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logs/rmvpe_ft/rmvpe_ft_v6_20260330_033150.log
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=== Fine-tune RMVPE — Mon Mar 30 03:31:50 HKT 2026 ===
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Disk usage:
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Filesystem Size Used Avail Use% Mounted on
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10.21.7.193:/dpool/userhome/cs/u3571824 200G 124G 77G 62% /userhome/cs/u3571824
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4.9G data/
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=== Run 1/3 — Mon Mar 30 03:31:50 HKT 2026 ===
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/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/site-packages/resampy/filters.py:50: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
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import pkg_resources
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/userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/finetune_rmvpe.py:655: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
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scaler = GradScaler(enabled=args.fp16 and device.type == 'cuda')
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RMVPE E2E verified at /userhome/cs/u3571824/fyp/muse/backend/ml_models/prod/weights/rmvpe.pt (368MB)
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Loading pretrained RMVPE from /userhome/cs/u3571824/fyp/muse/backend/ml_models/prod/weights/rmvpe.pt
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Generating pseudo-labels for 357 tracks...
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Pseudo-labels: 152 new, 205 cached in outputs/rmvpe_ft_v6/pseudo_labels
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Pseudo-label generation took 89s
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Datasets: ['mir_st500', 'medleydb']
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Train: 318 tracks, Val: 39 tracks
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Smoke test: audio=torch.Size([40960]), label=torch.Size([257, 360]), label_max=0.9229, label_sum=535.0
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RMVPE: 92.0M params
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Frozen 230/417 parameter groups (encoder + intermediate)
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=== Fine-tuning RMVPE: 30 epochs, lr=2e-06 ===
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/userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/finetune_rmvpe.py:684: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
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with cuda_autocast(enabled=args.fp16 and device.type == 'cuda'):
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Epoch 1/30 (7s) lr_head=1.99e-06 lr_enc=3.99e-08 | loss=0.1832 | val_RPA=0.8982
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★ New best RPA: 0.8982
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Epoch 2/30 (6s) lr_head=1.98e-06 lr_enc=3.96e-08 | loss=0.1833 | val_RPA=0.8638
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Epoch 3/30 (6s) lr_head=1.95e-06 lr_enc=3.90e-08 | loss=0.1830 | val_RPA=0.8350
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Epoch 4/30 (6s) lr_head=1.91e-06 lr_enc=3.83e-08 | loss=0.1834 | val_RPA=0.7768
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Epoch 5/30 (6s) lr_head=1.87e-06 lr_enc=3.73e-08 | loss=0.1836 | val_RPA=0.7556
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Epoch 6/30 (6s) lr_head=1.81e-06 lr_enc=3.62e-08 | loss=0.1836 | val_RPA=0.7374
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Epoch 7/30 (6s) lr_head=1.74e-06 lr_enc=3.49e-08 | loss=0.1835 | val_RPA=0.7056
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Epoch 8/30 (6s) lr_head=1.67e-06 lr_enc=3.34e-08 | loss=0.1832 | val_RPA=0.6924
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Epoch 9/30 (6s) lr_head=1.59e-06 lr_enc=3.18e-08 | loss=0.1831 | val_RPA=0.6773
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Early stopping at epoch 9
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Fine-tuning complete. Best RPA: 0.8982
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Training finished at Mon Mar 30 03:34:40 HKT 2026
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=== Upload to HuggingFace ===
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Uploading best.pt...
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