Comments (5)
Training is to atomization energies.
from ase_ani.
Thanks Justin (for this and the other issue!)
from ase_ani.
I need to clarify something else, are you guys normalizing the energies to the unit gaussian? We think Adrian may have mentioned something about this during the talk he gave at our company, but we couldn't find any references to this in the pre-print of the Chemical Science paper.
from ase_ani.
Are you you asking: are we normalizing the labels [energies] (after we remove the single atom energies from the total energy)? If so, the answer is no. We actually do no preprocessing on the energies aside from the atomization shift. Once the energies are shifted we train directly to hartrees, which are in the range -4 to 0 Ha (Figure 3C -> https://arxiv.org/pdf/1708.04987v1.pdf) unless something is wrong with the data (or working with larger systems in the training set). Early on in this work I noticed normalizing didn't make a difference so I stopped using it. However, if working with larger molecules in the training set it might be a good idea to start doing it. Does this answer your question?
from ase_ani.
Thanks, this is exactly what I was looking for.
from ase_ani.
Related Issues (20)
- wB97 single vs double precision? HOT 1
- Clarification on training the model HOT 2
- Cuda 9.1/9.2 support HOT 8
- Portable version? HOT 15
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- geometry optimization doesn't work HOT 1
- problem installing ASED3 HOT 4
- libAEV.so can not open HOT 2
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- computing energy of a benzene crystal results in a RuntimeError HOT 7
- Example of generating the feature vector from a geometry HOT 1
- `ani_quicktest.py` example requires changes to script HOT 4
- Libraries for OpenMM-ANI HOT 2
- libAtomicNNP.so: undefined symbol HOT 1
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from ase_ani.