The deep Wannier model utilizes the DeepPot-Se model, which incorporates all two-atom information . The cut-off radius is set to 6.0 Å, consistent with the potential energy model , and smoothing commences at 0.5 Å. To account for all neighboring atoms, the maximum possible number of neighbors is set to 100 for oxygen atoms and 200 for hydrogen atoms, which are deemed sufficient for encompassing the complete local environment. Regarding the neural network architecture, the embedding network consists of three layers with 25, 50, and 100 neurons, respectively. For the fitting network, a three-layer architecture with 100 neurons in each layer is employed.