How can I train spleeter based on pretrained_models

when I run the train command like 'spleeter train --verbose -p configs/musdb_config.json -d musdb18hq' ,and the musdb_config.json content like this :
`{
"train_csv": "configs/musdb_train.csv",
"validation_csv": "configs/musdb_validation.csv",
"model_dir": "pretrained_models/2stems",
"mix_name": "mix",
"instrument_list": ["vocals", "other"],
"sample_rate":44100,
"frame_length":4096,
"frame_step":1024,
"T":512,
"F":1024,
"n_channels":2,
"n_chunks_per_song":40,
"separation_exponent":2,
"mask_extension":"zeros",
"learning_rate": 1e-4,
"batch_size":4,
"training_cache":"cache/training",
"validation_cache":"cache/validation",
"train_max_steps": 200000,
"throttle_secs":1800,
"random_seed":3,
"save_checkpoints_steps":1000,
"save_summary_steps":5,
"model":{
"type":"unet.unet",
"params":{
"conv_activation":"ELU",
"deconv_activation":"ELU"
}
}
}`
I got errors :
2 root error(s) found.
(0) Not found: Key batch_normalization/beta/Adam not found in checkpoint
[[node save/RestoreV2 (defined at /miniforge3/lib/python3.9/site-packages/tensorflow_estimator/python/estimator/estimator.py:1497) ]]
[[save/RestoreV2/_301]]
(1) Not found: Key batch_normalization/beta/Adam not found in checkpoint
[[node save/RestoreV2 (defined at /miniforge3/lib/python3.9/site-packages/tensorflow_estimator/python/estimator/estimator.py:1497) ]]
So,is there any way to train spleeter based on pretrained_models?