Skip to content

Latest commit

 

History

History
28 lines (22 loc) · 712 Bytes

README.md

File metadata and controls

28 lines (22 loc) · 712 Bytes

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