Consider submitting to matbench

[sgbaird]

Note: I am unaffiliated with matbench.

https://matbench.materialsproject.org/

Matbench is an ImageNet for materials science; a curated set of 13 supervised, pre-cleaned, ready-to-use ML tasks for benchmarking and fair comparison. The tasks span a wide domain of inorganic materials science applications including electronic, thermodynamic, mechanical, and thermal properties among crystals, 2D materials, disordered metals, and more.

The Matbench python package provides everything needed to use Matbench with your ML algorithm in ~10 lines of code or less.

Feel free to use the CrabNet submission as a rough guide, since CrabNet is also composition-only, though it will need to be adapted to the API of ElemNet. https://github.com/materialsproject/matbench/blob/main/benchmarks/matbench_v0.1_CrabNet/notebook.ipynb