In this paper, we discussed the basic procedure of uncertain-driven active learning and the details of its implementation in constructing spectroscopically intermolecular PES for the Considering the MLRNet shows lower training w-RMSE in every sampling cycle as well as lower test w-RMSE in the first several cycles, we suggest the MLRNet is still promising in points saving, and the current active learning procedure is not an optimal choice. For the double-precision sampling, the FI-NN only required 613 points and 11 iterations to achieve a test w-RMSE of 0.0710 cm -1 , and is still possible to be more accurate with a smaller stop threshold. The ro-vibrational energy levels of both the single-and double-precision models showed good agreement with the reference PESs. The double-precision FI-NN is much better in the band origin shifts calculations, which means it may still be important to use double-precision sampling when studying the inter-and intra-molecular coupling effects.