Since tmQM provides a large and diverse collection of complexes, its structures and geometries were used as a basis for tmQM wB97MV. To investigate the impact of the choice of DFT functional and basis set on ML model performance, and to see if we could address the subset of structures whose energies were consistently underpredicted, the energies of the structures in tmQM were recomputed at the ωB97M-V/def2-SVPD level of theory using the Q-Chem electronic structure software 27 via a high-throughput workflow framework previously reported. In contrast with the TPSSh/def2-SVP level of theory used for tmQM, tmQM wB97MV's addition of diffuse functions and the use of a more modern and consistently high-performing functional should improve energy predictions. Despite this increase in quality and cost, only three structures (CSD's PIFFEP, NASBOA, and LIKBIS) had to be removed due to non convergence of the DFT code (thanks in large part to the use of on-the-fly error handlers ). All of tmQM wB97MV's structures can be found in an ASE database linked in the supporting code. While tmQM does include a number of material properties besides the energies, such as the HOMO and LUMO energies, HOMO/LUMO gap, dipole moment, metal natural charge, and polarizability, since we are interested in catalysis applications and our models are thus designed to take in only the 3D structure of the complexes and output only the corresponding energy, we only recompute and include the energy in tmQM wB97MV. Some additional preprocessing was done before finalizing the dataset used for training. Since all of the complexes were single-metal, the structures' coordinates were translated such that the metal was at the origin. In addition to this, some structures in the CSD, which were used in tmQM, use implicit hydrogens on some or all of the ligands in the geometry data file presented. This propagated into tmQM, which led to some anomalous structures. 155 such geometries were removed, found by inspecting structures that either lacked hydrogens completely or had a carbon with only one other atom within a three angstrom radius (which was used as a heuristic to find ligands missing hydrogens). An ASE database of these structures is uploaded with the code. We note that additional erroneous structures may remain in the dataset. It is difficult to deterministically assess if a structure is invalid, an issue that is compounded by the fact that geometry optimizations conducted with missing hydrogens can lead to structures different from their original representations. Despite this, the energies reported are for the xTB optimized geometries, so besides those data points with erroneous structures carrying little physical meaning, they are not a mismatch between structure and energy, merely a high-energy structure and corresponding DFT energy.