Comments (4)
ruizhecao96
commented on July 22, 2024
Hello, I want to ask if the weight under the path "src best_ckpt" is a trained weight? Because I use it to evaluate my own data results are not good.
Hello, the src best_ckpt is a trained weight. Can you give me more detail about your data? For different data maybe different pre-processing methods are needed. Or maybe the model is just not powerful enough.
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Blakey-Gavin
commented on July 22, 2024
Hello, thank you very much for your reply. My general situation is as
follows:
What I test with your weight is a file with noise such as keyboard tapping.
Later, I want to use your model to train the data in musdb18 to get vocals.
The linear addition of vocals and accompaniment is used as the input, and
the label is vocals. However, the effect is not particularly good, and the
SDR value is not very high when used for evaluation.
Have you ever used your model to get vocals from songs in a similar way?
Thank you again and look forward to your reply！
Ruizhe Cao ***@***.***> 于2022年10月20日周四 18:37写道：
… Hello, I want to ask if the weight under the path "src best_ckpt" is a
trained weight? Because I use it to evaluate my own data results are not
good.
Hello, the src best_ckpt is a trained weight. Can you give me more detail
about your data? For different data maybe different pre-processing methods
are needed. Or maybe the model is just not powerful enough.
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ruizhecao96
commented on July 22, 2024
I think the bad performance is due to the VCTK-DEMAND dataset doesn't include the keyboard typing noise, and this dataset is not very large, maybe a robust model should be obtained with much more data in the training set.
I am not very familiar with music separation, sorry I am not sure why the performance is not good.
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Blakey-Gavin
commented on July 22, 2024
OK, I see. Thank you very much for your help.
Best wishes！
Ruizhe Cao ***@***.***> 于2022年11月5日周六 21:45写道：
… I think the bad performance is due to the VCTK-DEMAND dataset doesn't
include the keyboard typing noise, and this dataset is not very large,
maybe a robust model should be obtained with much more data in the training
set.
I am not very familiar with music separation, sorry I am not sure why the
performance is not good.
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Related Issues (20)
- RuntimeError HOT 3
- the change of gen_loss during training HOT 1
- RuntimeError
- RuntimeError HOT 2
- About the decreasing of loss HOT 1
- Can not reproduce the results HOT 12
- Training can get stuck HOT 6
- Inferior results trained from scratch HOT 7
- RuntimeeError HOT 1
- Can not reproduce the results HOT 3
- Training GPU requirements
- File "pesq/cypesq.pyx", line 1, in init cypesq ImportError: numpy.core.multiarray failed to import (auto-generated because you didn't call 'numpy.import_array()' after cimporting numpy; use '<void>numpy._import_array' to disable if you are certain you don't need it)
- File "/anaconda3/envs/cmg/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 578, in __init__ dist._verify_model_across_ranks(self.process_group, parameters) RuntimeError: NCCL error in: ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:957, invalid usage, NCCL version 21.0.3 ncclInvalidUsage: This usually reflects invalid usage of NCCL library (such as too many async ops, too many collectives at once, mixing streams in a group, etc). HOT 2
- How do you resample to 16000? HOT 1
- 时域Loss计算疑惑
- the training speed confusion
- My server has a 3090, but reports that I don't have a gpu HOT 1
- Test set requirements when training
- epochs
- 模型训练的采样率以及显卡训练配置咨询
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