siat-nlp/IPRLS

Code and data for the SIGIR'2021 paper "Iterative Network Pruning with Uncertainty Regularization for Lifelong Sentiment Classification"

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README

IPRLS code for Iterative Pruning with Regularization for Lifelong Sentiment Classification

requirements

Python >=3.7
Pytorch 1.2.0
transformers

bert-base-uncased version BERT model need to be download from https://huggingface.co/bert-base-uncased , set it under path BERT/

You can run IPRLS with

$ bash experiment/run_IPRLS.sh

After completing the above process, you need to run following bash to obtain final results

$ bash experiment/eval_middle_results.sh

Run IPRLS with random task order

$ bash experiment/run_with_random_task_order.sh

To evaluate shuffle order results

$ bash experiment/eval_shuffle_middle_results.sh

Contributors

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