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32k-asahi/D_12000.pth

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32k-asahi/D_6000.pth

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32k-asahi/G_12000.pth

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32k-asahi/G_15000.pth

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32k-asahi/G_6000.pth

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32k-asahi/config.json

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+{
+  "train": {
+    "log_interval": 200,
+    "eval_interval": 1000,
+    "seed": 1234,
+    "epochs": 10000,
+    "learning_rate": 0.0001,
+    "betas": [
+      0.8,
+      0.99
+    ],
+    "eps": 1e-09,
+    "batch_size": 6,
+    "fp16_run": false,
+    "lr_decay": 0.999875,
+    "segment_size": 17920,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0,
+    "use_sr": true,
+    "max_speclen": 384,
+    "port": "8001"
+  },
+  "data": {
+    "training_files": "filelists/train.txt",
+    "validation_files": "filelists/val.txt",
+    "max_wav_value": 32768.0,
+    "sampling_rate": 32000,
+    "filter_length": 1280,
+    "hop_length": 320,
+    "win_length": 1280,
+    "n_mel_channels": 80,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0.1,
+    "resblock": "1",
+    "resblock_kernel_sizes": [
+      3,
+      7,
+      11
+    ],
+    "resblock_dilation_sizes": [
+      [
+        1,
+        3,
+        5
+      ],
+      [
+        1,
+        3,
+        5
+      ],
+      [
+        1,
+        3,
+        5
+      ]
+    ],
+    "upsample_rates": [
+      10,
+      8,
+      2,
+      2
+    ],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [
+      16,
+      16,
+      4,
+      4
+    ],
+    "n_layers_q": 3,
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "ssl_dim": 256,
+    "n_speakers": 2
+  },
+  "spk": {
+    "asahi": 0
+  }
+}

32k-asahi/train.log

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+2023-02-18 13:15:36,723	32k	INFO	{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 10000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 6, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 17920, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'use_sr': True, 'max_speclen': 384, 'port': '8001'}, 'data': {'training_files': 'filelists/train.txt', 'validation_files': 'filelists/val.txt', 'max_wav_value': 32768.0, 'sampling_rate': 32000, 'filter_length': 1280, 'hop_length': 320, 'win_length': 1280, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256, 'ssl_dim': 256, 'n_speakers': 2}, 'spk': {'asahi': 0}, 'model_dir': './logs\\32k'}
+2023-02-18 13:15:36,724	32k	WARNING	K:\AI\so-vits-svc-32k is not a git repository, therefore hash value comparison will be ignored.
+2023-02-18 13:16:46,085	32k	INFO	{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 10000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 6, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 17920, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'use_sr': True, 'max_speclen': 384, 'port': '8001'}, 'data': {'training_files': 'filelists/train.txt', 'validation_files': 'filelists/val.txt', 'max_wav_value': 32768.0, 'sampling_rate': 32000, 'filter_length': 1280, 'hop_length': 320, 'win_length': 1280, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256, 'ssl_dim': 256, 'n_speakers': 2}, 'spk': {'asahi': 0}, 'model_dir': './logs\\32k'}
+2023-02-18 13:16:46,086	32k	WARNING	K:\AI\so-vits-svc-32k is not a git repository, therefore hash value comparison will be ignored.
+2023-02-18 13:16:51,625	32k	INFO	emb_g.weight is not in the checkpoint
+2023-02-18 13:16:51,737	32k	INFO	Loaded checkpoint './logs\32k\G_0.pth' (iteration 1)
+2023-02-18 13:16:52,797	32k	INFO	Loaded checkpoint './logs\32k\D_0.pth' (iteration 1)
+2023-02-18 13:17:24,697	32k	INFO	Train Epoch: 1 [0%]
+2023-02-18 13:17:24,698	32k	INFO	[3.3069984912872314, 2.2735390663146973, 12.671528816223145, 44.619842529296875, 10.824443817138672, 0, 0.0001]
+2023-02-18 13:17:30,498	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\G_0.pth
+2023-02-18 13:17:45,076	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\D_0.pth
+2023-02-18 13:19:47,084	32k	INFO	====> Epoch: 1
+2023-02-18 13:22:06,314	32k	INFO	====> Epoch: 2
+2023-02-18 13:23:20,386	32k	INFO	Train Epoch: 3 [44%]
+2023-02-18 13:23:20,387	32k	INFO	[2.3857059478759766, 2.734795093536377, 12.341865539550781, 25.23939323425293, 1.1707755327224731, 200, 9.99750015625e-05]
+2023-02-18 13:24:25,089	32k	INFO	====> Epoch: 3
+2023-02-18 13:26:44,542	32k	INFO	====> Epoch: 4
+2023-02-18 13:28:50,668	32k	INFO	Train Epoch: 5 [88%]
+2023-02-18 13:28:50,668	32k	INFO	[2.599891185760498, 2.339749813079834, 8.97850513458252, 18.280649185180664, 1.2124148607254028, 400, 9.995000937421877e-05]
+2023-02-18 13:29:04,051	32k	INFO	====> Epoch: 5
+2023-02-18 13:31:22,495	32k	INFO	====> Epoch: 6
+2023-02-18 13:33:41,390	32k	INFO	====> Epoch: 7
+2023-02-18 13:34:46,904	32k	INFO	Train Epoch: 8 [32%]
+2023-02-18 13:34:46,904	32k	INFO	[2.428616523742676, 2.5334784984588623, 7.50093936920166, 13.943485260009766, 1.0122454166412354, 600, 9.991253280566489e-05]
+2023-02-18 13:36:46,611	32k	INFO	====> Epoch: 8
+2023-02-18 13:39:42,611	32k	INFO	====> Epoch: 9
+2023-02-18 13:42:01,156	32k	INFO	Train Epoch: 10 [76%]
+2023-02-18 13:42:01,156	32k	INFO	[2.539777994155884, 1.9696028232574463, 10.870598793029785, 20.18303680419922, 1.0394906997680664, 800, 9.98875562335968e-05]
+2023-02-18 13:42:36,519	32k	INFO	====> Epoch: 10
+2023-02-18 13:45:30,606	32k	INFO	====> Epoch: 11
+2023-02-18 13:48:27,421	32k	INFO	====> Epoch: 12
+2023-02-18 13:49:20,806	32k	INFO	Train Epoch: 13 [20%]
+2023-02-18 13:49:20,806	32k	INFO	[2.5772485733032227, 2.3823914527893066, 10.536639213562012, 20.34115219116211, 0.9894436597824097, 1000, 9.98501030820433e-05]
+2023-02-18 13:49:25,467	32k	INFO	Saving model and optimizer state at iteration 13 to ./logs\32k\G_1000.pth
+2023-02-18 13:49:42,627	32k	INFO	Saving model and optimizer state at iteration 13 to ./logs\32k\D_1000.pth
+2023-02-18 13:51:31,762	32k	INFO	====> Epoch: 13
+2023-02-18 13:53:49,535	32k	INFO	====> Epoch: 14
+2023-02-18 13:55:46,291	32k	INFO	Train Epoch: 15 [63%]
+2023-02-18 13:55:46,292	32k	INFO	[2.4663658142089844, 2.320800542831421, 11.314515113830566, 21.392370223999023, 1.4117159843444824, 1200, 9.982514211643064e-05]
+2023-02-18 13:56:38,705	32k	INFO	====> Epoch: 15
+2023-02-18 13:59:28,519	32k	INFO	====> Epoch: 16
+2023-02-18 14:02:17,766	32k	INFO	====> Epoch: 17
+2023-02-18 14:02:53,341	32k	INFO	Train Epoch: 18 [7%]
+2023-02-18 14:02:53,341	32k	INFO	[2.418344736099243, 2.726172924041748, 12.386476516723633, 20.22224998474121, 1.1661674976348877, 1400, 9.978771236724554e-05]
+2023-02-18 14:04:58,741	32k	INFO	====> Epoch: 18
+2023-02-18 14:07:40,854	32k	INFO	====> Epoch: 19
+2023-02-18 14:09:22,959	32k	INFO	Train Epoch: 20 [51%]
+2023-02-18 14:09:22,959	32k	INFO	[2.392646551132202, 2.6650896072387695, 11.132346153259277, 20.615514755249023, 1.3077448606491089, 1600, 9.976276699833672e-05]
+2023-02-18 14:10:37,010	32k	INFO	====> Epoch: 20
+2023-02-18 14:13:17,208	32k	INFO	====> Epoch: 21
+2023-02-18 14:15:24,422	32k	INFO	Train Epoch: 22 [95%]
+2023-02-18 14:15:24,423	32k	INFO	[2.4040393829345703, 2.239150047302246, 12.231693267822266, 20.794464111328125, 0.9484589695930481, 1800, 9.973782786538036e-05]
+2023-02-18 14:15:30,868	32k	INFO	====> Epoch: 22
+2023-02-18 14:17:59,875	32k	INFO	====> Epoch: 23
+2023-02-18 14:20:20,355	32k	INFO	====> Epoch: 24
+2023-02-18 14:21:30,802	32k	INFO	Train Epoch: 25 [39%]
+2023-02-18 14:21:30,802	32k	INFO	[2.4141862392425537, 2.3016927242279053, 13.739073753356934, 21.9274959564209, 1.2016680240631104, 2000, 9.970043085494672e-05]
+2023-02-18 14:21:35,541	32k	INFO	Saving model and optimizer state at iteration 25 to ./logs\32k\G_2000.pth
+2023-02-18 14:21:51,929	32k	INFO	Saving model and optimizer state at iteration 25 to ./logs\32k\D_2000.pth
+2023-02-18 14:23:05,507	32k	INFO	====> Epoch: 25
+2023-02-18 14:25:24,529	32k	INFO	====> Epoch: 26
+2023-02-18 14:27:25,212	32k	INFO	Train Epoch: 27 [83%]
+2023-02-18 14:27:25,212	32k	INFO	[2.485182285308838, 2.1557278633117676, 8.625478744506836, 17.08354377746582, 0.8900912404060364, 2200, 9.967550730505221e-05]
+2023-02-18 14:27:44,585	32k	INFO	====> Epoch: 27
+2023-02-18 14:30:04,953	32k	INFO	====> Epoch: 28
+2023-02-18 14:32:24,245	32k	INFO	====> Epoch: 29
+2023-02-18 14:33:19,017	32k	INFO	Train Epoch: 30 [27%]
+2023-02-18 14:33:19,018	32k	INFO	[2.314979076385498, 2.591787099838257, 8.379956245422363, 17.788272857666016, 0.9263051152229309, 2400, 9.963813366190753e-05]
+2023-02-18 14:34:43,546	32k	INFO	====> Epoch: 30
+2023-02-18 14:37:04,473	32k	INFO	====> Epoch: 31
+2023-02-18 14:38:51,951	32k	INFO	Train Epoch: 32 [71%]
+2023-02-18 14:38:51,952	32k	INFO	[2.530869960784912, 2.346663475036621, 9.290014266967773, 17.95098114013672, 0.8468811511993408, 2600, 9.961322568533789e-05]
+2023-02-18 14:39:25,876	32k	INFO	====> Epoch: 32
+2023-02-18 14:41:46,299	32k	INFO	====> Epoch: 33
+2023-02-18 14:44:06,079	32k	INFO	====> Epoch: 34
+2023-02-18 14:44:47,360	32k	INFO	Train Epoch: 35 [15%]
+2023-02-18 14:44:47,360	32k	INFO	[2.244014024734497, 2.303522825241089, 12.0291109085083, 20.503751754760742, 1.072399616241455, 2800, 9.957587539488128e-05]
+2023-02-18 14:46:28,086	32k	INFO	====> Epoch: 35
+2023-02-18 14:48:49,406	32k	INFO	====> Epoch: 36
+2023-02-18 14:50:21,699	32k	INFO	Train Epoch: 37 [59%]
+2023-02-18 14:50:21,700	32k	INFO	[2.5226240158081055, 2.235443115234375, 8.532631874084473, 17.06432342529297, 0.766471266746521, 3000, 9.95509829819056e-05]
+2023-02-18 14:50:26,448	32k	INFO	Saving model and optimizer state at iteration 37 to ./logs\32k\G_3000.pth
+2023-02-18 14:50:44,023	32k	INFO	Saving model and optimizer state at iteration 37 to ./logs\32k\D_3000.pth
+2023-02-18 14:51:35,085	32k	INFO	====> Epoch: 37
+2023-02-18 14:53:54,527	32k	INFO	====> Epoch: 38
+2023-02-18 14:56:14,690	32k	INFO	====> Epoch: 39
+2023-02-18 14:56:41,714	32k	INFO	Train Epoch: 40 [2%]
+2023-02-18 14:56:41,715	32k	INFO	[2.545912027359009, 2.1446070671081543, 11.442967414855957, 19.688390731811523, 1.1071820259094238, 3200, 9.951365602954526e-05]
+2023-02-18 14:58:35,254	32k	INFO	====> Epoch: 40
+2023-02-18 15:00:55,720	32k	INFO	====> Epoch: 41
+2023-02-18 15:02:14,254	32k	INFO	Train Epoch: 42 [46%]
+2023-02-18 15:02:14,256	32k	INFO	[2.4656083583831787, 2.3087027072906494, 8.831151962280273, 20.15584373474121, 0.6311391592025757, 3400, 9.948877917043875e-05]
+2023-02-18 15:03:21,337	32k	INFO	====> Epoch: 42
+2023-02-18 15:05:42,560	32k	INFO	====> Epoch: 43
+2023-02-18 15:07:53,352	32k	INFO	Train Epoch: 44 [90%]
+2023-02-18 15:07:53,353	32k	INFO	[2.423257827758789, 2.4318912029266357, 8.438339233398438, 18.954322814941406, 1.1647067070007324, 3600, 9.94639085301583e-05]
+2023-02-18 15:08:03,537	32k	INFO	====> Epoch: 44
+2023-02-18 15:10:23,855	32k	INFO	====> Epoch: 45
+2023-02-18 15:12:44,427	32k	INFO	====> Epoch: 46
+2023-02-18 15:13:48,785	32k	INFO	Train Epoch: 47 [34%]
+2023-02-18 15:13:48,786	32k	INFO	[2.1796677112579346, 2.7173850536346436, 11.570164680480957, 17.406679153442383, 1.1616911888122559, 3800, 9.942661422663591e-05]
+2023-02-18 15:15:05,864	32k	INFO	====> Epoch: 47
+2023-02-18 15:17:26,837	32k	INFO	====> Epoch: 48
+2023-02-18 15:19:22,655	32k	INFO	Train Epoch: 49 [78%]
+2023-02-18 15:19:22,656	32k	INFO	[2.7236239910125732, 2.036970376968384, 4.593118667602539, 7.638784408569336, 1.1607017517089844, 4000, 9.940175912662009e-05]
+2023-02-18 15:19:27,513	32k	INFO	Saving model and optimizer state at iteration 49 to ./logs\32k\G_4000.pth
+2023-02-18 15:19:45,391	32k	INFO	Saving model and optimizer state at iteration 49 to ./logs\32k\D_4000.pth
+2023-02-18 15:20:13,800	32k	INFO	====> Epoch: 49
+2023-02-18 15:22:33,780	32k	INFO	====> Epoch: 50
+2023-02-18 15:24:53,853	32k	INFO	====> Epoch: 51
+2023-02-18 15:25:43,949	32k	INFO	Train Epoch: 52 [22%]
+2023-02-18 15:25:43,949	32k	INFO	[2.6045544147491455, 2.4030346870422363, 10.298624992370605, 17.781221389770508, 0.9256278276443481, 4200, 9.936448812621091e-05]
+2023-02-18 15:27:14,911	32k	INFO	====> Epoch: 52
+2023-02-18 15:29:35,372	32k	INFO	====> Epoch: 53
+2023-02-18 15:31:16,948	32k	INFO	Train Epoch: 54 [66%]
+2023-02-18 15:31:16,948	32k	INFO	[2.4962995052337646, 2.134711503982544, 9.151311874389648, 16.35634422302246, 0.862859308719635, 4400, 9.933964855674948e-05]
+2023-02-18 15:31:56,360	32k	INFO	====> Epoch: 54
+2023-02-18 15:34:16,854	32k	INFO	====> Epoch: 55
+2023-02-18 15:36:36,402	32k	INFO	====> Epoch: 56
+2023-02-18 15:37:12,111	32k	INFO	Train Epoch: 57 [10%]
+2023-02-18 15:37:12,122	32k	INFO	[2.2373344898223877, 2.4235143661499023, 11.974388122558594, 18.775772094726562, 0.9912294745445251, 4600, 9.930240084489267e-05]
+2023-02-18 15:38:57,440	32k	INFO	====> Epoch: 57
+2023-02-18 15:41:17,548	32k	INFO	====> Epoch: 58
+2023-02-18 15:42:44,716	32k	INFO	Train Epoch: 59 [54%]
+2023-02-18 15:42:44,716	32k	INFO	[2.32612943649292, 2.505492687225342, 13.369050025939941, 21.683101654052734, 1.2278294563293457, 4800, 9.927757679628145e-05]
+2023-02-18 15:43:38,469	32k	INFO	====> Epoch: 59
+2023-02-18 15:45:59,553	32k	INFO	====> Epoch: 60
+2023-02-18 15:48:18,553	32k	INFO	Train Epoch: 61 [98%]
+2023-02-18 15:48:18,554	32k	INFO	[2.332657814025879, 2.309508800506592, 11.992413520812988, 21.970182418823242, 1.1714390516281128, 5000, 9.92527589532945e-05]
+2023-02-18 15:48:23,341	32k	INFO	Saving model and optimizer state at iteration 61 to ./logs\32k\G_5000.pth
+2023-02-18 15:48:41,872	32k	INFO	Saving model and optimizer state at iteration 61 to ./logs\32k\D_5000.pth
+2023-02-18 15:48:47,201	32k	INFO	====> Epoch: 61
+2023-02-18 15:51:06,990	32k	INFO	====> Epoch: 62
+2023-02-18 15:53:26,772	32k	INFO	====> Epoch: 63
+2023-02-18 15:54:39,947	32k	INFO	Train Epoch: 64 [41%]
+2023-02-18 15:54:39,947	32k	INFO	[2.581521987915039, 2.197911500930786, 10.526808738708496, 18.230852127075195, 0.5856090784072876, 5200, 9.921554382096622e-05]
+2023-02-18 15:56:05,134	32k	INFO	====> Epoch: 64
+2023-02-18 15:59:16,071	32k	INFO	====> Epoch: 65
+2023-02-18 16:02:00,609	32k	INFO	Train Epoch: 66 [85%]
+2023-02-18 16:02:00,610	32k	INFO	[2.4432015419006348, 2.4601447582244873, 11.853116989135742, 20.211322784423828, 0.9781383872032166, 5400, 9.919074148525384e-05]
+2023-02-18 16:02:23,489	32k	INFO	====> Epoch: 66
+2023-02-18 16:05:35,609	32k	INFO	====> Epoch: 67
+2023-02-18 16:08:44,666	32k	INFO	====> Epoch: 68
+2023-02-18 16:09:56,545	32k	INFO	Train Epoch: 69 [29%]
+2023-02-18 16:09:56,546	32k	INFO	[2.181422233581543, 2.8529210090637207, 11.916988372802734, 21.838470458984375, 1.0593645572662354, 5600, 9.915354960656915e-05]
+2023-02-18 16:11:49,999	32k	INFO	====> Epoch: 69
+2023-02-18 16:14:57,604	32k	INFO	====> Epoch: 70
+2023-02-18 16:17:27,420	32k	INFO	Train Epoch: 71 [73%]
+2023-02-18 16:17:27,420	32k	INFO	[1.9035147428512573, 3.021906852722168, 15.565659523010254, 21.79709815979004, 0.946706235408783, 5800, 9.912876276844171e-05]
+2023-02-18 16:18:11,589	32k	INFO	====> Epoch: 71
+2023-02-18 16:21:19,944	32k	INFO	====> Epoch: 72
+2023-02-18 16:24:31,441	32k	INFO	====> Epoch: 73
+2023-02-18 16:25:23,054	32k	INFO	Train Epoch: 74 [17%]
+2023-02-18 16:25:23,054	32k	INFO	[2.3623337745666504, 2.5799450874328613, 7.930063247680664, 17.0313777923584, 1.2069950103759766, 6000, 9.909159412887068e-05]
+2023-02-18 16:25:27,842	32k	INFO	Saving model and optimizer state at iteration 74 to ./logs\32k\G_6000.pth
+2023-02-18 16:25:48,638	32k	INFO	Saving model and optimizer state at iteration 74 to ./logs\32k\D_6000.pth
+2023-02-18 16:28:07,473	32k	INFO	====> Epoch: 74
+2023-02-18 16:31:15,829	32k	INFO	====> Epoch: 75
+2023-02-18 16:33:18,999	32k	INFO	Train Epoch: 76 [61%]
+2023-02-18 16:33:18,999	32k	INFO	[2.2943310737609863, 2.8715434074401855, 10.26145076751709, 14.741254806518555, 1.2504029273986816, 6200, 9.906682277864462e-05]
+2023-02-18 16:34:18,996	32k	INFO	====> Epoch: 76
+2023-02-18 16:37:25,713	32k	INFO	====> Epoch: 77
+2023-02-18 16:40:29,196	32k	INFO	====> Epoch: 78
+2023-02-18 16:41:01,456	32k	INFO	Train Epoch: 79 [5%]
+2023-02-18 16:41:01,457	32k	INFO	[2.1732935905456543, 2.650221347808838, 16.90458869934082, 23.275943756103516, 0.5908531546592712, 6400, 9.902967736366644e-05]
+2023-02-18 16:43:35,665	32k	INFO	====> Epoch: 79
+2023-02-18 16:46:40,281	32k	INFO	====> Epoch: 80
+2023-02-18 16:48:24,511	32k	INFO	Train Epoch: 81 [49%]
+2023-02-18 16:48:24,511	32k	INFO	[2.488065719604492, 2.189055919647217, 11.57202434539795, 20.690433502197266, 1.0104312896728516, 6600, 9.900492149166423e-05]
+2023-02-18 16:49:45,682	32k	INFO	====> Epoch: 81
+2023-02-18 16:52:48,841	32k	INFO	====> Epoch: 82
+2023-02-18 16:55:45,194	32k	INFO	Train Epoch: 83 [93%]
+2023-02-18 16:55:45,195	32k	INFO	[2.363006591796875, 2.5977485179901123, 11.85480785369873, 20.72893714904785, 1.1449049711227417, 6800, 9.89801718082432e-05]
+2023-02-18 16:55:54,936	32k	INFO	====> Epoch: 83
+2023-02-18 16:59:01,228	32k	INFO	====> Epoch: 84
+2023-02-18 17:02:06,730	32k	INFO	====> Epoch: 85
+2023-02-18 17:03:30,501	32k	INFO	Train Epoch: 86 [37%]
+2023-02-18 17:03:30,502	32k	INFO	[2.6049516201019287, 2.1475470066070557, 8.085922241210938, 17.217309951782227, 0.45161640644073486, 7000, 9.894305888331732e-05]
+2023-02-18 17:03:35,389	32k	INFO	Saving model and optimizer state at iteration 86 to ./logs\32k\G_7000.pth
+2023-02-18 17:03:53,165	32k	INFO	Saving model and optimizer state at iteration 86 to ./logs\32k\D_7000.pth
+2023-02-18 17:05:34,400	32k	INFO	====> Epoch: 86
+2023-02-18 17:08:41,181	32k	INFO	====> Epoch: 87
+2023-02-18 17:11:16,739	32k	INFO	Train Epoch: 88 [80%]
+2023-02-18 17:11:16,739	32k	INFO	[2.382134199142456, 2.5343871116638184, 9.086328506469727, 14.694384574890137, 0.7267480492591858, 7200, 9.891832466458178e-05]
+2023-02-18 17:11:47,110	32k	INFO	====> Epoch: 88
+2023-02-18 17:14:52,007	32k	INFO	====> Epoch: 89
+2023-02-18 17:17:56,142	32k	INFO	====> Epoch: 90
+2023-02-18 17:19:01,057	32k	INFO	Train Epoch: 91 [24%]
+2023-02-18 17:19:01,058	32k	INFO	[2.4476230144500732, 2.305821418762207, 8.499305725097656, 19.25327491760254, 0.8112967610359192, 7400, 9.888123492943583e-05]
+2023-02-18 17:21:03,549	32k	INFO	====> Epoch: 91
+2023-02-18 17:24:06,841	32k	INFO	====> Epoch: 92
+2023-02-18 17:26:22,681	32k	INFO	Train Epoch: 93 [68%]
+2023-02-18 17:26:22,688	32k	INFO	[2.185331344604492, 2.6872944831848145, 15.124022483825684, 21.444419860839844, 1.0479180812835693, 7600, 9.885651616572276e-05]
+2023-02-18 17:27:13,773	32k	INFO	====> Epoch: 93
+2023-02-18 17:30:21,451	32k	INFO	====> Epoch: 94
+2023-02-18 17:33:29,561	32k	INFO	====> Epoch: 95
+2023-02-18 17:34:13,186	32k	INFO	Train Epoch: 96 [12%]
+2023-02-18 17:34:13,187	32k	INFO	[2.347987174987793, 2.395303964614868, 9.463523864746094, 14.174880981445312, 0.40106111764907837, 7800, 9.881944960586671e-05]
+2023-02-18 17:36:35,656	32k	INFO	====> Epoch: 96
+2023-02-18 17:39:42,149	32k	INFO	====> Epoch: 97
+2023-02-18 17:41:37,677	32k	INFO	Train Epoch: 98 [56%]
+2023-02-18 17:41:37,677	32k	INFO	[2.503045082092285, 2.4578006267547607, 11.118446350097656, 18.708005905151367, 1.2328639030456543, 8000, 9.879474628751914e-05]
+2023-02-18 17:41:42,468	32k	INFO	Saving model and optimizer state at iteration 98 to ./logs\32k\G_8000.pth
+2023-02-18 17:41:59,137	32k	INFO	Saving model and optimizer state at iteration 98 to ./logs\32k\D_8000.pth
+2023-02-18 17:43:11,648	32k	INFO	====> Epoch: 98
+2023-02-18 17:46:14,721	32k	INFO	====> Epoch: 99
+2023-02-18 17:49:19,452	32k	INFO	====> Epoch: 100
+2023-02-18 17:49:43,660	32k	INFO	Train Epoch: 101 [0%]
+2023-02-18 17:49:43,660	32k	INFO	[2.5995795726776123, 2.3254148960113525, 7.9163641929626465, 16.673885345458984, 0.7785255908966064, 8200, 9.875770288847208e-05]
+2023-02-18 17:52:24,475	32k	INFO	====> Epoch: 101
+2023-02-18 17:55:27,166	32k	INFO	====> Epoch: 102
+2023-02-18 17:57:03,042	32k	INFO	Train Epoch: 103 [44%]
+2023-02-18 17:57:03,042	32k	INFO	[2.415909767150879, 2.438415288925171, 10.601877212524414, 19.733566284179688, 0.9555046558380127, 8400, 9.873301500583906e-05]
+2023-02-18 17:58:33,665	32k	INFO	====> Epoch: 103
+2023-02-18 18:01:38,657	32k	INFO	====> Epoch: 104
+2023-02-18 18:04:28,117	32k	INFO	Train Epoch: 105 [88%]
+2023-02-18 18:04:28,117	32k	INFO	[2.630995035171509, 2.1970698833465576, 10.794513702392578, 19.191852569580078, 0.7746363878250122, 8600, 9.870833329479095e-05]
+2023-02-18 18:04:45,705	32k	INFO	====> Epoch: 105
+2023-02-18 18:07:52,602	32k	INFO	====> Epoch: 106
+2023-02-18 18:10:57,947	32k	INFO	====> Epoch: 107
+2023-02-18 18:12:12,513	32k	INFO	Train Epoch: 108 [32%]
+2023-02-18 18:12:12,513	32k	INFO	[2.474118709564209, 2.5281760692596436, 7.3929548263549805, 14.464062690734863, 0.6939061880111694, 8800, 9.867132229656573e-05]
+2023-02-18 18:14:00,834	32k	INFO	====> Epoch: 108
+2023-02-18 18:17:07,249	32k	INFO	====> Epoch: 109
+2023-02-18 18:19:34,317	32k	INFO	Train Epoch: 110 [76%]
+2023-02-18 18:19:34,318	32k	INFO	[2.6343023777008057, 2.198140859603882, 9.245353698730469, 15.40959644317627, 0.5494029521942139, 9000, 9.864665600773098e-05]
+2023-02-18 18:19:39,249	32k	INFO	Saving model and optimizer state at iteration 110 to ./logs\32k\G_9000.pth
+2023-02-18 18:19:56,382	32k	INFO	Saving model and optimizer state at iteration 110 to ./logs\32k\D_9000.pth
+2023-02-18 18:20:37,170	32k	INFO	====> Epoch: 110
+2023-02-18 18:23:43,211	32k	INFO	====> Epoch: 111
+2023-02-18 18:26:56,368	32k	INFO	====> Epoch: 112
+2023-02-18 18:27:52,671	32k	INFO	Train Epoch: 113 [20%]
+2023-02-18 18:27:52,672	32k	INFO	[2.1823391914367676, 2.942514419555664, 12.15264892578125, 19.10240364074707, 0.7193117141723633, 9200, 9.86096681355974e-05]
+2023-02-18 18:30:11,006	32k	INFO	====> Epoch: 113
+2023-02-18 18:33:21,420	32k	INFO	====> Epoch: 114
+2023-02-18 18:35:32,306	32k	INFO	Train Epoch: 115 [63%]
+2023-02-18 18:35:32,306	32k	INFO	[2.3463950157165527, 2.4623875617980957, 13.173855781555176, 21.46563148498535, 0.5739250183105469, 9400, 9.858501725933955e-05]
+2023-02-18 18:36:30,806	32k	INFO	====> Epoch: 115
+2023-02-18 18:39:41,614	32k	INFO	====> Epoch: 116
+2023-02-18 18:42:56,740	32k	INFO	====> Epoch: 117
+2023-02-18 18:43:32,935	32k	INFO	Train Epoch: 118 [7%]
+2023-02-18 18:43:32,936	32k	INFO	[2.4906504154205322, 2.447946786880493, 11.754008293151855, 20.466285705566406, 0.8161544799804688, 9600, 9.854805249884741e-05]
+2023-02-18 18:46:10,002	32k	INFO	====> Epoch: 118
+2023-02-18 18:49:20,693	32k	INFO	====> Epoch: 119
+2023-02-18 18:51:10,250	32k	INFO	Train Epoch: 120 [51%]
+2023-02-18 18:51:10,251	32k	INFO	[2.4490957260131836, 2.738856077194214, 12.3360013961792, 19.310625076293945, 0.8394557237625122, 9800, 9.8523417025536e-05]
+2023-02-18 18:52:29,403	32k	INFO	====> Epoch: 120
+2023-02-18 18:55:31,737	32k	INFO	====> Epoch: 121
+2023-02-18 18:58:27,659	32k	INFO	Train Epoch: 122 [95%]
+2023-02-18 18:58:27,660	32k	INFO	[2.409554958343506, 2.3621697425842285, 13.538979530334473, 20.507600784301758, 1.1963660717010498, 10000, 9.8498787710708e-05]
+2023-02-18 18:58:32,617	32k	INFO	Saving model and optimizer state at iteration 122 to ./logs\32k\G_10000.pth
+2023-02-18 18:58:50,163	32k	INFO	Saving model and optimizer state at iteration 122 to ./logs\32k\D_10000.pth
+2023-02-18 18:58:59,800	32k	INFO	====> Epoch: 122
+2023-02-18 19:02:03,872	32k	INFO	====> Epoch: 123
+2023-02-18 19:05:06,686	32k	INFO	====> Epoch: 124
+2023-02-18 19:06:34,823	32k	INFO	Train Epoch: 125 [39%]
+2023-02-18 19:06:34,824	32k	INFO	[2.345095634460449, 2.178450345993042, 12.377983093261719, 19.660619735717773, 0.8193285465240479, 10200, 9.846185528225477e-05]
+2023-02-18 19:08:12,812	32k	INFO	====> Epoch: 125
+2023-02-18 19:11:15,775	32k	INFO	====> Epoch: 126
+2023-02-18 19:13:54,645	32k	INFO	Train Epoch: 127 [83%]
+2023-02-18 19:13:54,645	32k	INFO	[2.5806427001953125, 2.1979994773864746, 11.834625244140625, 18.687227249145508, 1.0435174703598022, 10400, 9.84372413569007e-05]
+2023-02-18 19:14:19,451	32k	INFO	====> Epoch: 127
+2023-02-18 19:17:26,036	32k	INFO	====> Epoch: 128
+2023-02-18 19:20:29,081	32k	INFO	====> Epoch: 129
+2023-02-18 19:21:35,465	32k	INFO	Train Epoch: 130 [27%]
+2023-02-18 19:21:35,466	32k	INFO	[2.351133346557617, 2.378753423690796, 10.939573287963867, 19.32187271118164, 0.8272395730018616, 10600, 9.840033200544528e-05]
+2023-02-18 19:23:33,960	32k	INFO	====> Epoch: 130
+2023-02-18 19:26:38,810	32k	INFO	====> Epoch: 131
+2023-02-18 19:28:57,008	32k	INFO	Train Epoch: 132 [71%]
+2023-02-18 19:28:57,048	32k	INFO	[2.4666779041290283, 2.4331767559051514, 12.116047859191895, 20.228519439697266, 1.3147556781768799, 10800, 9.837573345994909e-05]
+2023-02-18 19:29:43,726	32k	INFO	====> Epoch: 132
+2023-02-18 19:32:50,848	32k	INFO	====> Epoch: 133
+2023-02-18 19:35:56,257	32k	INFO	====> Epoch: 134
+2023-02-18 19:36:44,716	32k	INFO	Train Epoch: 135 [15%]
+2023-02-18 19:36:44,716	32k	INFO	[2.255558490753174, 2.5198585987091064, 12.21342945098877, 20.34984588623047, 1.0012221336364746, 11000, 9.833884717107196e-05]
+2023-02-18 19:36:49,985	32k	INFO	Saving model and optimizer state at iteration 135 to ./logs\32k\G_11000.pth
+2023-02-18 19:37:07,494	32k	INFO	Saving model and optimizer state at iteration 135 to ./logs\32k\D_11000.pth
+2023-02-18 19:39:27,828	32k	INFO	====> Epoch: 135
+2023-02-18 19:42:33,821	32k	INFO	====> Epoch: 136
+2023-02-18 19:44:35,721	32k	INFO	Train Epoch: 137 [59%]
+2023-02-18 19:44:35,721	32k	INFO	[2.6769304275512695, 2.0602264404296875, 9.101190567016602, 14.852888107299805, 0.7094751000404358, 11200, 9.831426399582366e-05]
+2023-02-18 19:45:41,712	32k	INFO	====> Epoch: 137
+2023-02-18 19:48:48,842	32k	INFO	====> Epoch: 138
+2023-02-18 19:51:55,030	32k	INFO	====> Epoch: 139
+2023-02-18 19:52:23,208	32k	INFO	Train Epoch: 140 [2%]
+2023-02-18 19:52:23,208	32k	INFO	[2.416285753250122, 2.515517234802246, 11.539551734924316, 18.85158348083496, 0.7964726090431213, 11400, 9.827740075511432e-05]
+2023-02-18 19:55:00,407	32k	INFO	====> Epoch: 140
+2023-02-18 19:58:07,313	32k	INFO	====> Epoch: 141
+2023-02-18 19:59:48,759	32k	INFO	Train Epoch: 142 [46%]
+2023-02-18 19:59:48,759	32k	INFO	[2.6437501907348633, 2.2807607650756836, 7.438623428344727, 16.5651798248291, 0.5293334126472473, 11600, 9.825283294050992e-05]
+2023-02-18 20:01:13,320	32k	INFO	====> Epoch: 142
+2023-02-18 20:04:19,009	32k	INFO	====> Epoch: 143
+2023-02-18 20:07:08,623	32k	INFO	Train Epoch: 144 [90%]
+2023-02-18 20:07:08,623	32k	INFO	[2.4082539081573486, 2.348365306854248, 13.17957878112793, 20.185009002685547, 1.1610592603683472, 11800, 9.822827126747529e-05]
+2023-02-18 20:07:22,174	32k	INFO	====> Epoch: 144
+2023-02-18 20:10:24,073	32k	INFO	====> Epoch: 145
+2023-02-18 20:13:29,961	32k	INFO	====> Epoch: 146
+2023-02-18 20:14:49,654	32k	INFO	Train Epoch: 147 [34%]
+2023-02-18 20:14:49,655	32k	INFO	[2.6301674842834473, 2.0582547187805176, 7.999320983886719, 13.03806209564209, 0.6115504503250122, 12000, 9.819144027000834e-05]
+2023-02-18 20:14:54,379	32k	INFO	Saving model and optimizer state at iteration 147 to ./logs\32k\G_12000.pth
+2023-02-18 20:15:13,472	32k	INFO	Saving model and optimizer state at iteration 147 to ./logs\32k\D_12000.pth
+2023-02-18 20:16:32,707	32k	INFO	====> Epoch: 147
+2023-02-18 20:18:51,573	32k	INFO	====> Epoch: 148
+2023-02-18 20:20:45,616	32k	INFO	Train Epoch: 149 [78%]
+2023-02-18 20:20:45,616	32k	INFO	[2.5716872215270996, 2.044759511947632, 7.352247714996338, 11.54852294921875, 0.6284887790679932, 12200, 9.816689394418209e-05]
+2023-02-18 20:21:09,668	32k	INFO	====> Epoch: 149
+2023-02-18 20:23:28,296	32k	INFO	====> Epoch: 150
+2023-02-18 20:25:46,478	32k	INFO	====> Epoch: 151
+2023-02-18 20:26:35,115	32k	INFO	Train Epoch: 152 [22%]
+2023-02-18 20:26:35,116	32k	INFO	[2.7496554851531982, 2.115495443344116, 8.033178329467773, 17.09941864013672, 0.5979650020599365, 12400, 9.813008596033443e-05]
+2023-02-18 20:28:04,631	32k	INFO	====> Epoch: 152
+2023-02-18 20:30:22,610	32k	INFO	====> Epoch: 153
+2023-02-18 20:32:02,056	32k	INFO	Train Epoch: 154 [66%]
+2023-02-18 20:32:02,057	32k	INFO	[2.5520501136779785, 2.038939952850342, 9.094746589660645, 17.24423599243164, 0.9727638959884644, 12600, 9.810555497212693e-05]
+2023-02-18 20:32:40,442	32k	INFO	====> Epoch: 154
+2023-02-18 20:34:58,936	32k	INFO	====> Epoch: 155
+2023-02-18 20:37:23,270	32k	INFO	====> Epoch: 156
+2023-02-18 20:37:58,290	32k	INFO	Train Epoch: 157 [10%]
+2023-02-18 20:37:58,290	32k	INFO	[2.4157652854919434, 2.302234411239624, 9.094962120056152, 15.25003433227539, 0.7912210822105408, 12800, 9.806876998751865e-05]
+2023-02-18 20:39:42,082	32k	INFO	====> Epoch: 157
+2023-02-18 20:42:09,378	32k	INFO	====> Epoch: 158
+2023-02-18 20:43:36,431	32k	INFO	Train Epoch: 159 [54%]
+2023-02-18 20:43:36,431	32k	INFO	[2.303689956665039, 2.5022518634796143, 12.047871589660645, 18.625017166137695, 0.8808897733688354, 13000, 9.804425432734629e-05]
+2023-02-18 20:43:40,953	32k	INFO	Saving model and optimizer state at iteration 159 to ./logs\32k\G_13000.pth
+2023-02-18 20:43:58,356	32k	INFO	Saving model and optimizer state at iteration 159 to ./logs\32k\D_13000.pth
+2023-02-18 20:44:54,917	32k	INFO	====> Epoch: 159
+2023-02-18 20:47:14,493	32k	INFO	====> Epoch: 160
+2023-02-18 20:49:30,972	32k	INFO	Train Epoch: 161 [98%]
+2023-02-18 20:49:30,973	32k	INFO	[2.311939001083374, 2.59867000579834, 12.213456153869629, 19.764371871948242, 0.9899132251739502, 13200, 9.801974479570593e-05]
+2023-02-18 20:49:32,766	32k	INFO	====> Epoch: 161
+2023-02-18 20:51:59,478	32k	INFO	====> Epoch: 162
+2023-02-18 20:55:31,794	32k	INFO	====> Epoch: 163
+2023-02-18 20:57:30,010	32k	INFO	Train Epoch: 164 [41%]
+2023-02-18 20:57:30,010	32k	INFO	[2.86376690864563, 1.865500807762146, 5.887643814086914, 11.784518241882324, 1.020143747329712, 13400, 9.798299198589162e-05]
+2023-02-18 20:59:20,512	32k	INFO	====> Epoch: 164
+2023-02-18 21:03:06,854	32k	INFO	====> Epoch: 165
+2023-02-18 21:06:30,117	32k	INFO	Train Epoch: 166 [85%]
+2023-02-18 21:06:30,117	32k	INFO	[2.325920343399048, 2.6557977199554443, 11.842923164367676, 20.726858139038086, 0.6900365352630615, 13600, 9.795849776887939e-05]
+2023-02-18 21:06:56,246	32k	INFO	====> Epoch: 166
+2023-02-18 21:10:48,496	32k	INFO	====> Epoch: 167
+2023-02-18 21:14:47,570	32k	INFO	====> Epoch: 168
+2023-02-18 21:16:21,507	32k	INFO	Train Epoch: 169 [29%]
+2023-02-18 21:16:21,507	32k	INFO	[2.5149126052856445, 2.531891345977783, 10.036737442016602, 18.885982513427734, 0.8873259425163269, 13800, 9.792176792382932e-05]
+2023-02-18 21:18:35,252	32k	INFO	====> Epoch: 169
+2023-02-18 21:22:06,753	32k	INFO	====> Epoch: 170
+2023-02-18 21:24:54,047	32k	INFO	Train Epoch: 171 [73%]
+2023-02-18 21:24:54,048	32k	INFO	[2.2129878997802734, 2.324878215789795, 15.463290214538574, 19.30773162841797, 0.8498368263244629, 14000, 9.789728901187598e-05]
+2023-02-18 21:25:03,662	32k	INFO	Saving model and optimizer state at iteration 171 to ./logs\32k\G_14000.pth
+2023-02-18 21:25:43,764	32k	INFO	Saving model and optimizer state at iteration 171 to ./logs\32k\D_14000.pth
+2023-02-18 21:26:48,302	32k	INFO	====> Epoch: 171
+2023-02-18 21:30:19,052	32k	INFO	====> Epoch: 172
+2023-02-18 21:33:46,770	32k	INFO	====> Epoch: 173
+2023-02-18 21:34:50,019	32k	INFO	Train Epoch: 174 [17%]
+2023-02-18 21:34:50,019	32k	INFO	[2.4638266563415527, 2.162075996398926, 9.001068115234375, 17.737350463867188, 0.4494396448135376, 14200, 9.786058211724074e-05]
+2023-02-18 21:37:15,289	32k	INFO	====> Epoch: 174
+2023-02-18 21:40:41,023	32k	INFO	====> Epoch: 175
+2023-02-18 21:43:06,569	32k	INFO	Train Epoch: 176 [61%]
+2023-02-18 21:43:06,570	32k	INFO	[2.4940695762634277, 2.29329514503479, 9.759041786193848, 15.883288383483887, 0.6593114137649536, 14400, 9.783611850078301e-05]
+2023-02-18 21:44:18,062	32k	INFO	====> Epoch: 176
+2023-02-18 21:47:51,907	32k	INFO	====> Epoch: 177
+2023-02-18 21:51:42,031	32k	INFO	====> Epoch: 178
+2023-02-18 21:52:30,304	32k	INFO	Train Epoch: 179 [5%]
+2023-02-18 21:52:30,305	32k	INFO	[2.24495267868042, 2.5450713634490967, 16.089956283569336, 20.423744201660156, 1.29641854763031, 14600, 9.779943454222217e-05]
+2023-02-18 21:55:35,640	32k	INFO	====> Epoch: 179
+2023-02-18 21:58:29,482	32k	INFO	====> Epoch: 180
+2023-02-18 22:00:10,005	32k	INFO	Train Epoch: 181 [49%]
+2023-02-18 22:00:10,005	32k	INFO	[2.0902342796325684, 2.3228907585144043, 15.107324600219727, 20.69207763671875, 0.6706202030181885, 14800, 9.777498621170277e-05]
+2023-02-18 22:01:19,615	32k	INFO	====> Epoch: 181
+2023-02-18 22:04:08,136	32k	INFO	====> Epoch: 182
+2023-02-18 22:06:51,660	32k	INFO	Train Epoch: 183 [93%]
+2023-02-18 22:06:51,662	32k	INFO	[2.6548900604248047, 2.4761009216308594, 8.531192779541016, 13.265990257263184, 0.7215445637702942, 15000, 9.7750543992884e-05]
+2023-02-18 22:07:00,968	32k	INFO	Saving model and optimizer state at iteration 183 to ./logs\32k\G_15000.pth
+2023-02-18 22:07:34,821	32k	INFO	Saving model and optimizer state at iteration 183 to ./logs\32k\D_15000.pth
+2023-02-18 22:07:54,739	32k	INFO	====> Epoch: 183
+2023-02-18 22:10:44,685	32k	INFO	====> Epoch: 184

32k-hiyo/D_12000.pth

@@ -0,0 +1,3 @@
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+size 561098185

32k-hiyo/D_6000.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 561098185

32k-hiyo/G_12000.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 699505437

32k-hiyo/G_6000.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 699505437

32k-hiyo/config.json

@@ -0,0 +1,90 @@
+{
+  "train": {
+    "log_interval": 200,
+    "eval_interval": 1000,
+    "seed": 1234,
+    "epochs": 10000,
+    "learning_rate": 0.0001,
+    "betas": [
+      0.8,
+      0.99
+    ],
+    "eps": 1e-09,
+    "batch_size": 6,
+    "fp16_run": false,
+    "lr_decay": 0.999875,
+    "segment_size": 17920,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0,
+    "use_sr": true,
+    "max_speclen": 384,
+    "port": "8001"
+  },
+  "data": {
+    "training_files": "filelists/train.txt",
+    "validation_files": "filelists/val.txt",
+    "max_wav_value": 32768.0,
+    "sampling_rate": 32000,
+    "filter_length": 1280,
+    "hop_length": 320,
+    "win_length": 1280,
+    "n_mel_channels": 80,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0.1,
+    "resblock": "1",
+    "resblock_kernel_sizes": [
+      3,
+      7,
+      11
+    ],
+    "resblock_dilation_sizes": [
+      [
+        1,
+        3,
+        5
+      ],
+      [
+        1,
+        3,
+        5
+      ],
+      [
+        1,
+        3,
+        5
+      ]
+    ],
+    "upsample_rates": [
+      10,
+      8,
+      2,
+      2
+    ],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [
+      16,
+      16,
+      4,
+      4
+    ],
+    "n_layers_q": 3,
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "ssl_dim": 256,
+    "n_speakers": 2
+  },
+  "spk": {
+    "hiyo": 0
+  }
+}

32k-hiyo/eval/events.out.tfevents.1676340776.DESKTOP-P582Q00.21940.1

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1754ba29492978a4370e854f2926a410478d586bfafb542d120fa5dcfc7e7dad
+size 19909795

32k-hiyo/train.log

@@ -0,0 +1,298 @@
+2023-02-14 13:12:41,308	32k	INFO	{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 10000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 6, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 17920, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'use_sr': True, 'max_speclen': 384, 'port': '8001'}, 'data': {'training_files': 'filelists/train.txt', 'validation_files': 'filelists/val.txt', 'max_wav_value': 32768.0, 'sampling_rate': 32000, 'filter_length': 1280, 'hop_length': 320, 'win_length': 1280, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256, 'ssl_dim': 256, 'n_speakers': 2}, 'spk': {'hiyo': 0}, 'model_dir': './logs\\32k'}
+2023-02-14 13:12:58,959	32k	INFO	Loaded checkpoint './logs\32k\G_0.pth' (iteration 1)
+2023-02-14 13:12:59,334	32k	INFO	Loaded checkpoint './logs\32k\D_0.pth' (iteration 1)
+2023-02-14 13:13:25,423	32k	INFO	Train Epoch: 1 [0%]
+2023-02-14 13:13:25,424	32k	INFO	[2.7184720039367676, 2.6034836769104004, 11.849114418029785, 47.374595642089844, 9.48661994934082, 0, 0.0001]
+2023-02-14 13:13:30,918	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\G_0.pth
+2023-02-14 13:13:47,803	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\D_0.pth
+2023-02-14 13:15:02,651	32k	INFO	====> Epoch: 1
+2023-02-14 13:16:34,036	32k	INFO	====> Epoch: 2
+2023-02-14 13:17:26,475	32k	INFO	Train Epoch: 3 [44%]
+2023-02-14 13:17:26,475	32k	INFO	[2.6585214138031006, 2.366513252258301, 10.955318450927734, 23.930110931396484, 1.0435259342193604, 200, 9.99750015625e-05]
+2023-02-14 13:18:05,652	32k	INFO	====> Epoch: 3
+2023-02-14 13:19:36,775	32k	INFO	====> Epoch: 4
+2023-02-14 13:20:59,955	32k	INFO	Train Epoch: 5 [88%]
+2023-02-14 13:20:59,955	32k	INFO	[2.501133441925049, 2.350158452987671, 9.644698143005371, 22.92068862915039, 0.7671791315078735, 400, 9.995000937421877e-05]
+2023-02-14 13:21:08,211	32k	INFO	====> Epoch: 5
+2023-02-14 13:22:39,553	32k	INFO	====> Epoch: 6
+2023-02-14 13:24:10,878	32k	INFO	====> Epoch: 7
+2023-02-14 13:24:54,687	32k	INFO	Train Epoch: 8 [32%]
+2023-02-14 13:24:54,688	32k	INFO	[2.5303597450256348, 2.077411413192749, 12.605754852294922, 22.12200355529785, 1.3761812448501587, 600, 9.991253280566489e-05]
+2023-02-14 13:25:42,491	32k	INFO	====> Epoch: 8
+2023-02-14 13:27:13,843	32k	INFO	====> Epoch: 9
+2023-02-14 13:28:28,606	32k	INFO	Train Epoch: 10 [76%]
+2023-02-14 13:28:28,606	32k	INFO	[2.6250500679016113, 2.1927847862243652, 10.148731231689453, 20.529062271118164, 0.5864875316619873, 800, 9.98875562335968e-05]
+2023-02-14 13:28:45,437	32k	INFO	====> Epoch: 10
+2023-02-14 13:30:16,681	32k	INFO	====> Epoch: 11
+2023-02-14 13:31:48,026	32k	INFO	====> Epoch: 12
+2023-02-14 13:32:23,413	32k	INFO	Train Epoch: 13 [20%]
+2023-02-14 13:32:23,413	32k	INFO	[2.4075894355773926, 2.307851791381836, 11.19032096862793, 22.16382598876953, 1.286623239517212, 1000, 9.98501030820433e-05]
+2023-02-14 13:32:27,543	32k	INFO	Saving model and optimizer state at iteration 13 to ./logs\32k\G_1000.pth
+2023-02-14 13:32:44,941	32k	INFO	Saving model and optimizer state at iteration 13 to ./logs\32k\D_1000.pth
+2023-02-14 13:33:44,326	32k	INFO	====> Epoch: 13
+2023-02-14 13:35:15,814	32k	INFO	====> Epoch: 14
+2023-02-14 13:36:22,132	32k	INFO	Train Epoch: 15 [63%]
+2023-02-14 13:36:22,132	32k	INFO	[2.5968217849731445, 2.164472818374634, 8.871170043945312, 20.146108627319336, 0.8499955534934998, 1200, 9.982514211643064e-05]
+2023-02-14 13:36:47,621	32k	INFO	====> Epoch: 15
+2023-02-14 13:38:19,098	32k	INFO	====> Epoch: 16
+2023-02-14 13:39:50,485	32k	INFO	====> Epoch: 17
+2023-02-14 13:40:17,300	32k	INFO	Train Epoch: 18 [7%]
+2023-02-14 13:40:17,300	32k	INFO	[2.55147647857666, 2.1380293369293213, 11.658864974975586, 21.447202682495117, 1.0160374641418457, 1400, 9.978771236724554e-05]
+2023-02-14 13:41:22,298	32k	INFO	====> Epoch: 18
+2023-02-14 13:42:53,875	32k	INFO	====> Epoch: 19
+2023-02-14 13:43:51,564	32k	INFO	Train Epoch: 20 [51%]
+2023-02-14 13:43:51,565	32k	INFO	[2.5742850303649902, 2.244190216064453, 8.551454544067383, 19.180246353149414, 0.9120607376098633, 1600, 9.976276699833672e-05]
+2023-02-14 13:44:25,617	32k	INFO	====> Epoch: 20
+2023-02-14 13:45:57,188	32k	INFO	====> Epoch: 21
+2023-02-14 13:47:25,925	32k	INFO	Train Epoch: 22 [95%]
+2023-02-14 13:47:25,925	32k	INFO	[2.5543036460876465, 2.2138490676879883, 10.766397476196289, 21.196224212646484, 0.7341710329055786, 1800, 9.973782786538036e-05]
+2023-02-14 13:47:29,068	32k	INFO	====> Epoch: 22
+2023-02-14 13:49:00,647	32k	INFO	====> Epoch: 23
+2023-02-14 13:50:32,139	32k	INFO	====> Epoch: 24
+2023-02-14 13:51:21,238	32k	INFO	Train Epoch: 25 [39%]
+2023-02-14 13:51:21,238	32k	INFO	[2.556088447570801, 2.2134010791778564, 11.56871223449707, 19.313758850097656, 1.033575177192688, 2000, 9.970043085494672e-05]
+2023-02-14 13:51:25,444	32k	INFO	Saving model and optimizer state at iteration 25 to ./logs\32k\G_2000.pth
+2023-02-14 13:51:42,644	32k	INFO	Saving model and optimizer state at iteration 25 to ./logs\32k\D_2000.pth
+2023-02-14 13:52:28,601	32k	INFO	====> Epoch: 25
+2023-02-14 13:54:00,018	32k	INFO	====> Epoch: 26
+2023-02-14 13:55:20,005	32k	INFO	Train Epoch: 27 [83%]
+2023-02-14 13:55:20,005	32k	INFO	[2.6195037364959717, 2.2152504920959473, 9.765068054199219, 19.97799301147461, 0.9908173680305481, 2200, 9.967550730505221e-05]
+2023-02-14 13:55:31,723	32k	INFO	====> Epoch: 27
+2023-02-14 13:57:03,227	32k	INFO	====> Epoch: 28
+2023-02-14 13:58:38,892	32k	INFO	====> Epoch: 29
+2023-02-14 13:59:19,484	32k	INFO	Train Epoch: 30 [27%]
+2023-02-14 13:59:19,484	32k	INFO	[2.4715116024017334, 2.2915375232696533, 13.360817909240723, 22.131193161010742, 1.3168777227401733, 2400, 9.963813366190753e-05]
+2023-02-14 14:00:10,655	32k	INFO	====> Epoch: 30
+2023-02-14 14:01:42,081	32k	INFO	====> Epoch: 31
+2023-02-14 14:02:53,596	32k	INFO	Train Epoch: 32 [71%]
+2023-02-14 14:02:53,596	32k	INFO	[2.593963384628296, 2.0387449264526367, 9.328591346740723, 17.955137252807617, 0.30882203578948975, 2600, 9.961322568533789e-05]
+2023-02-14 14:03:13,877	32k	INFO	====> Epoch: 32
+2023-02-14 14:04:45,281	32k	INFO	====> Epoch: 33
+2023-02-14 14:06:16,692	32k	INFO	====> Epoch: 34
+2023-02-14 14:06:48,668	32k	INFO	Train Epoch: 35 [15%]
+2023-02-14 14:06:48,669	32k	INFO	[2.5350048542022705, 1.9605062007904053, 7.99984884262085, 16.31661033630371, 0.5040841698646545, 2800, 9.957587539488128e-05]
+2023-02-14 14:07:48,449	32k	INFO	====> Epoch: 35
+2023-02-14 14:09:20,138	32k	INFO	====> Epoch: 36
+2023-02-14 14:10:23,083	32k	INFO	Train Epoch: 37 [59%]
+2023-02-14 14:10:23,083	32k	INFO	[2.4650959968566895, 2.2761664390563965, 9.025921821594238, 19.93177604675293, 0.5862252712249756, 3000, 9.95509829819056e-05]
+2023-02-14 14:10:27,302	32k	INFO	Saving model and optimizer state at iteration 37 to ./logs\32k\G_3000.pth
+2023-02-14 14:10:44,327	32k	INFO	Saving model and optimizer state at iteration 37 to ./logs\32k\D_3000.pth
+2023-02-14 14:11:16,616	32k	INFO	====> Epoch: 37
+2023-02-14 14:12:50,532	32k	INFO	====> Epoch: 38
+2023-02-14 14:14:23,408	32k	INFO	====> Epoch: 39
+2023-02-14 14:14:46,793	32k	INFO	Train Epoch: 40 [2%]
+2023-02-14 14:14:46,794	32k	INFO	[2.3914408683776855, 2.3529629707336426, 12.639781951904297, 19.53929901123047, 0.5159912109375, 3200, 9.951365602954526e-05]
+2023-02-14 14:15:55,371	32k	INFO	====> Epoch: 40
+2023-02-14 14:17:27,123	32k	INFO	====> Epoch: 41
+2023-02-14 14:18:21,616	32k	INFO	Train Epoch: 42 [46%]
+2023-02-14 14:18:21,616	32k	INFO	[2.4428353309631348, 2.258873462677002, 10.040135383605957, 17.569446563720703, 0.9567443132400513, 3400, 9.948877917043875e-05]
+2023-02-14 14:18:59,327	32k	INFO	====> Epoch: 42
+2023-02-14 14:20:31,127	32k	INFO	====> Epoch: 43
+2023-02-14 14:21:56,538	32k	INFO	Train Epoch: 44 [90%]
+2023-02-14 14:21:56,539	32k	INFO	[2.3611392974853516, 2.405252456665039, 12.823965072631836, 20.826034545898438, 0.8344462513923645, 3600, 9.94639085301583e-05]
+2023-02-14 14:22:03,119	32k	INFO	====> Epoch: 44
+2023-02-14 14:23:34,741	32k	INFO	====> Epoch: 45
+2023-02-14 14:25:06,470	32k	INFO	====> Epoch: 46
+2023-02-14 14:25:52,327	32k	INFO	Train Epoch: 47 [34%]
+2023-02-14 14:25:52,327	32k	INFO	[2.4644553661346436, 2.2366631031036377, 11.37562370300293, 20.556499481201172, 0.9424434304237366, 3800, 9.942661422663591e-05]
+2023-02-14 14:26:38,621	32k	INFO	====> Epoch: 47
+2023-02-14 14:28:10,337	32k	INFO	====> Epoch: 48
+2023-02-14 14:29:27,206	32k	INFO	Train Epoch: 49 [78%]
+2023-02-14 14:29:27,206	32k	INFO	[2.5212016105651855, 2.3413655757904053, 10.579129219055176, 19.582210540771484, 0.94678795337677, 4000, 9.940175912662009e-05]
+2023-02-14 14:29:31,315	32k	INFO	Saving model and optimizer state at iteration 49 to ./logs\32k\G_4000.pth
+2023-02-14 14:29:48,727	32k	INFO	Saving model and optimizer state at iteration 49 to ./logs\32k\D_4000.pth
+2023-02-14 14:30:07,524	32k	INFO	====> Epoch: 49
+2023-02-14 14:31:39,485	32k	INFO	====> Epoch: 50
+2023-02-14 14:33:11,385	32k	INFO	====> Epoch: 51
+2023-02-14 14:33:48,633	32k	INFO	Train Epoch: 52 [22%]
+2023-02-14 14:33:48,634	32k	INFO	[2.2625677585601807, 2.5999932289123535, 16.192663192749023, 21.976665496826172, 0.7557628750801086, 4200, 9.936448812621091e-05]
+2023-02-14 14:34:43,699	32k	INFO	====> Epoch: 52
+2023-02-14 14:36:15,604	32k	INFO	====> Epoch: 53
+2023-02-14 14:37:23,825	32k	INFO	Train Epoch: 54 [66%]
+2023-02-14 14:37:23,825	32k	INFO	[2.500643730163574, 2.2777493000030518, 8.213461875915527, 17.501588821411133, 0.7716516256332397, 4400, 9.933964855674948e-05]
+2023-02-14 14:37:47,647	32k	INFO	====> Epoch: 54
+2023-02-14 14:39:19,631	32k	INFO	====> Epoch: 55
+2023-02-14 14:40:51,967	32k	INFO	====> Epoch: 56
+2023-02-14 14:41:20,508	32k	INFO	Train Epoch: 57 [10%]
+2023-02-14 14:41:20,508	32k	INFO	[2.4037282466888428, 2.369466543197632, 11.0797758102417, 18.995946884155273, 0.6406805515289307, 4600, 9.930240084489267e-05]
+2023-02-14 14:42:23,986	32k	INFO	====> Epoch: 57
+2023-02-14 14:43:56,023	32k	INFO	====> Epoch: 58
+2023-02-14 14:44:55,964	32k	INFO	Train Epoch: 59 [54%]
+2023-02-14 14:44:55,965	32k	INFO	[2.243375778198242, 2.4461309909820557, 15.596379280090332, 22.729717254638672, 0.9244585037231445, 4800, 9.927757679628145e-05]
+2023-02-14 14:45:28,557	32k	INFO	====> Epoch: 59
+2023-02-14 14:47:00,367	32k	INFO	====> Epoch: 60
+2023-02-14 14:48:31,104	32k	INFO	Train Epoch: 61 [98%]
+2023-02-14 14:48:31,105	32k	INFO	[2.5503604412078857, 2.111229658126831, 8.807084083557129, 16.10047721862793, 1.107606053352356, 5000, 9.92527589532945e-05]
+2023-02-14 14:48:35,266	32k	INFO	Saving model and optimizer state at iteration 61 to ./logs\32k\G_5000.pth
+2023-02-14 14:48:51,439	32k	INFO	Saving model and optimizer state at iteration 61 to ./logs\32k\D_5000.pth
+2023-02-14 14:48:56,220	32k	INFO	====> Epoch: 61
+2023-02-14 14:50:27,858	32k	INFO	====> Epoch: 62
+2023-02-14 14:51:59,496	32k	INFO	====> Epoch: 63
+2023-02-14 14:52:50,498	32k	INFO	Train Epoch: 64 [41%]
+2023-02-14 14:52:50,498	32k	INFO	[2.603325128555298, 2.3429884910583496, 11.47877025604248, 19.95724868774414, 0.4535157382488251, 5200, 9.921554382096622e-05]
+2023-02-14 14:53:31,542	32k	INFO	====> Epoch: 64
+2023-02-14 14:55:03,278	32k	INFO	====> Epoch: 65
+2023-02-14 14:56:25,149	32k	INFO	Train Epoch: 66 [85%]
+2023-02-14 14:56:25,149	32k	INFO	[2.548145055770874, 2.1794002056121826, 8.618596076965332, 18.201990127563477, 0.42253807187080383, 5400, 9.919074148525384e-05]
+2023-02-14 14:56:35,169	32k	INFO	====> Epoch: 66
+2023-02-14 14:58:06,861	32k	INFO	====> Epoch: 67
+2023-02-14 14:59:38,893	32k	INFO	====> Epoch: 68
+2023-02-14 15:00:21,295	32k	INFO	Train Epoch: 69 [29%]
+2023-02-14 15:00:21,295	32k	INFO	[2.462594985961914, 2.514474868774414, 8.234503746032715, 16.56818962097168, 0.3946729898452759, 5600, 9.915354960656915e-05]
+2023-02-14 15:01:11,023	32k	INFO	====> Epoch: 69
+2023-02-14 15:02:42,743	32k	INFO	====> Epoch: 70
+2023-02-14 15:03:56,160	32k	INFO	Train Epoch: 71 [73%]
+2023-02-14 15:03:56,161	32k	INFO	[2.3674912452697754, 2.400963306427002, 11.68331241607666, 21.614397048950195, 0.8642704486846924, 5800, 9.912876276844171e-05]
+2023-02-14 15:04:14,926	32k	INFO	====> Epoch: 71
+2023-02-14 15:05:46,720	32k	INFO	====> Epoch: 72
+2023-02-14 15:07:18,452	32k	INFO	====> Epoch: 73
+2023-02-14 15:07:52,317	32k	INFO	Train Epoch: 74 [17%]
+2023-02-14 15:07:52,318	32k	INFO	[2.3848366737365723, 2.3195393085479736, 11.794806480407715, 20.811321258544922, 0.9752936959266663, 6000, 9.909159412887068e-05]
+2023-02-14 15:07:56,403	32k	INFO	Saving model and optimizer state at iteration 74 to ./logs\32k\G_6000.pth
+2023-02-14 15:08:11,990	32k	INFO	Saving model and optimizer state at iteration 74 to ./logs\32k\D_6000.pth
+2023-02-14 15:09:13,833	32k	INFO	====> Epoch: 74
+2023-02-14 15:10:45,810	32k	INFO	====> Epoch: 75
+2023-02-14 15:11:50,593	32k	INFO	Train Epoch: 76 [61%]
+2023-02-14 15:11:50,594	32k	INFO	[2.413219451904297, 2.3621764183044434, 11.660679817199707, 19.284757614135742, 0.46086761355400085, 6200, 9.906682277864462e-05]
+2023-02-14 15:12:17,911	32k	INFO	====> Epoch: 76
+2023-02-14 15:13:49,709	32k	INFO	====> Epoch: 77
+2023-02-14 15:15:21,342	32k	INFO	====> Epoch: 78
+2023-02-14 15:15:46,525	32k	INFO	Train Epoch: 79 [5%]
+2023-02-14 15:15:46,526	32k	INFO	[2.4900527000427246, 2.1775360107421875, 11.207487106323242, 18.59693717956543, 1.0485306978225708, 6400, 9.902967736366644e-05]
+2023-02-14 15:16:53,382	32k	INFO	====> Epoch: 79
+2023-02-14 15:18:25,180	32k	INFO	====> Epoch: 80
+2023-02-14 15:19:21,341	32k	INFO	Train Epoch: 81 [49%]
+2023-02-14 15:19:21,342	32k	INFO	[2.4466681480407715, 2.321159839630127, 10.79179573059082, 18.92087173461914, 0.9803774356842041, 6600, 9.900492149166423e-05]
+2023-02-14 15:19:57,171	32k	INFO	====> Epoch: 81
+2023-02-14 15:21:28,987	32k	INFO	====> Epoch: 82
+2023-02-14 15:22:56,286	32k	INFO	Train Epoch: 83 [93%]
+2023-02-14 15:22:56,287	32k	INFO	[2.425461530685425, 2.4654641151428223, 11.531881332397461, 20.07356071472168, 1.0066664218902588, 6800, 9.89801718082432e-05]
+2023-02-14 15:23:01,149	32k	INFO	====> Epoch: 83
+2023-02-14 15:24:32,889	32k	INFO	====> Epoch: 84
+2023-02-14 15:26:04,666	32k	INFO	====> Epoch: 85
+2023-02-14 15:26:52,217	32k	INFO	Train Epoch: 86 [37%]
+2023-02-14 15:26:52,217	32k	INFO	[2.526332378387451, 2.203555107116699, 11.341078758239746, 20.046627044677734, 1.3592050075531006, 7000, 9.894305888331732e-05]
+2023-02-14 15:26:56,417	32k	INFO	Saving model and optimizer state at iteration 86 to ./logs\32k\G_7000.pth
+2023-02-14 15:27:14,398	32k	INFO	Saving model and optimizer state at iteration 86 to ./logs\32k\D_7000.pth
+2023-02-14 15:28:02,287	32k	INFO	====> Epoch: 86
+2023-02-14 15:29:33,965	32k	INFO	====> Epoch: 87
+2023-02-14 15:30:52,509	32k	INFO	Train Epoch: 88 [80%]
+2023-02-14 15:30:52,509	32k	INFO	[2.5021166801452637, 2.4259166717529297, 8.362788200378418, 17.521188735961914, 1.4112741947174072, 7200, 9.891832466458178e-05]
+2023-02-14 15:31:05,995	32k	INFO	====> Epoch: 88
+2023-02-14 15:32:37,695	32k	INFO	====> Epoch: 89
+2023-02-14 15:34:09,432	32k	INFO	====> Epoch: 90
+2023-02-14 15:34:48,347	32k	INFO	Train Epoch: 91 [24%]
+2023-02-14 15:34:48,347	32k	INFO	[2.2584304809570312, 2.37516188621521, 11.344868659973145, 20.501863479614258, 0.8927188515663147, 7400, 9.888123492943583e-05]
+2023-02-14 15:35:41,516	32k	INFO	====> Epoch: 91
+2023-02-14 15:37:13,309	32k	INFO	====> Epoch: 92
+2023-02-14 15:38:23,255	32k	INFO	Train Epoch: 93 [68%]
+2023-02-14 15:38:23,256	32k	INFO	[2.407334327697754, 2.4313995838165283, 5.9084062576293945, 14.895120620727539, 0.34809207916259766, 7600, 9.885651616572276e-05]
+2023-02-14 15:38:45,350	32k	INFO	====> Epoch: 93
+2023-02-14 15:40:17,151	32k	INFO	====> Epoch: 94
+2023-02-14 15:41:48,881	32k	INFO	====> Epoch: 95
+2023-02-14 15:42:19,249	32k	INFO	Train Epoch: 96 [12%]
+2023-02-14 15:42:19,250	32k	INFO	[2.475175142288208, 2.287485361099243, 12.157411575317383, 19.902236938476562, 0.8755276799201965, 7800, 9.881944960586671e-05]
+2023-02-14 15:43:20,970	32k	INFO	====> Epoch: 96
+2023-02-14 15:44:52,717	32k	INFO	====> Epoch: 97
+2023-02-14 15:45:54,039	32k	INFO	Train Epoch: 98 [56%]
+2023-02-14 15:45:54,040	32k	INFO	[2.4083688259124756, 2.3332595825195312, 8.003752708435059, 16.818313598632812, 0.21219749748706818, 8000, 9.879474628751914e-05]
+2023-02-14 15:45:58,128	32k	INFO	Saving model and optimizer state at iteration 98 to ./logs\32k\G_8000.pth
+2023-02-14 15:46:17,546	32k	INFO	Saving model and optimizer state at iteration 98 to ./logs\32k\D_8000.pth
+2023-02-14 15:46:51,611	32k	INFO	====> Epoch: 98
+2023-02-14 15:48:23,605	32k	INFO	====> Epoch: 99
+2023-02-14 15:49:55,516	32k	INFO	====> Epoch: 100
+2023-02-14 15:50:17,192	32k	INFO	Train Epoch: 101 [0%]
+2023-02-14 15:50:17,193	32k	INFO	[2.4577560424804688, 2.4049196243286133, 9.910334587097168, 17.469593048095703, 1.0077900886535645, 8200, 9.875770288847208e-05]
+2023-02-14 15:51:27,581	32k	INFO	====> Epoch: 101
+2023-02-14 15:52:59,453	32k	INFO	====> Epoch: 102
+2023-02-14 15:53:52,351	32k	INFO	Train Epoch: 103 [44%]
+2023-02-14 15:53:52,352	32k	INFO	[2.3302505016326904, 2.4835445880889893, 12.40600299835205, 19.35659408569336, 1.1815543174743652, 8400, 9.873301500583906e-05]
+2023-02-14 15:54:31,690	32k	INFO	====> Epoch: 103
+2023-02-14 15:56:03,804	32k	INFO	====> Epoch: 104
+2023-02-14 15:57:27,545	32k	INFO	Train Epoch: 105 [88%]
+2023-02-14 15:57:27,546	32k	INFO	[2.442326068878174, 2.3513882160186768, 8.61225700378418, 19.59931755065918, 0.6629721522331238, 8600, 9.870833329479095e-05]
+2023-02-14 15:57:35,926	32k	INFO	====> Epoch: 105
+2023-02-14 15:59:07,717	32k	INFO	====> Epoch: 106
+2023-02-14 16:00:39,510	32k	INFO	====> Epoch: 107
+2023-02-14 16:01:23,648	32k	INFO	Train Epoch: 108 [32%]
+2023-02-14 16:01:23,649	32k	INFO	[2.329326629638672, 2.2350986003875732, 12.052788734436035, 20.033588409423828, 0.4254380762577057, 8800, 9.867132229656573e-05]
+2023-02-14 16:02:11,617	32k	INFO	====> Epoch: 108
+2023-02-14 16:03:43,324	32k	INFO	====> Epoch: 109
+2023-02-14 16:04:58,449	32k	INFO	Train Epoch: 110 [76%]
+2023-02-14 16:04:58,449	32k	INFO	[2.2845022678375244, 2.4646148681640625, 13.254862785339355, 20.803882598876953, 0.39776870608329773, 9000, 9.864665600773098e-05]
+2023-02-14 16:05:02,554	32k	INFO	Saving model and optimizer state at iteration 110 to ./logs\32k\G_9000.pth
+2023-02-14 16:05:20,872	32k	INFO	Saving model and optimizer state at iteration 110 to ./logs\32k\D_9000.pth
+2023-02-14 16:05:41,237	32k	INFO	====> Epoch: 110
+2023-02-14 16:07:12,826	32k	INFO	====> Epoch: 111
+2023-02-14 16:08:44,738	32k	INFO	====> Epoch: 112
+2023-02-14 16:09:20,227	32k	INFO	Train Epoch: 113 [20%]
+2023-02-14 16:09:20,228	32k	INFO	[2.4082977771759033, 2.255082845687866, 10.537095069885254, 17.689083099365234, 0.7687245607376099, 9200, 9.86096681355974e-05]
+2023-02-14 16:10:16,749	32k	INFO	====> Epoch: 113
+2023-02-14 16:11:48,707	32k	INFO	====> Epoch: 114
+2023-02-14 16:12:55,268	32k	INFO	Train Epoch: 115 [63%]
+2023-02-14 16:12:55,268	32k	INFO	[2.531501293182373, 2.146554946899414, 8.033232688903809, 17.08489990234375, 0.7147048115730286, 9400, 9.858501725933955e-05]
+2023-02-14 16:13:20,854	32k	INFO	====> Epoch: 115
+2023-02-14 16:14:52,750	32k	INFO	====> Epoch: 116
+2023-02-14 16:16:24,652	32k	INFO	====> Epoch: 117
+2023-02-14 16:16:51,576	32k	INFO	Train Epoch: 118 [7%]
+2023-02-14 16:16:51,576	32k	INFO	[2.305955648422241, 2.5261385440826416, 11.671979904174805, 17.262502670288086, 0.9132139682769775, 9600, 9.854805249884741e-05]
+2023-02-14 16:17:56,852	32k	INFO	====> Epoch: 118
+2023-02-14 16:19:28,743	32k	INFO	====> Epoch: 119
+2023-02-14 16:20:26,662	32k	INFO	Train Epoch: 120 [51%]
+2023-02-14 16:20:26,663	32k	INFO	[2.406419038772583, 2.3848094940185547, 12.830516815185547, 19.702857971191406, 0.9984562397003174, 9800, 9.8523417025536e-05]
+2023-02-14 16:21:00,932	32k	INFO	====> Epoch: 120
+2023-02-14 16:22:32,586	32k	INFO	====> Epoch: 121
+2023-02-14 16:24:01,646	32k	INFO	Train Epoch: 122 [95%]
+2023-02-14 16:24:01,646	32k	INFO	[2.6088125705718994, 2.3717613220214844, 7.807750225067139, 17.539306640625, 0.6654758453369141, 10000, 9.8498787710708e-05]
+2023-02-14 16:24:05,762	32k	INFO	Saving model and optimizer state at iteration 122 to ./logs\32k\G_10000.pth
+2023-02-14 16:24:21,684	32k	INFO	Saving model and optimizer state at iteration 122 to ./logs\32k\D_10000.pth
+2023-02-14 16:24:28,063	32k	INFO	====> Epoch: 122
+2023-02-14 16:26:00,976	32k	INFO	====> Epoch: 123
+2023-02-14 16:27:37,900	32k	INFO	====> Epoch: 124
+2023-02-14 16:28:33,348	32k	INFO	Train Epoch: 125 [39%]
+2023-02-14 16:28:33,348	32k	INFO	[2.4001426696777344, 2.470517158508301, 13.341828346252441, 17.714656829833984, 0.679930567741394, 10200, 9.846185528225477e-05]
+2023-02-14 16:29:19,086	32k	INFO	====> Epoch: 125
+2023-02-14 16:30:59,664	32k	INFO	====> Epoch: 126
+2023-02-14 16:32:28,289	32k	INFO	Train Epoch: 127 [83%]
+2023-02-14 16:32:28,290	32k	INFO	[2.491032600402832, 2.2914695739746094, 10.223406791687012, 18.337860107421875, 0.9281787872314453, 10400, 9.84372413569007e-05]
+2023-02-14 16:32:41,455	32k	INFO	====> Epoch: 127
+2023-02-14 16:34:22,334	32k	INFO	====> Epoch: 128
+2023-02-14 16:36:01,890	32k	INFO	====> Epoch: 129
+2023-02-14 16:36:43,266	32k	INFO	Train Epoch: 130 [27%]
+2023-02-14 16:36:43,266	32k	INFO	[2.5348987579345703, 2.291205883026123, 14.648847579956055, 19.59044647216797, 0.8180601596832275, 10600, 9.840033200544528e-05]
+2023-02-14 16:37:34,913	32k	INFO	====> Epoch: 130
+2023-02-14 16:39:06,291	32k	INFO	====> Epoch: 131
+2023-02-14 16:40:17,727	32k	INFO	Train Epoch: 132 [71%]
+2023-02-14 16:40:17,727	32k	INFO	[2.404866933822632, 2.1770548820495605, 9.80937671661377, 16.411579132080078, 0.1555909514427185, 10800, 9.837573345994909e-05]
+2023-02-14 16:40:37,992	32k	INFO	====> Epoch: 132
+2023-02-14 16:42:09,446	32k	INFO	====> Epoch: 133
+2023-02-14 16:43:42,676	32k	INFO	====> Epoch: 134
+2023-02-14 16:44:16,320	32k	INFO	Train Epoch: 135 [15%]
+2023-02-14 16:44:16,320	32k	INFO	[2.379476547241211, 2.3253965377807617, 12.204051971435547, 18.108963012695312, 0.6560300588607788, 11000, 9.833884717107196e-05]
+2023-02-14 16:44:20,463	32k	INFO	Saving model and optimizer state at iteration 135 to ./logs\32k\G_11000.pth
+2023-02-14 16:44:40,760	32k	INFO	Saving model and optimizer state at iteration 135 to ./logs\32k\D_11000.pth
+2023-02-14 16:45:43,602	32k	INFO	====> Epoch: 135
+2023-02-14 16:47:14,892	32k	INFO	====> Epoch: 136
+2023-02-14 16:48:17,804	32k	INFO	Train Epoch: 137 [59%]
+2023-02-14 16:48:17,804	32k	INFO	[2.182915210723877, 2.490650177001953, 13.673564910888672, 19.964622497558594, 0.8504718542098999, 11200, 9.831426399582366e-05]
+2023-02-14 16:48:46,586	32k	INFO	====> Epoch: 137
+2023-02-14 16:50:17,982	32k	INFO	====> Epoch: 138
+2023-02-14 16:51:49,652	32k	INFO	====> Epoch: 139
+2023-02-14 16:52:13,059	32k	INFO	Train Epoch: 140 [2%]
+2023-02-14 16:52:13,059	32k	INFO	[2.4849462509155273, 2.2978439331054688, 10.085766792297363, 16.271583557128906, 0.9613367915153503, 11400, 9.827740075511432e-05]
+2023-02-14 16:53:21,336	32k	INFO	====> Epoch: 140
+2023-02-14 16:54:52,874	32k	INFO	====> Epoch: 141
+2023-02-14 16:55:48,996	32k	INFO	Train Epoch: 142 [46%]
+2023-02-14 16:55:48,996	32k	INFO	[2.419895887374878, 2.231900215148926, 9.550468444824219, 15.956775665283203, 0.6037944555282593, 11600, 9.825283294050992e-05]
+2023-02-14 16:56:34,619	32k	INFO	====> Epoch: 142
+2023-02-14 16:58:12,965	32k	INFO	====> Epoch: 143
+2023-02-14 16:59:51,011	32k	INFO	Train Epoch: 144 [90%]
+2023-02-14 16:59:51,012	32k	INFO	[2.526609182357788, 2.2438442707061768, 9.708596229553223, 18.94228744506836, 0.6018266081809998, 11800, 9.822827126747529e-05]
+2023-02-14 16:59:58,459	32k	INFO	====> Epoch: 144
+2023-02-14 17:01:41,567	32k	INFO	====> Epoch: 145
+2023-02-14 17:03:19,851	32k	INFO	====> Epoch: 146
+2023-02-14 17:04:09,172	32k	INFO	Train Epoch: 147 [34%]
+2023-02-14 17:04:09,173	32k	INFO	[2.1274771690368652, 2.403050661087036, 14.53994083404541, 20.740161895751953, 0.8522300720214844, 12000, 9.819144027000834e-05]
+2023-02-14 17:04:13,341	32k	INFO	Saving model and optimizer state at iteration 147 to ./logs\32k\G_12000.pth
+2023-02-14 17:04:30,263	32k	INFO	Saving model and optimizer state at iteration 147 to ./logs\32k\D_12000.pth
+2023-02-14 17:05:36,434	32k	INFO	====> Epoch: 147

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32k-yuuka/train.log

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+2023-02-19 00:52:17,563	32k	INFO	{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 10000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 6, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 17920, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'use_sr': True, 'max_speclen': 384, 'port': '8001'}, 'data': {'training_files': 'filelists/train.txt', 'validation_files': 'filelists/val.txt', 'max_wav_value': 32768.0, 'sampling_rate': 32000, 'filter_length': 1280, 'hop_length': 320, 'win_length': 1280, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256, 'ssl_dim': 256, 'n_speakers': 2}, 'spk': {'yuuka': 0}, 'model_dir': './logs\\32k'}
+2023-02-19 00:52:17,563	32k	WARNING	K:\AI\so-vits-svc-32k is not a git repository, therefore hash value comparison will be ignored.
+2023-02-19 00:52:22,439	32k	INFO	Loaded checkpoint './logs\32k\G_0.pth' (iteration 1)
+2023-02-19 00:52:22,854	32k	INFO	Loaded checkpoint './logs\32k\D_0.pth' (iteration 1)
+2023-02-19 00:52:30,954	32k	INFO	Train Epoch: 1 [0%]
+2023-02-19 00:52:30,955	32k	INFO	[6.259579658508301, 2.384648084640503, 21.68582534790039, 51.37621307373047, 29.241214752197266, 0, 0.0001]
+2023-02-19 00:52:36,208	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\G_0.pth
+2023-02-19 00:52:55,481	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\D_0.pth
+2023-02-19 00:53:15,383	32k	INFO	====> Epoch: 1
+2023-02-19 00:53:35,194	32k	INFO	====> Epoch: 2
+2023-02-19 00:53:54,475	32k	INFO	====> Epoch: 3
+2023-02-19 00:54:14,074	32k	INFO	====> Epoch: 4
+2023-02-19 00:54:33,774	32k	INFO	====> Epoch: 5
+2023-02-19 00:54:53,292	32k	INFO	====> Epoch: 6
+2023-02-19 00:55:12,950	32k	INFO	====> Epoch: 7
+2023-02-19 00:55:32,408	32k	INFO	====> Epoch: 8
+2023-02-19 00:55:51,786	32k	INFO	====> Epoch: 9
+2023-02-19 00:56:11,304	32k	INFO	====> Epoch: 10
+2023-02-19 00:56:23,833	32k	INFO	Train Epoch: 11 [53%]
+2023-02-19 00:56:23,834	32k	INFO	[2.5820298194885254, 2.9517571926116943, 15.889677047729492, 22.983726501464844, 1.490109920501709, 200, 9.987507028906759e-05]
+2023-02-19 00:56:31,013	32k	INFO	====> Epoch: 11
+2023-02-19 00:56:50,430	32k	INFO	====> Epoch: 12
+2023-02-19 00:57:09,908	32k	INFO	====> Epoch: 13
+2023-02-19 00:57:29,328	32k	INFO	====> Epoch: 14
+2023-02-19 00:57:48,792	32k	INFO	====> Epoch: 15
+2023-02-19 00:58:08,199	32k	INFO	====> Epoch: 16
+2023-02-19 00:58:27,628	32k	INFO	====> Epoch: 17
+2023-02-19 00:58:47,154	32k	INFO	====> Epoch: 18
+2023-02-19 00:59:06,558	32k	INFO	====> Epoch: 19
+2023-02-19 00:59:26,031	32k	INFO	====> Epoch: 20
+2023-02-19 00:59:45,505	32k	INFO	====> Epoch: 21
+2023-02-19 00:59:50,417	32k	INFO	Train Epoch: 22 [5%]
+2023-02-19 00:59:50,417	32k	INFO	[2.3022522926330566, 2.7468957901000977, 13.526983261108398, 18.26525115966797, 1.2778617143630981, 400, 9.973782786538036e-05]
+2023-02-19 01:00:05,254	32k	INFO	====> Epoch: 22
+2023-02-19 01:00:24,645	32k	INFO	====> Epoch: 23
+2023-02-19 01:00:44,092	32k	INFO	====> Epoch: 24
+2023-02-19 01:01:03,835	32k	INFO	====> Epoch: 25
+2023-02-19 01:01:23,360	32k	INFO	====> Epoch: 26
+2023-02-19 01:01:43,029	32k	INFO	====> Epoch: 27
+2023-02-19 01:02:02,552	32k	INFO	====> Epoch: 28
+2023-02-19 01:02:22,021	32k	INFO	====> Epoch: 29
+2023-02-19 01:02:41,450	32k	INFO	====> Epoch: 30
+2023-02-19 01:03:00,956	32k	INFO	====> Epoch: 31
+2023-02-19 01:03:14,323	32k	INFO	Train Epoch: 32 [58%]
+2023-02-19 01:03:14,323	32k	INFO	[2.2709786891937256, 2.5444483757019043, 16.769325256347656, 22.406368255615234, 1.2876263856887817, 600, 9.961322568533789e-05]
+2023-02-19 01:03:20,673	32k	INFO	====> Epoch: 32
+2023-02-19 01:03:40,138	32k	INFO	====> Epoch: 33
+2023-02-19 01:03:59,566	32k	INFO	====> Epoch: 34
+2023-02-19 01:04:19,064	32k	INFO	====> Epoch: 35
+2023-02-19 01:04:38,491	32k	INFO	====> Epoch: 36
+2023-02-19 01:04:57,953	32k	INFO	====> Epoch: 37
+2023-02-19 01:05:17,368	32k	INFO	====> Epoch: 38
+2023-02-19 01:05:36,826	32k	INFO	====> Epoch: 39
+2023-02-19 01:05:56,268	32k	INFO	====> Epoch: 40
+2023-02-19 01:06:15,805	32k	INFO	====> Epoch: 41
+2023-02-19 01:06:35,572	32k	INFO	====> Epoch: 42
+2023-02-19 01:06:41,408	32k	INFO	Train Epoch: 43 [11%]
+2023-02-19 01:06:41,408	32k	INFO	[2.2252748012542725, 2.711310386657715, 18.655017852783203, 23.06989097595215, 0.9809578657150269, 800, 9.947634307304244e-05]
+2023-02-19 01:06:55,421	32k	INFO	====> Epoch: 43
+2023-02-19 01:07:15,100	32k	INFO	====> Epoch: 44
+2023-02-19 01:07:34,525	32k	INFO	====> Epoch: 45
+2023-02-19 09:58:01,753	32k	INFO	{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 10000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 6, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 17920, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'use_sr': True, 'max_speclen': 384, 'port': '8001'}, 'data': {'training_files': 'filelists/train.txt', 'validation_files': 'filelists/val.txt', 'max_wav_value': 32768.0, 'sampling_rate': 32000, 'filter_length': 1280, 'hop_length': 320, 'win_length': 1280, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256, 'ssl_dim': 256, 'n_speakers': 2}, 'spk': {'yuuka': 0}, 'model_dir': './logs\\32k'}
+2023-02-19 09:58:01,753	32k	WARNING	K:\AI\so-vits-svc-32k is not a git repository, therefore hash value comparison will be ignored.
+2023-02-19 09:58:06,761	32k	INFO	Loaded checkpoint './logs\32k\G_0.pth' (iteration 1)
+2023-02-19 09:58:07,189	32k	INFO	Loaded checkpoint './logs\32k\D_0.pth' (iteration 1)
+2023-02-19 09:58:15,314	32k	INFO	Train Epoch: 1 [0%]
+2023-02-19 09:58:15,315	32k	INFO	[4.885988712310791, 2.5791049003601074, 20.521387100219727, 48.8116455078125, 23.21308135986328, 0, 0.0001]
+2023-02-19 09:58:20,541	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\G_0.pth
+2023-02-19 09:58:38,703	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\D_0.pth
+2023-02-19 09:58:59,317	32k	INFO	====> Epoch: 1
+2023-02-19 09:59:19,529	32k	INFO	====> Epoch: 2
+2023-02-19 09:59:40,549	32k	INFO	====> Epoch: 3
+2023-02-19 10:00:00,988	32k	INFO	====> Epoch: 4
+2023-02-19 10:00:20,947	32k	INFO	====> Epoch: 5
+2023-02-19 10:00:40,486	32k	INFO	====> Epoch: 6
+2023-02-19 10:01:00,800	32k	INFO	====> Epoch: 7
+2023-02-19 10:01:24,452	32k	INFO	====> Epoch: 8
+2023-02-19 10:01:44,672	32k	INFO	====> Epoch: 9
+2023-02-19 10:02:04,480	32k	INFO	====> Epoch: 10
+2023-02-19 10:02:17,182	32k	INFO	Train Epoch: 11 [53%]
+2023-02-19 10:02:17,183	32k	INFO	[2.7012827396392822, 2.8637466430664062, 15.74413013458252, 22.798664093017578, 1.4917662143707275, 200, 9.987507028906759e-05]
+2023-02-19 10:02:24,886	32k	INFO	====> Epoch: 11
+2023-02-19 10:02:44,970	32k	INFO	====> Epoch: 12
+2023-02-19 10:03:05,381	32k	INFO	====> Epoch: 13
+2023-02-19 10:03:27,787	32k	INFO	====> Epoch: 14
+2023-02-19 10:03:48,128	32k	INFO	====> Epoch: 15
+2023-02-19 10:04:09,326	32k	INFO	====> Epoch: 16
+2023-02-19 10:04:30,931	32k	INFO	====> Epoch: 17
+2023-02-19 10:04:50,506	32k	INFO	====> Epoch: 18
+2023-02-19 10:05:10,053	32k	INFO	====> Epoch: 19
+2023-02-19 10:05:29,550	32k	INFO	====> Epoch: 20
+2023-02-19 10:05:49,075	32k	INFO	====> Epoch: 21
+2023-02-19 10:05:54,186	32k	INFO	Train Epoch: 22 [5%]
+2023-02-19 10:05:54,186	32k	INFO	[2.638063669204712, 2.1183853149414062, 12.34074878692627, 17.773197174072266, 1.2548296451568604, 400, 9.973782786538036e-05]
+2023-02-19 10:06:11,523	32k	INFO	====> Epoch: 22
+2023-02-19 10:06:31,785	32k	INFO	====> Epoch: 23
+2023-02-19 10:06:51,275	32k	INFO	====> Epoch: 24
+2023-02-19 10:07:10,746	32k	INFO	====> Epoch: 25
+2023-02-19 10:07:30,179	32k	INFO	====> Epoch: 26
+2023-02-19 10:07:49,638	32k	INFO	====> Epoch: 27
+2023-02-19 10:08:09,150	32k	INFO	====> Epoch: 28
+2023-02-19 10:08:28,647	32k	INFO	====> Epoch: 29
+2023-02-19 10:08:48,090	32k	INFO	====> Epoch: 30
+2023-02-19 10:09:07,588	32k	INFO	====> Epoch: 31
+2023-02-19 10:09:20,991	32k	INFO	Train Epoch: 32 [58%]
+2023-02-19 10:09:20,992	32k	INFO	[2.252321481704712, 2.6135807037353516, 16.764589309692383, 22.221206665039062, 1.2719413042068481, 600, 9.961322568533789e-05]
+2023-02-19 10:09:27,359	32k	INFO	====> Epoch: 32
+2023-02-19 10:09:46,836	32k	INFO	====> Epoch: 33
+2023-02-19 10:10:06,405	32k	INFO	====> Epoch: 34
+2023-02-19 10:10:25,867	32k	INFO	====> Epoch: 35
+2023-02-19 10:10:45,391	32k	INFO	====> Epoch: 36
+2023-02-19 10:11:04,848	32k	INFO	====> Epoch: 37
+2023-02-19 10:11:24,345	32k	INFO	====> Epoch: 38
+2023-02-19 10:11:43,820	32k	INFO	====> Epoch: 39
+2023-02-19 10:12:03,363	32k	INFO	====> Epoch: 40
+2023-02-19 10:12:22,862	32k	INFO	====> Epoch: 41
+2023-02-19 10:12:42,390	32k	INFO	====> Epoch: 42
+2023-02-19 10:12:48,119	32k	INFO	Train Epoch: 43 [11%]
+2023-02-19 10:12:48,119	32k	INFO	[2.34789776802063, 2.904107093811035, 18.322242736816406, 23.1386661529541, 0.9494408369064331, 800, 9.947634307304244e-05]
+2023-02-19 10:13:02,224	32k	INFO	====> Epoch: 43
+2023-02-19 10:13:22,121	32k	INFO	====> Epoch: 44
+2023-02-19 10:13:42,138	32k	INFO	====> Epoch: 45
+2023-02-19 10:14:03,880	32k	INFO	====> Epoch: 46
+2023-02-19 10:14:23,490	32k	INFO	====> Epoch: 47
+2023-02-19 10:14:43,058	32k	INFO	====> Epoch: 48
+2023-02-19 10:15:02,615	32k	INFO	====> Epoch: 49
+2023-02-19 10:15:22,189	32k	INFO	====> Epoch: 50
+2023-02-19 10:15:41,717	32k	INFO	====> Epoch: 51
+2023-02-19 10:16:01,286	32k	INFO	====> Epoch: 52
+2023-02-19 10:16:15,520	32k	INFO	Train Epoch: 53 [63%]
+2023-02-19 10:16:15,521	32k	INFO	[2.2673277854919434, 2.6267404556274414, 14.748597145080566, 20.428760528564453, 0.9188843965530396, 1000, 9.935206756519513e-05]
+2023-02-19 10:16:19,825	32k	INFO	Saving model and optimizer state at iteration 53 to ./logs\32k\G_1000.pth
+2023-02-19 10:16:38,782	32k	INFO	Saving model and optimizer state at iteration 53 to ./logs\32k\D_1000.pth
+2023-02-19 10:16:47,949	32k	INFO	====> Epoch: 53
+2023-02-19 10:17:11,828	32k	INFO	====> Epoch: 54
+2023-02-19 10:17:32,602	32k	INFO	====> Epoch: 55
+2023-02-19 10:17:54,697	32k	INFO	====> Epoch: 56
+2023-02-19 10:18:15,505	32k	INFO	====> Epoch: 57
+2023-02-19 10:18:36,471	32k	INFO	====> Epoch: 58
+2023-02-19 10:18:56,129	32k	INFO	====> Epoch: 59
+2023-02-19 10:19:15,687	32k	INFO	====> Epoch: 60
+2023-02-19 10:19:35,249	32k	INFO	====> Epoch: 61
+2023-02-19 10:19:54,920	32k	INFO	====> Epoch: 62
+2023-02-19 10:20:14,564	32k	INFO	====> Epoch: 63
+2023-02-19 10:20:21,217	32k	INFO	Train Epoch: 64 [16%]
+2023-02-19 10:20:21,217	32k	INFO	[2.6431660652160645, 2.1686131954193115, 11.168325424194336, 15.736719131469727, 0.8130778074264526, 1200, 9.921554382096622e-05]
+2023-02-19 10:20:34,458	32k	INFO	====> Epoch: 64
+2023-02-19 10:20:54,137	32k	INFO	====> Epoch: 65
+2023-02-19 10:21:13,820	32k	INFO	====> Epoch: 66
+2023-02-19 10:21:33,481	32k	INFO	====> Epoch: 67
+2023-02-19 10:21:53,127	32k	INFO	====> Epoch: 68
+2023-02-19 10:22:12,705	32k	INFO	====> Epoch: 69
+2023-02-19 10:22:32,335	32k	INFO	====> Epoch: 70
+2023-02-19 10:22:52,013	32k	INFO	====> Epoch: 71
+2023-02-19 10:23:11,631	32k	INFO	====> Epoch: 72
+2023-02-19 10:23:31,243	32k	INFO	====> Epoch: 73
+2023-02-19 10:23:46,491	32k	INFO	Train Epoch: 74 [68%]
+2023-02-19 10:23:46,491	32k	INFO	[2.523651361465454, 2.3198585510253906, 13.49683952331543, 19.15787124633789, 0.8243404626846313, 1400, 9.909159412887068e-05]
+2023-02-19 10:23:51,274	32k	INFO	====> Epoch: 74
+2023-02-19 10:24:10,913	32k	INFO	====> Epoch: 75
+2023-02-19 10:24:30,500	32k	INFO	====> Epoch: 76
+2023-02-19 10:24:50,118	32k	INFO	====> Epoch: 77
+2023-02-19 10:25:09,788	32k	INFO	====> Epoch: 78
+2023-02-19 10:25:29,434	32k	INFO	====> Epoch: 79
+2023-02-19 10:25:49,013	32k	INFO	====> Epoch: 80
+2023-02-19 10:26:08,630	32k	INFO	====> Epoch: 81
+2023-02-19 10:26:28,322	32k	INFO	====> Epoch: 82
+2023-02-19 10:26:47,986	32k	INFO	====> Epoch: 83
+2023-02-19 10:27:07,609	32k	INFO	====> Epoch: 84
+2023-02-19 10:27:15,126	32k	INFO	Train Epoch: 85 [21%]
+2023-02-19 10:27:15,126	32k	INFO	[2.234614610671997, 2.673915386199951, 15.113679885864258, 20.68456268310547, 0.9050352573394775, 1600, 9.895542831185631e-05]
+2023-02-19 10:27:27,568	32k	INFO	====> Epoch: 85
+2023-02-19 10:27:47,162	32k	INFO	====> Epoch: 86
+2023-02-19 10:28:06,803	32k	INFO	====> Epoch: 87
+2023-02-19 10:28:26,491	32k	INFO	====> Epoch: 88
+2023-02-19 10:28:46,205	32k	INFO	====> Epoch: 89
+2023-02-19 10:29:05,923	32k	INFO	====> Epoch: 90
+2023-02-19 10:29:25,543	32k	INFO	====> Epoch: 91
+2023-02-19 10:29:45,199	32k	INFO	====> Epoch: 92
+2023-02-19 10:30:04,872	32k	INFO	====> Epoch: 93
+2023-02-19 10:30:24,573	32k	INFO	====> Epoch: 94
+2023-02-19 10:30:40,658	32k	INFO	Train Epoch: 95 [74%]
+2023-02-19 10:30:40,658	32k	INFO	[2.3925275802612305, 2.410752773284912, 16.29819679260254, 21.02007484436035, 1.3434288501739502, 1800, 9.883180358131438e-05]
+2023-02-19 10:30:44,524	32k	INFO	====> Epoch: 95
+2023-02-19 10:31:04,176	32k	INFO	====> Epoch: 96
+2023-02-19 10:31:23,746	32k	INFO	====> Epoch: 97
+2023-02-19 10:31:43,345	32k	INFO	====> Epoch: 98
+2023-02-19 10:32:02,965	32k	INFO	====> Epoch: 99
+2023-02-19 10:32:22,613	32k	INFO	====> Epoch: 100
+2023-02-19 10:32:42,215	32k	INFO	====> Epoch: 101
+2023-02-19 10:33:01,781	32k	INFO	====> Epoch: 102
+2023-02-19 10:33:21,347	32k	INFO	====> Epoch: 103
+2023-02-19 10:33:40,936	32k	INFO	====> Epoch: 104
+2023-02-19 10:34:00,582	32k	INFO	====> Epoch: 105
+2023-02-19 10:34:08,972	32k	INFO	Train Epoch: 106 [26%]
+2023-02-19 10:34:08,972	32k	INFO	[2.4520838260650635, 2.415198564529419, 12.142949104309082, 16.184589385986328, 0.6698657274246216, 2000, 9.86959947531291e-05]
+2023-02-19 10:34:13,205	32k	INFO	Saving model and optimizer state at iteration 106 to ./logs\32k\G_2000.pth
+2023-02-19 10:34:31,330	32k	INFO	Saving model and optimizer state at iteration 106 to ./logs\32k\D_2000.pth
+2023-02-19 10:34:46,550	32k	INFO	====> Epoch: 106
+2023-02-19 10:35:06,128	32k	INFO	====> Epoch: 107
+2023-02-19 10:35:25,770	32k	INFO	====> Epoch: 108
+2023-02-19 10:35:45,316	32k	INFO	====> Epoch: 109
+2023-02-19 10:36:04,886	32k	INFO	====> Epoch: 110
+2023-02-19 10:36:24,494	32k	INFO	====> Epoch: 111
+2023-02-19 10:36:44,060	32k	INFO	====> Epoch: 112
+2023-02-19 10:37:03,612	32k	INFO	====> Epoch: 113
+2023-02-19 10:37:23,126	32k	INFO	====> Epoch: 114
+2023-02-19 10:37:42,791	32k	INFO	====> Epoch: 115
+2023-02-19 10:37:59,739	32k	INFO	Train Epoch: 116 [79%]
+2023-02-19 10:37:59,740	32k	INFO	[2.173581600189209, 2.597672939300537, 19.673391342163086, 20.529300689697266, 0.6353464722633362, 2200, 9.857269413218213e-05]
+2023-02-19 10:38:02,696	32k	INFO	====> Epoch: 116
+2023-02-19 10:38:22,357	32k	INFO	====> Epoch: 117
+2023-02-19 10:38:42,132	32k	INFO	====> Epoch: 118
+2023-02-19 10:39:01,840	32k	INFO	====> Epoch: 119
+2023-02-19 10:39:21,476	32k	INFO	====> Epoch: 120
+2023-02-19 10:39:41,098	32k	INFO	====> Epoch: 121
+2023-02-19 10:40:00,770	32k	INFO	====> Epoch: 122
+2023-02-19 10:40:20,435	32k	INFO	====> Epoch: 123
+2023-02-19 10:40:40,053	32k	INFO	====> Epoch: 124
+2023-02-19 10:40:59,685	32k	INFO	====> Epoch: 125
+2023-02-19 10:41:19,254	32k	INFO	====> Epoch: 126
+2023-02-19 10:41:28,468	32k	INFO	Train Epoch: 127 [32%]
+2023-02-19 10:41:28,468	32k	INFO	[2.2418031692504883, 2.729581356048584, 17.634613037109375, 18.02391815185547, 0.39771148562431335, 2400, 9.84372413569007e-05]
+2023-02-19 10:41:39,158	32k	INFO	====> Epoch: 127
+2023-02-19 10:41:58,736	32k	INFO	====> Epoch: 128
+2023-02-19 10:42:18,349	32k	INFO	====> Epoch: 129
+2023-02-19 10:42:37,898	32k	INFO	====> Epoch: 130
+2023-02-19 10:42:57,642	32k	INFO	====> Epoch: 131
+2023-02-19 10:43:17,176	32k	INFO	====> Epoch: 132
+2023-02-19 10:43:36,760	32k	INFO	====> Epoch: 133
+2023-02-19 10:43:56,375	32k	INFO	====> Epoch: 134
+2023-02-19 10:44:15,877	32k	INFO	====> Epoch: 135
+2023-02-19 10:44:35,387	32k	INFO	====> Epoch: 136
+2023-02-19 10:44:53,146	32k	INFO	Train Epoch: 137 [84%]
+2023-02-19 10:44:53,146	32k	INFO	[1.9678010940551758, 2.595189094543457, 15.501832962036133, 17.879207611083984, 0.4402991235256195, 2600, 9.831426399582366e-05]
+2023-02-19 10:44:55,266	32k	INFO	====> Epoch: 137
+2023-02-19 10:45:14,872	32k	INFO	====> Epoch: 138
+2023-02-19 10:45:34,425	32k	INFO	====> Epoch: 139
+2023-02-19 10:45:53,939	32k	INFO	====> Epoch: 140
+2023-02-19 10:46:13,513	32k	INFO	====> Epoch: 141
+2023-02-19 10:46:33,087	32k	INFO	====> Epoch: 142
+2023-02-19 10:46:52,703	32k	INFO	====> Epoch: 143
+2023-02-19 10:47:12,387	32k	INFO	====> Epoch: 144
+2023-02-19 10:47:31,975	32k	INFO	====> Epoch: 145
+2023-02-19 10:47:51,629	32k	INFO	====> Epoch: 146
+2023-02-19 10:48:11,263	32k	INFO	====> Epoch: 147
+2023-02-19 10:48:21,336	32k	INFO	Train Epoch: 148 [37%]
+2023-02-19 10:48:21,336	32k	INFO	[2.5357589721679688, 2.358914613723755, 13.429749488830566, 18.84111785888672, 1.1937034130096436, 2800, 9.817916633997459e-05]
+2023-02-19 10:48:31,130	32k	INFO	====> Epoch: 148
+2023-02-19 10:48:50,747	32k	INFO	====> Epoch: 149
+2023-02-19 10:49:10,411	32k	INFO	====> Epoch: 150
+2023-02-19 10:49:29,989	32k	INFO	====> Epoch: 151
+2023-02-19 10:49:49,583	32k	INFO	====> Epoch: 152
+2023-02-19 10:50:09,163	32k	INFO	====> Epoch: 153
+2023-02-19 10:50:28,800	32k	INFO	====> Epoch: 154
+2023-02-19 10:50:48,404	32k	INFO	====> Epoch: 155
+2023-02-19 10:51:08,009	32k	INFO	====> Epoch: 156
+2023-02-19 10:51:27,600	32k	INFO	====> Epoch: 157
+2023-02-19 10:51:46,235	32k	INFO	Train Epoch: 158 [89%]
+2023-02-19 10:51:46,236	32k	INFO	[2.284935712814331, 2.6029856204986572, 16.011905670166016, 19.070634841918945, 0.9385358095169067, 3000, 9.80565113912702e-05]
+2023-02-19 10:51:50,428	32k	INFO	Saving model and optimizer state at iteration 158 to ./logs\32k\G_3000.pth
+2023-02-19 10:52:08,420	32k	INFO	Saving model and optimizer state at iteration 158 to ./logs\32k\D_3000.pth
+2023-02-19 10:52:13,226	32k	INFO	====> Epoch: 158
+2023-02-19 10:52:32,753	32k	INFO	====> Epoch: 159
+2023-02-19 10:52:52,288	32k	INFO	====> Epoch: 160
+2023-02-19 10:53:11,815	32k	INFO	====> Epoch: 161
+2023-02-19 10:53:31,531	32k	INFO	====> Epoch: 162
+2023-02-19 10:53:51,096	32k	INFO	====> Epoch: 163
+2023-02-19 10:54:10,786	32k	INFO	====> Epoch: 164
+2023-02-19 10:54:30,334	32k	INFO	====> Epoch: 165
+2023-02-19 10:54:49,856	32k	INFO	====> Epoch: 166
+2023-02-19 10:55:09,469	32k	INFO	====> Epoch: 167
+2023-02-19 10:55:29,052	32k	INFO	====> Epoch: 168
+2023-02-19 10:55:39,985	32k	INFO	Train Epoch: 169 [42%]
+2023-02-19 10:55:39,985	32k	INFO	[2.055294990539551, 2.645547389984131, 18.572147369384766, 21.72458839416504, 0.7422290444374084, 3200, 9.792176792382932e-05]
+2023-02-19 10:55:48,948	32k	INFO	====> Epoch: 169
+2023-02-19 10:56:08,592	32k	INFO	====> Epoch: 170
+2023-02-19 10:56:28,191	32k	INFO	====> Epoch: 171
+2023-02-19 10:56:47,791	32k	INFO	====> Epoch: 172
+2023-02-19 10:57:07,401	32k	INFO	====> Epoch: 173
+2023-02-19 10:57:26,913	32k	INFO	====> Epoch: 174
+2023-02-19 10:57:46,480	32k	INFO	====> Epoch: 175
+2023-02-19 10:58:06,125	32k	INFO	====> Epoch: 176
+2023-02-19 10:58:25,833	32k	INFO	====> Epoch: 177
+2023-02-19 10:58:45,438	32k	INFO	====> Epoch: 178
+2023-02-19 10:59:04,582	32k	INFO	Train Epoch: 179 [95%]
+2023-02-19 10:59:04,583	32k	INFO	[2.4237661361694336, 2.700900077819824, 12.830799102783203, 15.212872505187988, 0.817108690738678, 3400, 9.779943454222217e-05]
+2023-02-19 10:59:05,360	32k	INFO	====> Epoch: 179
+2023-02-19 10:59:24,965	32k	INFO	====> Epoch: 180
+2023-02-19 10:59:44,593	32k	INFO	====> Epoch: 181
+2023-02-19 11:00:04,235	32k	INFO	====> Epoch: 182
+2023-02-19 11:00:23,857	32k	INFO	====> Epoch: 183
+2023-02-19 11:00:43,474	32k	INFO	====> Epoch: 184
+2023-02-19 11:01:03,074	32k	INFO	====> Epoch: 185
+2023-02-19 11:01:22,689	32k	INFO	====> Epoch: 186
+2023-02-19 11:01:42,329	32k	INFO	====> Epoch: 187
+2023-02-19 11:02:01,887	32k	INFO	====> Epoch: 188
+2023-02-19 11:02:21,485	32k	INFO	====> Epoch: 189
+2023-02-19 11:02:33,363	32k	INFO	Train Epoch: 190 [47%]
+2023-02-19 11:02:33,363	32k	INFO	[1.858404278755188, 3.373487949371338, 13.83063793182373, 16.426828384399414, 0.5386475324630737, 3600, 9.766504433460612e-05]
+2023-02-19 11:02:41,573	32k	INFO	====> Epoch: 190
+2023-02-19 11:03:01,193	32k	INFO	====> Epoch: 191
+2023-02-19 11:03:20,789	32k	INFO	====> Epoch: 192
+2023-02-19 11:03:40,453	32k	INFO	====> Epoch: 193
+2023-02-19 11:04:00,059	32k	INFO	====> Epoch: 194
+2023-02-19 11:04:19,651	32k	INFO	====> Epoch: 195
+2023-02-19 11:04:39,248	32k	INFO	====> Epoch: 196
+2023-02-19 11:04:58,894	32k	INFO	====> Epoch: 197
+2023-02-19 11:05:18,520	32k	INFO	====> Epoch: 198
+2023-02-19 11:05:38,110	32k	INFO	====> Epoch: 199
+2023-02-19 11:05:57,738	32k	INFO	====> Epoch: 200
+2023-02-19 11:06:01,790	32k	INFO	Train Epoch: 201 [0%]
+2023-02-19 11:06:01,790	32k	INFO	[2.286409854888916, 2.695997714996338, 20.394229888916016, 19.332231521606445, 0.7787021994590759, 3800, 9.753083879807726e-05]
+2023-02-19 11:06:17,635	32k	INFO	====> Epoch: 201
+2023-02-19 11:06:37,273	32k	INFO	====> Epoch: 202
+2023-02-19 11:06:56,889	32k	INFO	====> Epoch: 203
+2023-02-19 11:07:16,485	32k	INFO	====> Epoch: 204
+2023-02-19 11:07:36,099	32k	INFO	====> Epoch: 205
+2023-02-19 11:07:55,728	32k	INFO	====> Epoch: 206
+2023-02-19 11:08:15,343	32k	INFO	====> Epoch: 207
+2023-02-19 11:08:34,891	32k	INFO	====> Epoch: 208
+2023-02-19 11:08:54,540	32k	INFO	====> Epoch: 209
+2023-02-19 11:09:14,170	32k	INFO	====> Epoch: 210
+2023-02-19 11:09:26,797	32k	INFO	Train Epoch: 211 [53%]
+2023-02-19 11:09:26,798	32k	INFO	[2.2917189598083496, 2.7440385818481445, 15.518340110778809, 16.26446533203125, 0.6934877038002014, 4000, 9.740899380309685e-05]
+2023-02-19 11:09:31,011	32k	INFO	Saving model and optimizer state at iteration 211 to ./logs\32k\G_4000.pth
+2023-02-19 11:09:51,469	32k	INFO	Saving model and optimizer state at iteration 211 to ./logs\32k\D_4000.pth
+2023-02-19 11:10:02,495	32k	INFO	====> Epoch: 211
+2023-02-19 11:10:22,019	32k	INFO	====> Epoch: 212
+2023-02-19 11:10:41,554	32k	INFO	====> Epoch: 213
+2023-02-19 11:11:01,073	32k	INFO	====> Epoch: 214
+2023-02-19 11:11:20,612	32k	INFO	====> Epoch: 215
+2023-02-19 11:11:40,229	32k	INFO	====> Epoch: 216
+2023-02-19 11:11:59,823	32k	INFO	====> Epoch: 217
+2023-02-19 11:12:19,432	32k	INFO	====> Epoch: 218
+2023-02-19 11:12:38,982	32k	INFO	====> Epoch: 219
+2023-02-19 11:12:58,555	32k	INFO	====> Epoch: 220
+2023-02-19 11:13:18,155	32k	INFO	====> Epoch: 221
+2023-02-19 11:13:23,102	32k	INFO	Train Epoch: 222 [5%]
+2023-02-19 11:13:23,102	32k	INFO	[2.2692172527313232, 2.6678965091705322, 17.69780731201172, 20.136995315551758, 0.6864567995071411, 4200, 9.727514011608789e-05]
+2023-02-19 11:13:38,082	32k	INFO	====> Epoch: 222
+2023-02-19 11:13:57,751	32k	INFO	====> Epoch: 223
+2023-02-19 11:14:17,317	32k	INFO	====> Epoch: 224
+2023-02-19 11:14:36,905	32k	INFO	====> Epoch: 225
+2023-02-19 11:14:56,538	32k	INFO	====> Epoch: 226
+2023-02-19 11:15:16,180	32k	INFO	====> Epoch: 227
+2023-02-19 11:15:35,773	32k	INFO	====> Epoch: 228
+2023-02-19 11:15:55,427	32k	INFO	====> Epoch: 229
+2023-02-19 11:16:15,006	32k	INFO	====> Epoch: 230
+2023-02-19 11:16:34,619	32k	INFO	====> Epoch: 231
+2023-02-19 11:16:48,169	32k	INFO	Train Epoch: 232 [58%]
+2023-02-19 11:16:48,170	32k	INFO	[2.2375569343566895, 2.629099130630493, 15.8519868850708, 17.997573852539062, 0.4304458200931549, 4400, 9.715361456473177e-05]
+2023-02-19 11:16:54,566	32k	INFO	====> Epoch: 232
+2023-02-19 11:17:14,203	32k	INFO	====> Epoch: 233
+2023-02-19 11:17:33,790	32k	INFO	====> Epoch: 234
+2023-02-19 11:17:53,406	32k	INFO	====> Epoch: 235
+2023-02-19 11:18:13,072	32k	INFO	====> Epoch: 236
+2023-02-19 11:18:32,696	32k	INFO	====> Epoch: 237
+2023-02-19 11:18:52,331	32k	INFO	====> Epoch: 238
+2023-02-19 11:19:11,901	32k	INFO	====> Epoch: 239
+2023-02-19 11:19:31,520	32k	INFO	====> Epoch: 240
+2023-02-19 11:19:51,132	32k	INFO	====> Epoch: 241
+2023-02-19 11:20:10,731	32k	INFO	====> Epoch: 242
+2023-02-19 11:20:16,470	32k	INFO	Train Epoch: 243 [11%]
+2023-02-19 11:20:16,470	32k	INFO	[2.1481809616088867, 2.5824615955352783, 14.348868370056152, 17.293001174926758, 0.6088849902153015, 4600, 9.702011180479129e-05]
+2023-02-19 11:20:30,580	32k	INFO	====> Epoch: 243
+2023-02-19 11:20:50,191	32k	INFO	====> Epoch: 244
+2023-02-19 11:21:09,779	32k	INFO	====> Epoch: 245
+2023-02-19 11:21:29,444	32k	INFO	====> Epoch: 246
+2023-02-19 11:21:49,014	32k	INFO	====> Epoch: 247
+2023-02-19 11:22:08,589	32k	INFO	====> Epoch: 248
+2023-02-19 11:22:28,235	32k	INFO	====> Epoch: 249
+2023-02-19 11:22:47,886	32k	INFO	====> Epoch: 250
+2023-02-19 11:23:07,478	32k	INFO	====> Epoch: 251
+2023-02-19 11:23:27,108	32k	INFO	====> Epoch: 252
+2023-02-19 11:23:41,516	32k	INFO	Train Epoch: 253 [63%]
+2023-02-19 11:23:41,516	32k	INFO	[2.2075626850128174, 2.759037733078003, 16.229446411132812, 19.35388946533203, 0.7824491858482361, 4800, 9.689890485956725e-05]
+2023-02-19 11:23:47,056	32k	INFO	====> Epoch: 253
+2023-02-19 11:24:06,652	32k	INFO	====> Epoch: 254
+2023-02-19 11:24:26,228	32k	INFO	====> Epoch: 255
+2023-02-19 11:24:45,885	32k	INFO	====> Epoch: 256
+2023-02-19 11:25:05,450	32k	INFO	====> Epoch: 257
+2023-02-19 11:25:25,062	32k	INFO	====> Epoch: 258
+2023-02-19 11:25:44,680	32k	INFO	====> Epoch: 259
+2023-02-19 11:26:04,299	32k	INFO	====> Epoch: 260
+2023-02-19 11:26:23,879	32k	INFO	====> Epoch: 261
+2023-02-19 11:26:43,517	32k	INFO	====> Epoch: 262
+2023-02-19 11:27:03,127	32k	INFO	====> Epoch: 263
+2023-02-19 11:27:09,821	32k	INFO	Train Epoch: 264 [16%]
+2023-02-19 11:27:09,821	32k	INFO	[2.3156111240386963, 2.653826951980591, 14.277311325073242, 16.898771286010742, 0.792119026184082, 5000, 9.676575210666227e-05]
+2023-02-19 11:27:14,004	32k	INFO	Saving model and optimizer state at iteration 264 to ./logs\32k\G_5000.pth
+2023-02-19 11:27:31,625	32k	INFO	Saving model and optimizer state at iteration 264 to ./logs\32k\D_5000.pth
+2023-02-19 11:27:48,527	32k	INFO	====> Epoch: 264
+2023-02-19 11:28:08,128	32k	INFO	====> Epoch: 265
+2023-02-19 11:28:27,718	32k	INFO	====> Epoch: 266
+2023-02-19 11:28:47,282	32k	INFO	====> Epoch: 267
+2023-02-19 11:29:06,849	32k	INFO	====> Epoch: 268
+2023-02-19 11:29:26,398	32k	INFO	====> Epoch: 269
+2023-02-19 11:29:45,966	32k	INFO	====> Epoch: 270
+2023-02-19 11:30:05,588	32k	INFO	====> Epoch: 271
+2023-02-19 11:30:25,210	32k	INFO	====> Epoch: 272
+2023-02-19 11:30:44,805	32k	INFO	====> Epoch: 273
+2023-02-19 11:31:00,163	32k	INFO	Train Epoch: 274 [68%]
+2023-02-19 11:31:00,163	32k	INFO	[2.5202348232269287, 2.6853830814361572, 12.198919296264648, 17.470657348632812, 1.010284423828125, 5200, 9.664486293227385e-05]
+2023-02-19 11:31:04,871	32k	INFO	====> Epoch: 274
+2023-02-19 11:31:24,524	32k	INFO	====> Epoch: 275
+2023-02-19 11:31:44,192	32k	INFO	====> Epoch: 276
+2023-02-19 11:32:03,771	32k	INFO	====> Epoch: 277
+2023-02-19 11:32:23,441	32k	INFO	====> Epoch: 278
+2023-02-19 11:32:43,028	32k	INFO	====> Epoch: 279
+2023-02-19 11:33:02,669	32k	INFO	====> Epoch: 280
+2023-02-19 11:33:22,327	32k	INFO	====> Epoch: 281
+2023-02-19 11:33:41,904	32k	INFO	====> Epoch: 282
+2023-02-19 11:34:01,510	32k	INFO	====> Epoch: 283
+2023-02-19 11:34:21,149	32k	INFO	====> Epoch: 284
+2023-02-19 11:34:28,645	32k	INFO	Train Epoch: 285 [21%]
+2023-02-19 11:34:28,645	32k	INFO	[2.1849722862243652, 2.6742019653320312, 17.45437240600586, 19.302379608154297, 0.47049564123153687, 5400, 9.651205926878348e-05]
+2023-02-19 11:34:41,074	32k	INFO	====> Epoch: 285
+2023-02-19 11:35:00,663	32k	INFO	====> Epoch: 286
+2023-02-19 11:35:20,204	32k	INFO	====> Epoch: 287
+2023-02-19 11:35:39,792	32k	INFO	====> Epoch: 288
+2023-02-19 11:35:59,412	32k	INFO	====> Epoch: 289
+2023-02-19 11:36:19,030	32k	INFO	====> Epoch: 290
+2023-02-19 11:36:38,610	32k	INFO	====> Epoch: 291
+2023-02-19 11:36:58,221	32k	INFO	====> Epoch: 292
+2023-02-19 11:37:17,873	32k	INFO	====> Epoch: 293
+2023-02-19 11:37:37,744	32k	INFO	====> Epoch: 294
+2023-02-19 11:37:53,973	32k	INFO	Train Epoch: 295 [74%]
+2023-02-19 11:37:53,973	32k	INFO	[2.275301933288574, 2.737536907196045, 16.912981033325195, 20.602113723754883, 1.1094117164611816, 5600, 9.639148703212408e-05]
+2023-02-19 11:37:57,829	32k	INFO	====> Epoch: 295
+2023-02-19 11:38:17,495	32k	INFO	====> Epoch: 296
+2023-02-19 11:38:37,068	32k	INFO	====> Epoch: 297
+2023-02-19 11:38:56,622	32k	INFO	====> Epoch: 298
+2023-02-19 11:39:16,278	32k	INFO	====> Epoch: 299
+2023-02-19 11:39:35,894	32k	INFO	====> Epoch: 300
+2023-02-19 11:39:55,537	32k	INFO	====> Epoch: 301
+2023-02-19 11:40:15,105	32k	INFO	====> Epoch: 302
+2023-02-19 11:40:34,680	32k	INFO	====> Epoch: 303
+2023-02-19 11:40:54,337	32k	INFO	====> Epoch: 304
+2023-02-19 11:41:13,926	32k	INFO	====> Epoch: 305
+2023-02-19 11:41:22,265	32k	INFO	Train Epoch: 306 [26%]
+2023-02-19 11:41:22,266	32k	INFO	[2.1130294799804688, 2.605156660079956, 13.737504005432129, 18.2040958404541, 0.6517429351806641, 5800, 9.625903154283315e-05]
+2023-02-19 11:41:33,904	32k	INFO	====> Epoch: 306
+2023-02-19 11:41:53,551	32k	INFO	====> Epoch: 307
+2023-02-19 11:42:13,197	32k	INFO	====> Epoch: 308
+2023-02-19 11:42:32,740	32k	INFO	====> Epoch: 309
+2023-02-19 11:42:52,382	32k	INFO	====> Epoch: 310
+2023-02-19 11:43:12,004	32k	INFO	====> Epoch: 311
+2023-02-19 11:43:31,599	32k	INFO	====> Epoch: 312
+2023-02-19 11:43:51,218	32k	INFO	====> Epoch: 313
+2023-02-19 11:44:10,806	32k	INFO	====> Epoch: 314
+2023-02-19 11:44:30,411	32k	INFO	====> Epoch: 315
+2023-02-19 11:44:47,303	32k	INFO	Train Epoch: 316 [79%]
+2023-02-19 11:44:47,303	32k	INFO	[1.8626766204833984, 2.7689990997314453, 22.44615364074707, 18.596677780151367, 0.9108448028564453, 6000, 9.613877541298036e-05]
+2023-02-19 11:44:51,515	32k	INFO	Saving model and optimizer state at iteration 316 to ./logs\32k\G_6000.pth
+2023-02-19 11:45:09,459	32k	INFO	Saving model and optimizer state at iteration 316 to ./logs\32k\D_6000.pth
+2023-02-19 11:45:15,966	32k	INFO	====> Epoch: 316
+2023-02-19 11:45:35,566	32k	INFO	====> Epoch: 317
+2023-02-19 11:45:55,162	32k	INFO	====> Epoch: 318
+2023-02-19 11:46:14,676	32k	INFO	====> Epoch: 319
+2023-02-19 11:46:34,275	32k	INFO	====> Epoch: 320
+2023-02-19 11:46:53,846	32k	INFO	====> Epoch: 321
+2023-02-19 11:47:13,481	32k	INFO	====> Epoch: 322
+2023-02-19 11:47:33,118	32k	INFO	====> Epoch: 323
+2023-02-19 11:47:52,781	32k	INFO	====> Epoch: 324
+2023-02-19 11:48:12,412	32k	INFO	====> Epoch: 325
+2023-02-19 11:48:31,983	32k	INFO	====> Epoch: 326
+2023-02-19 11:48:41,283	32k	INFO	Train Epoch: 327 [32%]
+2023-02-19 11:48:41,283	32k	INFO	[2.134446620941162, 2.5606751441955566, 17.715618133544922, 18.039941787719727, 0.7827563285827637, 6200, 9.600666718507311e-05]
+2023-02-19 11:48:51,957	32k	INFO	====> Epoch: 327
+2023-02-19 11:49:11,559	32k	INFO	====> Epoch: 328
+2023-02-19 11:49:31,233	32k	INFO	====> Epoch: 329
+2023-02-19 11:49:50,840	32k	INFO	====> Epoch: 330
+2023-02-19 11:50:10,505	32k	INFO	====> Epoch: 331
+2023-02-19 11:50:30,086	32k	INFO	====> Epoch: 332
+2023-02-19 11:50:49,767	32k	INFO	====> Epoch: 333
+2023-02-19 11:51:09,467	32k	INFO	====> Epoch: 334
+2023-02-19 11:51:29,060	32k	INFO	====> Epoch: 335
+2023-02-19 11:51:48,709	32k	INFO	====> Epoch: 336
+2023-02-19 11:52:06,472	32k	INFO	Train Epoch: 337 [84%]
+2023-02-19 11:52:06,472	32k	INFO	[2.3614232540130615, 2.127523183822632, 13.096696853637695, 15.430811882019043, 1.0329926013946533, 6400, 9.588672633328296e-05]
+2023-02-19 11:52:08,588	32k	INFO	====> Epoch: 337
+2023-02-19 11:52:28,158	32k	INFO	====> Epoch: 338
+2023-02-19 11:52:47,762	32k	INFO	====> Epoch: 339
+2023-02-19 11:53:07,351	32k	INFO	====> Epoch: 340
+2023-02-19 11:53:26,929	32k	INFO	====> Epoch: 341
+2023-02-19 11:53:46,569	32k	INFO	====> Epoch: 342
+2023-02-19 11:54:06,210	32k	INFO	====> Epoch: 343
+2023-02-19 11:54:25,837	32k	INFO	====> Epoch: 344
+2023-02-19 11:54:45,483	32k	INFO	====> Epoch: 345
+2023-02-19 11:55:05,098	32k	INFO	====> Epoch: 346
+2023-02-19 11:55:24,762	32k	INFO	====> Epoch: 347
+2023-02-19 11:55:34,848	32k	INFO	Train Epoch: 348 [37%]
+2023-02-19 11:55:34,849	32k	INFO	[2.5325193405151367, 2.0467236042022705, 9.755393028259277, 12.007466316223145, 0.2873714864253998, 6600, 9.575496445633683e-05]
+2023-02-19 11:55:44,674	32k	INFO	====> Epoch: 348
+2023-02-19 11:56:04,439	32k	INFO	====> Epoch: 349
+2023-02-19 11:56:24,075	32k	INFO	====> Epoch: 350
+2023-02-19 11:56:43,652	32k	INFO	====> Epoch: 351
+2023-02-19 11:57:03,215	32k	INFO	====> Epoch: 352
+2023-02-19 11:57:22,843	32k	INFO	====> Epoch: 353
+2023-02-19 11:57:42,508	32k	INFO	====> Epoch: 354
+2023-02-19 11:58:02,106	32k	INFO	====> Epoch: 355
+2023-02-19 11:58:21,710	32k	INFO	====> Epoch: 356
+2023-02-19 11:58:41,438	32k	INFO	====> Epoch: 357
+2023-02-19 11:59:00,100	32k	INFO	Train Epoch: 358 [89%]
+2023-02-19 11:59:00,101	32k	INFO	[2.309570074081421, 2.5850276947021484, 13.4173583984375, 16.9825382232666, 0.4784981906414032, 6800, 9.56353380560381e-05]
+2023-02-19 11:59:01,366	32k	INFO	====> Epoch: 358
+2023-02-19 11:59:20,928	32k	INFO	====> Epoch: 359
+2023-02-19 11:59:40,589	32k	INFO	====> Epoch: 360
+2023-02-19 12:00:00,179	32k	INFO	====> Epoch: 361
+2023-02-19 12:00:19,818	32k	INFO	====> Epoch: 362
+2023-02-19 12:00:39,433	32k	INFO	====> Epoch: 363
+2023-02-19 12:00:59,077	32k	INFO	====> Epoch: 364
+2023-02-19 12:01:18,665	32k	INFO	====> Epoch: 365
+2023-02-19 12:01:38,287	32k	INFO	====> Epoch: 366
+2023-02-19 12:01:57,919	32k	INFO	====> Epoch: 367
+2023-02-19 12:02:17,535	32k	INFO	====> Epoch: 368
+2023-02-19 12:02:28,494	32k	INFO	Train Epoch: 369 [42%]
+2023-02-19 12:02:28,494	32k	INFO	[2.1438865661621094, 2.569798231124878, 18.708538055419922, 19.017616271972656, 0.3679341971874237, 7000, 9.550392162201736e-05]
+2023-02-19 12:02:32,717	32k	INFO	Saving model and optimizer state at iteration 369 to ./logs\32k\G_7000.pth
+2023-02-19 12:02:50,778	32k	INFO	Saving model and optimizer state at iteration 369 to ./logs\32k\D_7000.pth
+2023-02-19 12:03:03,651	32k	INFO	====> Epoch: 369
+2023-02-19 12:03:23,235	32k	INFO	====> Epoch: 370
+2023-02-19 12:03:42,803	32k	INFO	====> Epoch: 371
+2023-02-19 12:04:02,411	32k	INFO	====> Epoch: 372
+2023-02-19 12:04:21,953	32k	INFO	====> Epoch: 373
+2023-02-19 12:04:41,504	32k	INFO	====> Epoch: 374
+2023-02-19 12:05:01,114	32k	INFO	====> Epoch: 375
+2023-02-19 12:05:20,776	32k	INFO	====> Epoch: 376
+2023-02-19 12:05:40,345	32k	INFO	====> Epoch: 377
+2023-02-19 12:05:59,933	32k	INFO	====> Epoch: 378
+2023-02-19 12:06:19,091	32k	INFO	Train Epoch: 379 [95%]
+2023-02-19 12:06:19,091	32k	INFO	[2.0112531185150146, 3.151000499725342, 21.729772567749023, 17.626426696777344, 0.05288940668106079, 7200, 9.538460884880585e-05]
+2023-02-19 12:06:19,867	32k	INFO	====> Epoch: 379
+2023-02-19 12:06:39,460	32k	INFO	====> Epoch: 380
+2023-02-19 12:06:59,053	32k	INFO	====> Epoch: 381
+2023-02-19 12:07:18,709	32k	INFO	====> Epoch: 382
+2023-02-19 12:07:38,341	32k	INFO	====> Epoch: 383
+2023-02-19 12:07:57,934	32k	INFO	====> Epoch: 384
+2023-02-19 12:08:17,553	32k	INFO	====> Epoch: 385
+2023-02-19 12:08:37,236	32k	INFO	====> Epoch: 386
+2023-02-19 12:08:56,799	32k	INFO	====> Epoch: 387
+2023-02-19 12:09:16,406	32k	INFO	====> Epoch: 388
+2023-02-19 12:09:36,019	32k	INFO	====> Epoch: 389
+2023-02-19 12:09:47,851	32k	INFO	Train Epoch: 390 [47%]
+2023-02-19 12:09:47,851	32k	INFO	[2.3823697566986084, 2.554415702819824, 13.744731903076172, 18.62793731689453, 0.7019649147987366, 7400, 9.525353695205543e-05]
+2023-02-19 12:09:55,957	32k	INFO	====> Epoch: 390
+2023-02-19 12:10:15,602	32k	INFO	====> Epoch: 391
+2023-02-19 12:10:35,217	32k	INFO	====> Epoch: 392
+2023-02-19 12:10:54,874	32k	INFO	====> Epoch: 393
+2023-02-19 12:11:14,510	32k	INFO	====> Epoch: 394
+2023-02-19 12:11:34,263	32k	INFO	====> Epoch: 395
+2023-02-19 12:11:53,845	32k	INFO	====> Epoch: 396
+2023-02-19 12:12:13,473	32k	INFO	====> Epoch: 397
+2023-02-19 12:12:33,092	32k	INFO	====> Epoch: 398
+2023-02-19 12:12:52,723	32k	INFO	====> Epoch: 399
+2023-02-19 12:13:12,340	32k	INFO	====> Epoch: 400
+2023-02-19 12:13:16,360	32k	INFO	Train Epoch: 401 [0%]
+2023-02-19 12:13:16,361	32k	INFO	[2.060042381286621, 2.767242670059204, 16.21058464050293, 16.564598083496094, 0.580163836479187, 7600, 9.512264516656537e-05]
+2023-02-19 12:13:32,189	32k	INFO	====> Epoch: 401
+2023-02-19 12:13:51,798	32k	INFO	====> Epoch: 402
+2023-02-19 12:14:11,417	32k	INFO	====> Epoch: 403
+2023-02-19 12:14:31,034	32k	INFO	====> Epoch: 404
+2023-02-19 12:14:50,628	32k	INFO	====> Epoch: 405
+2023-02-19 12:15:10,268	32k	INFO	====> Epoch: 406
+2023-02-19 12:15:29,856	32k	INFO	====> Epoch: 407
+2023-02-19 12:15:49,473	32k	INFO	====> Epoch: 408
+2023-02-19 12:16:09,070	32k	INFO	====> Epoch: 409
+2023-02-19 12:16:28,647	32k	INFO	====> Epoch: 410
+2023-02-19 12:16:41,291	32k	INFO	Train Epoch: 411 [53%]
+2023-02-19 12:16:41,291	32k	INFO	[2.276326894760132, 2.791963815689087, 16.988666534423828, 16.02008819580078, 1.0126944780349731, 7800, 9.500380872092753e-05]
+2023-02-19 12:16:48,539	32k	INFO	====> Epoch: 411
+2023-02-19 12:17:08,149	32k	INFO	====> Epoch: 412
+2023-02-19 12:17:27,812	32k	INFO	====> Epoch: 413
+2023-02-19 12:17:47,415	32k	INFO	====> Epoch: 414
+2023-02-19 12:18:07,018	32k	INFO	====> Epoch: 415
+2023-02-19 12:18:26,626	32k	INFO	====> Epoch: 416
+2023-02-19 12:18:46,268	32k	INFO	====> Epoch: 417
+2023-02-19 12:19:05,865	32k	INFO	====> Epoch: 418
+2023-02-19 12:19:25,510	32k	INFO	====> Epoch: 419
+2023-02-19 12:19:45,050	32k	INFO	====> Epoch: 420
+2023-02-19 12:20:04,641	32k	INFO	====> Epoch: 421
+2023-02-19 12:20:09,552	32k	INFO	Train Epoch: 422 [5%]
+2023-02-19 12:20:09,552	32k	INFO	[1.8605238199234009, 2.7951276302337646, 22.017553329467773, 20.881940841674805, 0.5991621017456055, 8000, 9.487326009722552e-05]
+2023-02-19 12:20:13,861	32k	INFO	Saving model and optimizer state at iteration 422 to ./logs\32k\G_8000.pth
+2023-02-19 12:20:30,750	32k	INFO	Saving model and optimizer state at iteration 422 to ./logs\32k\D_8000.pth
+2023-02-19 12:20:49,367	32k	INFO	====> Epoch: 422
+2023-02-19 12:21:09,253	32k	INFO	====> Epoch: 423
+2023-02-19 12:21:29,092	32k	INFO	====> Epoch: 424
+2023-02-19 12:21:48,850	32k	INFO	====> Epoch: 425
+2023-02-19 12:22:08,448	32k	INFO	====> Epoch: 426
+2023-02-19 12:22:28,085	32k	INFO	====> Epoch: 427
+2023-02-19 12:22:47,686	32k	INFO	====> Epoch: 428
+2023-02-19 12:23:07,278	32k	INFO	====> Epoch: 429
+2023-02-19 12:23:27,118	32k	INFO	====> Epoch: 430
+2023-02-19 12:23:46,825	32k	INFO	====> Epoch: 431
+2023-02-19 12:24:00,324	32k	INFO	Train Epoch: 432 [58%]
+2023-02-19 12:24:00,325	32k	INFO	[2.2748827934265137, 2.393998861312866, 16.518442153930664, 15.991931915283203, 0.6844744086265564, 8200, 9.475473520763392e-05]
+2023-02-19 12:24:06,743	32k	INFO	====> Epoch: 432
+2023-02-19 12:24:26,417	32k	INFO	====> Epoch: 433
+2023-02-19 12:24:46,429	32k	INFO	====> Epoch: 434
+2023-02-19 12:25:06,352	32k	INFO	====> Epoch: 435
+2023-02-19 12:25:26,166	32k	INFO	====> Epoch: 436
+2023-02-19 12:25:45,962	32k	INFO	====> Epoch: 437
+2023-02-19 12:26:05,572	32k	INFO	====> Epoch: 438
+2023-02-19 12:26:25,223	32k	INFO	====> Epoch: 439
+2023-02-19 12:26:44,804	32k	INFO	====> Epoch: 440
+2023-02-19 12:27:04,427	32k	INFO	====> Epoch: 441
+2023-02-19 12:27:23,994	32k	INFO	====> Epoch: 442
+2023-02-19 12:27:29,761	32k	INFO	Train Epoch: 443 [11%]
+2023-02-19 12:27:29,761	32k	INFO	[2.212078332901001, 2.7991578578948975, 14.290653228759766, 16.723142623901367, 0.758256733417511, 8400, 9.46245288460454e-05]
+2023-02-19 12:27:43,980	32k	INFO	====> Epoch: 443
+2023-02-19 12:28:03,844	32k	INFO	====> Epoch: 444
+2023-02-19 12:28:23,653	32k	INFO	====> Epoch: 445
+2023-02-19 12:28:43,304	32k	INFO	====> Epoch: 446
+2023-02-19 12:29:03,085	32k	INFO	====> Epoch: 447
+2023-02-19 12:29:22,793	32k	INFO	====> Epoch: 448
+2023-02-19 12:29:42,697	32k	INFO	====> Epoch: 449
+2023-02-19 12:30:02,286	32k	INFO	====> Epoch: 450
+2023-02-19 12:30:21,939	32k	INFO	====> Epoch: 451
+2023-02-19 12:30:41,561	32k	INFO	====> Epoch: 452
+2023-02-19 12:30:55,959	32k	INFO	Train Epoch: 453 [63%]
+2023-02-19 12:30:55,960	32k	INFO	[2.3873302936553955, 2.6133875846862793, 14.57663631439209, 17.228395462036133, 0.6703507900238037, 8600, 9.450631469568687e-05]
+2023-02-19 12:31:01,484	32k	INFO	====> Epoch: 453
+2023-02-19 12:31:21,352	32k	INFO	====> Epoch: 454
+2023-02-19 12:31:41,004	32k	INFO	====> Epoch: 455
+2023-02-19 12:32:00,663	32k	INFO	====> Epoch: 456
+2023-02-19 12:32:20,262	32k	INFO	====> Epoch: 457
+2023-02-19 12:32:39,921	32k	INFO	====> Epoch: 458
+2023-02-19 12:32:59,815	32k	INFO	====> Epoch: 459
+2023-02-19 12:33:20,886	32k	INFO	====> Epoch: 460
+2023-02-19 12:33:40,723	32k	INFO	====> Epoch: 461
+2023-02-19 12:34:00,374	32k	INFO	====> Epoch: 462
+2023-02-19 12:34:20,007	32k	INFO	====> Epoch: 463
+2023-02-19 12:34:37,407	32k	INFO	Train Epoch: 464 [16%]
+2023-02-19 12:34:37,407	32k	INFO	[3.0064706802368164, 2.5415701866149902, 9.37286376953125, 13.644079208374023, 0.7945896983146667, 8800, 9.437644969889592e-05]
+2023-02-19 12:34:50,681	32k	INFO	====> Epoch: 464
+2023-02-19 12:35:10,328	32k	INFO	====> Epoch: 465
+2023-02-19 12:35:29,951	32k	INFO	====> Epoch: 466
+2023-02-19 12:35:49,602	32k	INFO	====> Epoch: 467
+2023-02-19 12:36:09,383	32k	INFO	====> Epoch: 468
+2023-02-19 12:36:29,051	32k	INFO	====> Epoch: 469
+2023-02-19 12:36:48,693	32k	INFO	====> Epoch: 470
+2023-02-19 12:37:08,307	32k	INFO	====> Epoch: 471
+2023-02-19 12:37:27,980	32k	INFO	====> Epoch: 472
+2023-02-19 12:37:47,600	32k	INFO	====> Epoch: 473
+2023-02-19 12:38:02,872	32k	INFO	Train Epoch: 474 [68%]
+2023-02-19 12:38:02,873	32k	INFO	[2.2592387199401855, 2.68511962890625, 14.775422096252441, 18.476463317871094, 0.7293793559074402, 9000, 9.425854547309881e-05]
+2023-02-19 12:38:07,146	32k	INFO	Saving model and optimizer state at iteration 474 to ./logs\32k\G_9000.pth
+2023-02-19 12:38:23,693	32k	INFO	Saving model and optimizer state at iteration 474 to ./logs\32k\D_9000.pth
+2023-02-19 12:38:31,718	32k	INFO	====> Epoch: 474
+2023-02-19 12:38:51,663	32k	INFO	====> Epoch: 475
+2023-02-19 12:39:11,421	32k	INFO	====> Epoch: 476
+2023-02-19 12:39:31,207	32k	INFO	====> Epoch: 477
+2023-02-19 12:39:50,792	32k	INFO	====> Epoch: 478
+2023-02-19 12:40:10,453	32k	INFO	====> Epoch: 479
+2023-02-19 12:40:30,150	32k	INFO	====> Epoch: 480
+2023-02-19 12:40:49,778	32k	INFO	====> Epoch: 481
+2023-02-19 12:41:09,416	32k	INFO	====> Epoch: 482
+2023-02-19 12:41:29,039	32k	INFO	====> Epoch: 483
+2023-02-19 12:41:48,739	32k	INFO	====> Epoch: 484
+2023-02-19 12:41:56,274	32k	INFO	Train Epoch: 485 [21%]
+2023-02-19 12:41:56,274	32k	INFO	[2.0364489555358887, 2.666236400604248, 15.535277366638184, 17.430566787719727, 0.9094477891921997, 9200, 9.412902094614211e-05]
+2023-02-19 12:42:08,707	32k	INFO	====> Epoch: 485
+2023-02-19 12:42:28,424	32k	INFO	====> Epoch: 486
+2023-02-19 12:42:48,137	32k	INFO	====> Epoch: 487
+2023-02-19 12:43:07,787	32k	INFO	====> Epoch: 488
+2023-02-19 12:43:27,391	32k	INFO	====> Epoch: 489
+2023-02-19 12:43:47,060	32k	INFO	====> Epoch: 490
+2023-02-19 12:44:06,721	32k	INFO	====> Epoch: 491
+2023-02-19 12:44:26,376	32k	INFO	====> Epoch: 492
+2023-02-19 12:44:46,053	32k	INFO	====> Epoch: 493
+2023-02-19 12:45:05,716	32k	INFO	====> Epoch: 494
+2023-02-19 12:45:21,792	32k	INFO	Train Epoch: 495 [74%]
+2023-02-19 12:45:21,793	32k	INFO	[2.3733603954315186, 2.47238826751709, 12.350341796875, 17.111530303955078, 0.7110298275947571, 9400, 9.401142583237059e-05]
+2023-02-19 12:45:25,630	32k	INFO	====> Epoch: 495
+2023-02-19 12:45:45,272	32k	INFO	====> Epoch: 496
+2023-02-19 12:46:04,842	32k	INFO	====> Epoch: 497
+2023-02-19 12:46:24,549	32k	INFO	====> Epoch: 498
+2023-02-19 12:46:44,160	32k	INFO	====> Epoch: 499
+2023-02-19 12:47:03,818	32k	INFO	====> Epoch: 500
+2023-02-19 12:47:23,460	32k	INFO	====> Epoch: 501
+2023-02-19 12:47:43,079	32k	INFO	====> Epoch: 502
+2023-02-19 12:48:02,692	32k	INFO	====> Epoch: 503
+2023-02-19 12:48:22,357	32k	INFO	====> Epoch: 504
+2023-02-19 12:48:41,987	32k	INFO	====> Epoch: 505
+2023-02-19 12:48:50,352	32k	INFO	Train Epoch: 506 [26%]
+2023-02-19 12:48:50,353	32k	INFO	[2.4896092414855957, 2.6762804985046387, 7.441979885101318, 12.384513854980469, 0.8221025466918945, 9600, 9.388224088263103e-05]
+2023-02-19 12:49:01,920	32k	INFO	====> Epoch: 506
+2023-02-19 12:49:21,631	32k	INFO	====> Epoch: 507
+2023-02-19 12:49:41,235	32k	INFO	====> Epoch: 508
+2023-02-19 12:50:00,878	32k	INFO	====> Epoch: 509
+2023-02-19 12:50:20,529	32k	INFO	====> Epoch: 510
+2023-02-19 12:50:40,218	32k	INFO	====> Epoch: 511
+2023-02-19 12:50:59,886	32k	INFO	====> Epoch: 512
+2023-02-19 12:51:19,546	32k	INFO	====> Epoch: 513
+2023-02-19 12:51:39,163	32k	INFO	====> Epoch: 514
+2023-02-19 12:51:58,821	32k	INFO	====> Epoch: 515
+2023-02-19 12:52:15,760	32k	INFO	Train Epoch: 516 [79%]
+2023-02-19 12:52:15,761	32k	INFO	[1.8880212306976318, 2.990048885345459, 18.54258918762207, 15.826509475708008, 0.7649766206741333, 9800, 9.376495407047951e-05]
+2023-02-19 12:52:18,707	32k	INFO	====> Epoch: 516
+2023-02-19 12:52:38,388	32k	INFO	====> Epoch: 517
+2023-02-19 12:52:58,019	32k	INFO	====> Epoch: 518
+2023-02-19 12:53:17,689	32k	INFO	====> Epoch: 519
+2023-02-19 12:53:37,358	32k	INFO	====> Epoch: 520
+2023-02-19 12:53:56,945	32k	INFO	====> Epoch: 521
+2023-02-19 12:54:16,610	32k	INFO	====> Epoch: 522
+2023-02-19 12:54:36,229	32k	INFO	====> Epoch: 523
+2023-02-19 12:54:55,834	32k	INFO	====> Epoch: 524
+2023-02-19 12:55:15,475	32k	INFO	====> Epoch: 525
+2023-02-19 12:55:35,099	32k	INFO	====> Epoch: 526
+2023-02-19 12:55:44,384	32k	INFO	Train Epoch: 527 [32%]
+2023-02-19 12:55:44,385	32k	INFO	[2.205662727355957, 2.867584705352783, 16.78660774230957, 16.71090316772461, 0.8774336576461792, 10000, 9.36361078076803e-05]
+2023-02-19 12:55:48,586	32k	INFO	Saving model and optimizer state at iteration 527 to ./logs\32k\G_10000.pth
+2023-02-19 12:56:06,798	32k	INFO	Saving model and optimizer state at iteration 527 to ./logs\32k\D_10000.pth
+2023-02-19 12:56:21,401	32k	INFO	====> Epoch: 527
+2023-02-19 12:56:41,345	32k	INFO	====> Epoch: 528
+2023-02-19 12:57:00,917	32k	INFO	====> Epoch: 529
+2023-02-19 12:57:20,811	32k	INFO	====> Epoch: 530
+2023-02-19 12:57:40,435	32k	INFO	====> Epoch: 531
+2023-02-19 12:58:00,053	32k	INFO	====> Epoch: 532
+2023-02-19 12:58:19,745	32k	INFO	====> Epoch: 533
+2023-02-19 12:58:39,609	32k	INFO	====> Epoch: 534
+2023-02-19 12:58:59,368	32k	INFO	====> Epoch: 535
+2023-02-19 12:59:18,968	32k	INFO	====> Epoch: 536
+2023-02-19 12:59:36,810	32k	INFO	Train Epoch: 537 [84%]
+2023-02-19 12:59:36,811	32k	INFO	[2.1262154579162598, 2.892063856124878, 15.072270393371582, 16.91364288330078, 0.7413275837898254, 10200, 9.351912848886779e-05]
+2023-02-19 12:59:38,927	32k	INFO	====> Epoch: 537
+2023-02-19 12:59:58,556	32k	INFO	====> Epoch: 538
+2023-02-19 13:00:18,246	32k	INFO	====> Epoch: 539
+2023-02-19 13:00:38,193	32k	INFO	====> Epoch: 540
+2023-02-19 13:00:57,974	32k	INFO	====> Epoch: 541
+2023-02-19 13:01:17,641	32k	INFO	====> Epoch: 542
+2023-02-19 13:01:37,271	32k	INFO	====> Epoch: 543
+2023-02-19 13:01:56,865	32k	INFO	====> Epoch: 544
+2023-02-19 13:02:16,505	32k	INFO	====> Epoch: 545
+2023-02-19 13:02:36,125	32k	INFO	====> Epoch: 546
+2023-02-19 13:02:55,699	32k	INFO	====> Epoch: 547
+2023-02-19 13:03:05,776	32k	INFO	Train Epoch: 548 [37%]
+2023-02-19 13:03:05,776	32k	INFO	[2.2443082332611084, 2.77612566947937, 14.530040740966797, 16.31207275390625, 0.7399520874023438, 10400, 9.339062002506615e-05]
+2023-02-19 13:03:15,650	32k	INFO	====> Epoch: 548
+2023-02-19 13:03:35,253	32k	INFO	====> Epoch: 549
+2023-02-19 13:03:54,904	32k	INFO	====> Epoch: 550
+2023-02-19 13:04:14,500	32k	INFO	====> Epoch: 551
+2023-02-19 13:04:34,189	32k	INFO	====> Epoch: 552
+2023-02-19 13:04:53,801	32k	INFO	====> Epoch: 553
+2023-02-19 13:05:13,431	32k	INFO	====> Epoch: 554
+2023-02-19 13:05:33,057	32k	INFO	====> Epoch: 555
+2023-02-19 13:05:52,677	32k	INFO	====> Epoch: 556
+2023-02-19 13:06:12,273	32k	INFO	====> Epoch: 557
+2023-02-19 13:06:30,977	32k	INFO	Train Epoch: 558 [89%]
+2023-02-19 13:06:30,978	32k	INFO	[1.9971816539764404, 2.9987430572509766, 16.42749786376953, 17.72498893737793, 0.7169369459152222, 10600, 9.327394739343082e-05]
+2023-02-19 13:06:32,240	32k	INFO	====> Epoch: 558
+2023-02-19 13:06:51,888	32k	INFO	====> Epoch: 559
+2023-02-19 13:07:11,500	32k	INFO	====> Epoch: 560
+2023-02-19 13:07:31,432	32k	INFO	====> Epoch: 561
+2023-02-19 13:07:51,063	32k	INFO	====> Epoch: 562
+2023-02-19 13:08:10,683	32k	INFO	====> Epoch: 563
+2023-02-19 13:08:30,306	32k	INFO	====> Epoch: 564
+2023-02-19 13:08:49,925	32k	INFO	====> Epoch: 565
+2023-02-19 13:09:09,599	32k	INFO	====> Epoch: 566
+2023-02-19 13:09:29,187	32k	INFO	====> Epoch: 567
+2023-02-19 13:09:48,800	32k	INFO	====> Epoch: 568
+2023-02-19 13:09:59,768	32k	INFO	Train Epoch: 569 [42%]
+2023-02-19 13:09:59,768	32k	INFO	[2.171602725982666, 2.590355157852173, 13.851484298706055, 15.077618598937988, 0.7326598167419434, 10800, 9.314577584301187e-05]
+2023-02-19 13:10:08,772	32k	INFO	====> Epoch: 569
+2023-02-19 13:10:28,413	32k	INFO	====> Epoch: 570
+2023-02-19 13:10:48,029	32k	INFO	====> Epoch: 571
+2023-02-19 13:11:07,762	32k	INFO	====> Epoch: 572
+2023-02-19 13:11:27,359	32k	INFO	====> Epoch: 573
+2023-02-19 13:11:46,968	32k	INFO	====> Epoch: 574
+2023-02-19 13:12:06,652	32k	INFO	====> Epoch: 575
+2023-02-19 13:12:26,301	32k	INFO	====> Epoch: 576
+2023-02-19 13:12:45,960	32k	INFO	====> Epoch: 577
+2023-02-19 13:13:05,579	32k	INFO	====> Epoch: 578
+2023-02-19 13:13:24,791	32k	INFO	Train Epoch: 579 [95%]
+2023-02-19 13:13:24,792	32k	INFO	[2.4127438068389893, 2.4390709400177, 18.234426498413086, 15.20917797088623, 0.9935965538024902, 11000, 9.302940909450543e-05]
+2023-02-19 13:13:29,089	32k	INFO	Saving model and optimizer state at iteration 579 to ./logs\32k\G_11000.pth
+2023-02-19 13:13:46,080	32k	INFO	Saving model and optimizer state at iteration 579 to ./logs\32k\D_11000.pth
+2023-02-19 13:13:50,303	32k	INFO	====> Epoch: 579
+2023-02-19 13:14:10,200	32k	INFO	====> Epoch: 580
+2023-02-19 13:14:29,994	32k	INFO	====> Epoch: 581
+2023-02-19 13:14:49,886	32k	INFO	====> Epoch: 582
+2023-02-19 13:15:09,476	32k	INFO	====> Epoch: 583
+2023-02-19 13:15:29,373	32k	INFO	====> Epoch: 584
+2023-02-19 13:15:49,189	32k	INFO	====> Epoch: 585
+2023-02-19 13:16:09,053	32k	INFO	====> Epoch: 586
+2023-02-19 13:16:28,930	32k	INFO	====> Epoch: 587
+2023-02-19 13:16:48,676	32k	INFO	====> Epoch: 588
+2023-02-19 13:17:08,497	32k	INFO	====> Epoch: 589
+2023-02-19 13:17:20,344	32k	INFO	Train Epoch: 590 [47%]
+2023-02-19 13:17:20,345	32k	INFO	[2.5262322425842285, 2.621953010559082, 13.513108253479004, 15.703678131103516, 0.5160157680511475, 11200, 9.29015735741762e-05]
+2023-02-19 13:17:28,485	32k	INFO	====> Epoch: 590
+2023-02-19 13:17:48,164	32k	INFO	====> Epoch: 591
+2023-02-19 13:18:07,959	32k	INFO	====> Epoch: 592
+2023-02-19 13:18:27,653	32k	INFO	====> Epoch: 593
+2023-02-19 13:18:47,325	32k	INFO	====> Epoch: 594
+2023-02-19 13:19:06,920	32k	INFO	====> Epoch: 595
+2023-02-19 13:19:26,787	32k	INFO	====> Epoch: 596
+2023-02-19 13:19:46,492	32k	INFO	====> Epoch: 597
+2023-02-19 13:20:06,128	32k	INFO	====> Epoch: 598
+2023-02-19 13:20:25,792	32k	INFO	====> Epoch: 599
+2023-02-19 13:20:45,413	32k	INFO	====> Epoch: 600
+2023-02-19 13:20:49,465	32k	INFO	Train Epoch: 601 [0%]
+2023-02-19 13:20:49,465	32k	INFO	[2.056851625442505, 2.9963862895965576, 17.283754348754883, 17.02275848388672, 0.9403309226036072, 11400, 9.277391371786995e-05]
+2023-02-19 13:21:05,470	32k	INFO	====> Epoch: 601
+2023-02-19 13:21:25,118	32k	INFO	====> Epoch: 602
+2023-02-19 13:21:44,922	32k	INFO	====> Epoch: 603
+2023-02-19 13:22:04,542	32k	INFO	====> Epoch: 604
+2023-02-19 13:22:24,116	32k	INFO	====> Epoch: 605
+2023-02-19 13:22:43,845	32k	INFO	====> Epoch: 606
+2023-02-19 13:23:03,995	32k	INFO	====> Epoch: 607
+2023-02-19 13:23:24,240	32k	INFO	====> Epoch: 608
+2023-02-19 13:23:44,685	32k	INFO	====> Epoch: 609
+2023-02-19 13:24:06,943	32k	INFO	====> Epoch: 610
+2023-02-19 13:24:21,160	32k	INFO	Train Epoch: 611 [53%]
+2023-02-19 13:24:21,161	32k	INFO	[2.046140193939209, 3.0505690574645996, 18.795839309692383, 19.634422302246094, 0.7730445265769958, 11600, 9.265801153564152e-05]
+2023-02-19 13:24:28,568	32k	INFO	====> Epoch: 611
+2023-02-19 13:24:48,706	32k	INFO	====> Epoch: 612
+2023-02-19 13:25:08,885	32k	INFO	====> Epoch: 613
+2023-02-19 13:25:28,992	32k	INFO	====> Epoch: 614
+2023-02-19 13:25:48,957	32k	INFO	====> Epoch: 615
+2023-02-19 13:26:08,955	32k	INFO	====> Epoch: 616
+2023-02-19 13:26:28,851	32k	INFO	====> Epoch: 617
+2023-02-19 13:26:48,849	32k	INFO	====> Epoch: 618
+2023-02-19 13:27:08,836	32k	INFO	====> Epoch: 619
+2023-02-19 13:27:28,912	32k	INFO	====> Epoch: 620
+2023-02-19 13:27:49,369	32k	INFO	====> Epoch: 621
+2023-02-19 13:27:54,743	32k	INFO	Train Epoch: 622 [5%]
+2023-02-19 13:27:54,744	32k	INFO	[2.1044559478759766, 2.9037117958068848, 18.362964630126953, 17.604398727416992, 0.6811983585357666, 11800, 9.25306863679056e-05]
+2023-02-19 13:28:10,067	32k	INFO	====> Epoch: 622
+2023-02-19 13:28:30,230	32k	INFO	====> Epoch: 623
+2023-02-19 13:28:50,259	32k	INFO	====> Epoch: 624
+2023-02-19 13:29:10,185	32k	INFO	====> Epoch: 625
+2023-02-19 13:29:30,067	32k	INFO	====> Epoch: 626
+2023-02-19 13:29:50,074	32k	INFO	====> Epoch: 627
+2023-02-19 13:30:10,092	32k	INFO	====> Epoch: 628
+2023-02-19 13:30:30,071	32k	INFO	====> Epoch: 629
+2023-02-19 13:30:50,611	32k	INFO	====> Epoch: 630
+2023-02-19 13:31:10,685	32k	INFO	====> Epoch: 631
+2023-02-19 13:31:24,362	32k	INFO	Train Epoch: 632 [58%]
+2023-02-19 13:31:24,362	32k	INFO	[2.0907158851623535, 2.8510940074920654, 16.303882598876953, 16.795988082885742, 0.6851125359535217, 12000, 9.24150880489024e-05]
+2023-02-19 13:31:28,856	32k	INFO	Saving model and optimizer state at iteration 632 to ./logs\32k\G_12000.pth
+2023-02-19 13:31:46,760	32k	INFO	Saving model and optimizer state at iteration 632 to ./logs\32k\D_12000.pth
+2023-02-19 13:31:56,955	32k	INFO	====> Epoch: 632
+2023-02-19 13:32:17,156	32k	INFO	====> Epoch: 633
+2023-02-19 13:32:37,149	32k	INFO	====> Epoch: 634
+2023-02-19 13:32:56,970	32k	INFO	====> Epoch: 635
+2023-02-19 13:33:16,861	32k	INFO	====> Epoch: 636
+2023-02-19 13:33:36,793	32k	INFO	====> Epoch: 637
+2023-02-19 13:33:56,654	32k	INFO	====> Epoch: 638
+2023-02-19 13:34:16,576	32k	INFO	====> Epoch: 639
+2023-02-19 13:34:36,445	32k	INFO	====> Epoch: 640
+2023-02-19 13:34:56,252	32k	INFO	====> Epoch: 641
+2023-02-19 13:35:16,142	32k	INFO	====> Epoch: 642
+2023-02-19 13:35:21,999	32k	INFO	Train Epoch: 643 [11%]
+2023-02-19 13:35:21,999	32k	INFO	[2.3126425743103027, 3.3445053100585938, 15.56027889251709, 17.644582748413086, 0.5389391779899597, 12200, 9.228809669227663e-05]
+2023-02-19 13:35:36,442	32k	INFO	====> Epoch: 643
+2023-02-19 13:35:56,329	32k	INFO	====> Epoch: 644
+2023-02-19 13:36:16,285	32k	INFO	====> Epoch: 645
+2023-02-19 13:36:36,225	32k	INFO	====> Epoch: 646
+2023-02-19 13:36:56,109	32k	INFO	====> Epoch: 647
+2023-02-19 13:37:15,986	32k	INFO	====> Epoch: 648
+2023-02-19 13:37:36,535	32k	INFO	====> Epoch: 649
+2023-02-19 13:37:58,438	32k	INFO	====> Epoch: 650
+2023-02-19 13:38:20,631	32k	INFO	====> Epoch: 651
+2023-02-19 13:38:48,478	32k	INFO	====> Epoch: 652
+2023-02-19 13:39:15,549	32k	INFO	Train Epoch: 653 [63%]
+2023-02-19 13:39:15,549	32k	INFO	[2.3998544216156006, 2.5205063819885254, 13.50827693939209, 16.829593658447266, 0.518319845199585, 12400, 9.217280143985396e-05]
+2023-02-19 13:39:23,399	32k	INFO	====> Epoch: 653
+2023-02-19 13:39:44,062	32k	INFO	====> Epoch: 654
+2023-02-19 13:40:04,509	32k	INFO	====> Epoch: 655
+2023-02-19 13:40:24,966	32k	INFO	====> Epoch: 656
+2023-02-19 13:40:46,616	32k	INFO	====> Epoch: 657
+2023-02-19 13:41:06,997	32k	INFO	====> Epoch: 658
+2023-02-19 13:41:27,230	32k	INFO	====> Epoch: 659
+2023-02-19 13:41:47,556	32k	INFO	====> Epoch: 660
+2023-02-19 13:42:07,868	32k	INFO	====> Epoch: 661
+2023-02-19 13:42:28,224	32k	INFO	====> Epoch: 662
+2023-02-19 13:42:48,842	32k	INFO	====> Epoch: 663
+2023-02-19 13:42:55,986	32k	INFO	Train Epoch: 664 [16%]
+2023-02-19 13:42:55,987	32k	INFO	[2.1531105041503906, 2.9205827713012695, 12.979509353637695, 14.956928253173828, 1.0134525299072266, 12600, 9.204614301917867e-05]
+2023-02-19 13:43:09,755	32k	INFO	====> Epoch: 664
+2023-02-19 13:43:30,293	32k	INFO	====> Epoch: 665
+2023-02-19 13:43:50,838	32k	INFO	====> Epoch: 666
+2023-02-19 13:44:11,454	32k	INFO	====> Epoch: 667
+2023-02-19 13:44:32,018	32k	INFO	====> Epoch: 668
+2023-02-19 13:44:52,353	32k	INFO	====> Epoch: 669
+2023-02-19 13:45:12,710	32k	INFO	====> Epoch: 670
+2023-02-19 13:45:32,939	32k	INFO	====> Epoch: 671
+2023-02-19 13:45:53,246	32k	INFO	====> Epoch: 672
+2023-02-19 13:46:13,398	32k	INFO	====> Epoch: 673
+2023-02-19 13:46:29,187	32k	INFO	Train Epoch: 674 [68%]
+2023-02-19 13:46:29,187	32k	INFO	[2.120356321334839, 2.7157726287841797, 13.795363426208496, 18.83095932006836, 0.682133138179779, 12800, 9.193115003878036e-05]
+2023-02-19 13:46:34,017	32k	INFO	====> Epoch: 674
+2023-02-19 13:46:54,188	32k	INFO	====> Epoch: 675
+2023-02-19 13:47:14,233	32k	INFO	====> Epoch: 676
+2023-02-19 13:47:34,315	32k	INFO	====> Epoch: 677
+2023-02-19 13:47:54,390	32k	INFO	====> Epoch: 678
+2023-02-19 13:48:14,419	32k	INFO	====> Epoch: 679
+2023-02-19 13:48:34,434	32k	INFO	====> Epoch: 680
+2023-02-19 13:48:54,500	32k	INFO	====> Epoch: 681
+2023-02-19 13:49:14,535	32k	INFO	====> Epoch: 682
+2023-02-19 13:49:34,589	32k	INFO	====> Epoch: 683
+2023-02-19 13:49:54,633	32k	INFO	====> Epoch: 684
+2023-02-19 13:50:02,241	32k	INFO	Train Epoch: 685 [21%]
+2023-02-19 13:50:02,241	32k	INFO	[1.9549205303192139, 2.509674549102783, 15.415645599365234, 16.405630111694336, 0.5037123560905457, 13000, 9.180482368119022e-05]
+2023-02-19 13:50:06,487	32k	INFO	Saving model and optimizer state at iteration 685 to ./logs\32k\G_13000.pth
+2023-02-19 13:50:24,993	32k	INFO	Saving model and optimizer state at iteration 685 to ./logs\32k\D_13000.pth
+2023-02-19 13:50:41,214	32k	INFO	====> Epoch: 685
+2023-02-19 13:51:01,502	32k	INFO	====> Epoch: 686
+2023-02-19 13:51:21,512	32k	INFO	====> Epoch: 687
+2023-02-19 13:51:41,753	32k	INFO	====> Epoch: 688
+2023-02-19 13:52:01,822	32k	INFO	====> Epoch: 689
+2023-02-19 13:52:21,926	32k	INFO	====> Epoch: 690
+2023-02-19 13:52:41,986	32k	INFO	====> Epoch: 691
+2023-02-19 13:53:02,270	32k	INFO	====> Epoch: 692
+2023-02-19 13:53:22,470	32k	INFO	====> Epoch: 693
+2023-02-19 13:53:42,473	32k	INFO	====> Epoch: 694
+2023-02-19 13:53:58,964	32k	INFO	Train Epoch: 695 [74%]
+2023-02-19 13:53:58,964	32k	INFO	[2.0492773056030273, 2.9210152626037598, 20.51807403564453, 21.43520164489746, 1.142478108406067, 13200, 9.169013218034329e-05]
+2023-02-19 13:54:02,863	32k	INFO	====> Epoch: 695
+2023-02-19 13:54:22,924	32k	INFO	====> Epoch: 696
+2023-02-19 13:54:42,972	32k	INFO	====> Epoch: 697
+2023-02-19 13:55:03,260	32k	INFO	====> Epoch: 698
+2023-02-19 13:55:23,335	32k	INFO	====> Epoch: 699
+2023-02-19 13:55:43,367	32k	INFO	====> Epoch: 700
+2023-02-19 13:56:03,452	32k	INFO	====> Epoch: 701
+2023-02-19 13:56:23,507	32k	INFO	====> Epoch: 702
+2023-02-19 13:56:43,553	32k	INFO	====> Epoch: 703
+2023-02-19 13:57:03,890	32k	INFO	====> Epoch: 704
+2023-02-19 13:57:24,195	32k	INFO	====> Epoch: 705
+2023-02-19 13:57:32,664	32k	INFO	Train Epoch: 706 [26%]
+2023-02-19 13:57:32,664	32k	INFO	[2.137279987335205, 2.8736164569854736, 16.14851188659668, 14.964777946472168, 0.5104328393936157, 13400, 9.156413701526141e-05]
+2023-02-19 13:57:44,470	32k	INFO	====> Epoch: 706
+2023-02-19 13:58:04,489	32k	INFO	====> Epoch: 707
+2023-02-19 13:58:24,565	32k	INFO	====> Epoch: 708
+2023-02-19 13:58:44,632	32k	INFO	====> Epoch: 709
+2023-02-19 13:59:04,804	32k	INFO	====> Epoch: 710
+2023-02-19 13:59:24,867	32k	INFO	====> Epoch: 711
+2023-02-19 13:59:45,104	32k	INFO	====> Epoch: 712
+2023-02-19 14:00:05,190	32k	INFO	====> Epoch: 713
+2023-02-19 14:00:25,258	32k	INFO	====> Epoch: 714
+2023-02-19 14:00:45,336	32k	INFO	====> Epoch: 715
+2023-02-19 14:01:02,624	32k	INFO	Train Epoch: 716 [79%]
+2023-02-19 14:01:02,624	32k	INFO	[1.762975811958313, 2.899984359741211, 21.13072967529297, 15.85500717163086, 1.2023099660873413, 13600, 9.144974620357048e-05]
+2023-02-19 14:01:05,730	32k	INFO	====> Epoch: 716
+2023-02-19 14:01:25,807	32k	INFO	====> Epoch: 717
+2023-02-19 14:01:45,813	32k	INFO	====> Epoch: 718
+2023-02-19 14:02:05,878	32k	INFO	====> Epoch: 719
+2023-02-19 14:02:26,003	32k	INFO	====> Epoch: 720
+2023-02-19 14:02:46,038	32k	INFO	====> Epoch: 721
+2023-02-19 14:03:06,130	32k	INFO	====> Epoch: 722
+2023-02-19 14:03:26,223	32k	INFO	====> Epoch: 723
+2023-02-19 14:03:46,269	32k	INFO	====> Epoch: 724
+2023-02-19 14:04:06,294	32k	INFO	====> Epoch: 725
+2023-02-19 14:04:26,438	32k	INFO	====> Epoch: 726
+2023-02-19 14:04:35,838	32k	INFO	Train Epoch: 727 [32%]
+2023-02-19 14:04:35,839	32k	INFO	[2.231358051300049, 2.4955027103424072, 12.61548137664795, 13.37820816040039, 0.7114076614379883, 13800, 9.132408136270243e-05]
+2023-02-19 14:04:46,835	32k	INFO	====> Epoch: 727
+2023-02-19 14:05:07,009	32k	INFO	====> Epoch: 728
+2023-02-19 14:05:27,022	32k	INFO	====> Epoch: 729
+2023-02-19 14:05:47,131	32k	INFO	====> Epoch: 730
+2023-02-19 14:06:07,140	32k	INFO	====> Epoch: 731
+2023-02-19 14:06:27,225	32k	INFO	====> Epoch: 732
+2023-02-19 14:06:47,266	32k	INFO	====> Epoch: 733
+2023-02-19 14:07:07,365	32k	INFO	====> Epoch: 734
+2023-02-19 14:07:27,419	32k	INFO	====> Epoch: 735
+2023-02-19 14:07:47,463	32k	INFO	====> Epoch: 736
+2023-02-19 14:08:05,749	32k	INFO	Train Epoch: 737 [84%]
+2023-02-19 14:08:05,750	32k	INFO	[2.0271754264831543, 2.876140594482422, 14.655152320861816, 14.280223846435547, 0.5791776180267334, 14000, 9.120999045184433e-05]
+2023-02-19 14:08:10,006	32k	INFO	Saving model and optimizer state at iteration 737 to ./logs\32k\G_14000.pth
+2023-02-19 14:08:26,063	32k	INFO	Saving model and optimizer state at iteration 737 to ./logs\32k\D_14000.pth
+2023-02-19 14:08:31,910	32k	INFO	====> Epoch: 737
+2023-02-19 14:08:52,271	32k	INFO	====> Epoch: 738
+2023-02-19 14:09:12,223	32k	INFO	====> Epoch: 739
+2023-02-19 14:09:32,201	32k	INFO	====> Epoch: 740
+2023-02-19 14:09:52,186	32k	INFO	====> Epoch: 741
+2023-02-19 14:10:12,190	32k	INFO	====> Epoch: 742
+2023-02-19 14:10:32,165	32k	INFO	====> Epoch: 743
+2023-02-19 14:10:52,419	32k	INFO	====> Epoch: 744
+2023-02-19 14:11:12,589	32k	INFO	====> Epoch: 745
+2023-02-19 14:11:32,627	32k	INFO	====> Epoch: 746
+2023-02-19 14:11:52,686	32k	INFO	====> Epoch: 747