Instead, we selected 256 data points from both the left and right sides of the eDOS spectrum centered around 0 energy value, and tried to predict normalised values, Fermi level energies and band gap values. Thus, we combined these tasks into one and trained final model using the MP2022 data set. To incorporate these adjustments, we made changes to the architecture of the model, introducing an additional branch to the basic model. This branch included an input layer that corresponds to the energies from the reference dataset, along with a dense layer. The output from this branch was then concatenated with the output from the PDF-LSTM branchs. Subsequently, the output from the concatenated layer is passed through the LSTM and the output layers. Compiled models were trained with 256 epochs. The predictions obtained from these modifications are presented in Figure .