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The reported matbench result (0.3463) seems a bit more in line with matbench_crabnet.py which uses 300 epochs and the full train/val dataset for training. It's not a huge difference, but I'm trying to figure out if/what the discrepancy is.
Maybe I'm missing something basic. Could you comment on this?
The text was updated successfully, but these errors were encountered:
Also, the CrabNet paper reports an even lower error for the matbench_expt_gap task (0.338 eV) than what's shown in the matbench submission (0.3463 eV). Maybe it is just that I didn't run it for enough epochs. Ran it for 100 epochs and got 0.3485 eV.
@MahamadSalah74 I ran the matbench notebook posted on the matbench GitHub page (materialsproject/matbench#23), and got somewhat higher MAEs for a few repeat runs (see below) compared to what was reported.
The reported matbench result (
0.3463
) seems a bit more in line withmatbench_crabnet.py
which uses 300 epochs and the full train/val dataset for training. It's not a huge difference, but I'm trying to figure out if/what the discrepancy is.Maybe I'm missing something basic. Could you comment on this?
The text was updated successfully, but these errors were encountered: