models on TACRED with 5-shot settings, follow these steps:

  1. Navigate to the CPL scripts directory:
    cd CPL/bash
  2. Run the 5-shot training script:
    bash tacred_5shot.sh

Alternatively, you can directly run the training script for different components:

  1. For SCKD with Mutual Information Maximization (MMI):

    cd SCKD
    python main-mmi.py --task tacred --shot 5 
  2. For ConPL:

    cd ConPL
    python main.py --task tacred --shot 5  

FewRel

To train BERT models on FewRel with 5-shot settings:

  1. Run the 5-shot script from the CPL directory:

    cd CPL/bash
    bash fewrel_5shot.sh
  2. Alternatively, run the training commands directly:

    • SCKD with MMI:

      cd SCKD
      python main-mmi.py --task fewrel --shot 5 
    • ConPL:

      cd ConPL
      python main.py --task fewrel --shot 5  

LLAMA2-based Models

To train using LLAMA2, ensure that you have set up your Hugging Face token (hf_token) in the required scripts:

  • For ConPL, add the token in main-llm.py and dataprocess.py.
  • For SCKD, add the token in sampler.py, main-llm.py, and main-llm-mmi.py.

TACRED

  1. To run SCKD with MMI:

    cd SCKD
    python main-llm-mmi.py --task tacred --shot 5 
  2. To run ConPL:

    cd ConPL
    python main-llm.py --task tacred --shot 5  

FewRel

  1. To run SCKD with MMI:

    cd SCKD
    python main-llm-mmi.py --task fewrel --shot 5 
  2. To run ConPL:

    cd ConPL
    python main-llm.py --task fewrel --shot 5  

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