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In the DPGen workflow, training in iter-0 seems all right. The model trained in iter-1 (with init-model) has a large RMSE ~100meV, while the lcurve shows a better accuracy
For the worst system, the RMSE increase by a factor >30 after training of iter-1.
This phenomenon does not appear when using finetune (instead of init-model) in iter-1.
DeePMD-kit Version
stable-0411
Backend and its version
Pytorch
How did you download the software?
docker
Input Files, Running Commands, Error Log, etc.
iter1input.zip
Steps to Reproduce
bash aefcb166ade9f2faf80a15e8a6f0d0cb70a6d33a.sub
Further Information, Files, and Links
No response
The text was updated successfully, but these errors were encountered:
Bug summary
In the DPGen workflow, training in iter-0 seems all right. The model trained in iter-1 (with init-model) has a large RMSE ~100meV, while the lcurve shows a better accuracy
For the worst system, the RMSE increase by a factor >30 after training of iter-1.
This phenomenon does not appear when using finetune (instead of init-model) in iter-1.
DeePMD-kit Version
stable-0411
Backend and its version
Pytorch
How did you download the software?
docker
Input Files, Running Commands, Error Log, etc.
iter1input.zip
Steps to Reproduce
bash aefcb166ade9f2faf80a15e8a6f0d0cb70a6d33a.sub
Further Information, Files, and Links
No response
The text was updated successfully, but these errors were encountered: