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.gitattributes

@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+examples/example_dry.wav filter=lfs diff=lfs merge=lfs -text
+examples/example_other.wav filter=lfs diff=lfs merge=lfs -text
+examples/example_raw.wav filter=lfs diff=lfs merge=lfs -text

config_dereverb-echo_mel_band_roformer.yaml

@@ -0,0 +1,77 @@
+audio:
+  chunk_size: 352800
+  dim_f: 1024
+  dim_t: 801 # don't work (use in model)
+  hop_length: 441 # don't work (use in model)
+  n_fft: 2048
+  num_channels: 2
+  sample_rate: 44100
+  min_mean_abs: 0.000
+
+model:
+  dim: 256
+  depth: 8
+  stereo: true
+  num_stems: 2
+  time_transformer_depth: 1
+  freq_transformer_depth: 1
+  linear_transformer_depth: 0
+  num_bands: 60
+  dim_head: 64
+  heads: 8
+  attn_dropout: 0.1
+  ff_dropout: 0.1
+  flash_attn: True
+  dim_freqs_in: 1025
+  sample_rate: 44100  # needed for mel filter bank from librosa
+  stft_n_fft: 2048
+  stft_hop_length: 441
+  stft_win_length: 2048
+  stft_normalized: False
+  mask_estimator_depth: 2
+  multi_stft_resolution_loss_weight: 1.0
+  multi_stft_resolutions_window_sizes: !!python/tuple
+  - 4096
+  - 2048
+  - 1024
+  - 512
+  - 256
+  multi_stft_hop_size: 147
+  multi_stft_normalized: False
+
+training:
+  batch_size: 1
+  gradient_accumulation_steps: 8
+  grad_clip: 0
+  instruments:
+  - dry
+  - other
+  lr: 4.0e-05
+  patience: 2
+  reduce_factor: 0.95
+  target_instrument: null
+  num_epochs: 1000
+  num_steps: 1000
+  q: 0.95
+  coarse_loss_clip: true
+  ema_momentum: 0.999
+  optimizer: adam
+  other_fix: false # it's needed for checking on multisong dataset if other is actually instrumental
+  use_amp: true # enable or disable usage of mixed precision (float16) - usually it must be true
+
+augmentations:
+  enable: true # enable or disable all augmentations (to fast disable if needed)
+  loudness: true # randomly change loudness of each stem on the range (loudness_min; loudness_max)
+  loudness_min: 0.5
+  loudness_max: 1.5
+  mixup: false # mix several stems of same type with some probability (only works for dataset types: 1, 2, 3)
+  mixup_probs: !!python/tuple # 2 additional stems of the same type (1st with prob 0.2, 2nd with prob 0.02)
+    - 0.2
+    - 0.02
+  mixup_loudness_min: 0.5
+  mixup_loudness_max: 1.5
+
+inference:
+  batch_size: 4
+  dim_t: 801
+  num_overlap: 4

dereverb-echo_mel_band_roformer_sdr_10.0169.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd2b737a394cfb80cd48cc9fcbaf89f5f4062f6b93066c2911617a06d8b7860a
+size 835997896

examples/README.md

@@ -0,0 +1,5 @@
+license: [cc-by-nc-sa-4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)
+
+Example audios are from [TestableFred](https://space.bilibili.com/258080618)'s video: https://www.bilibili.com/video/BV1UZUpYGEwM
+
+Before inputting it into the model for inference, the original audio was separated from the vocal and instrument using the `model_bs_roformer_ep_368_sdr_12.9628.ckpt` model.

examples/example_dry.wav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fd4336e1aa539279591b8c59a4367cef6adc72a46c6356e93f8b572e80a0132c
+size 3218824

examples/example_other.wav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb7f0787014754c0a08397ef6773143aa34653316276c51402b3fc442905eef0
+size 3218824

examples/example_raw.wav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:21d6b5f935dea3f3765539205e4fc5fd781fe17ed001b192ee45bf293771ab49
+size 3508968

scripts/create_reverb_delay.py

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+import os
+import argparse
+import librosa
+import numpy as np
+import soundfile as sf
+from pedalboard import Pedalboard, Reverb, Delay, HighpassFilter, LowpassFilter
+from random import uniform
+from tqdm import tqdm
+
+
+def random_effect(audio, sr):
+    reverb = Pedalboard([
+        Delay(
+            delay_seconds=uniform(0.001, 0.100), 
+            feedback=0.0, 
+            mix=1.0
+        ),
+        Reverb(
+            room_size=uniform(0.1, 0.8),
+            damping=uniform(0.1, 0.8),
+            wet_level=1.0, 
+            dry_level=0.0, 
+            width=uniform(0.6, 1.0)
+        ),
+        HighpassFilter(cutoff_frequency_hz=uniform(100, 1000)),
+        LowpassFilter(cutoff_frequency_hz=uniform(4000, 12000))
+    ])
+
+    delay = Pedalboard([
+        Delay(
+            delay_seconds=uniform(0.05, 0.500),
+            feedback=uniform(0.1, 0.5),
+            mix=1.0
+        ),
+        Reverb(
+            room_size=uniform(0.05, 0.3),
+            damping=uniform(0.1, 0.8),
+            wet_level=0.2,
+            dry_level=0.8,
+            width=uniform(0.6, 1.0)
+        ),
+        HighpassFilter(cutoff_frequency_hz=uniform(100, 1000)),
+        LowpassFilter(cutoff_frequency_hz=uniform(3000, 10000))
+    ])
+
+    effect = uniform(0.1, 0.4) * reverb(audio, sr) + uniform(0.1, 0.4) * delay(audio, sr)
+    mix = effect + audio
+
+    return mix, effect
+
+
+if __name__ == '__main__':
+    argparser = argparse.ArgumentParser(description='Add random reverb and delay effects to an audio file.')
+    argparser.add_argument('-i', '--input_folder', type=str, default="train", help='Path to the input audio file.')
+    argparser.add_argument('-o', '--output_folder', type=str, default="dataset_train", help='Path to the output audio file.')
+    args = argparser.parse_args()
+
+    index = 1
+    sr = 44100
+    for file in tqdm(os.listdir(args.input_folder)):
+        try:
+            audio, _ = librosa.load(os.path.join(args.input_folder, file), sr=sr)
+            if len(audio.shape) == 1:
+                audio = np.stack([audio, audio], axis=1)
+            effect = random_effect(audio.T, sr)
+        except:
+            print(f"Failed to process file: {file}")
+            continue
+
+        os.makedirs(os.path.join(args.output_folder, str(index)), exist_ok=True)
+
+        sf.write(os.path.join(args.output_folder, str(index), "mixture.wav"), effect[0].T, sr, subtype='PCM_16')
+        sf.write(os.path.join(args.output_folder, str(index), "other.wav"), effect[1].T, sr, subtype='PCM_16')
+        sf.write(os.path.join(args.output_folder, str(index), "dry.wav"), audio, sr, subtype='PCM_16')
+
+        index += 1

scripts/start_tensorboard.py

@@ -0,0 +1,89 @@
+import re
+import os
+import numpy as np
+from tensorboardX import SummaryWriter
+
+writer = SummaryWriter('runs/metrics_visualization')
+
+epoch_pattern = re.compile(r'Train epoch: (\d+) Learning rate: ([\d.eE+-]+)')
+training_loss_pattern = re.compile(r'Training loss: ([\d.]+)')
+metric_pattern = re.compile(r'(\w+ \w+ \w+): ([\d.]+) \(Std: ([\d.]+)\)')
+avg_metric_pattern = re.compile(r'Metric avg (\w+)\s+: ([\d.]+)')
+
+data = {
+    'common': {
+        'learning_rate': [],
+        'training_loss': []
+    },
+    'dry': {
+        'Instr dry sdr': [],
+        'Instr dry l1_freq': [],
+        'Instr dry si_sdr': []
+    },
+    'other': {
+        'Instr other sdr': [],
+        'Instr other l1_freq': [],
+        'Instr other si_sdr': []
+    },
+    'avg': {
+        'Metric avg sdr': [],
+        'Metric avg l1_freq': [],
+        'Metric avg si_sdr': []
+    }
+}
+
+std_data = {
+    'dry': {key: [] for key in data['dry'].keys()},
+    'other': {key: [] for key in data['other'].keys()}
+}
+
+with open(r'E:\AI\datasets\msst\train.log', 'r') as f:
+    epoch = -1
+    for line in f:
+        epoch_match = epoch_pattern.match(line)
+        if epoch_match:
+            epoch = int(epoch_match.group(1))
+            learning_rate = float(epoch_match.group(2))
+            data['common']['learning_rate'].append((epoch, learning_rate))
+            continue
+        
+        training_loss_match = training_loss_pattern.match(line)
+        if training_loss_match:
+            training_loss = float(training_loss_match.group(1))
+            data['common']['training_loss'].append((epoch, training_loss))
+            continue
+        
+        metric_match = metric_pattern.match(line)
+        if metric_match:
+            metric_name = metric_match.group(1)
+            metric_value = float(metric_match.group(2))
+            std_value = float(metric_match.group(3))
+
+            if metric_name in data['dry']:
+                data['dry'][metric_name].append((epoch, metric_value))
+                std_data['dry'][metric_name].append((epoch, std_value))
+            elif metric_name in data['other']:
+                data['other'][metric_name].append((epoch, metric_value))
+                std_data['other'][metric_name].append((epoch, std_value))
+            continue
+        
+        avg_metric_match = avg_metric_pattern.match(line)
+        if avg_metric_match:
+            avg_metric_name = f'Metric avg {avg_metric_match.group(1)}'
+            avg_metric_value = float(avg_metric_match.group(2))
+            data['avg'][avg_metric_name].append((epoch, avg_metric_value))
+
+for category, metrics in data.items():
+    for key, values in metrics.items():
+        category_path = f'{category}/{key.replace(" ", "_").lower()}'
+        for epoch, value in values:
+            writer.add_scalar(f'{category_path}', value, epoch)
+
+for category, metrics in std_data.items():
+    for key, values in metrics.items():
+        category_path = f'{category}/{key.replace(" ", "_").lower()}_std'
+        for epoch, std in values:
+            writer.add_scalar(f'{category_path}', std, epoch)
+
+writer.close()
+os.system('tensorboard --logdir=runs')

train.log

@@ -0,0 +1,2431 @@
+Train epoch: 0 Learning rate: 4e-05
+Training loss: 0.112203
+Instr dry sdr: 9.1842 (Std: 5.0694)
+Instr dry l1_freq: 43.0502 (Std: 16.4433)
+Instr dry si_sdr: 6.6879 (Std: 9.3848)
+Instr other sdr: 2.7113 (Std: 2.9820)
+Instr other l1_freq: 42.2600 (Std: 13.8038)
+Instr other si_sdr: 0.9734 (Std: 2.9438)
+Metric avg sdr        : 5.9478
+Metric avg l1_freq    : 42.6551
+Metric avg si_sdr     : 3.8307
+Train epoch: 1 Learning rate: 4e-05
+Training loss: 0.108346
+Instr dry sdr: 9.8077 (Std: 5.0427)
+Instr dry l1_freq: 45.2016 (Std: 16.0011)
+Instr dry si_sdr: 7.8796 (Std: 8.4374)
+Instr other sdr: 3.2853 (Std: 3.0210)
+Instr other l1_freq: 44.2322 (Std: 13.4866)
+Instr other si_sdr: 1.6467 (Std: 3.0609)
+Metric avg sdr        : 6.5465
+Metric avg l1_freq    : 44.7169
+Metric avg si_sdr     : 4.7632
+Train epoch: 2 Learning rate: 4e-05
+Training loss: 0.111557
+Instr dry sdr: 8.6600 (Std: 5.2673)
+Instr dry l1_freq: 40.4967 (Std: 16.3782)
+Instr dry si_sdr: 5.1406 (Std: 11.2339)
+Instr other sdr: 2.2686 (Std: 3.3155)
+Instr other l1_freq: 40.7998 (Std: 14.0537)
+Instr other si_sdr: 0.5386 (Std: 3.2345)
+Metric avg sdr        : 5.4643
+Metric avg l1_freq    : 40.6482
+Metric avg si_sdr     : 2.8396
+Train epoch: 3 Learning rate: 4e-05
+Training loss: 0.104671
+Instr dry sdr: 10.5112 (Std: 4.7450)
+Instr dry l1_freq: 47.0243 (Std: 15.3385)
+Instr dry si_sdr: 9.2583 (Std: 7.0059)
+Instr other sdr: 3.9533 (Std: 2.9623)
+Instr other l1_freq: 45.7660 (Std: 13.4354)
+Instr other si_sdr: 2.4055 (Std: 3.0344)
+Metric avg sdr        : 7.2322
+Metric avg l1_freq    : 46.3951
+Metric avg si_sdr     : 5.8319
+Train epoch: 4 Learning rate: 4e-05
+Training loss: 0.108527
+Instr dry sdr: 10.6624 (Std: 4.7885)
+Instr dry l1_freq: 47.5591 (Std: 15.3929)
+Instr dry si_sdr: 9.3465 (Std: 7.2948)
+Instr other sdr: 4.1154 (Std: 3.0104)
+Instr other l1_freq: 45.9004 (Std: 13.4133)
+Instr other si_sdr: 2.6202 (Std: 3.0885)
+Metric avg sdr        : 7.3889
+Metric avg l1_freq    : 46.7298
+Metric avg si_sdr     : 5.9833
+Train epoch: 5 Learning rate: 4e-05
+Training loss: 0.107057
+Instr dry sdr: 11.0292 (Std: 4.6336)
+Instr dry l1_freq: 48.4740 (Std: 15.0574)
+Instr dry si_sdr: 9.9518 (Std: 6.6424)
+Instr other sdr: 4.4880 (Std: 2.9169)
+Instr other l1_freq: 46.8940 (Std: 13.1882)
+Instr other si_sdr: 3.0556 (Std: 3.0106)
+Metric avg sdr        : 7.7586
+Metric avg l1_freq    : 47.6840
+Metric avg si_sdr     : 6.5037
+Train epoch: 6 Learning rate: 4e-05
+Training loss: 0.102628
+Instr dry sdr: 10.4956 (Std: 5.0565)
+Instr dry l1_freq: 47.0258 (Std: 15.6716)
+Instr dry si_sdr: 8.7730 (Std: 8.3461)
+Instr other sdr: 4.0236 (Std: 3.1916)
+Instr other l1_freq: 45.9433 (Std: 13.4968)
+Instr other si_sdr: 2.6168 (Std: 3.2038)
+Metric avg sdr        : 7.2596
+Metric avg l1_freq    : 46.4846
+Metric avg si_sdr     : 5.6949
+Train epoch: 7 Learning rate: 4e-05
+Training loss: 0.102433
+Instr dry sdr: 10.4234 (Std: 5.2507)
+Instr dry l1_freq: 46.5551 (Std: 16.1208)
+Instr dry si_sdr: 8.2495 (Std: 9.4586)
+Instr other sdr: 3.9662 (Std: 3.3640)
+Instr other l1_freq: 45.5177 (Std: 13.8393)
+Instr other si_sdr: 2.6240 (Std: 3.3432)
+Metric avg sdr        : 7.1948
+Metric avg l1_freq    : 46.0364
+Metric avg si_sdr     : 5.4368
+Train epoch: 8 Learning rate: 4e-05
+Training loss: 0.102206
+Instr dry sdr: 11.2823 (Std: 4.6485)
+Instr dry l1_freq: 49.1632 (Std: 14.9530)
+Instr dry si_sdr: 10.2208 (Std: 6.6984)
+Instr other sdr: 4.7831 (Std: 2.9732)
+Instr other l1_freq: 47.7291 (Std: 13.1676)
+Instr other si_sdr: 3.4409 (Std: 3.0674)
+Metric avg sdr        : 8.0327
+Metric avg l1_freq    : 48.4461
+Metric avg si_sdr     : 6.8308
+Train epoch: 9 Learning rate: 4e-05
+Training loss: 0.102105
+Instr dry sdr: 9.8860 (Std: 5.7882)
+Instr dry l1_freq: 44.9209 (Std: 17.4682)
+Instr dry si_sdr: 6.8763 (Std: 10.9794)
+Instr other sdr: 3.4941 (Std: 3.7512)
+Instr other l1_freq: 44.9048 (Std: 14.8870)
+Instr other si_sdr: 2.3025 (Std: 3.5580)
+Metric avg sdr        : 6.6900
+Metric avg l1_freq    : 44.9128
+Metric avg si_sdr     : 4.5894
+Train epoch: 10 Learning rate: 4e-05
+Training loss: 0.105466
+Instr dry sdr: 10.6825 (Std: 5.4309)
+Instr dry l1_freq: 47.1887 (Std: 16.3474)
+Instr dry si_sdr: 8.5463 (Std: 9.5558)
+Instr other sdr: 4.2599 (Std: 3.5437)
+Instr other l1_freq: 46.4425 (Std: 13.9931)
+Instr other si_sdr: 3.0562 (Std: 3.5099)
+Metric avg sdr        : 7.4712
+Metric avg l1_freq    : 46.8156
+Metric avg si_sdr     : 5.8013
+Train epoch: 11 Learning rate: 4e-05
+Training loss: 0.102414
+Instr dry sdr: 9.6486 (Std: 5.9472)
+Instr dry l1_freq: 44.1544 (Std: 18.0469)
+Instr dry si_sdr: 6.1325 (Std: 11.8517)
+Instr other sdr: 3.3058 (Std: 3.8984)
+Instr other l1_freq: 43.9748 (Std: 15.1864)
+Instr other si_sdr: 2.1583 (Std: 3.6656)
+Metric avg sdr        : 6.4772
+Metric avg l1_freq    : 44.0646
+Metric avg si_sdr     : 4.1454
+Train epoch: 12 Learning rate: 3.8e-05
+Training loss: 0.102746
+Instr dry sdr: 11.2203 (Std: 4.7064)
+Instr dry l1_freq: 49.1167 (Std: 15.4703)
+Instr dry si_sdr: 9.9747 (Std: 7.3762)
+Instr other sdr: 4.8413 (Std: 3.0495)
+Instr other l1_freq: 47.1270 (Std: 13.4432)
+Instr other si_sdr: 3.5202 (Std: 3.1601)
+Metric avg sdr        : 8.0308
+Metric avg l1_freq    : 48.1219
+Metric avg si_sdr     : 6.7475
+Train epoch: 13 Learning rate: 3.8e-05
+Training loss: 0.098055
+Instr dry sdr: 11.4479 (Std: 4.6584)
+Instr dry l1_freq: 49.8237 (Std: 15.2150)
+Instr dry si_sdr: 10.2828 (Std: 7.2318)
+Instr other sdr: 5.0567 (Std: 3.0666)
+Instr other l1_freq: 47.9391 (Std: 13.2528)
+Instr other si_sdr: 3.8100 (Std: 3.1556)
+Metric avg sdr        : 8.2523
+Metric avg l1_freq    : 48.8814
+Metric avg si_sdr     : 7.0464
+Train epoch: 14 Learning rate: 3.8e-05
+Training loss: 0.098851
+Instr dry sdr: 11.2437 (Std: 4.4635)
+Instr dry l1_freq: 48.9190 (Std: 14.9174)
+Instr dry si_sdr: 10.0969 (Std: 7.1745)
+Instr other sdr: 4.8748 (Std: 2.9083)
+Instr other l1_freq: 47.2522 (Std: 13.2537)
+Instr other si_sdr: 3.4444 (Std: 3.1525)
+Metric avg sdr        : 8.0592
+Metric avg l1_freq    : 48.0856
+Metric avg si_sdr     : 6.7706
+Train epoch: 15 Learning rate: 3.8e-05
+Training loss: 0.100223
+Instr dry sdr: 11.8901 (Std: 3.8317)
+Instr dry l1_freq: 51.2161 (Std: 12.9691)
+Instr dry si_sdr: 11.2922 (Std: 5.1277)
+Instr other sdr: 5.5019 (Std: 2.2995)
+Instr other l1_freq: 48.7933 (Std: 11.9829)
+Instr other si_sdr: 4.1441 (Std: 2.6947)
+Metric avg sdr        : 8.6960
+Metric avg l1_freq    : 50.0047
+Metric avg si_sdr     : 7.7181
+Train epoch: 16 Learning rate: 3.8e-05
+Training loss: 0.104321
+Instr dry sdr: 11.9911 (Std: 3.9050)
+Instr dry l1_freq: 51.5090 (Std: 13.0993)
+Instr dry si_sdr: 11.3194 (Std: 5.4409)
+Instr other sdr: 5.5892 (Std: 2.4072)
+Instr other l1_freq: 49.2916 (Std: 11.9865)
+Instr other si_sdr: 4.2758 (Std: 2.7573)
+Metric avg sdr        : 8.7901
+Metric avg l1_freq    : 50.4003
+Metric avg si_sdr     : 7.7976
+Train epoch: 17 Learning rate: 3.8e-05
+Training loss: 0.101089
+Instr dry sdr: 11.3998 (Std: 4.4243)
+Instr dry l1_freq: 49.5020 (Std: 14.6672)
+Instr dry si_sdr: 10.2264 (Std: 7.2563)
+Instr other sdr: 5.0164 (Std: 2.9508)
+Instr other l1_freq: 47.8112 (Std: 13.1082)
+Instr other si_sdr: 3.6554 (Std: 3.1220)
+Metric avg sdr        : 8.2081
+Metric avg l1_freq    : 48.6566
+Metric avg si_sdr     : 6.9409
+Train epoch: 18 Learning rate: 3.8e-05
+Training loss: 0.104896
+Instr dry sdr: 11.8436 (Std: 4.2132)
+Instr dry l1_freq: 50.8741 (Std: 13.9037)
+Instr dry si_sdr: 10.9560 (Std: 6.3993)
+Instr other sdr: 5.4496 (Std: 2.7765)
+Instr other l1_freq: 49.0518 (Std: 12.5874)
+Instr other si_sdr: 4.1728 (Std: 2.9902)
+Metric avg sdr        : 8.6466
+Metric avg l1_freq    : 49.9630
+Metric avg si_sdr     : 7.5644
+Train epoch: 19 Learning rate: 3.8e-05
+Training loss: 0.102872
+Instr dry sdr: 11.6119 (Std: 4.4405)
+Instr dry l1_freq: 50.0832 (Std: 14.4807)
+Instr dry si_sdr: 10.3961 (Std: 7.4146)
+Instr other sdr: 5.2438 (Std: 2.9718)
+Instr other l1_freq: 48.5173 (Std: 12.9634)
+Instr other si_sdr: 3.9460 (Std: 3.1250)
+Metric avg sdr        : 8.4278
+Metric avg l1_freq    : 49.3003
+Metric avg si_sdr     : 7.1711
+Train epoch: 20 Learning rate: 3.61e-05
+Training loss: 0.103917
+Instr dry sdr: 11.8600 (Std: 4.3186)
+Instr dry l1_freq: 50.7067 (Std: 14.1043)
+Instr dry si_sdr: 10.8580 (Std: 6.8196)
+Instr other sdr: 5.4763 (Std: 2.8551)
+Instr other l1_freq: 49.0513 (Std: 12.7018)
+Instr other si_sdr: 4.2312 (Std: 3.0315)
+Metric avg sdr        : 8.6681
+Metric avg l1_freq    : 49.8790
+Metric avg si_sdr     : 7.5446
+Train epoch: 21 Learning rate: 3.61e-05
+Training loss: 0.099953
+Instr dry sdr: 11.6488 (Std: 4.4892)
+Instr dry l1_freq: 50.1608 (Std: 14.5906)
+Instr dry si_sdr: 10.4241 (Std: 7.4959)
+Instr other sdr: 5.2680 (Std: 2.9869)
+Instr other l1_freq: 48.7911 (Std: 12.9553)
+Instr other si_sdr: 3.9999 (Std: 3.1246)
+Metric avg sdr        : 8.4584
+Metric avg l1_freq    : 49.4760
+Metric avg si_sdr     : 7.2120
+Train epoch: 22 Learning rate: 3.61e-05
+Training loss: 0.106623
+Instr dry sdr: 11.4431 (Std: 4.5723)
+Instr dry l1_freq: 49.5066 (Std: 14.8685)
+Instr dry si_sdr: 10.0020 (Std: 8.1887)
+Instr other sdr: 5.0968 (Std: 3.0595)
+Instr other l1_freq: 48.0954 (Std: 13.1793)
+Instr other si_sdr: 3.8148 (Std: 3.1874)
+Metric avg sdr        : 8.2699
+Metric avg l1_freq    : 48.8010
+Metric avg si_sdr     : 6.9084
+Train epoch: 23 Learning rate: 3.4295e-05
+Training loss: 0.102432
+Instr dry sdr: 11.7803 (Std: 4.5411)
+Instr dry l1_freq: 50.1692 (Std: 14.6833)
+Instr dry si_sdr: 10.4433 (Std: 7.9273)
+Instr other sdr: 5.4089 (Std: 3.0554)
+Instr other l1_freq: 48.6791 (Std: 13.1322)
+Instr other si_sdr: 4.2015 (Std: 3.1739)
+Metric avg sdr        : 8.5946
+Metric avg l1_freq    : 49.4242
+Metric avg si_sdr     : 7.3224
+Train epoch: 24 Learning rate: 3.4295e-05
+Training loss: 0.099989
+Instr dry sdr: 11.8416 (Std: 4.5566)
+Instr dry l1_freq: 50.3986 (Std: 14.6825)
+Instr dry si_sdr: 10.4740 (Std: 8.0559)
+Instr other sdr: 5.4663 (Std: 3.0807)
+Instr other l1_freq: 49.1233 (Std: 13.1509)
+Instr other si_sdr: 4.2740 (Std: 3.1957)
+Metric avg sdr        : 8.6540
+Metric avg l1_freq    : 49.7609
+Metric avg si_sdr     : 7.3740
+Train epoch: 25 Learning rate: 3.4295e-05
+Training loss: 0.098635
+Instr dry sdr: 11.9577 (Std: 4.5334)
+Instr dry l1_freq: 51.0521 (Std: 14.5271)
+Instr dry si_sdr: 10.8045 (Std: 7.3315)
+Instr other sdr: 5.5823 (Std: 3.0608)
+Instr other l1_freq: 49.4446 (Std: 12.9467)
+Instr other si_sdr: 4.4169 (Std: 3.1841)
+Metric avg sdr        : 8.7700
+Metric avg l1_freq    : 50.2483
+Metric avg si_sdr     : 7.6107
+Train epoch: 26 Learning rate: 3.258025e-05
+Training loss: 0.099137
+Instr dry sdr: 11.9302 (Std: 4.6017)
+Instr dry l1_freq: 50.8494 (Std: 14.8073)
+Instr dry si_sdr: 10.5274 (Std: 8.1764)
+Instr other sdr: 5.5601 (Std: 3.1095)
+Instr other l1_freq: 49.3405 (Std: 13.1348)
+Instr other si_sdr: 4.4060 (Std: 3.2139)
+Metric avg sdr        : 8.7451
+Metric avg l1_freq    : 50.0949
+Metric avg si_sdr     : 7.4667
+Train epoch: 27 Learning rate: 3.258025e-05
+Training loss: 0.097129
+Instr dry sdr: 11.8247 (Std: 4.5460)
+Instr dry l1_freq: 50.5849 (Std: 14.6852)
+Instr dry si_sdr: 10.4771 (Std: 7.9980)
+Instr other sdr: 5.4648 (Std: 3.0762)
+Instr other l1_freq: 48.8602 (Std: 13.0388)
+Instr other si_sdr: 4.2713 (Std: 3.1981)
+Metric avg sdr        : 8.6448
+Metric avg l1_freq    : 49.7225
+Metric avg si_sdr     : 7.3742
+Train epoch: 28 Learning rate: 3.258025e-05
+Training loss: 0.099773
+Instr dry sdr: 11.9798 (Std: 4.5750)
+Instr dry l1_freq: 51.0790 (Std: 14.6501)
+Instr dry si_sdr: 10.6954 (Std: 7.7941)
+Instr other sdr: 5.6008 (Std: 3.0957)
+Instr other l1_freq: 49.4151 (Std: 13.0527)
+Instr other si_sdr: 4.4569 (Std: 3.1976)
+Metric avg sdr        : 8.7903
+Metric avg l1_freq    : 50.2470
+Metric avg si_sdr     : 7.5762
+Train epoch: 29 Learning rate: 3.09512375e-05
+Training loss: 0.099705
+Instr dry sdr: 11.9371 (Std: 4.6418)
+Instr dry l1_freq: 51.0463 (Std: 14.8174)
+Instr dry si_sdr: 10.5877 (Std: 7.9657)
+Instr other sdr: 5.5785 (Std: 3.1468)
+Instr other l1_freq: 49.4233 (Std: 13.1175)
+Instr other si_sdr: 4.4452 (Std: 3.2448)
+Metric avg sdr        : 8.7578
+Metric avg l1_freq    : 50.2348
+Metric avg si_sdr     : 7.5165
+Train epoch: 30 Learning rate: 3.09512375e-05
+Training loss: 0.101415
+Instr dry sdr: 12.1884 (Std: 4.4321)
+Instr dry l1_freq: 51.4162 (Std: 14.2252)
+Instr dry si_sdr: 11.1747 (Std: 6.8448)
+Instr other sdr: 5.8140 (Std: 3.0305)
+Instr other l1_freq: 50.1628 (Std: 12.9061)
+Instr other si_sdr: 4.6854 (Std: 3.1503)
+Metric avg sdr        : 9.0012
+Metric avg l1_freq    : 50.7895
+Metric avg si_sdr     : 7.9300
+Train epoch: 31 Learning rate: 3.09512375e-05
+Training loss: 0.102380
+Instr dry sdr: 12.2048 (Std: 4.4409)
+Instr dry l1_freq: 51.5894 (Std: 14.3102)
+Instr dry si_sdr: 11.1695 (Std: 7.0154)
+Instr other sdr: 5.8346 (Std: 3.0329)
+Instr other l1_freq: 50.0733 (Std: 12.9218)
+Instr other si_sdr: 4.7251 (Std: 3.1519)
+Metric avg sdr        : 9.0197
+Metric avg l1_freq    : 50.8314
+Metric avg si_sdr     : 7.9473
+Train epoch: 32 Learning rate: 3.09512375e-05
+Training loss: 0.101785
+Instr dry sdr: 12.1684 (Std: 4.5522)
+Instr dry l1_freq: 51.4581 (Std: 14.5296)
+Instr dry si_sdr: 11.0002 (Std: 7.4294)
+Instr other sdr: 5.8010 (Std: 3.0979)
+Instr other l1_freq: 49.9899 (Std: 13.0052)
+Instr other si_sdr: 4.7016 (Std: 3.2061)
+Metric avg sdr        : 8.9847
+Metric avg l1_freq    : 50.7240
+Metric avg si_sdr     : 7.8509
+Train epoch: 33 Learning rate: 3.09512375e-05
+Training loss: 0.100284
+Instr dry sdr: 11.9117 (Std: 4.7139)
+Instr dry l1_freq: 50.5437 (Std: 14.9248)
+Instr dry si_sdr: 10.4955 (Std: 8.2177)
+Instr other sdr: 5.5665 (Std: 3.1587)
+Instr other l1_freq: 49.5938 (Std: 13.3054)
+Instr other si_sdr: 4.4402 (Std: 3.2527)
+Metric avg sdr        : 8.7391
+Metric avg l1_freq    : 50.0688
+Metric avg si_sdr     : 7.4679
+Train epoch: 34 Learning rate: 3.09512375e-05
+Training loss: 0.098834
+Instr dry sdr: 11.8616 (Std: 4.6685)
+Instr dry l1_freq: 50.6035 (Std: 14.8479)
+Instr dry si_sdr: 10.4479 (Std: 8.1880)
+Instr other sdr: 5.5394 (Std: 3.1456)
+Instr other l1_freq: 49.5593 (Std: 13.2399)
+Instr other si_sdr: 4.3980 (Std: 3.2515)
+Metric avg sdr        : 8.7005
+Metric avg l1_freq    : 50.0814
+Metric avg si_sdr     : 7.4229
+Train epoch: 35 Learning rate: 2.9403675625e-05
+Training loss: 0.103044
+Instr dry sdr: 12.0009 (Std: 4.6071)
+Instr dry l1_freq: 51.2387 (Std: 14.6381)
+Instr dry si_sdr: 10.7337 (Std: 7.7206)
+Instr other sdr: 5.6760 (Std: 3.1386)
+Instr other l1_freq: 49.7333 (Std: 13.0192)
+Instr other si_sdr: 4.5561 (Std: 3.2552)
+Metric avg sdr        : 8.8384
+Metric avg l1_freq    : 50.4860
+Metric avg si_sdr     : 7.6449
+Train epoch: 36 Learning rate: 2.9403675625e-05
+Training loss: 0.095640
+Instr dry sdr: 12.1978 (Std: 4.6388)
+Instr dry l1_freq: 51.5424 (Std: 14.6671)
+Instr dry si_sdr: 10.9504 (Std: 7.7064)
+Instr other sdr: 5.8538 (Std: 3.1690)
+Instr other l1_freq: 50.2770 (Std: 13.1821)
+Instr other si_sdr: 4.7852 (Std: 3.2577)
+Metric avg sdr        : 9.0258
+Metric avg l1_freq    : 50.9097
+Metric avg si_sdr     : 7.8678
+Train epoch: 37 Learning rate: 2.9403675625e-05
+Training loss: 0.097300
+Instr dry sdr: 12.1350 (Std: 4.7538)
+Instr dry l1_freq: 51.1537 (Std: 14.8995)
+Instr dry si_sdr: 10.6954 (Std: 8.3349)
+Instr other sdr: 5.7904 (Std: 3.2381)
+Instr other l1_freq: 50.0719 (Std: 13.2881)
+Instr other si_sdr: 4.7196 (Std: 3.3284)
+Metric avg sdr        : 8.9627
+Metric avg l1_freq    : 50.6128
+Metric avg si_sdr     : 7.7075
+Train epoch: 38 Learning rate: 2.9403675625e-05
+Training loss: 0.097327
+Instr dry sdr: 12.0688 (Std: 4.8227)
+Instr dry l1_freq: 50.9813 (Std: 15.0747)
+Instr dry si_sdr: 10.5224 (Std: 8.6736)
+Instr other sdr: 5.7242 (Std: 3.2753)
+Instr other l1_freq: 50.0266 (Std: 13.4201)
+Instr other si_sdr: 4.6608 (Std: 3.3507)
+Metric avg sdr        : 8.8965
+Metric avg l1_freq    : 50.5040
+Metric avg si_sdr     : 7.5916
+Train epoch: 39 Learning rate: 2.9403675625e-05
+Training loss: 0.100668
+Instr dry sdr: 11.8969 (Std: 4.8789)
+Instr dry l1_freq: 50.1775 (Std: 15.0496)
+Instr dry si_sdr: 10.4221 (Std: 8.4724)
+Instr other sdr: 5.5662 (Std: 3.2807)
+Instr other l1_freq: 49.3151 (Std: 13.3768)
+Instr other si_sdr: 4.4702 (Std: 3.3781)
+Metric avg sdr        : 8.7316
+Metric avg l1_freq    : 49.7463
+Metric avg si_sdr     : 7.4462
+Train epoch: 40 Learning rate: 2.7933491843749998e-05
+Training loss: 0.096047
+Instr dry sdr: 11.7411 (Std: 5.1290)
+Instr dry l1_freq: 49.9637 (Std: 15.4402)
+Instr dry si_sdr: 10.1175 (Std: 8.8404)
+Instr other sdr: 5.4359 (Std: 3.4525)
+Instr other l1_freq: 49.2590 (Std: 13.6127)
+Instr other si_sdr: 4.3865 (Std: 3.5094)
+Metric avg sdr        : 8.5885
+Metric avg l1_freq    : 49.6114
+Metric avg si_sdr     : 7.2520
+Train epoch: 41 Learning rate: 2.7933491843749998e-05
+Training loss: 0.095904
+Instr dry sdr: 12.2122 (Std: 4.6289)
+Instr dry l1_freq: 51.6605 (Std: 14.6610)
+Instr dry si_sdr: 11.2688 (Std: 6.6841)
+Instr other sdr: 5.8853 (Std: 3.1060)
+Instr other l1_freq: 50.0406 (Std: 13.1129)
+Instr other si_sdr: 4.8181 (Std: 3.2378)
+Metric avg sdr        : 9.0487
+Metric avg l1_freq    : 50.8506
+Metric avg si_sdr     : 8.0434
+Train epoch: 42 Learning rate: 2.7933491843749998e-05
+Training loss: 0.100599
+Instr dry sdr: 12.1917 (Std: 4.6540)
+Instr dry l1_freq: 51.6310 (Std: 14.7739)
+Instr dry si_sdr: 11.0723 (Std: 7.3049)
+Instr other sdr: 5.8670 (Std: 3.1752)
+Instr other l1_freq: 50.0911 (Std: 13.2149)
+Instr other si_sdr: 4.8079 (Std: 3.2820)
+Metric avg sdr        : 9.0293
+Metric avg l1_freq    : 50.8610
+Metric avg si_sdr     : 7.9401
+Train epoch: 43 Learning rate: 2.7933491843749998e-05
+Training loss: 0.098432
+Instr dry sdr: 12.2574 (Std: 4.6928)
+Instr dry l1_freq: 51.7157 (Std: 14.8442)
+Instr dry si_sdr: 11.0937 (Std: 7.4824)
+Instr other sdr: 5.9243 (Std: 3.2065)
+Instr other l1_freq: 50.3579 (Std: 13.3033)
+Instr other si_sdr: 4.8882 (Std: 3.3074)
+Metric avg sdr        : 9.0909
+Metric avg l1_freq    : 51.0368
+Metric avg si_sdr     : 7.9909
+Train epoch: 44 Learning rate: 2.7933491843749998e-05
+Training loss: 0.099358
+Instr dry sdr: 12.1303 (Std: 4.8594)
+Instr dry l1_freq: 51.3296 (Std: 15.1673)
+Instr dry si_sdr: 10.7959 (Std: 8.0152)
+Instr other sdr: 5.8136 (Std: 3.3279)
+Instr other l1_freq: 50.1510 (Std: 13.4426)
+Instr other si_sdr: 4.7747 (Std: 3.4179)
+Metric avg sdr        : 8.9719
+Metric avg l1_freq    : 50.7403
+Metric avg si_sdr     : 7.7853
+Train epoch: 45 Learning rate: 2.7933491843749998e-05
+Training loss: 0.094929
+Instr dry sdr: 12.0053 (Std: 4.9333)
+Instr dry l1_freq: 51.0921 (Std: 15.2064)
+Instr dry si_sdr: 10.6287 (Std: 8.1391)
+Instr other sdr: 5.6823 (Std: 3.3632)
+Instr other l1_freq: 49.9480 (Std: 13.4875)
+Instr other si_sdr: 4.6250 (Std: 3.4695)
+Metric avg sdr        : 8.8438
+Metric avg l1_freq    : 50.5201
+Metric avg si_sdr     : 7.6269
+Train epoch: 46 Learning rate: 2.7933491843749998e-05
+Training loss: 0.094544
+Instr dry sdr: 12.2630 (Std: 4.7134)
+Instr dry l1_freq: 51.8582 (Std: 14.7762)
+Instr dry si_sdr: 11.2257 (Std: 7.0517)
+Instr other sdr: 5.9420 (Std: 3.2099)
+Instr other l1_freq: 50.4802 (Std: 13.1570)
+Instr other si_sdr: 4.9045 (Std: 3.3225)
+Metric avg sdr        : 9.1025
+Metric avg l1_freq    : 51.1692
+Metric avg si_sdr     : 8.0651
+Train epoch: 47 Learning rate: 2.7933491843749998e-05
+Training loss: 0.100300
+Instr dry sdr: 12.5258 (Std: 4.2445)
+Instr dry l1_freq: 52.7581 (Std: 13.7617)
+Instr dry si_sdr: 11.9621 (Std: 5.3200)
+Instr other sdr: 6.2022 (Std: 2.8190)
+Instr other l1_freq: 50.9424 (Std: 12.3721)
+Instr other si_sdr: 5.1532 (Std: 3.0129)
+Metric avg sdr        : 9.3640
+Metric avg l1_freq    : 51.8502
+Metric avg si_sdr     : 8.5576
+Train epoch: 48 Learning rate: 2.7933491843749998e-05
+Training loss: 0.095596
+Instr dry sdr: 12.4497 (Std: 4.4619)
+Instr dry l1_freq: 52.3584 (Std: 14.2714)
+Instr dry si_sdr: 11.6337 (Std: 6.2797)
+Instr other sdr: 6.1288 (Std: 3.0325)
+Instr other l1_freq: 50.8711 (Std: 12.8454)
+Instr other si_sdr: 5.0948 (Std: 3.1700)
+Metric avg sdr        : 9.2892
+Metric avg l1_freq    : 51.6147
+Metric avg si_sdr     : 8.3643
+Train epoch: 49 Learning rate: 2.7933491843749998e-05
+Training loss: 0.103359
+Instr dry sdr: 12.4709 (Std: 4.3961)
+Instr dry l1_freq: 51.9473 (Std: 14.2387)
+Instr dry si_sdr: 11.8527 (Std: 5.5742)
+Instr other sdr: 6.1567 (Std: 2.9016)
+Instr other l1_freq: 50.5832 (Std: 12.7367)
+Instr other si_sdr: 5.1042 (Std: 3.1088)
+Metric avg sdr        : 9.3138
+Metric avg l1_freq    : 51.2652
+Metric avg si_sdr     : 8.4785
+Train epoch: 50 Learning rate: 2.7933491843749998e-05
+Training loss: 0.097140
+Instr dry sdr: 12.5480 (Std: 4.4551)
+Instr dry l1_freq: 52.4209 (Std: 14.3051)
+Instr dry si_sdr: 11.8755 (Std: 5.8093)
+Instr other sdr: 6.2244 (Std: 2.9714)
+Instr other l1_freq: 50.8542 (Std: 12.8472)
+Instr other si_sdr: 5.2055 (Std: 3.1398)
+Metric avg sdr        : 9.3862
+Metric avg l1_freq    : 51.6375
+Metric avg si_sdr     : 8.5405
+Train epoch: 51 Learning rate: 2.7933491843749998e-05
+Training loss: 0.095402
+Instr dry sdr: 12.4629 (Std: 4.4734)
+Instr dry l1_freq: 52.3328 (Std: 14.3300)
+Instr dry si_sdr: 11.7317 (Std: 6.0010)
+Instr other sdr: 6.1470 (Std: 3.0206)
+Instr other l1_freq: 50.7004 (Std: 12.8662)
+Instr other si_sdr: 5.1226 (Std: 3.1724)
+Metric avg sdr        : 9.3050
+Metric avg l1_freq    : 51.5166
+Metric avg si_sdr     : 8.4272
+Train epoch: 52 Learning rate: 2.7933491843749998e-05
+Training loss: 0.099080
+Instr dry sdr: 12.6029 (Std: 4.4025)
+Instr dry l1_freq: 52.7431 (Std: 14.1114)
+Instr dry si_sdr: 12.0241 (Std: 5.4395)
+Instr other sdr: 6.2833 (Std: 2.9341)
+Instr other l1_freq: 51.1383 (Std: 12.6247)
+Instr other si_sdr: 5.2792 (Std: 3.1178)
+Metric avg sdr        : 9.4431
+Metric avg l1_freq    : 51.9407
+Metric avg si_sdr     : 8.6517
+Train epoch: 53 Learning rate: 2.7933491843749998e-05
+Training loss: 0.094254
+Instr dry sdr: 12.5107 (Std: 4.6218)
+Instr dry l1_freq: 52.4360 (Std: 14.5449)
+Instr dry si_sdr: 11.7284 (Std: 6.2280)
+Instr other sdr: 6.1962 (Std: 3.1480)
+Instr other l1_freq: 50.9403 (Std: 13.0012)
+Instr other si_sdr: 5.2072 (Std: 3.2774)
+Metric avg sdr        : 9.3534
+Metric avg l1_freq    : 51.6882
+Metric avg si_sdr     : 8.4678
+Train epoch: 54 Learning rate: 2.7933491843749998e-05
+Training loss: 0.091159
+Instr dry sdr: 12.0227 (Std: 4.9936)
+Instr dry l1_freq: 51.1259 (Std: 15.4072)
+Instr dry si_sdr: 10.5224 (Std: 8.5369)
+Instr other sdr: 5.7271 (Std: 3.4290)
+Instr other l1_freq: 49.7751 (Std: 13.6606)
+Instr other si_sdr: 4.7132 (Std: 3.4658)
+Metric avg sdr        : 8.8749
+Metric avg l1_freq    : 50.4505
+Metric avg si_sdr     : 7.6178
+Train epoch: 55 Learning rate: 2.7933491843749998e-05
+Training loss: 0.096296
+Instr dry sdr: 12.2970 (Std: 4.8705)
+Instr dry l1_freq: 51.8453 (Std: 15.0951)
+Instr dry si_sdr: 11.0047 (Std: 7.9714)
+Instr other sdr: 5.9926 (Std: 3.3691)
+Instr other l1_freq: 50.5093 (Std: 13.4355)
+Instr other si_sdr: 5.0113 (Std: 3.4300)
+Metric avg sdr        : 9.1448
+Metric avg l1_freq    : 51.1773
+Metric avg si_sdr     : 8.0080
+Train epoch: 56 Learning rate: 2.6536817251562497e-05
+Training loss: 0.094687
+Instr dry sdr: 12.2359 (Std: 5.0098)
+Instr dry l1_freq: 51.4253 (Std: 15.2918)
+Instr dry si_sdr: 10.7536 (Std: 8.5601)
+Instr other sdr: 5.9342 (Std: 3.4720)
+Instr other l1_freq: 50.4779 (Std: 13.6366)
+Instr other si_sdr: 4.9585 (Std: 3.5136)
+Metric avg sdr        : 9.0850
+Metric avg l1_freq    : 50.9516
+Metric avg si_sdr     : 7.8560
+Train epoch: 57 Learning rate: 2.6536817251562497e-05
+Training loss: 0.095657
+Instr dry sdr: 12.2102 (Std: 4.9633)
+Instr dry l1_freq: 51.4960 (Std: 15.2521)
+Instr dry si_sdr: 10.7497 (Std: 8.4845)
+Instr other sdr: 5.9077 (Std: 3.4567)
+Instr other l1_freq: 50.2654 (Std: 13.5850)
+Instr other si_sdr: 4.9244 (Std: 3.4981)
+Metric avg sdr        : 9.0590
+Metric avg l1_freq    : 50.8807
+Metric avg si_sdr     : 7.8371
+Train epoch: 58 Learning rate: 2.6536817251562497e-05
+Training loss: 0.097515
+Instr dry sdr: 12.4264 (Std: 4.8078)
+Instr dry l1_freq: 52.1458 (Std: 14.9872)
+Instr dry si_sdr: 11.3226 (Std: 7.4191)
+Instr other sdr: 6.1070 (Std: 3.3150)
+Instr other l1_freq: 50.8045 (Std: 13.3580)
+Instr other si_sdr: 5.1458 (Std: 3.3906)
+Metric avg sdr        : 9.2667
+Metric avg l1_freq    : 51.4752
+Metric avg si_sdr     : 8.2342
+Train epoch: 59 Learning rate: 2.5209976388984372e-05
+Training loss: 0.097498
+Instr dry sdr: 12.3827 (Std: 4.9430)
+Instr dry l1_freq: 51.7468 (Std: 15.2411)
+Instr dry si_sdr: 10.9553 (Std: 8.4594)
+Instr other sdr: 6.0841 (Std: 3.4534)
+Instr other l1_freq: 50.8139 (Std: 13.6451)
+Instr other si_sdr: 5.1394 (Std: 3.4837)
+Metric avg sdr        : 9.2334
+Metric avg l1_freq    : 51.2803
+Metric avg si_sdr     : 8.0473
+Train epoch: 60 Learning rate: 2.5209976388984372e-05
+Training loss: 0.093099
+Instr dry sdr: 12.2849 (Std: 4.9824)
+Instr dry l1_freq: 51.6414 (Std: 15.1842)
+Instr dry si_sdr: 10.8583 (Std: 8.4044)
+Instr other sdr: 5.9955 (Std: 3.4715)
+Instr other l1_freq: 50.6220 (Std: 13.5627)
+Instr other si_sdr: 5.0373 (Std: 3.5125)
+Metric avg sdr        : 9.1402
+Metric avg l1_freq    : 51.1317
+Metric avg si_sdr     : 7.9478
+Train epoch: 61 Learning rate: 2.5209976388984372e-05
+Training loss: 0.103669
+Instr dry sdr: 12.0979 (Std: 5.1797)
+Instr dry l1_freq: 50.9696 (Std: 15.3880)
+Instr dry si_sdr: 10.4390 (Std: 9.0538)
+Instr other sdr: 5.8103 (Std: 3.6200)
+Instr other l1_freq: 50.1947 (Std: 13.6859)
+Instr other si_sdr: 4.8524 (Std: 3.6527)
+Metric avg sdr        : 8.9541
+Metric avg l1_freq    : 50.5821
+Metric avg si_sdr     : 7.6457
+Train epoch: 62 Learning rate: 2.3949477569535154e-05
+Training loss: 0.092208
+Instr dry sdr: 12.2718 (Std: 5.0631)
+Instr dry l1_freq: 51.3891 (Std: 15.3569)
+Instr dry si_sdr: 10.7125 (Std: 8.8047)
+Instr other sdr: 5.9777 (Std: 3.5298)
+Instr other l1_freq: 50.5797 (Std: 13.7257)
+Instr other si_sdr: 5.0241 (Std: 3.5631)
+Metric avg sdr        : 9.1248
+Metric avg l1_freq    : 50.9844
+Metric avg si_sdr     : 7.8683
+Train epoch: 63 Learning rate: 2.3949477569535154e-05
+Training loss: 0.102014
+Instr dry sdr: 11.9243 (Std: 5.3757)
+Instr dry l1_freq: 50.3253 (Std: 15.8274)
+Instr dry si_sdr: 10.0076 (Std: 9.6708)
+Instr other sdr: 5.6612 (Std: 3.7498)
+Instr other l1_freq: 49.9824 (Std: 13.9572)
+Instr other si_sdr: 4.7142 (Std: 3.7771)
+Metric avg sdr        : 8.7927
+Metric avg l1_freq    : 50.1539
+Metric avg si_sdr     : 7.3609
+Train epoch: 64 Learning rate: 2.3949477569535154e-05
+Training loss: 0.095988
+Instr dry sdr: 12.2540 (Std: 5.0462)
+Instr dry l1_freq: 51.4500 (Std: 15.3783)
+Instr dry si_sdr: 10.7858 (Std: 8.5484)
+Instr other sdr: 5.9716 (Std: 3.5017)
+Instr other l1_freq: 50.5902 (Std: 13.7341)
+Instr other si_sdr: 5.0183 (Std: 3.5460)
+Metric avg sdr        : 9.1128
+Metric avg l1_freq    : 51.0201
+Metric avg si_sdr     : 7.9021
+Train epoch: 65 Learning rate: 2.2752003691058396e-05
+Training loss: 0.098379
+Instr dry sdr: 12.3659 (Std: 5.0193)
+Instr dry l1_freq: 51.6833 (Std: 15.3331)
+Instr dry si_sdr: 10.9391 (Std: 8.4503)
+Instr other sdr: 6.0788 (Std: 3.4828)
+Instr other l1_freq: 50.8337 (Std: 13.6849)
+Instr other si_sdr: 5.1414 (Std: 3.5247)
+Metric avg sdr        : 9.2224
+Metric avg l1_freq    : 51.2585
+Metric avg si_sdr     : 8.0402
+Train epoch: 66 Learning rate: 2.2752003691058396e-05
+Training loss: 0.091182
+Instr dry sdr: 12.5520 (Std: 4.7837)
+Instr dry l1_freq: 52.3609 (Std: 14.9107)
+Instr dry si_sdr: 11.5022 (Std: 7.2267)
+Instr other sdr: 6.2720 (Std: 3.3150)
+Instr other l1_freq: 51.2592 (Std: 13.3255)
+Instr other si_sdr: 5.3416 (Std: 3.3879)
+Metric avg sdr        : 9.4120
+Metric avg l1_freq    : 51.8101
+Metric avg si_sdr     : 8.4219
+Train epoch: 67 Learning rate: 2.2752003691058396e-05
+Training loss: 0.092582
+Instr dry sdr: 12.6093 (Std: 4.8153)
+Instr dry l1_freq: 52.3751 (Std: 15.0178)
+Instr dry si_sdr: 11.5044 (Std: 7.4468)
+Instr other sdr: 6.3197 (Std: 3.3409)
+Instr other l1_freq: 51.4147 (Std: 13.4250)
+Instr other si_sdr: 5.4056 (Std: 3.4002)
+Metric avg sdr        : 9.4645
+Metric avg l1_freq    : 51.8949
+Metric avg si_sdr     : 8.4550
+Train epoch: 68 Learning rate: 2.2752003691058396e-05
+Training loss: 0.095525
+Instr dry sdr: 12.6933 (Std: 4.6196)
+Instr dry l1_freq: 52.7676 (Std: 14.5984)
+Instr dry si_sdr: 11.9203 (Std: 6.2891)
+Instr other sdr: 6.4140 (Std: 3.1507)
+Instr other l1_freq: 51.5851 (Std: 12.9630)
+Instr other si_sdr: 5.4850 (Std: 3.2781)
+Metric avg sdr        : 9.5537
+Metric avg l1_freq    : 52.1764
+Metric avg si_sdr     : 8.7026
+Train epoch: 69 Learning rate: 2.2752003691058396e-05
+Training loss: 0.094700
+Instr dry sdr: 12.6011 (Std: 4.7247)
+Instr dry l1_freq: 52.4801 (Std: 14.7547)
+Instr dry si_sdr: 11.6395 (Std: 6.9502)
+Instr other sdr: 6.3259 (Std: 3.2496)
+Instr other l1_freq: 51.3514 (Std: 13.1609)
+Instr other si_sdr: 5.3912 (Std: 3.3501)
+Metric avg sdr        : 9.4635
+Metric avg l1_freq    : 51.9158
+Metric avg si_sdr     : 8.5153
+Train epoch: 70 Learning rate: 2.2752003691058396e-05
+Training loss: 0.094604
+Instr dry sdr: 12.7777 (Std: 4.4996)
+Instr dry l1_freq: 52.9749 (Std: 14.2646)
+Instr dry si_sdr: 12.0962 (Std: 5.9162)
+Instr other sdr: 6.4962 (Std: 3.0231)
+Instr other l1_freq: 51.8018 (Std: 12.7076)
+Instr other si_sdr: 5.5538 (Std: 3.1770)
+Metric avg sdr        : 9.6370
+Metric avg l1_freq    : 52.3884
+Metric avg si_sdr     : 8.8250
+Train epoch: 71 Learning rate: 2.2752003691058396e-05
+Training loss: 0.097073
+Instr dry sdr: 12.5640 (Std: 4.8496)
+Instr dry l1_freq: 52.2550 (Std: 14.9567)
+Instr dry si_sdr: 11.5595 (Std: 7.0962)
+Instr other sdr: 6.2763 (Std: 3.3485)
+Instr other l1_freq: 51.3199 (Std: 13.3586)
+Instr other si_sdr: 5.3568 (Std: 3.4202)
+Metric avg sdr        : 9.4202
+Metric avg l1_freq    : 51.7875
+Metric avg si_sdr     : 8.4581
+Train epoch: 72 Learning rate: 2.2752003691058396e-05
+Training loss: 0.095600
+Instr dry sdr: 12.8003 (Std: 4.5423)
+Instr dry l1_freq: 52.7600 (Std: 14.3588)
+Instr dry si_sdr: 12.1805 (Std: 5.7041)
+Instr other sdr: 6.5115 (Std: 2.9982)
+Instr other l1_freq: 52.0823 (Std: 12.7863)
+Instr other si_sdr: 5.5840 (Std: 3.1398)
+Metric avg sdr        : 9.6559
+Metric avg l1_freq    : 52.4211
+Metric avg si_sdr     : 8.8822
+Train epoch: 73 Learning rate: 2.2752003691058396e-05
+Training loss: 0.094673
+Instr dry sdr: 12.4820 (Std: 4.9681)
+Instr dry l1_freq: 51.8282 (Std: 15.2062)
+Instr dry si_sdr: 11.2022 (Std: 8.0409)
+Instr other sdr: 6.1976 (Std: 3.4702)
+Instr other l1_freq: 51.1850 (Std: 13.6441)
+Instr other si_sdr: 5.2832 (Std: 3.5149)
+Metric avg sdr        : 9.3398
+Metric avg l1_freq    : 51.5066
+Metric avg si_sdr     : 8.2427
+Train epoch: 74 Learning rate: 2.2752003691058396e-05
+Training loss: 0.098970
+Instr dry sdr: 13.0093 (Std: 4.1357)
+Instr dry l1_freq: 53.5719 (Std: 13.3422)
+Instr dry si_sdr: 12.5743 (Std: 4.8086)
+Instr other sdr: 6.7228 (Std: 2.5965)
+Instr other l1_freq: 52.6082 (Std: 11.9304)
+Instr other si_sdr: 5.7645 (Std: 2.8514)
+Metric avg sdr        : 9.8661
+Metric avg l1_freq    : 53.0901
+Metric avg si_sdr     : 9.1694
+Train epoch: 75 Learning rate: 2.2752003691058396e-05
+Training loss: 0.098243
+Instr dry sdr: 12.3501 (Std: 5.0944)
+Instr dry l1_freq: 51.7057 (Std: 15.2088)
+Instr dry si_sdr: 10.9885 (Std: 8.2387)
+Instr other sdr: 6.0836 (Std: 3.5578)
+Instr other l1_freq: 51.0110 (Std: 13.5603)
+Instr other si_sdr: 5.1709 (Std: 3.5957)
+Metric avg sdr        : 9.2169
+Metric avg l1_freq    : 51.3583
+Metric avg si_sdr     : 8.0797
+Train epoch: 76 Learning rate: 2.2752003691058396e-05
+Training loss: 0.100630
+Instr dry sdr: 12.7034 (Std: 4.6444)
+Instr dry l1_freq: 52.7285 (Std: 14.6490)
+Instr dry si_sdr: 11.8711 (Std: 6.4940)
+Instr other sdr: 6.4306 (Std: 3.1718)
+Instr other l1_freq: 51.6144 (Std: 13.1196)
+Instr other si_sdr: 5.5063 (Std: 3.2832)
+Metric avg sdr        : 9.5670
+Metric avg l1_freq    : 52.1714
+Metric avg si_sdr     : 8.6887
+Train epoch: 77 Learning rate: 2.2752003691058396e-05
+Training loss: 0.096283
+Instr dry sdr: 12.4348 (Std: 5.0475)
+Instr dry l1_freq: 51.7710 (Std: 15.2990)
+Instr dry si_sdr: 11.0244 (Std: 8.4198)
+Instr other sdr: 6.1578 (Std: 3.5390)
+Instr other l1_freq: 50.9328 (Std: 13.6746)
+Instr other si_sdr: 5.2448 (Std: 3.5768)
+Metric avg sdr        : 9.2963
+Metric avg l1_freq    : 51.3519
+Metric avg si_sdr     : 8.1346
+Train epoch: 78 Learning rate: 2.1614403506505474e-05
+Training loss: 0.097837
+Instr dry sdr: 13.0207 (Std: 4.1453)
+Instr dry l1_freq: 53.6459 (Std: 13.1713)
+Instr dry si_sdr: 12.6080 (Std: 4.7312)
+Instr other sdr: 6.7353 (Std: 2.5701)
+Instr other l1_freq: 52.6842 (Std: 11.7093)
+Instr other si_sdr: 5.7647 (Std: 2.8744)
+Metric avg sdr        : 9.8780
+Metric avg l1_freq    : 53.1650
+Metric avg si_sdr     : 9.1863
+Train epoch: 79 Learning rate: 2.1614403506505474e-05
+Training loss: 0.101947
+Instr dry sdr: 12.9332 (Std: 4.3436)
+Instr dry l1_freq: 53.3537 (Std: 13.8190)
+Instr dry si_sdr: 12.4283 (Std: 5.2005)
+Instr other sdr: 6.6543 (Std: 2.8273)
+Instr other l1_freq: 52.4335 (Std: 12.2786)
+Instr other si_sdr: 5.7128 (Std: 3.0416)
+Metric avg sdr        : 9.7937
+Metric avg l1_freq    : 52.8936
+Metric avg si_sdr     : 9.0706
+Train epoch: 80 Learning rate: 2.1614403506505474e-05
+Training loss: 0.099350
+Instr dry sdr: 12.4723 (Std: 5.0149)
+Instr dry l1_freq: 52.1068 (Std: 15.3157)
+Instr dry si_sdr: 11.0805 (Std: 8.3241)
+Instr other sdr: 6.2074 (Std: 3.5594)
+Instr other l1_freq: 51.0360 (Std: 13.6940)
+Instr other si_sdr: 5.3164 (Std: 3.5688)
+Metric avg sdr        : 9.3399
+Metric avg l1_freq    : 51.5714
+Metric avg si_sdr     : 8.1985
+Train epoch: 81 Learning rate: 2.1614403506505474e-05
+Training loss: 0.093635
+Instr dry sdr: 12.7099 (Std: 4.8541)
+Instr dry l1_freq: 52.5968 (Std: 15.0617)
+Instr dry si_sdr: 11.8017 (Std: 6.8042)
+Instr other sdr: 6.4319 (Std: 3.3872)
+Instr other l1_freq: 51.6630 (Std: 13.4759)
+Instr other si_sdr: 5.5562 (Std: 3.4348)
+Metric avg sdr        : 9.5709
+Metric avg l1_freq    : 52.1299
+Metric avg si_sdr     : 8.6790
+Train epoch: 82 Learning rate: 2.05336833311802e-05
+Training loss: 0.096353
+Instr dry sdr: 12.9787 (Std: 4.3767)
+Instr dry l1_freq: 53.1769 (Std: 14.0526)
+Instr dry si_sdr: 12.4865 (Std: 5.1844)
+Instr other sdr: 6.6993 (Std: 2.8520)
+Instr other l1_freq: 52.2443 (Std: 12.6081)
+Instr other si_sdr: 5.7706 (Std: 3.0585)
+Metric avg sdr        : 9.8390
+Metric avg l1_freq    : 52.7106
+Metric avg si_sdr     : 9.1286
+Train epoch: 83 Learning rate: 2.05336833311802e-05
+Training loss: 0.097904
+Instr dry sdr: 12.7420 (Std: 4.8454)
+Instr dry l1_freq: 52.7578 (Std: 15.0835)
+Instr dry si_sdr: 11.7943 (Std: 6.9475)
+Instr other sdr: 6.4755 (Std: 3.3666)
+Instr other l1_freq: 51.7215 (Std: 13.4713)
+Instr other si_sdr: 5.6022 (Std: 3.4287)
+Metric avg sdr        : 9.6088
+Metric avg l1_freq    : 52.2396
+Metric avg si_sdr     : 8.6982
+Train epoch: 84 Learning rate: 2.05336833311802e-05
+Training loss: 0.100543
+Instr dry sdr: 12.6633 (Std: 4.9497)
+Instr dry l1_freq: 52.5279 (Std: 15.2972)
+Instr dry si_sdr: 11.4269 (Std: 7.9240)
+Instr other sdr: 6.3931 (Std: 3.4863)
+Instr other l1_freq: 51.4757 (Std: 13.7058)
+Instr other si_sdr: 5.5262 (Std: 3.5109)
+Metric avg sdr        : 9.5282
+Metric avg l1_freq    : 52.0018
+Metric avg si_sdr     : 8.4766
+Train epoch: 85 Learning rate: 1.9506999164621187e-05
+Training loss: 0.094997
+Instr dry sdr: 12.6071 (Std: 4.9734)
+Instr dry l1_freq: 52.4756 (Std: 15.3162)
+Instr dry si_sdr: 11.3062 (Std: 8.1111)
+Instr other sdr: 6.3386 (Std: 3.5149)
+Instr other l1_freq: 51.1921 (Std: 13.6591)
+Instr other si_sdr: 5.4646 (Std: 3.5364)
+Metric avg sdr        : 9.4728
+Metric avg l1_freq    : 51.8338
+Metric avg si_sdr     : 8.3854
+Train epoch: 86 Learning rate: 1.9506999164621187e-05
+Training loss: 0.088851
+Instr dry sdr: 12.7812 (Std: 4.8315)
+Instr dry l1_freq: 52.8639 (Std: 14.9941)
+Instr dry si_sdr: 11.8750 (Std: 6.8288)
+Instr other sdr: 6.5110 (Std: 3.3512)
+Instr other l1_freq: 51.8905 (Std: 13.4302)
+Instr other si_sdr: 5.6364 (Std: 3.4245)
+Metric avg sdr        : 9.6461
+Metric avg l1_freq    : 52.3772
+Metric avg si_sdr     : 8.7557
+Train epoch: 87 Learning rate: 1.9506999164621187e-05
+Training loss: 0.096688
+Instr dry sdr: 12.6107 (Std: 5.0691)
+Instr dry l1_freq: 52.2532 (Std: 15.5093)
+Instr dry si_sdr: 11.1608 (Std: 8.5200)
+Instr other sdr: 6.3398 (Std: 3.6006)
+Instr other l1_freq: 51.5105 (Std: 13.9688)
+Instr other si_sdr: 5.4765 (Std: 3.5912)
+Metric avg sdr        : 9.4752
+Metric avg l1_freq    : 51.8819
+Metric avg si_sdr     : 8.3187
+Train epoch: 88 Learning rate: 1.8531649206390126e-05
+Training loss: 0.088508
+Instr dry sdr: 12.7883 (Std: 4.8446)
+Instr dry l1_freq: 52.9156 (Std: 15.0524)
+Instr dry si_sdr: 11.9754 (Std: 6.4877)
+Instr other sdr: 6.5203 (Std: 3.3676)
+Instr other l1_freq: 51.7987 (Std: 13.4090)
+Instr other si_sdr: 5.6604 (Std: 3.4343)
+Metric avg sdr        : 9.6543
+Metric avg l1_freq    : 52.3571
+Metric avg si_sdr     : 8.8179
+Train epoch: 89 Learning rate: 1.8531649206390126e-05
+Training loss: 0.093433
+Instr dry sdr: 12.6572 (Std: 4.9947)
+Instr dry l1_freq: 52.4093 (Std: 15.3350)
+Instr dry si_sdr: 11.4798 (Std: 7.6844)
+Instr other sdr: 6.3887 (Std: 3.5282)
+Instr other l1_freq: 51.5581 (Std: 13.7855)
+Instr other si_sdr: 5.5268 (Std: 3.5389)
+Metric avg sdr        : 9.5229
+Metric avg l1_freq    : 51.9837
+Metric avg si_sdr     : 8.5033
+Train epoch: 90 Learning rate: 1.8531649206390126e-05
+Training loss: 0.094809
+Instr dry sdr: 13.1507 (Std: 4.1088)
+Instr dry l1_freq: 53.7715 (Std: 13.3363)
+Instr dry si_sdr: 12.7707 (Std: 4.6134)
+Instr other sdr: 6.8830 (Std: 2.5547)
+Instr other l1_freq: 52.7358 (Std: 11.8587)
+Instr other si_sdr: 5.9448 (Std: 2.8721)
+Metric avg sdr        : 10.0169
+Metric avg l1_freq    : 53.2536
+Metric avg si_sdr     : 9.3577
+Train epoch: 91 Learning rate: 1.8531649206390126e-05
+Training loss: 0.098019
+Instr dry sdr: 12.2693 (Std: 5.2773)
+Instr dry l1_freq: 51.0024 (Std: 15.6507)
+Instr dry si_sdr: 10.1893 (Std: 10.3445)
+Instr other sdr: 6.0155 (Std: 3.7583)
+Instr other l1_freq: 50.2293 (Std: 13.8978)
+Instr other si_sdr: 5.1193 (Std: 3.7885)
+Metric avg sdr        : 9.1424
+Metric avg l1_freq    : 50.6159
+Metric avg si_sdr     : 7.6543
+Train epoch: 92 Learning rate: 1.8531649206390126e-05
+Training loss: 0.095568
+Instr dry sdr: 12.1517 (Std: 5.4645)
+Instr dry l1_freq: 50.5573 (Std: 16.0760)
+Instr dry si_sdr: 9.7243 (Std: 11.3482)
+Instr other sdr: 5.9071 (Std: 3.8700)
+Instr other l1_freq: 50.2320 (Std: 14.1274)
+Instr other si_sdr: 5.0182 (Std: 3.9033)
+Metric avg sdr        : 9.0294
+Metric avg l1_freq    : 50.3946
+Metric avg si_sdr     : 7.3713
+Train epoch: 93 Learning rate: 1.8531649206390126e-05
+Training loss: 0.099267
+Instr dry sdr: 12.3923 (Std: 5.3252)
+Instr dry l1_freq: 51.3353 (Std: 15.7117)
+Instr dry si_sdr: 10.3237 (Std: 10.3709)
+Instr other sdr: 6.1382 (Std: 3.7639)
+Instr other l1_freq: 50.9070 (Std: 14.0275)
+Instr other si_sdr: 5.2708 (Std: 3.7720)
+Metric avg sdr        : 9.2653
+Metric avg l1_freq    : 51.1212
+Metric avg si_sdr     : 7.7973
+Train epoch: 94 Learning rate: 1.760506674607062e-05
+Training loss: 0.098203
+Instr dry sdr: 12.1776 (Std: 5.5474)
+Instr dry l1_freq: 50.2574 (Std: 16.2700)
+Instr dry si_sdr: 9.8557 (Std: 11.1696)
+Instr other sdr: 5.9308 (Std: 3.9415)
+Instr other l1_freq: 50.1638 (Std: 14.2621)
+Instr other si_sdr: 5.0634 (Std: 3.9698)
+Metric avg sdr        : 9.0542
+Metric avg l1_freq    : 50.2106
+Metric avg si_sdr     : 7.4596
+Train epoch: 95 Learning rate: 1.760506674607062e-05
+Training loss: 0.091828
+Instr dry sdr: 12.7154 (Std: 5.0649)
+Instr dry l1_freq: 52.3362 (Std: 15.4446)
+Instr dry si_sdr: 11.3587 (Std: 8.4150)
+Instr other sdr: 6.4484 (Std: 3.5644)
+Instr other l1_freq: 51.5290 (Std: 13.8994)
+Instr other si_sdr: 5.6174 (Std: 3.5561)
+Metric avg sdr        : 9.5819
+Metric avg l1_freq    : 51.9326
+Metric avg si_sdr     : 8.4881
+Train epoch: 96 Learning rate: 1.760506674607062e-05
+Training loss: 0.092210
+Instr dry sdr: 12.5542 (Std: 5.1640)
+Instr dry l1_freq: 51.9249 (Std: 15.4726)
+Instr dry si_sdr: 10.9541 (Std: 9.0623)
+Instr other sdr: 6.2939 (Std: 3.6601)
+Instr other l1_freq: 51.3135 (Std: 13.9318)
+Instr other si_sdr: 5.4368 (Std: 3.6569)
+Metric avg sdr        : 9.4241
+Metric avg l1_freq    : 51.6192
+Metric avg si_sdr     : 8.1955
+Train epoch: 97 Learning rate: 1.6724813408767087e-05
+Training loss: 0.092498
+Instr dry sdr: 12.3693 (Std: 5.3792)
+Instr dry l1_freq: 51.2841 (Std: 15.7054)
+Instr dry si_sdr: 10.3668 (Std: 10.1002)
+Instr other sdr: 6.1246 (Std: 3.8157)
+Instr other l1_freq: 50.8108 (Std: 13.9787)
+Instr other si_sdr: 5.2606 (Std: 3.8357)
+Metric avg sdr        : 9.2470
+Metric avg l1_freq    : 51.0475
+Metric avg si_sdr     : 7.8137
+Train epoch: 98 Learning rate: 1.6724813408767087e-05
+Training loss: 0.096498
+Instr dry sdr: 12.7051 (Std: 5.0507)
+Instr dry l1_freq: 52.3622 (Std: 15.4344)
+Instr dry si_sdr: 11.5561 (Std: 7.6149)
+Instr other sdr: 6.4355 (Std: 3.5707)
+Instr other l1_freq: 51.5607 (Std: 13.8798)
+Instr other si_sdr: 5.6009 (Std: 3.5600)
+Metric avg sdr        : 9.5703
+Metric avg l1_freq    : 51.9614
+Metric avg si_sdr     : 8.5785
+Train epoch: 99 Learning rate: 1.6724813408767087e-05
+Training loss: 0.100907
+Instr dry sdr: 12.7264 (Std: 4.9980)
+Instr dry l1_freq: 52.5787 (Std: 15.3304)
+Instr dry si_sdr: 11.6759 (Std: 7.3167)
+Instr other sdr: 6.4726 (Std: 3.5190)
+Instr other l1_freq: 51.7835 (Std: 13.7848)
+Instr other si_sdr: 5.6326 (Std: 3.5291)
+Metric avg sdr        : 9.5995
+Metric avg l1_freq    : 52.1811
+Metric avg si_sdr     : 8.6543
+Train epoch: 100 Learning rate: 1.5888572738328732e-05
+Training loss: 0.092124
+Instr dry sdr: 12.5440 (Std: 5.1811)
+Instr dry l1_freq: 52.0072 (Std: 15.5140)
+Instr dry si_sdr: 11.0584 (Std: 8.6049)
+Instr other sdr: 6.2961 (Std: 3.6691)
+Instr other l1_freq: 51.5142 (Std: 13.9767)
+Instr other si_sdr: 5.4429 (Std: 3.6636)
+Metric avg sdr        : 9.4201
+Metric avg l1_freq    : 51.7607
+Metric avg si_sdr     : 8.2507
+Train epoch: 101 Learning rate: 1.5888572738328732e-05
+Training loss: 0.090086
+Instr dry sdr: 12.5978 (Std: 5.1102)
+Instr dry l1_freq: 52.2081 (Std: 15.3974)
+Instr dry si_sdr: 11.2203 (Std: 8.3888)
+Instr other sdr: 6.3431 (Std: 3.6186)
+Instr other l1_freq: 51.4018 (Std: 13.8223)
+Instr other si_sdr: 5.4885 (Std: 3.6250)
+Metric avg sdr        : 9.4705
+Metric avg l1_freq    : 51.8049
+Metric avg si_sdr     : 8.3544
+Train epoch: 102 Learning rate: 1.5888572738328732e-05
+Training loss: 0.096567
+Instr dry sdr: 12.7490 (Std: 4.9942)
+Instr dry l1_freq: 52.5952 (Std: 15.2602)
+Instr dry si_sdr: 11.6794 (Std: 7.4370)
+Instr other sdr: 6.4891 (Std: 3.5021)
+Instr other l1_freq: 51.8253 (Std: 13.7127)
+Instr other si_sdr: 5.6486 (Std: 3.5285)
+Metric avg sdr        : 9.6190
+Metric avg l1_freq    : 52.2103
+Metric avg si_sdr     : 8.6640
+Train epoch: 103 Learning rate: 1.5094144101412296e-05
+Training loss: 0.096566
+Instr dry sdr: 12.7887 (Std: 4.9264)
+Instr dry l1_freq: 52.6449 (Std: 15.1826)
+Instr dry si_sdr: 11.9172 (Std: 6.7330)
+Instr other sdr: 6.5313 (Std: 3.4205)
+Instr other l1_freq: 52.0825 (Std: 13.6229)
+Instr other si_sdr: 5.6871 (Std: 3.4548)
+Metric avg sdr        : 9.6600
+Metric avg l1_freq    : 52.3637
+Metric avg si_sdr     : 8.8022
+Train epoch: 104 Learning rate: 1.5094144101412296e-05
+Training loss: 0.093049
+Instr dry sdr: 12.6579 (Std: 5.0226)
+Instr dry l1_freq: 52.3947 (Std: 15.3537)
+Instr dry si_sdr: 11.4864 (Std: 7.7357)
+Instr other sdr: 6.4079 (Std: 3.5368)
+Instr other l1_freq: 51.5370 (Std: 13.7596)
+Instr other si_sdr: 5.5595 (Std: 3.5535)
+Metric avg sdr        : 9.5329
+Metric avg l1_freq    : 51.9658
+Metric avg si_sdr     : 8.5229
+Train epoch: 105 Learning rate: 1.5094144101412296e-05
+Training loss: 0.098858
+Instr dry sdr: 12.6818 (Std: 5.0442)
+Instr dry l1_freq: 52.4730 (Std: 15.3907)
+Instr dry si_sdr: 11.5151 (Std: 7.6824)
+Instr other sdr: 6.4299 (Std: 3.5690)
+Instr other l1_freq: 51.6939 (Std: 13.8234)
+Instr other si_sdr: 5.5873 (Std: 3.5722)
+Metric avg sdr        : 9.5559
+Metric avg l1_freq    : 52.0835
+Metric avg si_sdr     : 8.5512
+Train epoch: 106 Learning rate: 1.433943689634168e-05
+Training loss: 0.097726
+Instr dry sdr: 12.5751 (Std: 5.1911)
+Instr dry l1_freq: 51.9894 (Std: 15.5097)
+Instr dry si_sdr: 11.0083 (Std: 8.8566)
+Instr other sdr: 6.3257 (Std: 3.6878)
+Instr other l1_freq: 51.5607 (Std: 13.9770)
+Instr other si_sdr: 5.4763 (Std: 3.6851)
+Metric avg sdr        : 9.4504
+Metric avg l1_freq    : 51.7750
+Metric avg si_sdr     : 8.2423
+Train epoch: 107 Learning rate: 1.433943689634168e-05
+Training loss: 0.092017
+Instr dry sdr: 12.7352 (Std: 5.0253)
+Instr dry l1_freq: 52.4895 (Std: 15.3276)
+Instr dry si_sdr: 11.6367 (Std: 7.5058)
+Instr other sdr: 6.4876 (Std: 3.5314)
+Instr other l1_freq: 51.7795 (Std: 13.7572)
+Instr other si_sdr: 5.6532 (Std: 3.5388)
+Metric avg sdr        : 9.6114
+Metric avg l1_freq    : 52.1345
+Metric avg si_sdr     : 8.6450
+Train epoch: 108 Learning rate: 1.433943689634168e-05
+Training loss: 0.093190
+Instr dry sdr: 12.8397 (Std: 4.8776)
+Instr dry l1_freq: 52.8024 (Std: 15.0866)
+Instr dry si_sdr: 11.9941 (Std: 6.6657)
+Instr other sdr: 6.5905 (Std: 3.3897)
+Instr other l1_freq: 52.0548 (Std: 13.5235)
+Instr other si_sdr: 5.7513 (Std: 3.4407)
+Metric avg sdr        : 9.7151
+Metric avg l1_freq    : 52.4286
+Metric avg si_sdr     : 8.8727
+Train epoch: 109 Learning rate: 1.3622465051524595e-05
+Training loss: 0.097330
+Instr dry sdr: 12.9161 (Std: 4.7276)
+Instr dry l1_freq: 53.0033 (Std: 14.7825)
+Instr dry si_sdr: 12.2813 (Std: 5.8908)
+Instr other sdr: 6.6614 (Std: 3.2214)
+Instr other l1_freq: 52.2954 (Std: 13.1528)
+Instr other si_sdr: 5.8090 (Std: 3.3168)
+Metric avg sdr        : 9.7888
+Metric avg l1_freq    : 52.6493
+Metric avg si_sdr     : 9.0452
+Train epoch: 110 Learning rate: 1.3622465051524595e-05
+Training loss: 0.093989
+Instr dry sdr: 13.0471 (Std: 4.5122)
+Instr dry l1_freq: 53.2873 (Std: 14.2572)
+Instr dry si_sdr: 12.5396 (Std: 5.3434)
+Instr other sdr: 6.7939 (Std: 2.9733)
+Instr other l1_freq: 52.7643 (Std: 12.6462)
+Instr other si_sdr: 5.9262 (Std: 3.1305)
+Metric avg sdr        : 9.9205
+Metric avg l1_freq    : 53.0258
+Metric avg si_sdr     : 9.2329
+Train epoch: 111 Learning rate: 1.3622465051524595e-05
+Training loss: 0.091716
+Instr dry sdr: 12.8921 (Std: 4.7097)
+Instr dry l1_freq: 53.0324 (Std: 14.7172)
+Instr dry si_sdr: 12.2804 (Std: 5.7996)
+Instr other sdr: 6.6447 (Std: 3.2111)
+Instr other l1_freq: 52.1832 (Std: 13.0902)
+Instr other si_sdr: 5.7832 (Std: 3.3266)
+Metric avg sdr        : 9.7684
+Metric avg l1_freq    : 52.6078
+Metric avg si_sdr     : 9.0318
+Train epoch: 112 Learning rate: 1.2941341798948365e-05
+Training loss: 0.093010
+Instr dry sdr: 12.7339 (Std: 4.9894)
+Instr dry l1_freq: 52.5628 (Std: 15.2270)
+Instr dry si_sdr: 11.7856 (Std: 6.9943)
+Instr other sdr: 6.4929 (Std: 3.4961)
+Instr other l1_freq: 51.8127 (Std: 13.6453)
+Instr other si_sdr: 5.6540 (Std: 3.5220)
+Metric avg sdr        : 9.6134
+Metric avg l1_freq    : 52.1878
+Metric avg si_sdr     : 8.7198
+Train epoch: 113 Learning rate: 1.2941341798948365e-05
+Training loss: 0.091633
+Instr dry sdr: 12.8765 (Std: 4.7889)
+Instr dry l1_freq: 52.9751 (Std: 14.8547)
+Instr dry si_sdr: 12.1655 (Std: 6.1935)
+Instr other sdr: 6.6291 (Std: 3.2774)
+Instr other l1_freq: 52.1851 (Std: 13.2451)
+Instr other si_sdr: 5.7841 (Std: 3.3589)
+Metric avg sdr        : 9.7528
+Metric avg l1_freq    : 52.5801
+Metric avg si_sdr     : 8.9748
+Train epoch: 114 Learning rate: 1.2941341798948365e-05
+Training loss: 0.092634
+Instr dry sdr: 12.7374 (Std: 5.0415)
+Instr dry l1_freq: 52.4767 (Std: 15.2749)
+Instr dry si_sdr: 11.7247 (Std: 7.2032)
+Instr other sdr: 6.4891 (Std: 3.5588)
+Instr other l1_freq: 51.8537 (Std: 13.7385)
+Instr other si_sdr: 5.6611 (Std: 3.5587)
+Metric avg sdr        : 9.6133
+Metric avg l1_freq    : 52.1652
+Metric avg si_sdr     : 8.6929
+Train epoch: 115 Learning rate: 1.2294274709000947e-05
+Training loss: 0.096644
+Instr dry sdr: 12.6075 (Std: 5.1926)
+Instr dry l1_freq: 52.0390 (Std: 15.4268)
+Instr dry si_sdr: 11.1788 (Std: 8.4648)
+Instr other sdr: 6.3639 (Std: 3.6876)
+Instr other l1_freq: 51.6923 (Std: 13.8963)
+Instr other si_sdr: 5.5344 (Std: 3.6760)
+Metric avg sdr        : 9.4857
+Metric avg l1_freq    : 51.8657
+Metric avg si_sdr     : 8.3566
+Train epoch: 116 Learning rate: 1.2294274709000947e-05
+Training loss: 0.094321
+Instr dry sdr: 12.6282 (Std: 5.2046)
+Instr dry l1_freq: 52.0768 (Std: 15.4735)
+Instr dry si_sdr: 11.1439 (Std: 8.6633)
+Instr other sdr: 6.3837 (Std: 3.6983)
+Instr other l1_freq: 51.5680 (Std: 13.9084)
+Instr other si_sdr: 5.5586 (Std: 3.6887)
+Metric avg sdr        : 9.5060
+Metric avg l1_freq    : 51.8224
+Metric avg si_sdr     : 8.3512
+Train epoch: 117 Learning rate: 1.2294274709000947e-05
+Training loss: 0.093851
+Instr dry sdr: 12.7273 (Std: 5.0907)
+Instr dry l1_freq: 52.3832 (Std: 15.3896)
+Instr dry si_sdr: 11.5779 (Std: 7.6525)
+Instr other sdr: 6.4779 (Std: 3.6006)
+Instr other l1_freq: 51.7455 (Std: 13.8349)
+Instr other si_sdr: 5.6541 (Std: 3.5949)
+Metric avg sdr        : 9.6026
+Metric avg l1_freq    : 52.0644
+Metric avg si_sdr     : 8.6160
+Train epoch: 118 Learning rate: 1.1679560973550899e-05
+Training loss: 0.095892
+Instr dry sdr: 12.8512 (Std: 4.9712)
+Instr dry l1_freq: 52.6765 (Std: 15.2045)
+Instr dry si_sdr: 12.0067 (Std: 6.6730)
+Instr other sdr: 6.6058 (Std: 3.4656)
+Instr other l1_freq: 52.1678 (Std: 13.6668)
+Instr other si_sdr: 5.7832 (Std: 3.4873)
+Metric avg sdr        : 9.7285
+Metric avg l1_freq    : 52.4222
+Metric avg si_sdr     : 8.8950
+Train epoch: 119 Learning rate: 1.1679560973550899e-05
+Training loss: 0.091460
+Instr dry sdr: 12.7908 (Std: 5.0447)
+Instr dry l1_freq: 52.5138 (Std: 15.2710)
+Instr dry si_sdr: 11.8395 (Std: 7.0315)
+Instr other sdr: 6.5475 (Std: 3.5367)
+Instr other l1_freq: 52.1575 (Std: 13.7656)
+Instr other si_sdr: 5.7225 (Std: 3.5484)
+Metric avg sdr        : 9.6691
+Metric avg l1_freq    : 52.3357
+Metric avg si_sdr     : 8.7810
+Train epoch: 120 Learning rate: 1.1679560973550899e-05
+Training loss: 0.095307
+Instr dry sdr: 12.6581 (Std: 5.1660)
+Instr dry l1_freq: 52.2390 (Std: 15.4570)
+Instr dry si_sdr: 11.3697 (Std: 8.0572)
+Instr other sdr: 6.4173 (Std: 3.6589)
+Instr other l1_freq: 51.7268 (Std: 13.8933)
+Instr other si_sdr: 5.5903 (Std: 3.6538)
+Metric avg sdr        : 9.5377
+Metric avg l1_freq    : 51.9829
+Metric avg si_sdr     : 8.4800
+Train epoch: 121 Learning rate: 1.1095582924873354e-05
+Training loss: 0.092688
+Instr dry sdr: 12.8339 (Std: 4.9952)
+Instr dry l1_freq: 52.7786 (Std: 15.2630)
+Instr dry si_sdr: 11.9348 (Std: 6.8469)
+Instr other sdr: 6.5914 (Std: 3.5119)
+Instr other l1_freq: 51.9780 (Std: 13.6690)
+Instr other si_sdr: 5.7741 (Std: 3.5316)
+Metric avg sdr        : 9.7127
+Metric avg l1_freq    : 52.3783
+Metric avg si_sdr     : 8.8545
+Train epoch: 122 Learning rate: 1.1095582924873354e-05
+Training loss: 0.089389
+Instr dry sdr: 12.6868 (Std: 5.1543)
+Instr dry l1_freq: 52.2544 (Std: 15.4487)
+Instr dry si_sdr: 11.3596 (Std: 8.1785)
+Instr other sdr: 6.4391 (Std: 3.6619)
+Instr other l1_freq: 51.7883 (Std: 13.9304)
+Instr other si_sdr: 5.6145 (Std: 3.6520)
+Metric avg sdr        : 9.5629
+Metric avg l1_freq    : 52.0214
+Metric avg si_sdr     : 8.4870
+Train epoch: 123 Learning rate: 1.1095582924873354e-05
+Training loss: 0.092695
+Instr dry sdr: 13.1334 (Std: 4.4033)
+Instr dry l1_freq: 53.5958 (Std: 13.9688)
+Instr dry si_sdr: 12.6618 (Std: 5.1663)
+Instr other sdr: 6.8817 (Std: 2.8615)
+Instr other l1_freq: 52.8812 (Std: 12.3821)
+Instr other si_sdr: 6.0108 (Std: 3.0557)
+Metric avg sdr        : 10.0075
+Metric avg l1_freq    : 53.2385
+Metric avg si_sdr     : 9.3363
+Train epoch: 124 Learning rate: 1.0540803778629686e-05
+Training loss: 0.090865
+Instr dry sdr: 12.8815 (Std: 4.9351)
+Instr dry l1_freq: 52.8738 (Std: 15.1633)
+Instr dry si_sdr: 12.0065 (Std: 6.7775)
+Instr other sdr: 6.6391 (Std: 3.4489)
+Instr other l1_freq: 52.2346 (Std: 13.5820)
+Instr other si_sdr: 5.8236 (Std: 3.4771)
+Metric avg sdr        : 9.7603
+Metric avg l1_freq    : 52.5542
+Metric avg si_sdr     : 8.9150
+Train epoch: 125 Learning rate: 1.0540803778629686e-05
+Training loss: 0.097932
+Instr dry sdr: 12.8245 (Std: 5.0095)
+Instr dry l1_freq: 52.7419 (Std: 15.3479)
+Instr dry si_sdr: 11.7842 (Std: 7.3198)
+Instr other sdr: 6.5780 (Std: 3.5360)
+Instr other l1_freq: 52.0653 (Std: 13.7986)
+Instr other si_sdr: 5.7681 (Std: 3.5339)
+Metric avg sdr        : 9.7012
+Metric avg l1_freq    : 52.4036
+Metric avg si_sdr     : 8.7762
+Train epoch: 126 Learning rate: 1.0540803778629686e-05
+Training loss: 0.090215
+Instr dry sdr: 12.7792 (Std: 5.1109)
+Instr dry l1_freq: 52.4720 (Std: 15.4843)
+Instr dry si_sdr: 11.5726 (Std: 7.8367)
+Instr other sdr: 6.5294 (Std: 3.6304)
+Instr other l1_freq: 51.8799 (Std: 13.9584)
+Instr other si_sdr: 5.7211 (Std: 3.6152)
+Metric avg sdr        : 9.6543
+Metric avg l1_freq    : 52.1760
+Metric avg si_sdr     : 8.6469
+Train epoch: 127 Learning rate: 1.0013763589698201e-05
+Training loss: 0.089430
+Instr dry sdr: 12.9886 (Std: 4.7834)
+Instr dry l1_freq: 53.1443 (Std: 14.8720)
+Instr dry si_sdr: 12.3267 (Std: 6.0204)
+Instr other sdr: 6.7426 (Std: 3.2993)
+Instr other l1_freq: 52.4058 (Std: 13.3023)
+Instr other si_sdr: 5.9186 (Std: 3.3788)
+Metric avg sdr        : 9.8656
+Metric avg l1_freq    : 52.7750
+Metric avg si_sdr     : 9.1226
+Train epoch: 128 Learning rate: 1.0013763589698201e-05
+Training loss: 0.094312
+Instr dry sdr: 12.8587 (Std: 5.0473)
+Instr dry l1_freq: 52.7096 (Std: 15.3562)
+Instr dry si_sdr: 11.8176 (Std: 7.3272)
+Instr other sdr: 6.6173 (Std: 3.5731)
+Instr other l1_freq: 52.1558 (Std: 13.8513)
+Instr other si_sdr: 5.8106 (Std: 3.5761)
+Metric avg sdr        : 9.7380
+Metric avg l1_freq    : 52.4327
+Metric avg si_sdr     : 8.8141
+Train epoch: 129 Learning rate: 1.0013763589698201e-05
+Training loss: 0.097339
+Instr dry sdr: 12.9453 (Std: 4.9302)
+Instr dry l1_freq: 52.9732 (Std: 15.1751)
+Instr dry si_sdr: 12.1253 (Std: 6.5995)
+Instr other sdr: 6.7016 (Std: 3.4517)
+Instr other l1_freq: 52.3808 (Std: 13.6101)
+Instr other si_sdr: 5.8944 (Std: 3.4824)
+Metric avg sdr        : 9.8235
+Metric avg l1_freq    : 52.6770
+Metric avg si_sdr     : 9.0099
+Train epoch: 130 Learning rate: 9.513075410213291e-06
+Training loss: 0.093759
+Instr dry sdr: 12.6769 (Std: 5.1848)
+Instr dry l1_freq: 52.2604 (Std: 15.4905)
+Instr dry si_sdr: 11.2656 (Std: 8.4064)
+Instr other sdr: 6.4356 (Std: 3.7061)
+Instr other l1_freq: 51.7764 (Std: 13.9597)
+Instr other si_sdr: 5.6129 (Std: 3.6973)
+Metric avg sdr        : 9.5563
+Metric avg l1_freq    : 52.0184
+Metric avg si_sdr     : 8.4393
+Train epoch: 131 Learning rate: 9.513075410213291e-06
+Training loss: 0.098356
+Instr dry sdr: 12.7425 (Std: 5.1650)
+Instr dry l1_freq: 52.4089 (Std: 15.4820)
+Instr dry si_sdr: 11.4501 (Std: 8.0911)
+Instr other sdr: 6.4990 (Std: 3.6775)
+Instr other l1_freq: 51.8683 (Std: 13.9575)
+Instr other si_sdr: 5.6862 (Std: 3.6691)
+Metric avg sdr        : 9.6207
+Metric avg l1_freq    : 52.1386
+Metric avg si_sdr     : 8.5681
+Train epoch: 132 Learning rate: 9.513075410213291e-06
+Training loss: 0.095287
+Instr dry sdr: 12.4559 (Std: 5.4014)
+Instr dry l1_freq: 51.3773 (Std: 15.7209)
+Instr dry si_sdr: 10.6520 (Std: 9.5616)
+Instr other sdr: 6.2205 (Std: 3.8719)
+Instr other l1_freq: 51.2221 (Std: 14.0111)
+Instr other si_sdr: 5.3885 (Std: 3.8971)
+Metric avg sdr        : 9.3382
+Metric avg l1_freq    : 51.2997
+Metric avg si_sdr     : 8.0202
+Train epoch: 133 Learning rate: 9.037421639702626e-06
+Training loss: 0.094915
+Instr dry sdr: 12.7138 (Std: 5.1674)
+Instr dry l1_freq: 52.4015 (Std: 15.4349)
+Instr dry si_sdr: 11.4121 (Std: 8.1166)
+Instr other sdr: 6.4753 (Std: 3.6846)
+Instr other l1_freq: 51.8321 (Std: 13.8875)
+Instr other si_sdr: 5.6583 (Std: 3.6783)
+Metric avg sdr        : 9.5945
+Metric avg l1_freq    : 52.1168
+Metric avg si_sdr     : 8.5352
+Train epoch: 134 Learning rate: 9.037421639702626e-06
+Training loss: 0.096393
+Instr dry sdr: 12.7945 (Std: 5.1220)
+Instr dry l1_freq: 52.6010 (Std: 15.3983)
+Instr dry si_sdr: 11.6378 (Std: 7.6964)
+Instr other sdr: 6.5584 (Std: 3.6388)
+Instr other l1_freq: 51.9830 (Std: 13.8424)
+Instr other si_sdr: 5.7504 (Std: 3.6350)
+Metric avg sdr        : 9.6764
+Metric avg l1_freq    : 52.2920
+Metric avg si_sdr     : 8.6941
+Train epoch: 135 Learning rate: 9.037421639702626e-06
+Training loss: 0.099597
+Instr dry sdr: 12.7919 (Std: 5.1178)
+Instr dry l1_freq: 52.5562 (Std: 15.4150)
+Instr dry si_sdr: 11.6321 (Std: 7.6935)
+Instr other sdr: 6.5530 (Std: 3.6320)
+Instr other l1_freq: 52.0400 (Std: 13.8747)
+Instr other si_sdr: 5.7409 (Std: 3.6274)
+Metric avg sdr        : 9.6724
+Metric avg l1_freq    : 52.2981
+Metric avg si_sdr     : 8.6865
+Train epoch: 136 Learning rate: 8.585550557717495e-06
+Training loss: 0.090295
+Instr dry sdr: 12.8795 (Std: 4.9871)
+Instr dry l1_freq: 52.8569 (Std: 15.2440)
+Instr dry si_sdr: 11.9876 (Std: 6.8381)
+Instr other sdr: 6.6420 (Std: 3.5077)
+Instr other l1_freq: 52.2082 (Std: 13.6723)
+Instr other si_sdr: 5.8337 (Std: 3.5257)
+Metric avg sdr        : 9.7607
+Metric avg l1_freq    : 52.5326
+Metric avg si_sdr     : 8.9106
+Train epoch: 137 Learning rate: 8.585550557717495e-06
+Training loss: 0.089884
+Instr dry sdr: 12.8850 (Std: 5.0298)
+Instr dry l1_freq: 52.7489 (Std: 15.2832)
+Instr dry si_sdr: 11.9058 (Std: 7.1376)
+Instr other sdr: 6.6479 (Std: 3.5415)
+Instr other l1_freq: 52.2620 (Std: 13.7692)
+Instr other si_sdr: 5.8442 (Std: 3.5491)
+Metric avg sdr        : 9.7665
+Metric avg l1_freq    : 52.5055
+Metric avg si_sdr     : 8.8750
+Train epoch: 138 Learning rate: 8.585550557717495e-06
+Training loss: 0.088977
+Instr dry sdr: 12.9498 (Std: 4.8888)
+Instr dry l1_freq: 53.0007 (Std: 15.0386)
+Instr dry si_sdr: 12.1730 (Std: 6.4540)
+Instr other sdr: 6.7089 (Std: 3.3994)
+Instr other l1_freq: 52.4736 (Std: 13.5112)
+Instr other si_sdr: 5.8944 (Std: 3.4422)
+Metric avg sdr        : 9.8294
+Metric avg l1_freq    : 52.7371
+Metric avg si_sdr     : 9.0337
+Train epoch: 139 Learning rate: 8.156273029831619e-06
+Training loss: 0.094878
+Instr dry sdr: 13.0263 (Std: 4.8388)
+Instr dry l1_freq: 53.2131 (Std: 14.9437)
+Instr dry si_sdr: 12.3148 (Std: 6.2340)
+Instr other sdr: 6.7840 (Std: 3.3348)
+Instr other l1_freq: 52.5629 (Std: 13.3594)
+Instr other si_sdr: 5.9767 (Std: 3.3971)
+Metric avg sdr        : 9.9051
+Metric avg l1_freq    : 52.8880
+Metric avg si_sdr     : 9.1457
+Train epoch: 140 Learning rate: 8.156273029831619e-06
+Training loss: 0.095048
+Instr dry sdr: 13.0318 (Std: 4.7903)
+Instr dry l1_freq: 53.2220 (Std: 14.8110)
+Instr dry si_sdr: 12.3731 (Std: 6.0319)
+Instr other sdr: 6.7918 (Std: 3.2833)
+Instr other l1_freq: 52.5610 (Std: 13.2352)
+Instr other si_sdr: 5.9756 (Std: 3.3698)
+Metric avg sdr        : 9.9118
+Metric avg l1_freq    : 52.8915
+Metric avg si_sdr     : 9.1744
+Train epoch: 141 Learning rate: 8.156273029831619e-06
+Training loss: 0.100407
+Instr dry sdr: 12.8483 (Std: 5.0633)
+Instr dry l1_freq: 52.7168 (Std: 15.3261)
+Instr dry si_sdr: 11.7780 (Std: 7.4301)
+Instr other sdr: 6.6118 (Std: 3.5896)
+Instr other l1_freq: 52.0975 (Std: 13.7927)
+Instr other si_sdr: 5.8122 (Std: 3.5883)
+Metric avg sdr        : 9.7301
+Metric avg l1_freq    : 52.4071
+Metric avg si_sdr     : 8.7951
+Train epoch: 142 Learning rate: 7.748459378340037e-06
+Training loss: 0.098264
+Instr dry sdr: 12.9012 (Std: 5.0163)
+Instr dry l1_freq: 52.9055 (Std: 15.2636)
+Instr dry si_sdr: 11.9283 (Std: 7.1281)
+Instr other sdr: 6.6659 (Std: 3.5414)
+Instr other l1_freq: 52.2809 (Std: 13.7113)
+Instr other si_sdr: 5.8686 (Std: 3.5462)
+Metric avg sdr        : 9.7835
+Metric avg l1_freq    : 52.5932
+Metric avg si_sdr     : 8.8984
+Train epoch: 143 Learning rate: 7.748459378340037e-06
+Training loss: 0.091402
+Instr dry sdr: 12.9116 (Std: 5.0022)
+Instr dry l1_freq: 52.9557 (Std: 15.2628)
+Instr dry si_sdr: 11.9703 (Std: 7.0275)
+Instr other sdr: 6.6674 (Std: 3.5289)
+Instr other l1_freq: 52.2054 (Std: 13.6955)
+Instr other si_sdr: 5.8712 (Std: 3.5378)
+Metric avg sdr        : 9.7895
+Metric avg l1_freq    : 52.5805
+Metric avg si_sdr     : 8.9208
+Train epoch: 144 Learning rate: 7.748459378340037e-06
+Training loss: 0.094382
+Instr dry sdr: 12.9307 (Std: 4.9579)
+Instr dry l1_freq: 52.8868 (Std: 15.1344)
+Instr dry si_sdr: 12.0759 (Std: 6.7416)
+Instr other sdr: 6.6924 (Std: 3.4671)
+Instr other l1_freq: 52.4059 (Std: 13.6066)
+Instr other si_sdr: 5.8890 (Std: 3.4903)
+Metric avg sdr        : 9.8116
+Metric avg l1_freq    : 52.6464
+Metric avg si_sdr     : 8.9825
+Train epoch: 145 Learning rate: 7.361036409423035e-06
+Training loss: 0.097014
+Instr dry sdr: 12.8796 (Std: 5.0266)
+Instr dry l1_freq: 52.7791 (Std: 15.2656)
+Instr dry si_sdr: 11.9162 (Std: 7.1001)
+Instr other sdr: 6.6454 (Std: 3.5405)
+Instr other l1_freq: 52.2561 (Std: 13.7232)
+Instr other si_sdr: 5.8467 (Std: 3.5463)
+Metric avg sdr        : 9.7625
+Metric avg l1_freq    : 52.5176
+Metric avg si_sdr     : 8.8815
+Train epoch: 146 Learning rate: 7.361036409423035e-06
+Training loss: 0.090039
+Instr dry sdr: 12.9316 (Std: 4.9567)
+Instr dry l1_freq: 52.9859 (Std: 15.1807)
+Instr dry si_sdr: 12.0449 (Std: 6.8583)
+Instr other sdr: 6.6940 (Std: 3.4768)
+Instr other l1_freq: 52.3062 (Std: 13.5915)
+Instr other si_sdr: 5.8962 (Std: 3.4986)
+Metric avg sdr        : 9.8128
+Metric avg l1_freq    : 52.6460
+Metric avg si_sdr     : 8.9706
+Train epoch: 147 Learning rate: 7.361036409423035e-06
+Training loss: 0.086740
+Instr dry sdr: 12.9175 (Std: 5.0477)
+Instr dry l1_freq: 52.8124 (Std: 15.3145)
+Instr dry si_sdr: 11.9079 (Std: 7.2653)
+Instr other sdr: 6.6818 (Std: 3.5602)
+Instr other l1_freq: 52.3869 (Std: 13.7973)
+Instr other si_sdr: 5.8909 (Std: 3.5586)
+Metric avg sdr        : 9.7996
+Metric avg l1_freq    : 52.5997
+Metric avg si_sdr     : 8.8994
+Train epoch: 148 Learning rate: 6.992984588951883e-06
+Training loss: 0.093262
+Instr dry sdr: 12.9297 (Std: 4.9863)
+Instr dry l1_freq: 52.9437 (Std: 15.2206)
+Instr dry si_sdr: 12.0304 (Std: 6.8971)
+Instr other sdr: 6.6975 (Std: 3.4967)
+Instr other l1_freq: 52.3166 (Std: 13.6655)
+Instr other si_sdr: 5.9003 (Std: 3.5149)
+Metric avg sdr        : 9.8136
+Metric avg l1_freq    : 52.6301
+Metric avg si_sdr     : 8.9654
+Train epoch: 149 Learning rate: 6.992984588951883e-06
+Training loss: 0.089209
+Instr dry sdr: 12.9448 (Std: 4.9485)
+Instr dry l1_freq: 52.9930 (Std: 15.1825)
+Instr dry si_sdr: 12.0571 (Std: 6.8559)
+Instr other sdr: 6.7064 (Std: 3.4694)
+Instr other l1_freq: 52.3082 (Std: 13.6207)
+Instr other si_sdr: 5.9045 (Std: 3.4973)
+Metric avg sdr        : 9.8256
+Metric avg l1_freq    : 52.6506
+Metric avg si_sdr     : 8.9808
+Train epoch: 150 Learning rate: 6.992984588951883e-06
+Training loss: 0.091250
+Instr dry sdr: 13.0154 (Std: 4.8329)
+Instr dry l1_freq: 53.1560 (Std: 14.9594)
+Instr dry si_sdr: 12.2982 (Std: 6.2567)
+Instr other sdr: 6.7774 (Std: 3.3365)
+Instr other l1_freq: 52.5333 (Std: 13.4056)
+Instr other si_sdr: 5.9671 (Std: 3.4008)
+Metric avg sdr        : 9.8964
+Metric avg l1_freq    : 52.8446
+Metric avg si_sdr     : 9.1326
+Train epoch: 151 Learning rate: 6.643335359504288e-06
+Training loss: 0.089285
+Instr dry sdr: 12.9558 (Std: 5.0116)
+Instr dry l1_freq: 52.8557 (Std: 15.2873)
+Instr dry si_sdr: 12.0446 (Std: 6.9359)
+Instr other sdr: 6.7192 (Std: 3.5214)
+Instr other l1_freq: 52.2718 (Std: 13.7646)
+Instr other si_sdr: 5.9287 (Std: 3.5342)
+Metric avg sdr        : 9.8375
+Metric avg l1_freq    : 52.5638
+Metric avg si_sdr     : 8.9866
+Train epoch: 152 Learning rate: 6.643335359504288e-06
+Training loss: 0.093715
+Instr dry sdr: 12.8837 (Std: 5.0895)
+Instr dry l1_freq: 52.7785 (Std: 15.4209)
+Instr dry si_sdr: 11.8158 (Std: 7.4261)
+Instr other sdr: 6.6453 (Std: 3.6111)
+Instr other l1_freq: 52.1904 (Std: 13.9012)
+Instr other si_sdr: 5.8519 (Std: 3.6058)
+Metric avg sdr        : 9.7645
+Metric avg l1_freq    : 52.4845
+Metric avg si_sdr     : 8.8338
+Train epoch: 153 Learning rate: 6.643335359504288e-06
+Training loss: 0.094634
+Instr dry sdr: 12.9221 (Std: 5.0286)
+Instr dry l1_freq: 52.7799 (Std: 15.3241)
+Instr dry si_sdr: 11.9359 (Std: 7.1872)
+Instr other sdr: 6.6838 (Std: 3.5465)
+Instr other l1_freq: 52.2104 (Std: 13.8029)
+Instr other si_sdr: 5.8925 (Std: 3.5535)
+Metric avg sdr        : 9.8030
+Metric avg l1_freq    : 52.4951
+Metric avg si_sdr     : 8.9142
+Train epoch: 154 Learning rate: 6.311168591529074e-06
+Training loss: 0.090340
+Instr dry sdr: 12.5977 (Std: 5.3607)
+Instr dry l1_freq: 51.7653 (Std: 15.6438)
+Instr dry si_sdr: 10.8231 (Std: 9.5397)
+Instr other sdr: 6.3668 (Std: 3.8433)
+Instr other l1_freq: 51.4808 (Std: 14.0331)
+Instr other si_sdr: 5.5531 (Std: 3.8592)
+Metric avg sdr        : 9.4822
+Metric avg l1_freq    : 51.6231
+Metric avg si_sdr     : 8.1881
+Train epoch: 155 Learning rate: 6.311168591529074e-06
+Training loss: 0.094673
+Instr dry sdr: 12.6857 (Std: 5.2910)
+Instr dry l1_freq: 52.0814 (Std: 15.5593)
+Instr dry si_sdr: 11.0689 (Std: 9.0954)
+Instr other sdr: 6.4517 (Std: 3.7781)
+Instr other l1_freq: 51.7817 (Std: 14.0336)
+Instr other si_sdr: 5.6439 (Std: 3.7786)
+Metric avg sdr        : 9.5687
+Metric avg l1_freq    : 51.9316
+Metric avg si_sdr     : 8.3564
+Train epoch: 156 Learning rate: 6.311168591529074e-06
+Training loss: 0.097054
+Instr dry sdr: 12.8776 (Std: 5.1045)
+Instr dry l1_freq: 52.6716 (Std: 15.4472)
+Instr dry si_sdr: 11.7472 (Std: 7.6424)
+Instr other sdr: 6.6376 (Std: 3.6234)
+Instr other l1_freq: 52.1721 (Std: 13.9403)
+Instr other si_sdr: 5.8483 (Std: 3.6134)
+Metric avg sdr        : 9.7576
+Metric avg l1_freq    : 52.4218
+Metric avg si_sdr     : 8.7978
+Train epoch: 157 Learning rate: 5.9956101619526196e-06
+Training loss: 0.086725
+Instr dry sdr: 12.7567 (Std: 5.1877)
+Instr dry l1_freq: 52.3955 (Std: 15.5117)
+Instr dry si_sdr: 11.3619 (Std: 8.4342)
+Instr other sdr: 6.5151 (Std: 3.7013)
+Instr other l1_freq: 51.9408 (Std: 13.9934)
+Instr other si_sdr: 5.7100 (Std: 3.6893)
+Metric avg sdr        : 9.6359
+Metric avg l1_freq    : 52.1681
+Metric avg si_sdr     : 8.5360
+Train epoch: 158 Learning rate: 5.9956101619526196e-06
+Training loss: 0.088358
+Instr dry sdr: 12.8922 (Std: 5.0698)
+Instr dry l1_freq: 52.7622 (Std: 15.3663)
+Instr dry si_sdr: 11.8662 (Std: 7.3063)
+Instr other sdr: 6.6547 (Std: 3.5908)
+Instr other l1_freq: 52.2345 (Std: 13.8596)
+Instr other si_sdr: 5.8634 (Std: 3.5879)
+Metric avg sdr        : 9.7735
+Metric avg l1_freq    : 52.4984
+Metric avg si_sdr     : 8.8648
+Train epoch: 159 Learning rate: 5.9956101619526196e-06
+Training loss: 0.095690
+Instr dry sdr: 12.8906 (Std: 5.0697)
+Instr dry l1_freq: 52.7371 (Std: 15.3624)
+Instr dry si_sdr: 11.8548 (Std: 7.3340)
+Instr other sdr: 6.6570 (Std: 3.5914)
+Instr other l1_freq: 52.2013 (Std: 13.8421)
+Instr other si_sdr: 5.8675 (Std: 3.5863)
+Metric avg sdr        : 9.7738
+Metric avg l1_freq    : 52.4692
+Metric avg si_sdr     : 8.8611
+Train epoch: 160 Learning rate: 5.695829653854988e-06
+Training loss: 0.092579
+Instr dry sdr: 12.8544 (Std: 5.1251)
+Instr dry l1_freq: 52.6313 (Std: 15.4354)
+Instr dry si_sdr: 11.7075 (Std: 7.6726)
+Instr other sdr: 6.6202 (Std: 3.6433)
+Instr other l1_freq: 52.2660 (Std: 13.9422)
+Instr other si_sdr: 5.8278 (Std: 3.6284)
+Metric avg sdr        : 9.7373
+Metric avg l1_freq    : 52.4487
+Metric avg si_sdr     : 8.7676
+Train epoch: 161 Learning rate: 5.695829653854988e-06
+Training loss: 0.097362
+Instr dry sdr: 12.9443 (Std: 5.0329)
+Instr dry l1_freq: 52.8741 (Std: 15.3065)
+Instr dry si_sdr: 11.9991 (Std: 7.0508)
+Instr other sdr: 6.7074 (Std: 3.5450)
+Instr other l1_freq: 52.4280 (Std: 13.8087)
+Instr other si_sdr: 5.9183 (Std: 3.5510)
+Metric avg sdr        : 9.8259
+Metric avg l1_freq    : 52.6510
+Metric avg si_sdr     : 8.9587
+Train epoch: 162 Learning rate: 5.695829653854988e-06
+Training loss: 0.091346
+Instr dry sdr: 12.8804 (Std: 5.1055)
+Instr dry l1_freq: 52.7372 (Std: 15.4190)
+Instr dry si_sdr: 11.7930 (Std: 7.5043)
+Instr other sdr: 6.6422 (Std: 3.6245)
+Instr other l1_freq: 52.2196 (Std: 13.9112)
+Instr other si_sdr: 5.8524 (Std: 3.6164)
+Metric avg sdr        : 9.7613
+Metric avg l1_freq    : 52.4784
+Metric avg si_sdr     : 8.8227
+Train epoch: 163 Learning rate: 5.411038171162238e-06
+Training loss: 0.091542
+Instr dry sdr: 12.8616 (Std: 5.1150)
+Instr dry l1_freq: 52.6565 (Std: 15.4280)
+Instr dry si_sdr: 11.7335 (Std: 7.6210)
+Instr other sdr: 6.6225 (Std: 3.6385)
+Instr other l1_freq: 52.1651 (Std: 13.9175)
+Instr other si_sdr: 5.8302 (Std: 3.6274)
+Metric avg sdr        : 9.7421
+Metric avg l1_freq    : 52.4108
+Metric avg si_sdr     : 8.7819
+Train epoch: 164 Learning rate: 5.411038171162238e-06
+Training loss: 0.094600
+Instr dry sdr: 12.8673 (Std: 5.1267)
+Instr dry l1_freq: 52.6975 (Std: 15.4468)
+Instr dry si_sdr: 11.7171 (Std: 7.6899)
+Instr other sdr: 6.6311 (Std: 3.6509)
+Instr other l1_freq: 52.1967 (Std: 13.9381)
+Instr other si_sdr: 5.8418 (Std: 3.6379)
+Metric avg sdr        : 9.7492
+Metric avg l1_freq    : 52.4471
+Metric avg si_sdr     : 8.7795
+Train epoch: 165 Learning rate: 5.411038171162238e-06
+Training loss: 0.097291
+Instr dry sdr: 13.0089 (Std: 4.9530)
+Instr dry l1_freq: 53.1224 (Std: 15.1908)
+Instr dry si_sdr: 12.2088 (Std: 6.5852)
+Instr other sdr: 6.7727 (Std: 3.4620)
+Instr other l1_freq: 52.4034 (Std: 13.6353)
+Instr other si_sdr: 5.9884 (Std: 3.4897)
+Metric avg sdr        : 9.8908
+Metric avg l1_freq    : 52.7629
+Metric avg si_sdr     : 9.0986
+Train epoch: 166 Learning rate: 5.1404862626041264e-06
+Training loss: 0.094797
+Instr dry sdr: 13.0049 (Std: 4.9604)
+Instr dry l1_freq: 53.0771 (Std: 15.1746)
+Instr dry si_sdr: 12.2103 (Std: 6.5536)
+Instr other sdr: 6.7714 (Std: 3.4740)
+Instr other l1_freq: 52.4696 (Std: 13.6267)
+Instr other si_sdr: 5.9851 (Std: 3.5005)
+Metric avg sdr        : 9.8881
+Metric avg l1_freq    : 52.7734
+Metric avg si_sdr     : 9.0977
+Train epoch: 167 Learning rate: 5.1404862626041264e-06
+Training loss: 0.100379
+Instr dry sdr: 12.9419 (Std: 5.0760)
+Instr dry l1_freq: 52.8755 (Std: 15.3623)
+Instr dry si_sdr: 11.9785 (Std: 7.1096)
+Instr other sdr: 6.7099 (Std: 3.5933)
+Instr other l1_freq: 52.3490 (Std: 13.8569)
+Instr other si_sdr: 5.9277 (Std: 3.5915)
+Metric avg sdr        : 9.8259
+Metric avg l1_freq    : 52.6122
+Metric avg si_sdr     : 8.9531
+Train epoch: 168 Learning rate: 5.1404862626041264e-06
+Training loss: 0.097326
+Instr dry sdr: 12.8634 (Std: 5.1823)
+Instr dry l1_freq: 52.4627 (Std: 15.5339)
+Instr dry si_sdr: 11.6184 (Std: 7.9900)
+Instr other sdr: 6.6246 (Std: 3.6947)
+Instr other l1_freq: 52.0684 (Std: 14.0159)
+Instr other si_sdr: 5.8370 (Std: 3.6815)
+Metric avg sdr        : 9.7440
+Metric avg l1_freq    : 52.2656
+Metric avg si_sdr     : 8.7277
+Train epoch: 169 Learning rate: 4.88346194947392e-06
+Training loss: 0.092164
+Instr dry sdr: 13.0002 (Std: 4.9702)
+Instr dry l1_freq: 52.9855 (Std: 15.2065)
+Instr dry si_sdr: 12.1563 (Std: 6.7287)
+Instr other sdr: 6.7648 (Std: 3.4724)
+Instr other l1_freq: 52.3790 (Std: 13.6860)
+Instr other si_sdr: 5.9752 (Std: 3.5019)
+Metric avg sdr        : 9.8825
+Metric avg l1_freq    : 52.6822
+Metric avg si_sdr     : 9.0658
+Train epoch: 170 Learning rate: 4.88346194947392e-06
+Training loss: 0.093825
+Instr dry sdr: 13.0661 (Std: 4.8525)
+Instr dry l1_freq: 53.1495 (Std: 14.9630)
+Instr dry si_sdr: 12.3687 (Std: 6.2087)
+Instr other sdr: 6.8300 (Std: 3.3398)
+Instr other l1_freq: 52.6276 (Std: 13.4359)
+Instr other si_sdr: 6.0311 (Std: 3.4032)
+Metric avg sdr        : 9.9481
+Metric avg l1_freq    : 52.8886
+Metric avg si_sdr     : 9.1999
+Train epoch: 171 Learning rate: 4.88346194947392e-06
+Training loss: 0.093724
+Instr dry sdr: 13.1031 (Std: 4.7939)
+Instr dry l1_freq: 53.2780 (Std: 14.8401)
+Instr dry si_sdr: 12.4540 (Std: 6.0211)
+Instr other sdr: 6.8673 (Std: 3.2787)
+Instr other l1_freq: 52.7146 (Std: 13.2905)
+Instr other si_sdr: 6.0661 (Std: 3.3589)
+Metric avg sdr        : 9.9852
+Metric avg l1_freq    : 52.9963
+Metric avg si_sdr     : 9.2600
+Train epoch: 172 Learning rate: 4.639288852000224e-06
+Training loss: 0.092525
+Instr dry sdr: 12.9381 (Std: 4.9911)
+Instr dry l1_freq: 52.8903 (Std: 15.2267)
+Instr dry si_sdr: 12.0534 (Std: 6.8457)
+Instr other sdr: 6.7037 (Std: 3.5046)
+Instr other l1_freq: 52.3353 (Std: 13.6947)
+Instr other si_sdr: 5.9037 (Std: 3.5301)
+Metric avg sdr        : 9.8209
+Metric avg l1_freq    : 52.6128
+Metric avg si_sdr     : 8.9786
+Train epoch: 173 Learning rate: 4.639288852000224e-06
+Training loss: 0.093124
+Instr dry sdr: 12.9824 (Std: 4.9425)
+Instr dry l1_freq: 52.9453 (Std: 15.1376)
+Instr dry si_sdr: 12.1760 (Std: 6.5795)
+Instr other sdr: 6.7494 (Std: 3.4530)
+Instr other l1_freq: 52.4448 (Std: 13.6078)
+Instr other si_sdr: 5.9532 (Std: 3.4866)
+Metric avg sdr        : 9.8659
+Metric avg l1_freq    : 52.6951
+Metric avg si_sdr     : 9.0646
+Train epoch: 174 Learning rate: 4.639288852000224e-06
+Training loss: 0.097429
+Instr dry sdr: 12.8439 (Std: 5.1313)
+Instr dry l1_freq: 52.6034 (Std: 15.4667)
+Instr dry si_sdr: 11.7080 (Std: 7.6385)
+Instr other sdr: 6.6100 (Std: 3.6477)
+Instr other l1_freq: 52.0806 (Std: 13.9462)
+Instr other si_sdr: 5.8138 (Std: 3.6422)
+Metric avg sdr        : 9.7269
+Metric avg l1_freq    : 52.3420
+Metric avg si_sdr     : 8.7609
+Train epoch: 175 Learning rate: 4.407324409400213e-06
+Training loss: 0.095886
+Instr dry sdr: 12.9012 (Std: 5.1151)
+Instr dry l1_freq: 52.6466 (Std: 15.4250)
+Instr dry si_sdr: 11.8163 (Std: 7.5033)
+Instr other sdr: 6.6675 (Std: 3.6232)
+Instr other l1_freq: 52.2440 (Std: 13.9307)
+Instr other si_sdr: 5.8780 (Std: 3.6207)
+Metric avg sdr        : 9.7844
+Metric avg l1_freq    : 52.4453
+Metric avg si_sdr     : 8.8472
+Train epoch: 176 Learning rate: 4.407324409400213e-06
+Training loss: 0.098037
+Instr dry sdr: 12.9997 (Std: 4.9698)
+Instr dry l1_freq: 53.0118 (Std: 15.2028)
+Instr dry si_sdr: 12.1703 (Std: 6.6775)
+Instr other sdr: 6.7685 (Std: 3.4791)
+Instr other l1_freq: 52.4436 (Std: 13.6768)
+Instr other si_sdr: 5.9799 (Std: 3.5082)
+Metric avg sdr        : 9.8841
+Metric avg l1_freq    : 52.7277
+Metric avg si_sdr     : 9.0751
+Train epoch: 177 Learning rate: 4.407324409400213e-06
+Training loss: 0.091857
+Instr dry sdr: 13.0062 (Std: 4.9606)
+Instr dry l1_freq: 52.9682 (Std: 15.1650)
+Instr dry si_sdr: 12.1977 (Std: 6.6035)
+Instr other sdr: 6.7729 (Std: 3.4661)
+Instr other l1_freq: 52.4945 (Std: 13.6502)
+Instr other si_sdr: 5.9841 (Std: 3.4967)
+Metric avg sdr        : 9.8896
+Metric avg l1_freq    : 52.7313
+Metric avg si_sdr     : 9.0909
+Train epoch: 178 Learning rate: 4.1869581889302025e-06
+Training loss: 0.098096
+Instr dry sdr: 12.9103 (Std: 5.0752)
+Instr dry l1_freq: 52.7613 (Std: 15.3833)
+Instr dry si_sdr: 11.8924 (Std: 7.2792)
+Instr other sdr: 6.6783 (Std: 3.5937)
+Instr other l1_freq: 52.2686 (Std: 13.8729)
+Instr other si_sdr: 5.8899 (Std: 3.5947)
+Metric avg sdr        : 9.7943
+Metric avg l1_freq    : 52.5150
+Metric avg si_sdr     : 8.8912
+Train epoch: 179 Learning rate: 4.1869581889302025e-06
+Training loss: 0.090818
+Instr dry sdr: 12.9573 (Std: 5.0339)
+Instr dry l1_freq: 52.8341 (Std: 15.3070)
+Instr dry si_sdr: 12.0437 (Std: 6.9474)
+Instr other sdr: 6.7252 (Std: 3.5486)
+Instr other l1_freq: 52.3729 (Std: 13.7904)
+Instr other si_sdr: 5.9393 (Std: 3.5573)
+Metric avg sdr        : 9.8412
+Metric avg l1_freq    : 52.6035
+Metric avg si_sdr     : 8.9915
+Train epoch: 180 Learning rate: 4.1869581889302025e-06
+Training loss: 0.092787
+Instr dry sdr: 13.0645 (Std: 4.8733)
+Instr dry l1_freq: 53.1646 (Std: 15.0069)
+Instr dry si_sdr: 12.3598 (Std: 6.2420)
+Instr other sdr: 6.8317 (Std: 3.3670)
+Instr other l1_freq: 52.6292 (Std: 13.4452)
+Instr other si_sdr: 6.0409 (Std: 3.4202)
+Metric avg sdr        : 9.9481
+Metric avg l1_freq    : 52.8969
+Metric avg si_sdr     : 9.2003
+Train epoch: 181 Learning rate: 3.977610279483693e-06
+Training loss: 0.098106
+Instr dry sdr: 13.0562 (Std: 4.8652)
+Instr dry l1_freq: 53.1336 (Std: 14.9775)
+Instr dry si_sdr: 12.3658 (Std: 6.1905)
+Instr other sdr: 6.8223 (Std: 3.3560)
+Instr other l1_freq: 52.5849 (Std: 13.4299)
+Instr other si_sdr: 6.0296 (Std: 3.4127)
+Metric avg sdr        : 9.9393
+Metric avg l1_freq    : 52.8593
+Metric avg si_sdr     : 9.1977
+Train epoch: 182 Learning rate: 3.977610279483693e-06
+Training loss: 0.091860
+Instr dry sdr: 13.0554 (Std: 4.9438)
+Instr dry l1_freq: 53.0550 (Std: 15.1489)
+Instr dry si_sdr: 12.2779 (Std: 6.5097)
+Instr other sdr: 6.8257 (Std: 3.4539)
+Instr other l1_freq: 52.5838 (Std: 13.6336)
+Instr other si_sdr: 6.0443 (Std: 3.4877)
+Metric avg sdr        : 9.9406
+Metric avg l1_freq    : 52.8194
+Metric avg si_sdr     : 9.1611
+Train epoch: 183 Learning rate: 3.977610279483693e-06
+Training loss: 0.093953
+Instr dry sdr: 13.0706 (Std: 4.9253)
+Instr dry l1_freq: 53.1449 (Std: 15.1201)
+Instr dry si_sdr: 12.3207 (Std: 6.4185)
+Instr other sdr: 6.8401 (Std: 3.4303)
+Instr other l1_freq: 52.6158 (Std: 13.5921)
+Instr other si_sdr: 6.0593 (Std: 3.4694)
+Metric avg sdr        : 9.9554
+Metric avg l1_freq    : 52.8804
+Metric avg si_sdr     : 9.1900
+Train epoch: 184 Learning rate: 3.778729765509508e-06
+Training loss: 0.092398
+Instr dry sdr: 12.9325 (Std: 5.1393)
+Instr dry l1_freq: 52.6756 (Std: 15.4664)
+Instr dry si_sdr: 11.8159 (Std: 7.6263)
+Instr other sdr: 6.7009 (Std: 3.6478)
+Instr other l1_freq: 52.2670 (Std: 13.9723)
+Instr other si_sdr: 5.9239 (Std: 3.6360)
+Metric avg sdr        : 9.8167
+Metric avg l1_freq    : 52.4713
+Metric avg si_sdr     : 8.8699
+Train epoch: 185 Learning rate: 3.778729765509508e-06
+Training loss: 0.096717
+Instr dry sdr: 13.0490 (Std: 4.9449)
+Instr dry l1_freq: 53.0591 (Std: 15.1325)
+Instr dry si_sdr: 12.2904 (Std: 6.4531)
+Instr other sdr: 6.8182 (Std: 3.4383)
+Instr other l1_freq: 52.6409 (Std: 13.6066)
+Instr other si_sdr: 6.0330 (Std: 3.4746)
+Metric avg sdr        : 9.9336
+Metric avg l1_freq    : 52.8500
+Metric avg si_sdr     : 9.1617
+Train epoch: 186 Learning rate: 3.778729765509508e-06
+Training loss: 0.090671
+Instr dry sdr: 12.9600 (Std: 5.0693)
+Instr dry l1_freq: 52.8589 (Std: 15.3583)
+Instr dry si_sdr: 11.9827 (Std: 7.1793)
+Instr other sdr: 6.7297 (Std: 3.5853)
+Instr other l1_freq: 52.3399 (Std: 13.8491)
+Instr other si_sdr: 5.9496 (Std: 3.5872)
+Metric avg sdr        : 9.8448
+Metric avg l1_freq    : 52.5994
+Metric avg si_sdr     : 8.9661
+Train epoch: 187 Learning rate: 3.5897932772340322e-06
+Training loss: 0.093142
+Instr dry sdr: 12.9661 (Std: 5.0599)
+Instr dry l1_freq: 52.8261 (Std: 15.3346)
+Instr dry si_sdr: 12.0146 (Std: 7.0952)
+Instr other sdr: 6.7368 (Std: 3.5686)
+Instr other l1_freq: 52.4203 (Std: 13.8399)
+Instr other si_sdr: 5.9544 (Std: 3.5748)
+Metric avg sdr        : 9.8515
+Metric avg l1_freq    : 52.6232
+Metric avg si_sdr     : 8.9845
+Train epoch: 188 Learning rate: 3.5897932772340322e-06
+Training loss: 0.090606
+Instr dry sdr: 12.9711 (Std: 5.0377)
+Instr dry l1_freq: 52.8756 (Std: 15.3093)
+Instr dry si_sdr: 12.0522 (Std: 6.9833)
+Instr other sdr: 6.7401 (Std: 3.5500)
+Instr other l1_freq: 52.3409 (Std: 13.7953)
+Instr other si_sdr: 5.9555 (Std: 3.5622)
+Metric avg sdr        : 9.8556
+Metric avg l1_freq    : 52.6082
+Metric avg si_sdr     : 9.0039
+Train epoch: 189 Learning rate: 3.5897932772340322e-06
+Training loss: 0.092085
+Instr dry sdr: 12.8997 (Std: 5.1578)
+Instr dry l1_freq: 52.5542 (Std: 15.4780)
+Instr dry si_sdr: 11.7110 (Std: 7.8564)
+Instr other sdr: 6.6677 (Std: 3.6722)
+Instr other l1_freq: 52.2427 (Std: 13.9940)
+Instr other si_sdr: 5.8874 (Std: 3.6602)
+Metric avg sdr        : 9.7837
+Metric avg l1_freq    : 52.3984
+Metric avg si_sdr     : 8.7992
+Train epoch: 190 Learning rate: 3.4103036133723303e-06
+Training loss: 0.093211
+Instr dry sdr: 12.9938 (Std: 5.0237)
+Instr dry l1_freq: 52.8923 (Std: 15.2859)
+Instr dry si_sdr: 12.0941 (Std: 6.9351)
+Instr other sdr: 6.7622 (Std: 3.5370)
+Instr other l1_freq: 52.4834 (Std: 13.7856)
+Instr other si_sdr: 5.9802 (Std: 3.5492)
+Metric avg sdr        : 9.8780
+Metric avg l1_freq    : 52.6879
+Metric avg si_sdr     : 9.0371
+Train epoch: 191 Learning rate: 3.4103036133723303e-06
+Training loss: 0.093054
+Instr dry sdr: 12.9460 (Std: 5.0873)
+Instr dry l1_freq: 52.7413 (Std: 15.3860)
+Instr dry si_sdr: 11.9249 (Std: 7.3263)
+Instr other sdr: 6.7154 (Std: 3.6001)
+Instr other l1_freq: 52.3403 (Std: 13.8921)
+Instr other si_sdr: 5.9341 (Std: 3.6000)
+Metric avg sdr        : 9.8307
+Metric avg l1_freq    : 52.5408
+Metric avg si_sdr     : 8.9295
+Train epoch: 192 Learning rate: 3.4103036133723303e-06
+Training loss: 0.094299
+Instr dry sdr: 12.9910 (Std: 5.0396)
+Instr dry l1_freq: 52.9021 (Std: 15.3228)
+Instr dry si_sdr: 12.0614 (Std: 7.0331)
+Instr other sdr: 6.7601 (Std: 3.5478)
+Instr other l1_freq: 52.4129 (Std: 13.7910)
+Instr other si_sdr: 5.9815 (Std: 3.5567)
+Metric avg sdr        : 9.8756
+Metric avg l1_freq    : 52.6575
+Metric avg si_sdr     : 9.0214
+Train epoch: 193 Learning rate: 3.2397884327037135e-06
+Training loss: 0.099640
+Instr dry sdr: 12.9444 (Std: 5.0973)
+Instr dry l1_freq: 52.7317 (Std: 15.4063)
+Instr dry si_sdr: 11.9180 (Std: 7.3313)
+Instr other sdr: 6.7131 (Std: 3.6097)
+Instr other l1_freq: 52.3779 (Std: 13.9158)
+Instr other si_sdr: 5.9322 (Std: 3.6066)
+Metric avg sdr        : 9.8287
+Metric avg l1_freq    : 52.5548
+Metric avg si_sdr     : 8.9251
+Train epoch: 194 Learning rate: 3.2397884327037135e-06
+Training loss: 0.095810
+Instr dry sdr: 13.0026 (Std: 4.9771)
+Instr dry l1_freq: 53.0306 (Std: 15.2164)
+Instr dry si_sdr: 12.1626 (Std: 6.7231)
+Instr other sdr: 6.7734 (Std: 3.4885)
+Instr other l1_freq: 52.5501 (Std: 13.6774)
+Instr other si_sdr: 5.9869 (Std: 3.5131)
+Metric avg sdr        : 9.8880
+Metric avg l1_freq    : 52.7903
+Metric avg si_sdr     : 9.0747
+Train epoch: 195 Learning rate: 3.2397884327037135e-06
+Training loss: 0.094791
+Instr dry sdr: 13.0254 (Std: 4.9660)
+Instr dry l1_freq: 53.1081 (Std: 15.2067)
+Instr dry si_sdr: 12.2018 (Std: 6.6747)
+Instr other sdr: 6.7945 (Std: 3.4757)
+Instr other l1_freq: 52.5520 (Std: 13.6617)
+Instr other si_sdr: 6.0107 (Std: 3.5039)
+Metric avg sdr        : 9.9100
+Metric avg l1_freq    : 52.8300
+Metric avg si_sdr     : 9.1063
+Train epoch: 196 Learning rate: 3.077799011068528e-06
+Training loss: 0.094022
+Instr dry sdr: 12.9993 (Std: 5.0386)
+Instr dry l1_freq: 52.9897 (Std: 15.3230)
+Instr dry si_sdr: 12.0766 (Std: 7.0081)
+Instr other sdr: 6.7706 (Std: 3.5526)
+Instr other l1_freq: 52.5178 (Std: 13.8153)
+Instr other si_sdr: 5.9919 (Std: 3.5632)
+Metric avg sdr        : 9.8849
+Metric avg l1_freq    : 52.7538
+Metric avg si_sdr     : 9.0343
+Train epoch: 197 Learning rate: 3.077799011068528e-06
+Training loss: 0.089808
+Instr dry sdr: 12.9030 (Std: 5.1382)
+Instr dry l1_freq: 52.6801 (Std: 15.4695)
+Instr dry si_sdr: 11.7579 (Std: 7.6938)
+Instr other sdr: 6.6722 (Std: 3.6608)
+Instr other l1_freq: 52.2401 (Std: 13.9689)
+Instr other si_sdr: 5.8911 (Std: 3.6494)
+Metric avg sdr        : 9.7876
+Metric avg l1_freq    : 52.4601
+Metric avg si_sdr     : 8.8245
+Train epoch: 198 Learning rate: 3.077799011068528e-06
+Training loss: 0.096411
+Instr dry sdr: 12.9705 (Std: 5.0528)
+Instr dry l1_freq: 52.8596 (Std: 15.3333)
+Instr dry si_sdr: 12.0465 (Std: 6.9944)
+Instr other sdr: 6.7392 (Std: 3.5682)
+Instr other l1_freq: 52.4578 (Std: 13.8326)
+Instr other si_sdr: 5.9563 (Std: 3.5730)
+Metric avg sdr        : 9.8548
+Metric avg l1_freq    : 52.6587
+Metric avg si_sdr     : 9.0014
+Train epoch: 199 Learning rate: 2.9239090605151014e-06
+Training loss: 0.089098
+Instr dry sdr: 12.9623 (Std: 5.0550)
+Instr dry l1_freq: 52.8382 (Std: 15.3452)
+Instr dry si_sdr: 12.0264 (Std: 7.0291)
+Instr other sdr: 6.7334 (Std: 3.5707)
+Instr other l1_freq: 52.3943 (Std: 13.8395)
+Instr other si_sdr: 5.9517 (Std: 3.5752)
+Metric avg sdr        : 9.8479
+Metric avg l1_freq    : 52.6162
+Metric avg si_sdr     : 8.9891
+Train epoch: 200 Learning rate: 2.9239090605151014e-06
+Training loss: 0.098282
+Instr dry sdr: 13.0326 (Std: 4.9732)
+Instr dry l1_freq: 53.0502 (Std: 15.1913)
+Instr dry si_sdr: 12.2395 (Std: 6.5679)
+Instr other sdr: 6.8032 (Std: 3.4785)
+Instr other l1_freq: 52.5799 (Std: 13.6677)
+Instr other si_sdr: 6.0207 (Std: 3.5036)
+Metric avg sdr        : 9.9179
+Metric avg l1_freq    : 52.8151
+Metric avg si_sdr     : 9.1301
+Train epoch: 201 Learning rate: 2.9239090605151014e-06
+Training loss: 0.087879
+Instr dry sdr: 12.9945 (Std: 5.0327)
+Instr dry l1_freq: 52.9379 (Std: 15.2901)
+Instr dry si_sdr: 12.1233 (Std: 6.8245)
+Instr other sdr: 6.7651 (Std: 3.5438)
+Instr other l1_freq: 52.4752 (Std: 13.7720)
+Instr other si_sdr: 5.9853 (Std: 3.5541)
+Metric avg sdr        : 9.8798
+Metric avg l1_freq    : 52.7065
+Metric avg si_sdr     : 9.0543
+Train epoch: 202 Learning rate: 2.777713607489346e-06
+Training loss: 0.090894
+Instr dry sdr: 13.0100 (Std: 5.0205)
+Instr dry l1_freq: 52.9811 (Std: 15.2788)
+Instr dry si_sdr: 12.1530 (Std: 6.7770)
+Instr other sdr: 6.7815 (Std: 3.5375)
+Instr other l1_freq: 52.5304 (Std: 13.7598)
+Instr other si_sdr: 6.0045 (Std: 3.5471)
+Metric avg sdr        : 9.8958
+Metric avg l1_freq    : 52.7557
+Metric avg si_sdr     : 9.0787
+Train epoch: 203 Learning rate: 2.777713607489346e-06
+Training loss: 0.088920
+Instr dry sdr: 13.0696 (Std: 4.9347)
+Instr dry l1_freq: 53.1452 (Std: 15.1341)
+Instr dry si_sdr: 12.3204 (Std: 6.4161)
+Instr other sdr: 6.8407 (Std: 3.4438)
+Instr other l1_freq: 52.6320 (Std: 13.5918)
+Instr other si_sdr: 6.0610 (Std: 3.4786)
+Metric avg sdr        : 9.9551
+Metric avg l1_freq    : 52.8886
+Metric avg si_sdr     : 9.1907
+Train epoch: 204 Learning rate: 2.777713607489346e-06
+Training loss: 0.090892
+Instr dry sdr: 13.0883 (Std: 4.9306)
+Instr dry l1_freq: 53.1626 (Std: 15.1372)
+Instr dry si_sdr: 12.3271 (Std: 6.4656)
+Instr other sdr: 6.8572 (Std: 3.4362)
+Instr other l1_freq: 52.6256 (Std: 13.6013)
+Instr other si_sdr: 6.0819 (Std: 3.4702)
+Metric avg sdr        : 9.9728
+Metric avg l1_freq    : 52.8941
+Metric avg si_sdr     : 9.2045
+Train epoch: 205 Learning rate: 2.6388279271148787e-06
+Training loss: 0.091701
+Instr dry sdr: 13.0661 (Std: 4.9780)
+Instr dry l1_freq: 53.1265 (Std: 15.2127)
+Instr dry si_sdr: 12.2558 (Std: 6.6377)
+Instr other sdr: 6.8350 (Std: 3.4867)
+Instr other l1_freq: 52.6264 (Std: 13.6752)
+Instr other si_sdr: 6.0612 (Std: 3.5109)
+Metric avg sdr        : 9.9505
+Metric avg l1_freq    : 52.8764
+Metric avg si_sdr     : 9.1585
+Train epoch: 206 Learning rate: 2.6388279271148787e-06
+Training loss: 0.090879
+Instr dry sdr: 12.9585 (Std: 5.1246)
+Instr dry l1_freq: 52.7450 (Std: 15.4385)
+Instr dry si_sdr: 11.8962 (Std: 7.4500)
+Instr other sdr: 6.7270 (Std: 3.6377)
+Instr other l1_freq: 52.3973 (Std: 13.9477)
+Instr other si_sdr: 5.9538 (Std: 3.6284)
+Metric avg sdr        : 9.8427
+Metric avg l1_freq    : 52.5711
+Metric avg si_sdr     : 8.9250
+Train epoch: 207 Learning rate: 2.6388279271148787e-06
+Training loss: 0.095157
+Instr dry sdr: 12.9809 (Std: 5.0754)
+Instr dry l1_freq: 52.8825 (Std: 15.3618)
+Instr dry si_sdr: 12.0220 (Std: 7.1175)
+Instr other sdr: 6.7499 (Std: 3.5911)
+Instr other l1_freq: 52.4251 (Std: 13.8466)
+Instr other si_sdr: 5.9755 (Std: 3.5914)
+Metric avg sdr        : 9.8654
+Metric avg l1_freq    : 52.6538
+Metric avg si_sdr     : 8.9987
+Train epoch: 208 Learning rate: 2.5068865307591348e-06
+Training loss: 0.097233
+Instr dry sdr: 12.8730 (Std: 5.1897)
+Instr dry l1_freq: 52.4444 (Std: 15.5242)
+Instr dry si_sdr: 11.6652 (Std: 7.8875)
+Instr other sdr: 6.6421 (Std: 3.7050)
+Instr other l1_freq: 52.1159 (Std: 14.0080)
+Instr other si_sdr: 5.8584 (Std: 3.6978)
+Metric avg sdr        : 9.7575
+Metric avg l1_freq    : 52.2802
+Metric avg si_sdr     : 8.7618
+Train epoch: 209 Learning rate: 2.5068865307591348e-06
+Training loss: 0.095122
+Instr dry sdr: 12.8892 (Std: 5.1783)
+Instr dry l1_freq: 52.5212 (Std: 15.5039)
+Instr dry si_sdr: 11.7113 (Std: 7.7958)
+Instr other sdr: 6.6589 (Std: 3.6976)
+Instr other l1_freq: 52.2186 (Std: 13.9996)
+Instr other si_sdr: 5.8758 (Std: 3.6899)
+Metric avg sdr        : 9.7741
+Metric avg l1_freq    : 52.3699
+Metric avg si_sdr     : 8.7936
+Train epoch: 210 Learning rate: 2.5068865307591348e-06
+Training loss: 0.089211
+Instr dry sdr: 12.9099 (Std: 5.1559)
+Instr dry l1_freq: 52.5873 (Std: 15.4712)
+Instr dry si_sdr: 11.7934 (Std: 7.6123)
+Instr other sdr: 6.6795 (Std: 3.6688)
+Instr other l1_freq: 52.3068 (Std: 13.9848)
+Instr other si_sdr: 5.8986 (Std: 3.6603)
+Metric avg sdr        : 9.7947
+Metric avg l1_freq    : 52.4471
+Metric avg si_sdr     : 8.8460
+Train epoch: 211 Learning rate: 2.381542204221178e-06
+Training loss: 0.089044
+Instr dry sdr: 12.9820 (Std: 5.0812)
+Instr dry l1_freq: 52.8154 (Std: 15.3662)
+Instr dry si_sdr: 12.0162 (Std: 7.1432)
+Instr other sdr: 6.7530 (Std: 3.5918)
+Instr other l1_freq: 52.4064 (Std: 13.8646)
+Instr other si_sdr: 5.9778 (Std: 3.5935)
+Metric avg sdr        : 9.8675
+Metric avg l1_freq    : 52.6109
+Metric avg si_sdr     : 8.9970
+Train epoch: 212 Learning rate: 2.381542204221178e-06
+Training loss: 0.096083
+Instr dry sdr: 12.9687 (Std: 5.0974)
+Instr dry l1_freq: 52.7944 (Std: 15.3968)
+Instr dry si_sdr: 11.9689 (Std: 7.2526)
+Instr other sdr: 6.7396 (Std: 3.6083)
+Instr other l1_freq: 52.3940 (Std: 13.8941)
+Instr other si_sdr: 5.9640 (Std: 3.6065)
+Metric avg sdr        : 9.8542
+Metric avg l1_freq    : 52.5942
+Metric avg si_sdr     : 8.9664
+Train epoch: 213 Learning rate: 2.381542204221178e-06
+Training loss: 0.090508
+Instr dry sdr: 12.9640 (Std: 5.1021)
+Instr dry l1_freq: 52.7599 (Std: 15.4043)
+Instr dry si_sdr: 11.9621 (Std: 7.2544)
+Instr other sdr: 6.7350 (Std: 3.6160)
+Instr other l1_freq: 52.3958 (Std: 13.9046)
+Instr other si_sdr: 5.9594 (Std: 3.6121)
+Metric avg sdr        : 9.8495
+Metric avg l1_freq    : 52.5779
+Metric avg si_sdr     : 8.9608
+Train epoch: 214 Learning rate: 2.262465094010119e-06
+Training loss: 0.088221
+Instr dry sdr: 12.9630 (Std: 5.1008)
+Instr dry l1_freq: 52.7650 (Std: 15.3975)
+Instr dry si_sdr: 11.9661 (Std: 7.2363)
+Instr other sdr: 6.7336 (Std: 3.6175)
+Instr other l1_freq: 52.3711 (Std: 13.8972)
+Instr other si_sdr: 5.9574 (Std: 3.6153)
+Metric avg sdr        : 9.8483
+Metric avg l1_freq    : 52.5680
+Metric avg si_sdr     : 8.9618
+Train epoch: 215 Learning rate: 2.262465094010119e-06
+Training loss: 0.094517
+Instr dry sdr: 12.9718 (Std: 5.1046)
+Instr dry l1_freq: 52.7098 (Std: 15.3992)
+Instr dry si_sdr: 11.9743 (Std: 7.2457)
+Instr other sdr: 6.7441 (Std: 3.6193)
+Instr other l1_freq: 52.4082 (Std: 13.9162)
+Instr other si_sdr: 5.9692 (Std: 3.6165)
+Metric avg sdr        : 9.8580
+Metric avg l1_freq    : 52.5590
+Metric avg si_sdr     : 8.9718
+Train epoch: 216 Learning rate: 2.262465094010119e-06
+Training loss: 0.094498
+Instr dry sdr: 12.9965 (Std: 5.0813)
+Instr dry l1_freq: 52.8448 (Std: 15.3691)
+Instr dry si_sdr: 12.0471 (Std: 7.0910)
+Instr other sdr: 6.7677 (Std: 3.5996)
+Instr other l1_freq: 52.4100 (Std: 13.8670)
+Instr other si_sdr: 5.9949 (Std: 3.6015)
+Metric avg sdr        : 9.8821
+Metric avg l1_freq    : 52.6274
+Metric avg si_sdr     : 9.0210
+Train epoch: 217 Learning rate: 2.1493418393096127e-06
+Training loss: 0.090574
+Instr dry sdr: 13.0157 (Std: 5.0651)
+Instr dry l1_freq: 52.8412 (Std: 15.3343)
+Instr dry si_sdr: 12.1058 (Std: 6.9677)
+Instr other sdr: 6.7868 (Std: 3.5797)
+Instr other l1_freq: 52.5147 (Std: 13.8538)
+Instr other si_sdr: 6.0139 (Std: 3.5843)
+Metric avg sdr        : 9.9012
+Metric avg l1_freq    : 52.6779
+Metric avg si_sdr     : 9.0599
+Train epoch: 218 Learning rate: 2.1493418393096127e-06
+Training loss: 0.095987
+Instr dry sdr: 13.1272 (Std: 4.8777)
+Instr dry l1_freq: 53.2347 (Std: 14.9888)
+Instr dry si_sdr: 12.4565 (Std: 6.1439)
+Instr other sdr: 6.8968 (Std: 3.3798)
+Instr other l1_freq: 52.7438 (Std: 13.4634)
+Instr other si_sdr: 6.1177 (Std: 3.4341)
+Metric avg sdr        : 10.0120
+Metric avg l1_freq    : 52.9893
+Metric avg si_sdr     : 9.2871
+Train epoch: 219 Learning rate: 2.1493418393096127e-06
+Training loss: 0.097191
+Instr dry sdr: 12.9955 (Std: 5.0869)
+Instr dry l1_freq: 52.8392 (Std: 15.3718)
+Instr dry si_sdr: 12.0471 (Std: 7.0882)
+Instr other sdr: 6.7699 (Std: 3.6042)
+Instr other l1_freq: 52.4275 (Std: 13.8716)
+Instr other si_sdr: 5.9983 (Std: 3.6054)
+Metric avg sdr        : 9.8827
+Metric avg l1_freq    : 52.6334
+Metric avg si_sdr     : 9.0227
+Train epoch: 220 Learning rate: 2.041874747344132e-06
+Training loss: 0.090682
+Instr dry sdr: 13.0097 (Std: 5.0718)
+Instr dry l1_freq: 52.8619 (Std: 15.3403)
+Instr dry si_sdr: 12.0965 (Std: 6.9746)
+Instr other sdr: 6.7831 (Std: 3.5878)
+Instr other l1_freq: 52.5006 (Std: 13.8541)
+Instr other si_sdr: 6.0114 (Std: 3.5907)
+Metric avg sdr        : 9.8964
+Metric avg l1_freq    : 52.6813
+Metric avg si_sdr     : 9.0540