Comments (1)
SherifAbdulatif
commented on July 22, 2024
No it is not a smooth decrease here is a part of the logs:
INFO:root:Epoch 0, Step 2000, loss: 0.0698222815990448, disc_loss: 0.003855810035020113
INFO:root:Epoch 0, Step 4000, loss: 0.10153232514858246, disc_loss: 0.0027087130583822727
INFO:root:Epoch 0, Step 6000, loss: 0.09570753574371338, disc_loss: 0.013898389413952827
INFO:root:Epoch 0, Step 8000, loss: 0.1152464747428894, disc_loss: 0.003877736860886216
INFO:root:Epoch time: 5668.203575849533
INFO:root:Epoch 1, Step 2000, loss: 0.07784414291381836, disc_loss: 0.020618950948119164
INFO:root:Epoch 1, Step 4000, loss: 0.061434850096702576, disc_loss: 0.043131016194820404
INFO:root:Epoch 1, Step 6000, loss: 0.06747680902481079, disc_loss: 0.001505840104073286
INFO:root:Epoch 1, Step 8000, loss: 0.04802854731678963, disc_loss: 0.014482944272458553
INFO:root:Epoch time: 5658.317040681839
INFO:root:Epoch 2, Step 2000, loss: 0.08109544962644577, disc_loss: 0.0069780051708221436
INFO:root:Epoch 2, Step 4000, loss: 0.07633058726787567, disc_loss: 0.006170968525111675
INFO:root:Epoch 2, Step 6000, loss: 0.08500031381845474, disc_loss: 0.0013521842192858458
INFO:root:Epoch 2, Step 8000, loss: 0.04127846658229828, disc_loss: 0.0018893849337473512
INFO:root:Epoch time: 5657.765841007233
INFO:root:Epoch 3, Step 2000, loss: 0.07090915739536285, disc_loss: 0.005887601524591446
INFO:root:Epoch 3, Step 4000, loss: 0.059316493570804596, disc_loss: 0.0012161008780822158
INFO:root:Epoch 3, Step 6000, loss: 0.10464320331811905, disc_loss: 0.0052590081468224525
INFO:root:Epoch 3, Step 8000, loss: 0.06500907987356186, disc_loss: 0.0010780195007100701
INFO:root:Epoch time: 5662.782829999924
INFO:root:Epoch 4, Step 2000, loss: 0.03907656669616699, disc_loss: 0.008593665435910225
INFO:root:Epoch 4, Step 4000, loss: 0.0602584108710289, disc_loss: 0.003996850922703743
INFO:root:Epoch 4, Step 6000, loss: 0.12089455872774124, disc_loss: 0.0021806589793413877
INFO:root:Epoch 4, Step 8000, loss: 0.09586295485496521, disc_loss: 0.0031526663806289434
INFO:root:Epoch time: 5669.503582715988
INFO:root:Epoch 5, Step 2000, loss: 0.0668821632862091, disc_loss: 0.0061484831385314465
INFO:root:Epoch 5, Step 4000, loss: 0.04616473987698555, disc_loss: 0.0014118528924882412
INFO:root:Epoch 5, Step 6000, loss: 0.06401266157627106, disc_loss: 0.0012459662975743413
INFO:root:Epoch 5, Step 8000, loss: 0.05762811750173569, disc_loss: 0.0017574067460373044
INFO:root:Epoch time: 5669.170885562897
INFO:root:Epoch 6, Step 2000, loss: 0.09387986361980438, disc_loss: 0.002971608191728592
INFO:root:Epoch 6, Step 4000, loss: 0.10805267840623856, disc_loss: 0.00345245492644608
INFO:root:Epoch 6, Step 6000, loss: 0.1099756583571434, disc_loss: 0.00208111759275198
INFO:root:Epoch 6, Step 8000, loss: 0.052734144032001495, disc_loss: 0.002511049387976527
INFO:root:Epoch time: 5673.420320510864
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Related Issues (20)
- RuntimeError HOT 3
- the change of gen_loss during training HOT 1
- RuntimeError
- RuntimeError HOT 2
- 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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