2024-01-22 20:16:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:173 - INFO ] Create optimizer adam: {'lr': 0.001, 'weight_decay': 1e-05} 2024-01-22 20:16:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:140 - INFO ] Model summary: ConvTasNet( (encoder_1d): Conv1D(1, 512, kernel_size=(40,), stride=(20,)) (ln): ChannelWiseLayerNorm((512,), eps=1e-05, elementwise_affine=True) (proj): Conv1D(512, 256, kernel_size=(1,), stride=(1,)) (repeats): Sequential( (0): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) (1): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) (2): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) (3): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) ) (mask): Conv1D(256, 1024, kernel_size=(1,), stride=(1,)) (decoder_1d): ConvTrans1D(512, 1, kernel_size=(40,), stride=(20,)) ) 2024-01-22 20:16:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:141 - INFO ] Loading model to GPUs:(4, 5), #param: 8.98M 2024-01-22 20:16:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:145 - INFO ] Gradient clipping by 5, default L2 2024-01-22 20:16:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-22 20:17:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +51.65)... 2024-01-22 20:17:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +51.97)... 2024-01-22 20:17:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 46.10,63.79,50.53,51.90,48.61,52.66,46.21,55.93,50.46,52.17,52.49,48.74,50.90,45.32,53.26,50.07,52.50,47.43,55.77,53.53,48.52,46.46,52.21,50.06,53.76,51.40,58.70,52.27,49.77,47.28,50.41,52.42,50.85,50.44,55.03,51.17,49.47,55.08,46.81,47.55,45.87,45.89,53.67,50.70,49.75,49.01,52.46,51.00,57.58,67.21,52.49,47.80,49.19,51.59,51.52,53.87,45.88,50.24,46.16,55.20,53.15,51.43,49.16,54.75,54.96,44.78,50.65,46.01,43.52,52.32,61.07,53.16,51.15,53.16,51.31,48.36,50.19,49.78,50.60,50.82,47.21,51.58,46.90,59.53,50.07,56.71,55.68,53.34,50.13,54.58,48.53,52.17,60.29,67.80,57.92,58.72,71.36,52.37,73.76,57.66,52.61,46.83,48.24,51.45,49.01,48.43,55.38,48.56,52.58,45.04,48.56,51.00,44.06,51.63,51.11,51.53,50.92,50.49,56.10,59.41,55.49,61.49,57.85,52.79,63.15,51.30,47.55,51.83,50.94,49.40,49.68,49.61,53.71,47.24,46.78,45.17,50.30,51.52,52.63,50.25,51.98,57.18,54.13,48.78,52.26,45.63,51.15,60.00,54.20,43.78,58.44,49.62,57.05,56.35,53.66,52.16,45.13,48.97,49.06,48.30,48.42,46.96,47.96,48.36,42.89,50.39,47.71,47.71,49.74,53.36,47.63,58.46,56.79,53.27,56.33,52.73,50.14,51.88,52.70,56.11,45.16,47.98,51.73,48.06,49.67,45.04,55.77,48.49,48.64,52.49,51.03,48.42,51.20,53.99,53.50,52.19,51.09,45.34,49.56,49.79,48.77,53.16,45.94,46.98,50.88,53.03,55.21,61.38,52.56,50.81,56.20,43.50,47.71,47.60,56.34,50.13,57.22,52.82,53.66,54.48,57.59,55.61,52.21,41.87,54.06,49.85,50.38,55.28,54.18,48.97,49.01,50.51,58.69,50.91,48.63,46.49,45.35,47.92,49.86,52.72,48.75,48.37,58.42,54.50,55.27,60.15,53.67,46.19,52.94,44.58,49.37,54.24,54.15,56.81,48.78,55.44,54.86,48.45,52.68,46.51,47.79,52.31,54.79,56.38,52.03,51.19,53.86,50.37,54.94,53.17,52.38,45.89,50.98,50.03,50.70,53.37,53.42,47.69,55.62,59.66,58.25,53.99,55.22,54.08,60.15,47.42,52.31,50.74,50.96,45.15,49.89,56.36,56.12,58.48,56.72,54.74,51.75,65.77,50.28,48.45,47.08,53.38,58.51,55.66,60.10,54.33,53.63,51.35,50.33,53.46,51.28,57.27,47.36,57.69,54.37,56.67,48.16,50.64,48.29,64.53,46.42,50.99,53.91,52.26,51.86,58.83,52.51,51.07,47.73,46.22,48.63,54.27,52.70,63.10,58.69,47.03,52.77,51.19,50.88,54.20,48.82,55.10,51.16,47.24,55.23,50.09,48.77,45.91,47.67,57.23,55.74,49.48,50.84,55.59,47.43,48.43,51.09,50.12,46.96,51.79,53.06,50.92,58.28,53.27,49.04,54.15,54.71,44.71,49.63,46.80,48.18,49.98,56.69,47.92,45.10,47.58,48.37,53.49,55.87,48.27,48.44,48.14,56.84,48.63,44.02,48.94,51.58,47.58,55.58,53.06,52.58,56.86,51.01,53.22,47.23,51.69,53.61,48.41,49.20,52.06,49.03,49.86,53.56,46.18,53.13,50.06,54.51,50.78,49.85,54.30,57.24,66.08,51.25,45.25,47.09,46.14,50.81,61.01,58.20,60.24,58.13,57.36,55.24,50.08,50.98,53.31,48.47,49.82,46.01,52.00,48.67,47.69 2024-01-22 20:17:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:221 - INFO ] START FROM EPOCH 0, LOSS = 51.8449 2024-01-22 20:17:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-22 20:20:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +10.08)... 2024-01-22 20:22:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +8.40)... 2024-01-22 20:24:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +7.95)... 2024-01-22 20:27:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +7.59)... 2024-01-22 20:29:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +7.50)... 2024-01-22 20:31:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +7.44)... 2024-01-22 20:33:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +7.13)... 2024-01-22 20:36:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +7.09)... 2024-01-22 20:38:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +7.31)... 2024-01-22 20:40:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +7.05)... 2024-01-22 20:42:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +6.81)... 2024-01-22 20:43:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-22 20:44:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +8.02)... 2024-01-22 20:45:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +8.28)... 2024-01-22 20:45:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 2.66,21.69,6.97,8.85,7.76,9.68,3.47,11.73,5.44,9.95,7.74,4.86,7.69,1.13,9.50,6.09,8.58,2.13,9.76,8.46,3.07,4.70,6.20,6.25,11.76,6.68,16.20,6.77,7.31,2.78,4.33,6.83,3.35,6.24,11.24,8.18,6.68,8.41,6.53,6.32,2.65,1.30,8.16,6.11,2.79,4.71,6.45,6.45,14.24,26.45,10.06,3.48,6.79,8.10,6.22,7.88,1.63,6.11,2.75,9.51,7.68,6.61,6.04,11.23,13.03,1.45,4.65,1.38,1.65,8.59,18.22,8.19,6.86,9.58,7.84,3.01,5.44,6.00,7.96,6.79,4.34,7.05,1.30,18.29,4.62,12.51,17.25,9.66,6.49,11.22,4.60,8.34,16.69,27.04,13.18,19.42,33.69,7.96,34.70,12.97,9.52,3.16,4.70,6.61,5.04,1.77,10.48,4.87,7.89,2.63,4.96,9.58,0.74,8.06,6.51,7.98,8.31,6.14,11.91,16.60,13.20,17.66,13.45,9.19,19.47,8.12,6.30,8.79,7.51,4.94,8.14,6.33,10.55,4.99,4.49,1.33,6.42,5.48,5.77,4.44,8.49,14.71,9.87,5.27,8.24,2.07,4.50,18.18,9.18,1.02,15.99,5.90,15.62,9.99,8.11,9.91,0.02,6.23,6.25,3.79,6.43,3.14,1.56,4.87,1.29,7.75,4.87,2.48,4.60,11.26,2.46,20.10,12.98,12.07,11.18,10.17,5.49,11.64,8.11,13.14,1.15,5.09,9.72,4.20,4.85,1.07,14.30,8.61,4.25,12.23,8.26,4.50,7.85,9.09,11.29,8.02,5.82,2.44,4.47,4.62,2.87,8.09,0.12,6.28,6.68,7.81,11.48,19.44,6.55,7.00,13.20,1.36,6.36,2.94,13.80,4.70,11.63,8.35,9.68,10.46,11.37,9.96,9.56,-0.54,12.82,6.17,8.14,12.88,11.52,5.67,6.18,5.37,13.01,7.19,2.78,1.75,2.71,5.21,7.17,9.65,8.10,4.71,14.88,7.95,11.24,14.45,9.21,2.56,7.53,1.11,4.95,11.51,12.96,12.07,7.57,11.00,9.68,3.09,7.45,2.97,3.94,6.42,10.23,15.13,5.28,8.32,11.33,6.51,12.78,11.56,9.84,1.38,3.73,6.14,7.37,8.04,13.01,4.90,19.06,16.94,15.84,10.63,10.03,11.92,17.28,4.95,8.00,6.80,6.57,2.59,8.07,10.70,16.88,16.50,13.47,9.59,8.39,23.34,4.53,8.03,2.73,10.00,15.43,10.97,14.54,9.71,9.46,8.00,6.33,10.81,9.92,17.72,0.70,11.33,9.92,12.14,2.58,6.80,5.15,23.83,1.26,10.98,10.11,6.37,10.04,15.58,7.87,8.21,4.75,1.27,6.13,11.61,6.49,20.31,14.81,4.75,8.37,6.24,8.27,11.54,4.64,9.68,6.45,2.12,11.45,4.97,4.50,2.94,4.91,13.42,9.22,5.28,6.68,11.73,4.81,1.53,6.14,7.73,3.46,7.73,8.03,8.05,14.65,11.51,4.83,7.94,10.12,-0.17,8.14,1.63,6.09,8.18,16.05,4.75,1.46,2.71,6.52,9.92,11.10,3.32,3.65,3.55,12.91,8.21,-0.15,5.50,7.65,7.92,13.64,9.93,8.74,12.36,6.28,8.18,3.05,7.64,6.58,4.47,1.24,8.48,4.97,4.67,9.65,3.23,10.43,6.58,9.73,7.96,6.36,9.88,13.48,23.67,9.72,3.14,2.63,2.89,6.41,16.31,16.23,17.42,16.56,15.14,12.72,9.89,6.48,9.46,3.43,6.83,4.52,9.71,4.43,3.17 2024-01-22 20:45:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 1: train = +7.6636(25.57m/2257) | dev = +8.2111(1.76m/432) 2024-01-22 20:45:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-22 20:47:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +6.80)... 2024-01-22 20:49:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +7.45)... 2024-01-22 20:52:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +7.18)... 2024-01-22 20:54:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +6.95)... 2024-01-22 20:56:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +6.67)... 2024-01-22 20:58:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +6.05)... 2024-01-22 21:01:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +6.19)... 2024-01-22 21:03:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +7.10)... 2024-01-22 21:05:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +6.25)... 2024-01-22 21:07:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +6.49)... 2024-01-22 21:10:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +6.72)... 2024-01-22 21:10:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-22 21:11:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +7.15)... 2024-01-22 21:12:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +7.46)... 2024-01-22 21:12:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 2.04,20.39,6.20,7.50,6.98,8.57,2.72,10.78,4.78,8.84,7.08,4.07,6.51,0.82,8.38,5.20,7.68,1.63,8.41,7.41,2.21,4.14,5.77,5.33,10.59,5.34,15.12,5.82,6.39,1.83,3.11,6.00,2.34,4.67,10.16,7.34,5.56,7.29,6.00,5.33,1.74,0.97,7.12,5.50,2.53,4.09,5.34,5.78,13.57,24.78,8.95,2.36,5.83,6.66,5.35,6.90,1.31,5.88,2.45,8.96,7.14,5.60,4.94,10.17,11.78,1.32,4.41,1.12,0.99,8.15,16.61,7.21,6.22,8.63,7.42,2.80,4.49,5.29,7.32,5.83,3.66,6.61,0.70,17.00,3.96,11.38,16.40,9.14,5.58,10.09,3.98,7.24,15.12,24.86,12.21,18.57,32.31,7.09,32.22,11.53,8.62,2.63,4.07,5.60,4.44,1.19,9.31,3.49,6.91,2.08,4.05,8.16,0.38,7.05,5.62,7.31,7.22,5.28,10.68,14.96,11.78,16.57,12.43,8.41,17.34,7.55,6.06,7.51,5.95,3.91,7.16,5.72,9.30,4.43,3.63,1.04,5.77,4.79,5.09,3.81,6.85,13.80,8.67,4.06,7.79,1.34,3.80,16.90,7.68,1.26,15.09,5.51,14.25,9.22,7.22,9.18,-0.87,5.82,5.49,3.33,5.95,2.36,0.81,4.24,0.92,6.71,3.72,2.09,4.08,11.01,1.95,19.15,12.36,11.05,10.32,9.45,4.69,10.82,7.59,12.64,0.71,4.13,8.58,3.47,3.69,0.34,12.88,7.31,3.96,11.13,7.31,3.76,7.17,8.43,10.58,6.88,4.28,1.41,4.22,4.18,2.69,7.19,-0.10,5.66,6.40,7.05,10.11,17.88,5.31,5.80,11.85,0.53,5.36,1.99,12.19,3.60,10.81,7.96,8.88,9.56,10.50,8.65,8.32,-0.78,12.13,5.25,7.22,11.59,10.58,4.73,5.89,4.42,11.96,6.81,2.30,1.04,2.36,4.58,6.09,8.63,7.13,4.09,13.20,7.27,10.25,12.98,8.20,1.73,6.16,1.16,4.46,10.42,12.15,10.76,6.99,10.37,8.90,2.33,6.88,2.30,3.55,5.81,8.74,13.78,4.79,7.64,10.56,5.79,11.71,10.50,9.19,1.36,3.28,5.54,5.75,7.32,11.61,4.06,18.67,15.77,14.86,9.52,9.24,11.29,16.34,4.33,6.71,5.97,6.21,1.79,7.67,9.55,16.24,15.36,12.17,8.51,7.50,21.51,3.73,7.30,2.38,9.07,14.42,10.38,12.76,8.86,8.17,7.10,5.92,9.87,9.14,15.76,0.14,10.34,9.17,10.82,2.07,6.16,4.76,21.97,0.89,10.21,8.89,6.15,8.70,14.30,7.53,7.55,4.17,0.89,5.33,10.96,6.18,18.95,13.75,4.28,7.09,5.33,7.95,10.22,3.55,8.71,5.66,1.76,10.39,4.07,3.82,2.87,4.53,12.49,7.73,4.34,5.60,10.36,3.60,1.39,5.31,7.27,2.39,6.54,6.84,7.49,12.80,10.76,4.55,7.17,9.69,-1.21,7.10,1.44,5.88,7.48,14.96,4.11,1.39,2.27,5.44,8.99,10.30,3.52,3.23,2.92,11.96,7.07,-0.60,5.10,7.44,7.91,12.94,9.04,7.69,11.42,5.55,7.49,2.74,7.19,6.11,4.18,1.13,8.27,4.71,4.60,8.65,2.85,9.70,5.97,8.76,7.73,5.63,8.87,12.31,22.11,8.88,3.23,2.11,2.43,5.53,15.20,15.41,16.11,15.22,13.43,12.14,8.61,5.65,8.65,2.96,6.43,3.76,9.11,3.72,2.68 2024-01-22 21:12:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 2: train = +6.6917(25.47m/2259) | dev = +7.3736(1.67m/432) 2024-01-22 21:12:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-22 21:14:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +6.74)... 2024-01-22 21:17:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +7.10)... 2024-01-22 21:19:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +5.87)... 2024-01-22 21:21:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +6.22)... 2024-01-22 21:23:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +6.01)... 2024-01-22 21:26:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +5.71)... 2024-01-22 21:28:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +5.94)... 2024-01-22 21:30:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +5.86)... 2024-01-22 21:32:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +5.84)... 2024-01-22 21:35:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +6.24)... 2024-01-22 21:37:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +6.26)... 2024-01-22 21:37:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-22 21:38:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +6.89)... 2024-01-22 21:39:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +7.21)... 2024-01-22 21:39:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 2.14,20.42,6.26,7.62,6.19,8.38,2.37,10.72,4.71,9.49,6.74,4.33,6.93,0.85,8.30,4.82,7.11,0.96,8.06,7.02,1.98,4.07,5.49,4.55,9.75,4.57,15.10,5.84,6.00,1.26,2.67,5.80,1.47,4.02,10.17,7.04,5.44,7.19,5.68,5.44,1.32,-0.05,6.34,5.20,2.61,3.98,5.11,5.41,13.54,24.42,8.08,2.08,5.92,6.61,4.75,6.25,0.52,5.69,2.32,8.86,7.24,5.32,4.58,9.65,11.55,0.76,4.42,1.08,1.15,7.80,16.89,7.19,5.90,8.38,7.50,1.89,4.21,4.45,7.68,5.28,3.02,5.31,-0.36,17.43,4.03,11.62,17.00,9.11,5.49,10.37,4.05,6.96,15.12,25.23,12.37,17.80,31.92,6.22,32.12,11.13,8.95,2.04,3.63,5.73,4.18,0.69,8.62,3.02,6.83,1.87,3.94,7.35,0.04,6.61,5.14,7.01,7.25,5.51,10.03,15.57,12.02,16.99,12.85,8.28,17.53,7.34,6.21,7.34,5.22,2.95,6.93,5.45,8.46,2.88,3.31,-0.31,5.52,4.83,5.20,3.83,6.58,12.94,7.82,4.00,7.74,1.42,3.60,17.04,7.83,0.29,14.48,5.47,14.22,8.65,7.26,9.38,-1.43,5.29,5.02,2.79,6.11,2.05,0.46,4.10,0.74,6.54,2.71,1.36,3.35,10.76,2.02,19.69,11.94,12.27,10.30,9.59,4.13,10.40,7.48,12.33,0.12,3.63,7.82,2.69,3.28,-0.40,12.26,7.13,3.70,11.12,7.38,3.60,7.25,8.62,10.43,6.31,4.05,1.05,3.82,3.63,2.37,7.74,-0.35,5.30,6.00,6.79,9.77,17.73,5.44,5.81,11.41,-0.06,5.45,1.48,11.87,2.88,10.68,7.52,9.01,9.08,10.38,9.24,8.07,-1.04,11.89,4.94,7.21,10.44,9.46,4.10,6.17,3.27,10.78,5.26,1.59,0.82,2.14,4.39,5.73,8.44,6.82,3.89,13.82,7.42,10.37,13.07,8.09,0.45,5.81,0.45,4.05,9.95,11.88,10.75,7.58,10.80,9.11,2.68,7.32,0.72,2.84,5.50,7.80,13.46,4.67,7.00,10.22,5.98,11.87,10.60,8.99,1.18,3.21,4.84,4.10,7.01,11.74,2.77,18.88,16.16,15.24,9.12,8.66,11.39,16.07,4.44,6.22,5.58,6.66,1.12,7.59,9.10,17.78,15.86,11.88,8.17,6.74,21.95,3.91,7.51,1.91,9.06,14.35,10.54,13.13,9.17,7.30,5.77,5.46,10.78,9.24,15.57,-0.66,10.48,9.11,10.87,1.66,6.01,4.63,22.23,0.02,9.77,8.94,5.24,8.11,13.85,7.82,7.39,4.26,0.66,5.03,10.87,5.93,19.66,14.32,5.15,7.41,5.66,7.86,9.98,2.27,7.67,5.79,0.76,9.37,2.71,3.80,2.52,4.21,12.15,8.04,4.04,5.97,9.75,3.07,0.54,4.85,6.99,2.65,7.02,7.53,7.17,11.92,10.15,4.23,7.16,9.29,-2.31,6.44,0.79,5.50,6.64,13.74,3.31,1.39,1.31,4.61,9.13,10.69,2.77,2.79,2.61,11.75,5.80,-1.62,4.48,7.26,7.38,12.69,9.02,7.36,11.04,5.77,7.13,2.25,6.70,6.08,3.80,1.12,9.41,5.08,3.56,7.93,2.23,9.61,5.85,8.38,7.65,5.69,8.81,12.29,22.29,8.68,2.66,1.90,2.06,5.39,16.00,15.08,15.56,15.04,14.18,11.94,8.56,5.57,8.55,2.60,6.55,3.45,8.83,3.59,3.15 2024-01-22 21:39:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 3: train = +6.1711(25.62m/2258) | dev = +7.1240(1.79m/432) 2024-01-22 21:39:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-22 21:42:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +5.99)... 2024-01-22 21:44:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +5.69)... 2024-01-22 21:46:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +5.99)... 2024-01-22 21:49:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +5.70)... 2024-01-22 21:51:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +5.73)... 2024-01-22 21:53:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +5.30)... 2024-01-22 21:55:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +5.20)... 2024-01-22 21:58:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +5.56)... 2024-01-22 22:00:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +5.30)... 2024-01-22 22:02:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +5.56)... 2024-01-22 22:04:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +5.55)... 2024-01-22 22:05:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-22 22:06:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +5.82)... 2024-01-22 22:07:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +6.04)... 2024-01-22 22:07:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 1.68,19.09,4.67,5.48,4.49,7.21,1.96,9.47,3.91,8.29,5.80,3.56,5.81,0.54,7.52,3.43,5.59,-0.20,7.00,6.24,1.19,3.54,4.89,3.69,8.33,3.08,14.30,4.68,4.62,-0.25,1.58,4.64,-0.02,2.67,9.51,6.19,4.11,6.21,4.90,4.69,0.61,-1.07,5.19,4.32,2.37,2.27,3.36,4.72,13.04,23.34,6.31,1.15,5.24,5.84,3.10,4.96,-0.40,4.79,1.95,7.91,6.32,4.52,3.64,7.61,10.06,-0.11,4.15,0.28,-0.22,6.98,15.65,6.34,4.99,7.21,7.09,1.62,3.11,3.10,6.87,4.70,2.09,4.15,-1.19,15.06,2.85,9.93,14.48,8.18,4.72,9.11,3.12,5.90,14.05,24.15,11.92,16.91,30.88,4.44,30.89,8.93,8.16,1.80,2.41,4.07,3.73,0.04,7.22,1.77,5.84,1.59,1.94,6.09,-1.03,5.75,4.07,6.13,6.48,4.59,8.43,14.03,10.80,15.83,11.96,7.41,16.22,6.54,5.20,6.37,3.11,1.09,5.40,4.76,7.40,1.06,2.10,-1.41,4.46,4.03,4.58,3.32,5.53,11.85,6.44,2.24,7.02,0.78,2.61,15.78,6.37,-0.60,13.45,4.33,13.11,7.85,5.89,8.42,-2.24,4.73,4.01,1.59,5.74,1.72,-0.34,3.31,0.27,4.97,1.38,-0.12,1.70,9.90,1.20,17.20,10.73,9.85,9.46,8.19,3.32,9.15,7.08,11.85,-0.46,2.88,6.69,1.11,2.74,-1.35,10.82,5.69,2.96,9.95,6.19,2.68,6.33,8.11,9.98,4.94,2.22,-0.13,2.56,3.02,1.57,6.48,-0.97,4.88,5.45,5.08,8.50,15.86,4.76,4.97,10.51,-1.38,4.66,1.07,10.29,1.97,9.52,6.27,7.79,8.24,9.05,8.22,7.05,-1.66,11.46,4.13,5.28,8.67,7.67,3.13,5.33,1.58,9.12,4.07,0.60,-0.24,1.78,4.07,3.87,7.18,6.42,3.85,12.23,6.29,9.68,12.18,7.60,-1.34,3.42,-0.69,3.35,8.74,10.91,9.86,6.33,9.48,8.44,2.05,5.46,-0.41,1.80,4.71,6.23,12.24,3.48,5.97,9.15,4.78,10.30,9.62,7.39,0.24,3.12,4.01,2.98,5.79,9.86,1.48,16.76,14.67,13.68,7.81,7.08,9.25,15.45,3.81,3.95,4.55,5.36,-0.48,5.14,7.55,14.78,14.04,10.12,5.90,5.58,21.78,2.85,6.28,1.18,7.61,13.23,10.01,12.29,8.28,5.47,3.75,4.90,10.33,7.84,13.37,-2.05,9.88,8.60,9.27,0.98,5.09,3.58,19.75,-1.35,8.97,8.06,3.56,6.89,12.66,6.83,6.59,3.89,-0.22,3.52,9.47,4.39,18.50,13.40,3.77,6.38,4.87,6.98,8.97,0.46,5.92,4.80,-0.26,7.60,0.85,2.07,1.62,3.27,10.24,7.18,3.38,5.44,8.07,1.44,0.05,4.62,5.85,1.69,6.33,5.57,6.13,9.97,8.71,3.35,6.58,7.55,-3.87,4.96,-0.52,4.82,5.70,12.53,2.28,0.64,-0.55,3.00,8.41,9.73,2.33,1.84,1.94,10.93,4.83,-3.34,3.22,6.85,6.82,11.47,8.14,5.80,10.47,4.78,6.08,1.71,6.12,4.55,1.63,-0.04,7.94,3.82,2.23,5.88,0.41,9.03,4.93,6.10,6.70,4.70,7.15,11.29,21.33,8.02,1.79,0.27,1.49,4.46,14.54,12.96,13.60,13.56,11.94,10.97,7.77,4.81,7.74,1.70,5.29,2.38,7.68,3.08,2.01 2024-01-22 22:07:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 4: train = +5.6187(25.84m/2259) | dev = +5.9981(1.80m/432) 2024-01-22 22:07:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-22 22:09:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +5.03)... 2024-01-22 22:12:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +5.08)... 2024-01-22 22:14:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +5.18)... 2024-01-22 22:16:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +4.79)... 2024-01-22 22:19:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +5.58)... 2024-01-22 22:21:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +4.64)... 2024-01-22 22:23:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +6.01)... 2024-01-22 22:25:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +4.79)... 2024-01-22 22:28:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +5.15)... 2024-01-22 22:30:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +5.01)... 2024-01-22 22:32:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +4.78)... 2024-01-22 22:33:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-22 22:34:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +5.76)... 2024-01-22 22:34:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +5.94)... 2024-01-22 22:34:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 1.89,19.04,4.66,5.12,4.21,6.93,1.93,9.27,3.92,8.42,5.47,4.06,6.04,0.59,7.55,3.53,5.15,-0.46,6.68,6.39,1.64,3.36,5.02,3.51,8.32,3.28,14.11,4.65,4.72,-0.29,1.79,4.49,-0.26,2.55,9.91,5.86,4.01,6.68,4.76,5.25,1.02,-0.90,5.29,4.65,2.85,2.53,3.61,4.84,13.12,23.17,5.57,0.91,5.30,5.96,2.99,5.00,-0.97,4.71,1.28,7.71,5.96,4.62,3.68,7.23,9.90,-0.34,4.51,0.58,-0.49,6.56,15.80,6.35,5.15,7.28,7.35,1.44,3.49,2.87,6.91,5.00,1.86,3.52,-1.38,13.93,2.72,9.25,13.72,8.25,4.14,8.64,2.65,5.66,14.31,24.63,12.29,16.25,30.52,4.39,30.32,8.85,8.23,1.82,2.45,4.22,3.81,0.04,6.94,1.66,6.20,1.98,1.78,6.01,-1.35,5.75,4.05,6.45,7.03,4.60,8.71,13.87,11.21,14.90,12.19,7.45,16.15,6.50,5.15,6.30,2.65,0.92,4.97,4.42,6.77,1.24,1.59,-1.30,4.61,4.12,4.18,3.80,5.30,11.09,6.48,1.51,6.66,0.25,3.00,15.94,7.13,-0.49,13.66,4.79,12.93,7.95,6.17,8.50,-2.42,4.69,3.86,2.21,6.34,2.25,-0.05,2.75,1.20,4.79,1.18,-0.26,1.19,10.16,1.64,16.53,10.33,9.62,9.77,8.18,2.73,9.12,7.07,11.53,-0.62,2.45,6.57,0.51,2.58,-1.39,10.72,5.52,2.79,9.74,6.84,2.88,6.62,7.88,10.13,4.95,2.34,-0.28,1.94,2.68,1.91,7.33,-0.26,5.02,5.36,5.18,8.40,15.34,4.50,5.10,10.59,-1.46,4.92,1.15,10.18,2.11,9.66,6.28,7.33,8.19,9.17,8.30,6.97,-1.62,11.53,3.89,4.89,8.60,7.81,2.73,4.58,1.59,9.05,4.14,0.73,-0.06,1.78,3.73,3.57,7.23,6.85,3.53,11.29,6.67,9.73,12.40,7.67,-1.02,3.10,-0.59,3.90,8.85,11.17,10.44,5.71,9.41,8.70,1.35,5.25,-0.22,1.76,4.80,5.96,12.26,3.21,5.69,8.89,4.52,10.08,9.15,6.97,0.65,3.16,3.97,2.99,5.53,10.56,1.40,15.66,14.94,13.85,8.09,6.66,8.72,14.91,3.38,3.38,4.89,5.52,-0.80,4.88,7.66,14.54,13.77,9.94,5.84,5.56,21.12,3.03,6.35,1.07,7.98,12.94,9.25,12.64,8.27,5.68,3.85,5.16,9.14,7.28,13.67,-2.36,9.34,8.72,8.99,0.48,4.91,3.49,19.83,-1.54,8.93,7.57,3.72,6.99,12.58,6.82,6.79,3.95,-0.33,3.08,8.84,4.11,17.96,13.09,3.10,6.81,4.73,6.67,8.24,0.11,5.99,3.73,-0.47,7.78,1.08,2.10,1.60,2.93,10.27,7.48,3.49,5.76,7.95,1.00,0.39,4.49,5.54,1.77,5.81,5.19,5.84,9.76,8.48,3.48,6.66,7.56,-3.97,4.66,-0.87,4.53,5.48,12.47,2.51,0.75,-0.60,2.78,7.72,9.70,2.27,1.51,1.79,10.87,5.08,-2.83,3.40,7.00,6.76,10.83,8.36,5.87,10.07,4.68,5.87,1.46,5.65,4.60,1.53,-0.26,7.20,3.82,2.47,6.07,0.42,8.96,5.14,6.03,6.60,4.71,6.56,11.50,20.99,7.73,1.84,0.04,1.61,3.93,14.36,12.74,14.09,13.50,11.82,10.56,7.39,4.79,7.68,1.31,5.17,2.10,7.99,2.84,2.06 2024-01-22 22:35:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 5: train = +5.1013(25.79m/2257) | dev = +5.9213(1.79m/432) 2024-01-22 22:35:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-22 22:37:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +5.61)... 2024-01-22 22:39:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +4.84)... 2024-01-22 22:42:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +4.73)... 2024-01-22 22:44:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +4.36)... 2024-01-22 22:46:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +4.84)... 2024-01-22 22:49:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +4.61)... 2024-01-22 22:51:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +4.62)... 2024-01-22 22:53:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +5.25)... 2024-01-22 22:55:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +5.42)... 2024-01-22 22:58:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +4.16)... 2024-01-22 23:00:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +5.06)... 2024-01-22 23:01:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-22 23:02:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +5.51)... 2024-01-22 23:02:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +5.56)... 2024-01-22 23:02:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 2.42,18.74,4.91,5.64,4.39,6.56,1.32,8.79,3.33,8.21,5.51,3.46,6.25,0.28,7.06,3.16,4.69,-0.58,7.89,6.07,0.63,3.87,5.00,3.67,8.09,3.18,13.89,5.03,4.60,-0.30,2.42,5.19,0.46,2.20,9.54,5.74,4.05,6.45,4.81,5.20,1.02,-1.65,5.03,4.11,1.99,1.63,3.08,4.07,12.38,22.55,5.46,0.91,5.02,5.75,3.30,4.48,-1.67,4.39,1.15,7.52,6.36,4.24,3.68,7.80,9.86,-0.75,3.76,0.32,-0.97,5.87,15.46,5.76,4.28,6.93,7.31,0.87,1.79,2.66,6.89,4.91,2.32,4.10,-1.09,14.00,2.37,9.39,13.84,7.68,4.75,8.82,2.44,5.81,14.45,22.98,11.41,15.23,30.22,3.55,29.86,8.51,8.14,1.48,2.04,3.30,3.62,-0.32,6.43,1.17,6.05,1.48,1.22,5.98,-1.01,5.07,3.53,5.71,7.53,4.58,9.19,14.39,10.82,15.14,12.01,6.42,15.77,6.02,4.82,5.30,3.11,0.63,5.49,4.44,6.65,0.82,2.06,-2.01,4.10,3.94,4.31,3.77,5.44,10.60,5.97,2.40,6.94,0.21,2.37,15.51,5.82,-1.06,12.11,4.40,12.77,7.35,5.80,8.00,-2.64,4.25,3.50,1.17,5.72,1.80,-0.28,3.13,0.17,4.38,0.78,-0.72,1.28,9.17,0.99,15.88,10.10,9.40,9.17,7.81,2.85,8.90,6.35,11.47,-0.72,3.01,6.53,0.54,2.09,-1.52,10.02,5.28,2.50,9.56,5.49,2.10,6.14,7.71,10.25,4.48,2.30,-0.58,2.13,1.79,1.42,5.57,-0.80,4.71,4.93,5.09,8.11,15.49,5.03,5.05,10.78,-1.55,4.99,0.95,10.00,1.53,9.04,5.87,6.90,7.74,8.78,7.64,6.34,-2.30,10.83,3.20,4.10,8.22,7.49,2.30,5.29,1.81,8.42,3.42,-0.21,-0.36,1.60,3.66,3.36,6.05,5.75,2.60,11.25,6.72,9.43,11.64,6.97,-0.79,3.92,-0.82,3.09,8.06,10.40,9.34,5.40,9.41,8.22,1.07,4.61,-0.93,1.17,4.54,6.33,12.21,2.62,5.20,8.51,3.92,9.76,9.20,6.80,0.05,2.62,3.69,2.57,4.96,9.22,0.70,15.77,13.99,13.23,7.35,6.26,7.90,15.01,3.06,3.69,4.83,5.06,-0.92,4.62,7.29,14.25,13.99,10.40,6.15,5.76,21.04,3.04,6.09,0.30,6.97,12.03,9.25,12.11,7.47,5.91,3.50,4.27,10.14,7.14,12.51,-2.94,9.51,8.44,9.67,0.38,4.44,3.17,19.31,-2.10,9.28,7.92,3.01,6.12,12.13,6.36,5.40,3.10,-0.83,2.61,9.20,3.46,18.37,12.63,3.27,5.81,4.31,6.18,8.13,0.27,5.31,4.09,-0.73,7.63,0.18,1.10,1.20,2.66,9.97,6.83,2.87,4.95,7.21,0.69,-0.40,3.73,4.97,1.32,5.82,4.46,5.36,9.94,7.65,2.50,5.56,7.80,-4.05,4.32,-1.49,4.12,5.28,11.75,1.96,0.14,-0.91,2.40,7.55,8.86,1.85,1.20,1.24,10.25,4.41,-4.36,3.35,6.34,6.25,11.30,7.89,5.25,9.67,4.52,5.85,1.00,5.22,4.16,1.44,-0.63,7.63,3.30,1.80,4.95,-0.12,8.36,4.42,5.69,5.91,3.83,6.87,11.22,20.25,7.26,1.33,-0.32,1.47,3.62,14.08,12.12,13.05,13.02,11.36,10.21,7.75,4.40,7.31,0.75,4.77,1.84,7.60,2.71,1.65 2024-01-22 23:02:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 6: train = +4.8345(26.06m/2260) | dev = +5.5937(1.80m/432) 2024-01-22 23:02:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-22 23:05:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +5.41)... 2024-01-22 23:07:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +4.24)... 2024-01-22 23:09:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +4.13)... 2024-01-22 23:12:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +4.68)... 2024-01-22 23:14:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +4.69)... 2024-01-22 23:16:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +4.35)... 2024-01-22 23:19:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +4.26)... 2024-01-22 23:21:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +4.27)... 2024-01-22 23:23:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +4.44)... 2024-01-22 23:25:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +4.24)... 2024-01-22 23:28:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +3.95)... 2024-01-22 23:28:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-22 23:29:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +4.70)... 2024-01-22 23:30:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +4.73)... 2024-01-22 23:30:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 1.10,17.79,3.95,3.98,3.57,5.98,0.82,7.70,2.32,7.12,4.90,3.02,5.01,-0.32,6.43,2.23,3.77,-1.27,5.72,4.99,0.67,2.96,4.47,2.89,7.27,2.62,12.97,3.82,3.37,-1.47,0.50,3.21,-0.97,1.18,8.44,5.31,3.20,5.23,3.78,3.67,0.01,-2.00,3.92,3.53,1.92,1.43,2.39,3.66,11.89,21.67,4.68,0.53,4.31,4.74,1.64,3.78,-1.96,3.95,0.78,6.79,5.26,3.90,2.49,6.21,8.46,-1.03,3.58,-0.12,-1.43,5.76,14.33,5.15,3.97,6.15,6.40,0.85,1.24,1.98,6.28,3.93,1.10,2.56,-2.04,13.02,1.70,8.04,13.66,7.32,3.73,7.87,1.86,4.75,12.56,22.24,10.56,14.82,28.77,3.06,27.97,7.36,7.29,1.07,1.46,2.93,3.15,-0.63,5.40,0.37,4.88,1.07,0.66,5.09,-2.11,4.75,2.84,4.84,5.68,3.51,7.39,12.54,10.00,13.75,10.92,6.03,14.53,5.92,4.50,4.59,1.64,0.04,3.99,3.98,5.80,-0.23,1.08,-2.36,3.63,3.29,3.94,2.87,4.16,10.00,5.05,0.88,6.04,-0.31,1.52,14.53,5.13,-1.31,11.80,3.52,11.93,6.81,4.63,7.19,-3.05,3.84,2.91,0.80,5.42,1.41,-1.33,1.70,-0.28,3.54,-0.21,-1.34,0.54,8.59,0.79,15.11,9.52,8.73,8.87,7.13,2.05,7.89,5.93,11.12,-1.12,2.15,5.44,0.00,1.68,-2.11,9.33,4.66,1.86,8.55,5.15,1.78,5.52,6.74,9.08,3.87,0.93,-0.96,1.49,1.50,1.08,5.27,-1.05,3.88,4.55,3.74,6.87,13.84,3.97,4.09,9.50,-2.26,3.80,0.48,8.79,0.70,7.90,4.72,6.86,6.89,7.24,6.94,5.53,-3.44,10.47,3.56,3.94,7.22,6.31,1.79,3.72,0.53,7.65,3.24,-0.24,-1.78,0.95,3.01,1.70,4.84,5.39,2.50,10.08,5.37,8.29,10.83,6.74,-1.92,1.68,-1.04,3.14,6.96,9.10,8.44,4.53,7.40,7.27,0.85,4.02,-1.06,0.98,4.00,4.74,10.79,2.00,4.70,7.81,3.02,9.29,8.59,5.69,-0.64,2.17,3.07,1.40,4.15,8.30,0.33,14.43,13.65,12.79,6.64,4.94,6.83,13.73,2.22,1.78,3.84,4.10,-1.65,3.41,6.23,13.71,12.57,8.92,4.69,4.55,19.26,1.71,4.85,0.14,6.22,11.12,8.07,10.94,7.46,4.63,2.59,4.30,7.78,5.93,11.18,-3.40,7.84,7.71,7.10,0.13,4.23,2.74,17.60,-2.97,7.88,6.45,1.77,4.81,11.06,6.00,4.67,2.64,-0.83,2.82,8.13,2.68,15.43,11.92,2.18,5.12,3.43,5.89,7.69,-0.85,4.70,3.58,-0.88,6.51,-0.24,1.40,0.86,2.25,8.81,5.75,2.75,4.39,6.35,0.28,-0.48,3.49,4.33,0.44,4.91,4.08,4.88,8.09,7.07,1.89,5.66,6.60,-4.50,3.49,-1.74,3.86,5.00,11.08,1.37,0.10,-1.67,1.66,6.57,8.36,1.08,0.29,0.54,9.46,4.36,-4.40,2.46,5.88,5.90,9.52,6.62,4.46,8.99,3.46,4.70,0.66,4.73,3.27,0.14,-1.81,6.13,2.78,1.68,4.19,-0.74,7.80,3.58,4.78,5.49,2.92,5.27,9.91,19.72,6.80,1.28,-1.36,0.93,2.96,13.16,11.42,12.00,12.35,10.21,9.59,6.21,3.41,6.80,0.84,3.47,1.25,6.46,2.13,1.34 2024-01-22 23:30:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 7: train = +4.4321(25.95m/2260) | dev = +4.7825(1.82m/432) 2024-01-22 23:30:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-22 23:33:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +4.92)... 2024-01-22 23:35:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +4.52)... 2024-01-22 23:37:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +3.79)... 2024-01-22 23:40:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +4.22)... 2024-01-22 23:42:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +4.72)... 2024-01-22 23:44:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +3.71)... 2024-01-22 23:46:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.71)... 2024-01-22 23:49:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +4.02)... 2024-01-22 23:51:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +4.13)... 2024-01-22 23:53:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +4.13)... 2024-01-22 23:55:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +4.07)... 2024-01-22 23:56:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-22 23:57:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +4.81)... 2024-01-22 23:58:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +5.18)... 2024-01-22 23:58:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 1.34,17.70,3.74,4.72,3.48,6.31,1.12,7.74,2.58,8.51,5.26,2.98,6.06,-0.85,6.39,2.33,4.28,-1.08,6.84,5.07,-0.01,3.13,4.17,3.21,7.58,2.46,13.25,4.18,3.95,-0.90,0.87,3.68,-0.79,1.24,8.49,6.11,3.01,5.48,3.76,4.66,0.69,-2.21,4.29,3.18,1.40,0.86,2.01,3.62,11.73,21.93,4.67,-0.01,3.96,4.73,1.98,3.45,-2.31,4.58,1.13,7.41,5.74,3.67,2.78,6.31,8.65,-1.02,3.62,-1.08,-1.73,5.92,15.28,4.81,3.36,6.16,6.18,-0.23,1.44,1.75,6.48,3.12,0.92,2.31,-2.45,14.16,2.13,9.20,14.39,6.54,4.23,7.73,1.55,4.94,13.14,22.35,11.11,15.04,29.14,2.64,28.57,7.87,7.79,0.89,1.66,2.94,3.15,-1.02,5.58,0.58,4.80,0.90,0.57,4.92,-1.63,4.83,2.75,4.92,6.39,3.86,7.66,13.48,10.43,14.33,11.17,5.77,14.72,5.55,4.34,4.51,1.81,-0.19,3.55,4.06,5.76,0.29,1.24,-2.18,3.77,3.44,4.00,2.84,3.92,9.74,4.94,1.31,5.71,0.59,0.97,15.45,5.24,-1.40,11.73,3.05,11.69,6.92,5.70,7.64,-3.01,3.66,2.65,-0.51,5.15,1.24,-1.17,2.21,-0.57,3.71,-0.34,-0.93,0.60,8.30,0.37,17.26,9.58,9.14,8.24,7.05,2.94,8.42,6.28,10.95,-1.21,2.15,5.51,-0.40,1.34,-1.95,9.15,5.57,2.41,9.21,4.69,0.74,5.95,7.10,9.43,3.54,2.43,-1.16,1.50,1.28,0.33,5.10,-1.46,3.80,4.29,3.67,6.81,15.19,4.15,3.88,9.76,-2.99,3.73,0.16,9.23,1.05,7.33,4.38,7.42,7.04,7.18,7.60,6.13,-3.80,10.46,3.22,3.11,7.14,6.60,1.87,4.92,1.83,7.44,3.07,-0.45,-1.77,0.39,5.35,1.58,4.29,5.07,1.94,11.71,5.39,8.84,11.59,6.68,-1.88,2.95,-1.40,3.20,6.59,9.23,8.84,5.13,8.07,7.26,1.53,4.16,-1.31,1.06,4.42,5.28,11.42,3.55,5.29,7.85,2.67,10.58,9.78,6.65,-1.32,2.52,3.42,2.14,5.03,9.68,0.07,16.45,14.65,13.85,7.35,5.63,6.92,14.20,3.51,2.68,5.15,5.55,-1.63,3.83,6.45,14.16,14.56,9.64,5.93,5.77,21.62,2.85,5.46,0.05,7.66,13.51,9.42,12.86,7.87,4.93,2.73,4.60,9.79,6.73,12.25,-2.96,9.59,8.04,8.12,0.65,4.54,2.86,19.05,-2.99,8.99,7.32,1.79,5.19,12.22,6.89,4.44,2.14,-1.21,2.56,8.34,4.23,17.91,13.22,3.52,5.80,3.83,5.56,7.70,-0.08,4.61,5.02,-1.07,6.83,-0.55,1.20,0.85,2.81,8.47,5.55,2.49,4.49,6.55,0.50,-0.66,3.22,4.03,0.95,6.50,4.54,5.10,9.23,7.35,2.60,6.55,8.32,-4.63,4.09,-1.42,4.07,5.20,11.14,2.08,0.21,-1.03,2.27,8.09,8.43,1.19,0.86,1.10,9.73,4.25,-5.03,2.72,6.25,5.96,10.62,6.69,4.07,9.69,4.67,4.71,0.66,4.91,4.49,0.50,-1.45,7.77,3.56,1.60,4.51,0.04,8.74,4.96,5.14,5.61,2.93,5.65,10.16,20.12,7.03,0.87,-1.21,0.57,4.80,15.22,12.21,12.35,12.66,11.62,9.96,6.85,3.44,7.22,1.16,3.84,1.11,6.28,3.24,1.87 2024-01-22 23:58:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 8: train = +4.1610(25.99m/2260) | dev = +5.0722(1.83m/432) | no impr, best = 4.7825 2024-01-22 23:58:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 00:01:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +4.37)... 2024-01-23 00:03:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +4.03)... 2024-01-23 00:05:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +3.86)... 2024-01-23 00:07:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +3.75)... 2024-01-23 00:10:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +3.72)... 2024-01-23 00:12:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +4.80)... 2024-01-23 00:14:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.73)... 2024-01-23 00:17:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +3.90)... 2024-01-23 00:19:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +3.89)... 2024-01-23 00:21:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +3.69)... 2024-01-23 00:23:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +3.70)... 2024-01-23 00:24:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 00:25:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +4.78)... 2024-01-23 00:26:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +5.08)... 2024-01-23 00:26:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 2.13,18.44,4.04,4.41,3.87,5.81,1.33,7.99,1.71,7.80,5.61,2.01,5.58,-1.16,6.56,2.64,3.88,-0.90,7.49,4.60,-0.74,3.02,4.03,2.52,7.14,2.70,13.98,5.08,3.79,-0.42,2.20,4.54,-0.27,1.32,8.73,6.26,2.99,5.58,3.46,4.70,1.14,-2.68,3.92,3.02,1.61,1.51,1.81,4.47,12.98,22.14,4.93,0.33,4.31,5.15,2.15,3.29,-1.91,4.82,-0.51,5.86,4.73,3.86,3.37,7.46,8.79,-0.97,3.30,-2.42,-1.76,5.60,15.73,4.22,2.65,5.77,7.11,0.72,1.10,1.66,6.81,4.13,1.40,2.33,-2.54,13.99,2.50,9.06,12.84,5.66,3.19,8.24,1.83,4.88,14.39,22.81,11.25,15.34,29.64,2.64,29.45,8.21,8.17,1.48,1.15,2.51,3.06,-0.62,5.85,0.23,5.81,1.39,0.50,5.14,-2.03,4.80,1.89,4.66,6.58,3.99,7.28,13.57,10.56,14.72,11.04,5.12,14.35,5.84,4.42,4.25,1.81,-0.33,4.33,4.85,6.21,0.45,1.39,-2.24,2.79,3.08,3.56,3.02,5.38,9.89,5.02,1.91,5.88,0.16,-0.15,14.45,4.68,-1.19,12.08,1.76,10.82,7.31,4.40,6.60,-2.87,3.99,2.28,-1.41,4.88,1.30,-1.51,1.06,-0.18,3.61,-0.10,-0.99,0.67,8.30,-1.54,16.57,9.63,7.95,7.06,6.48,3.08,9.06,5.50,9.87,-0.99,2.20,5.66,-0.42,1.58,-2.17,9.41,6.09,2.18,9.14,4.89,0.23,5.56,7.80,9.70,3.89,1.84,-1.25,1.51,1.32,-0.47,4.41,-2.18,4.38,5.00,3.94,6.89,14.97,4.10,4.60,9.77,-3.36,4.19,0.16,9.24,0.51,6.82,3.45,7.19,6.74,7.38,7.97,5.97,-3.98,10.19,3.08,3.38,7.51,6.11,1.97,5.14,1.15,7.53,3.19,-0.81,-1.57,-0.15,5.06,2.04,4.53,5.14,1.97,12.23,4.66,8.25,11.30,6.64,-1.56,3.30,-1.67,3.13,6.99,9.54,9.14,5.04,8.09,6.97,1.21,4.19,-1.39,0.92,4.16,5.43,12.15,2.50,5.44,7.72,2.79,10.58,9.54,5.69,-2.11,3.10,3.50,2.24,5.38,9.17,0.12,15.89,15.23,13.59,7.25,5.26,6.80,14.61,3.48,3.17,4.99,5.36,-1.85,3.47,6.68,14.29,14.00,9.39,6.18,5.68,21.20,2.70,5.39,-0.35,6.95,11.84,8.96,12.08,7.48,5.60,2.98,4.06,10.02,7.68,12.25,-3.19,9.30,8.25,8.48,0.52,4.12,2.68,18.57,-3.87,8.02,7.86,1.27,5.15,11.62,6.56,5.15,1.85,-1.66,2.25,8.45,3.17,17.24,13.55,3.79,5.68,4.66,5.66,8.05,-0.38,5.00,6.07,-1.06,7.41,-0.36,1.13,0.85,2.28,8.90,5.47,2.49,4.50,6.62,0.46,-0.56,3.35,3.95,0.77,6.04,4.33,5.12,9.16,7.10,1.99,7.19,8.28,-4.18,4.12,-1.79,4.24,5.15,10.98,2.07,0.21,-1.57,1.15,7.62,8.54,0.57,0.37,1.22,10.03,4.15,-5.38,2.85,6.30,5.59,10.43,6.60,4.46,9.77,4.05,4.38,0.52,4.79,4.43,0.50,-2.16,7.67,3.88,1.53,4.42,-0.28,8.62,5.09,4.96,5.77,2.79,5.70,10.44,19.91,7.02,0.65,-1.47,-0.21,4.12,14.52,11.91,12.33,12.48,12.00,9.96,6.67,2.82,7.54,0.61,3.96,0.67,6.57,3.26,1.32 2024-01-23 00:26:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 9: train = +3.9446(26.06m/2257) | dev = +5.0061(1.81m/432) | no impr, best = 4.7825 2024-01-23 00:26:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 00:28:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +4.12)... 2024-01-23 00:31:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.54)... 2024-01-23 00:33:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +3.67)... 2024-01-23 00:35:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +3.84)... 2024-01-23 00:38:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +3.66)... 2024-01-23 00:40:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +3.42)... 2024-01-23 00:42:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.67)... 2024-01-23 00:44:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +4.09)... 2024-01-23 00:47:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +3.49)... 2024-01-23 00:49:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +3.85)... 2024-01-23 00:51:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +3.79)... 2024-01-23 00:52:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 00:53:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +4.25)... 2024-01-23 00:54:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +4.19)... 2024-01-23 00:54:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 1.08,17.19,3.13,3.03,3.45,6.12,0.77,8.24,1.37,6.87,5.10,1.90,3.73,-1.30,6.73,2.29,3.23,-1.18,5.51,3.71,-1.30,1.64,4.73,3.15,7.26,2.12,13.21,3.89,2.44,-1.68,0.62,3.29,-1.03,1.10,9.05,5.53,2.85,5.14,3.55,3.76,0.21,-2.10,4.03,3.22,2.32,1.47,1.59,3.61,11.64,20.82,3.97,0.26,5.01,5.23,1.60,3.39,-2.44,4.26,-1.38,4.34,2.76,4.08,2.08,5.45,7.83,-1.13,3.91,-2.24,-2.31,5.49,14.59,3.82,2.59,5.11,6.91,0.81,1.54,1.75,6.02,3.76,1.14,2.29,-1.99,12.63,1.46,8.01,11.03,5.27,1.80,7.82,1.86,4.19,12.40,22.37,10.96,14.39,28.02,3.18,27.48,6.98,6.81,1.68,0.90,2.79,3.60,-0.45,5.21,-0.17,4.94,1.33,0.30,4.78,-2.67,4.52,2.15,4.61,5.97,3.46,6.53,12.14,9.79,13.14,10.83,4.88,14.17,5.78,4.56,4.74,1.35,-0.26,3.66,3.85,5.83,-0.65,0.50,-1.90,2.71,1.45,1.77,2.57,3.93,8.98,4.93,0.03,5.36,-0.47,0.14,12.95,4.07,-1.06,11.94,1.44,9.88,6.64,3.53,5.46,-3.47,3.92,1.08,-1.85,4.75,1.85,-1.70,0.61,-0.07,3.14,-0.19,-1.26,0.25,7.23,-2.19,15.02,9.42,7.00,7.17,5.80,1.99,7.56,4.69,8.72,-1.24,2.35,5.51,-0.53,1.82,-2.22,9.11,4.33,1.84,8.81,4.66,0.45,4.62,6.73,8.86,3.66,0.53,-0.91,0.83,1.70,0.13,4.39,-2.46,3.75,4.52,3.50,7.07,13.98,3.76,3.74,9.39,-3.07,3.86,0.32,8.49,-0.06,6.66,2.87,5.96,5.96,7.26,6.63,4.70,-3.63,9.24,2.99,2.51,6.47,5.62,1.85,3.34,0.08,6.97,2.94,-0.79,-2.51,-0.37,2.74,1.73,4.00,4.56,1.62,9.71,4.14,7.00,10.76,6.07,-2.54,1.16,-1.65,2.76,6.59,8.74,7.94,4.26,6.26,6.00,0.17,3.37,-1.80,0.66,4.17,4.05,9.79,1.70,4.46,6.70,3.10,9.09,9.43,4.69,-1.99,2.12,2.48,1.31,4.04,7.84,-0.31,13.40,12.66,12.41,6.39,4.15,5.72,13.21,1.81,2.07,3.57,4.64,-2.94,2.75,5.79,13.32,12.37,8.43,4.38,3.71,18.80,1.53,3.98,-0.63,5.70,10.46,7.41,10.45,6.47,4.36,2.19,4.28,7.90,4.96,10.59,-3.60,8.30,7.34,6.59,-0.47,3.49,2.44,17.02,-4.28,6.99,6.76,1.65,4.53,10.33,6.13,4.54,1.28,-1.13,2.04,7.43,2.12,15.22,11.38,1.75,4.97,2.28,5.03,7.18,-1.56,4.07,3.04,-1.21,5.75,-0.55,0.76,0.49,1.93,8.22,5.19,2.14,3.82,5.55,-0.77,-0.53,2.67,3.17,-0.32,5.47,3.60,4.53,7.55,5.75,1.51,4.83,6.23,-4.55,3.13,-2.16,3.38,4.48,9.90,1.03,0.04,-2.33,0.93,5.88,8.21,0.57,-0.63,0.40,9.37,3.56,-5.49,1.72,5.33,5.38,8.50,6.14,3.70,8.83,2.73,3.36,0.25,3.80,2.78,-0.78,-2.07,5.65,2.44,1.06,3.76,-1.65,7.29,3.25,4.64,4.11,2.65,4.93,9.30,18.61,6.17,0.67,-1.80,-0.46,2.83,11.99,10.93,11.08,11.35,9.70,9.00,5.57,2.22,6.20,0.17,2.66,-0.84,5.25,1.54,0.94 2024-01-23 00:54:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 10: train = +3.7352(26.12m/2259) | dev = +4.2714(1.82m/432) 2024-01-23 00:54:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 00:56:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +4.08)... 2024-01-23 00:59:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.81)... 2024-01-23 01:01:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +3.50)... 2024-01-23 01:03:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +3.73)... 2024-01-23 01:05:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +3.66)... 2024-01-23 01:08:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +3.38)... 2024-01-23 01:10:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.58)... 2024-01-23 01:12:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +3.84)... 2024-01-23 01:15:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +3.49)... 2024-01-23 01:17:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +3.29)... 2024-01-23 01:19:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +3.17)... 2024-01-23 01:20:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 01:21:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +4.20)... 2024-01-23 01:21:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +4.50)... 2024-01-23 01:22:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 1.30,17.77,2.95,3.25,3.54,6.02,0.49,8.06,0.80,6.29,5.27,0.92,3.66,-1.46,6.87,1.91,3.32,-1.23,6.06,3.82,-1.66,1.48,4.49,2.71,7.26,2.11,13.79,3.80,1.99,-2.08,0.83,3.07,-0.86,1.21,8.58,5.08,2.41,4.86,3.11,3.92,0.56,-2.75,3.74,3.16,2.00,1.13,1.55,3.65,12.13,21.27,3.92,0.26,4.74,5.37,1.31,3.38,-2.39,4.28,-1.46,4.31,2.83,3.93,2.33,6.09,7.85,-0.96,3.56,-2.69,-2.38,5.53,15.22,4.00,1.92,5.22,6.76,0.28,0.50,1.50,6.16,4.18,1.25,1.65,-2.19,13.29,1.83,8.06,11.24,5.20,2.03,8.33,1.28,4.39,12.72,22.94,11.41,14.73,28.47,3.17,28.20,6.89,7.06,1.36,0.51,2.39,3.65,-0.79,4.73,-0.09,5.18,1.28,0.40,4.93,-2.70,4.59,1.58,4.06,6.10,3.23,6.61,12.22,9.63,14.22,10.90,4.25,13.64,5.62,4.65,4.21,1.59,-0.34,3.67,3.72,5.84,0.44,0.50,-1.54,2.36,1.53,1.51,2.32,4.92,9.34,5.07,0.21,5.17,-0.36,-0.37,12.57,3.54,-1.33,12.06,0.76,9.83,6.85,3.87,5.08,-3.63,4.14,0.16,-1.81,4.59,1.43,-2.14,0.05,-0.30,3.12,-0.07,-1.28,0.42,6.67,-2.43,15.39,9.73,7.16,6.72,5.50,2.04,7.99,4.02,8.60,-1.13,2.36,5.25,-0.35,1.80,-2.61,9.04,5.31,1.48,8.88,3.99,-0.26,4.29,6.59,8.67,3.58,0.73,-1.43,0.80,1.70,-0.96,3.50,-2.37,4.06,4.53,3.64,6.91,14.53,4.06,4.09,9.35,-3.35,3.82,0.03,8.34,-0.21,6.55,2.88,6.64,5.87,7.38,7.74,5.41,-4.96,8.37,3.48,3.17,6.87,5.65,1.91,4.26,1.39,7.01,3.44,0.08,-3.10,-1.49,2.94,1.02,3.76,4.71,2.22,10.22,3.74,5.97,11.28,6.77,-2.47,1.68,-1.37,4.06,6.42,8.26,8.55,4.28,6.16,5.51,0.71,3.26,-1.52,1.45,4.97,4.36,10.06,2.89,5.10,6.18,1.73,9.23,9.32,4.54,-2.58,2.54,2.76,1.75,5.29,7.93,-0.63,14.94,14.44,13.50,7.29,4.66,6.05,13.92,2.78,2.63,4.29,6.70,-2.58,2.45,6.65,13.79,13.44,8.54,5.07,4.76,19.70,1.53,3.25,0.04,6.31,10.20,7.80,11.37,7.63,4.65,2.19,4.72,9.46,5.86,11.12,-3.55,8.29,7.79,6.91,-0.76,4.13,2.67,17.51,-4.55,7.40,6.75,1.41,4.61,10.72,6.46,4.11,0.51,-1.22,3.10,7.30,2.35,15.25,12.41,1.96,4.99,2.04,5.33,7.81,-1.01,4.36,4.64,-0.21,6.33,-0.17,1.64,1.88,1.97,8.56,5.30,2.43,4.70,6.27,-0.42,-0.11,3.72,2.90,-0.66,5.91,4.02,5.08,7.96,5.91,1.60,6.12,7.53,-4.28,3.78,-1.62,4.69,5.00,10.17,1.86,0.44,-2.03,0.83,7.41,8.75,0.05,-1.20,0.26,9.97,3.56,-5.41,2.51,5.89,4.65,8.06,5.85,4.14,9.14,2.86,3.61,0.82,4.57,3.58,-0.51,-2.17,6.74,3.68,1.46,3.97,-0.92,7.87,4.62,4.92,4.65,3.13,5.12,9.64,19.37,7.07,1.05,-2.04,-0.34,3.22,12.56,11.17,11.39,12.36,10.54,10.35,4.81,1.74,6.68,1.29,2.68,-1.42,5.31,2.09,0.82 2024-01-23 01:22:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 11: train = +3.5881(25.96m/2260) | dev = +4.4193(1.82m/432) | no impr, best = 4.2714 2024-01-23 01:22:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 01:24:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.66)... 2024-01-23 01:26:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.99)... 2024-01-23 01:29:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +2.81)... 2024-01-23 01:31:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +3.92)... 2024-01-23 01:33:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +3.07)... 2024-01-23 01:36:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +3.17)... 2024-01-23 01:38:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.35)... 2024-01-23 01:40:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +3.51)... 2024-01-23 01:42:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +3.60)... 2024-01-23 01:45:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.99)... 2024-01-23 01:47:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +4.45)... 2024-01-23 01:48:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 01:48:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.90)... 2024-01-23 01:49:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.99)... 2024-01-23 01:49:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 1.07,17.03,3.51,3.24,3.17,5.67,0.63,7.74,0.15,6.10,4.98,0.62,2.96,-1.67,6.51,1.97,3.09,-1.63,5.55,3.41,-1.56,1.17,4.34,2.24,6.75,1.58,13.42,3.55,2.05,-2.30,0.18,2.78,-1.68,0.70,8.06,5.61,2.46,4.40,3.06,3.73,0.22,-3.19,2.89,2.96,2.10,0.69,1.05,3.09,12.16,20.99,3.84,-0.49,3.97,4.89,0.99,2.83,-2.80,4.36,-1.41,4.24,2.61,3.59,1.93,5.79,7.64,-1.45,3.79,-2.81,-2.60,5.66,14.70,3.14,1.90,4.97,6.59,-0.05,0.20,0.93,5.81,3.26,1.01,1.99,-2.57,12.62,1.80,8.10,11.31,5.27,1.49,7.30,0.73,3.64,12.12,22.14,10.25,14.03,28.51,1.96,27.67,6.64,6.90,1.10,0.51,2.03,3.12,-1.34,4.33,-0.41,4.90,0.81,0.16,4.40,-2.95,4.49,1.34,3.86,5.96,2.60,6.24,12.15,9.83,13.22,10.30,4.34,13.51,5.62,4.20,3.70,1.07,-0.69,3.08,3.28,5.53,-0.93,0.05,-2.29,2.24,1.47,1.66,1.90,3.73,8.96,4.50,-0.45,5.26,-0.77,-0.90,12.55,3.24,-1.14,12.00,1.13,9.65,6.46,3.34,5.30,-3.89,3.77,0.48,-2.12,4.37,1.23,-2.89,0.29,-0.28,3.14,-0.47,-1.50,-0.42,6.88,-2.56,15.47,9.60,7.06,6.97,5.64,1.68,7.64,3.86,8.75,-1.65,1.63,4.93,-0.99,1.23,-2.85,9.05,4.32,1.30,8.89,4.09,-0.31,4.25,6.60,8.78,3.60,0.28,-1.68,0.61,1.46,-1.18,3.04,-2.78,3.53,4.30,3.28,6.16,14.34,3.62,4.06,9.13,-3.47,3.77,0.13,8.49,-0.25,6.14,2.54,5.95,5.51,6.26,6.68,4.85,-5.44,8.37,3.49,2.56,6.83,5.31,1.41,3.82,0.03,6.72,2.86,-1.14,-3.31,-1.36,1.63,0.71,3.34,4.50,1.75,9.95,3.38,6.17,11.55,6.70,-2.55,1.40,-1.90,2.87,5.98,7.89,7.72,3.91,5.77,5.24,0.05,2.93,-1.98,0.22,3.38,3.93,9.33,1.80,4.34,6.01,1.48,9.08,8.69,4.75,-2.54,1.93,2.41,1.37,4.15,7.47,-0.74,13.61,13.20,12.48,6.95,5.01,6.10,13.39,2.15,1.73,4.37,3.64,-3.04,2.45,5.99,13.82,12.86,8.29,4.48,3.94,19.24,0.76,3.33,-0.80,5.11,10.04,7.43,10.32,6.66,4.54,1.99,3.26,7.57,5.43,10.75,-4.00,7.33,7.07,6.43,-0.84,3.99,2.14,17.11,-4.46,6.76,6.13,0.63,3.90,10.56,5.85,3.82,0.49,-1.65,1.92,6.91,1.91,15.42,11.83,1.66,4.74,1.85,5.13,7.16,-1.59,4.16,2.95,-1.52,5.76,-0.52,0.71,0.22,1.40,8.09,4.92,2.08,3.71,5.40,-0.49,-1.25,1.75,3.00,-0.37,5.14,3.34,4.29,7.64,5.99,1.38,4.88,6.31,-5.17,3.03,-2.85,3.22,4.29,10.00,0.75,0.20,-2.30,0.67,5.94,7.80,0.22,-1.30,-0.37,9.69,3.65,-5.59,1.79,5.23,4.40,8.53,5.88,3.70,9.01,2.52,3.53,0.13,4.49,2.45,-0.71,-2.86,5.26,2.35,1.17,3.72,-1.74,7.51,3.21,4.32,4.01,2.51,4.71,9.37,18.68,6.28,0.37,-2.25,-0.94,2.72,12.18,11.00,11.23,12.04,10.05,9.26,4.82,1.71,6.36,-0.04,2.61,-1.43,5.24,1.56,0.73 2024-01-23 01:49:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 12: train = +3.5416(25.98m/2259) | dev = +4.0072(1.68m/432) 2024-01-23 01:49:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 01:52:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.39)... 2024-01-23 01:54:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.00)... 2024-01-23 01:56:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +3.82)... 2024-01-23 01:59:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +4.10)... 2024-01-23 02:01:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +3.57)... 2024-01-23 02:03:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +2.75)... 2024-01-23 02:06:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.52)... 2024-01-23 02:08:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +3.26)... 2024-01-23 02:10:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +2.90)... 2024-01-23 02:12:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +4.12)... 2024-01-23 02:15:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +2.87)... 2024-01-23 02:15:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 02:16:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.49)... 2024-01-23 02:17:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.58)... 2024-01-23 02:17:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 0.60,16.24,2.86,2.77,2.63,4.73,0.45,6.59,-0.45,5.40,4.24,0.43,2.73,-1.72,5.96,1.52,2.43,-2.21,4.82,2.96,-1.62,1.62,4.01,1.87,6.50,1.80,12.53,2.96,1.45,-2.38,0.18,2.45,-1.65,0.20,7.57,5.41,1.84,4.16,2.59,3.27,0.22,-3.36,2.59,2.40,1.61,0.08,0.65,2.83,11.22,20.28,3.40,-0.76,3.84,4.71,0.37,2.70,-3.04,3.77,-1.88,4.13,2.30,3.26,1.45,5.07,7.07,-1.95,3.04,-3.07,-3.18,4.82,13.80,2.94,1.29,4.23,5.88,-0.81,-0.23,0.72,5.39,3.13,0.42,1.00,-2.97,12.29,0.71,7.66,10.88,4.64,1.27,6.89,0.26,3.46,11.94,21.33,10.15,13.40,27.52,1.33,26.88,6.19,6.74,0.53,-0.12,1.51,3.21,-1.63,4.25,-0.39,4.20,0.55,-0.53,4.11,-3.10,4.36,0.80,3.28,5.32,2.47,6.10,11.44,9.95,12.47,9.41,3.85,12.44,5.22,3.76,3.35,0.67,-1.04,2.79,3.22,4.48,-1.32,0.10,-2.70,1.83,0.96,1.85,2.15,3.33,8.56,4.03,-0.18,4.61,-1.17,-1.45,11.97,3.30,-1.92,11.02,0.17,8.93,5.84,3.23,4.63,-3.96,3.40,0.36,-2.81,4.19,1.17,-2.68,-0.16,-0.12,2.59,-0.79,-1.81,-1.10,6.10,-2.90,14.59,8.67,6.46,6.15,5.44,1.43,7.45,3.87,8.28,-1.54,1.28,4.83,-0.74,1.23,-2.38,8.45,4.70,0.75,8.53,3.77,-0.59,3.97,6.24,8.33,2.71,-0.26,-2.21,0.12,0.87,-1.84,2.78,-2.98,3.11,3.82,2.99,5.67,13.07,3.17,3.38,8.78,-3.64,3.32,-0.15,7.93,-0.42,5.34,2.11,5.63,5.13,5.53,6.51,4.38,-5.75,8.05,2.74,2.42,6.52,4.82,0.56,3.52,-0.42,6.43,2.57,-1.51,-3.62,-1.92,2.77,0.27,2.91,4.02,0.71,9.24,2.82,5.22,10.20,6.12,-2.61,1.14,-2.32,2.57,5.39,7.65,7.22,3.43,5.56,4.74,-0.47,2.12,-1.52,0.10,2.96,3.23,8.98,1.39,4.07,5.18,1.05,9.67,8.41,4.14,-3.37,1.34,2.36,1.56,4.02,6.75,-1.26,13.02,12.87,11.76,6.31,3.93,5.11,12.74,1.59,1.91,4.00,3.46,-3.30,1.98,5.40,13.41,12.56,8.22,3.92,3.79,18.78,1.25,2.86,-1.31,4.80,9.21,6.55,10.23,6.61,3.94,1.46,3.07,7.30,4.91,10.24,-4.72,7.07,6.68,6.22,-0.77,3.05,1.70,16.54,-4.99,6.80,6.12,0.34,3.29,10.14,5.54,3.30,0.26,-2.23,1.60,6.52,1.91,14.15,11.60,1.40,4.15,1.73,4.45,6.62,-1.92,3.75,4.05,-1.73,5.37,-1.12,0.23,-0.20,1.10,7.41,4.19,1.75,3.41,4.99,-1.13,-1.29,1.64,2.09,-1.10,3.94,2.98,3.97,7.15,5.28,0.55,4.90,5.79,-5.46,2.66,-2.98,2.88,4.02,9.06,0.86,-0.06,-2.45,0.29,5.63,6.93,-0.96,-1.72,-0.37,8.93,3.32,-6.28,1.42,5.16,3.95,7.98,5.16,3.26,8.13,2.55,2.85,-0.28,3.65,2.46,-0.56,-3.03,5.59,2.76,0.67,2.91,-1.80,6.68,4.06,4.04,3.47,2.06,4.45,9.09,18.65,5.93,0.55,-2.50,-0.92,2.33,11.91,10.52,10.59,11.05,9.56,8.52,4.27,0.87,6.09,-0.24,1.73,-1.43,5.28,1.36,0.26 2024-01-23 02:17:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 13: train = +3.4037(25.99m/2259) | dev = +3.6006(1.81m/432) 2024-01-23 02:17:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 02:20:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.07)... 2024-01-23 02:22:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.98)... 2024-01-23 02:24:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +3.31)... 2024-01-23 02:27:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +4.03)... 2024-01-23 02:29:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +3.06)... 2024-01-23 02:31:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +3.66)... 2024-01-23 02:33:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.77)... 2024-01-23 02:36:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +2.75)... 2024-01-23 02:38:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +3.20)... 2024-01-23 02:40:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.31)... 2024-01-23 02:42:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +2.59)... 2024-01-23 02:43:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 02:44:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.38)... 2024-01-23 02:45:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.54)... 2024-01-23 02:45:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 0.56,16.33,2.68,2.58,2.68,4.88,0.64,6.75,0.02,5.92,4.29,0.75,2.90,-1.97,5.50,1.14,2.47,-2.17,5.26,2.81,-1.94,1.04,3.69,1.69,6.13,1.23,12.38,3.23,1.58,-1.92,-0.16,2.33,-2.19,-0.04,7.57,4.99,1.75,3.97,2.37,3.25,-0.38,-3.40,2.70,2.16,1.19,-0.26,1.20,2.77,11.13,20.62,3.41,-0.86,3.50,3.94,0.53,2.57,-3.07,3.59,-1.64,4.03,2.96,2.87,1.54,5.00,6.98,-1.94,2.79,-3.11,-3.64,5.08,13.88,2.94,1.17,4.38,5.74,-0.79,-0.47,0.73,5.76,2.60,0.41,1.01,-3.08,12.20,0.76,7.88,10.96,4.27,1.34,7.03,0.31,3.56,12.05,21.44,9.70,13.61,27.35,1.70,26.92,5.88,6.97,0.55,-0.01,1.37,2.77,-1.68,3.88,-0.91,4.23,0.48,-0.59,3.93,-3.13,4.03,0.84,3.24,5.18,2.16,6.06,11.13,9.32,12.61,9.84,3.66,12.62,5.04,3.53,3.68,0.63,-1.05,3.19,3.01,5.22,-1.00,-0.06,-3.24,1.75,0.96,1.24,1.49,3.18,8.84,4.02,-0.55,4.65,-1.39,-1.28,12.33,3.01,-2.09,10.27,-0.11,8.99,5.80,3.11,4.77,-4.54,2.83,0.27,-2.54,4.28,0.65,-2.55,-0.24,-0.95,2.73,-1.13,-2.03,-0.81,6.33,-3.45,14.20,8.59,6.09,6.02,4.97,1.39,7.17,3.55,8.32,-2.18,1.14,4.54,-0.90,0.72,-3.29,8.12,3.57,1.31,8.24,3.35,-0.79,3.62,6.28,8.33,2.61,-0.29,-2.34,0.06,0.71,-1.65,3.06,-3.42,3.12,3.39,2.93,5.62,13.29,2.89,3.07,8.75,-4.04,3.19,-0.27,7.76,-0.79,5.66,2.24,5.56,4.95,5.96,6.18,4.45,-5.66,8.19,2.50,2.00,6.32,4.87,0.69,3.27,-0.26,6.43,2.37,-1.43,-3.53,-1.73,1.59,0.44,2.81,4.06,1.57,9.38,3.38,5.58,10.05,5.93,-2.98,0.80,-2.24,2.75,5.60,7.90,7.55,3.33,5.87,5.05,-0.72,2.90,-2.18,-0.04,2.91,3.44,9.50,1.13,4.01,5.35,1.18,8.53,8.02,4.05,-3.24,1.44,2.34,0.65,3.83,6.97,-1.48,13.04,12.87,12.15,5.81,3.84,5.19,12.83,1.46,1.63,3.88,3.39,-3.44,2.18,5.41,12.98,12.12,7.79,3.75,3.41,19.05,0.69,2.92,-1.24,4.82,9.02,7.00,10.44,6.59,3.97,1.65,3.21,6.94,4.85,10.67,-4.52,7.27,6.92,6.29,-0.85,3.34,1.75,16.63,-4.96,6.11,5.80,0.37,3.57,10.16,5.39,3.29,-0.07,-1.99,1.43,6.61,1.11,14.62,11.68,1.30,4.21,1.76,4.45,6.59,-1.51,3.78,2.64,-1.77,5.49,-1.21,0.30,-0.53,0.90,7.62,4.29,1.49,3.46,5.03,-1.36,-1.52,1.61,2.42,-0.97,4.05,3.07,4.02,6.90,5.80,0.76,4.58,5.95,-5.64,2.43,-3.27,2.81,4.00,9.73,0.49,-0.29,-2.87,-0.29,5.41,7.15,-0.30,-1.47,-0.57,8.95,3.06,-6.33,1.53,4.92,4.32,8.18,5.26,3.05,8.26,2.10,2.92,-0.10,3.86,2.51,-0.94,-2.78,5.41,2.00,0.84,3.21,-2.12,7.03,2.68,3.83,3.58,1.80,4.39,8.71,18.23,5.80,0.14,-2.75,-1.05,2.30,12.08,10.38,10.93,11.20,9.62,8.58,4.07,1.22,6.01,-0.52,1.96,-1.54,4.86,1.04,0.40 2024-01-23 02:45:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 14: train = +3.2533(26.04m/2259) | dev = +3.5293(1.81m/432) 2024-01-23 02:45:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 02:48:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.89)... 2024-01-23 02:50:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.43)... 2024-01-23 02:52:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +2.95)... 2024-01-23 02:54:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +3.54)... 2024-01-23 02:57:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +3.10)... 2024-01-23 02:59:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +3.59)... 2024-01-23 03:01:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.35)... 2024-01-23 03:04:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +3.09)... 2024-01-23 03:06:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +2.57)... 2024-01-23 03:08:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.72)... 2024-01-23 03:10:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +3.14)... 2024-01-23 03:11:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 03:12:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.00)... 2024-01-23 03:13:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.13)... 2024-01-23 03:13:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 0.85,15.17,2.43,1.89,1.92,4.24,-0.01,5.71,-0.77,5.60,3.86,0.51,2.79,-1.88,4.98,0.86,1.83,-2.53,4.92,2.00,-2.53,1.98,3.20,1.28,5.82,1.04,12.02,2.79,1.14,-2.16,0.06,1.95,-2.31,-0.66,6.84,3.87,0.96,3.98,1.91,3.32,0.89,-3.52,3.00,2.58,0.81,-0.76,0.41,2.28,10.47,19.22,3.03,-1.05,3.14,3.90,0.16,2.03,-3.34,3.56,-1.87,4.03,2.65,2.64,1.10,4.87,6.82,-2.39,2.39,-2.96,-3.80,4.22,13.55,2.40,0.76,3.46,6.14,-0.89,-0.86,0.24,5.03,2.13,-0.04,0.67,-3.07,11.69,0.04,6.89,10.60,4.13,1.38,6.23,0.01,3.39,11.21,19.93,9.27,12.90,26.17,1.23,25.42,5.35,5.98,0.25,-0.46,0.87,2.35,-1.59,3.54,-1.16,3.52,0.24,-1.05,3.31,-3.58,3.32,0.59,2.65,5.19,1.60,5.32,10.57,8.84,12.25,9.11,3.03,12.02,4.64,3.18,2.83,0.25,-1.31,2.16,2.36,4.36,-1.61,-0.74,-3.00,1.28,0.87,2.35,1.63,2.92,8.01,3.42,-0.98,3.99,-1.46,-1.72,11.61,2.34,-2.78,9.57,-0.39,8.04,5.47,3.70,4.60,-4.71,2.75,-0.66,-2.58,3.90,0.96,-2.89,-0.44,-0.88,1.91,-1.46,-2.39,-1.18,5.52,-3.62,13.93,8.11,5.68,5.84,5.08,1.47,6.69,3.45,7.80,-2.35,0.88,3.88,-1.35,0.17,-3.33,7.31,3.42,1.77,7.82,2.94,-1.30,3.44,5.75,8.57,2.27,-0.71,-2.47,-0.40,-0.02,-1.93,2.42,-2.87,2.92,3.01,2.83,5.03,12.02,3.60,2.88,8.05,-3.98,2.69,-0.81,7.01,-1.12,5.32,1.71,5.24,4.57,5.27,5.69,3.45,-6.04,6.97,1.28,1.39,5.46,4.27,0.06,3.50,-0.46,5.74,2.33,-1.76,-3.85,-1.40,0.94,0.05,2.19,3.44,0.56,8.57,2.25,4.53,9.44,5.68,-2.37,0.41,-2.48,2.49,4.74,6.90,6.69,2.66,5.36,4.59,-1.27,1.93,-2.66,-0.11,2.75,3.24,8.60,1.67,3.61,5.50,0.54,7.52,7.13,4.11,-3.22,1.54,2.05,0.70,2.99,6.10,-1.82,12.46,12.63,10.93,5.10,3.13,4.61,12.20,1.66,1.20,3.86,2.80,-3.53,1.63,4.78,12.31,10.99,7.04,3.38,3.19,17.85,0.85,2.93,-1.92,4.44,8.32,5.64,9.78,5.68,3.60,1.21,2.86,6.50,4.72,9.63,-4.46,7.97,6.54,5.97,-1.23,2.76,1.40,15.69,-5.21,6.54,5.51,-0.25,3.14,9.56,5.37,2.77,-0.40,-2.43,0.67,6.77,0.78,13.95,11.08,1.22,4.33,1.13,3.87,5.68,-1.84,3.50,2.20,-2.07,5.30,-1.33,0.04,-0.10,0.74,6.93,3.59,1.25,2.78,4.22,-1.96,-1.32,1.68,2.27,-1.25,3.24,2.30,3.60,6.51,5.33,0.59,4.71,5.25,-5.83,2.01,-3.36,2.54,3.87,8.74,0.23,-0.03,-2.93,-0.84,4.96,6.53,-0.59,-1.96,-0.71,8.25,2.67,-6.17,1.63,4.92,4.34,7.51,4.65,2.79,7.54,1.52,2.54,-0.45,3.26,1.95,-1.49,-3.18,5.23,2.65,0.32,2.55,-2.63,6.34,2.56,3.73,3.20,1.47,4.28,8.20,17.68,5.28,0.35,-3.11,-1.05,2.14,11.60,9.53,9.84,10.24,8.33,7.65,4.32,0.80,5.43,-0.89,1.87,-2.24,4.39,0.37,-0.50 2024-01-23 03:13:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 15: train = +3.1142(26.06m/2259) | dev = +3.1245(1.81m/432) 2024-01-23 03:13:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 03:15:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.91)... 2024-01-23 03:18:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.23)... 2024-01-23 03:20:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +3.06)... 2024-01-23 03:22:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +2.88)... 2024-01-23 03:25:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +3.26)... 2024-01-23 03:27:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +3.15)... 2024-01-23 03:29:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.22)... 2024-01-23 03:31:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +3.23)... 2024-01-23 03:34:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +2.53)... 2024-01-23 03:36:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +3.55)... 2024-01-23 03:38:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +2.55)... 2024-01-23 03:39:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 03:40:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.52)... 2024-01-23 03:41:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.55)... 2024-01-23 03:41:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 0.90,16.38,2.55,2.99,2.53,4.67,0.97,6.30,0.45,6.99,4.29,1.15,3.58,-1.87,5.67,1.44,2.34,-2.04,5.56,3.23,-2.03,1.77,3.64,1.84,6.07,1.53,12.75,3.25,1.67,-2.35,0.70,2.94,-1.98,0.06,7.16,5.14,1.57,3.83,2.29,3.90,-0.07,-3.55,2.74,1.97,0.99,0.16,0.73,2.76,11.23,20.78,3.32,-0.81,3.41,4.02,0.37,2.34,-3.01,3.50,-1.01,4.53,3.47,3.03,1.79,5.65,7.15,-1.91,2.85,-3.31,-3.24,4.48,14.17,2.87,1.03,4.41,5.62,-0.94,-0.08,0.68,5.95,2.38,0.45,1.06,-3.43,12.55,1.22,7.96,12.24,4.67,2.02,7.14,0.66,3.79,12.20,21.05,10.11,13.45,27.17,1.58,26.60,6.29,6.95,-0.09,0.37,1.80,2.55,-1.27,4.52,-0.68,4.29,0.32,-0.35,3.77,-3.28,3.94,0.69,3.18,4.74,2.75,6.39,11.20,8.92,12.46,9.20,4.06,13.02,5.29,3.49,3.52,0.90,-1.22,3.44,3.32,5.21,-1.03,0.34,-2.84,1.98,1.32,1.87,1.84,3.60,8.54,3.63,0.13,4.90,-1.21,-1.21,12.52,3.35,-2.69,10.59,0.10,9.49,5.76,3.89,4.88,-3.88,3.01,0.80,-2.52,4.39,0.63,-2.39,0.03,-1.05,2.94,-1.13,-1.72,-0.57,5.94,-3.06,14.45,8.41,6.30,6.28,5.71,1.75,7.21,3.80,8.36,-2.06,1.10,4.54,-1.04,0.90,-2.34,7.91,3.66,1.22,8.33,3.49,-1.20,4.09,6.90,8.55,2.96,0.25,-2.13,0.26,0.67,-1.77,2.55,-3.18,3.16,3.48,2.96,5.77,13.26,3.32,3.62,8.50,-4.10,3.23,-0.44,7.47,-0.79,5.74,1.96,6.03,5.11,5.82,6.09,4.89,-6.02,7.80,2.29,2.15,6.33,4.82,0.13,3.52,-0.00,6.03,2.12,-1.33,-3.06,-1.51,1.84,0.39,2.81,3.85,0.80,9.73,2.89,5.47,10.22,5.89,-2.54,1.74,-2.51,2.16,4.99,7.76,7.30,3.18,6.41,5.03,-0.56,2.73,-2.18,0.02,2.36,4.12,9.92,1.20,4.08,5.26,1.16,8.59,8.06,4.39,-3.50,1.38,2.49,0.89,3.72,6.67,-1.60,12.60,12.45,12.08,5.77,3.42,5.13,12.67,1.76,1.50,4.00,3.27,-3.23,1.87,5.44,13.01,12.71,7.61,4.95,3.39,18.75,1.08,3.51,-1.34,4.98,9.22,6.59,10.37,6.81,3.76,1.63,3.02,7.04,5.37,10.36,-4.56,7.11,6.65,6.27,-0.39,2.89,1.43,16.34,-4.56,6.23,6.67,-0.22,3.83,10.33,5.65,3.24,0.14,-2.01,1.53,6.60,1.01,14.48,11.74,1.55,4.10,1.77,4.34,6.65,-1.44,3.68,2.69,-1.92,5.48,-1.32,0.29,-0.39,1.11,7.05,3.91,1.63,3.23,4.95,-1.21,-1.25,1.78,2.46,-0.81,4.11,2.81,3.70,7.34,5.31,0.62,4.70,5.85,-5.18,2.56,-2.84,2.51,3.84,9.30,0.29,-0.10,-2.62,-0.31,6.20,6.85,-0.77,-0.85,0.06,8.79,2.95,-6.44,1.43,5.24,4.18,8.35,4.89,3.06,8.08,2.53,2.88,-0.60,3.51,2.74,-0.64,-3.10,5.53,2.17,0.50,3.31,-2.16,7.36,3.02,3.73,3.37,2.05,3.99,8.75,18.09,5.89,0.40,-2.56,-0.61,2.46,12.41,10.19,11.12,10.99,9.79,8.31,4.58,1.47,6.17,-0.39,1.80,-0.51,4.97,1.07,0.49 2024-01-23 03:41:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 16: train = +2.9715(26.00m/2260) | dev = +3.6012(1.83m/432) | no impr, best = 3.1245 2024-01-23 03:41:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 03:43:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.97)... 2024-01-23 03:46:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.32)... 2024-01-23 03:48:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +2.64)... 2024-01-23 03:50:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +2.62)... 2024-01-23 03:52:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +2.85)... 2024-01-23 03:55:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +3.25)... 2024-01-23 03:57:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.16)... 2024-01-23 03:59:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +3.28)... 2024-01-23 04:01:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +2.85)... 2024-01-23 04:04:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +3.53)... 2024-01-23 04:06:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +2.77)... 2024-01-23 04:07:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 04:08:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.52)... 2024-01-23 04:08:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.56)... 2024-01-23 04:09:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 0.96,16.90,3.03,2.56,2.53,5.23,0.29,6.95,0.16,6.92,4.20,0.73,2.87,-1.95,5.81,1.38,2.41,-1.96,5.35,3.11,-2.07,1.32,3.83,1.90,6.34,1.63,12.62,3.41,1.39,-2.35,-0.16,2.64,-2.22,-0.01,7.89,4.77,1.72,4.10,2.44,3.30,0.21,-3.37,2.99,2.22,1.28,0.70,0.68,2.58,11.11,20.49,3.37,-0.79,3.56,4.78,0.35,2.38,-2.84,3.99,-1.69,4.45,2.67,3.41,1.40,5.06,7.15,-1.58,3.04,-3.50,-3.32,5.27,14.23,3.20,1.16,4.31,5.84,-0.17,-0.05,0.84,5.32,2.94,0.61,0.72,-3.26,12.76,1.33,7.54,11.40,4.45,1.33,6.96,0.68,3.89,11.80,21.58,9.85,13.55,27.39,1.54,27.04,6.10,6.67,0.39,-0.01,1.52,2.75,-1.45,4.32,-0.90,4.33,0.49,-0.72,3.90,-2.97,4.04,0.86,3.51,5.42,2.30,5.87,11.89,9.26,13.23,9.86,3.95,12.68,5.09,4.13,3.60,0.59,-1.13,2.58,3.43,5.03,-0.85,-0.31,-2.69,1.98,1.27,0.82,1.73,3.61,8.61,3.89,-0.36,4.78,-0.80,-1.16,12.10,3.31,-1.42,11.17,0.05,8.94,5.93,2.85,4.63,-3.56,3.07,-0.02,-2.58,4.43,1.09,-2.79,0.02,-0.66,2.64,-0.95,-1.76,-0.13,5.60,-2.92,14.72,8.84,6.33,5.92,4.75,2.00,8.13,3.47,8.08,-1.41,1.67,4.84,-0.57,0.73,-3.28,8.14,3.80,1.34,8.59,3.52,-0.86,3.61,6.24,8.22,2.95,0.00,-1.71,0.39,1.01,-1.76,3.03,-2.68,2.71,4.04,2.84,5.50,13.41,3.14,3.19,8.90,-3.93,3.28,-0.17,8.23,-0.75,5.50,2.04,5.48,5.27,5.79,6.63,4.51,-5.86,7.69,2.44,2.04,6.17,4.98,0.91,3.30,-0.42,6.35,2.21,-1.84,-3.42,-1.74,2.14,0.22,2.97,3.96,1.35,9.56,2.98,5.01,10.35,6.15,-3.03,1.38,-2.29,2.50,5.31,7.66,7.47,3.67,5.69,4.74,-1.09,2.49,-2.13,-0.09,2.87,3.67,9.33,1.34,4.10,5.07,1.27,8.64,8.50,4.00,-3.61,1.48,2.37,0.96,3.46,6.81,-1.44,13.09,12.83,11.62,5.58,4.23,5.22,13.09,2.12,1.89,3.72,3.78,-3.32,2.04,5.21,13.04,12.20,7.98,4.33,3.12,19.17,0.97,2.67,-1.21,4.98,9.20,7.29,10.98,6.89,3.78,1.47,2.99,7.64,4.91,10.12,-4.38,7.21,6.93,6.05,-1.05,3.32,1.91,17.07,-5.01,6.13,6.48,0.28,3.85,10.12,5.09,3.37,-0.15,-2.14,1.38,6.57,0.86,14.61,11.16,1.83,4.29,1.41,4.36,6.78,-1.39,3.87,2.74,-1.95,5.30,-1.09,0.16,-0.50,1.04,7.69,4.73,1.73,3.59,5.13,-1.15,-1.48,1.94,2.07,-0.80,4.03,2.96,3.99,7.21,5.75,0.75,5.01,5.98,-5.38,2.41,-3.24,3.14,4.02,9.41,0.39,-0.66,-3.03,0.22,5.38,7.39,-0.86,-1.64,-0.47,8.92,2.95,-6.04,1.42,4.66,3.88,7.80,5.00,2.96,8.44,2.19,3.10,-0.05,3.66,2.48,-0.97,-3.31,5.83,2.61,0.95,3.17,-1.86,7.09,2.98,3.83,3.89,1.95,4.43,9.64,18.57,6.03,0.33,-2.67,-1.00,2.43,11.60,10.09,10.77,11.07,9.70,8.28,4.07,0.90,5.98,-0.15,2.04,-1.90,4.87,1.22,0.26 2024-01-23 04:09:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 17: train = +3.0319(26.02m/2261) | dev = +3.6055(1.82m/432) | no impr, best = 3.1245 2024-01-23 04:09:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 04:11:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.04)... 2024-01-23 04:13:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.61)... 2024-01-23 04:16:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +3.05)... 2024-01-23 04:18:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +2.68)... 2024-01-23 04:20:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +3.21)... 2024-01-23 04:23:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +3.08)... 2024-01-23 04:25:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +3.56)... 2024-01-23 04:27:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +3.11)... 2024-01-23 04:29:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +2.18)... 2024-01-23 04:32:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.71)... 2024-01-23 04:34:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +2.95)... 2024-01-23 04:35:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 04:36:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.09)... 2024-01-23 04:36:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.21)... 2024-01-23 04:36:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 0.18,16.06,1.94,1.94,1.82,4.98,0.27,6.19,-0.38,4.88,4.17,0.26,2.03,-2.08,5.37,1.21,2.10,-2.46,4.77,2.51,-2.59,0.15,3.92,1.64,5.93,0.93,12.29,2.55,1.14,-3.07,-0.70,1.98,-2.53,-0.21,7.08,4.11,1.18,3.88,2.51,3.21,-0.37,-3.33,2.58,2.43,1.29,-0.41,0.52,2.60,10.97,20.19,2.95,-0.95,3.80,4.08,0.15,2.68,-3.31,3.61,-2.35,3.55,2.33,3.02,1.47,4.51,6.60,-2.45,2.84,-3.52,-4.00,4.44,13.58,2.39,0.88,4.00,5.91,-0.99,-0.58,0.62,5.22,2.61,-0.18,0.57,-3.36,11.74,0.53,7.14,9.85,3.63,0.89,6.82,0.12,2.64,11.60,21.25,10.18,13.79,27.14,1.30,26.81,5.94,6.19,-0.07,-0.15,1.23,3.14,-1.61,3.90,-1.02,4.02,0.52,-1.02,3.53,-3.73,3.90,0.52,2.91,5.20,1.84,5.53,10.56,8.57,11.99,9.53,3.41,11.84,4.93,3.60,3.84,0.50,-1.15,3.14,3.16,4.52,-1.23,-0.29,-2.78,1.42,0.79,0.92,1.70,3.35,8.42,3.61,-1.14,3.89,-1.58,-1.70,11.51,2.75,-2.21,10.92,-0.39,8.54,5.75,2.30,4.12,-4.68,2.97,-0.15,-3.10,3.93,0.76,-3.25,-0.38,-0.99,2.45,-1.31,-2.16,-1.09,5.34,-3.86,13.50,8.43,6.03,5.72,4.59,0.79,6.78,3.14,7.75,-2.33,1.03,4.45,-1.61,0.83,-3.42,7.68,3.46,0.22,7.79,3.15,-1.18,3.23,5.84,8.18,2.37,-0.65,-2.36,-0.22,0.46,-2.02,2.42,-3.14,3.27,3.42,2.73,5.37,13.16,2.72,3.13,8.38,-4.15,3.24,-0.57,7.07,-0.98,5.11,1.72,5.42,4.66,5.42,5.60,4.31,-6.08,7.28,2.36,2.27,5.89,4.58,0.13,3.28,-0.76,6.25,2.38,-1.66,-3.95,-1.89,1.42,0.18,2.37,3.64,1.10,8.64,2.64,4.61,9.94,5.63,-3.38,0.31,-2.25,2.88,5.55,7.11,7.24,3.38,5.23,4.95,-1.24,2.00,-2.15,-0.04,3.14,2.96,8.88,0.93,3.62,4.74,0.73,8.20,7.59,3.68,-3.40,1.19,2.05,0.91,3.42,6.32,-1.88,12.53,12.32,11.68,5.28,3.24,4.59,12.37,0.88,0.89,3.62,3.14,-3.67,1.42,5.13,12.74,11.51,7.55,2.91,3.30,18.57,-0.04,2.07,-1.58,4.42,8.71,6.89,9.81,6.08,3.48,1.16,2.86,6.66,3.92,9.56,-4.84,6.86,6.58,5.45,-1.29,2.88,1.35,15.99,-5.14,6.09,5.13,0.27,3.09,9.67,5.17,3.15,0.05,-2.19,1.54,6.15,0.66,13.96,11.71,0.82,4.00,0.71,4.64,6.15,-2.12,3.70,2.32,-1.63,5.17,-1.43,0.13,0.15,0.68,7.23,3.90,1.27,3.07,4.56,-1.79,-1.32,1.66,1.89,-1.15,3.57,2.46,3.82,6.58,5.29,0.64,4.78,5.37,-6.01,2.03,-3.30,2.67,3.84,9.22,0.13,-0.04,-2.92,-0.79,4.98,7.12,-1.09,-2.03,-0.82,8.87,3.05,-6.61,1.70,5.22,3.77,7.62,4.89,2.72,8.04,1.76,2.74,-0.51,3.39,2.01,-1.36,-3.37,4.08,1.77,0.11,2.86,-2.35,6.50,2.79,3.49,3.44,1.81,4.13,8.48,17.93,5.61,0.14,-3.22,-1.24,1.88,11.70,9.97,10.33,10.74,8.84,8.52,3.50,0.51,5.61,-0.14,1.52,-2.51,4.43,0.66,0.27 2024-01-23 04:36:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 18: train = +2.9362(26.12m/2260) | dev = +3.2105(1.81m/432) | no impr, best = 3.1245 2024-01-23 04:36:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 04:39:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.67)... 2024-01-23 04:41:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.51)... 2024-01-23 04:44:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +2.54)... 2024-01-23 04:46:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +2.61)... 2024-01-23 04:48:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +2.11)... 2024-01-23 04:50:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +1.91)... 2024-01-23 04:53:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +2.27)... 2024-01-23 04:55:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +1.84)... 2024-01-23 04:57:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +2.21)... 2024-01-23 05:00:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.31)... 2024-01-23 05:02:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +2.53)... 2024-01-23 05:03:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 05:04:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.33)... 2024-01-23 05:04:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.52)... 2024-01-23 05:04:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 0.07,16.36,2.48,2.34,2.33,5.23,-0.14,6.24,-0.15,5.32,4.23,0.40,3.05,-2.19,5.59,1.42,2.54,-2.66,4.80,2.36,-1.87,0.89,3.75,1.68,6.42,1.30,12.29,2.76,1.46,-2.72,-0.75,1.93,-2.13,-0.07,6.84,4.31,1.20,4.25,2.74,3.18,-0.41,-3.30,2.62,2.25,1.65,-0.38,0.97,2.55,10.85,20.45,3.22,-0.60,3.52,4.05,0.46,3.41,-3.50,3.66,-1.91,4.07,2.47,3.09,1.60,4.97,7.24,-2.56,2.75,-2.52,-3.28,4.51,13.61,2.98,2.05,4.47,6.03,-0.31,-0.13,0.71,4.97,2.59,0.13,1.44,-2.88,12.22,0.77,7.25,11.56,4.68,1.43,7.31,0.42,3.16,11.58,21.02,10.03,13.30,27.51,1.76,27.23,5.79,6.36,0.10,-0.14,1.81,2.96,-1.46,3.97,-0.59,4.28,0.03,-0.74,4.13,-3.66,3.55,1.42,3.21,4.83,2.11,5.66,10.79,8.68,12.37,9.77,3.93,12.74,5.06,3.99,3.33,0.43,-1.11,2.62,3.22,4.55,-1.36,-0.54,-3.26,1.83,1.69,1.86,2.15,3.20,8.89,3.89,-0.96,3.94,-1.65,-1.21,12.40,2.98,-2.69,10.88,0.89,9.22,5.86,3.40,5.12,-4.96,2.97,0.25,-1.93,3.64,0.65,-2.51,0.06,-1.19,2.99,-0.78,-2.13,-0.99,6.29,-2.46,13.96,8.39,6.10,6.10,5.10,1.04,6.37,3.86,8.32,-2.02,0.85,4.55,-0.99,0.80,-3.33,8.06,3.31,0.38,7.99,3.43,-0.41,4.05,5.63,8.07,2.58,-0.16,-2.41,-0.14,0.66,-1.84,2.89,-2.82,3.25,3.01,3.02,5.66,13.94,3.48,3.03,8.75,-4.03,3.39,-0.43,7.49,-0.90,5.53,2.84,5.90,4.99,5.73,6.59,3.93,-5.41,7.82,2.68,1.98,6.50,4.89,0.02,3.24,-0.61,6.58,2.60,-1.75,-3.47,-1.45,1.25,0.36,3.19,4.01,1.17,9.25,3.58,5.97,10.02,5.55,-3.08,0.83,-2.54,2.89,5.61,7.86,7.46,2.60,6.02,5.24,-1.08,2.23,-2.18,0.01,2.69,3.21,8.77,0.79,3.86,5.89,1.42,8.49,7.86,4.05,-2.79,1.66,2.34,0.38,3.44,6.86,-1.30,13.42,13.48,11.42,5.33,4.43,5.85,12.65,1.34,1.04,4.09,2.97,-3.18,2.33,5.37,13.49,11.44,7.59,4.04,3.42,18.47,0.62,3.18,-1.44,4.62,9.40,6.83,10.21,6.14,4.14,2.10,3.33,6.91,4.30,9.94,-3.81,6.82,6.72,6.19,-0.84,3.11,1.75,16.19,-4.22,6.14,5.21,0.58,3.23,10.14,5.46,3.77,0.27,-1.80,0.99,6.75,2.11,14.48,11.52,1.27,3.88,1.77,5.21,6.78,-1.97,3.98,2.39,-1.96,5.42,-0.98,0.75,-0.47,0.60,7.78,4.95,1.47,3.20,5.30,-1.20,-1.28,1.59,2.63,-0.91,3.54,2.82,3.79,6.97,5.44,0.82,4.80,5.55,-5.52,2.36,-3.24,2.68,4.09,9.29,0.37,0.28,-2.63,0.03,4.70,6.79,-0.50,-1.48,-0.77,8.56,3.16,-5.40,1.58,5.08,4.47,7.93,5.63,3.27,7.85,2.11,3.56,-0.35,3.39,1.86,-1.11,-3.18,4.82,1.53,0.38,3.18,-1.38,6.73,2.78,4.27,3.88,1.67,4.50,8.79,17.71,5.60,0.07,-2.65,-1.19,2.10,11.58,10.59,10.96,11.45,9.15,8.18,4.25,1.21,5.98,-0.32,1.94,-1.93,4.95,0.84,0.30 2024-01-23 05:04:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 19: train = +2.3343(26.11m/2259) | dev = +3.4908(1.81m/432) | no impr, best = 3.1245 2024-01-23 05:04:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 05:07:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.47)... 2024-01-23 05:09:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +1.70)... 2024-01-23 05:12:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +1.58)... 2024-01-23 05:14:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +2.49)... 2024-01-23 05:16:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +1.94)... 2024-01-23 05:18:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +2.18)... 2024-01-23 05:21:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +1.73)... 2024-01-23 05:23:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +2.77)... 2024-01-23 05:25:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +2.12)... 2024-01-23 05:28:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.48)... 2024-01-23 05:30:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +3.18)... 2024-01-23 05:30:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 05:31:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.63)... 2024-01-23 05:32:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.89)... 2024-01-23 05:32:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: -0.28,15.09,1.61,1.58,1.79,4.15,-0.59,5.48,-1.21,4.69,3.61,-0.37,1.67,-2.42,4.75,0.67,1.73,-3.01,4.18,1.76,-2.71,0.28,3.01,1.22,5.36,0.55,11.60,2.05,0.99,-3.31,-1.07,1.38,-2.94,-0.67,6.35,3.60,0.89,3.28,2.12,2.51,-0.83,-3.82,2.73,1.78,1.08,-0.68,0.24,2.60,10.40,19.57,2.75,-1.41,2.70,3.71,-0.06,2.18,-3.78,2.85,-2.60,3.21,1.54,2.60,1.12,4.26,6.22,-2.75,2.57,-3.60,-3.96,3.64,12.84,1.86,0.94,3.28,5.05,-1.40,-0.15,0.17,4.45,1.98,-0.44,0.39,-3.58,11.38,0.00,6.51,9.45,3.65,0.47,6.38,-0.28,3.00,10.69,20.17,9.12,12.73,26.56,0.78,25.75,5.03,5.71,-0.17,-0.59,0.60,2.22,-1.86,3.44,-1.27,3.39,-0.22,-1.42,3.17,-3.88,3.10,0.15,2.44,4.21,1.14,4.99,9.99,7.81,11.28,8.84,3.17,11.30,4.84,3.20,2.90,-0.29,-1.57,2.69,2.48,3.94,-1.72,-0.52,-3.50,1.13,0.64,0.48,1.21,2.43,7.94,3.29,-1.29,3.80,-1.78,-2.04,11.21,2.30,-2.91,10.23,-0.58,8.08,5.21,2.09,3.78,-4.98,2.33,-0.61,-3.15,3.67,0.27,-3.26,-1.04,-1.30,2.08,-1.70,-2.72,-1.73,5.13,-3.59,12.77,7.90,5.37,5.40,4.57,0.50,6.24,2.70,7.46,-2.61,0.46,3.88,-1.63,0.20,-4.13,7.29,2.72,-0.00,7.49,2.53,-1.67,2.84,5.38,7.47,2.09,-1.12,-2.97,-0.42,0.15,-2.56,1.82,-3.87,2.88,2.82,2.43,4.65,11.90,2.63,2.55,8.01,-4.38,2.98,-0.98,6.62,-1.46,4.55,1.40,6.00,4.15,4.71,5.81,4.77,-6.49,6.85,2.19,1.82,5.42,4.19,-0.34,3.04,-0.99,5.64,1.71,-1.58,-3.99,-2.20,1.65,0.19,2.22,3.67,1.30,8.28,1.91,3.97,9.49,5.29,-3.45,0.69,-2.29,2.44,4.69,6.85,8.06,2.75,5.33,4.79,-0.27,1.54,-2.54,-0.35,2.33,2.37,7.91,1.24,3.43,4.40,0.33,8.03,7.45,3.32,-4.11,1.01,2.00,-0.01,2.75,6.25,-2.12,11.98,12.80,10.95,4.42,2.89,4.38,11.89,1.86,0.24,3.67,2.55,-4.06,1.17,4.66,12.63,10.59,6.84,3.15,2.80,17.78,-0.05,2.27,-1.95,3.93,8.17,6.57,10.25,6.63,3.01,0.86,2.87,6.76,4.40,9.45,-5.37,6.42,5.98,5.28,-0.46,2.46,1.69,15.25,-5.23,6.23,5.49,-0.18,2.55,9.29,4.46,2.78,-0.79,-2.31,0.57,6.31,0.15,13.25,10.31,0.95,3.15,1.11,3.99,5.85,-2.17,3.12,2.82,-2.03,4.59,-1.58,-0.18,-0.70,0.51,6.93,3.45,1.16,2.79,4.20,-1.92,-1.74,1.48,1.56,-1.84,3.24,2.67,3.39,6.02,4.75,0.03,4.02,4.91,-6.44,1.74,-3.88,2.58,3.72,8.50,0.77,-0.52,-3.50,-1.01,4.43,6.46,-1.33,-2.39,-0.84,8.26,2.44,-6.71,0.76,4.38,3.76,7.19,4.38,2.29,7.18,1.61,2.16,-0.78,3.17,1.66,-1.79,-4.43,4.53,1.51,0.37,2.70,-2.60,6.05,1.93,2.91,2.98,1.00,3.56,8.11,17.63,5.11,0.27,-3.50,-1.80,1.60,10.84,9.32,9.64,10.14,8.54,7.11,3.38,-0.02,5.34,-0.86,0.95,-2.52,4.02,0.45,0.10 2024-01-23 05:32:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 20: train = +2.2595(26.07m/2257) | dev = +2.8217(1.80m/432) 2024-01-23 05:32:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 05:35:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.41)... 2024-01-23 05:37:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.00)... 2024-01-23 05:39:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +2.20)... 2024-01-23 05:42:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +2.18)... 2024-01-23 05:44:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +1.89)... 2024-01-23 05:46:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +2.61)... 2024-01-23 05:49:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +2.53)... 2024-01-23 05:51:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +2.04)... 2024-01-23 05:53:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +1.99)... 2024-01-23 05:55:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.56)... 2024-01-23 05:58:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +1.69)... 2024-01-23 05:58:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 05:59:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.23)... 2024-01-23 06:00:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.43)... 2024-01-23 06:00:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: -0.30,14.38,1.39,1.10,1.41,3.28,-0.11,5.20,-1.42,4.32,3.12,-0.61,1.30,-2.31,4.03,-0.02,1.18,-3.04,3.96,1.23,-3.12,-0.23,2.58,0.55,4.95,0.41,11.40,1.90,0.13,-3.54,-0.96,1.41,-2.86,-1.07,5.99,3.83,0.48,3.02,1.57,2.46,-0.94,-4.14,2.30,1.31,0.36,-1.17,-0.14,1.91,10.54,18.64,2.11,-1.61,2.62,3.14,-0.61,1.59,-3.56,2.52,-2.85,2.93,1.54,2.19,0.83,3.65,5.72,-2.92,1.99,-3.91,-4.33,3.27,12.24,1.47,0.09,2.70,4.56,-1.22,-1.03,-0.04,3.99,1.86,-0.56,-0.34,-3.85,10.75,-0.55,5.69,8.85,2.90,0.15,5.74,-0.40,2.43,10.41,19.11,8.31,11.81,25.09,0.47,24.36,4.22,5.54,-0.51,-0.98,0.19,1.86,-2.15,2.83,-1.78,3.16,-0.61,-1.64,2.72,-4.41,2.70,-0.07,2.14,3.92,1.74,4.52,9.40,7.35,10.77,8.14,2.44,10.56,4.33,2.78,2.13,-0.66,-1.77,1.96,2.02,3.70,-1.63,-1.05,-3.63,0.69,0.11,0.56,0.77,2.36,7.39,2.79,-1.41,3.42,-1.91,-2.51,10.32,1.66,-3.42,9.16,-1.01,7.17,4.60,1.61,3.35,-5.10,2.29,-1.20,-3.55,3.50,0.28,-3.29,-1.29,-1.48,1.25,-2.03,-3.17,-2.00,4.58,-4.20,12.23,7.31,4.78,4.84,4.11,0.23,6.29,2.25,6.76,-2.66,0.05,3.32,-1.74,-0.18,-4.21,6.69,2.35,0.34,6.86,2.02,-2.01,2.18,5.27,6.98,1.92,-1.35,-2.94,-0.71,-0.30,-2.72,1.35,-3.58,2.42,2.48,2.15,4.10,11.41,2.13,2.23,7.49,-4.79,2.49,-1.18,7.67,-1.93,4.19,0.93,4.64,3.68,4.56,5.22,3.10,-6.60,6.71,1.36,1.35,4.75,3.73,-0.55,2.31,-1.22,5.06,1.37,-1.88,-4.09,-2.12,0.53,-1.09,1.48,2.41,0.42,7.66,1.75,3.51,9.19,5.05,-3.66,-0.51,-2.73,1.84,4.07,6.99,7.26,2.32,4.42,3.75,-1.21,1.37,-2.77,-0.86,1.76,1.84,7.62,0.18,3.14,3.87,0.19,7.24,7.22,2.76,-4.27,0.66,1.25,-0.26,2.24,5.58,-2.33,10.97,11.48,10.29,4.39,2.10,3.57,11.40,0.67,0.05,3.68,2.19,-4.36,0.96,4.00,11.76,10.04,6.37,3.43,1.90,17.20,-0.33,1.76,-2.33,4.11,7.22,6.07,9.41,5.67,3.10,0.32,2.31,5.40,3.39,8.41,-5.41,6.06,5.54,4.67,-1.46,2.24,0.93,14.70,-5.83,4.89,4.39,-0.84,2.28,8.69,4.45,2.26,-1.16,-2.50,0.29,5.35,-0.27,12.78,9.86,0.90,2.88,0.40,3.65,5.32,-2.64,2.73,2.62,-2.77,4.23,-1.86,-0.73,-0.74,0.16,6.68,2.92,0.91,2.29,3.56,-2.50,-1.88,0.98,0.96,-2.08,2.60,1.68,2.79,5.77,4.28,-0.14,4.21,4.39,-5.89,1.64,-4.13,1.85,3.26,8.36,-0.24,-0.80,-3.60,-1.48,3.98,5.71,-1.55,-2.67,-1.09,7.63,2.07,-7.01,0.61,3.74,3.05,6.28,4.00,1.98,6.71,1.58,1.82,-1.13,2.40,1.52,-2.15,-3.95,4.86,1.89,0.39,2.22,-2.96,5.59,1.92,2.74,2.53,1.13,3.37,7.60,16.81,4.54,-0.08,-3.82,-1.87,1.17,10.32,8.77,9.20,9.35,7.72,6.74,3.01,-0.14,4.63,-1.17,0.71,-2.72,3.59,-0.20,-0.44 2024-01-23 06:00:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 21: train = +2.1910(26.03m/2259) | dev = +2.3944(1.81m/432) 2024-01-23 06:00:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 06:03:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.36)... 2024-01-23 06:05:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.18)... 2024-01-23 06:07:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +2.19)... 2024-01-23 06:10:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +1.96)... 2024-01-23 06:12:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +2.38)... 2024-01-23 06:14:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +2.67)... 2024-01-23 06:16:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +1.98)... 2024-01-23 06:19:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +1.82)... 2024-01-23 06:21:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +1.69)... 2024-01-23 06:23:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.75)... 2024-01-23 06:26:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +1.98)... 2024-01-23 06:26:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 06:27:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.08)... 2024-01-23 06:28:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.22)... 2024-01-23 06:28:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: -0.74,13.98,1.19,0.89,1.37,3.28,-0.50,4.65,-1.39,3.84,3.29,-0.82,0.97,-2.50,3.76,-0.20,1.20,-3.13,3.47,0.95,-2.83,-0.19,2.39,0.41,5.04,0.40,11.33,1.80,-0.05,-3.15,-1.57,1.15,-3.17,-1.26,5.82,2.89,0.50,2.86,1.65,1.94,-0.51,-3.97,1.70,1.26,0.54,-1.57,-0.15,1.35,9.73,18.42,2.21,-1.71,2.37,2.93,-0.39,1.65,-4.01,2.46,-2.98,2.92,0.69,2.08,0.51,3.49,5.36,-2.82,2.29,-3.95,-4.38,3.81,12.09,1.37,0.31,2.23,4.76,-1.48,-1.25,-0.10,3.52,1.57,-0.70,-0.50,-3.63,10.34,-0.38,5.81,8.37,3.20,0.02,5.43,-0.77,2.36,10.01,18.80,8.20,11.60,24.88,0.38,23.90,3.87,4.73,-0.94,-0.96,0.18,1.62,-2.01,3.02,-1.83,2.81,-0.80,-1.85,2.61,-4.52,2.39,-0.13,2.21,3.65,0.59,4.53,9.18,7.26,10.60,8.38,2.30,10.49,4.07,2.76,2.22,-0.88,-1.86,1.17,1.71,3.34,-1.97,-1.15,-3.36,0.74,0.12,0.27,1.07,1.75,7.25,2.84,-1.90,3.15,-2.40,-2.56,10.25,1.68,-3.14,9.12,-1.07,7.07,4.84,1.63,3.17,-5.22,2.05,-1.58,-3.47,3.16,0.31,-3.74,-0.98,-1.46,1.04,-2.04,-2.91,-1.95,4.48,-4.08,12.00,7.45,4.72,4.75,3.87,-0.28,5.80,2.16,6.71,-3.02,-0.19,3.22,-1.96,-0.29,-4.52,6.54,2.44,-0.32,7.03,2.12,-2.01,2.22,4.70,6.75,1.90,-1.53,-2.87,-0.94,-0.70,-2.68,1.33,-4.03,2.25,2.19,2.21,3.96,11.59,1.80,2.05,7.27,-4.67,1.99,-1.17,5.97,-1.93,4.10,0.72,4.36,3.53,4.32,4.81,2.94,-6.65,6.03,0.64,0.80,4.50,3.66,-0.93,1.73,-1.46,4.97,1.48,-2.48,-4.66,-2.46,0.78,-1.23,1.48,2.43,-0.18,7.32,1.48,3.51,8.80,4.72,-3.86,0.16,-2.93,1.97,4.26,6.00,6.11,2.29,4.08,3.57,-2.11,1.31,-2.89,-0.82,1.83,1.76,7.50,-0.02,2.98,3.67,-0.18,7.10,6.58,2.60,-3.96,1.11,1.20,-0.40,2.43,5.09,-2.35,11.30,11.51,10.04,4.02,2.26,3.60,10.91,0.26,-0.20,3.25,1.84,-4.25,0.99,3.98,12.18,9.49,6.01,1.85,1.85,16.80,-0.72,1.13,-2.32,3.25,7.47,5.45,8.73,5.34,2.58,0.25,2.32,5.61,2.93,8.08,-5.42,5.65,5.66,4.41,-1.75,1.93,1.00,14.29,-5.90,5.19,4.03,-0.84,2.45,8.51,4.29,2.21,-1.14,-2.46,0.47,5.35,-0.36,12.45,9.86,0.61,2.86,0.13,3.30,4.77,-2.93,2.64,1.69,-2.58,4.30,-1.90,-0.94,-0.87,-0.12,6.15,2.54,0.82,2.11,3.49,-2.65,-1.53,0.68,0.88,-2.14,2.18,1.33,2.61,5.37,4.59,-0.21,3.43,4.15,-6.67,1.29,-4.00,1.94,3.05,7.79,-0.31,-0.78,-3.81,-1.67,3.39,5.46,-1.66,-2.77,-1.45,7.42,2.00,-6.88,0.51,3.85,3.14,6.11,3.83,1.83,6.65,0.85,1.72,-1.01,2.33,1.00,-2.19,-4.62,3.69,1.15,-0.12,2.10,-3.14,5.76,1.44,2.53,1.82,0.84,3.25,7.37,16.40,4.40,-0.34,-3.59,-1.85,1.20,9.75,8.70,8.74,9.24,7.40,6.59,2.44,-0.49,4.89,-1.26,0.43,-3.40,3.74,-0.50,-0.23 2024-01-23 06:28:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 22: train = +2.1798(26.08m/2260) | dev = +2.2100(1.81m/432) 2024-01-23 06:28:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 06:31:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +1.91)... 2024-01-23 06:33:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +1.84)... 2024-01-23 06:35:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +1.83)... 2024-01-23 06:37:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +2.23)... 2024-01-23 06:40:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +1.82)... 2024-01-23 06:42:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +2.14)... 2024-01-23 06:44:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +2.46)... 2024-01-23 06:47:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +2.32)... 2024-01-23 06:49:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +1.78)... 2024-01-23 06:51:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.03)... 2024-01-23 06:53:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +2.44)... 2024-01-23 06:54:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 06:55:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.56)... 2024-01-23 06:56:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.70)... 2024-01-23 06:56:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: -0.13,15.24,1.58,1.78,1.78,3.87,-0.46,5.48,-1.24,4.63,3.60,-0.37,1.64,-2.27,4.25,0.45,1.60,-2.74,4.47,1.60,-3.06,0.55,2.74,0.96,5.33,0.75,11.73,2.25,0.44,-3.48,-1.08,1.46,-2.63,-0.77,6.57,4.20,0.69,3.26,1.97,2.45,-0.41,-3.95,2.27,1.18,0.37,-1.01,0.19,2.06,10.36,19.47,2.62,-1.46,2.81,3.29,-0.36,1.92,-3.62,2.75,-2.58,3.28,1.86,2.46,1.03,4.03,6.43,-2.44,2.22,-3.97,-4.32,3.54,13.14,2.00,0.30,3.01,5.29,-1.37,-0.84,0.05,4.45,2.01,-0.31,0.69,-3.80,11.36,-0.09,6.48,9.47,3.20,0.38,6.25,-0.27,2.85,10.89,19.98,8.96,12.58,26.40,0.86,25.76,4.85,5.89,-0.53,-0.61,0.46,2.04,-2.16,3.23,-1.56,3.37,-0.60,-1.57,3.17,-4.27,2.95,0.08,2.42,4.25,1.42,5.04,10.21,8.41,11.56,8.70,2.92,11.59,4.47,3.17,2.82,-0.40,-1.71,2.33,2.35,4.38,-1.56,-1.10,-3.61,0.92,0.28,0.74,1.42,2.55,7.94,3.23,-1.61,3.52,-1.80,-2.23,11.75,2.10,-3.16,9.94,-0.65,7.88,5.27,2.00,3.70,-5.05,2.22,-1.15,-3.28,3.98,0.43,-3.67,-0.69,-1.21,1.65,-1.61,-2.77,-1.66,4.78,-3.74,12.93,7.78,5.33,5.24,4.64,0.36,6.51,2.59,7.11,-3.12,-0.11,3.75,-1.59,-0.06,-4.51,7.15,3.02,0.31,7.63,2.32,-1.78,2.70,5.42,7.19,2.14,-0.96,-2.83,-0.59,-0.35,-2.71,1.62,-4.03,2.70,2.77,2.72,4.68,12.34,2.52,2.58,7.87,-4.30,2.62,-1.12,6.71,-1.51,4.73,1.17,4.70,4.13,4.99,5.67,3.13,-6.60,6.73,1.46,1.23,5.31,4.19,-0.48,2.51,-1.12,5.49,1.65,-2.47,-4.35,-2.33,0.87,-0.72,2.00,2.94,0.35,8.36,1.95,4.14,9.55,5.25,-3.43,0.13,-2.59,1.97,4.58,6.72,6.96,2.38,4.81,4.14,-1.48,1.57,-2.71,-0.67,2.07,2.53,7.85,0.38,3.15,4.22,0.23,7.68,7.55,3.61,-3.74,1.30,1.68,-0.15,2.87,5.91,-2.19,11.85,12.27,10.96,4.47,2.96,4.09,11.72,0.56,0.13,3.15,2.81,-4.07,1.17,4.67,12.56,10.63,6.94,3.73,2.35,18.22,-0.41,1.72,-2.27,3.84,8.08,6.13,9.62,5.90,3.22,0.88,2.71,6.04,3.78,9.28,-5.22,6.86,6.20,5.23,-1.51,2.60,1.28,15.53,-5.60,5.27,4.75,-0.25,2.84,9.15,4.95,2.52,-1.02,-2.56,0.72,6.19,0.21,13.74,10.63,0.84,3.42,0.33,3.61,5.33,-1.85,3.17,1.78,-2.35,4.72,-1.74,-0.44,-1.24,-0.10,6.69,3.35,0.60,2.58,4.09,-2.26,-1.92,0.76,1.62,-1.69,2.71,1.75,2.98,6.15,4.72,-0.10,3.71,5.10,-6.26,1.61,-3.70,2.08,3.27,8.45,-0.18,-0.90,-3.56,-1.18,4.21,6.12,-1.63,-2.41,-1.09,7.91,2.39,-6.86,0.93,4.33,3.18,7.04,4.27,2.29,7.14,1.16,2.11,-0.73,2.87,1.61,-1.77,-3.60,4.61,1.83,-0.19,2.74,-2.74,6.11,2.12,3.10,2.91,0.85,3.88,8.05,17.36,4.73,-0.23,-3.43,-1.53,1.55,10.91,9.37,9.75,10.26,8.51,7.21,3.30,0.23,5.08,-0.99,0.80,-3.47,4.19,-0.21,-0.07 2024-01-23 06:56:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 23: train = +2.0884(26.04m/2261) | dev = +2.6917(1.80m/432) | no impr, best = 2.2100 2024-01-23 06:56:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 06:58:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +1.80)... 2024-01-23 07:01:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.15)... 2024-01-23 07:03:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +2.35)... 2024-01-23 07:05:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +2.20)... 2024-01-23 07:08:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +1.96)... 2024-01-23 07:10:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +2.23)... 2024-01-23 07:12:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +2.62)... 2024-01-23 07:15:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +2.12)... 2024-01-23 07:17:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +2.14)... 2024-01-23 07:19:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.51)... 2024-01-23 07:21:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +1.88)... 2024-01-23 07:22:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 07:23:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +3.10)... 2024-01-23 07:24:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +3.23)... 2024-01-23 07:24:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: -0.21,16.57,1.95,2.20,2.23,4.59,0.06,5.93,-0.78,4.97,4.43,0.03,2.26,-2.39,5.13,0.91,2.19,-2.69,4.71,2.72,-2.51,0.51,3.33,1.47,5.94,0.87,12.43,2.11,1.27,-3.12,-0.73,1.96,-2.72,-0.14,6.70,4.01,1.27,3.99,2.51,2.71,-0.74,-3.47,2.49,1.93,1.18,-0.34,0.68,2.37,11.34,20.97,3.22,-1.12,3.31,3.93,0.17,2.43,-3.29,3.45,-2.56,3.61,2.38,2.81,1.51,4.93,7.13,-2.39,3.03,-2.94,-3.82,4.21,13.90,2.40,0.93,3.66,5.55,-1.06,-0.73,0.37,4.70,2.60,-0.09,1.05,-3.74,12.45,0.38,7.34,10.56,4.12,0.78,6.99,-0.26,3.62,11.84,21.40,9.51,13.79,28.88,1.52,27.85,5.45,6.08,-0.70,-0.46,0.96,2.23,-1.75,3.95,-0.91,4.20,-0.23,-1.05,3.65,-3.89,3.45,0.25,3.11,4.23,1.89,5.83,10.39,8.91,12.80,9.55,4.04,12.65,5.12,3.38,3.13,0.66,-1.58,3.14,2.92,4.93,-1.25,-0.27,-3.09,1.55,0.91,1.23,2.24,2.99,8.79,3.50,-0.92,3.88,-1.51,-1.85,12.25,2.67,-2.98,11.19,-0.29,9.38,5.74,3.31,4.39,-4.81,2.91,-0.08,-2.95,3.98,0.91,-3.29,-0.47,-1.30,2.39,-1.42,-2.31,-1.45,5.92,-3.41,14.47,8.89,6.32,5.98,5.20,0.78,6.39,3.34,7.98,-2.36,0.82,4.41,-1.69,0.30,-4.17,7.89,3.22,0.18,8.02,3.27,-1.43,3.05,5.57,8.20,2.80,-0.93,-2.72,-0.26,0.33,-2.36,2.79,-3.52,3.51,3.14,2.66,5.11,13.55,3.19,3.24,8.41,-4.28,3.27,-1.01,7.28,-0.98,4.99,1.48,5.60,4.66,5.78,5.79,4.18,-6.41,7.77,2.06,2.02,6.35,4.86,-0.47,3.16,-0.82,6.42,2.34,-1.68,-4.09,-2.40,1.52,-0.31,2.59,3.70,1.11,8.85,2.55,4.68,10.12,5.70,-3.45,0.28,-2.68,2.51,5.13,7.55,8.06,3.01,5.53,4.78,-1.60,1.90,-2.22,-0.19,2.32,3.28,9.19,0.74,3.61,5.47,0.72,8.56,7.99,3.94,-3.88,1.21,2.03,0.69,3.39,6.37,-1.79,13.04,13.54,11.87,5.21,3.70,5.01,12.69,1.12,0.76,3.63,2.99,-3.74,1.68,5.41,13.68,11.75,7.56,3.17,2.76,18.94,-0.01,2.22,-2.06,4.27,8.87,6.26,10.20,5.95,3.58,1.10,2.79,7.23,4.22,10.18,-4.91,7.19,6.58,5.55,-0.96,2.75,1.60,16.01,-5.10,6.41,5.17,0.67,3.40,10.07,5.47,3.28,-0.32,-2.18,1.58,6.23,0.55,13.87,11.23,1.13,3.65,0.99,4.30,6.07,-1.88,3.76,2.49,-1.82,5.41,-1.50,0.42,-0.39,0.47,7.26,3.78,1.24,2.75,4.65,-1.40,-1.71,1.21,1.98,-1.35,3.09,2.96,3.62,6.63,5.76,0.46,4.60,5.36,-6.31,2.05,-3.71,2.43,4.02,9.73,0.18,-0.06,-3.07,-0.75,5.02,6.65,-1.16,-2.14,-0.66,8.69,3.01,-6.61,1.14,4.98,3.97,7.78,4.72,2.70,8.00,1.73,2.72,-0.63,3.26,1.77,-1.44,-3.94,4.99,1.60,0.22,3.32,-2.26,6.97,2.63,3.42,3.39,1.47,4.53,8.69,18.20,5.89,0.21,-3.04,-1.52,1.96,11.75,10.42,10.70,10.98,9.23,8.13,3.68,0.25,6.00,-0.52,1.29,-2.56,4.54,0.29,-0.01 2024-01-23 07:24:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 24: train = +2.1576(26.14m/2257) | dev = +3.2296(1.81m/432) | no impr, best = 2.2100 2024-01-23 07:24:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 07:26:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +1.86)... 2024-01-23 07:29:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.05)... 2024-01-23 07:31:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +1.54)... 2024-01-23 07:33:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +2.80)... 2024-01-23 07:36:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +1.80)... 2024-01-23 07:38:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +2.05)... 2024-01-23 07:40:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +1.87)... 2024-01-23 07:42:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +2.51)... 2024-01-23 07:45:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +2.12)... 2024-01-23 07:47:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +2.15)... 2024-01-23 07:49:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +1.88)... 2024-01-23 07:50:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 07:51:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.23)... 2024-01-23 07:52:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.27)... 2024-01-23 07:52:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: -0.39,14.88,1.07,0.94,1.21,3.59,-0.41,5.27,-1.54,3.99,3.43,-0.22,1.25,-2.50,4.49,-0.17,1.20,-2.97,3.74,1.06,-3.29,-0.61,2.94,0.70,5.04,0.32,11.09,1.72,-0.00,-3.90,-1.71,1.13,-3.40,-1.09,5.76,3.65,0.64,3.00,2.03,2.31,-1.04,-3.91,1.74,1.89,1.29,-1.09,-0.04,1.64,9.99,19.00,2.01,-1.73,2.41,3.25,-0.47,1.48,-3.62,2.73,-3.08,2.77,0.77,2.58,0.51,3.48,5.69,-2.90,2.18,-3.48,-4.55,3.52,12.64,1.48,-0.06,2.41,5.01,-1.46,-1.31,-0.24,3.73,1.79,-0.77,-0.14,-3.86,10.57,-0.47,6.24,8.40,3.07,0.16,6.04,-0.54,1.90,10.44,19.57,8.85,12.11,25.65,0.72,24.87,4.29,5.20,-0.38,-0.97,0.36,2.62,-1.94,2.98,-1.75,3.00,-0.38,-1.86,2.86,-4.23,2.62,-0.30,2.19,3.86,0.91,4.49,9.30,7.61,10.99,8.85,2.43,10.60,4.10,3.48,2.81,-0.68,-1.86,1.66,2.59,3.72,-1.87,-1.24,-3.62,0.52,0.36,0.24,1.16,2.09,7.32,2.72,-2.02,3.13,-2.07,-2.55,10.56,1.81,-2.56,9.40,-1.16,7.31,4.94,1.82,3.19,-5.10,2.18,-1.59,-3.54,3.28,0.54,-3.74,-1.46,-1.34,1.64,-2.24,-2.90,-2.12,4.26,-3.98,12.24,7.72,4.84,4.96,4.00,0.07,5.73,2.03,6.75,-2.86,-0.09,3.47,-2.20,0.03,-4.54,6.53,2.19,0.14,7.11,2.25,-1.90,2.10,4.82,7.20,2.30,-1.58,-2.99,-0.85,0.06,-2.89,1.54,-4.01,3.09,2.93,2.17,4.10,12.48,1.86,2.07,7.52,-4.59,2.69,-1.02,6.10,-1.85,4.35,0.79,4.61,3.66,4.85,4.87,2.79,-6.83,6.10,0.83,0.97,4.69,3.63,-0.90,1.94,-1.24,5.22,1.62,-2.62,-4.47,-2.31,0.38,-1.05,1.58,2.46,0.20,7.28,1.60,3.26,9.08,4.56,-3.63,0.43,-3.20,2.21,4.34,6.61,6.29,2.17,4.51,3.90,-2.85,1.15,-2.72,-0.77,1.60,1.88,7.36,-0.13,2.46,3.89,0.03,7.09,6.61,2.52,-3.78,1.00,1.29,-0.56,2.21,5.08,-2.41,11.46,11.06,10.03,4.12,2.35,3.41,11.11,-0.01,-0.27,2.58,2.19,-4.22,0.67,4.33,12.24,9.89,6.32,1.81,1.62,16.96,-0.92,1.18,-2.53,3.39,7.24,5.25,8.98,4.87,2.66,0.21,2.13,5.31,2.90,8.30,-5.44,5.93,5.71,4.32,-2.16,2.14,0.82,14.65,-5.82,5.30,3.95,-0.73,2.71,8.64,4.39,2.32,-0.94,-2.59,0.42,5.15,-0.38,12.47,10.01,0.12,3.06,-0.20,3.37,4.67,-2.93,2.84,1.25,-2.56,4.36,-2.05,-0.95,-1.04,-0.28,6.46,2.59,0.68,2.15,3.53,-2.67,-2.08,0.60,1.17,-1.99,2.32,1.42,2.93,5.45,4.23,-0.01,3.51,4.47,-6.66,1.31,-4.14,1.79,3.35,7.93,-0.23,-0.36,-3.90,-1.72,3.86,5.50,-1.60,-2.80,-1.43,7.64,2.08,-7.06,0.61,4.03,3.53,6.25,3.91,2.10,6.78,0.95,2.02,-0.96,2.27,1.34,-2.23,-4.59,3.01,0.88,-0.34,2.21,-3.22,5.51,1.75,2.76,1.91,0.92,3.25,7.52,16.54,4.56,-0.28,-3.87,-1.78,1.30,10.26,8.72,8.88,9.52,7.10,7.21,2.43,-0.36,4.62,-1.07,0.65,-3.72,4.10,-0.74,-0.52 2024-01-23 07:52:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 25: train = +2.0462(26.15m/2260) | dev = +2.3057(1.78m/432) | no impr, best = 2.2100 2024-01-23 07:52:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 07:54:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +1.66)... 2024-01-23 07:57:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.01)... 2024-01-23 07:59:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +1.77)... 2024-01-23 08:01:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +1.70)... 2024-01-23 08:03:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +2.15)... 2024-01-23 08:06:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +1.23)... 2024-01-23 08:08:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +1.63)... 2024-01-23 08:10:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +1.61)... 2024-01-23 08:13:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +1.09)... 2024-01-23 08:15:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +1.50)... 2024-01-23 08:17:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +1.22)... 2024-01-23 08:18:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 08:19:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.09)... 2024-01-23 08:20:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.19)... 2024-01-23 08:20:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: -0.54,14.20,1.01,0.87,1.20,3.36,-0.89,4.91,-1.44,4.19,3.08,-0.52,1.15,-2.71,4.11,-0.35,1.10,-3.19,3.74,1.02,-3.17,-0.56,2.41,0.28,5.07,0.25,10.81,1.84,-0.23,-3.80,-1.67,1.10,-3.33,-1.22,5.84,3.16,0.44,2.94,1.58,2.29,-1.09,-4.09,1.84,1.44,0.52,-1.14,-0.22,1.47,9.82,18.63,1.84,-1.85,2.44,2.88,-0.33,1.43,-3.59,2.59,-2.97,2.86,1.28,2.13,0.42,3.30,5.36,-3.03,1.87,-4.09,-4.51,3.30,12.44,1.56,-0.01,2.78,4.64,-1.70,-1.26,-0.27,3.87,1.36,-0.97,-0.52,-3.97,10.33,-0.49,5.62,8.65,3.00,0.17,5.66,-0.67,2.05,10.39,19.38,8.61,11.73,24.83,0.43,24.36,4.25,5.14,-0.60,-1.24,0.24,1.80,-2.28,2.90,-1.97,2.90,-0.33,-2.01,2.65,-4.34,2.34,-0.31,2.15,3.94,0.84,4.65,9.25,7.40,10.75,8.28,2.24,10.54,4.04,2.77,2.43,-0.85,-2.06,1.72,1.93,3.32,-1.65,-1.40,-3.55,0.59,0.18,0.87,0.80,1.95,7.07,2.69,-2.06,3.14,-2.34,-2.64,10.56,1.75,-2.91,8.99,-0.98,7.23,4.81,1.53,3.17,-5.22,1.81,-1.48,-3.57,3.50,0.30,-3.74,-1.42,-1.29,1.11,-2.23,-2.90,-2.02,4.42,-4.14,11.94,7.18,4.64,4.69,3.55,-0.31,5.67,2.26,6.76,-2.83,-0.13,3.38,-2.04,-0.33,-4.65,6.45,2.11,-0.15,6.88,2.44,-1.96,2.20,5.08,6.76,1.87,-1.49,-3.10,-0.94,-0.12,-2.85,1.80,-4.18,2.41,2.49,1.92,3.89,11.21,2.20,1.70,7.38,-4.89,2.21,-1.17,6.00,-1.94,4.15,0.93,4.46,3.67,4.61,4.63,3.01,-6.46,6.23,0.33,0.80,4.64,3.59,-0.87,1.88,-1.19,4.99,1.47,-2.57,-4.31,-2.34,0.43,-1.10,1.47,2.33,-0.18,7.39,1.64,3.44,8.66,4.48,-3.72,-0.68,-3.22,1.89,4.15,6.29,6.54,2.18,4.43,3.99,-2.93,1.27,-2.89,-1.01,1.45,1.88,7.40,-0.20,2.36,3.67,-0.08,6.92,6.48,2.56,-4.01,0.79,1.24,-0.58,2.32,5.11,-2.53,11.40,10.61,10.19,3.89,2.19,3.52,11.06,0.31,-0.21,2.79,1.98,-4.37,0.66,4.21,11.51,9.92,6.10,2.01,1.75,16.97,-0.91,1.17,-2.58,3.29,7.21,5.00,8.64,4.60,2.67,0.32,2.12,5.51,2.87,8.53,-5.35,6.00,5.71,4.58,-2.00,1.91,0.52,14.54,-6.01,5.04,3.98,-0.40,2.27,8.50,4.14,2.10,-0.98,-2.84,-0.09,5.36,-0.34,12.39,9.89,-0.07,3.09,-0.06,3.21,4.57,-2.76,2.74,1.43,-2.80,4.31,-2.05,-1.00,-1.14,-0.24,6.43,2.63,0.73,2.09,3.55,-2.44,-2.20,0.55,1.11,-2.09,2.58,1.33,2.95,5.44,4.15,0.01,3.23,4.42,-6.58,1.33,-4.06,1.81,2.83,7.74,-0.37,-0.82,-3.93,-1.70,3.81,5.47,-1.61,-2.75,-1.50,7.47,2.05,-6.89,0.37,4.08,2.95,6.30,3.95,1.96,6.94,0.97,1.73,-1.07,2.39,1.36,-2.09,-4.45,3.34,0.99,-0.30,2.31,-3.10,5.64,1.66,2.46,2.05,0.85,3.30,7.43,16.59,4.42,-0.65,-3.78,-1.93,1.11,10.22,8.64,8.85,9.39,7.14,6.44,2.70,-0.26,4.36,-1.46,0.57,-3.32,3.79,-0.64,-0.61 2024-01-23 08:20:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 26: train = +1.5991(26.16m/2258) | dev = +2.2012(1.83m/432) 2024-01-23 08:20:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 08:22:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +1.41)... 2024-01-23 08:25:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +1.74)... 2024-01-23 08:27:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +1.76)... 2024-01-23 08:29:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +1.63)... 2024-01-23 08:32:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +2.09)... 2024-01-23 08:34:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +1.79)... 2024-01-23 08:36:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +1.36)... 2024-01-23 08:38:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +1.69)... 2024-01-23 08:41:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +1.26)... 2024-01-23 08:43:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +1.14)... 2024-01-23 08:45:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +1.57)... 2024-01-23 08:46:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 08:47:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +1.82)... 2024-01-23 08:48:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +1.97)... 2024-01-23 08:48:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: -0.33,13.70,1.00,0.62,1.21,2.96,-0.70,4.73,-1.71,3.47,2.93,-1.08,1.26,-2.84,3.43,-0.45,0.90,-3.30,3.48,1.17,-3.27,-0.34,1.66,0.00,4.55,0.13,10.84,1.54,-0.54,-3.82,-1.61,0.91,-3.10,-1.38,5.60,3.56,0.04,2.74,1.11,2.10,-0.58,-4.24,1.57,0.95,-0.34,-1.86,-0.33,1.17,9.63,17.93,1.79,-1.86,2.14,2.55,-0.68,1.28,-4.25,2.32,-3.15,2.71,1.06,1.94,0.55,3.25,5.27,-3.52,1.47,-4.28,-4.88,2.86,11.81,1.26,-0.17,2.31,4.48,-2.15,-1.96,-0.26,3.32,1.45,-0.73,-0.48,-4.01,10.15,-0.65,5.50,8.43,2.48,-0.05,5.20,-0.90,2.28,10.12,18.44,8.16,11.31,24.44,0.19,23.43,3.76,4.74,-1.65,-1.27,-0.16,1.35,-2.25,2.36,-2.15,2.43,-0.84,-2.29,2.43,-4.53,2.04,-0.41,1.68,3.57,0.29,4.23,9.00,6.72,10.29,8.17,2.14,10.10,3.95,2.31,2.00,-0.99,-2.08,1.14,1.52,3.22,-2.26,-1.69,-3.83,0.38,0.13,0.14,0.46,1.51,6.93,2.48,-2.01,2.80,-2.24,-2.76,9.89,1.34,-3.48,8.45,-1.32,6.79,4.32,1.67,2.93,-5.26,1.85,-1.92,-3.64,2.95,0.35,-3.92,-1.50,-1.58,0.74,-2.31,-3.40,-1.94,4.06,-4.14,11.33,6.43,4.31,4.40,3.78,-0.17,5.39,1.92,6.30,-3.11,-0.37,2.91,-2.12,-0.65,-4.66,6.24,1.88,-0.40,6.71,1.91,-2.18,1.99,4.60,6.67,1.46,-1.67,-3.17,-0.92,-1.09,-2.81,1.15,-4.22,1.98,2.09,1.89,3.63,10.56,1.68,1.85,6.95,-5.06,2.07,-1.41,5.61,-2.24,3.87,0.51,4.18,3.24,4.06,4.51,2.41,-6.84,6.19,0.50,0.52,4.18,3.24,-0.93,1.55,-1.61,4.61,1.20,-2.60,-4.75,-2.57,0.49,-1.01,1.13,1.97,-0.09,7.11,1.06,3.01,8.37,4.18,-3.17,0.42,-3.34,1.82,3.71,5.70,6.16,1.65,4.00,3.23,-2.81,0.98,-2.85,-0.95,1.29,1.55,6.92,-0.39,2.39,3.43,-0.29,6.65,6.52,2.18,-4.49,0.29,1.06,-0.76,2.39,5.04,-2.62,10.64,10.58,9.70,3.45,1.70,3.20,10.53,0.07,-0.42,3.36,1.87,-4.54,0.46,3.72,11.30,9.59,5.68,3.00,1.33,16.48,-0.42,1.13,-2.51,3.62,7.04,4.88,8.69,4.67,3.12,0.00,1.94,5.18,3.32,8.26,-5.62,5.48,5.51,4.14,-1.88,1.57,0.52,14.38,-6.19,4.61,3.76,-1.00,2.51,8.15,4.18,1.89,-1.23,-2.66,-0.27,4.97,-0.67,12.13,9.42,-0.30,2.40,0.38,3.01,4.39,-2.72,2.42,1.03,-2.92,3.95,-2.16,-1.16,-1.39,-0.39,5.86,2.23,0.50,1.98,3.32,-2.79,-2.24,0.45,0.85,-2.23,2.10,0.93,2.38,5.17,3.94,-0.38,3.17,4.02,-6.48,1.03,-4.45,1.41,2.87,7.44,-0.31,-1.00,-4.25,-1.72,3.23,5.02,-1.78,-3.03,-1.59,7.21,1.70,-6.96,0.24,3.85,2.47,5.77,3.58,1.73,6.49,0.50,1.52,-1.35,1.93,0.91,-2.44,-4.80,3.73,0.91,-0.45,1.92,-3.24,5.39,1.17,2.20,1.96,0.39,3.14,7.01,16.07,4.16,-0.77,-4.16,-2.23,0.66,9.65,8.26,8.41,8.83,6.80,6.32,2.32,-0.59,4.26,-1.34,0.37,-3.54,3.38,-0.88,-0.63 2024-01-23 08:48:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 27: train = +1.5624(26.22m/2259) | dev = +1.9537(1.81m/432) 2024-01-23 08:48:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 08:50:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +1.46)... 2024-01-23 08:53:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +0.95)... 2024-01-23 08:55:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +2.04)... 2024-01-23 08:57:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +1.13)... 2024-01-23 09:00:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +1.58)... 2024-01-23 09:02:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +1.75)... 2024-01-23 09:04:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +1.21)... 2024-01-23 09:07:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1600 batches(loss = +1.45)... 2024-01-23 09:09:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1800 batches(loss = +1.56)... 2024-01-23 09:11:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2000 batches(loss = +1.44)... 2024-01-23 09:13:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 2200 batches(loss = +1.82)... 2024-01-23 09:14:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 09:15:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +1.94)... 2024-01-23 09:16:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +2.10)... 2024-01-23 09:16:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: -0.25,13.66,1.13,0.53,1.13,3.42,-0.18,4.71,-1.54,3.50,2.80,-0.72,0.95,-2.37,3.98,-0.52,0.72,-2.90,3.30,1.09,-3.21,-0.74,2.28,0.54,4.80,0.17,10.46,1.73,-0.45,-3.74,-1.80,0.87,-3.22,-1.49,5.81,3.66,0.44,2.65,1.43,2.08,-1.47,-3.95,1.75,1.10,0.57,-1.83,-0.45,1.45,9.52,17.56,1.72,-1.64,2.31,2.62,-0.92,1.11,-3.73,2.92,-2.99,2.74,0.70,2.21,0.95,3.06,5.38,-2.32,1.96,-3.76,-4.51,3.10,11.62,1.34,-0.22,2.60,4.48,-1.32,-1.47,-0.24,4.11,1.88,-0.61,-0.49,-3.51,9.79,-0.68,5.01,8.15,2.73,0.10,5.37,-0.65,1.74,9.58,18.34,8.09,11.76,23.79,0.38,23.00,3.75,4.69,-0.43,-1.32,-0.11,1.84,-2.11,2.59,-2.26,2.69,-0.15,-1.64,2.49,-4.41,2.26,-0.39,2.01,3.42,0.82,4.12,8.94,7.03,10.45,7.87,1.98,9.65,3.96,3.00,2.05,-1.04,-1.80,0.95,1.71,3.24,-1.99,-1.39,-3.11,0.25,0.13,0.11,0.82,1.63,6.98,2.52,-2.30,2.98,-2.09,-2.75,9.69,1.42,-2.36,8.77,-1.31,6.60,4.72,1.58,2.87,-4.87,2.24,-1.88,-3.66,3.01,0.48,-3.22,-1.62,-1.32,0.94,-2.16,-2.97,-2.00,4.15,-4.11,11.46,7.10,4.69,4.46,3.78,-0.13,5.69,1.82,6.41,-2.77,0.37,3.27,-2.23,-0.27,-4.49,5.96,2.03,-0.27,6.48,2.11,-2.06,1.85,4.32,6.62,1.66,-1.64,-3.20,-1.02,-0.23,-2.69,1.27,-4.04,2.43,2.54,1.92,3.57,10.81,1.85,1.94,7.27,-4.52,2.14,-1.44,5.56,-2.31,4.24,0.61,4.81,3.25,3.97,4.22,2.71,-6.75,5.71,1.53,0.98,4.09,3.33,-0.72,2.64,-1.08,4.76,1.52,-2.33,-4.58,-2.40,0.95,-1.51,1.12,2.43,-0.13,6.63,1.27,2.88,8.35,4.79,-3.45,-0.63,-2.68,2.16,3.68,5.69,6.34,1.94,4.02,3.23,-3.10,1.11,-2.49,-0.47,1.96,1.72,6.90,0.26,2.46,3.22,-0.04,6.75,6.68,2.34,-4.35,0.54,1.14,-0.15,1.98,4.82,-2.35,11.40,10.83,9.62,3.60,1.69,2.98,10.17,0.15,-0.67,3.74,2.47,-4.22,0.62,4.12,11.16,9.65,5.68,2.00,1.54,15.80,-1.10,0.94,-2.15,3.37,6.70,4.83,7.88,4.89,2.55,0.04,2.00,4.98,2.62,8.02,-5.31,5.72,5.54,4.05,-1.79,2.08,1.05,13.75,-6.06,5.36,3.66,-0.96,2.42,8.09,4.01,1.62,-1.20,-2.36,0.70,5.30,-0.43,11.69,10.06,0.41,2.56,-0.31,3.44,5.13,-2.82,2.43,1.37,-2.32,4.00,-2.00,-0.70,-0.28,-0.24,5.81,2.36,0.98,2.14,3.10,-2.87,-1.86,0.86,0.95,-2.15,2.59,1.33,2.74,4.87,3.92,-0.22,3.50,4.39,-6.36,1.09,-3.92,2.15,2.92,7.40,-0.17,-0.20,-3.87,-1.90,3.52,5.45,-1.74,-2.87,-1.29,7.54,1.94,-7.01,0.42,3.65,2.74,5.50,3.68,1.89,6.46,1.11,1.41,-1.02,2.67,1.65,-2.27,-4.52,3.24,1.15,-0.43,1.83,-3.11,5.15,1.34,2.05,1.88,0.72,3.36,6.97,16.03,4.63,0.10,-3.98,-1.75,1.27,9.61,8.33,8.24,8.64,6.48,6.09,2.08,-0.60,4.37,-1.02,0.55,-3.65,3.43,-0.83,-0.38 2024-01-23 09:16:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 28: train = +1.4969(26.27m/2260) | dev = +2.0776(1.79m/432) | no impr, best = 1.9537 2024-01-23 09:16:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 09:18:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +2.00)... 2024-01-23 09:21:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +1.66)... 2024-01-23 09:23:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = +1.09)... 2024-01-23 09:25:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = +1.69)... 2024-01-23 09:28:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = +1.62)... 2024-01-23 09:30:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1200 batches(loss = +1.30)... 2024-01-23 09:32:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1400 batches(loss = +1.51)... 2024-01-23 09:36:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:173 - INFO ] Create optimizer adam: {'lr': 0.001, 'weight_decay': 1e-05} 2024-01-23 09:36:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:140 - INFO ] Model summary: ConvTasNet( (encoder_1d): Conv1D(1, 512, kernel_size=(40,), stride=(20,)) (ln): ChannelWiseLayerNorm((512,), eps=1e-05, elementwise_affine=True) (proj): Conv1D(512, 256, kernel_size=(1,), stride=(1,)) (repeats): Sequential( (0): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) (1): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) (2): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) (3): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) ) (mask): Conv1D(256, 1024, kernel_size=(1,), stride=(1,)) (decoder_1d): ConvTrans1D(512, 1, kernel_size=(40,), stride=(20,)) ) 2024-01-23 09:36:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:141 - INFO ] Loading model to GPUs:(4, 5), #param: 8.98M 2024-01-23 09:36:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:145 - INFO ] Gradient clipping by 5, default L2 2024-01-23 09:36:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 09:37:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +48.22)... 2024-01-23 09:38:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +48.64)... 2024-01-23 09:38:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 43.11,60.48,47.35,49.27,45.72,48.85,42.12,52.22,47.49,49.88,49.05,45.36,49.00,42.33,48.74,46.86,49.22,43.43,49.33,50.30,44.81,42.76,47.33,46.64,51.27,47.37,55.22,47.99,46.91,43.71,47.22,49.75,46.55,47.89,52.83,46.75,44.90,51.25,44.02,44.07,43.68,42.45,47.54,48.29,44.82,42.70,48.05,46.79,54.48,63.99,49.86,45.88,46.60,47.59,47.64,50.74,41.80,46.49,43.22,49.87,49.21,47.17,46.24,50.32,49.92,40.15,48.27,41.65,40.53,49.61,57.80,50.68,49.19,50.22,47.70,43.28,46.04,48.54,46.52,47.13,44.00,48.61,43.17,56.57,46.58,52.14,52.60,49.69,45.52,51.67,45.72,48.72,57.34,65.67,54.55,57.53,68.14,48.80,70.81,55.17,47.45,44.62,44.92,48.04,48.55,44.85,53.46,46.78,47.64,43.03,45.18,48.28,40.76,47.98,48.06,47.00,48.69,46.83,54.03,55.54,52.76,56.57,55.36,48.91,59.09,47.05,45.59,48.63,47.54,46.89,46.70,47.14,51.23,43.79,45.51,42.46,48.17,45.95,48.50,46.56,48.57,54.10,51.81,45.98,50.00,41.79,46.66,57.09,50.73,40.81,54.75,45.50,53.64,50.75,50.17,48.34,41.44,46.24,44.72,43.50,44.41,43.75,43.96,43.53,40.47,46.22,44.08,43.26,45.38,50.40,44.63,55.58,52.74,49.95,51.29,49.23,45.84,50.76,50.44,51.58,41.18,43.75,48.84,47.16,45.78,41.06,52.93,45.55,45.12,50.88,47.04,44.77,47.95,49.36,49.06,46.69,47.53,41.53,46.85,45.94,46.45,49.78,44.43,44.03,48.22,49.25,53.83,59.96,47.87,46.49,52.34,36.97,44.07,42.96,53.90,45.75,52.40,49.07,48.53,52.17,53.82,52.77,49.19,42.30,51.99,46.25,46.58,51.62,50.99,45.23,44.33,48.10,53.48,47.83,43.51,43.50,42.14,45.25,47.00,51.58,46.18,47.21,56.42,47.62,52.93,54.98,49.79,44.07,51.13,40.09,46.86,52.13,53.72,54.00,46.54,51.91,52.01,46.38,49.56,44.08,44.95,47.66,51.28,53.49,48.14,49.20,48.51,46.78,51.72,50.08,48.78,42.44,47.03,45.63,47.74,49.74,51.06,42.92,53.39,55.74,54.15,49.91,50.17,51.35,55.46,42.86,48.49,46.46,47.26,41.78,46.71,52.60,53.14,56.31,53.16,50.56,47.47,61.65,47.44,46.13,43.87,52.09,55.70,52.25,57.02,50.99,49.97,47.57,47.32,51.70,48.32,54.18,43.19,54.53,50.61,53.74,44.28,46.25,45.86,61.69,41.88,50.36,50.59,49.17,50.69,54.69,50.04,47.40,44.09,42.84,45.43,52.11,49.05,59.20,54.56,42.79,48.09,48.46,45.81,51.80,45.50,50.85,47.61,42.50,51.95,46.92,45.99,43.33,44.53,54.20,52.27,46.81,47.19,52.14,43.14,44.99,46.50,47.01,43.77,49.37,49.50,50.77,54.33,50.43,45.71,49.82,51.22,40.90,46.50,44.99,45.63,45.44,53.97,45.85,42.31,43.94,45.55,50.00,53.12,43.68,43.79,45.62,51.60,45.33,41.81,45.00,48.69,45.14,53.02,49.08,48.18,52.45,47.22,49.32,42.49,47.74,48.28,46.94,45.34,48.57,45.46,43.57,52.02,43.45,50.95,47.40,52.54,47.52,46.11,52.94,53.76,64.31,50.84,41.70,43.34,42.90,47.11,57.66,55.99,57.13,56.04,55.40,53.33,48.09,48.54,49.82,44.89,46.11,43.86,51.35,45.75,43.23 2024-01-23 09:38:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:221 - INFO ] START FROM EPOCH 0, LOSS = 48.5094 2024-01-23 09:38:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 09:41:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +1.15)... 2024-01-23 09:43:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -0.81)... 2024-01-23 09:45:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -1.12)... 2024-01-23 09:48:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -1.43)... 2024-01-23 09:50:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -1.65)... 2024-01-23 09:51:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 09:52:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +8.47)... 2024-01-23 09:53:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +8.72)... 2024-01-23 09:53:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 4.43,23.10,6.44,9.84,7.45,9.51,3.66,11.82,6.45,11.08,9.09,6.46,9.61,0.84,10.07,6.59,8.31,0.77,11.55,9.93,2.69,6.01,6.35,6.02,11.04,5.07,18.48,7.54,8.64,2.97,5.60,7.03,3.12,5.78,11.84,8.86,5.67,9.06,6.80,8.17,3.36,-0.32,8.31,5.94,2.90,4.77,6.40,6.22,15.67,29.46,9.40,3.71,7.34,9.22,5.46,7.85,0.21,5.67,2.46,9.89,8.93,6.18,6.36,11.71,15.32,0.12,4.59,1.16,1.65,8.53,20.87,7.96,7.75,10.41,8.49,1.66,6.64,5.08,9.07,6.44,4.98,7.06,-0.94,19.50,5.56,15.30,18.95,10.54,6.67,12.43,4.89,8.13,18.67,28.53,14.58,20.93,37.90,7.22,38.93,13.38,11.67,2.50,3.83,7.64,4.56,1.27,11.40,5.21,9.40,2.50,5.03,8.80,0.91,9.15,6.63,8.66,9.38,7.18,13.13,18.15,15.27,19.22,13.72,11.19,23.27,8.73,5.89,8.38,7.73,1.92,10.09,6.88,10.95,2.38,4.57,-0.67,7.11,6.57,6.75,5.57,8.96,14.85,7.76,5.39,8.17,3.85,5.05,21.29,9.60,-1.37,16.32,7.17,18.98,9.58,9.76,10.73,-1.41,5.44,8.25,4.31,7.11,3.08,1.16,5.67,1.49,9.28,4.47,1.91,3.16,12.11,2.32,22.73,12.26,12.89,12.18,10.91,5.65,11.00,9.22,13.35,1.18,5.04,9.66,2.21,4.53,0.66,14.38,9.22,4.50,13.62,8.96,4.71,9.60,10.22,13.87,7.83,5.19,2.58,4.57,4.45,2.55,8.89,-0.01,7.15,5.99,6.93,12.53,21.37,8.67,9.80,12.86,-0.73,7.62,3.60,14.15,4.24,12.01,6.69,10.10,11.42,11.03,11.74,11.38,-0.66,13.26,7.65,7.85,13.19,10.90,4.35,6.69,4.28,11.44,5.58,1.90,0.93,2.36,6.87,6.90,10.64,8.69,5.37,17.19,9.13,13.96,16.85,10.14,1.71,7.80,-0.74,4.27,11.88,13.75,13.97,7.75,12.30,10.78,5.34,9.36,1.22,2.68,5.72,11.35,16.88,5.28,8.80,13.27,7.16,14.41,12.59,10.36,0.73,4.91,5.76,5.88,8.24,13.66,2.67,19.07,20.95,18.93,11.78,10.61,12.57,20.36,6.07,7.99,7.04,7.52,1.90,8.20,11.17,19.18,19.62,13.55,10.39,9.03,26.22,5.31,8.67,1.64,9.66,17.95,13.20,17.20,10.64,8.35,7.21,6.10,14.06,13.38,19.37,1.36,12.90,10.55,13.93,2.82,6.69,4.53,24.81,1.13,11.77,11.02,5.20,11.04,17.15,9.40,8.76,5.16,0.01,5.09,11.68,6.78,22.81,17.50,6.03,9.65,8.03,8.10,12.22,4.35,8.57,7.45,0.51,10.94,2.21,3.96,2.09,4.59,13.23,10.71,5.99,7.65,12.21,4.47,0.52,6.10,7.54,4.14,8.65,9.76,7.75,14.99,10.73,4.15,8.84,11.02,-1.84,7.00,-0.17,5.97,7.38,16.80,3.38,0.64,2.29,6.57,11.48,12.49,3.45,3.76,4.34,13.63,7.61,-1.47,5.47,9.02,8.12,15.96,10.39,8.79,13.72,7.81,8.38,2.06,8.03,6.85,4.68,1.73,9.67,6.06,3.12,9.88,2.56,12.13,7.95,8.91,9.32,7.21,10.13,14.05,25.64,10.58,2.47,2.74,2.81,6.73,19.53,16.47,19.06,18.13,19.67,14.63,11.93,7.25,11.31,3.23,7.69,5.80,11.10,6.33,4.47 2024-01-23 09:53:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 1: train = -0.9133(13.41m/1151) | dev = +8.6948(1.83m/432) 2024-01-23 09:53:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 09:56:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -2.04)... 2024-01-23 09:58:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -2.23)... 2024-01-23 10:00:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -2.48)... 2024-01-23 10:03:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -2.68)... 2024-01-23 10:05:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -2.95)... 2024-01-23 10:07:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 10:08:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +7.58)... 2024-01-23 10:08:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = +7.40)... 2024-01-23 10:08:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 432 batches: 3.59,22.89,5.94,8.66,6.70,8.80,3.12,10.76,3.79,9.87,9.24,4.98,8.51,-0.27,9.53,5.76,7.56,0.27,11.00,8.87,0.86,4.90,5.55,5.66,10.33,3.85,17.94,6.83,7.51,1.61,4.94,6.80,2.79,4.98,10.71,8.46,4.60,8.66,6.27,7.74,2.76,-1.09,7.15,4.86,2.07,3.29,5.33,4.83,15.37,28.88,8.90,2.94,7.09,8.47,4.87,7.22,-0.17,5.51,1.42,9.09,7.33,5.92,5.95,10.71,14.98,-0.81,4.08,-1.05,-0.46,7.84,20.74,6.41,5.39,8.91,7.53,0.93,5.90,4.06,8.71,5.93,4.48,5.63,-1.63,18.84,4.59,15.05,17.95,9.57,5.92,12.35,4.21,7.29,18.44,28.10,14.31,19.90,36.84,5.94,38.37,12.38,10.70,1.38,2.68,6.49,3.93,0.81,11.36,4.74,8.01,1.73,4.14,7.97,0.62,7.96,4.31,7.27,8.34,6.14,12.02,17.34,15.14,18.01,12.51,9.78,22.12,8.14,5.29,7.56,6.68,1.02,9.76,6.76,10.82,1.44,3.76,-1.90,5.79,5.65,5.39,5.24,8.63,13.80,6.98,4.61,7.45,3.00,3.24,19.77,7.62,-2.10,17.01,5.72,18.43,9.09,9.01,9.84,-1.96,5.20,6.78,2.57,5.99,2.34,0.10,4.21,0.87,8.82,3.86,0.80,2.57,10.53,0.45,21.74,11.60,12.31,11.00,10.04,5.13,9.78,7.51,12.06,0.35,4.47,8.69,1.09,3.83,0.00,13.55,8.58,3.39,12.37,7.69,2.05,7.54,9.62,12.96,7.15,4.67,1.45,3.73,3.37,1.33,7.04,-1.69,7.09,5.53,6.69,11.70,20.27,8.15,8.85,12.16,-2.34,7.09,2.53,13.50,3.43,10.72,5.77,8.78,9.51,9.80,10.00,9.86,-3.50,10.69,5.57,5.39,12.55,9.45,2.71,5.45,3.04,10.17,4.58,0.73,-0.40,0.46,5.62,5.28,9.13,6.84,2.24,15.92,7.62,12.56,15.94,9.06,0.37,6.13,-1.85,3.37,9.80,12.22,12.31,5.52,10.49,9.64,3.07,7.36,0.10,1.58,4.13,10.42,15.73,4.03,7.79,11.67,5.57,13.14,11.35,9.30,-0.76,3.67,4.35,4.85,7.31,12.08,1.24,17.76,19.93,17.82,10.53,9.00,11.09,19.26,5.02,6.36,6.17,6.36,0.30,6.14,10.23,19.02,18.59,12.47,8.57,7.43,25.53,4.44,7.38,0.31,8.59,16.61,12.19,15.92,8.98,7.57,5.83,4.60,13.05,11.60,18.13,-0.67,11.85,9.30,12.64,2.15,5.28,3.19,23.67,0.22,11.28,10.18,3.39,9.45,15.72,8.17,7.18,3.00,-1.02,3.76,10.66,5.21,22.28,16.93,5.16,8.21,6.63,6.77,10.77,3.17,7.48,6.63,-0.23,9.74,0.94,2.95,1.44,3.55,12.42,8.88,4.68,6.06,10.32,2.97,-0.93,5.03,6.07,2.85,7.19,7.15,6.07,13.59,9.49,2.82,7.76,10.04,-3.41,5.90,-2.16,4.29,6.46,15.45,1.98,-0.02,1.15,5.58,10.42,11.09,2.28,2.26,2.97,12.69,6.23,-4.06,4.01,8.27,7.00,14.76,9.39,7.95,12.39,6.50,7.23,0.69,6.17,4.72,2.78,-0.41,8.14,4.53,2.19,8.22,1.06,11.33,7.37,7.68,7.29,5.89,9.25,13.75,24.21,8.81,1.57,1.64,1.24,5.36,18.25,15.25,18.10,17.16,17.98,13.45,10.45,5.46,10.41,2.18,5.89,3.55,9.96,4.70,3.58 2024-01-23 10:08:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 2: train = -2.5646(13.26m/1152) | dev = +7.5794(1.78m/432) 2024-01-23 10:08:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 10:11:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -3.20)... 2024-01-23 10:13:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -3.48)... 2024-01-23 10:15:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -3.60)... 2024-01-23 10:18:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -3.82)... 2024-01-23 10:19:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:173 - INFO ] Create optimizer adam: {'lr': 0.001, 'weight_decay': 1e-05} 2024-01-23 10:19:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:140 - INFO ] Model summary: ConvTasNet( (encoder_1d): Conv1D(1, 512, kernel_size=(40,), stride=(20,)) (ln): ChannelWiseLayerNorm((512,), eps=1e-05, elementwise_affine=True) (proj): Conv1D(512, 256, kernel_size=(1,), stride=(1,)) (repeats): Sequential( (0): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) (1): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) (2): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) (3): Sequential( (0): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(1,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (1): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(2,), dilation=(2,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (2): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(4,), dilation=(4,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (3): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(8,), dilation=(8,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (4): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(16,), dilation=(16,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (5): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(32,), dilation=(32,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (6): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(64,), dilation=(64,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) (7): Conv1DBlock( (conv1x1): Conv1D(256, 512, kernel_size=(1,), stride=(1,)) (prelu1): PReLU(num_parameters=1) (lnorm1): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (dconv): Conv1d(512, 512, kernel_size=(3,), stride=(1,), padding=(128,), dilation=(128,), groups=512) (prelu2): PReLU(num_parameters=1) (lnorm2): GlobalChannelLayerNorm(512, eps=1e-05, elementwise_affine=True) (sconv): Conv1d(512, 256, kernel_size=(1,), stride=(1,)) ) ) ) (mask): Conv1D(256, 1024, kernel_size=(1,), stride=(1,)) (decoder_1d): ConvTrans1D(512, 1, kernel_size=(40,), stride=(20,)) ) 2024-01-23 10:19:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:141 - INFO ] Loading model to GPUs:(4, 5), #param: 8.98M 2024-01-23 10:19:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:145 - INFO ] Gradient clipping by 5, default L2 2024-01-23 10:19:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 10:20:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 44.19,45.20,43.93,46.07,45.68,45.51,45.50,47.21,45.02,44.86,44.93,45.26,46.38,45.37,45.16,43.01,46.18,45.45,45.49,45.43,44.45,45.65,46.88,44.95,45.78,45.99,44.47,44.34,45.76,44.73,44.11,45.33,46.51,44.58,46.46,45.84,45.59,44.80,44.56,44.41,43.93,43.50,46.07,44.03,45.76,45.19,46.36,44.16,45.08,45.53,45.61,45.41,45.54,45.74,44.98,44.38,45.53,46.31,48.42,45.94,46.55,45.36,45.53,45.18,45.46,45.69,46.28,45.05,45.11,44.41,48.98,44.91,44.73,43.98,44.78,44.59,43.90,45.82,45.88,46.62,44.67,45.57,45.66,45.02,45.70,46.24,43.52,44.22,44.75,46.83,45.18,44.60,44.23,43.82,45.91,45.44,44.41,47.08,46.78,46.04,45.16,45.68,44.99,43.42,46.02,44.86,45.06,45.35,43.69,46.13,45.25,44.12,43.81,47.85,44.71,45.78,44.91,46.18,45.65,45.48,46.85,45.62,46.88,46.13,44.98,45.65,44.72,45.03,44.74,46.60,44.58,45.24,46.72,46.16,44.23,46.13,46.23,46.43,44.89,46.03,44.14,45.35,44.31,44.15,44.28,43.68,45.07,44.66,43.37,45.46,44.63,47.03,45.66,44.36,44.69,44.80,45.65,45.18,45.38,44.94,45.73,45.78,45.01,46.52,44.38,44.41,44.75,46.09,45.63,45.89,45.98,46.01,44.26 2024-01-23 10:20:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:221 - INFO ] START FROM EPOCH 0, LOSS = 45.3068 2024-01-23 10:20:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 10:23:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = +1.36)... 2024-01-23 10:25:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -0.82)... 2024-01-23 10:27:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -1.26)... 2024-01-23 10:29:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -1.56)... 2024-01-23 10:32:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -1.81)... 2024-01-23 10:33:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 10:34:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -1.15,-3.32,-1.83,-2.31,-1.79,-1.71,-3.05,-2.16,-1.86,-3.16,-1.57,-2.55,-2.93,-2.57,-1.89,-1.18,-2.00,-2.54,-2.02,-2.46,-2.91,-1.92,-3.02,-2.62,-2.53,-2.47,-2.09,-1.84,-1.95,-2.00,-1.94,-2.52,-1.54,-2.87,-2.83,-2.99,-2.11,-2.55,-1.91,-2.49,-1.35,-1.95,-2.26,-2.05,-2.32,-2.53,-1.02,-2.43,-2.70,-1.68,-2.03,-2.84,-2.73,-3.41,-3.47,-2.32,-1.56,-3.11,-2.05,-1.66,-2.88,-1.81,-2.33,-2.35,-1.85,-0.78,-1.30,-2.06,-3.35,-2.42,-2.81,-2.05,-2.46,-2.18,-3.54,-2.62,-3.16,-1.64,-1.63,-2.15,-2.39,-2.09,-1.53,-1.54,-3.15,-1.69,-2.26,-2.83,-2.76,-2.61,-2.14,-1.63,-3.70,-2.79,-4.36,-2.60,-1.93,-2.29,-1.23,-1.59,-3.20,-2.68,-2.65,-1.70,-1.81,-3.36,-3.41,-2.39,-1.89,-1.88,-2.09,-3.46,-2.59,-2.32,-2.13,-3.63,-2.34,-1.88,-2.67,-1.28,-3.06,-1.71,-3.21,-1.50,-2.45,-1.26,-2.05,-1.83,-2.35,-2.10,-1.35,-2.68,-1.99,-1.22,-1.16,-3.27,-2.41,-3.53,-2.57,-2.70,-1.30,-2.45,-1.98,-1.78,-2.59,-3.60,-2.10,-2.85,-2.55,-1.97,-2.19,-2.47,-1.55,-2.80,-2.79,-1.74,-2.22,-1.96,-2.22,-2.66,-1.68,-2.74,-2.52,-2.73,-2.49,-2.34,-2.31,-2.62,-3.16,-1.98,-1.73,-2.13,-1.53 2024-01-23 10:34:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 1: train = -0.9717(13.25m/1151) | dev = -2.3038(0.82m/173) 2024-01-23 10:34:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 10:37:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -2.14)... 2024-01-23 10:39:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -2.38)... 2024-01-23 10:41:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -2.66)... 2024-01-23 10:43:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -2.87)... 2024-01-23 10:46:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -3.05)... 2024-01-23 10:47:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 10:48:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -2.25,-4.25,-2.67,-4.29,-3.00,-3.19,-4.38,-3.82,-2.88,-4.06,-2.43,-3.82,-4.32,-4.19,-2.66,-1.64,-3.24,-3.33,-3.38,-3.36,-3.90,-3.02,-4.21,-3.64,-3.86,-3.37,-2.72,-3.37,-3.18,-4.10,-2.62,-4.22,-2.38,-4.34,-3.87,-4.19,-3.02,-3.70,-2.76,-3.99,-2.43,-2.79,-2.94,-3.25,-3.69,-3.83,-3.21,-3.23,-3.65,-3.44,-2.89,-4.46,-3.98,-4.18,-3.94,-3.00,-2.70,-4.34,-3.43,-3.67,-4.43,-3.28,-2.69,-2.98,-3.75,-1.90,-2.28,-2.62,-4.50,-4.07,-4.28,-3.33,-4.11,-2.94,-5.17,-4.14,-4.63,-3.36,-2.99,-2.96,-3.93,-3.78,-3.16,-2.16,-4.09,-2.32,-3.43,-3.90,-4.42,-4.23,-3.59,-4.10,-5.36,-4.32,-5.57,-3.82,-3.69,-4.28,-2.91,-3.48,-4.72,-3.40,-4.74,-3.56,-3.29,-4.34,-5.04,-3.73,-3.13,-3.22,-3.69,-4.69,-3.75,-4.14,-3.49,-4.99,-4.49,-2.94,-4.02,-2.28,-4.48,-3.26,-4.52,-2.21,-4.50,-2.73,-3.42,-3.00,-3.51,-4.32,-3.41,-3.95,-3.53,-1.64,-2.59,-4.37,-3.71,-4.69,-3.21,-4.03,-2.15,-4.21,-2.77,-3.10,-4.35,-5.16,-2.92,-4.47,-3.74,-3.39,-3.27,-3.44,-3.02,-3.84,-4.84,-2.69,-3.39,-3.41,-3.74,-3.95,-2.65,-3.94,-3.41,-4.03,-3.79,-3.24,-3.72,-3.79,-4.69,-3.34,-3.18,-3.33,-2.84 2024-01-23 10:48:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 2: train = -2.7048(13.13m/1152) | dev = -3.5846(0.81m/173) 2024-01-23 10:48:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 10:51:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -3.40)... 2024-01-23 10:53:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -3.55)... 2024-01-23 10:55:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -3.73)... 2024-01-23 10:57:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -3.91)... 2024-01-23 11:00:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -3.99)... 2024-01-23 11:01:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 11:02:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -3.07,-5.21,-3.24,-5.62,-3.77,-4.30,-5.18,-4.82,-3.99,-5.22,-3.19,-4.78,-5.34,-4.87,-3.97,-2.71,-4.42,-4.41,-5.06,-4.20,-5.09,-3.97,-5.24,-4.05,-4.79,-4.43,-3.27,-5.04,-3.53,-6.13,-3.67,-5.63,-4.03,-5.38,-4.63,-5.34,-3.80,-4.52,-3.48,-4.41,-3.45,-4.11,-4.05,-4.40,-4.81,-4.54,-4.76,-4.69,-4.73,-4.82,-3.96,-5.11,-4.98,-5.08,-5.19,-3.80,-3.75,-5.53,-4.53,-4.63,-4.86,-4.72,-4.36,-3.89,-4.54,-2.47,-3.35,-3.83,-5.20,-5.29,-5.29,-4.54,-4.55,-4.18,-6.19,-5.16,-5.47,-3.91,-4.24,-4.12,-5.15,-4.65,-4.51,-2.57,-5.42,-3.52,-4.98,-5.18,-5.07,-4.98,-4.82,-5.26,-6.33,-4.97,-6.36,-4.91,-4.82,-5.43,-3.70,-4.28,-5.49,-4.27,-5.32,-4.38,-4.02,-5.24,-6.39,-4.78,-4.68,-4.26,-4.38,-5.53,-4.93,-4.93,-4.47,-5.89,-5.23,-3.46,-4.97,-3.10,-5.60,-3.91,-5.43,-2.26,-5.32,-3.53,-4.54,-4.07,-4.65,-5.57,-4.55,-5.52,-5.17,-2.19,-3.65,-5.76,-4.61,-5.47,-4.11,-5.25,-3.47,-5.14,-3.71,-3.62,-5.14,-5.93,-3.23,-5.17,-4.70,-4.41,-4.43,-3.75,-3.71,-4.41,-5.47,-3.20,-4.37,-3.77,-4.44,-4.92,-3.74,-4.58,-4.50,-4.70,-4.63,-4.28,-4.69,-3.99,-5.64,-4.22,-4.49,-4.73,-3.77 2024-01-23 11:02:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 3: train = -3.7651(13.18m/1151) | dev = -4.5527(0.83m/173) 2024-01-23 11:02:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 11:05:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -4.34)... 2024-01-23 11:07:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -4.41)... 2024-01-23 11:09:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -4.51)... 2024-01-23 11:11:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -4.46)... 2024-01-23 11:14:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -4.45)... 2024-01-23 11:15:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 11:16:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -3.91,-5.68,-3.96,-6.22,-4.41,-4.49,-5.79,-5.63,-4.69,-5.53,-3.24,-5.69,-6.06,-5.61,-4.74,-3.45,-5.19,-5.18,-5.81,-5.08,-5.59,-4.15,-5.97,-5.10,-5.41,-4.63,-4.11,-5.75,-4.17,-6.57,-4.52,-6.17,-4.13,-5.68,-4.87,-5.94,-4.59,-5.14,-3.90,-5.01,-4.27,-4.74,-4.49,-4.89,-5.28,-5.79,-5.16,-5.65,-5.49,-5.46,-4.47,-5.63,-5.39,-5.81,-5.66,-5.18,-4.44,-6.13,-4.74,-5.54,-5.90,-5.68,-5.09,-4.49,-4.80,-3.59,-4.41,-4.64,-5.82,-6.18,-6.17,-5.19,-5.39,-4.87,-6.81,-5.53,-5.72,-4.58,-4.76,-4.57,-5.45,-5.32,-5.12,-3.64,-5.82,-4.42,-5.32,-5.27,-5.78,-5.59,-5.50,-5.85,-6.88,-5.69,-6.87,-5.14,-5.23,-5.76,-4.69,-4.86,-6.18,-4.66,-5.88,-5.17,-4.66,-5.76,-6.73,-5.25,-5.67,-4.93,-4.55,-6.32,-5.83,-5.19,-4.94,-6.65,-5.96,-4.35,-5.72,-3.81,-6.23,-4.50,-6.21,-3.75,-6.07,-4.32,-5.07,-4.95,-4.83,-6.25,-5.01,-6.15,-5.65,-2.97,-4.45,-6.22,-5.39,-5.98,-4.61,-5.72,-3.83,-5.63,-4.31,-4.75,-5.98,-6.68,-4.00,-5.61,-4.99,-5.19,-4.54,-4.99,-4.56,-5.10,-6.31,-4.38,-5.06,-4.56,-5.08,-5.60,-4.40,-5.16,-4.46,-5.39,-5.37,-4.84,-5.31,-5.20,-6.12,-4.88,-4.96,-5.36,-4.36 2024-01-23 11:16:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 4: train = -4.4648(13.10m/1152) | dev = -5.1899(0.83m/173) 2024-01-23 11:16:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 11:19:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -4.93)... 2024-01-23 11:21:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -4.92)... 2024-01-23 11:23:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -4.95)... 2024-01-23 11:25:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -5.02)... 2024-01-23 11:28:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -5.13)... 2024-01-23 11:29:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 11:30:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -3.89,-6.17,-4.26,-6.68,-4.95,-4.98,-6.32,-5.78,-5.10,-6.08,-3.57,-5.78,-6.20,-5.95,-5.43,-3.36,-5.41,-5.57,-6.34,-5.06,-5.92,-4.31,-6.19,-5.04,-5.81,-5.34,-4.40,-6.43,-4.77,-7.06,-4.66,-6.75,-5.25,-6.45,-5.17,-6.44,-4.73,-5.59,-3.73,-5.57,-4.10,-5.06,-4.79,-5.15,-5.87,-5.96,-5.76,-6.07,-5.72,-5.90,-4.86,-6.37,-5.94,-5.93,-6.27,-5.59,-4.84,-6.60,-5.54,-6.05,-6.38,-6.32,-5.31,-5.04,-5.90,-3.57,-4.16,-4.68,-6.32,-6.46,-6.48,-5.77,-6.00,-5.12,-7.12,-6.12,-6.29,-5.23,-5.40,-5.09,-6.09,-5.93,-5.63,-3.74,-6.20,-4.55,-5.91,-5.97,-6.17,-5.91,-6.05,-6.08,-7.36,-5.98,-7.27,-5.45,-5.68,-6.29,-4.48,-5.34,-6.64,-5.14,-6.60,-5.48,-5.15,-6.17,-7.24,-5.55,-6.39,-5.32,-5.04,-6.57,-5.88,-5.58,-5.27,-6.76,-6.13,-4.48,-6.09,-3.95,-6.41,-3.86,-6.29,-3.72,-6.72,-4.55,-5.44,-5.42,-5.33,-6.61,-4.86,-6.69,-6.07,-3.12,-4.43,-6.81,-5.71,-6.18,-4.74,-6.33,-3.97,-6.07,-4.71,-5.20,-6.48,-7.11,-4.30,-6.03,-5.47,-5.51,-5.29,-5.35,-4.72,-5.19,-6.68,-4.48,-5.30,-4.95,-5.52,-6.17,-4.99,-5.28,-5.31,-5.76,-5.67,-5.36,-5.85,-5.64,-6.51,-4.82,-5.34,-5.78,-4.78 2024-01-23 11:30:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 5: train = -4.9917(13.17m/1152) | dev = -5.5602(0.83m/173) 2024-01-23 11:30:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 11:33:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -5.28)... 2024-01-23 11:35:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -5.32)... 2024-01-23 11:37:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -5.35)... 2024-01-23 11:39:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -5.30)... 2024-01-23 11:42:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -5.44)... 2024-01-23 11:43:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 11:44:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -4.49,-6.59,-4.52,-7.39,-4.98,-5.19,-6.32,-6.09,-5.24,-6.38,-3.95,-6.40,-6.74,-6.43,-5.74,-3.67,-6.03,-5.94,-6.65,-5.75,-6.01,-4.81,-6.29,-5.78,-6.08,-5.06,-4.98,-6.49,-5.32,-7.08,-5.13,-7.28,-5.12,-6.56,-5.14,-6.68,-5.21,-5.81,-4.36,-6.03,-4.62,-5.60,-5.27,-5.22,-6.13,-6.23,-5.94,-6.32,-6.28,-5.46,-5.01,-6.82,-5.99,-6.44,-6.51,-5.76,-5.49,-6.80,-5.50,-6.15,-6.14,-5.97,-6.24,-5.73,-6.28,-4.34,-4.74,-5.13,-6.29,-6.83,-6.58,-6.14,-6.16,-5.65,-7.50,-6.04,-6.45,-5.27,-5.09,-5.52,-6.47,-5.77,-5.87,-4.15,-6.28,-4.73,-5.61,-5.59,-6.70,-6.67,-6.10,-6.25,-6.89,-5.99,-7.40,-5.74,-6.21,-6.88,-5.39,-5.68,-6.85,-5.32,-7.15,-5.56,-5.37,-6.37,-7.47,-6.23,-5.84,-5.99,-5.35,-7.04,-6.43,-6.00,-5.28,-6.67,-6.10,-4.56,-6.16,-4.52,-6.73,-5.29,-6.95,-4.52,-6.73,-4.88,-5.85,-5.52,-5.76,-6.80,-5.66,-6.58,-6.39,-3.44,-4.81,-6.96,-5.91,-6.49,-5.26,-6.22,-4.48,-6.30,-5.26,-5.52,-6.66,-6.93,-4.78,-6.14,-5.83,-5.53,-5.17,-5.70,-5.09,-5.60,-7.18,-5.16,-5.65,-5.24,-5.82,-6.30,-4.94,-6.07,-5.54,-5.97,-5.96,-5.33,-6.10,-5.81,-6.61,-5.72,-5.69,-5.87,-4.68 2024-01-23 11:44:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 6: train = -5.3594(13.19m/1152) | dev = -5.8456(0.82m/173) 2024-01-23 11:44:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 11:47:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -5.61)... 2024-01-23 11:49:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -5.59)... 2024-01-23 11:51:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -5.73)... 2024-01-23 11:53:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -5.72)... 2024-01-23 11:56:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -5.71)... 2024-01-23 11:57:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 11:58:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -4.80,-6.98,-5.35,-7.23,-5.49,-5.36,-7.07,-6.76,-5.91,-6.69,-4.09,-6.76,-7.23,-6.94,-6.23,-4.13,-6.29,-6.85,-7.43,-5.59,-6.51,-4.94,-6.60,-6.14,-6.34,-5.90,-5.21,-6.77,-5.36,-7.58,-5.43,-7.65,-6.02,-7.14,-5.72,-7.21,-5.60,-6.42,-4.51,-5.92,-4.96,-5.88,-5.65,-5.82,-6.37,-7.04,-6.23,-6.82,-6.64,-6.12,-5.77,-7.24,-6.43,-6.90,-6.87,-6.55,-5.77,-7.25,-6.24,-6.68,-7.16,-6.89,-6.09,-5.62,-6.36,-4.96,-5.38,-5.14,-6.62,-6.78,-7.28,-6.59,-6.45,-6.11,-8.05,-6.70,-7.07,-5.13,-5.49,-5.98,-7.08,-6.59,-6.35,-4.69,-6.89,-5.81,-6.62,-6.33,-6.98,-6.84,-6.67,-6.81,-7.83,-6.40,-7.80,-6.01,-6.55,-7.28,-5.56,-6.08,-7.18,-5.52,-7.39,-6.06,-5.74,-6.78,-7.76,-6.57,-6.93,-6.24,-5.63,-7.37,-6.91,-6.25,-5.45,-7.09,-6.73,-5.07,-6.75,-4.89,-7.20,-5.50,-7.51,-4.77,-7.03,-5.38,-6.33,-6.10,-6.15,-7.16,-6.33,-7.37,-6.42,-3.61,-5.28,-7.47,-6.04,-7.08,-5.44,-7.11,-4.72,-6.49,-5.57,-5.90,-7.03,-7.58,-4.96,-6.57,-6.09,-5.88,-5.70,-5.97,-5.66,-5.77,-7.79,-5.72,-6.15,-5.90,-6.46,-6.90,-5.57,-6.19,-5.95,-6.62,-6.24,-6.04,-6.72,-6.08,-7.22,-6.10,-6.35,-6.23,-5.41 2024-01-23 11:58:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 7: train = -5.6900(13.10m/1151) | dev = -6.2860(0.83m/173) 2024-01-23 11:58:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 12:01:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -5.80)... 2024-01-23 12:03:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -5.90)... 2024-01-23 12:05:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -6.03)... 2024-01-23 12:07:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -5.96)... 2024-01-23 12:10:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -6.07)... 2024-01-23 12:11:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 12:12:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -5.08,-7.30,-5.41,-7.88,-5.67,-5.97,-7.06,-6.68,-6.13,-6.90,-4.62,-6.95,-7.37,-6.54,-6.74,-4.52,-6.37,-6.61,-7.31,-6.32,-6.68,-5.58,-6.92,-6.31,-6.72,-5.84,-5.28,-6.82,-5.58,-7.63,-5.45,-7.92,-5.69,-7.48,-6.16,-7.40,-5.94,-6.50,-4.42,-6.71,-4.86,-5.70,-5.78,-6.14,-6.36,-7.12,-6.59,-6.46,-6.82,-6.63,-5.64,-7.07,-6.42,-7.12,-7.15,-6.72,-6.01,-7.31,-6.33,-6.99,-7.15,-6.48,-6.49,-6.02,-6.66,-4.93,-5.90,-5.75,-6.97,-7.42,-7.35,-6.77,-6.93,-6.07,-8.07,-6.75,-6.97,-5.53,-5.52,-6.07,-7.08,-6.29,-6.47,-4.91,-7.16,-5.79,-6.44,-6.64,-7.22,-7.07,-6.92,-7.06,-8.02,-6.72,-8.00,-6.22,-6.66,-7.29,-6.28,-6.14,-7.27,-5.79,-7.65,-6.15,-5.89,-6.98,-8.06,-6.98,-7.17,-6.71,-5.87,-7.59,-7.03,-6.40,-6.37,-7.37,-7.01,-5.66,-7.10,-5.28,-7.48,-4.91,-7.27,-4.99,-7.32,-5.65,-6.14,-6.34,-6.38,-7.67,-6.65,-7.56,-6.94,-4.13,-5.62,-7.58,-6.48,-7.22,-5.57,-7.15,-5.16,-6.82,-5.95,-6.24,-7.10,-7.77,-5.48,-6.82,-6.50,-6.15,-6.00,-6.24,-5.59,-5.84,-7.74,-5.72,-6.16,-5.75,-6.32,-7.11,-5.75,-6.43,-6.21,-6.82,-6.55,-5.63,-6.86,-6.43,-7.35,-6.00,-6.63,-6.67,-5.67 2024-01-23 12:12:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 8: train = -5.9567(13.21m/1150) | dev = -6.4781(0.82m/173) 2024-01-23 12:12:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 12:15:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -6.15)... 2024-01-23 12:17:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -6.19)... 2024-01-23 12:19:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -6.10)... 2024-01-23 12:22:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -6.23)... 2024-01-23 12:24:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -6.28)... 2024-01-23 12:26:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 12:27:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -5.06,-7.18,-5.34,-8.09,-6.07,-5.79,-7.26,-6.90,-6.26,-6.94,-4.62,-7.21,-7.59,-7.36,-6.53,-4.74,-6.97,-7.06,-8.02,-6.39,-6.73,-5.50,-6.98,-6.47,-6.74,-6.20,-5.29,-7.08,-5.76,-8.14,-5.85,-7.69,-6.32,-7.73,-6.14,-7.35,-5.99,-6.60,-4.98,-6.62,-5.95,-6.47,-6.40,-6.38,-6.78,-7.34,-6.73,-7.40,-7.12,-6.80,-5.42,-7.51,-6.76,-7.30,-7.35,-6.75,-5.97,-7.52,-6.58,-6.76,-7.58,-6.91,-6.64,-6.37,-6.60,-4.89,-5.81,-6.17,-7.30,-6.95,-7.71,-7.07,-6.92,-6.31,-8.55,-7.14,-7.56,-5.89,-5.95,-6.34,-7.21,-6.83,-6.87,-5.38,-7.16,-5.88,-6.96,-6.66,-7.34,-7.43,-6.97,-7.25,-7.97,-6.81,-8.14,-6.34,-6.82,-7.34,-5.92,-6.06,-7.49,-6.08,-7.76,-6.54,-6.23,-7.11,-8.08,-7.01,-7.13,-6.83,-6.15,-7.69,-7.33,-6.60,-6.23,-7.81,-7.05,-5.69,-7.28,-5.31,-7.68,-5.59,-7.79,-4.80,-7.48,-5.41,-6.72,-6.50,-6.77,-7.69,-6.64,-7.62,-7.19,-4.41,-5.63,-7.84,-6.68,-7.35,-5.69,-7.53,-5.42,-6.90,-5.95,-6.55,-7.57,-8.17,-5.33,-6.90,-6.70,-6.61,-6.12,-6.87,-5.86,-6.08,-7.94,-5.98,-6.49,-5.92,-6.75,-7.47,-6.22,-6.32,-6.30,-7.03,-6.79,-6.16,-7.02,-6.65,-7.50,-6.51,-6.81,-6.83,-5.89 2024-01-23 12:27:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 9: train = -6.2047(13.65m/1151) | dev = -6.6868(0.86m/173) 2024-01-23 12:27:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 12:29:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -6.48)... 2024-01-23 12:32:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -6.40)... 2024-01-23 12:34:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -6.45)... 2024-01-23 12:37:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -6.49)... 2024-01-23 12:39:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -6.55)... 2024-01-23 12:41:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 12:41:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 12:41:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 10: train = -6.4683(13.91m/1150) | dev = -6.9671(0.83m/173) 2024-01-23 12:41:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 12:44:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -6.65)... 2024-01-23 12:46:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -6.54)... 2024-01-23 12:49:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -6.67)... 2024-01-23 12:51:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -6.76)... 2024-01-23 12:53:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -6.78)... 2024-01-23 12:55:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 12:56:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -5.24,-7.57,-5.74,-8.37,-6.26,-6.49,-7.77,-7.33,-6.58,-7.43,-4.96,-7.53,-8.07,-7.69,-7.12,-4.94,-7.18,-7.82,-8.32,-6.73,-7.42,-5.97,-7.47,-6.48,-7.01,-6.80,-5.95,-7.49,-6.11,-8.60,-5.90,-8.47,-6.94,-8.10,-6.72,-7.89,-6.41,-7.01,-5.26,-6.79,-6.25,-7.07,-6.75,-6.60,-7.46,-7.74,-7.06,-7.73,-7.33,-7.27,-6.12,-7.59,-7.07,-7.71,-7.79,-7.36,-6.47,-8.07,-7.06,-7.46,-7.84,-7.38,-7.04,-6.56,-6.99,-5.06,-5.93,-6.37,-7.52,-7.80,-7.83,-7.36,-7.47,-6.60,-8.82,-7.66,-7.78,-6.15,-6.64,-7.03,-7.75,-7.11,-7.33,-5.52,-7.81,-6.63,-7.36,-7.15,-7.76,-7.56,-7.54,-7.45,-8.79,-7.44,-8.50,-6.96,-7.13,-7.80,-6.43,-6.40,-7.76,-6.16,-8.08,-6.88,-6.89,-7.41,-8.51,-7.55,-7.92,-6.77,-6.64,-8.05,-7.79,-7.42,-7.05,-8.17,-7.63,-6.32,-7.64,-5.69,-8.15,-5.97,-8.20,-4.93,-8.20,-6.20,-7.13,-6.64,-6.76,-7.78,-7.19,-8.30,-7.68,-4.82,-6.28,-8.20,-6.77,-7.66,-6.09,-7.54,-5.79,-7.26,-6.52,-6.82,-8.08,-8.68,-5.76,-7.21,-7.20,-6.86,-6.45,-7.19,-6.31,-6.56,-8.14,-5.99,-6.81,-6.48,-7.46,-7.85,-6.57,-6.70,-6.88,-7.57,-7.40,-6.61,-7.40,-6.88,-7.95,-6.77,-7.15,-7.31,-6.29 2024-01-23 12:56:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 11: train = -6.6731(13.35m/1151) | dev = -7.0976(0.84m/173) 2024-01-23 12:56:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 12:58:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -6.87)... 2024-01-23 13:01:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -6.70)... 2024-01-23 13:03:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -6.92)... 2024-01-23 13:05:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -6.89)... 2024-01-23 13:08:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -6.80)... 2024-01-23 13:10:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 13:10:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -5.67,-8.03,-6.17,-8.87,-6.56,-6.46,-8.09,-7.71,-6.76,-7.56,-5.26,-7.44,-8.07,-7.86,-6.91,-5.45,-7.23,-7.85,-8.30,-6.94,-7.57,-5.82,-7.55,-6.96,-7.05,-6.82,-6.00,-7.89,-6.41,-8.52,-6.13,-8.59,-6.86,-8.38,-6.39,-7.93,-6.88,-7.39,-5.05,-6.98,-6.60,-7.38,-6.98,-6.86,-7.20,-7.92,-7.54,-7.51,-7.45,-7.41,-6.66,-7.98,-7.24,-7.95,-8.00,-7.31,-6.63,-8.22,-7.14,-7.41,-7.94,-7.91,-7.49,-6.89,-7.37,-5.68,-6.30,-6.61,-7.50,-8.01,-8.10,-7.41,-7.62,-6.85,-8.90,-7.59,-7.83,-6.39,-6.53,-6.89,-7.91,-7.24,-7.42,-5.84,-8.12,-7.09,-7.79,-7.25,-7.66,-7.58,-7.60,-7.78,-8.97,-7.40,-8.62,-6.98,-7.31,-7.74,-6.49,-6.19,-7.71,-6.40,-8.23,-7.05,-6.62,-7.52,-8.60,-7.71,-8.14,-7.17,-6.75,-8.06,-7.88,-7.17,-7.00,-8.20,-7.56,-5.81,-7.71,-5.32,-8.24,-6.14,-8.13,-5.28,-8.40,-5.95,-6.76,-6.89,-6.99,-8.43,-7.18,-8.37,-7.80,-5.11,-6.31,-8.29,-7.20,-7.71,-6.09,-8.00,-5.71,-7.51,-6.73,-6.89,-7.93,-8.67,-5.92,-7.51,-7.17,-6.96,-6.84,-7.19,-6.43,-6.43,-8.55,-6.22,-6.87,-6.40,-7.22,-7.99,-6.92,-7.17,-7.12,-7.68,-7.39,-6.33,-7.56,-6.93,-7.84,-6.95,-7.20,-7.30,-6.46 2024-01-23 13:10:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 12: train = -6.8326(13.88m/1151) | dev = -7.2276(0.85m/173) 2024-01-23 13:10:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 13:13:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -7.01)... 2024-01-23 13:15:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -6.96)... 2024-01-23 13:18:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -6.96)... 2024-01-23 13:20:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -6.96)... 2024-01-23 13:22:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -6.89)... 2024-01-23 13:24:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 13:25:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -5.96,-8.55,-6.38,-8.72,-6.83,-6.56,-8.20,-7.91,-6.97,-8.09,-5.37,-7.89,-8.43,-8.08,-7.43,-5.68,-7.64,-7.57,-8.71,-7.08,-7.67,-6.38,-7.47,-7.18,-7.16,-7.16,-6.63,-7.99,-6.60,-8.80,-6.06,-8.96,-6.97,-8.71,-6.78,-8.20,-7.14,-7.60,-6.17,-8.13,-7.02,-7.72,-7.02,-7.02,-7.61,-8.16,-7.63,-8.01,-7.54,-7.73,-6.34,-8.19,-7.25,-7.89,-7.96,-7.25,-6.79,-8.38,-7.35,-7.60,-8.17,-8.06,-7.34,-7.05,-7.56,-5.86,-6.91,-6.70,-7.78,-8.19,-8.43,-7.67,-7.69,-7.27,-9.28,-7.82,-8.22,-6.55,-6.91,-7.42,-8.40,-7.44,-7.46,-5.77,-8.48,-7.21,-8.08,-7.50,-8.23,-8.09,-7.77,-8.13,-8.93,-7.61,-8.77,-7.59,-7.72,-8.35,-6.41,-6.96,-8.03,-6.62,-8.64,-7.42,-6.77,-7.63,-8.87,-8.00,-8.01,-7.60,-6.95,-8.44,-8.19,-7.77,-7.39,-8.18,-7.78,-6.42,-8.22,-6.43,-8.25,-6.22,-8.14,-5.33,-8.47,-6.27,-7.10,-7.21,-7.46,-8.68,-7.23,-8.11,-8.02,-4.91,-6.45,-8.10,-7.29,-7.71,-6.20,-8.08,-5.99,-7.63,-6.75,-7.21,-8.05,-8.90,-5.94,-7.74,-7.50,-6.97,-6.86,-7.48,-6.95,-6.54,-8.91,-6.51,-6.99,-6.64,-7.46,-8.09,-7.04,-7.61,-7.23,-7.74,-7.25,-6.72,-7.70,-7.17,-8.36,-7.37,-7.33,-7.54,-6.44 2024-01-23 13:25:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 13: train = -6.9781(13.38m/1151) | dev = -7.4638(0.84m/173) 2024-01-23 13:25:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 13:27:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -7.07)... 2024-01-23 13:30:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -7.19)... 2024-01-23 13:32:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -7.13)... 2024-01-23 13:34:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -7.02)... 2024-01-23 13:36:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -7.11)... 2024-01-23 13:38:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 13:39:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 13:39:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 14: train = -7.1044(13.38m/1151) | dev = -7.4303(0.84m/173) | no impr, best = -7.4638 2024-01-23 13:39:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 13:41:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -7.27)... 2024-01-23 13:44:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -7.30)... 2024-01-23 13:46:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -7.30)... 2024-01-23 13:48:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -7.37)... 2024-01-23 13:50:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -7.33)... 2024-01-23 13:52:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 13:53:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 13:53:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 15: train = -7.2980(13.25m/1150) | dev = -7.6929(0.85m/173) 2024-01-23 13:53:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 13:56:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -7.48)... 2024-01-23 13:58:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -7.37)... 2024-01-23 14:00:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -7.42)... 2024-01-23 14:02:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -7.51)... 2024-01-23 14:05:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -7.45)... 2024-01-23 14:06:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 14:07:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 14:07:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 16: train = -7.4582(13.29m/1152) | dev = -7.8335(0.83m/173) 2024-01-23 14:07:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 14:10:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -7.58)... 2024-01-23 14:12:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -7.69)... 2024-01-23 14:14:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -7.57)... 2024-01-23 14:16:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -7.52)... 2024-01-23 14:19:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -7.53)... 2024-01-23 14:20:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 14:21:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -5.94,-8.44,-6.85,-9.03,-7.20,-6.84,-8.57,-8.44,-7.38,-8.38,-5.50,-8.41,-8.57,-8.45,-7.83,-5.60,-7.95,-8.19,-9.04,-7.34,-8.05,-6.56,-7.95,-7.41,-7.55,-7.28,-6.76,-8.13,-7.15,-9.04,-6.61,-9.22,-7.54,-8.89,-6.62,-8.51,-6.96,-7.43,-6.06,-8.47,-7.21,-7.84,-7.28,-7.30,-7.53,-8.45,-7.96,-8.09,-7.80,-7.43,-7.09,-8.49,-7.19,-8.55,-8.39,-8.21,-7.26,-8.77,-7.53,-8.08,-8.32,-8.19,-7.52,-7.42,-7.54,-6.11,-7.22,-7.32,-8.21,-8.74,-8.79,-8.14,-7.78,-7.57,-9.68,-8.40,-8.21,-6.61,-7.04,-7.43,-8.44,-8.02,-7.84,-6.40,-8.45,-7.31,-8.25,-7.57,-8.39,-8.25,-7.88,-7.98,-8.92,-7.96,-9.13,-7.65,-7.71,-8.45,-7.37,-7.01,-8.47,-6.79,-8.66,-7.16,-7.01,-7.85,-9.15,-8.08,-8.21,-7.95,-7.49,-8.73,-8.20,-7.59,-7.56,-8.59,-8.19,-6.52,-8.44,-6.00,-8.86,-6.66,-8.47,-5.55,-8.97,-6.93,-7.49,-7.49,-7.64,-9.10,-7.81,-8.68,-8.39,-5.47,-6.82,-8.76,-7.56,-8.11,-6.37,-8.40,-6.03,-7.95,-6.93,-7.39,-8.38,-9.26,-6.49,-8.18,-8.13,-7.61,-7.20,-7.87,-6.97,-7.02,-9.06,-6.61,-7.14,-6.74,-7.92,-8.58,-7.18,-8.01,-7.63,-8.04,-8.07,-6.88,-8.24,-7.37,-8.51,-7.29,-7.63,-7.92,-6.68 2024-01-23 14:21:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 17: train = -7.5420(13.36m/1152) | dev = -7.7393(0.84m/173) | no impr, best = -7.8335 2024-01-23 14:21:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 14:24:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -7.72)... 2024-01-23 14:26:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -7.82)... 2024-01-23 14:28:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -7.64)... 2024-01-23 14:31:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -7.53)... 2024-01-23 14:33:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -7.63)... 2024-01-23 14:35:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 14:36:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -6.24,-8.49,-7.08,-9.46,-7.32,-7.24,-8.46,-8.28,-7.75,-8.50,-5.56,-8.09,-8.77,-8.64,-8.44,-5.80,-7.96,-8.06,-9.08,-7.26,-8.12,-6.89,-8.28,-7.57,-7.79,-7.59,-6.88,-8.40,-6.95,-9.23,-6.11,-9.36,-7.28,-8.84,-6.93,-8.70,-7.48,-7.94,-6.57,-8.61,-7.03,-8.04,-7.47,-7.53,-7.92,-8.37,-8.23,-8.42,-7.76,-8.17,-6.87,-8.72,-7.72,-8.47,-8.47,-8.00,-7.24,-8.88,-8.05,-7.90,-8.67,-8.53,-7.50,-7.80,-8.11,-6.13,-7.34,-6.89,-8.22,-8.72,-8.92,-8.18,-8.24,-7.83,-9.72,-8.49,-8.49,-7.18,-7.56,-7.65,-8.58,-7.83,-8.16,-6.63,-8.79,-7.92,-8.45,-7.87,-8.65,-8.11,-8.29,-8.15,-9.33,-7.62,-9.18,-7.93,-8.07,-8.84,-7.65,-7.21,-8.48,-6.95,-9.01,-8.00,-7.37,-7.95,-9.20,-8.40,-8.63,-7.99,-7.36,-8.96,-8.60,-8.22,-7.77,-8.61,-8.40,-6.93,-8.71,-6.52,-9.08,-7.12,-8.94,-6.01,-9.02,-6.88,-7.76,-7.62,-7.87,-9.41,-7.92,-9.01,-8.35,-5.33,-7.06,-8.79,-7.80,-8.43,-6.73,-8.63,-6.22,-8.02,-6.92,-7.35,-8.59,-9.20,-6.48,-8.11,-7.99,-7.31,-7.18,-8.02,-6.99,-7.20,-9.18,-6.97,-7.32,-6.95,-7.95,-8.67,-7.30,-8.18,-7.70,-8.08,-7.90,-7.13,-8.35,-7.48,-8.68,-7.84,-7.82,-8.15,-7.03 2024-01-23 14:36:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 18: train = -7.6420(13.43m/1152) | dev = -7.9123(0.85m/173) 2024-01-23 14:36:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 14:38:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -7.82)... 2024-01-23 14:40:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -7.84)... 2024-01-23 14:43:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -7.75)... 2024-01-23 14:45:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -7.57)... 2024-01-23 14:47:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -7.78)... 2024-01-23 14:49:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 14:50:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 14:50:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 19: train = -7.7497(13.27m/1151) | dev = -7.9775(0.74m/173) 2024-01-23 14:50:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 14:52:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -7.77)... 2024-01-23 14:54:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -7.87)... 2024-01-23 14:57:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -7.80)... 2024-01-23 14:59:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -7.89)... 2024-01-23 15:01:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -7.93)... 2024-01-23 15:03:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 15:04:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 15:04:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 20: train = -7.8547(13.21m/1150) | dev = -8.0288(0.84m/173) 2024-01-23 15:04:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 15:06:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -7.95)... 2024-01-23 15:09:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.04)... 2024-01-23 15:11:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.03)... 2024-01-23 15:13:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.04)... 2024-01-23 15:15:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -7.84)... 2024-01-23 15:17:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 15:18:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 15:18:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 21: train = -7.9644(13.34m/1150) | dev = -8.2130(0.85m/173) 2024-01-23 15:18:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 15:20:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.09)... 2024-01-23 15:23:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.09)... 2024-01-23 15:25:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.10)... 2024-01-23 15:27:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -7.97)... 2024-01-23 15:30:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -7.97)... 2024-01-23 15:31:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 15:32:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -6.75,-9.05,-7.08,-9.67,-7.86,-7.54,-9.19,-8.55,-7.87,-8.86,-6.19,-8.61,-9.28,-9.07,-8.76,-6.01,-8.59,-8.51,-9.62,-7.64,-8.66,-7.12,-8.55,-7.80,-8.09,-8.09,-6.94,-8.81,-7.73,-9.69,-7.02,-9.74,-7.51,-9.45,-7.07,-8.93,-7.54,-8.32,-6.57,-8.87,-7.70,-8.52,-7.88,-7.78,-8.02,-8.54,-8.57,-8.91,-8.45,-8.21,-7.07,-8.91,-7.97,-8.73,-8.90,-8.49,-7.76,-9.29,-7.88,-8.29,-8.82,-8.99,-8.20,-8.10,-8.30,-6.75,-7.54,-7.31,-8.52,-9.12,-9.28,-8.52,-8.48,-7.64,-10.18,-8.69,-8.75,-7.24,-7.90,-8.13,-9.06,-8.27,-8.51,-6.99,-9.10,-8.49,-9.08,-8.08,-9.13,-8.43,-8.52,-8.84,-9.68,-8.16,-9.38,-8.19,-8.17,-9.27,-7.74,-7.51,-8.84,-7.30,-9.43,-8.12,-7.77,-8.12,-9.41,-8.64,-9.09,-8.31,-7.65,-9.34,-9.07,-8.39,-7.96,-9.01,-8.84,-7.15,-8.98,-7.18,-9.40,-7.15,-9.09,-7.02,-9.36,-7.21,-8.11,-7.94,-8.15,-9.76,-8.32,-9.41,-8.68,-5.93,-7.39,-9.00,-8.15,-8.58,-6.80,-8.79,-6.86,-8.23,-7.63,-7.52,-9.01,-9.37,-6.39,-8.48,-8.36,-7.96,-7.52,-8.14,-7.91,-7.55,-9.74,-7.33,-7.68,-7.47,-8.25,-9.07,-7.75,-8.38,-8.05,-8.46,-7.94,-7.66,-8.22,-7.45,-8.94,-8.01,-8.42,-8.32,-7.21 2024-01-23 15:32:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 22: train = -8.0569(13.41m/1152) | dev = -8.2552(0.83m/173) 2024-01-23 15:32:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 15:35:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.33)... 2024-01-23 15:37:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.22)... 2024-01-23 15:39:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.19)... 2024-01-23 15:41:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.05)... 2024-01-23 15:44:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.01)... 2024-01-23 15:45:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 15:46:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 15:46:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 23: train = -8.1581(13.27m/1151) | dev = -8.3537(0.85m/173) 2024-01-23 15:46:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 15:49:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.28)... 2024-01-23 15:51:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.24)... 2024-01-23 15:53:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.21)... 2024-01-23 15:56:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.18)... 2024-01-23 15:58:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.27)... 2024-01-23 16:00:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 16:00:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -6.56,-9.22,-7.33,-9.77,-7.68,-7.18,-9.27,-8.70,-8.16,-8.82,-6.25,-8.88,-9.44,-9.01,-8.75,-6.37,-8.45,-8.71,-9.72,-8.00,-8.68,-7.09,-8.52,-7.80,-8.18,-8.19,-7.32,-8.84,-7.40,-9.79,-7.47,-9.79,-8.58,-9.60,-7.38,-9.05,-7.89,-8.69,-7.06,-9.27,-7.89,-8.45,-8.02,-7.84,-8.50,-9.02,-8.50,-8.87,-8.36,-8.42,-7.74,-9.18,-8.14,-9.26,-9.00,-8.20,-7.78,-9.47,-8.18,-8.62,-8.99,-8.63,-8.29,-8.07,-8.22,-6.86,-7.84,-7.64,-9.08,-9.15,-9.49,-8.73,-8.74,-8.21,-10.40,-8.97,-8.86,-7.26,-7.97,-8.20,-9.17,-8.53,-8.75,-7.16,-9.40,-8.35,-8.97,-8.30,-9.00,-8.15,-8.64,-9.11,-9.92,-8.27,-9.64,-8.39,-8.32,-9.17,-8.32,-7.40,-9.03,-7.10,-9.50,-7.96,-7.87,-8.43,-9.63,-8.76,-9.18,-8.64,-7.81,-9.39,-9.04,-8.81,-8.15,-9.40,-9.04,-7.55,-9.41,-7.10,-9.38,-7.52,-9.47,-6.76,-9.58,-7.66,-8.16,-7.94,-8.36,-9.89,-8.53,-9.59,-8.90,-6.04,-7.43,-9.38,-8.12,-8.82,-7.08,-9.19,-7.43,-8.46,-7.84,-7.59,-9.13,-9.76,-7.05,-8.69,-8.49,-8.01,-8.02,-8.40,-7.71,-7.35,-9.82,-7.22,-7.66,-7.62,-8.75,-9.26,-8.01,-8.30,-8.27,-8.62,-8.13,-7.59,-8.63,-7.61,-9.21,-8.25,-8.29,-8.49,-7.30 2024-01-23 16:00:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 24: train = -8.2274(13.29m/1151) | dev = -8.4127(0.82m/173) 2024-01-23 16:00:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 16:03:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.32)... 2024-01-23 16:05:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.26)... 2024-01-23 16:07:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.30)... 2024-01-23 16:10:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.26)... 2024-01-23 16:12:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.34)... 2024-01-23 16:14:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 16:15:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 16:15:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 25: train = -8.2912(13.36m/1152) | dev = -8.3514(0.84m/173) | no impr, best = -8.4127 2024-01-23 16:15:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 16:17:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.33)... 2024-01-23 16:19:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.30)... 2024-01-23 16:22:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.33)... 2024-01-23 16:24:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.36)... 2024-01-23 16:26:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.41)... 2024-01-23 16:28:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 16:29:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 16:29:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 26: train = -8.3519(13.35m/1151) | dev = -8.4815(0.83m/173) 2024-01-23 16:29:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 16:31:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.53)... 2024-01-23 16:34:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.40)... 2024-01-23 16:36:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.45)... 2024-01-23 16:38:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.40)... 2024-01-23 16:40:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.43)... 2024-01-23 16:42:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 16:43:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 16:43:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 27: train = -8.4476(13.29m/1150) | dev = -8.4844(0.84m/173) 2024-01-23 16:43:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 16:46:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.74)... 2024-01-23 16:48:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.50)... 2024-01-23 16:50:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.54)... 2024-01-23 16:52:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.45)... 2024-01-23 16:55:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.44)... 2024-01-23 16:56:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 16:57:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -6.81,-9.34,-7.53,-9.87,-7.07,-7.55,-9.13,-8.65,-7.85,-9.21,-6.40,-9.17,-9.34,-8.83,-8.93,-6.39,-8.26,-8.34,-9.81,-8.19,-8.64,-7.76,-8.80,-7.64,-8.23,-7.89,-7.14,-8.85,-7.42,-9.84,-7.14,-9.72,-7.51,-9.66,-6.92,-9.13,-8.02,-8.36,-6.15,-9.28,-7.55,-8.29,-8.09,-8.25,-8.09,-8.66,-8.67,-8.77,-8.28,-8.71,-6.38,-9.25,-8.15,-9.03,-9.06,-8.49,-7.89,-9.50,-8.43,-8.72,-9.34,-8.57,-8.19,-8.25,-8.37,-6.33,-8.04,-7.96,-8.86,-9.19,-9.49,-8.50,-8.60,-7.75,-10.42,-8.89,-8.83,-7.75,-7.30,-8.26,-9.21,-8.35,-8.45,-6.72,-9.25,-8.53,-8.49,-8.70,-9.26,-9.18,-8.73,-8.72,-9.99,-8.55,-9.72,-8.42,-8.33,-9.18,-8.48,-7.56,-8.78,-7.23,-9.62,-8.32,-7.97,-8.57,-9.79,-8.97,-9.27,-8.69,-7.83,-9.50,-8.78,-8.63,-8.34,-9.61,-9.17,-7.61,-9.19,-7.12,-9.37,-6.72,-9.18,-6.52,-9.65,-7.57,-8.42,-8.02,-8.63,-9.77,-8.73,-9.31,-9.07,-6.55,-7.67,-9.50,-8.28,-8.88,-7.05,-9.30,-6.80,-8.59,-8.09,-7.72,-9.20,-10.00,-7.64,-8.63,-8.41,-8.31,-7.96,-8.67,-7.81,-7.40,-10.01,-7.42,-7.72,-7.66,-8.42,-9.08,-7.75,-7.85,-8.30,-8.49,-8.71,-7.27,-8.84,-8.07,-9.17,-8.42,-8.39,-8.62,-7.56 2024-01-23 16:57:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 28: train = -8.5151(13.31m/1151) | dev = -8.4157(0.84m/173) | no impr, best = -8.4844 2024-01-23 16:57:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 17:00:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.47)... 2024-01-23 17:02:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.68)... 2024-01-23 17:04:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.63)... 2024-01-23 17:06:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.51)... 2024-01-23 17:09:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.56)... 2024-01-23 17:10:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 17:11:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -6.89,-9.16,-7.52,-9.68,-7.71,-7.58,-9.32,-8.73,-7.98,-8.76,-6.13,-8.95,-9.46,-9.29,-9.13,-6.43,-9.11,-8.96,-9.89,-8.25,-8.73,-7.21,-8.88,-7.84,-8.39,-8.27,-7.46,-8.78,-7.59,-9.83,-7.63,-9.83,-8.39,-10.04,-7.08,-9.24,-7.99,-8.71,-6.70,-8.92,-8.07,-8.71,-7.95,-8.06,-8.48,-9.13,-8.98,-9.03,-8.70,-8.55,-7.48,-9.44,-8.14,-9.36,-9.22,-8.68,-7.75,-9.59,-8.42,-8.74,-9.35,-8.69,-8.46,-8.13,-8.46,-7.22,-7.76,-7.76,-9.17,-9.39,-9.55,-8.73,-8.77,-8.38,-10.49,-9.27,-8.96,-7.60,-8.07,-8.34,-9.08,-8.74,-8.96,-7.65,-9.53,-8.32,-9.03,-8.73,-9.43,-8.84,-8.95,-9.04,-10.16,-8.34,-9.63,-8.37,-8.45,-9.38,-8.20,-8.25,-9.16,-7.34,-9.61,-8.37,-8.21,-8.51,-9.67,-8.76,-9.41,-8.95,-8.19,-9.45,-9.21,-9.03,-8.23,-9.36,-9.34,-7.40,-9.52,-7.84,-9.64,-7.95,-9.24,-6.82,-9.65,-7.73,-8.55,-8.34,-8.32,-10.14,-8.53,-9.50,-8.89,-6.92,-7.41,-9.54,-8.18,-8.90,-7.31,-9.26,-7.07,-8.62,-8.13,-7.99,-9.29,-9.88,-7.30,-8.80,-8.63,-8.02,-8.08,-8.68,-7.93,-7.62,-10.04,-7.51,-8.43,-8.13,-8.37,-9.45,-8.28,-8.76,-8.10,-8.71,-8.20,-8.29,-8.92,-8.17,-9.33,-8.41,-8.34,-8.70,-7.63 2024-01-23 17:11:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 29: train = -8.5745(13.30m/1150) | dev = -8.5706(0.86m/173) 2024-01-23 17:11:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 17:14:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.65)... 2024-01-23 17:16:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.74)... 2024-01-23 17:18:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.66)... 2024-01-23 17:21:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.60)... 2024-01-23 17:23:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.55)... 2024-01-23 17:25:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 17:25:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 17:25:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 30: train = -8.6273(13.29m/1152) | dev = -8.6582(0.85m/173) 2024-01-23 17:25:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 17:28:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.69)... 2024-01-23 17:30:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.70)... 2024-01-23 17:32:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.68)... 2024-01-23 17:35:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.71)... 2024-01-23 17:37:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.59)... 2024-01-23 17:39:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 17:40:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 17:40:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 31: train = -8.6671(13.29m/1151) | dev = -8.6654(0.83m/173) 2024-01-23 17:40:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 17:42:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.86)... 2024-01-23 17:44:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.83)... 2024-01-23 17:47:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.74)... 2024-01-23 17:49:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.71)... 2024-01-23 17:51:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.64)... 2024-01-23 17:53:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 17:54:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.13,-9.32,-7.55,-10.23,-8.00,-7.63,-9.19,-9.21,-7.99,-8.94,-6.29,-9.18,-9.57,-9.22,-8.66,-6.38,-9.05,-9.03,-9.86,-8.18,-8.93,-7.79,-8.92,-7.81,-8.42,-8.37,-7.58,-9.16,-7.91,-10.10,-7.70,-10.20,-8.03,-9.83,-7.33,-9.19,-8.18,-8.32,-7.74,-9.86,-8.23,-8.94,-8.30,-8.08,-8.51,-9.04,-9.00,-9.04,-8.92,-8.65,-7.48,-9.57,-8.25,-9.14,-9.17,-8.68,-8.02,-9.55,-8.24,-8.79,-9.22,-8.99,-8.71,-7.98,-8.40,-7.18,-7.74,-8.07,-9.21,-9.27,-9.75,-8.88,-8.82,-8.49,-10.66,-9.07,-8.95,-7.61,-8.05,-8.51,-9.37,-8.59,-8.94,-7.67,-9.44,-8.85,-9.56,-8.43,-9.39,-9.23,-9.02,-9.04,-10.25,-8.66,-9.65,-8.56,-8.62,-9.50,-8.50,-7.81,-9.17,-7.49,-9.80,-8.52,-8.15,-8.43,-9.78,-9.11,-9.42,-8.99,-8.01,-9.55,-9.41,-9.04,-8.33,-9.66,-8.95,-7.29,-9.35,-7.39,-9.72,-7.57,-9.49,-6.99,-9.77,-7.75,-8.22,-8.44,-8.80,-10.17,-8.48,-9.82,-8.97,-6.99,-8.01,-9.56,-8.48,-8.70,-7.16,-9.26,-7.33,-8.54,-7.75,-7.85,-9.23,-9.95,-7.55,-8.99,-8.42,-8.37,-8.14,-8.64,-8.23,-8.00,-10.08,-7.61,-8.34,-7.99,-8.74,-9.49,-8.06,-8.78,-8.31,-8.76,-8.60,-7.53,-8.92,-8.67,-9.41,-8.45,-8.66,-8.82,-7.59 2024-01-23 17:54:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 32: train = -8.7449(13.37m/1151) | dev = -8.6488(0.86m/173) | no impr, best = -8.6654 2024-01-23 17:54:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 17:56:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.73)... 2024-01-23 17:59:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.80)... 2024-01-23 18:01:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.73)... 2024-01-23 18:03:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.82)... 2024-01-23 18:05:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.77)... 2024-01-23 18:07:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 18:08:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.71,-9.64,-7.62,-10.20,-8.07,-7.79,-9.55,-8.93,-8.33,-9.58,-6.46,-9.29,-9.52,-9.51,-8.86,-7.05,-8.69,-8.65,-10.04,-8.56,-9.11,-7.73,-8.87,-8.06,-8.57,-8.79,-7.49,-9.18,-8.17,-10.10,-7.71,-10.24,-8.70,-10.00,-7.55,-9.31,-8.41,-8.80,-7.06,-9.57,-8.44,-8.97,-8.43,-8.18,-8.69,-9.50,-8.93,-9.42,-8.85,-8.83,-7.88,-9.45,-8.56,-9.30,-9.47,-8.73,-8.35,-9.80,-8.64,-8.84,-9.47,-8.86,-8.68,-8.61,-8.58,-7.08,-8.01,-8.02,-8.92,-9.56,-9.87,-8.90,-8.70,-8.59,-10.71,-9.28,-9.27,-7.81,-8.08,-8.72,-9.46,-8.46,-8.95,-7.71,-9.94,-9.45,-9.49,-8.63,-9.50,-9.31,-9.11,-9.22,-10.29,-8.90,-9.87,-8.66,-8.87,-9.56,-8.50,-8.16,-9.30,-7.82,-9.77,-8.54,-8.15,-8.65,-9.89,-9.13,-9.62,-8.95,-8.29,-9.73,-9.51,-9.21,-8.45,-9.72,-9.08,-7.56,-9.37,-7.42,-9.75,-8.24,-9.87,-6.80,-9.66,-8.02,-8.42,-8.54,-9.06,-10.41,-8.43,-9.82,-9.21,-6.98,-8.03,-9.70,-8.53,-9.05,-7.47,-9.43,-7.23,-8.74,-8.19,-8.21,-9.35,-9.95,-8.15,-8.99,-8.87,-8.37,-8.26,-9.00,-8.05,-7.90,-10.13,-7.69,-8.39,-7.85,-9.06,-9.55,-8.41,-9.14,-8.54,-9.19,-8.75,-7.57,-8.90,-8.51,-9.42,-8.82,-8.90,-8.82,-7.81 2024-01-23 18:08:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 33: train = -8.7640(13.26m/1151) | dev = -8.7909(0.85m/173) 2024-01-23 18:08:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 18:11:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -8.90)... 2024-01-23 18:13:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.93)... 2024-01-23 18:15:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.78)... 2024-01-23 18:17:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.72)... 2024-01-23 18:20:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.82)... 2024-01-23 18:21:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 18:22:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.68,-9.63,-8.09,-10.16,-7.88,-7.79,-9.63,-9.11,-8.66,-9.47,-6.41,-9.40,-9.79,-9.53,-9.06,-6.78,-9.07,-9.05,-10.20,-8.40,-9.16,-7.95,-9.03,-8.15,-8.65,-8.69,-7.46,-9.19,-7.90,-10.21,-7.71,-10.42,-9.04,-10.16,-7.64,-9.36,-8.50,-8.86,-6.80,-9.34,-8.41,-9.36,-8.70,-8.21,-8.77,-9.45,-9.26,-9.22,-9.01,-8.86,-7.79,-9.43,-8.89,-9.29,-9.41,-8.74,-8.06,-9.91,-8.72,-8.84,-9.60,-8.95,-8.73,-8.58,-8.91,-6.86,-8.18,-8.11,-9.02,-9.54,-9.99,-8.86,-9.03,-8.88,-10.79,-9.27,-9.22,-7.92,-8.37,-8.42,-9.60,-8.38,-9.06,-7.60,-9.81,-9.18,-9.53,-8.66,-9.55,-9.17,-9.06,-9.32,-10.14,-8.70,-9.96,-8.86,-8.83,-9.60,-8.29,-7.92,-9.36,-7.48,-9.84,-8.76,-8.17,-8.67,-9.94,-9.10,-9.65,-9.00,-8.36,-9.68,-9.55,-8.88,-8.46,-9.62,-9.20,-7.68,-9.46,-7.86,-9.86,-7.69,-9.64,-6.55,-9.57,-8.12,-8.91,-8.47,-8.79,-10.27,-9.01,-9.95,-9.28,-6.72,-8.01,-9.82,-8.33,-9.00,-7.57,-9.51,-7.72,-8.86,-8.06,-8.22,-9.50,-10.07,-7.38,-9.05,-8.78,-8.54,-8.46,-8.75,-8.34,-8.03,-10.04,-7.51,-8.24,-8.15,-8.84,-9.67,-8.28,-9.53,-8.56,-8.95,-8.74,-7.97,-9.16,-8.51,-9.58,-8.71,-8.91,-8.90,-7.74 2024-01-23 18:22:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 34: train = -8.8285(13.44m/1150) | dev = -8.8231(0.86m/173) 2024-01-23 18:22:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 18:25:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.00)... 2024-01-23 18:27:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.03)... 2024-01-23 18:29:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.98)... 2024-01-23 18:32:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.74)... 2024-01-23 18:34:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.80)... 2024-01-23 18:36:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 18:36:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 18:36:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 35: train = -8.8974(13.29m/1151) | dev = -8.7208(0.74m/173) | no impr, best = -8.8231 2024-01-23 18:36:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 18:39:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.04)... 2024-01-23 18:41:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -8.97)... 2024-01-23 18:43:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -8.86)... 2024-01-23 18:46:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.87)... 2024-01-23 18:48:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.91)... 2024-01-23 18:50:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 18:50:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.53,-9.69,-7.86,-10.13,-8.03,-7.98,-9.50,-9.12,-8.35,-9.45,-6.76,-9.36,-9.71,-9.33,-9.13,-6.80,-9.03,-9.45,-10.07,-8.45,-9.11,-7.45,-8.95,-8.04,-8.76,-8.91,-7.62,-9.33,-8.20,-10.26,-8.07,-10.27,-8.36,-10.33,-7.38,-9.40,-8.45,-8.91,-6.74,-9.96,-8.30,-9.33,-8.57,-8.19,-8.72,-9.41,-9.40,-9.28,-9.25,-8.97,-7.60,-9.60,-8.25,-9.43,-9.48,-8.74,-8.27,-9.80,-8.46,-8.94,-9.41,-9.18,-8.64,-8.62,-8.94,-7.32,-8.00,-8.10,-9.22,-9.63,-10.04,-8.96,-9.14,-8.74,-10.76,-9.26,-9.35,-7.99,-8.16,-8.78,-9.67,-8.54,-9.27,-8.07,-9.98,-9.00,-9.57,-8.90,-9.68,-9.32,-9.00,-9.37,-10.28,-8.68,-9.97,-8.55,-8.96,-9.81,-8.49,-8.07,-9.42,-7.74,-9.92,-8.81,-8.37,-8.74,-10.03,-9.32,-9.71,-9.13,-8.59,-9.79,-9.48,-9.38,-8.72,-9.48,-9.36,-7.85,-9.54,-7.71,-9.97,-8.16,-10.00,-7.29,-9.73,-8.03,-8.69,-8.26,-9.14,-10.49,-8.74,-9.97,-9.33,-7.01,-8.19,-9.76,-8.67,-9.16,-7.25,-9.52,-7.66,-8.86,-8.22,-8.05,-9.52,-10.11,-7.91,-9.18,-8.77,-8.56,-8.33,-9.02,-8.30,-7.67,-10.23,-8.03,-8.34,-8.31,-8.81,-9.71,-8.32,-9.20,-8.79,-9.07,-8.60,-7.94,-8.98,-8.61,-9.45,-8.88,-8.76,-8.95,-7.81 2024-01-23 18:50:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 36: train = -8.9190(13.30m/1152) | dev = -8.8727(0.83m/173) 2024-01-23 18:50:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 18:53:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.07)... 2024-01-23 18:55:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.00)... 2024-01-23 18:58:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.08)... 2024-01-23 19:00:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -8.99)... 2024-01-23 19:02:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.83)... 2024-01-23 19:04:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 19:05:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.31,-9.60,-8.00,-10.21,-8.26,-7.75,-9.40,-9.26,-8.42,-9.24,-6.42,-9.34,-9.75,-9.54,-9.25,-7.00,-9.05,-9.03,-10.02,-8.59,-9.29,-7.91,-9.06,-8.17,-8.53,-8.76,-7.88,-9.17,-8.19,-10.10,-7.85,-10.25,-8.46,-10.18,-7.60,-9.42,-8.23,-8.87,-6.73,-9.61,-8.58,-9.63,-8.51,-8.35,-8.99,-9.38,-8.76,-9.45,-9.14,-8.71,-7.54,-9.94,-8.38,-9.41,-9.54,-9.11,-8.26,-9.80,-8.43,-9.03,-9.76,-9.14,-8.64,-8.57,-8.85,-7.48,-8.29,-8.41,-9.23,-9.66,-10.05,-8.93,-8.88,-8.57,-10.89,-9.55,-9.32,-7.99,-8.22,-8.25,-9.59,-8.93,-9.57,-7.80,-10.06,-8.60,-9.54,-8.70,-9.64,-9.06,-9.15,-9.24,-10.27,-8.90,-10.00,-8.68,-8.70,-9.82,-8.72,-8.27,-9.38,-7.42,-9.77,-8.59,-8.44,-8.86,-9.98,-9.05,-9.76,-9.18,-8.49,-9.97,-9.52,-9.39,-8.79,-9.46,-9.43,-7.76,-9.72,-7.65,-9.99,-8.44,-9.67,-6.97,-9.94,-8.41,-8.75,-8.44,-8.83,-10.49,-8.85,-9.95,-9.36,-6.86,-7.88,-9.71,-8.66,-9.22,-7.48,-9.20,-7.53,-8.89,-8.21,-8.22,-9.62,-10.16,-7.85,-9.08,-8.74,-8.46,-8.30,-8.98,-8.01,-8.11,-10.39,-7.76,-8.37,-8.00,-9.01,-9.77,-8.58,-9.21,-8.31,-9.27,-8.50,-7.78,-9.28,-8.38,-9.51,-8.79,-8.91,-8.97,-7.88 2024-01-23 19:05:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 37: train = -8.9900(13.35m/1152) | dev = -8.8733(0.84m/173) 2024-01-23 19:05:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 19:07:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.12)... 2024-01-23 19:09:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.06)... 2024-01-23 19:12:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.13)... 2024-01-23 19:14:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.05)... 2024-01-23 19:16:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -8.95)... 2024-01-23 19:18:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 19:19:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.86,-9.33,-7.98,-10.23,-8.11,-7.47,-9.57,-8.79,-8.87,-9.31,-6.52,-9.26,-9.78,-9.58,-9.33,-6.53,-9.16,-9.14,-10.14,-8.46,-9.10,-7.27,-8.82,-7.83,-8.55,-8.41,-7.93,-9.33,-8.03,-9.81,-7.96,-10.31,-7.76,-10.20,-7.14,-9.47,-8.44,-9.17,-6.61,-9.62,-8.23,-8.71,-8.37,-8.32,-8.85,-9.33,-8.91,-9.25,-8.88,-8.82,-7.96,-9.75,-8.41,-9.33,-9.43,-9.07,-8.31,-9.69,-8.31,-9.04,-9.47,-9.13,-8.71,-8.48,-8.71,-7.40,-8.03,-7.93,-9.21,-9.74,-9.86,-9.06,-9.34,-8.12,-10.71,-9.51,-9.47,-8.21,-8.30,-8.73,-9.51,-8.67,-8.95,-7.68,-9.79,-9.15,-9.55,-8.80,-9.76,-8.88,-9.35,-8.89,-10.01,-8.43,-9.92,-8.93,-8.85,-9.68,-8.22,-8.59,-9.33,-7.69,-9.81,-8.67,-8.59,-8.80,-10.08,-9.22,-9.58,-8.98,-8.42,-9.96,-9.27,-9.53,-8.85,-10.01,-9.29,-7.60,-9.45,-7.78,-9.83,-8.95,-9.93,-6.64,-9.92,-8.13,-8.72,-8.36,-9.01,-9.90,-9.02,-9.47,-9.19,-6.96,-7.80,-9.81,-8.67,-9.15,-7.29,-9.27,-7.58,-8.91,-8.30,-8.25,-9.59,-10.43,-8.27,-9.25,-8.91,-8.32,-8.15,-8.95,-8.28,-8.07,-10.36,-7.56,-8.51,-8.52,-8.58,-9.65,-7.61,-9.31,-8.61,-9.02,-8.55,-8.27,-9.12,-7.95,-9.54,-8.63,-8.83,-8.87,-7.69 2024-01-23 19:19:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 38: train = -9.0556(13.24m/1151) | dev = -8.8278(0.86m/173) | no impr, best = -8.8733 2024-01-23 19:19:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 19:21:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.17)... 2024-01-23 19:24:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.16)... 2024-01-23 19:26:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.06)... 2024-01-23 19:28:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.10)... 2024-01-23 19:30:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.05)... 2024-01-23 19:32:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 19:33:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.42,-9.70,-7.65,-10.48,-8.20,-8.14,-9.74,-9.27,-8.85,-9.55,-6.39,-9.54,-9.80,-9.74,-9.17,-6.93,-9.10,-9.35,-10.26,-8.50,-9.40,-7.55,-9.11,-8.18,-8.81,-8.96,-8.03,-9.48,-8.26,-10.31,-7.36,-10.30,-8.71,-10.41,-7.62,-9.58,-8.63,-8.89,-7.47,-9.76,-7.91,-9.14,-8.59,-8.20,-8.99,-9.54,-9.32,-9.63,-8.73,-9.15,-7.86,-9.87,-8.55,-9.48,-9.34,-9.16,-8.29,-9.91,-8.65,-8.96,-9.85,-9.25,-8.87,-8.44,-8.93,-7.43,-8.00,-8.55,-9.63,-9.81,-10.13,-9.10,-9.16,-8.85,-11.03,-9.52,-9.29,-8.44,-8.41,-8.79,-9.73,-8.81,-9.15,-7.92,-9.55,-9.58,-9.96,-9.04,-9.76,-9.13,-9.06,-9.12,-10.32,-8.85,-10.11,-8.72,-8.71,-9.78,-8.64,-8.21,-9.61,-7.75,-10.00,-8.83,-8.45,-8.84,-10.15,-9.22,-9.62,-9.20,-8.52,-9.97,-9.98,-9.92,-8.79,-9.60,-9.47,-7.44,-9.62,-7.39,-10.07,-8.16,-9.63,-7.91,-9.84,-8.43,-9.12,-8.30,-9.06,-10.67,-8.94,-9.95,-9.40,-6.80,-8.08,-9.92,-8.80,-9.21,-7.55,-9.67,-7.22,-9.00,-8.51,-8.25,-9.46,-10.32,-8.23,-9.20,-8.62,-8.41,-8.58,-9.16,-8.42,-8.09,-10.37,-7.71,-8.44,-7.97,-9.17,-9.72,-8.66,-8.84,-8.71,-9.21,-8.84,-7.83,-9.38,-8.56,-9.56,-8.70,-9.25,-9.12,-8.22 2024-01-23 19:33:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 39: train = -9.0973(13.40m/1152) | dev = -8.9659(0.85m/173) 2024-01-23 19:33:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 19:36:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.31)... 2024-01-23 19:38:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.18)... 2024-01-23 19:40:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.17)... 2024-01-23 19:42:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.23)... 2024-01-23 19:45:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.02)... 2024-01-23 19:46:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 19:47:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 19:47:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 40: train = -9.1538(13.35m/1151) | dev = -8.9376(0.84m/173) | no impr, best = -8.9659 2024-01-23 19:47:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 19:50:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.29)... 2024-01-23 19:52:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.21)... 2024-01-23 19:54:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.17)... 2024-01-23 19:57:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.19)... 2024-01-23 19:59:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.16)... 2024-01-23 20:01:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 20:01:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.32,-9.50,-8.16,-10.23,-7.93,-7.93,-9.80,-9.16,-8.92,-9.31,-6.59,-9.56,-9.92,-9.59,-9.26,-7.08,-9.33,-9.41,-10.25,-9.02,-9.12,-7.56,-8.92,-8.26,-8.57,-8.60,-7.88,-9.24,-8.36,-9.94,-7.99,-10.54,-8.66,-10.35,-7.84,-9.54,-8.72,-9.07,-7.04,-9.80,-8.36,-9.28,-8.65,-8.44,-9.08,-9.58,-9.06,-9.50,-9.00,-8.61,-7.76,-9.98,-8.62,-9.70,-9.47,-9.19,-8.13,-9.92,-8.79,-9.22,-9.72,-9.20,-8.59,-8.70,-8.82,-7.66,-8.20,-8.43,-9.36,-9.83,-10.07,-9.07,-9.25,-8.94,-10.87,-9.42,-9.39,-8.08,-8.44,-8.54,-9.66,-8.84,-9.27,-7.89,-10.08,-9.32,-9.69,-9.06,-9.90,-9.48,-9.31,-9.41,-10.36,-8.95,-9.95,-9.16,-8.78,-9.95,-8.68,-8.61,-9.55,-7.99,-10.21,-8.88,-8.47,-8.93,-10.13,-9.31,-9.90,-9.16,-8.64,-10.16,-9.99,-9.74,-8.53,-9.63,-9.42,-7.77,-9.83,-7.93,-10.08,-8.22,-9.89,-7.27,-9.65,-8.46,-8.98,-8.51,-9.30,-10.49,-9.04,-10.00,-9.33,-7.00,-8.01,-9.93,-8.57,-9.27,-7.60,-9.52,-7.43,-8.89,-8.39,-8.39,-9.53,-10.21,-7.93,-9.20,-9.03,-8.45,-8.41,-9.30,-8.42,-8.27,-10.48,-8.04,-8.51,-8.15,-9.09,-9.86,-8.70,-9.38,-8.88,-9.40,-8.69,-8.18,-9.36,-8.85,-9.77,-8.74,-8.89,-8.88,-7.79 2024-01-23 20:01:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 41: train = -9.1852(13.45m/1152) | dev = -8.9959(0.83m/173) 2024-01-23 20:01:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 20:04:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.38)... 2024-01-23 20:06:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.25)... 2024-01-23 20:09:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.17)... 2024-01-23 20:11:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.08)... 2024-01-23 20:13:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.22)... 2024-01-23 20:15:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 20:16:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.36,-9.91,-8.13,-10.51,-8.55,-7.94,-9.69,-9.20,-8.75,-9.56,-6.43,-9.62,-9.96,-9.60,-9.37,-7.41,-9.11,-9.63,-10.39,-9.26,-8.89,-8.17,-8.93,-8.02,-8.87,-8.73,-8.06,-9.67,-8.26,-10.28,-8.17,-10.48,-8.65,-10.28,-7.76,-9.67,-8.30,-8.97,-6.30,-9.51,-8.49,-9.15,-8.41,-8.38,-9.00,-9.37,-9.18,-9.34,-9.07,-9.10,-7.75,-9.91,-8.73,-9.49,-9.66,-9.22,-7.94,-9.76,-8.61,-9.37,-9.42,-9.25,-8.98,-8.33,-8.83,-7.50,-8.02,-7.89,-9.56,-9.71,-9.96,-9.13,-9.36,-8.97,-10.93,-9.48,-9.20,-8.38,-8.50,-8.47,-9.45,-8.88,-9.30,-7.65,-10.07,-9.26,-9.65,-8.86,-9.60,-9.44,-9.39,-9.67,-10.49,-9.11,-10.15,-9.06,-8.86,-9.80,-8.72,-8.33,-9.60,-7.82,-10.05,-8.78,-8.65,-8.86,-10.14,-9.42,-10.04,-9.03,-8.54,-9.98,-9.83,-9.55,-8.68,-10.13,-9.60,-8.11,-9.74,-7.53,-10.05,-8.05,-9.47,-7.25,-9.92,-8.51,-8.94,-8.53,-8.87,-10.60,-9.21,-9.89,-9.52,-7.28,-8.39,-9.89,-8.85,-9.32,-7.63,-9.43,-7.54,-9.06,-8.55,-8.24,-9.72,-10.38,-7.73,-9.26,-8.96,-8.70,-8.32,-9.04,-8.39,-8.09,-10.45,-7.84,-8.86,-8.29,-8.78,-9.87,-8.55,-9.75,-8.91,-9.38,-9.09,-7.78,-8.93,-8.49,-9.57,-8.78,-8.96,-9.01,-8.00 2024-01-23 20:16:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 42: train = -9.2146(13.37m/1151) | dev = -8.9990(0.85m/173) 2024-01-23 20:16:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 20:18:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.20)... 2024-01-23 20:21:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.31)... 2024-01-23 20:23:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.25)... 2024-01-23 20:25:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.28)... 2024-01-23 20:27:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.15)... 2024-01-23 20:29:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 20:30:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.99,-9.80,-7.91,-10.57,-8.28,-7.97,-9.80,-9.17,-8.76,-9.32,-6.54,-9.57,-9.83,-9.83,-9.39,-6.99,-9.45,-9.78,-10.45,-8.56,-9.33,-7.88,-9.21,-8.34,-8.85,-8.84,-8.18,-9.66,-8.71,-10.47,-7.47,-10.30,-9.07,-10.34,-7.72,-9.59,-8.67,-9.13,-7.45,-9.55,-8.19,-9.64,-8.59,-8.42,-9.04,-9.43,-9.41,-9.58,-9.06,-9.27,-8.49,-9.92,-8.87,-9.44,-9.71,-9.27,-8.25,-10.05,-8.92,-9.13,-9.60,-9.31,-9.09,-8.72,-9.05,-7.46,-8.18,-8.36,-9.59,-9.87,-10.19,-9.17,-9.29,-9.22,-11.10,-9.66,-9.46,-8.33,-8.50,-8.64,-9.82,-9.09,-9.55,-8.38,-10.13,-9.37,-9.78,-9.08,-9.82,-9.25,-9.29,-9.49,-10.64,-8.88,-10.18,-9.16,-8.59,-10.07,-8.42,-8.15,-9.77,-7.84,-10.14,-9.16,-8.58,-9.00,-10.08,-9.37,-9.91,-9.29,-8.68,-10.17,-9.80,-9.35,-8.92,-9.97,-9.77,-8.03,-9.76,-7.89,-10.18,-8.72,-9.79,-7.36,-9.80,-8.38,-9.01,-8.48,-9.00,-10.60,-9.09,-10.13,-9.50,-7.22,-8.37,-10.00,-8.64,-9.40,-7.55,-9.66,-7.99,-9.05,-8.60,-8.60,-9.60,-10.55,-7.91,-9.15,-9.07,-8.86,-8.58,-9.35,-8.64,-8.32,-10.41,-8.05,-8.47,-8.02,-8.95,-9.97,-8.59,-9.73,-9.13,-9.50,-9.11,-8.26,-9.34,-8.70,-9.75,-8.75,-8.89,-9.14,-8.11 2024-01-23 20:30:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 43: train = -9.2423(13.37m/1150) | dev = -9.0917(0.83m/173) 2024-01-23 20:30:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 20:32:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.49)... 2024-01-23 20:35:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.26)... 2024-01-23 20:37:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.27)... 2024-01-23 20:39:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.28)... 2024-01-23 20:42:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.27)... 2024-01-23 20:43:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 20:44:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.59,-9.78,-7.90,-10.36,-8.02,-7.61,-9.68,-9.26,-8.62,-9.64,-6.34,-9.63,-9.85,-9.64,-9.51,-7.01,-9.40,-9.32,-10.27,-8.45,-9.31,-7.67,-9.15,-8.38,-8.81,-8.95,-7.83,-9.27,-8.20,-10.17,-7.87,-10.59,-9.06,-10.39,-7.59,-9.32,-8.59,-9.18,-7.27,-9.80,-8.42,-9.12,-8.16,-8.34,-8.85,-9.74,-9.06,-9.61,-8.93,-8.59,-8.68,-10.01,-8.58,-9.84,-9.61,-9.02,-8.27,-9.93,-8.66,-9.06,-9.45,-9.12,-8.80,-8.77,-9.09,-7.76,-8.50,-8.36,-9.44,-9.87,-10.10,-9.00,-8.95,-9.11,-11.11,-9.30,-9.29,-7.86,-8.56,-8.68,-9.94,-8.67,-9.29,-7.96,-9.85,-9.26,-9.52,-8.92,-10.12,-9.04,-9.33,-9.47,-10.49,-8.84,-10.14,-9.10,-8.77,-9.82,-8.76,-8.69,-9.68,-8.13,-10.12,-8.87,-8.69,-8.95,-10.09,-9.46,-9.83,-9.32,-8.75,-10.16,-9.47,-9.72,-8.51,-9.61,-9.24,-7.94,-9.44,-8.05,-10.14,-8.25,-10.04,-7.43,-9.73,-7.78,-8.93,-8.43,-8.51,-10.40,-9.24,-10.22,-9.35,-6.61,-8.00,-9.98,-8.59,-9.21,-7.42,-9.65,-7.91,-9.05,-8.39,-8.34,-9.66,-10.23,-8.42,-9.30,-8.78,-8.50,-8.39,-9.16,-8.55,-8.27,-10.35,-7.93,-8.37,-8.60,-9.34,-9.61,-8.42,-9.67,-8.67,-9.17,-9.02,-8.21,-9.30,-8.57,-9.66,-8.76,-9.02,-9.07,-7.95 2024-01-23 20:44:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 44: train = -9.3211(13.32m/1152) | dev = -9.0029(0.86m/173) | no impr, best = -9.0917 2024-01-23 20:44:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 20:47:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.39)... 2024-01-23 20:49:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.27)... 2024-01-23 20:51:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.31)... 2024-01-23 20:53:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.29)... 2024-01-23 20:56:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.36)... 2024-01-23 20:57:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 20:58:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 20:58:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 45: train = -9.3013(13.37m/1151) | dev = -9.0458(0.85m/173) | no impr, best = -9.0917 2024-01-23 20:58:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 21:01:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.36)... 2024-01-23 21:03:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.35)... 2024-01-23 21:05:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.42)... 2024-01-23 21:08:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.35)... 2024-01-23 21:10:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.42)... 2024-01-23 21:11:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 21:12:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 21:12:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 46: train = -9.3776(13.16m/1150) | dev = -9.1572(0.78m/173) 2024-01-23 21:12:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 21:15:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.56)... 2024-01-23 21:17:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.52)... 2024-01-23 21:19:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.36)... 2024-01-23 21:22:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.40)... 2024-01-23 21:24:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.45)... 2024-01-23 21:26:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 21:26:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 21:26:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 47: train = -9.4332(13.26m/1151) | dev = -9.0862(0.70m/173) | no impr, best = -9.1572 2024-01-23 21:26:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 21:29:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.56)... 2024-01-23 21:31:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.52)... 2024-01-23 21:33:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.47)... 2024-01-23 21:35:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.40)... 2024-01-23 21:38:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.38)... 2024-01-23 21:39:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 21:40:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.85,-9.61,-8.20,-10.68,-8.52,-8.06,-9.88,-9.50,-9.01,-9.48,-6.89,-9.92,-9.89,-9.81,-9.55,-7.16,-9.42,-9.93,-10.34,-9.27,-9.53,-7.45,-9.30,-8.40,-8.93,-9.20,-7.95,-9.49,-8.32,-10.53,-7.45,-10.50,-9.07,-10.30,-7.80,-9.72,-8.42,-9.00,-7.52,-9.89,-8.55,-9.26,-8.78,-8.66,-9.18,-9.72,-9.43,-9.24,-9.16,-9.30,-8.27,-9.89,-8.67,-9.52,-9.59,-9.17,-8.39,-10.00,-8.59,-9.06,-9.91,-9.56,-9.32,-8.84,-9.01,-7.77,-8.32,-8.55,-9.76,-10.01,-10.14,-9.28,-9.50,-8.90,-11.02,-9.70,-9.61,-8.43,-8.62,-8.71,-9.66,-8.75,-9.50,-8.21,-10.00,-9.76,-9.79,-8.90,-10.22,-9.50,-9.30,-9.94,-10.49,-9.07,-10.23,-9.17,-8.94,-9.92,-8.72,-8.39,-9.52,-8.09,-10.26,-8.99,-8.42,-9.12,-10.34,-9.55,-9.72,-9.39,-8.72,-10.19,-9.98,-9.53,-9.01,-10.21,-9.48,-8.22,-9.78,-7.80,-10.08,-7.69,-9.72,-7.61,-9.98,-8.37,-9.14,-8.98,-8.65,-10.77,-9.00,-10.17,-9.61,-7.59,-8.41,-10.11,-8.84,-9.31,-7.67,-9.84,-7.77,-9.15,-8.47,-8.09,-9.72,-10.58,-8.26,-9.40,-9.21,-8.92,-8.32,-9.22,-8.73,-8.17,-10.54,-8.14,-8.43,-7.93,-9.14,-9.79,-8.55,-9.47,-8.86,-9.27,-8.81,-8.30,-9.33,-8.84,-9.69,-8.70,-9.12,-9.20,-7.97 2024-01-23 21:40:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 48: train = -9.4553(13.18m/1152) | dev = -9.1303(0.72m/173) | no impr, best = -9.1572 2024-01-23 21:40:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 21:43:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.56)... 2024-01-23 21:45:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.50)... 2024-01-23 21:47:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.43)... 2024-01-23 21:49:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.47)... 2024-01-23 21:52:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.50)... 2024-01-23 21:53:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 21:54:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.94,-9.91,-8.46,-10.52,-8.57,-8.18,-9.69,-9.34,-8.59,-9.52,-6.64,-9.85,-10.02,-9.93,-9.57,-7.04,-9.73,-9.80,-10.56,-8.62,-9.54,-8.03,-9.27,-8.50,-8.85,-9.06,-8.00,-9.25,-8.41,-10.39,-8.25,-10.40,-8.84,-10.40,-7.69,-9.77,-8.58,-9.14,-8.03,-9.97,-8.53,-9.34,-8.57,-8.57,-9.03,-9.39,-9.42,-9.66,-9.35,-9.03,-8.25,-9.99,-9.07,-9.92,-9.70,-9.20,-8.50,-10.12,-8.71,-9.02,-9.81,-9.49,-9.29,-8.81,-9.31,-8.01,-8.27,-8.42,-9.68,-10.09,-10.17,-9.06,-9.25,-9.16,-11.14,-9.47,-9.54,-8.16,-7.99,-8.76,-9.93,-8.73,-9.19,-8.14,-10.16,-9.62,-9.91,-8.96,-10.05,-9.40,-9.27,-9.62,-10.56,-9.08,-10.21,-9.31,-8.97,-10.22,-8.78,-8.63,-9.73,-8.00,-10.19,-9.04,-8.52,-8.97,-10.17,-9.50,-10.04,-9.44,-8.90,-10.17,-9.90,-9.65,-8.80,-9.93,-9.38,-8.16,-9.88,-8.18,-10.27,-8.19,-10.14,-7.16,-10.06,-8.43,-9.30,-8.95,-9.10,-10.56,-9.29,-10.23,-9.49,-7.37,-8.49,-10.12,-8.79,-9.39,-7.75,-9.54,-7.99,-9.13,-8.70,-8.43,-9.64,-10.48,-8.16,-9.18,-8.95,-8.60,-8.56,-9.12,-8.79,-8.45,-10.38,-8.00,-8.61,-8.38,-9.16,-9.99,-8.78,-10.14,-9.05,-9.37,-8.90,-8.87,-9.60,-8.72,-9.86,-9.06,-9.15,-9.31,-8.04 2024-01-23 21:54:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 49: train = -9.4758(13.16m/1151) | dev = -9.1652(0.69m/173) 2024-01-23 21:54:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 21:56:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.49)... 2024-01-23 21:59:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.58)... 2024-01-23 22:01:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.45)... 2024-01-23 22:03:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.50)... 2024-01-23 22:05:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.51)... 2024-01-23 22:07:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 22:08:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 22:08:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 50: train = -9.4932(13.08m/1151) | dev = -9.2005(0.69m/173) 2024-01-23 22:08:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 22:10:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.73)... 2024-01-23 22:12:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.61)... 2024-01-23 22:15:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.61)... 2024-01-23 22:17:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.51)... 2024-01-23 22:19:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.42)... 2024-01-23 22:21:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 22:22:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-23 22:22:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 51: train = -9.5566(13.15m/1152) | dev = -9.2312(0.71m/173) 2024-01-23 22:22:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 22:24:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.50)... 2024-01-23 22:26:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.58)... 2024-01-23 22:29:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.49)... 2024-01-23 22:31:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.52)... 2024-01-23 22:33:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.56)... 2024-01-23 22:35:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 22:36:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.87,-10.08,-8.38,-10.57,-8.53,-7.95,-9.82,-9.38,-8.69,-9.64,-6.41,-9.96,-10.15,-9.94,-9.42,-6.91,-9.20,-9.59,-10.48,-8.86,-9.45,-8.00,-9.17,-8.58,-9.12,-9.27,-7.87,-9.47,-8.51,-10.55,-8.06,-10.57,-8.84,-10.53,-7.59,-9.72,-8.73,-8.80,-7.62,-10.01,-8.53,-9.47,-8.59,-8.27,-8.68,-9.76,-9.08,-9.58,-9.26,-9.10,-8.25,-9.98,-8.64,-9.70,-9.66,-9.35,-8.46,-10.16,-8.82,-9.31,-9.75,-9.50,-9.06,-8.82,-9.17,-7.47,-8.31,-8.44,-9.23,-10.03,-10.26,-9.22,-9.28,-8.96,-11.00,-9.66,-9.40,-8.01,-8.06,-8.94,-9.96,-9.08,-9.32,-8.50,-10.27,-9.14,-9.91,-8.96,-9.94,-9.89,-9.29,-9.76,-10.69,-9.07,-10.23,-8.87,-8.92,-9.96,-8.95,-8.74,-9.79,-8.27,-10.20,-9.14,-8.96,-9.17,-10.32,-9.55,-9.69,-9.58,-8.75,-10.21,-10.04,-9.69,-9.08,-9.93,-9.72,-8.00,-9.75,-8.17,-10.16,-8.63,-10.39,-8.02,-10.07,-8.28,-9.21,-9.03,-8.90,-10.77,-8.87,-10.18,-9.63,-6.90,-8.23,-10.26,-8.78,-9.32,-7.58,-9.67,-8.08,-9.05,-8.49,-8.37,-9.72,-10.47,-7.73,-9.45,-9.09,-8.87,-8.13,-9.24,-8.62,-7.91,-10.61,-8.23,-8.94,-8.59,-9.53,-9.92,-8.82,-9.95,-8.87,-9.63,-8.88,-8.58,-9.24,-8.75,-9.71,-8.93,-9.19,-9.14,-7.81 2024-01-23 22:36:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 52: train = -9.5225(13.18m/1152) | dev = -9.1581(0.70m/173) | no impr, best = -9.2312 2024-01-23 22:36:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 22:38:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.59)... 2024-01-23 22:40:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.70)... 2024-01-23 22:42:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.64)... 2024-01-23 22:45:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.64)... 2024-01-23 22:47:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.54)... 2024-01-23 22:49:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 22:49:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.44,-9.94,-8.35,-10.64,-8.40,-7.92,-9.90,-9.59,-8.95,-9.84,-6.69,-9.79,-9.94,-9.95,-9.41,-7.08,-9.97,-9.79,-10.49,-8.80,-9.45,-8.17,-9.33,-8.44,-9.03,-8.77,-8.28,-9.90,-8.61,-10.63,-7.72,-10.37,-9.07,-10.53,-7.64,-9.72,-8.72,-8.87,-8.27,-10.08,-8.41,-9.56,-8.88,-8.33,-9.34,-9.69,-9.46,-9.86,-9.41,-9.19,-8.04,-10.29,-8.71,-9.90,-9.67,-9.38,-8.43,-10.15,-8.98,-9.21,-9.82,-9.55,-9.14,-8.64,-9.26,-7.60,-8.62,-8.59,-9.70,-9.93,-10.38,-9.43,-9.45,-9.08,-11.14,-9.46,-9.47,-8.30,-8.39,-8.54,-10.05,-8.93,-9.62,-8.48,-10.19,-9.14,-10.11,-9.06,-10.09,-9.47,-9.11,-9.63,-10.55,-8.94,-10.40,-9.13,-8.84,-9.84,-9.08,-8.43,-9.90,-8.20,-10.36,-8.99,-8.70,-9.24,-10.25,-9.62,-9.85,-9.38,-9.04,-10.44,-9.62,-9.84,-9.10,-10.24,-10.08,-8.56,-9.92,-8.26,-10.30,-8.73,-10.47,-7.44,-10.05,-8.42,-9.30,-8.82,-8.70,-10.90,-9.13,-10.16,-9.68,-7.04,-8.19,-10.17,-8.97,-9.67,-7.52,-9.90,-8.01,-9.17,-8.66,-8.34,-9.80,-10.70,-8.38,-9.36,-8.91,-8.70,-8.43,-9.27,-8.79,-8.33,-10.70,-8.15,-8.83,-8.70,-9.58,-9.95,-8.91,-9.81,-9.29,-9.70,-9.10,-8.53,-9.35,-8.86,-9.88,-8.82,-9.30,-9.21,-8.19 2024-01-23 22:49:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 53: train = -9.5994(13.13m/1152) | dev = -9.2244(0.72m/173) | no impr, best = -9.2312 2024-01-23 22:49:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 22:52:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.73)... 2024-01-23 22:54:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.68)... 2024-01-23 22:56:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.66)... 2024-01-23 22:59:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.58)... 2024-01-23 23:01:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.57)... 2024-01-23 23:03:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 23:03:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.05,-10.11,-8.77,-10.69,-8.20,-7.95,-10.00,-9.26,-9.44,-9.90,-6.65,-9.80,-10.03,-10.11,-9.79,-7.19,-9.97,-9.96,-10.56,-9.15,-9.65,-7.93,-9.42,-8.48,-9.02,-9.07,-8.61,-9.42,-8.76,-10.64,-8.31,-10.75,-9.19,-10.53,-7.75,-9.86,-8.91,-9.13,-7.80,-10.29,-8.59,-9.92,-9.05,-8.52,-9.28,-9.81,-9.38,-9.96,-9.32,-9.63,-8.44,-10.18,-9.01,-10.07,-9.94,-9.51,-8.67,-10.23,-9.04,-9.50,-10.00,-9.66,-9.17,-8.79,-9.10,-7.94,-8.49,-8.34,-9.67,-10.07,-10.29,-9.44,-9.38,-8.87,-11.17,-9.92,-9.66,-8.02,-8.71,-9.07,-10.01,-9.25,-9.73,-8.49,-10.24,-9.61,-10.28,-9.34,-10.11,-9.62,-9.19,-9.92,-10.82,-9.14,-10.16,-9.57,-8.97,-10.16,-8.98,-8.70,-10.03,-8.12,-10.55,-9.09,-8.91,-9.33,-10.40,-9.83,-9.94,-9.45,-9.14,-10.43,-9.89,-10.04,-8.67,-10.09,-9.90,-8.30,-10.12,-8.37,-10.45,-8.66,-10.24,-7.69,-10.11,-8.75,-9.21,-9.16,-9.54,-10.97,-9.33,-10.23,-9.64,-7.05,-8.52,-10.29,-8.88,-9.66,-7.61,-10.00,-8.41,-9.27,-9.02,-8.76,-9.67,-10.80,-8.04,-9.50,-9.48,-8.99,-8.70,-9.33,-8.74,-8.71,-10.76,-8.34,-9.14,-8.63,-9.27,-10.11,-8.74,-10.03,-9.03,-9.84,-9.04,-8.66,-9.44,-9.04,-10.02,-9.22,-9.29,-9.39,-8.05 2024-01-23 23:03:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 54: train = -9.6497(13.17m/1151) | dev = -9.3363(0.72m/173) 2024-01-23 23:03:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 23:06:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.73)... 2024-01-23 23:08:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.66)... 2024-01-23 23:10:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.67)... 2024-01-23 23:13:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.62)... 2024-01-23 23:15:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.61)... 2024-01-23 23:17:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 23:17:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.17,-10.09,-9.01,-10.75,-8.87,-7.87,-9.97,-9.70,-8.99,-9.97,-6.66,-10.13,-10.20,-10.04,-9.54,-7.39,-9.60,-9.82,-10.72,-9.25,-9.34,-8.09,-9.22,-8.56,-8.94,-8.99,-8.38,-9.81,-8.54,-10.50,-8.27,-10.61,-8.63,-10.53,-7.82,-9.84,-8.75,-8.96,-7.49,-10.11,-8.60,-9.24,-9.04,-8.97,-9.20,-9.76,-9.49,-9.74,-9.40,-9.31,-8.45,-10.25,-9.01,-9.70,-9.82,-9.27,-8.46,-10.18,-8.84,-9.55,-9.95,-9.33,-9.45,-9.12,-8.92,-7.81,-8.69,-8.62,-9.72,-10.05,-10.31,-9.31,-9.52,-8.89,-11.30,-9.84,-9.71,-8.58,-8.32,-8.84,-10.29,-9.02,-9.63,-8.14,-10.54,-9.12,-9.79,-9.16,-10.10,-9.85,-9.66,-9.87,-10.88,-9.25,-10.37,-9.28,-9.13,-10.08,-9.10,-8.76,-9.85,-8.54,-10.33,-9.35,-8.56,-9.16,-10.34,-9.82,-10.03,-9.44,-8.92,-10.26,-9.78,-9.87,-9.23,-10.24,-9.77,-8.11,-10.16,-8.35,-10.30,-8.30,-10.03,-7.48,-10.20,-8.48,-9.20,-9.10,-9.19,-10.95,-9.29,-10.41,-9.71,-7.36,-8.33,-10.24,-9.00,-9.55,-7.55,-9.99,-8.02,-9.28,-8.87,-8.80,-9.61,-10.84,-8.45,-9.63,-9.18,-8.99,-8.70,-9.27,-8.60,-8.53,-10.69,-8.21,-9.19,-8.94,-9.51,-10.07,-8.61,-9.49,-9.31,-9.69,-9.15,-8.07,-9.28,-8.84,-9.87,-9.10,-9.59,-9.19,-8.13 2024-01-23 23:17:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 55: train = -9.6548(13.22m/1151) | dev = -9.3020(0.70m/173) | no impr, best = -9.3363 2024-01-23 23:17:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 23:20:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.82)... 2024-01-23 23:22:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.66)... 2024-01-23 23:24:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.74)... 2024-01-23 23:26:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.62)... 2024-01-23 23:29:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.53)... 2024-01-23 23:30:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 23:31:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.04,-9.88,-8.49,-10.70,-8.48,-8.07,-9.75,-9.27,-8.69,-9.89,-6.62,-10.05,-10.22,-10.16,-9.61,-7.08,-9.65,-9.61,-10.75,-8.74,-9.59,-7.81,-9.43,-8.54,-9.00,-9.20,-8.28,-9.85,-8.45,-10.65,-7.86,-10.57,-8.84,-10.51,-7.58,-9.80,-8.40,-9.10,-7.36,-10.05,-8.69,-9.60,-8.92,-8.47,-9.17,-9.54,-9.72,-9.82,-9.37,-9.43,-7.88,-10.47,-8.82,-9.63,-9.76,-9.30,-8.75,-9.99,-9.00,-9.56,-10.16,-9.47,-8.89,-9.05,-9.19,-7.66,-8.72,-8.59,-9.74,-10.10,-10.39,-9.13,-9.39,-9.48,-11.15,-9.88,-9.56,-8.63,-8.48,-8.63,-10.15,-9.12,-9.70,-8.58,-10.35,-8.85,-10.01,-9.03,-10.01,-9.72,-9.47,-9.89,-10.76,-8.99,-10.33,-9.32,-9.13,-9.83,-8.89,-8.82,-9.88,-8.42,-10.54,-9.31,-8.47,-9.14,-10.28,-9.69,-9.96,-9.43,-9.00,-10.25,-10.13,-9.85,-8.90,-10.49,-9.50,-7.82,-9.67,-8.04,-10.23,-8.09,-10.15,-7.40,-10.09,-8.25,-9.15,-9.06,-9.30,-11.02,-9.14,-10.38,-9.76,-7.20,-8.50,-10.16,-9.17,-9.60,-7.60,-9.96,-7.79,-9.18,-8.75,-8.59,-9.75,-10.77,-7.74,-9.57,-9.42,-9.02,-8.57,-9.41,-8.70,-8.33,-10.67,-8.12,-9.01,-8.26,-9.50,-10.08,-8.88,-9.29,-9.07,-9.44,-9.07,-8.12,-9.33,-8.77,-9.75,-9.09,-9.49,-9.22,-8.09 2024-01-23 23:31:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 56: train = -9.6631(13.26m/1152) | dev = -9.2460(0.71m/173) | no impr, best = -9.3363 2024-01-23 23:31:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 23:34:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.73)... 2024-01-23 23:36:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -9.79)... 2024-01-23 23:38:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -9.77)... 2024-01-23 23:40:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -9.72)... 2024-01-23 23:43:12 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -9.63)... 2024-01-23 23:44:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 23:45:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -7.79,-9.98,-8.34,-10.42,-8.54,-7.95,-9.95,-9.47,-8.64,-9.66,-7.01,-9.70,-10.03,-9.78,-9.70,-7.33,-9.75,-9.48,-10.43,-9.00,-9.68,-7.54,-9.25,-8.51,-8.82,-9.06,-8.03,-9.19,-8.52,-10.51,-7.85,-10.64,-8.99,-10.72,-7.93,-9.74,-8.85,-9.16,-7.36,-10.21,-8.75,-9.76,-8.55,-8.68,-9.15,-9.58,-9.54,-10.01,-9.31,-9.10,-8.39,-10.07,-8.91,-9.69,-9.81,-9.30,-8.76,-9.99,-8.91,-9.65,-9.90,-9.65,-9.24,-8.61,-9.08,-7.87,-8.51,-8.38,-9.76,-10.13,-10.37,-9.37,-9.45,-9.12,-11.19,-9.64,-9.73,-8.42,-8.41,-8.73,-10.00,-9.10,-9.58,-8.31,-10.33,-9.39,-9.96,-9.06,-10.12,-9.27,-9.35,-10.06,-10.65,-8.78,-10.18,-9.17,-9.07,-9.96,-8.31,-9.02,-9.41,-8.30,-10.31,-9.32,-8.65,-9.01,-10.16,-9.75,-9.92,-9.63,-8.86,-10.33,-9.71,-10.03,-9.01,-10.06,-9.61,-8.08,-9.86,-8.64,-10.25,-8.89,-10.19,-7.35,-9.99,-8.17,-9.14,-8.75,-9.12,-10.79,-9.12,-10.10,-9.66,-7.19,-8.44,-10.25,-8.97,-9.49,-7.86,-9.77,-8.44,-9.16,-8.95,-8.49,-9.62,-10.54,-8.19,-9.45,-9.04,-8.95,-8.52,-9.43,-8.69,-8.54,-10.67,-8.38,-8.83,-8.39,-9.12,-9.92,-8.89,-9.72,-8.91,-9.58,-9.15,-8.67,-9.47,-8.77,-9.79,-8.76,-9.34,-9.21,-7.89 2024-01-23 23:45:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.000e-03) - Epoch 57: train = -9.7162(13.21m/1151) | dev = -9.2268(0.70m/173) | no impr, best = -9.3363 2024-01-23 23:45:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-23 23:48:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -9.98)... 2024-01-23 23:50:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.11)... 2024-01-23 23:52:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.18)... 2024-01-23 23:55:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.13)... 2024-01-23 23:57:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.09)... 2024-01-23 23:59:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-23 23:59:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.50,-10.31,-8.69,-10.86,-8.61,-8.44,-10.21,-9.93,-9.44,-10.16,-7.02,-10.20,-10.36,-10.17,-9.83,-7.56,-10.11,-9.93,-11.02,-9.42,-9.93,-8.34,-9.61,-8.75,-9.28,-9.60,-9.20,-10.06,-8.65,-10.83,-8.51,-10.87,-9.18,-11.09,-7.87,-10.04,-9.10,-9.35,-8.43,-10.47,-9.00,-10.14,-9.27,-9.08,-9.66,-10.04,-9.75,-10.21,-9.61,-9.60,-8.63,-10.56,-9.09,-10.39,-9.97,-9.58,-8.73,-10.30,-9.34,-9.71,-10.17,-9.83,-9.58,-9.34,-9.76,-8.06,-8.79,-8.80,-10.02,-10.42,-10.64,-9.86,-9.82,-9.79,-11.45,-10.33,-9.97,-8.61,-9.11,-9.11,-10.45,-9.19,-10.05,-8.72,-10.64,-9.94,-10.29,-9.73,-10.60,-10.18,-9.55,-10.25,-10.98,-9.18,-10.61,-9.58,-9.39,-10.25,-9.17,-9.34,-10.23,-8.76,-10.61,-9.54,-8.87,-9.50,-10.59,-10.08,-10.32,-9.77,-9.50,-10.49,-10.16,-10.49,-9.42,-10.62,-9.88,-8.58,-10.62,-8.98,-10.64,-8.50,-10.37,-8.24,-10.49,-8.94,-9.58,-9.34,-9.81,-11.26,-9.56,-10.94,-9.92,-7.67,-8.77,-10.53,-9.28,-9.77,-8.09,-10.20,-8.38,-9.50,-9.08,-8.77,-9.89,-10.93,-8.46,-9.82,-9.32,-9.04,-9.05,-9.49,-9.15,-8.89,-10.86,-8.63,-9.31,-9.17,-9.57,-10.19,-9.10,-10.28,-9.44,-9.76,-9.38,-8.34,-9.63,-9.22,-10.13,-9.28,-9.66,-9.60,-8.40 2024-01-23 23:59:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 58: train = -10.0962(13.40m/1151) | dev = -9.6114(0.70m/173) 2024-01-23 23:59:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 00:02:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.22)... 2024-01-24 00:04:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.26)... 2024-01-24 00:06:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.24)... 2024-01-24 00:08:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.15)... 2024-01-24 00:11:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.22)... 2024-01-24 00:12:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 00:13:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.15,-9.99,-8.73,-10.92,-9.02,-8.17,-10.19,-9.90,-9.39,-10.08,-7.00,-10.16,-10.45,-10.40,-10.00,-7.91,-10.18,-10.13,-11.07,-9.58,-9.85,-7.94,-9.56,-8.70,-9.18,-9.33,-8.57,-9.98,-8.68,-10.77,-8.76,-10.96,-9.36,-10.82,-7.85,-10.03,-9.09,-9.51,-8.36,-10.74,-9.24,-9.93,-9.14,-8.82,-9.83,-10.07,-9.90,-10.07,-9.38,-9.63,-8.56,-10.86,-9.06,-10.15,-9.97,-9.67,-8.83,-10.42,-9.27,-9.73,-10.06,-9.91,-9.89,-9.08,-9.52,-8.23,-8.41,-8.71,-10.03,-10.42,-10.59,-9.79,-9.76,-9.60,-11.56,-10.18,-9.94,-8.46,-8.74,-9.00,-10.30,-9.31,-9.81,-8.87,-10.39,-9.72,-9.84,-9.58,-10.55,-9.70,-9.91,-10.28,-11.15,-9.16,-10.63,-9.79,-9.41,-10.44,-9.19,-8.98,-10.08,-8.17,-10.70,-9.32,-9.13,-9.60,-10.50,-9.86,-10.35,-9.85,-9.29,-10.76,-10.41,-10.58,-8.92,-10.28,-9.82,-8.55,-10.48,-8.88,-10.61,-9.32,-10.66,-8.08,-10.50,-8.88,-9.44,-9.07,-9.93,-11.03,-9.36,-10.78,-10.00,-7.27,-8.55,-10.53,-9.18,-9.85,-7.83,-10.36,-8.41,-9.48,-9.20,-9.09,-10.01,-10.92,-8.56,-9.75,-9.36,-9.24,-9.32,-9.56,-8.92,-8.58,-10.91,-8.47,-9.30,-8.76,-9.80,-10.27,-9.31,-10.47,-9.36,-9.95,-9.42,-8.50,-9.94,-8.71,-10.11,-9.50,-9.50,-9.62,-8.38 2024-01-24 00:13:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 59: train = -10.2284(13.20m/1151) | dev = -9.5855(0.69m/173) | no impr, best = -9.6114 2024-01-24 00:13:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 00:16:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.27)... 2024-01-24 00:18:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.27)... 2024-01-24 00:20:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.33)... 2024-01-24 00:22:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.27)... 2024-01-24 00:25:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.23)... 2024-01-24 00:26:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 00:27:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 00:27:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 60: train = -10.2866(13.25m/1152) | dev = -9.6399(0.72m/173) 2024-01-24 00:27:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 00:30:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.41)... 2024-01-24 00:32:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.33)... 2024-01-24 00:34:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.34)... 2024-01-24 00:36:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.33)... 2024-01-24 00:39:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.33)... 2024-01-24 00:40:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 00:41:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 00:41:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 61: train = -10.3409(13.23m/1151) | dev = -9.6597(0.73m/173) 2024-01-24 00:41:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 00:44:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.42)... 2024-01-24 00:46:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.35)... 2024-01-24 00:48:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.32)... 2024-01-24 00:50:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.38)... 2024-01-24 00:53:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.37)... 2024-01-24 00:54:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 00:55:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 00:55:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 62: train = -10.3524(13.30m/1151) | dev = -9.6815(0.72m/173) 2024-01-24 00:55:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 00:58:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.45)... 2024-01-24 01:00:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.43)... 2024-01-24 01:02:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.40)... 2024-01-24 01:04:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.33)... 2024-01-24 01:07:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.40)... 2024-01-24 01:08:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 01:09:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.75,-10.35,-9.01,-10.95,-9.01,-8.22,-10.34,-9.97,-9.60,-10.32,-6.87,-10.19,-10.49,-10.42,-9.90,-8.04,-10.02,-10.12,-11.16,-9.91,-9.94,-8.29,-9.66,-8.88,-9.32,-9.38,-8.67,-10.17,-9.01,-10.95,-8.75,-11.09,-9.23,-11.00,-7.72,-10.05,-9.29,-9.24,-8.37,-10.31,-9.25,-10.05,-9.30,-9.18,-9.65,-10.11,-9.68,-10.31,-9.53,-9.61,-8.64,-10.54,-9.13,-10.31,-10.23,-9.79,-8.93,-10.36,-9.35,-9.61,-10.24,-9.90,-9.66,-9.13,-9.44,-8.12,-8.84,-8.87,-9.99,-10.43,-10.69,-9.85,-9.76,-9.41,-11.52,-10.15,-9.97,-8.76,-8.89,-9.28,-10.48,-9.48,-9.95,-9.12,-10.85,-9.87,-10.31,-9.53,-10.33,-10.16,-10.00,-10.20,-11.12,-9.23,-10.69,-9.72,-9.42,-10.23,-9.57,-8.86,-10.32,-8.82,-10.81,-9.60,-8.86,-9.49,-10.66,-10.17,-10.47,-9.71,-9.52,-10.66,-10.65,-10.56,-9.62,-10.41,-10.08,-8.43,-10.56,-8.89,-10.66,-9.10,-10.40,-8.00,-10.59,-8.75,-9.73,-9.08,-9.73,-11.45,-9.77,-10.98,-9.98,-8.08,-8.87,-10.57,-9.26,-9.88,-7.76,-10.25,-8.74,-9.61,-9.33,-9.17,-10.20,-11.07,-9.08,-9.86,-9.51,-9.25,-8.97,-9.76,-8.88,-8.59,-11.01,-8.70,-9.44,-9.10,-10.09,-10.36,-9.13,-10.56,-9.57,-9.94,-9.50,-8.43,-9.81,-9.32,-10.22,-9.52,-10.02,-9.65,-8.39 2024-01-24 01:09:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 63: train = -10.4064(13.15m/1150) | dev = -9.6794(0.71m/173) | no impr, best = -9.6815 2024-01-24 01:09:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 01:11:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.39)... 2024-01-24 01:14:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.42)... 2024-01-24 01:16:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.43)... 2024-01-24 01:18:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.38)... 2024-01-24 01:20:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.40)... 2024-01-24 01:22:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 01:23:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.36,-10.36,-8.94,-11.18,-9.25,-8.34,-10.33,-9.58,-9.44,-10.27,-6.93,-10.21,-10.47,-10.32,-10.09,-7.87,-10.11,-10.11,-11.17,-9.00,-9.80,-7.99,-9.66,-8.97,-9.42,-9.22,-8.96,-10.02,-8.94,-10.91,-8.40,-10.95,-9.43,-10.93,-7.73,-10.14,-9.29,-9.18,-8.15,-10.77,-9.05,-10.30,-9.16,-9.08,-9.75,-10.20,-9.87,-10.54,-9.42,-9.59,-8.98,-10.69,-9.24,-10.33,-10.23,-9.76,-9.02,-10.45,-9.25,-10.00,-10.02,-9.90,-9.70,-9.04,-9.54,-8.27,-8.84,-8.90,-10.29,-10.51,-10.71,-9.93,-9.75,-9.81,-11.45,-10.34,-10.03,-8.55,-8.86,-9.30,-10.23,-9.39,-10.12,-9.03,-10.54,-10.09,-10.22,-9.98,-10.45,-9.52,-9.89,-10.21,-11.33,-9.46,-10.61,-9.96,-9.27,-10.50,-9.16,-9.08,-10.11,-8.71,-10.87,-9.50,-9.23,-9.56,-10.68,-10.21,-10.39,-9.94,-9.39,-10.72,-10.60,-10.71,-9.50,-10.22,-10.04,-8.72,-10.30,-8.46,-10.64,-9.49,-10.51,-8.36,-10.55,-9.19,-9.54,-9.18,-9.84,-11.51,-9.58,-10.66,-10.03,-7.40,-8.93,-10.64,-9.34,-9.98,-8.22,-10.41,-8.79,-9.58,-9.27,-9.08,-10.26,-11.02,-9.00,-9.83,-9.46,-9.27,-9.14,-9.58,-8.92,-8.47,-10.98,-8.77,-9.37,-8.86,-9.92,-10.35,-9.18,-10.81,-9.62,-10.01,-9.38,-8.15,-9.73,-8.91,-10.38,-9.65,-9.93,-9.67,-8.56 2024-01-24 01:23:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 64: train = -10.4140(13.21m/1151) | dev = -9.6800(0.71m/173) | no impr, best = -9.6815 2024-01-24 01:23:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 01:25:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.44)... 2024-01-24 01:28:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.47)... 2024-01-24 01:30:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.51)... 2024-01-24 01:32:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.50)... 2024-01-24 01:34:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.42)... 2024-01-24 01:36:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 01:37:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 01:37:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=5.000e-04) - Epoch 65: train = -10.4645(13.22m/1152) | dev = -9.6648(0.70m/173) | no impr, best = -9.6815 2024-01-24 01:37:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 01:39:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.54)... 2024-01-24 01:42:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.58)... 2024-01-24 01:44:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.63)... 2024-01-24 01:46:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.66)... 2024-01-24 01:48:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.69)... 2024-01-24 01:50:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 01:51:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 01:51:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 66: train = -10.6254(13.21m/1151) | dev = -9.8203(0.71m/173) 2024-01-24 01:51:15 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 01:53:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.70)... 2024-01-24 01:56:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.67)... 2024-01-24 01:58:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.66)... 2024-01-24 02:00:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.75)... 2024-01-24 02:02:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.66)... 2024-01-24 02:04:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 02:05:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 02:05:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 67: train = -10.6917(13.25m/1152) | dev = -9.8345(0.70m/173) 2024-01-24 02:05:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 02:07:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.75)... 2024-01-24 02:09:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.69)... 2024-01-24 02:12:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.72)... 2024-01-24 02:14:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.71)... 2024-01-24 02:16:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.72)... 2024-01-24 02:18:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 02:19:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.62,-10.53,-9.15,-11.19,-9.11,-8.42,-10.52,-10.20,-9.77,-10.51,-7.15,-10.39,-10.67,-10.64,-10.02,-8.16,-9.79,-10.37,-11.29,-9.62,-10.01,-8.53,-9.81,-9.15,-9.47,-9.67,-8.85,-10.29,-9.02,-11.07,-8.63,-11.20,-9.43,-11.27,-7.99,-10.30,-9.29,-9.51,-8.35,-11.01,-9.34,-10.35,-9.44,-9.04,-9.94,-10.47,-10.11,-10.58,-9.45,-9.86,-8.88,-10.93,-9.38,-10.51,-10.48,-9.93,-9.00,-10.67,-9.62,-9.98,-10.60,-10.14,-9.99,-9.41,-9.61,-8.50,-9.24,-9.02,-10.34,-10.62,-10.89,-10.00,-9.90,-10.01,-11.74,-10.38,-10.14,-8.92,-8.90,-9.32,-10.53,-9.70,-10.04,-8.99,-10.80,-10.20,-10.54,-10.02,-10.62,-10.32,-10.10,-10.49,-11.45,-9.51,-10.84,-10.02,-9.39,-10.49,-9.65,-9.38,-10.38,-9.17,-10.94,-9.82,-9.08,-9.81,-10.85,-10.28,-10.56,-9.97,-9.75,-10.90,-10.88,-10.83,-9.83,-10.65,-10.30,-8.81,-10.72,-9.17,-10.77,-9.13,-10.60,-8.33,-10.70,-9.51,-9.85,-9.31,-9.77,-11.60,-9.75,-11.09,-10.17,-8.25,-9.20,-10.78,-9.49,-10.15,-7.96,-10.26,-8.83,-9.65,-9.38,-9.17,-10.24,-11.24,-8.80,-9.95,-9.49,-9.23,-9.21,-9.91,-9.12,-8.65,-11.16,-8.64,-9.77,-9.29,-9.99,-10.46,-9.39,-10.91,-9.50,-10.11,-9.77,-8.70,-10.05,-9.37,-10.43,-9.85,-9.78,-9.75,-8.40 2024-01-24 02:19:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 68: train = -10.7248(13.24m/1150) | dev = -9.8568(0.71m/173) 2024-01-24 02:19:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 02:21:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.78)... 2024-01-24 02:23:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.79)... 2024-01-24 02:26:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.83)... 2024-01-24 02:28:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.76)... 2024-01-24 02:30:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.71)... 2024-01-24 02:32:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 02:33:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.67,-10.54,-8.81,-11.11,-9.38,-8.45,-10.52,-10.15,-9.68,-10.40,-7.14,-10.43,-10.63,-10.65,-10.10,-7.97,-10.19,-10.45,-11.35,-9.60,-9.89,-8.41,-9.80,-9.43,-9.46,-9.77,-8.84,-10.16,-8.92,-11.09,-8.75,-11.09,-9.75,-11.04,-7.82,-10.27,-9.35,-9.56,-8.08,-11.05,-9.44,-10.23,-9.44,-9.05,-10.13,-10.48,-10.06,-10.60,-9.43,-9.97,-8.85,-10.93,-9.22,-10.58,-10.37,-9.83,-9.09,-10.61,-9.58,-9.84,-10.38,-10.08,-9.94,-9.36,-9.95,-8.48,-9.00,-9.10,-10.27,-10.63,-10.95,-10.03,-9.95,-10.09,-11.80,-10.44,-10.23,-8.95,-9.06,-9.28,-10.49,-9.52,-10.33,-9.06,-10.74,-10.09,-10.46,-10.02,-10.65,-10.20,-10.13,-10.42,-11.43,-9.59,-10.85,-9.97,-9.58,-10.52,-9.53,-9.36,-10.27,-9.14,-10.94,-9.77,-9.28,-9.79,-10.78,-10.29,-10.53,-9.99,-9.77,-10.89,-10.89,-10.69,-9.62,-10.85,-10.37,-8.99,-10.68,-9.03,-10.82,-9.32,-10.66,-8.31,-10.78,-9.37,-9.65,-9.04,-10.14,-11.57,-9.81,-11.14,-10.21,-8.16,-9.13,-10.74,-9.55,-10.14,-8.02,-10.45,-8.87,-9.70,-9.36,-9.07,-10.33,-11.23,-9.03,-10.07,-9.47,-9.31,-9.52,-9.92,-9.19,-8.71,-11.12,-8.96,-9.75,-9.06,-10.17,-10.48,-9.60,-10.89,-9.70,-10.10,-9.97,-8.72,-9.79,-9.55,-10.38,-9.76,-9.95,-9.88,-8.48 2024-01-24 02:33:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 69: train = -10.7693(13.23m/1151) | dev = -9.8672(0.72m/173) 2024-01-24 02:33:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 02:35:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.83)... 2024-01-24 02:37:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.74)... 2024-01-24 02:40:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.78)... 2024-01-24 02:42:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.79)... 2024-01-24 02:44:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.77)... 2024-01-24 02:46:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 02:47:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 02:47:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 70: train = -10.7818(13.25m/1151) | dev = -9.8797(0.70m/173) 2024-01-24 02:47:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 02:49:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.83)... 2024-01-24 02:51:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.77)... 2024-01-24 02:54:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.79)... 2024-01-24 02:56:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.82)... 2024-01-24 02:58:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.81)... 2024-01-24 03:00:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 03:01:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 03:01:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 71: train = -10.8070(13.21m/1151) | dev = -9.8730(0.69m/173) | no impr, best = -9.8797 2024-01-24 03:01:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 03:03:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.82)... 2024-01-24 03:05:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.87)... 2024-01-24 03:07:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.77)... 2024-01-24 03:10:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.79)... 2024-01-24 03:12:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.88)... 2024-01-24 03:14:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 03:14:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 03:14:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 72: train = -10.8329(13.01m/1151) | dev = -9.8676(0.68m/173) | no impr, best = -9.8797 2024-01-24 03:14:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 03:17:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.85)... 2024-01-24 03:19:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.93)... 2024-01-24 03:21:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.83)... 2024-01-24 03:23:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.85)... 2024-01-24 03:26:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.86)... 2024-01-24 03:27:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 03:28:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.64,-10.58,-9.14,-11.22,-9.33,-8.62,-10.48,-10.23,-9.86,-10.44,-6.99,-10.50,-10.70,-10.57,-10.03,-7.99,-10.23,-10.35,-11.45,-9.84,-10.04,-8.63,-9.82,-9.29,-9.52,-9.80,-8.97,-10.39,-9.09,-11.09,-8.82,-11.28,-9.85,-11.12,-7.65,-10.36,-9.35,-9.48,-8.79,-11.11,-9.60,-10.35,-9.60,-9.19,-9.92,-10.24,-9.75,-10.42,-9.46,-9.84,-8.71,-10.94,-9.30,-10.51,-10.32,-10.00,-9.18,-10.66,-9.53,-9.85,-10.39,-10.07,-10.04,-9.44,-9.97,-8.58,-9.24,-9.26,-10.33,-10.52,-10.97,-10.11,-9.93,-10.20,-11.80,-10.41,-10.26,-8.92,-9.02,-9.47,-10.60,-9.58,-10.30,-9.25,-10.87,-9.74,-10.65,-9.88,-10.77,-10.39,-9.89,-10.68,-11.49,-9.78,-10.90,-10.14,-9.49,-10.61,-9.64,-9.42,-10.40,-9.31,-11.04,-9.85,-9.39,-9.79,-10.87,-10.39,-10.57,-10.03,-9.78,-10.79,-10.92,-10.73,-9.95,-10.99,-10.28,-8.88,-10.86,-9.17,-10.86,-8.91,-10.89,-8.19,-10.87,-9.30,-9.88,-9.33,-10.03,-11.60,-9.76,-11.13,-10.18,-8.15,-9.20,-10.80,-9.58,-10.12,-8.20,-10.47,-8.85,-9.71,-9.53,-8.99,-10.36,-11.14,-8.82,-10.08,-9.83,-9.35,-9.43,-10.00,-9.24,-8.56,-11.20,-8.75,-9.70,-9.25,-10.17,-10.49,-9.54,-10.89,-9.75,-10.21,-9.84,-8.29,-9.86,-9.34,-10.36,-9.67,-10.01,-9.90,-8.35 2024-01-24 03:28:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 73: train = -10.8568(13.03m/1151) | dev = -9.9010(0.69m/173) 2024-01-24 03:28:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 03:30:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.93)... 2024-01-24 03:33:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.85)... 2024-01-24 03:35:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.93)... 2024-01-24 03:37:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.84)... 2024-01-24 03:39:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.88)... 2024-01-24 03:41:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 03:42:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.79,-10.58,-8.67,-11.26,-9.01,-8.77,-10.55,-10.15,-9.84,-10.50,-7.00,-10.46,-10.75,-10.60,-10.10,-7.90,-10.29,-10.47,-11.48,-9.78,-10.02,-8.07,-9.80,-9.20,-9.53,-9.67,-9.09,-10.37,-9.03,-11.09,-8.70,-11.28,-9.58,-11.10,-7.78,-10.30,-9.04,-9.63,-8.61,-10.97,-9.76,-10.42,-9.54,-9.20,-10.23,-10.40,-10.02,-10.62,-9.62,-9.89,-9.12,-10.94,-9.32,-10.49,-10.28,-10.01,-9.07,-10.55,-9.79,-9.89,-10.61,-10.25,-10.10,-9.33,-9.98,-8.61,-9.03,-8.93,-10.36,-10.71,-10.93,-10.10,-10.08,-9.89,-11.81,-10.36,-10.18,-8.59,-9.22,-9.36,-10.59,-9.64,-10.13,-9.08,-10.81,-9.98,-10.44,-9.83,-10.82,-10.21,-10.22,-10.75,-11.54,-9.62,-10.89,-10.10,-9.53,-10.63,-9.61,-9.39,-10.39,-9.41,-11.02,-9.71,-9.34,-9.88,-10.90,-10.42,-10.62,-10.09,-9.82,-10.91,-10.78,-10.89,-9.74,-11.05,-10.41,-8.90,-10.70,-9.08,-10.87,-9.49,-10.61,-8.23,-10.94,-9.52,-9.78,-9.36,-9.98,-11.60,-9.61,-11.27,-10.17,-8.37,-9.20,-10.82,-9.50,-10.23,-8.35,-10.44,-9.05,-9.72,-9.49,-9.29,-10.41,-11.26,-8.99,-10.13,-9.93,-9.41,-9.48,-9.64,-9.18,-8.55,-11.18,-8.81,-9.87,-9.16,-10.16,-10.47,-9.65,-10.90,-9.70,-10.25,-9.76,-8.23,-9.96,-9.50,-10.37,-9.77,-9.97,-9.90,-8.49 2024-01-24 03:42:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 74: train = -10.8797(12.97m/1152) | dev = -9.9090(0.70m/173) 2024-01-24 03:42:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 03:44:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.97)... 2024-01-24 03:46:46 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.85)... 2024-01-24 03:49:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.90)... 2024-01-24 03:51:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.89)... 2024-01-24 03:53:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.92)... 2024-01-24 03:55:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 03:55:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 03:55:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 75: train = -10.8968(12.98m/1151) | dev = -9.8925(0.71m/173) | no impr, best = -9.9090 2024-01-24 03:55:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 03:58:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.92)... 2024-01-24 04:00:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.95)... 2024-01-24 04:02:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.87)... 2024-01-24 04:04:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.91)... 2024-01-24 04:07:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.83)... 2024-01-24 04:08:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 04:09:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 04:09:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 76: train = -10.9006(13.02m/1150) | dev = -9.9106(0.70m/173) 2024-01-24 04:09:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 04:12:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.95)... 2024-01-24 04:14:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.96)... 2024-01-24 04:16:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.95)... 2024-01-24 04:18:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.88)... 2024-01-24 04:20:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.91)... 2024-01-24 04:22:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 04:23:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 04:23:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 77: train = -10.9284(13.04m/1152) | dev = -9.9115(0.69m/173) 2024-01-24 04:23:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 04:25:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.93)... 2024-01-24 04:27:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.04)... 2024-01-24 04:30:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.92)... 2024-01-24 04:32:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.92)... 2024-01-24 04:34:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.90)... 2024-01-24 04:36:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 04:37:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.77,-10.60,-8.69,-11.34,-9.25,-8.64,-10.57,-10.22,-9.70,-10.43,-6.96,-10.55,-10.69,-10.53,-10.13,-8.34,-10.52,-10.43,-11.45,-9.67,-10.13,-8.51,-9.79,-8.93,-9.75,-9.67,-8.99,-10.19,-9.07,-11.13,-8.68,-11.17,-9.78,-11.04,-7.80,-10.40,-9.20,-9.38,-8.73,-11.01,-9.55,-10.36,-9.54,-9.35,-10.10,-10.53,-10.18,-10.71,-9.59,-9.88,-8.62,-10.94,-9.31,-10.45,-10.36,-10.01,-9.05,-10.65,-9.73,-9.97,-10.56,-10.10,-9.98,-9.45,-9.96,-8.59,-9.18,-9.23,-10.39,-10.71,-11.03,-10.15,-9.99,-9.48,-11.90,-10.34,-10.25,-9.01,-8.99,-9.44,-10.66,-9.72,-10.39,-9.24,-10.85,-10.68,-10.62,-9.69,-10.65,-10.28,-10.10,-10.71,-11.51,-9.50,-10.95,-10.08,-9.66,-10.64,-9.71,-9.58,-10.33,-9.36,-11.09,-9.73,-9.40,-9.85,-10.94,-10.42,-10.61,-10.19,-9.75,-10.92,-10.98,-10.63,-9.93,-10.83,-10.28,-8.81,-10.86,-9.07,-10.88,-8.98,-10.78,-8.34,-10.83,-9.46,-9.82,-9.64,-9.97,-11.56,-9.63,-11.22,-10.21,-8.33,-9.19,-10.80,-9.58,-10.17,-8.25,-10.54,-9.03,-9.74,-9.55,-9.22,-10.49,-11.22,-8.57,-10.14,-10.00,-9.41,-9.40,-9.79,-9.18,-8.54,-11.23,-8.74,-9.99,-9.29,-10.24,-10.55,-9.69,-10.55,-9.73,-10.38,-9.96,-8.53,-9.93,-9.49,-10.54,-9.69,-10.09,-9.96,-8.42 2024-01-24 04:37:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 78: train = -10.9463(12.99m/1150) | dev = -9.9259(0.73m/173) 2024-01-24 04:37:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 04:39:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.94)... 2024-01-24 04:41:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.95)... 2024-01-24 04:43:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.97)... 2024-01-24 04:46:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.95)... 2024-01-24 04:48:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.00)... 2024-01-24 04:50:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 04:50:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.30,-10.65,-8.72,-11.34,-9.19,-8.87,-10.60,-10.28,-9.56,-10.46,-7.03,-10.58,-10.61,-10.61,-10.19,-8.44,-10.41,-10.27,-11.41,-9.56,-10.03,-8.60,-9.83,-8.99,-9.55,-9.69,-9.23,-10.38,-9.05,-11.15,-9.04,-11.36,-9.59,-11.11,-7.90,-10.37,-9.36,-9.68,-8.84,-11.10,-9.74,-10.14,-9.58,-9.26,-10.00,-10.37,-10.00,-10.65,-9.44,-9.92,-8.35,-11.09,-9.19,-10.82,-10.38,-10.00,-9.07,-10.68,-9.52,-10.14,-10.42,-10.07,-10.07,-9.61,-9.97,-8.52,-9.33,-9.19,-10.39,-10.73,-11.00,-10.13,-9.96,-10.05,-11.83,-10.47,-10.27,-8.84,-8.75,-9.19,-10.32,-9.58,-10.22,-9.27,-10.84,-10.22,-10.69,-9.88,-10.86,-10.00,-10.22,-10.71,-11.51,-9.57,-10.94,-9.99,-9.62,-10.63,-9.79,-9.62,-10.28,-9.49,-11.08,-9.56,-9.52,-9.91,-10.93,-10.44,-10.56,-10.22,-9.77,-10.98,-10.90,-10.97,-9.88,-10.79,-10.17,-8.87,-10.79,-9.27,-10.90,-9.26,-10.63,-8.03,-10.86,-9.31,-9.93,-9.52,-9.89,-11.62,-9.63,-11.11,-10.20,-8.29,-9.09,-10.80,-9.56,-10.22,-8.19,-10.52,-8.97,-9.76,-9.58,-9.27,-10.51,-11.22,-8.99,-10.12,-9.86,-9.33,-9.40,-9.95,-9.21,-8.52,-11.26,-8.83,-10.14,-9.51,-10.26,-10.56,-9.56,-10.99,-9.85,-10.23,-9.83,-8.41,-9.98,-9.58,-10.37,-9.71,-10.09,-9.93,-8.49 2024-01-24 04:50:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 79: train = -10.9595(12.99m/1151) | dev = -9.9293(0.69m/173) 2024-01-24 04:50:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 04:53:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -10.98)... 2024-01-24 04:55:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -10.99)... 2024-01-24 04:57:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.01)... 2024-01-24 04:59:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.97)... 2024-01-24 05:02:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.96)... 2024-01-24 05:03:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 05:04:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 05:04:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 80: train = -10.9694(13.01m/1150) | dev = -9.9521(0.70m/173) 2024-01-24 05:04:28 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 05:06:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.03)... 2024-01-24 05:09:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.03)... 2024-01-24 05:11:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.96)... 2024-01-24 05:13:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -10.97)... 2024-01-24 05:15:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.98)... 2024-01-24 05:17:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 05:18:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 05:18:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 81: train = -10.9972(13.06m/1152) | dev = -9.9432(0.70m/173) | no impr, best = -9.9521 2024-01-24 05:18:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 05:20:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.00)... 2024-01-24 05:22:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.09)... 2024-01-24 05:25:09 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.95)... 2024-01-24 05:27:22 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.06)... 2024-01-24 05:29:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.99)... 2024-01-24 05:31:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 05:31:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 05:31:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 82: train = -11.0067(13.05m/1151) | dev = -9.9621(0.71m/173) 2024-01-24 05:31:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 05:34:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.03)... 2024-01-24 05:36:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.02)... 2024-01-24 05:38:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -10.99)... 2024-01-24 05:41:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.07)... 2024-01-24 05:43:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -10.97)... 2024-01-24 05:44:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 05:45:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.27,-10.66,-8.95,-11.39,-9.03,-8.47,-10.56,-10.17,-9.59,-10.53,-7.23,-10.51,-10.55,-10.60,-10.00,-8.10,-10.57,-10.47,-11.50,-9.65,-9.86,-8.53,-9.81,-9.31,-9.46,-9.76,-8.92,-10.42,-9.07,-11.16,-8.90,-11.29,-9.40,-11.17,-7.92,-10.39,-9.52,-9.29,-8.82,-11.12,-9.61,-10.29,-9.52,-9.14,-10.01,-10.38,-10.10,-10.67,-9.51,-9.99,-8.57,-11.01,-9.31,-10.71,-10.40,-10.01,-9.18,-10.68,-9.64,-9.98,-10.51,-10.12,-10.09,-9.59,-10.02,-8.55,-9.34,-9.28,-10.22,-10.75,-11.06,-10.17,-10.00,-9.85,-11.98,-10.39,-10.20,-8.94,-8.96,-9.63,-10.64,-9.69,-10.10,-9.07,-10.76,-10.34,-10.76,-9.61,-10.67,-10.15,-10.22,-10.77,-11.44,-9.65,-10.95,-10.06,-9.48,-10.61,-9.80,-9.60,-10.43,-9.32,-11.10,-9.76,-9.28,-9.95,-10.98,-10.42,-10.63,-10.02,-9.77,-11.10,-10.68,-11.00,-9.79,-10.68,-10.55,-9.11,-10.94,-9.32,-10.89,-9.20,-10.78,-9.10,-10.89,-9.43,-9.91,-9.45,-10.01,-11.57,-9.74,-11.09,-10.19,-8.07,-8.90,-10.83,-9.62,-10.13,-8.40,-10.58,-8.96,-9.77,-9.56,-9.25,-10.67,-11.19,-8.87,-10.14,-9.90,-9.40,-9.33,-10.12,-9.21,-8.57,-11.28,-8.70,-9.93,-9.35,-10.22,-10.63,-9.73,-10.91,-9.87,-10.28,-9.80,-8.42,-9.88,-9.49,-10.38,-9.79,-10.02,-9.94,-8.43 2024-01-24 05:45:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 83: train = -11.0100(12.97m/1151) | dev = -9.9377(0.71m/173) | no impr, best = -9.9621 2024-01-24 05:45:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 05:48:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.12)... 2024-01-24 05:50:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.09)... 2024-01-24 05:52:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.00)... 2024-01-24 05:54:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.03)... 2024-01-24 05:56:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.00)... 2024-01-24 05:58:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 05:59:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.41,-10.65,-9.06,-11.40,-9.23,-8.38,-10.61,-10.26,-9.73,-10.46,-7.01,-10.59,-10.78,-10.67,-10.13,-8.21,-10.59,-10.40,-11.50,-10.01,-10.21,-8.39,-9.85,-9.26,-9.85,-9.74,-9.02,-10.15,-8.99,-11.16,-8.78,-11.35,-9.80,-11.26,-7.80,-10.38,-9.47,-9.45,-8.20,-10.88,-9.66,-10.48,-9.41,-9.10,-9.95,-10.39,-9.91,-10.69,-9.77,-9.97,-8.97,-11.11,-9.18,-10.84,-10.39,-10.07,-9.08,-10.73,-9.82,-9.99,-10.30,-10.09,-9.92,-9.77,-10.07,-8.75,-9.25,-9.32,-10.36,-10.76,-11.00,-10.16,-10.01,-9.80,-11.85,-10.47,-10.33,-8.63,-9.32,-9.48,-10.53,-9.68,-10.18,-9.51,-10.83,-10.17,-10.77,-9.59,-10.66,-10.26,-10.02,-10.76,-11.43,-9.46,-10.94,-10.10,-9.65,-10.63,-9.47,-9.60,-10.27,-9.35,-11.07,-9.79,-9.52,-9.91,-10.91,-10.41,-10.68,-10.22,-9.80,-10.97,-10.91,-10.84,-9.97,-10.56,-10.51,-9.04,-10.80,-9.24,-10.91,-9.22,-10.79,-8.64,-10.95,-9.33,-9.98,-9.70,-9.96,-11.43,-10.04,-10.94,-10.20,-8.18,-8.96,-10.85,-9.65,-10.22,-8.41,-10.41,-9.15,-9.75,-9.60,-9.18,-10.55,-11.27,-8.87,-10.12,-10.17,-9.54,-9.42,-9.87,-9.26,-8.54,-11.19,-8.89,-9.87,-9.08,-10.10,-10.66,-9.68,-10.98,-9.79,-10.24,-9.73,-8.72,-9.96,-9.54,-10.45,-9.49,-10.10,-9.96,-8.47 2024-01-24 05:59:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 84: train = -11.0350(12.96m/1151) | dev = -9.9492(0.71m/173) | no impr, best = -9.9621 2024-01-24 05:59:21 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 06:01:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.13)... 2024-01-24 06:03:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.05)... 2024-01-24 06:06:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.00)... 2024-01-24 06:08:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.09)... 2024-01-24 06:10:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.00)... 2024-01-24 06:12:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 06:13:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.82,-10.61,-8.72,-11.40,-9.11,-8.75,-10.58,-10.21,-9.77,-10.30,-6.82,-10.49,-10.80,-10.65,-10.11,-8.07,-10.46,-10.48,-11.45,-9.56,-9.86,-8.41,-9.83,-9.02,-9.66,-9.73,-9.15,-10.49,-9.14,-11.18,-8.72,-11.26,-9.96,-11.03,-7.98,-10.45,-8.91,-9.65,-8.52,-10.59,-9.20,-10.41,-9.47,-9.17,-10.14,-10.39,-10.12,-10.74,-9.72,-10.05,-9.16,-10.95,-9.30,-10.51,-10.54,-10.01,-9.08,-10.64,-9.80,-10.03,-10.56,-10.25,-10.20,-9.49,-9.69,-8.63,-9.09,-9.20,-10.33,-10.71,-11.09,-10.14,-10.00,-10.00,-11.83,-10.47,-10.27,-8.95,-9.14,-9.51,-10.70,-9.46,-10.43,-9.25,-10.84,-9.90,-10.59,-9.83,-10.64,-10.17,-10.01,-10.78,-11.49,-9.64,-10.96,-10.07,-9.75,-10.73,-9.88,-9.41,-10.30,-9.25,-11.07,-9.85,-9.33,-9.88,-11.00,-10.37,-10.67,-9.98,-9.68,-10.85,-10.95,-10.80,-9.86,-10.17,-10.62,-8.86,-10.97,-9.13,-10.97,-9.27,-10.67,-8.74,-10.91,-9.21,-10.04,-9.34,-10.04,-11.52,-9.98,-11.15,-10.24,-8.32,-9.24,-10.80,-9.60,-10.31,-8.28,-10.28,-9.05,-9.76,-9.45,-9.41,-10.34,-11.20,-8.50,-10.10,-10.12,-9.43,-9.17,-9.96,-9.19,-8.52,-11.22,-8.76,-9.88,-9.14,-9.93,-10.63,-9.61,-10.91,-9.92,-10.27,-9.80,-8.36,-9.85,-9.45,-10.41,-9.79,-10.16,-10.03,-8.55 2024-01-24 06:13:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=2.500e-04) - Epoch 85: train = -11.0473(12.97m/1152) | dev = -9.9283(0.69m/173) | no impr, best = -9.9621 2024-01-24 06:13:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 06:15:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.06)... 2024-01-24 06:17:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.14)... 2024-01-24 06:19:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.14)... 2024-01-24 06:22:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.15)... 2024-01-24 06:24:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.14)... 2024-01-24 06:26:02 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 06:26:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 06:26:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.250e-04) - Epoch 86: train = -11.1273(13.02m/1152) | dev = -10.0097(0.70m/173) 2024-01-24 06:26:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 06:29:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.12)... 2024-01-24 06:31:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.19)... 2024-01-24 06:33:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.18)... 2024-01-24 06:35:54 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.13)... 2024-01-24 06:38:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.14)... 2024-01-24 06:39:48 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 06:40:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.72,-10.68,-9.03,-11.42,-9.27,-8.75,-10.67,-10.33,-9.75,-10.58,-7.15,-10.62,-10.70,-10.73,-10.30,-8.13,-10.50,-10.59,-11.49,-9.77,-10.11,-8.49,-9.88,-9.15,-9.70,-9.79,-8.91,-10.38,-9.02,-11.22,-9.07,-11.42,-9.80,-11.24,-7.97,-10.37,-9.42,-9.58,-8.73,-10.40,-9.81,-10.36,-9.46,-9.30,-10.13,-10.41,-10.17,-10.59,-9.68,-10.08,-8.42,-11.06,-9.23,-10.87,-10.42,-10.11,-9.20,-10.71,-9.86,-10.05,-10.28,-10.26,-10.08,-9.61,-10.07,-8.73,-9.39,-9.45,-10.41,-10.80,-11.11,-10.20,-10.05,-10.15,-12.07,-10.46,-10.31,-9.06,-9.12,-9.59,-10.71,-9.53,-10.41,-9.20,-10.92,-9.90,-10.74,-9.72,-10.79,-10.15,-10.42,-10.92,-11.50,-9.60,-10.98,-10.14,-9.62,-10.82,-9.95,-9.73,-10.54,-9.40,-11.12,-9.77,-9.44,-9.98,-11.02,-10.51,-10.74,-10.19,-9.81,-10.94,-10.90,-11.05,-10.04,-10.73,-10.58,-8.90,-11.02,-9.25,-10.96,-9.24,-10.88,-8.67,-11.00,-9.37,-10.01,-9.66,-9.90,-11.71,-9.89,-11.12,-10.13,-8.57,-9.20,-10.87,-9.62,-10.29,-8.45,-10.36,-9.12,-9.79,-9.69,-9.23,-10.49,-11.27,-8.95,-10.15,-10.19,-9.52,-9.51,-10.06,-9.32,-8.60,-11.28,-8.83,-10.07,-9.32,-10.23,-10.72,-9.74,-11.11,-9.83,-10.35,-9.80,-9.00,-9.98,-9.62,-10.42,-9.72,-10.05,-10.00,-8.64 2024-01-24 06:40:29 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.250e-04) - Epoch 87: train = -11.1518(13.05m/1151) | dev = -10.0061(0.69m/173) | no impr, best = -10.0097 2024-01-24 06:40:30 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 06:42:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.19)... 2024-01-24 06:45:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.10)... 2024-01-24 06:47:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.13)... 2024-01-24 06:49:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.16)... 2024-01-24 06:51:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.21)... 2024-01-24 06:53:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 06:54:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.48,-10.68,-8.83,-11.46,-9.43,-8.74,-10.65,-10.27,-9.91,-10.48,-7.23,-10.61,-10.58,-10.71,-10.32,-8.10,-10.46,-10.60,-11.53,-9.76,-10.24,-8.43,-9.88,-9.24,-9.77,-9.70,-9.18,-10.35,-9.08,-11.20,-8.87,-11.38,-9.73,-11.28,-7.90,-10.40,-9.39,-9.57,-8.95,-10.93,-9.74,-10.42,-9.55,-9.30,-10.17,-10.54,-10.22,-10.76,-9.73,-10.00,-8.86,-11.09,-9.34,-10.82,-10.46,-10.12,-9.18,-10.78,-9.90,-10.13,-10.61,-10.20,-10.10,-9.63,-10.04,-8.73,-9.24,-9.53,-10.26,-10.82,-11.13,-10.20,-10.07,-10.15,-11.98,-10.41,-10.35,-8.80,-9.04,-9.52,-10.62,-9.56,-10.28,-9.19,-10.93,-9.99,-10.70,-9.84,-10.60,-9.46,-10.25,-10.81,-11.57,-9.87,-11.02,-10.23,-9.74,-10.77,-9.94,-9.84,-10.59,-9.39,-11.14,-9.90,-9.33,-9.90,-11.00,-10.56,-10.68,-10.23,-9.89,-10.97,-10.88,-11.11,-9.92,-10.22,-10.47,-9.29,-10.90,-9.17,-10.97,-9.44,-10.87,-8.98,-11.03,-9.37,-10.02,-9.29,-9.99,-11.67,-10.03,-11.16,-10.30,-8.45,-9.05,-10.89,-9.66,-10.37,-8.41,-10.46,-9.03,-9.82,-9.63,-9.33,-10.51,-11.26,-9.44,-10.20,-9.86,-9.57,-9.50,-9.99,-9.30,-8.57,-11.28,-8.79,-9.92,-9.21,-10.32,-10.70,-9.78,-11.15,-9.86,-10.36,-9.64,-8.95,-9.94,-9.59,-10.53,-9.92,-10.08,-10.02,-8.55 2024-01-24 06:54:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.250e-04) - Epoch 88: train = -11.1601(13.03m/1151) | dev = -10.0115(0.70m/173) 2024-01-24 06:54:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 06:56:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.15)... 2024-01-24 06:58:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.19)... 2024-01-24 07:01:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.18)... 2024-01-24 07:03:19 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.22)... 2024-01-24 07:05:32 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.18)... 2024-01-24 07:07:14 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 07:07:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.57,-10.70,-9.14,-11.43,-9.21,-8.75,-10.66,-10.22,-9.90,-10.61,-7.15,-10.62,-10.81,-10.72,-10.32,-8.24,-10.71,-10.54,-11.55,-9.88,-9.91,-8.52,-9.88,-9.44,-9.69,-9.73,-9.01,-10.44,-9.07,-11.23,-8.96,-11.48,-9.86,-11.37,-7.63,-10.49,-9.50,-9.61,-8.71,-11.19,-9.72,-10.37,-9.53,-9.27,-9.94,-10.41,-10.23,-10.69,-9.62,-10.06,-8.68,-11.18,-9.28,-10.75,-10.45,-10.11,-9.13,-10.78,-9.78,-10.08,-10.41,-10.29,-10.11,-9.63,-10.15,-8.76,-9.31,-9.52,-10.31,-10.81,-11.15,-10.23,-10.09,-10.21,-12.06,-10.38,-10.32,-8.90,-9.02,-9.45,-10.48,-9.68,-10.18,-9.44,-10.93,-10.02,-10.79,-9.78,-10.81,-9.98,-10.22,-10.87,-11.59,-9.57,-11.03,-10.25,-9.67,-10.77,-9.95,-9.86,-10.59,-9.43,-11.16,-10.03,-9.31,-9.96,-11.03,-10.59,-10.80,-10.10,-9.88,-11.13,-10.81,-11.00,-10.04,-10.72,-10.78,-9.00,-11.07,-9.42,-10.98,-9.45,-10.93,-8.83,-11.01,-9.30,-9.94,-9.47,-9.90,-11.64,-10.00,-11.14,-10.29,-8.45,-9.14,-10.88,-9.66,-10.34,-8.48,-10.39,-9.25,-9.79,-9.60,-9.30,-10.49,-11.31,-9.65,-10.20,-10.20,-9.48,-9.56,-10.03,-9.35,-8.63,-11.25,-8.81,-9.94,-9.26,-10.26,-10.70,-9.68,-11.10,-9.69,-10.37,-9.94,-8.80,-9.96,-9.60,-10.48,-9.69,-10.18,-10.04,-8.52 2024-01-24 07:07:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.250e-04) - Epoch 89: train = -11.1878(13.00m/1152) | dev = -10.0273(0.69m/173) 2024-01-24 07:07:56 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 07:10:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.21)... 2024-01-24 07:12:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.17)... 2024-01-24 07:14:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.20)... 2024-01-24 07:17:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.21)... 2024-01-24 07:19:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.17)... 2024-01-24 07:20:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 07:21:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 07:21:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.250e-04) - Epoch 90: train = -11.1903(12.95m/1150) | dev = -10.0105(0.70m/173) | no impr, best = -10.0273 2024-01-24 07:21:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 07:24:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.18)... 2024-01-24 07:26:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.23)... 2024-01-24 07:28:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.16)... 2024-01-24 07:30:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.26)... 2024-01-24 07:32:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.17)... 2024-01-24 07:34:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 07:35:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 07:35:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.250e-04) - Epoch 91: train = -11.1963(12.98m/1152) | dev = -10.0065(0.71m/173) | no impr, best = -10.0273 2024-01-24 07:35:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 07:37:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.22)... 2024-01-24 07:39:55 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.29)... 2024-01-24 07:42:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.15)... 2024-01-24 07:44:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.23)... 2024-01-24 07:46:36 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.18)... 2024-01-24 07:48:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 07:48:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 07:48:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=1.250e-04) - Epoch 92: train = -11.2114(13.00m/1151) | dev = -9.9998(0.70m/173) | no impr, best = -10.0273 2024-01-24 07:48:59 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 07:51:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.21)... 2024-01-24 07:53:38 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.25)... 2024-01-24 07:55:51 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.25)... 2024-01-24 07:58:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.28)... 2024-01-24 08:00:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.28)... 2024-01-24 08:01:58 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 08:02:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.73,-10.72,-8.85,-11.45,-9.26,-8.71,-10.67,-10.31,-9.89,-10.50,-7.21,-10.64,-10.83,-10.68,-10.20,-8.18,-10.67,-10.65,-11.55,-9.82,-10.12,-8.65,-9.90,-9.35,-9.76,-9.71,-9.02,-10.47,-9.08,-11.25,-8.93,-11.47,-9.77,-11.12,-7.93,-10.47,-9.29,-9.57,-8.70,-10.64,-9.66,-10.57,-9.69,-9.39,-10.09,-10.43,-10.29,-10.71,-9.74,-10.05,-8.89,-11.08,-9.25,-10.92,-10.44,-10.11,-9.30,-10.76,-9.88,-10.03,-10.46,-10.42,-10.13,-9.73,-9.97,-8.71,-9.14,-9.47,-10.37,-10.83,-11.16,-10.20,-10.11,-10.32,-12.08,-10.43,-10.36,-8.97,-9.05,-9.44,-10.85,-9.64,-10.40,-9.49,-10.77,-9.67,-10.79,-9.61,-10.88,-10.32,-10.15,-10.79,-11.26,-9.78,-11.05,-10.10,-9.66,-10.68,-9.99,-9.83,-10.59,-9.47,-11.20,-10.06,-9.27,-9.97,-11.04,-10.54,-10.72,-10.12,-9.95,-10.94,-10.89,-10.81,-9.92,-10.94,-10.76,-9.15,-11.09,-9.38,-11.01,-9.21,-10.94,-8.66,-11.04,-9.50,-9.93,-9.21,-9.76,-11.69,-10.00,-11.21,-10.29,-8.45,-9.26,-10.91,-9.69,-10.37,-8.39,-10.19,-9.27,-9.80,-9.71,-9.33,-10.52,-11.31,-9.24,-10.25,-10.11,-9.45,-9.51,-10.15,-9.34,-8.68,-11.31,-8.84,-9.96,-9.34,-10.25,-10.69,-9.71,-11.06,-9.91,-10.38,-10.03,-8.59,-10.12,-9.61,-10.50,-9.73,-10.24,-10.10,-8.64 2024-01-24 08:02:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=6.250e-05) - Epoch 93: train = -11.2484(12.98m/1151) | dev = -10.0300(0.69m/173) 2024-01-24 08:02:41 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 08:05:06 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.33)... 2024-01-24 08:07:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.25)... 2024-01-24 08:09:33 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.33)... 2024-01-24 08:11:47 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.20)... 2024-01-24 08:14:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.27)... 2024-01-24 08:15:42 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 08:16:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.83,-10.74,-8.99,-11.46,-9.25,-8.69,-10.71,-10.33,-9.90,-10.58,-7.29,-10.69,-10.83,-10.80,-10.23,-8.26,-10.65,-10.49,-11.55,-9.99,-10.05,-8.61,-9.90,-9.35,-9.70,-9.65,-9.02,-10.46,-9.08,-11.26,-9.04,-11.49,-9.81,-11.17,-7.86,-10.46,-9.35,-9.53,-8.85,-10.73,-9.83,-10.59,-9.57,-9.37,-10.11,-10.34,-10.29,-10.58,-9.67,-9.99,-8.80,-11.19,-9.36,-10.99,-10.48,-10.13,-9.26,-10.79,-9.76,-10.04,-10.48,-10.39,-10.14,-9.86,-9.98,-8.71,-9.13,-9.45,-10.50,-10.81,-11.17,-10.20,-10.13,-10.28,-12.06,-10.44,-10.35,-8.90,-9.03,-9.45,-10.83,-9.74,-10.36,-9.38,-10.99,-9.47,-10.76,-9.78,-10.84,-10.32,-10.17,-10.79,-11.44,-9.67,-11.05,-10.15,-9.68,-10.75,-10.02,-9.84,-10.55,-9.46,-11.26,-10.06,-9.36,-9.99,-11.04,-10.59,-10.65,-10.11,-9.96,-11.01,-10.73,-11.13,-9.89,-10.90,-10.70,-9.06,-11.08,-9.44,-11.05,-9.22,-10.86,-8.68,-11.08,-9.41,-9.88,-9.59,-9.75,-11.72,-10.03,-11.21,-10.26,-8.47,-9.28,-10.91,-9.66,-10.35,-8.46,-9.99,-9.17,-9.83,-9.76,-9.31,-10.51,-11.32,-9.43,-10.30,-9.89,-9.22,-9.58,-9.99,-9.34,-8.69,-11.30,-8.72,-9.97,-9.48,-10.26,-10.67,-9.65,-11.12,-9.98,-10.37,-10.09,-9.00,-10.04,-9.70,-10.49,-9.66,-10.25,-10.07,-8.66 2024-01-24 08:16:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=6.250e-05) - Epoch 94: train = -11.2655(13.02m/1151) | dev = -10.0398(0.70m/173) 2024-01-24 08:16:24 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 08:18:50 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.29)... 2024-01-24 08:21:04 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.29)... 2024-01-24 08:23:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.29)... 2024-01-24 08:25:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.30)... 2024-01-24 08:27:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.24)... 2024-01-24 08:29:27 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 08:30:07 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 08:30:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=6.250e-05) - Epoch 95: train = -11.2752(13.04m/1151) | dev = -10.0497(0.68m/173) 2024-01-24 08:30:08 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 08:32:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.28)... 2024-01-24 08:34:49 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.32)... 2024-01-24 08:37:03 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.30)... 2024-01-24 08:39:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.26)... 2024-01-24 08:41:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.25)... 2024-01-24 08:43:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 08:43:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.77,-10.72,-8.96,-11.47,-9.22,-8.78,-10.70,-10.30,-9.89,-10.57,-7.19,-10.67,-10.65,-10.81,-10.23,-8.11,-10.68,-10.49,-11.53,-9.83,-10.12,-8.70,-9.92,-9.25,-9.76,-9.64,-9.06,-10.40,-9.12,-11.25,-8.92,-11.49,-9.85,-11.18,-7.91,-10.49,-9.41,-9.60,-8.80,-10.68,-9.67,-10.61,-9.59,-9.37,-10.09,-10.49,-10.23,-10.75,-9.74,-10.08,-8.63,-11.27,-9.31,-10.71,-10.49,-10.13,-9.25,-10.77,-9.80,-10.10,-10.53,-10.43,-10.16,-9.81,-9.90,-8.75,-9.13,-9.56,-10.50,-10.83,-11.17,-10.17,-10.09,-10.18,-12.06,-10.44,-10.37,-9.00,-9.04,-9.50,-10.79,-9.67,-10.12,-9.46,-10.88,-9.99,-10.80,-9.84,-10.86,-10.35,-10.24,-10.80,-11.51,-9.76,-11.05,-10.16,-9.70,-10.69,-10.08,-9.81,-10.58,-9.44,-11.16,-10.11,-9.36,-10.00,-11.09,-10.58,-10.72,-10.16,-9.95,-11.02,-10.72,-10.91,-10.06,-10.64,-10.71,-8.99,-11.07,-9.39,-11.04,-9.14,-10.93,-8.69,-11.06,-9.61,-9.94,-9.58,-9.76,-11.71,-10.01,-11.23,-10.32,-8.42,-9.24,-10.92,-9.67,-10.38,-8.40,-10.49,-9.15,-9.84,-9.72,-9.38,-10.49,-11.31,-9.44,-10.26,-9.99,-9.55,-9.60,-10.12,-9.39,-8.63,-11.32,-8.73,-9.87,-9.36,-10.31,-10.69,-9.70,-11.10,-9.95,-10.38,-10.09,-8.75,-10.19,-9.71,-10.52,-9.65,-10.27,-10.11,-8.62 2024-01-24 08:43:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=6.250e-05) - Epoch 96: train = -11.2751(13.05m/1150) | dev = -10.0456(0.69m/173) | no impr, best = -10.0497 2024-01-24 08:43:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 08:46:17 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.24)... 2024-01-24 08:48:31 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.25)... 2024-01-24 08:50:44 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.33)... 2024-01-24 08:52:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.29)... 2024-01-24 08:55:11 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.31)... 2024-01-24 08:56:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 08:57:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.61,-10.72,-9.06,-11.42,-9.03,-8.77,-10.69,-10.31,-9.85,-10.55,-7.23,-10.66,-10.79,-10.54,-10.25,-8.25,-10.66,-10.48,-11.56,-9.65,-10.04,-8.60,-9.92,-9.40,-9.64,-9.76,-9.07,-10.52,-9.07,-11.26,-8.97,-11.49,-9.78,-11.27,-7.89,-10.48,-9.20,-9.70,-8.73,-10.82,-9.60,-10.53,-9.65,-9.27,-10.07,-10.49,-10.31,-10.55,-9.74,-9.88,-8.47,-11.19,-9.30,-10.79,-10.50,-10.15,-9.34,-10.83,-9.77,-10.08,-10.50,-10.42,-10.12,-9.72,-9.95,-8.73,-9.17,-9.52,-10.48,-10.85,-11.19,-10.23,-10.12,-10.28,-12.08,-10.45,-10.36,-8.83,-9.08,-9.47,-10.78,-9.67,-10.15,-9.56,-10.84,-10.13,-10.83,-9.73,-10.82,-10.31,-10.28,-10.99,-11.52,-9.67,-11.05,-10.14,-9.69,-10.69,-10.05,-9.83,-10.60,-9.38,-11.22,-10.04,-9.46,-10.01,-11.09,-10.61,-10.79,-10.12,-9.92,-10.97,-10.84,-10.94,-10.03,-10.52,-10.73,-9.20,-11.07,-9.35,-11.04,-9.26,-11.03,-8.72,-11.08,-9.46,-9.98,-9.62,-9.79,-11.69,-10.08,-11.28,-10.31,-8.37,-9.24,-10.90,-9.67,-10.43,-8.50,-10.48,-9.10,-9.85,-9.70,-9.31,-10.58,-11.32,-9.43,-10.24,-9.99,-9.46,-9.60,-10.16,-9.34,-8.65,-11.33,-8.77,-10.01,-9.40,-10.34,-10.69,-9.60,-11.12,-9.99,-10.36,-9.96,-8.88,-10.23,-9.68,-10.48,-9.67,-10.17,-10.08,-8.66 2024-01-24 08:57:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=6.250e-05) - Epoch 97: train = -11.2855(13.00m/1152) | dev = -10.0430(0.70m/173) | no impr, best = -10.0497 2024-01-24 08:57:35 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 09:00:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.33)... 2024-01-24 09:02:13 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.29)... 2024-01-24 09:04:26 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.32)... 2024-01-24 09:06:40 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.24)... 2024-01-24 09:08:53 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.30)... 2024-01-24 09:10:34 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 09:11:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.77,-10.73,-8.98,-11.45,-9.35,-8.69,-10.70,-10.38,-9.80,-10.56,-7.31,-10.69,-10.78,-10.74,-10.14,-8.09,-10.66,-10.51,-11.55,-9.90,-10.04,-8.64,-9.92,-9.42,-9.68,-9.65,-9.02,-10.44,-9.05,-11.27,-8.87,-11.50,-9.80,-11.15,-7.82,-10.48,-9.21,-9.57,-8.75,-10.74,-9.68,-10.59,-9.54,-9.35,-10.11,-10.48,-10.26,-10.73,-9.77,-10.06,-8.64,-11.00,-9.32,-10.81,-10.50,-10.17,-9.28,-10.79,-9.78,-10.04,-10.48,-10.46,-10.17,-9.68,-10.02,-8.67,-9.15,-9.54,-10.43,-10.84,-11.20,-10.22,-10.11,-10.23,-12.06,-10.37,-10.39,-8.89,-9.02,-9.44,-10.86,-9.67,-10.07,-9.50,-10.87,-10.15,-10.77,-9.65,-10.82,-10.32,-10.24,-10.85,-11.32,-9.67,-11.06,-10.27,-9.66,-10.74,-10.06,-9.84,-10.63,-9.41,-11.23,-10.11,-9.54,-10.02,-11.08,-10.61,-10.74,-10.14,-9.93,-10.91,-10.92,-11.07,-9.81,-10.64,-10.67,-9.08,-11.10,-9.36,-11.05,-9.22,-11.00,-8.77,-11.09,-9.40,-9.93,-9.52,-9.74,-11.74,-10.13,-11.25,-10.32,-8.40,-9.31,-10.93,-9.70,-10.39,-8.52,-10.51,-9.13,-9.85,-9.74,-9.39,-10.56,-11.28,-9.49,-10.28,-10.05,-9.54,-9.51,-10.06,-9.41,-8.68,-11.32,-8.84,-10.06,-9.53,-10.24,-10.66,-9.76,-11.10,-9.96,-10.38,-10.10,-8.54,-10.16,-9.69,-10.52,-9.77,-10.25,-10.09,-8.64 2024-01-24 09:11:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=6.250e-05) - Epoch 98: train = -11.2943(12.99m/1151) | dev = -10.0460(0.69m/173) | no impr, best = -10.0497 2024-01-24 09:11:16 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 09:13:43 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.37)... 2024-01-24 09:15:57 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.29)... 2024-01-24 09:18:10 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.33)... 2024-01-24 09:20:23 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.33)... 2024-01-24 09:22:37 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.26)... 2024-01-24 09:24:18 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 09:25:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: -8.63,-10.74,-8.85,-11.46,-9.33,-8.65,-10.70,-10.29,-9.86,-10.59,-7.32,-10.68,-10.59,-10.68,-10.20,-8.16,-10.66,-10.51,-11.46,-9.96,-10.05,-8.63,-9.91,-9.41,-9.69,-9.65,-8.96,-10.46,-9.04,-11.27,-8.90,-11.33,-9.82,-11.17,-7.84,-10.48,-9.29,-9.61,-8.75,-10.72,-9.62,-10.61,-9.53,-9.38,-10.15,-10.40,-10.26,-10.71,-9.79,-10.05,-8.69,-11.16,-9.32,-10.76,-10.50,-10.16,-9.23,-10.82,-9.81,-10.04,-10.46,-10.28,-10.10,-9.73,-10.06,-8.66,-9.22,-9.55,-10.40,-10.75,-11.21,-10.21,-10.13,-10.19,-12.09,-10.39,-10.37,-8.92,-9.05,-9.54,-10.84,-9.75,-10.06,-9.56,-10.91,-10.20,-10.85,-9.74,-10.83,-10.35,-10.24,-10.87,-11.46,-9.70,-11.06,-10.16,-9.75,-10.72,-10.03,-9.86,-10.60,-9.51,-11.25,-10.11,-9.37,-10.03,-11.10,-10.60,-10.71,-10.14,-9.94,-10.99,-10.72,-11.00,-9.95,-10.76,-10.68,-8.93,-11.08,-9.42,-11.06,-9.18,-11.01,-8.73,-11.08,-9.47,-9.92,-9.54,-9.72,-11.73,-9.90,-11.24,-10.33,-8.42,-9.27,-10.93,-9.69,-10.39,-8.45,-10.56,-9.10,-9.86,-9.75,-9.32,-10.60,-11.32,-9.61,-10.28,-10.03,-9.44,-9.51,-10.15,-9.36,-8.66,-11.33,-8.93,-9.99,-9.49,-10.26,-10.68,-9.73,-11.13,-10.00,-10.44,-10.13,-8.96,-10.07,-9.68,-10.53,-9.67,-10.23,-10.12,-8.65 2024-01-24 09:25:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=3.125e-05) - Epoch 99: train = -11.3099(13.03m/1152) | dev = -10.0466(0.69m/173) | no impr, best = -10.0497 2024-01-24 09:25:00 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:183 - INFO ] Set train mode... 2024-01-24 09:27:25 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 200 batches(loss = -11.25)... 2024-01-24 09:29:39 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 400 batches(loss = -11.27)... 2024-01-24 09:31:52 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 600 batches(loss = -11.36)... 2024-01-24 09:34:05 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 800 batches(loss = -11.27)... 2024-01-24 09:36:20 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:64 - INFO ] Processed 1000 batches(loss = -11.41)... 2024-01-24 09:38:01 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:202 - INFO ] Set eval mode... 2024-01-24 09:38:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:72 - INFO ] Loss on 173 batches: 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2024-01-24 09:38:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:251 - INFO ] Loss(time/N, lr=3.125e-05) - Epoch 100: train = -11.3162(13.01m/1151) | dev = -10.0425(0.74m/173) | no impr, best = -10.0497 2024-01-24 09:38:45 [/star-home/jinzengrui/dev/conv-tasnet-libriheavymix/nnet_whamr_w_small/libs/trainer.py:263 - INFO ] Training for 100/100 epoches done!