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I am trying to train a model of a system that contains > 4000 training data with 3 type of elements: Fe, C, H, by Nequip and Allegro. The error in training session by nequip seems good but the training time is rather slow, so I tried Allegro to accelerate, but it seems the error in training session by Allegro is not good, especially in energy.
This is the latest results after 2 days for Nequip:
And this is by Allegro after 3 days:
In the train.yaml file, in both case I used the loss coeffs as the default
loss_coeffs:
forces: 1.
total_energy:
- 1.
- PerAtomMSELoss
I don't know what is the reason causes the bad performance in energy training by Allegro. Are there any better loss function values or another hyperparameters to improve the accuracy?
I attach the yaml file for training in both cases I use as below.
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Hello,
I am trying to train a model of a system that contains > 4000 training data with 3 type of elements: Fe, C, H, by Nequip and Allegro. The error in training session by nequip seems good but the training time is rather slow, so I tried Allegro to accelerate, but it seems the error in training session by Allegro is not good, especially in energy.
This is the latest results after 2 days for Nequip:
And this is by Allegro after 3 days:
In the train.yaml file, in both case I used the loss coeffs as the default
loss_coeffs:
forces: 1.
total_energy:
- 1.
- PerAtomMSELoss
I don't know what is the reason causes the bad performance in energy training by Allegro. Are there any better loss function values or another hyperparameters to improve the accuracy?
I attach the yaml file for training in both cases I use as below.
train_allegro.txt
train_nequip.txt
Thank you for your concern.
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