About hyper-parameters

[fukuzawa-e]

python run_zerogen.py --alpha ${ALPHA} --beta ${BETA} --eta ${ETA} --k ${K} --condition_method add
--task ${TASK} --decoding_len ${LENGTH} --alpha_scale --alpha_activasize ${ALPHA_HAT}
--beta_scale --beta_activesize 0.2 --beta_upper ${BETA_HAT} --n_obj ${N} --kw_mode max --k2t

By the above command, I want to test making long output, for example more than 100 words. I changed --decoding_len by 100, but the length of the results is not changed so different, the results are still short.
Thus, I tried to only set --decoding_len by 100, and the longer results can be output, but quality of the result text is not so good.
I want to confirm effective of each parameter, but there are no details in the paper, is there any documents that can explain mean of each parameter ?

[ImKeTT]

Thank you for your interest in our work.
For generating high-quality long controllable texts, you need to fine-tune the base LM on textual corpus with longer length rather than simply twiching the decoding_len parameter.

[fukuzawa-e]

Thank you so much for your reply.
About fine-tune the base LM, do you use SimCTG for fine-tuning new LM model ?

[ImKeTT]

Yes, I employed this codebase for fine-tuning the base LM.