Experiments - choderalab/modelforge GitHub Wiki
Lessons learned
- it seems necessary to decrease the learning rate to 5*10^-4 to achieve stable performance.
Training performance
Each neural network is trained on a fixed test set with each implemented neural network potential. We repeat each training 5 times with random parameter initialization.
PHALKETHOH
| NNP | average number of epochs | time @ epoch [min:sec] | RMSE test set [kcal/mol] | reported performance [kcal/mol] |
|---|---|---|---|---|
| ANI2x | ||||
| SchNet | ||||
| PaiNN | ||||
| PhysNet | ||||
| SAKE | ||||
| TensorNet | ||||
| AimNet2 |
SPICE2
| NNP | average number of epochs | time @ epoch [min:sec] | RMSE test set [kcal/mol] | reported performance [kcal/mol] |
|---|---|---|---|---|
| ANI2x | ||||
| SchNet | ||||
| PaiNN | ||||
| PhysNet | ||||
| SAKE | ||||
| TensorNet | ||||
| AimNet2 |