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[NAACL 2022] This is the code repo for our paper `ACTUNE: Uncertainty-based Active Self-Training for Active Fine-Tuning of Pretrained Language Models'.

Python 73.44% Shell 26.56%

active-learning uncertainty weak-supervision weakly-supervised-learning semi-supervised-active-learning bert-fine-tuning label-efficient

actune's Issues

some descriptions in ReadMe not clear

Hi, Yu, I don't understand some descriptions in this project ReadMe.

In https://github.com/yueyu1030/actune#training

Take AG News dataset as an example, run_agnews_finetune.sh is used for running the experiment of standard active learning approaches, and run_agnews_finetune.sh is used for running active self-training experiments as unlabeled data is also used during fine-tuning.

You use the same file name run_agnews_finetune.sh twice. Which one is your paper's method?

In https://github.com/yueyu1030/actune#hyperparameter-tuning
pool stands for what?

Thank you!

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