We performed calculations on two versions of The Materials Project 31 dataset. The first version, is collected for training Mat2Spec model . This dataset contains 38688 structures with a unified energy range between Emin and Emax. The second version, referred to as the MP2022 dataset, was manually collected using the Materials Project API and consist total 126,334 crystals. This dataset contains various quantum-chemically computed properties, including formation energy, band gap, Fermi level energies, bulk moduli, and shear moduli. In addition, eDOS patterns calculated under the same computational conditions and with a single pseudopotential are available for 43,891 bulk structures in MP2022, each with eDOS spectra within different Emin and Emax energy ranges with high resolution 2000 datapoints. Comparing our model with existing ones helps us evaluate how well it captures important input data features and makes accurate predictions.