Calculations in 00.scf do not converge, resulting in failure to continue training. raise RuntimeError("No system is avaliable") RuntimeError: No system is avaliable

I am using deepks for multi-label training. In the log.data in the 00.scf for each iter, the computation gradually does not converge, eventually leading to not being able to continue training. In iter.02, there is no configuration in 00.scf that can converge the calculation. It causes an error in 01.train of iter.02. **Any suggestions for setting and tuning the training parameters?**

This is the error message.
# data_train/group.00 no system.raw, infer meta from data
# data_train/group.00 reset batch size to 0
# ignore empty dataset: data_train/group.00
Traceback (most recent call last):
File "", line 198, in _run_module_as_main
File "", line 88, in _run_code
File "/home/zwj/miniconda3/envs/deepks/lib/python3.12/site-packages/deepks/model/train.py", line 303, in
cli()
File "/home/zwj/miniconda3/envs/deepks/lib/python3.12/site-packages/deepks/main.py", line 71, in train_cli
main(**argdict)
File "/home/zwj/miniconda3/envs/deepks/lib/python3.12/site-packages/deepks/model/train.py", line 270, in main
g_reader = GroupReader(train_paths, **data_args)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/zwj/miniconda3/envs/deepks/lib/python3.12/site-packages/deepks/model/reader.py", line 207, in __init__
raise RuntimeError("No system is avaliable")
RuntimeError: No system is avaliable

This is the log.data of iter.init, iter.00,iter.01,iter.02.