Upload logs/onset_v5_v6/vocal_onset_v5_v6_20260404_132617.log with huggingface_hub

logs/onset_v5_v6/vocal_onset_v5_v6_20260404_132617.log

@@ -560,3 +560,122 @@ RuntimeError: Pin memory thread exited unexpectedly
   COnP             0.1780     0.2728     0.2141
   COnPOff          0.0955     0.1450     0.1145
 Uploaded: eval/con_eval_onset_tcn.json
+Uploaded: logs/onset_v5_v6/vocal_onset_v5_v6_20260404_132617.log
+
+--- Arch: transformer ---
+/userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/src/onset_arch.py:123: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.norm_first was True
+  self.encoder = nn.TransformerEncoder(encoder_layer, num_layers=num_layers)
+/userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/train_onset_arch_compare.py:381: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
+  scaler = GradScaler(enabled=(args.fp16 and device == 'cuda'))
+Arch: transformer  Device: cuda
+Train: 11283  Val: 39  Cached: 11322
+transformer: 0.421M params
+
+=== Training transformer: 40 epochs ===
+/userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/train_onset_arch_compare.py:249: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
+  with cuda_autocast(enabled=scaler.is_enabled()):
+/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/site-packages/mir_eval/onset.py:49: UserWarning: Reference onsets are empty.
+  warnings.warn("Reference onsets are empty.")
+/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/site-packages/mir_eval/onset.py:51: UserWarning: Estimated onsets are empty.
+  warnings.warn("Estimated onsets are empty.")
+Ep 1/40 (11s) lr=1.00e-03 | train_loss=0.0307 | val_f1=0.1118 P=0.0941 R=0.1944
+  ★ New best: 0.1118
+/userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/train_onset_arch_compare.py:249: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
+  with cuda_autocast(enabled=scaler.is_enabled()):
+Exception in thread Thread-3 (_pin_memory_loop):
+Traceback (most recent call last):
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/threading.py", line 1016, in _bootstrap_inner
+    self.run()
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/threading.py", line 953, in run
+    self._target(*self._args, **self._kwargs)
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/site-packages/torch/utils/data/_utils/pin_memory.py", line 52, in _pin_memory_loop
+    do_one_step()
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/site-packages/torch/utils/data/_utils/pin_memory.py", line 28, in do_one_step
+    r = in_queue.get(timeout=MP_STATUS_CHECK_INTERVAL)
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/multiprocessing/queues.py", line 122, in get
+    return _ForkingPickler.loads(res)
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/site-packages/torch/multiprocessing/reductions.py", line 540, in rebuild_storage_fd
+    fd = df.detach()
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/multiprocessing/resource_sharer.py", line 57, in detach
+    with _resource_sharer.get_connection(self._id) as conn:
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/multiprocessing/resource_sharer.py", line 86, in get_connection
+    c = Client(address, authkey=process.current_process().authkey)
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/multiprocessing/connection.py", line 502, in Client
+    c = SocketClient(address)
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/multiprocessing/connection.py", line 630, in SocketClient
+    s.connect(address)
+FileNotFoundError: [Errno 2] No such file or directory
+Traceback (most recent call last):
+  File "/userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/train_onset_arch_compare.py", line 430, in <module>
+    main()
+  File "/userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/train_onset_arch_compare.py", line 392, in main
+    train_loss = train_epoch(model, train_loader, optim, sched, scaler, device, focal)
+  File "/userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/train_onset_arch_compare.py", line 245, in train_epoch
+    for batch in loader:
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 741, in __next__
+    data = self._next_data()
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1524, in _next_data
+    idx, data = self._get_data()
+  File "/userhome/cs/u3571824/anaconda3/envs/bass/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1478, in _get_data
+    raise RuntimeError("Pin memory thread exited unexpectedly")
+RuntimeError: Pin memory thread exited unexpectedly
+2026-04-04 15:27:34,919 INFO MIR-ST500 eval ready
+/userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/src/onset_arch.py:123: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.norm_first was True
+  self.encoder = nn.TransformerEncoder(encoder_layer, num_layers=num_layers)
+2026-04-04 15:27:36,692 INFO Loaded onset_transformer from /userhome/cs/u3571824/fyp/muse/backend/ml_models/dev/vocal/outputs/onset_transformer/best.pt
+2026-04-04 15:27:36,695 INFO Found 39 MIR-ST500 test tracks
+2026-04-04 15:27:36,696 INFO [1/39] mir_st500_259
+2026-04-04 15:27:38,151 INFO Loading RMVPE from /userhome/cs/u3571824/fyp/muse/backend/ml_models/prod/weights/rmvpe.pt
+2026-04-04 15:27:39,661 INFO [2/39] mir_st500_225
+2026-04-04 15:27:40,457 INFO [3/39] mir_st500_66
+2026-04-04 15:27:40,950 INFO [4/39] mir_st500_324
+2026-04-04 15:27:41,723 INFO [5/39] mir_st500_86
+2026-04-04 15:27:42,410 INFO [6/39] mir_st500_227
+2026-04-04 15:27:43,077 INFO [7/39] mir_st500_12
+2026-04-04 15:27:43,643 INFO [8/39] mir_st500_293
+2026-04-04 15:27:44,397 INFO [9/39] mir_st500_46
+2026-04-04 15:27:45,163 INFO [10/39] mir_st500_382
+2026-04-04 15:27:45,912 INFO [11/39] mir_st500_260
+2026-04-04 15:27:46,501 INFO [12/39] mir_st500_368
+2026-04-04 15:27:47,237 INFO [13/39] mir_st500_89
+2026-04-04 15:27:47,970 INFO [14/39] mir_st500_73
+2026-04-04 15:27:48,765 INFO [15/39] mir_st500_492
+2026-04-04 15:27:49,663 INFO [16/39] mir_st500_25
+2026-04-04 15:27:50,301 INFO [17/39] mir_st500_444
+2026-04-04 15:27:51,028 INFO [18/39] mir_st500_155
+2026-04-04 15:27:51,790 INFO [19/39] mir_st500_466
+2026-04-04 15:27:52,576 INFO [20/39] mir_st500_412
+2026-04-04 15:27:53,324 INFO [21/39] mir_st500_268
+2026-04-04 15:27:53,815 INFO [22/39] mir_st500_26
+2026-04-04 15:27:54,610 INFO [23/39] mir_st500_190
+2026-04-04 15:27:55,217 INFO [24/39] mir_st500_158
+2026-04-04 15:27:55,962 INFO [25/39] mir_st500_159
+2026-04-04 15:27:56,678 INFO [26/39] mir_st500_37
+2026-04-04 15:27:57,420 INFO [27/39] mir_st500_460
+2026-04-04 15:27:58,260 INFO [28/39] mir_st500_188
+2026-04-04 15:27:58,975 INFO [29/39] mir_st500_435
+2026-04-04 15:27:59,732 INFO [30/39] mir_st500_57
+2026-04-04 15:28:00,436 INFO [31/39] mir_st500_195
+2026-04-04 15:28:01,160 INFO [32/39] mir_st500_213
+2026-04-04 15:28:01,850 INFO [33/39] mir_st500_262
+2026-04-04 15:28:02,573 INFO [34/39] mir_st500_275
+2026-04-04 15:28:03,298 INFO [35/39] mir_st500_290
+2026-04-04 15:28:04,033 INFO [36/39] mir_st500_93
+2026-04-04 15:28:04,800 INFO [37/39] mir_st500_154
+2026-04-04 15:28:05,569 INFO [38/39] mir_st500_2
+2026-04-04 15:28:06,266 INFO [39/39] mir_st500_487
+2026-04-04 15:28:07,033 INFO Results saved to con_eval_onset_transformer.json
+
+======================================================================
+  MIR-ST500 (onset_transformer) — 39 tracks
+======================================================================
+  System                                       COn    COnP COnPOff
+  ---------------------------------------- ------- ------- -------
+  RMVPE + heuristic (ours)                   0.259   0.173   0.078
+
+  Metric        Precision     Recall         F1
+  ------------ ---------- ---------- ----------
+  COn              0.2253     0.3324     0.2589
+  COnP             0.1502     0.2212     0.1726
+  COnPOff          0.0681     0.0979     0.0777
+Uploaded: eval/con_eval_onset_transformer.json