some descriptions in ReadMe not clear about actune HOT 3 OPEN

Thanks for reaching out.

For question #1, run_agnews.sh is used as our main method (active self-training). We will modify the README to avoid confusion.

For question #2, pool is the size of unlabeled data used in self-training. In self-training, we often do not use the whole unlabeled data as many pseudo-labels may contain noise. A common solution is to first select a subset of data with low uncertainty (pool is the size for such a subset), and fine-tune the pretrained language model on the subset (together with the labeled data) only. Hope these explanations help.

Best,
Yue

from actune.

so how you config this number with different datasets. What is the value of this number if I test your with TREC?

from actune.

Overall we tune this parameter based on the performance of the validation set.
If there is no validation set, we recommend gradually (linearly) increasing the number of unlabeled examples to around 50% of the size of the unlabeled pool.

from actune.