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MEGNet-Eform-MP-2018.6.1
materialyze/MEGNet-Eform-MP-2018.6.1
MEGNet-Eform-MP-2018.6.1 is a machine learning model from materialyze. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for matgl.
This model is a MEGNet formation energy model for 89 elements of the periodic table. It contains the formation energy for most materials. This is essentially a retrained version of the MEGNet formation energy model or…
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Updated May 6, 2026
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At a glance
- Library
- matgl
- Access
- Public
- Created
- May 6, 2026
- Updated
- May 6, 2026
- SHA
- 10c13f7e
Model card
From the Hugging Face model README
Aim
This model is a MEGNet formation energy model for 89 elements of the periodic table. It contains the formation energy for most materials. This is essentially a retrained version of the MEGNet formation energy model originally implemented in tensorflow.
Training dataset
MP-2018.6.1: Materials Project formation energy as of 2018.6.1.
- Training set size: : 62315
- Validation set size: 3461
- Test set size: 3463
Performance metrics
MAE of formation energy in eV/atom.
- Training: 0.010 eV/atom
- Validation: 0.029 eV/atom
- Test: 0.028 eV/atom
References
Chen, C.; Ye, W.; Zuo, Y.; Zheng, C.; Ong, S. P. Graph Networks as a Universal Machine Learning Framework for
Molecules and Crystals. Chem. Mater. 2019, 31 (9), 3564–3572. https://doi.org/10.1021/acs.chemmater.9b01294.
- Library
- matgl
- Created
- May 6, 2026
- Updated
- May 6, 2026