logs/9nineM/train.log

2023-01-25 23:46:00,530	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 24, 'fp16_run': True, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-01-25 23:46:38,282	9nineM	INFO	Train Epoch: 1 [0%]
2023-01-25 23:46:38,282	9nineM	INFO	[6.073990345001221, 6.072503566741943, 0.30118170380592346, 101.45647430419922, 1.7897791862487793, 198.48548889160156, 0, 0.0002]
2023-01-25 23:47:05,692	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\G_0.pth
2023-01-25 23:47:05,958	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\D_0.pth
2023-01-25 23:49:33,816	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 24, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-01-25 23:49:37,570	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_0.pth' (iteration 1)
2023-01-25 23:49:37,678	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_0.pth' (iteration 1)
2023-01-25 23:50:10,424	9nineM	INFO	Train Epoch: 1 [0%]
2023-01-25 23:50:10,425	9nineM	INFO	[6.073970317840576, 4.677792549133301, 0.30806946754455566, 101.44989776611328, 1.7897722721099854, 198.4989013671875, 0, 0.0002]
2023-01-25 23:50:36,468	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\G_0.pth
2023-01-25 23:50:37,251	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\D_0.pth
2023-01-25 23:54:21,335	9nineM	INFO	Train Epoch: 1 [35%]
2023-01-25 23:54:21,335	9nineM	INFO	[2.0056729316711426, 2.2880539894104004, 5.171030044555664, 47.03142547607422, 1.995613932609558, 1.627901554107666, 200, 0.0002]
2023-01-25 23:59:20,162	9nineM	INFO	Train Epoch: 1 [70%]
2023-01-25 23:59:20,163	9nineM	INFO	[2.313659191131592, 2.3724217414855957, 3.7704148292541504, 40.99565887451172, 2.0197911262512207, 1.2937748432159424, 400, 0.0002]
2023-01-25 23:59:45,658	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\G_400.pth
2023-01-25 23:59:46,341	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\D_400.pth
2023-01-26 00:02:43,047	9nineM	INFO	====> Epoch: 1
2023-01-26 00:03:37,133	9nineM	INFO	Train Epoch: 2 [5%]
2023-01-26 00:03:37,133	9nineM	INFO	[2.34749436378479, 2.807877779006958, 3.85154390335083, 36.201969146728516, 2.026376724243164, 1.5017982721328735, 600, 0.000199975]
2023-01-26 00:06:59,932	9nineM	INFO	Train Epoch: 2 [40%]
2023-01-26 00:06:59,933	9nineM	INFO	[2.2677979469299316, 2.7484307289123535, 3.9582455158233643, 32.791133880615234, 2.033611536026001, 1.4443621635437012, 800, 0.000199975]
2023-01-26 00:07:25,282	9nineM	INFO	Saving model and optimizer state at iteration 2 to ./logs\9nineM\G_800.pth
2023-01-26 00:07:25,953	9nineM	INFO	Saving model and optimizer state at iteration 2 to ./logs\9nineM\D_800.pth
2023-01-26 00:10:47,662	9nineM	INFO	Train Epoch: 2 [75%]
2023-01-26 00:10:47,663	9nineM	INFO	[2.4101669788360596, 1.9714564085006714, 3.4384775161743164, 30.411867141723633, 2.0720434188842773, 1.4144717454910278, 1000, 0.000199975]
2023-01-26 00:13:13,823	9nineM	INFO	====> Epoch: 2
2023-01-26 00:14:38,413	9nineM	INFO	Train Epoch: 3 [11%]
2023-01-26 00:14:38,413	9nineM	INFO	[2.357465982437134, 2.5078492164611816, 3.657393455505371, 34.19534683227539, 1.9945192337036133, 1.623528003692627, 1200, 0.000199950003125]
2023-01-26 00:15:03,696	9nineM	INFO	Saving model and optimizer state at iteration 3 to ./logs\9nineM\G_1200.pth
2023-01-26 00:15:04,370	9nineM	INFO	Saving model and optimizer state at iteration 3 to ./logs\9nineM\D_1200.pth
2023-01-26 00:18:25,883	9nineM	INFO	Train Epoch: 3 [46%]
2023-01-26 00:19:21,494	9nineM	INFO	[2.4258036613464355, 2.256639242172241, 3.5157554149627686, 33.91616439819336, 2.2258315086364746, 1.2393535375595093, 1400, 0.000199950003125]
2023-01-26 00:19:41,710	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 24, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-01-26 00:19:45,443	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_1200.pth' (iteration 3)
2023-01-26 00:19:45,808	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_1200.pth' (iteration 3)
2023-01-26 00:21:26,746	9nineM	INFO	Train Epoch: 3 [11%]
2023-01-26 00:21:26,747	9nineM	INFO	[2.3221030235290527, 2.3704800605773926, 3.8071811199188232, 34.25653076171875, 2.0056378841400146, 1.6272631883621216, 1200, 0.00019992500937460937]
2023-01-26 00:21:52,686	9nineM	INFO	Saving model and optimizer state at iteration 3 to ./logs\9nineM\G_1200.pth
2023-01-26 00:21:53,394	9nineM	INFO	Saving model and optimizer state at iteration 3 to ./logs\9nineM\D_1200.pth
2023-01-26 00:25:29,110	9nineM	INFO	Train Epoch: 3 [46%]
2023-01-26 00:25:29,110	9nineM	INFO	[2.640127182006836, 2.103668689727783, 2.8140110969543457, 29.13928985595703, 2.2003533840179443, 1.3579349517822266, 1400, 0.00019992500937460937]
2023-01-26 00:28:54,650	9nineM	INFO	Train Epoch: 3 [81%]
2023-01-26 00:28:54,650	9nineM	INFO	[2.5244946479797363, 2.0201079845428467, 3.0896544456481934, 29.836584091186523, 1.9984928369522095, 1.1511805057525635, 1600, 0.00019992500937460937]
2023-01-26 00:29:20,048	9nineM	INFO	Saving model and optimizer state at iteration 3 to ./logs\9nineM\G_1600.pth
2023-01-26 00:29:20,796	9nineM	INFO	Saving model and optimizer state at iteration 3 to ./logs\9nineM\D_1600.pth
2023-01-26 00:31:15,326	9nineM	INFO	====> Epoch: 3
2023-01-26 00:33:09,483	9nineM	INFO	Train Epoch: 4 [16%]
2023-01-26 00:33:09,484	9nineM	INFO	[2.3062384128570557, 2.1731457710266113, 3.7697784900665283, 30.14053726196289, 2.0052859783172607, 1.4556211233139038, 1800, 0.00019990001874843754]
2023-01-26 00:36:31,391	9nineM	INFO	Train Epoch: 4 [51%]
2023-01-26 00:36:31,391	9nineM	INFO	[2.538445472717285, 2.1030821800231934, 3.1004858016967773, 30.39350700378418, 1.9460492134094238, 1.4961357116699219, 2000, 0.00019990001874843754]
2023-01-26 00:36:57,126	9nineM	INFO	Saving model and optimizer state at iteration 4 to ./logs\9nineM\G_2000.pth
2023-01-26 00:36:57,789	9nineM	INFO	Saving model and optimizer state at iteration 4 to ./logs\9nineM\D_2000.pth
2023-01-26 00:40:22,230	9nineM	INFO	Train Epoch: 4 [86%]
2023-01-26 00:40:22,230	9nineM	INFO	[2.2768425941467285, 2.3642055988311768, 3.762643814086914, 29.680871963500977, 1.8728859424591064, 1.559889316558838, 2200, 0.00019990001874843754]
2023-01-26 00:41:41,845	9nineM	INFO	====> Epoch: 4
2023-01-26 00:44:06,172	9nineM	INFO	Train Epoch: 5 [21%]
2023-01-26 00:44:06,173	9nineM	INFO	[2.34861159324646, 2.4874701499938965, 3.741352081298828, 30.817813873291016, 2.043848991394043, 1.1385068893432617, 2400, 0.00019987503124609398]
2023-01-26 00:44:31,651	9nineM	INFO	Saving model and optimizer state at iteration 5 to ./logs\9nineM\G_2400.pth
2023-01-26 00:44:32,309	9nineM	INFO	Saving model and optimizer state at iteration 5 to ./logs\9nineM\D_2400.pth
2023-01-26 00:47:52,710	9nineM	INFO	Train Epoch: 5 [56%]
2023-01-26 00:47:52,710	9nineM	INFO	[2.7938294410705566, 2.050962209701538, 2.652010679244995, 28.363901138305664, 2.0211844444274902, 1.408889651298523, 2600, 0.00019987503124609398]
2023-01-26 00:51:15,681	9nineM	INFO	Train Epoch: 5 [91%]
2023-01-26 00:51:15,681	9nineM	INFO	[2.497097969055176, 2.0679380893707275, 2.9265832901000977, 26.662799835205078, 1.8392996788024902, 1.1821995973587036, 2800, 0.00019987503124609398]
2023-01-26 00:51:41,418	9nineM	INFO	Saving model and optimizer state at iteration 5 to ./logs\9nineM\G_2800.pth
2023-01-26 00:51:42,076	9nineM	INFO	Saving model and optimizer state at iteration 5 to ./logs\9nineM\D_2800.pth
2023-01-26 00:52:32,791	9nineM	INFO	====> Epoch: 5
2023-01-26 00:55:26,207	9nineM	INFO	Train Epoch: 6 [26%]
2023-01-26 00:55:26,208	9nineM	INFO	[2.600545644760132, 1.8324110507965088, 3.007281541824341, 27.99269676208496, 1.8528962135314941, 1.5542216300964355, 3000, 0.0001998500468671882]
2023-01-26 00:58:49,002	9nineM	INFO	Train Epoch: 6 [61%]
2023-01-26 00:58:49,002	9nineM	INFO	[2.5305962562561035, 2.0720105171203613, 2.8197600841522217, 26.332839965820312, 1.933664083480835, 1.6304469108581543, 3200, 0.0001998500468671882]
2023-01-26 00:59:14,960	9nineM	INFO	Saving model and optimizer state at iteration 6 to ./logs\9nineM\G_3200.pth
2023-01-26 00:59:15,627	9nineM	INFO	Saving model and optimizer state at iteration 6 to ./logs\9nineM\D_3200.pth
2023-01-26 01:02:37,221	9nineM	INFO	Train Epoch: 6 [96%]
2023-01-26 01:02:37,222	9nineM	INFO	[2.67600154876709, 2.077462911605835, 3.057732343673706, 27.05984878540039, 1.9372596740722656, 1.4464811086654663, 3400, 0.0001998500468671882]
2023-01-26 01:02:57,537	9nineM	INFO	====> Epoch: 6
2023-01-26 01:06:21,797	9nineM	INFO	Train Epoch: 7 [32%]
2023-01-26 01:06:21,798	9nineM	INFO	[2.8754048347473145, 1.7571762800216675, 1.9291565418243408, 24.49405288696289, 1.978126049041748, 1.6392502784729004, 3600, 0.00019982506561132978]
2023-01-26 01:06:47,857	9nineM	INFO	Saving model and optimizer state at iteration 7 to ./logs\9nineM\G_3600.pth
2023-01-26 01:06:48,512	9nineM	INFO	Saving model and optimizer state at iteration 7 to ./logs\9nineM\D_3600.pth
2023-01-26 01:10:10,491	9nineM	INFO	Train Epoch: 7 [67%]
2023-01-26 01:10:10,492	9nineM	INFO	[2.846407413482666, 1.746802568435669, 2.026045560836792, 23.640016555786133, 1.9296040534973145, 1.5151889324188232, 3800, 0.00019982506561132978]
2023-01-26 01:13:20,916	9nineM	INFO	====> Epoch: 7
2023-01-26 01:13:55,559	9nineM	INFO	Train Epoch: 8 [2%]
2023-01-26 01:13:55,560	9nineM	INFO	[2.677149772644043, 1.9254252910614014, 2.465095281600952, 22.880842208862305, 1.9207991361618042, 1.3455860614776611, 4000, 0.00019980008747812837]
2023-01-26 01:14:21,049	9nineM	INFO	Saving model and optimizer state at iteration 8 to ./logs\9nineM\G_4000.pth
2023-01-26 01:14:22,079	9nineM	INFO	Saving model and optimizer state at iteration 8 to ./logs\9nineM\D_4000.pth
2023-01-26 01:17:44,557	9nineM	INFO	Train Epoch: 8 [37%]
2023-01-26 01:17:44,558	9nineM	INFO	[2.6028459072113037, 1.8677709102630615, 2.768541097640991, 25.192880630493164, 1.8907232284545898, 1.4924492835998535, 4200, 0.00019980008747812837]
2023-01-26 01:21:04,611	9nineM	INFO	Train Epoch: 8 [72%]
2023-01-26 01:21:04,611	9nineM	INFO	[2.736124038696289, 1.8049640655517578, 2.620659112930298, 26.275257110595703, 2.048452138900757, 1.4815564155578613, 4400, 0.00019980008747812837]
2023-01-26 01:21:30,323	9nineM	INFO	Saving model and optimizer state at iteration 8 to ./logs\9nineM\G_4400.pth
2023-01-26 01:21:30,981	9nineM	INFO	Saving model and optimizer state at iteration 8 to ./logs\9nineM\D_4400.pth
2023-01-26 01:24:11,402	9nineM	INFO	====> Epoch: 8
2023-01-26 01:25:16,374	9nineM	INFO	Train Epoch: 9 [7%]
2023-01-26 01:25:16,374	9nineM	INFO	[2.5049564838409424, 2.069748878479004, 3.278918981552124, 24.914398193359375, 1.8940491676330566, 1.5463682413101196, 4600, 0.0001997751124671936]
2023-01-26 01:28:37,874	9nineM	INFO	Train Epoch: 9 [42%]
2023-01-26 01:28:37,875	9nineM	INFO	[2.6231088638305664, 1.9032471179962158, 2.948408603668213, 26.60008430480957, 1.9691338539123535, 1.664552092552185, 4800, 0.0001997751124671936]
2023-01-26 01:29:03,509	9nineM	INFO	Saving model and optimizer state at iteration 9 to ./logs\9nineM\G_4800.pth
2023-01-26 01:29:04,253	9nineM	INFO	Saving model and optimizer state at iteration 9 to ./logs\9nineM\D_4800.pth
2023-01-26 01:32:24,537	9nineM	INFO	Train Epoch: 9 [77%]
2023-01-26 01:32:24,538	9nineM	INFO	[2.762094497680664, 1.8685764074325562, 2.75244140625, 23.52878189086914, 1.8895244598388672, 1.5115458965301514, 5000, 0.0001997751124671936]
2023-01-26 01:34:35,433	9nineM	INFO	====> Epoch: 9
2023-01-26 01:36:10,253	9nineM	INFO	Train Epoch: 10 [12%]
2023-01-26 01:36:10,254	9nineM	INFO	[2.6434783935546875, 2.1471564769744873, 2.7777180671691895, 22.199459075927734, 1.8439451456069946, 1.3497384786605835, 5200, 0.00019975014057813518]
2023-01-26 01:36:36,113	9nineM	INFO	Saving model and optimizer state at iteration 10 to ./logs\9nineM\G_5200.pth
2023-01-26 01:36:37,151	9nineM	INFO	Saving model and optimizer state at iteration 10 to ./logs\9nineM\D_5200.pth
2023-01-26 01:39:58,308	9nineM	INFO	Train Epoch: 10 [47%]
2023-01-26 01:39:58,308	9nineM	INFO	[2.6279044151306152, 2.083256721496582, 3.124328851699829, 26.54741096496582, 1.807456374168396, 1.491945743560791, 5400, 0.00019975014057813518]
2023-01-26 01:43:20,472	9nineM	INFO	Train Epoch: 10 [82%]
2023-01-26 01:43:20,473	9nineM	INFO	[2.732877016067505, 2.007030725479126, 3.1029460430145264, 23.12151527404785, 1.792919397354126, 1.6385772228240967, 5600, 0.00019975014057813518]
2023-01-26 01:43:46,593	9nineM	INFO	Saving model and optimizer state at iteration 10 to ./logs\9nineM\G_5600.pth
2023-01-26 01:43:47,258	9nineM	INFO	Saving model and optimizer state at iteration 10 to ./logs\9nineM\D_5600.pth
2023-01-26 01:45:27,070	9nineM	INFO	====> Epoch: 10
2023-01-26 01:47:32,232	9nineM	INFO	Train Epoch: 11 [18%]
2023-01-26 01:47:32,232	9nineM	INFO	[2.6612348556518555, 1.988817811012268, 3.1589221954345703, 25.66359519958496, 1.9967055320739746, 1.3854045867919922, 5800, 0.00019972517181056292]
2023-01-26 01:50:52,101	9nineM	INFO	Train Epoch: 11 [53%]
2023-01-26 01:50:52,101	9nineM	INFO	[2.4814376831054688, 2.278113842010498, 3.72249436378479, 27.97443389892578, 1.910007357597351, 1.6735199689865112, 6000, 0.00019972517181056292]
2023-01-26 01:51:18,095	9nineM	INFO	Saving model and optimizer state at iteration 11 to ./logs\9nineM\G_6000.pth
2023-01-26 01:51:18,748	9nineM	INFO	Saving model and optimizer state at iteration 11 to ./logs\9nineM\D_6000.pth
2023-01-26 01:54:41,547	9nineM	INFO	Train Epoch: 11 [88%]
2023-01-26 01:54:41,548	9nineM	INFO	[2.840207099914551, 1.8148894309997559, 2.635929584503174, 21.973249435424805, 1.9021368026733398, 1.4054532051086426, 6200, 0.00019972517181056292]
2023-01-26 01:55:52,153	9nineM	INFO	====> Epoch: 11
2023-01-26 01:58:25,991	9nineM	INFO	Train Epoch: 12 [23%]
2023-01-26 01:58:25,992	9nineM	INFO	[2.571866035461426, 2.0023553371429443, 3.5940442085266113, 23.71394157409668, 1.854814052581787, 1.5348354578018188, 6400, 0.0001997002061640866]
2023-01-26 01:58:51,408	9nineM	INFO	Saving model and optimizer state at iteration 12 to ./logs\9nineM\G_6400.pth
2023-01-26 01:58:52,079	9nineM	INFO	Saving model and optimizer state at iteration 12 to ./logs\9nineM\D_6400.pth
2023-01-26 02:02:13,024	9nineM	INFO	Train Epoch: 12 [58%]
2023-01-26 02:02:13,024	9nineM	INFO	[2.714251756668091, 1.8494516611099243, 2.969529628753662, 23.68009376525879, 1.8685411214828491, 1.7101963758468628, 6600, 0.0001997002061640866]
2023-01-26 02:05:34,069	9nineM	INFO	Train Epoch: 12 [93%]
2023-01-26 02:05:34,069	9nineM	INFO	[2.633039951324463, 2.013820171356201, 3.084203004837036, 24.739593505859375, 1.8181004524230957, 1.4082469940185547, 6800, 0.0001997002061640866]
2023-01-26 02:05:59,782	9nineM	INFO	Saving model and optimizer state at iteration 12 to ./logs\9nineM\G_6800.pth
2023-01-26 02:06:00,459	9nineM	INFO	Saving model and optimizer state at iteration 12 to ./logs\9nineM\D_6800.pth
2023-01-26 02:06:41,305	9nineM	INFO	====> Epoch: 12
2023-01-26 02:09:44,501	9nineM	INFO	Train Epoch: 13 [28%]
2023-01-26 02:09:44,502	9nineM	INFO	[2.659205436706543, 2.0233755111694336, 3.2026572227478027, 26.249746322631836, 1.8654255867004395, 1.6150071620941162, 7000, 0.00019967524363831608]
2023-01-26 09:02:48,598	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 16, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-01-26 09:02:52,820	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_6800.pth' (iteration 12)
2023-01-26 09:02:53,280	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_6800.pth' (iteration 12)
2023-01-26 09:03:48,148	9nineM	INFO	Train Epoch: 12 [2%]
2023-01-26 09:03:48,148	9nineM	INFO	[2.67508602142334, 2.0451996326446533, 3.7132022380828857, 26.097049713134766, 1.8588463068008423, 1.780286431312561, 9400, 0.00019967524363831608]
2023-01-26 09:07:02,008	9nineM	INFO	Train Epoch: 12 [25%]
2023-01-26 09:07:02,009	9nineM	INFO	[2.731718063354492, 2.0827178955078125, 2.848446846008301, 25.81690216064453, 1.7822844982147217, 1.586802363395691, 9600, 0.00019967524363831608]
2023-01-26 09:07:32,154	9nineM	INFO	Saving model and optimizer state at iteration 12 to ./logs\9nineM\G_9600.pth
2023-01-26 09:07:33,015	9nineM	INFO	Saving model and optimizer state at iteration 12 to ./logs\9nineM\D_9600.pth
2023-01-26 09:10:21,101	9nineM	INFO	Train Epoch: 12 [49%]
2023-01-26 09:10:21,101	9nineM	INFO	[2.7443857192993164, 2.0565314292907715, 2.6688475608825684, 23.358121871948242, 1.7311820983886719, 1.3396525382995605, 9800, 0.00019967524363831608]
2023-01-26 09:13:06,102	9nineM	INFO	Train Epoch: 12 [72%]
2023-01-26 09:13:06,102	9nineM	INFO	[2.5754849910736084, 2.032925605773926, 3.5489773750305176, 28.008331298828125, 1.9132494926452637, 1.494615912437439, 10000, 0.00019967524363831608]
2023-01-26 09:13:32,731	9nineM	INFO	Saving model and optimizer state at iteration 12 to ./logs\9nineM\G_10000.pth
2023-01-26 09:13:33,393	9nineM	INFO	Saving model and optimizer state at iteration 12 to ./logs\9nineM\D_10000.pth
2023-01-26 09:16:18,444	9nineM	INFO	Train Epoch: 12 [96%]
2023-01-26 09:16:18,445	9nineM	INFO	[3.0923495292663574, 2.1421830654144287, 2.986941337585449, 26.63436508178711, 2.0824522972106934, 1.6558291912078857, 10200, 0.00019967524363831608]
2023-01-26 09:16:47,388	9nineM	INFO	====> Epoch: 12
2023-01-26 09:19:24,538	9nineM	INFO	Train Epoch: 13 [19%]
2023-01-26 09:19:24,538	9nineM	INFO	[2.610954999923706, 1.9253101348876953, 3.20231556892395, 23.34046173095703, 1.7719695568084717, 1.6583393812179565, 10400, 0.0001996502842328613]
2023-01-26 09:19:51,949	9nineM	INFO	Saving model and optimizer state at iteration 13 to ./logs\9nineM\G_10400.pth
2023-01-26 09:19:52,649	9nineM	INFO	Saving model and optimizer state at iteration 13 to ./logs\9nineM\D_10400.pth
2023-01-26 09:22:34,160	9nineM	INFO	Train Epoch: 13 [43%]
2023-01-26 09:22:34,161	9nineM	INFO	[2.7569684982299805, 1.9873456954956055, 2.755460500717163, 23.19409942626953, 1.8952136039733887, 1.5852245092391968, 10600, 0.0001996502842328613]
2023-01-26 09:25:16,266	9nineM	INFO	Train Epoch: 13 [66%]
2023-01-26 15:54:46,732	9nineM	INFO	[2.592890501022339, 1.9014997482299805, 3.476469039916992, 25.275184631347656, 1.8789172172546387, 1.4371107816696167, 10800, 0.0001996502842328613]
2023-01-26 15:55:05,473	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 16, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-01-26 15:55:09,358	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_10400.pth' (iteration 13)
2023-01-26 15:55:09,730	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_10400.pth' (iteration 13)
2023-01-26 15:58:21,399	9nineM	INFO	Train Epoch: 13 [19%]
2023-01-26 15:58:21,399	9nineM	INFO	[2.716689109802246, 1.9423905611038208, 3.1998724937438965, 23.012908935546875, 1.7540184259414673, 1.386572003364563, 10400, 0.00019962532794733217]
2023-01-26 15:58:49,606	9nineM	INFO	Saving model and optimizer state at iteration 13 to ./logs\9nineM\G_10400.pth
2023-01-26 15:58:50,328	9nineM	INFO	Saving model and optimizer state at iteration 13 to ./logs\9nineM\D_10400.pth
2023-01-27 00:38:53,535	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 16, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-01-27 00:39:02,315	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_10400.pth' (iteration 13)
2023-01-27 00:39:02,742	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_10400.pth' (iteration 13)
2023-01-27 00:42:11,285	9nineM	INFO	Train Epoch: 13 [19%]
2023-01-27 00:42:11,285	9nineM	INFO	[2.593064308166504, 2.0389575958251953, 3.3138771057128906, 22.423709869384766, 1.7547038793563843, 1.432450771331787, 10400, 0.00019960037478133875]
2023-01-27 00:42:32,259	9nineM	INFO	Saving model and optimizer state at iteration 13 to ./logs\9nineM\G_10400.pth
2023-01-27 00:42:33,008	9nineM	INFO	Saving model and optimizer state at iteration 13 to ./logs\9nineM\D_10400.pth
2023-01-27 00:46:13,827	9nineM	INFO	Train Epoch: 13 [43%]
2023-01-27 00:46:13,827	9nineM	INFO	[2.556051254272461, 1.9022951126098633, 3.661127805709839, 25.124727249145508, 1.8842947483062744, 1.5525946617126465, 10600, 0.00019960037478133875]
2023-01-27 00:49:07,975	9nineM	INFO	Train Epoch: 13 [66%]
2023-01-27 00:49:07,975	9nineM	INFO	[2.8230438232421875, 1.8189220428466797, 3.3968722820281982, 24.511898040771484, 1.8688939809799194, 1.4538723230361938, 10800, 0.00019960037478133875]
2023-01-27 00:49:28,686	9nineM	INFO	Saving model and optimizer state at iteration 13 to ./logs\9nineM\G_10800.pth
2023-01-27 00:49:29,421	9nineM	INFO	Saving model and optimizer state at iteration 13 to ./logs\9nineM\D_10800.pth
2023-01-27 00:52:19,115	9nineM	INFO	Train Epoch: 13 [90%]
2023-01-27 00:52:19,117	9nineM	INFO	[2.5895962715148926, 2.039095163345337, 3.4108002185821533, 24.823158264160156, 1.814432144165039, 1.4367151260375977, 11000, 0.00019960037478133875]
2023-01-27 00:53:33,975	9nineM	INFO	====> Epoch: 13
2023-01-27 00:55:27,532	9nineM	INFO	Train Epoch: 14 [13%]
2023-01-27 00:55:27,532	9nineM	INFO	[2.579453945159912, 2.1276276111602783, 3.180767297744751, 23.461275100708008, 1.7200267314910889, 1.4411695003509521, 11200, 0.00019957542473449108]
2023-01-27 00:55:48,182	9nineM	INFO	Saving model and optimizer state at iteration 14 to ./logs\9nineM\G_11200.pth
2023-01-27 00:55:48,900	9nineM	INFO	Saving model and optimizer state at iteration 14 to ./logs\9nineM\D_11200.pth
2023-01-27 00:58:39,222	9nineM	INFO	Train Epoch: 14 [36%]
2023-01-27 00:58:39,223	9nineM	INFO	[2.481574535369873, 2.234732151031494, 4.649705410003662, 29.452627182006836, 1.8431586027145386, 1.7566641569137573, 11400, 0.00019957542473449108]
2023-01-27 01:01:28,593	9nineM	INFO	Train Epoch: 14 [60%]
2023-01-27 01:01:28,594	9nineM	INFO	[2.433722972869873, 1.9445536136627197, 4.080624580383301, 25.17411994934082, 1.9031004905700684, 1.701436161994934, 11600, 0.00019957542473449108]
2023-01-27 01:01:49,821	9nineM	INFO	Saving model and optimizer state at iteration 14 to ./logs\9nineM\G_11600.pth
2023-01-27 01:01:50,532	9nineM	INFO	Saving model and optimizer state at iteration 14 to ./logs\9nineM\D_11600.pth
2023-01-27 01:04:40,027	9nineM	INFO	Train Epoch: 14 [83%]
2023-01-27 01:04:40,027	9nineM	INFO	[2.8180198669433594, 1.7142263650894165, 2.1654834747314453, 21.86096954345703, 1.836047649383545, 1.513923168182373, 11800, 0.00019957542473449108]
2023-01-27 01:06:39,771	9nineM	INFO	====> Epoch: 14
2023-01-27 01:07:50,087	9nineM	INFO	Train Epoch: 15 [7%]
2023-01-27 01:07:50,088	9nineM	INFO	[2.7611851692199707, 1.9578686952590942, 3.163517951965332, 23.736661911010742, 1.855008840560913, 1.37441086769104, 12000, 0.00019955047780639926]
2023-01-27 01:08:10,892	9nineM	INFO	Saving model and optimizer state at iteration 15 to ./logs\9nineM\G_12000.pth
2023-01-27 01:08:11,614	9nineM	INFO	Saving model and optimizer state at iteration 15 to ./logs\9nineM\D_12000.pth
2023-01-27 01:10:58,238	9nineM	INFO	Train Epoch: 15 [30%]
2023-01-27 01:10:58,238	9nineM	INFO	[2.6380977630615234, 2.1591074466705322, 3.333003044128418, 26.53448486328125, 1.8846534490585327, 1.4161484241485596, 12200, 0.00019955047780639926]
2023-01-27 01:13:48,357	9nineM	INFO	Train Epoch: 15 [54%]
2023-01-27 01:13:48,357	9nineM	INFO	[2.781557083129883, 1.881882905960083, 2.525613307952881, 23.762874603271484, 1.7821922302246094, 1.4436811208724976, 12400, 0.00019955047780639926]
2023-01-27 01:14:08,613	9nineM	INFO	Saving model and optimizer state at iteration 15 to ./logs\9nineM\G_12400.pth
2023-01-27 01:14:09,329	9nineM	INFO	Saving model and optimizer state at iteration 15 to ./logs\9nineM\D_12400.pth
2023-01-27 01:16:59,263	9nineM	INFO	Train Epoch: 15 [77%]
2023-01-27 01:16:59,264	9nineM	INFO	[2.6985788345336914, 2.0964505672454834, 3.055563449859619, 25.889053344726562, 1.8032093048095703, 1.5241085290908813, 12600, 0.00019955047780639926]
2023-01-27 01:19:43,427	9nineM	INFO	====> Epoch: 15
2023-01-27 01:20:08,148	9nineM	INFO	Train Epoch: 16 [1%]
2023-01-27 01:20:08,149	9nineM	INFO	[2.829136610031128, 1.9012501239776611, 2.156665802001953, 18.423717498779297, 1.8231360912322998, 1.171872854232788, 12800, 0.00019952553399667344]
2023-01-27 01:20:28,566	9nineM	INFO	Saving model and optimizer state at iteration 16 to ./logs\9nineM\G_12800.pth
2023-01-27 01:20:29,380	9nineM	INFO	Saving model and optimizer state at iteration 16 to ./logs\9nineM\D_12800.pth
2023-01-27 01:23:18,991	9nineM	INFO	Train Epoch: 16 [24%]
2023-01-27 01:23:18,991	9nineM	INFO	[2.5594887733459473, 1.8920013904571533, 3.3290469646453857, 23.873504638671875, 1.8619343042373657, 1.33939528465271, 13000, 0.00019952553399667344]
2023-01-27 01:26:07,022	9nineM	INFO	Train Epoch: 16 [47%]
2023-01-27 01:26:07,022	9nineM	INFO	[2.687272787094116, 2.1016502380371094, 3.4579007625579834, 24.758956909179688, 2.1824357509613037, 1.4737794399261475, 13200, 0.00019952553399667344]
2023-01-27 01:26:27,949	9nineM	INFO	Saving model and optimizer state at iteration 16 to ./logs\9nineM\G_13200.pth
2023-01-27 01:26:28,659	9nineM	INFO	Saving model and optimizer state at iteration 16 to ./logs\9nineM\D_13200.pth
2023-01-27 01:29:17,992	9nineM	INFO	Train Epoch: 16 [71%]
2023-01-27 01:29:17,993	9nineM	INFO	[2.369150400161743, 2.2178428173065186, 4.281978130340576, 27.698043823242188, 1.7796082496643066, 1.4050066471099854, 13400, 0.00019952553399667344]
2023-01-27 01:32:06,129	9nineM	INFO	Train Epoch: 16 [94%]
2023-01-27 01:32:06,130	9nineM	INFO	[2.589958429336548, 1.8505977392196655, 4.508889675140381, 27.62240219116211, 1.8430498838424683, 1.6121509075164795, 13600, 0.00019952553399667344]
2023-01-27 01:32:27,115	9nineM	INFO	Saving model and optimizer state at iteration 16 to ./logs\9nineM\G_13600.pth
2023-01-27 01:32:27,776	9nineM	INFO	Saving model and optimizer state at iteration 16 to ./logs\9nineM\D_13600.pth
2023-01-27 01:33:09,471	9nineM	INFO	====> Epoch: 16
2023-01-27 02:17:32,708	9nineM	INFO	Train Epoch: 17 [18%]
2023-01-27 02:17:32,709	9nineM	INFO	[2.5355350971221924, 2.052407741546631, 3.6694445610046387, 24.39693260192871, 1.6474822759628296, 1.6971988677978516, 13800, 0.00019950059330492385]
2023-01-27 02:20:34,347	9nineM	INFO	Train Epoch: 17 [41%]
2023-01-27 02:20:34,347	9nineM	INFO	[2.6254193782806396, 1.9815117120742798, 3.237941026687622, 25.04691505432129, 1.856569528579712, 1.5068683624267578, 14000, 0.00019950059330492385]
2023-01-27 02:20:57,626	9nineM	INFO	Saving model and optimizer state at iteration 17 to ./logs\9nineM\G_14000.pth
2023-01-27 02:20:58,314	9nineM	INFO	Saving model and optimizer state at iteration 17 to ./logs\9nineM\D_14000.pth
2023-01-27 02:23:47,432	9nineM	INFO	Train Epoch: 17 [65%]
2023-01-27 02:23:47,432	9nineM	INFO	[2.7365574836730957, 1.892822265625, 4.043918609619141, 28.595083236694336, 1.8436254262924194, 1.4542126655578613, 14200, 0.00019950059330492385]
2023-01-27 02:26:35,935	9nineM	INFO	Train Epoch: 17 [88%]
2023-01-27 02:26:35,936	9nineM	INFO	[2.5287258625030518, 2.2656726837158203, 4.5845842361450195, 26.422998428344727, 1.8147163391113281, 2.022395610809326, 14400, 0.00019950059330492385]
2023-01-27 02:26:57,398	9nineM	INFO	Saving model and optimizer state at iteration 17 to ./logs\9nineM\G_14400.pth
2023-01-27 02:26:58,079	9nineM	INFO	Saving model and optimizer state at iteration 17 to ./logs\9nineM\D_14400.pth
2023-01-27 02:28:22,913	9nineM	INFO	====> Epoch: 17
2023-01-27 02:30:06,542	9nineM	INFO	Train Epoch: 18 [12%]
2023-01-27 02:30:06,542	9nineM	INFO	[2.778486967086792, 1.9738329648971558, 2.865037202835083, 21.840980529785156, 1.8540937900543213, 1.3941742181777954, 14600, 0.00019947565573076072]
2023-01-27 02:32:53,975	9nineM	INFO	Train Epoch: 18 [35%]
2023-01-27 02:32:53,976	9nineM	INFO	[2.7022876739501953, 2.006470203399658, 3.4777889251708984, 23.463714599609375, 1.8447226285934448, 1.5847468376159668, 14800, 0.00019947565573076072]
2023-01-27 02:33:17,026	9nineM	INFO	Saving model and optimizer state at iteration 18 to ./logs\9nineM\G_14800.pth
2023-01-27 02:33:17,823	9nineM	INFO	Saving model and optimizer state at iteration 18 to ./logs\9nineM\D_14800.pth
2023-01-27 02:36:05,752	9nineM	INFO	Train Epoch: 18 [58%]
2023-01-27 02:36:05,752	9nineM	INFO	[2.6429147720336914, 1.9132986068725586, 2.695805072784424, 21.64963722229004, 1.835808515548706, 1.7501988410949707, 15000, 0.00019947565573076072]
2023-01-27 02:38:53,179	9nineM	INFO	Train Epoch: 18 [82%]
2023-01-27 02:38:53,179	9nineM	INFO	[2.5898306369781494, 2.3537399768829346, 4.625082015991211, 26.387826919555664, 1.6278905868530273, 1.1732033491134644, 15200, 0.00019947565573076072]
2023-01-27 02:39:15,268	9nineM	INFO	Saving model and optimizer state at iteration 18 to ./logs\9nineM\G_15200.pth
2023-01-27 02:39:15,999	9nineM	INFO	Saving model and optimizer state at iteration 18 to ./logs\9nineM\D_15200.pth
2023-01-27 02:41:24,911	9nineM	INFO	====> Epoch: 18
2023-01-27 02:42:24,025	9nineM	INFO	Train Epoch: 19 [5%]
2023-01-27 02:42:24,026	9nineM	INFO	[2.788545608520508, 1.7051345109939575, 2.6826417446136475, 22.653915405273438, 1.8110618591308594, 1.6172281503677368, 15400, 0.00019945072127379438]
2023-01-27 02:45:12,216	9nineM	INFO	Train Epoch: 19 [29%]
2023-01-27 02:45:12,217	9nineM	INFO	[2.7693731784820557, 2.0767621994018555, 3.6112165451049805, 25.01015281677246, 1.833752989768982, 1.9589978456497192, 15600, 0.00019945072127379438]
2023-01-27 02:45:34,167	9nineM	INFO	Saving model and optimizer state at iteration 19 to ./logs\9nineM\G_15600.pth
2023-01-27 02:45:34,961	9nineM	INFO	Saving model and optimizer state at iteration 19 to ./logs\9nineM\D_15600.pth
2023-01-27 02:48:22,774	9nineM	INFO	Train Epoch: 19 [52%]
2023-01-27 02:48:22,774	9nineM	INFO	[2.8319051265716553, 1.6597378253936768, 2.118863105773926, 18.201990127563477, 1.8336409330368042, 1.4559197425842285, 15800, 0.00019945072127379438]
2023-01-27 08:46:44,957	9nineM	INFO	Train Epoch: 19 [76%]
2023-01-27 08:46:44,958	9nineM	INFO	[2.675089120864868, 1.9621834754943848, 3.9128692150115967, 27.38287353515625, 1.9015834331512451, 1.762534737586975, 16000, 0.00019945072127379438]
2023-01-27 08:47:07,560	9nineM	INFO	Saving model and optimizer state at iteration 19 to ./logs\9nineM\G_16000.pth
2023-01-27 08:47:08,457	9nineM	INFO	Saving model and optimizer state at iteration 19 to ./logs\9nineM\D_16000.pth
2023-01-27 08:49:57,926	9nineM	INFO	Train Epoch: 19 [99%]
2023-01-27 08:49:57,926	9nineM	INFO	[2.556715965270996, 2.1266891956329346, 3.8266289234161377, 22.89759635925293, 1.8226630687713623, 1.8882153034210205, 16200, 0.00019945072127379438]
2023-01-27 08:50:04,038	9nineM	INFO	====> Epoch: 19
2023-01-27 08:53:13,237	9nineM	INFO	Train Epoch: 20 [23%]
2023-01-27 08:53:13,238	9nineM	INFO	[2.628126621246338, 2.0548593997955322, 3.6064229011535645, 23.717012405395508, 1.8935389518737793, 1.7230987548828125, 16400, 0.00019942578993363514]
2023-01-27 08:53:35,923	9nineM	INFO	Saving model and optimizer state at iteration 20 to ./logs\9nineM\G_16400.pth
2023-01-27 08:53:36,716	9nineM	INFO	Saving model and optimizer state at iteration 20 to ./logs\9nineM\D_16400.pth
2023-01-27 08:56:28,080	9nineM	INFO	Train Epoch: 20 [46%]
2023-01-27 08:56:28,081	9nineM	INFO	[2.8109192848205566, 1.8798633813858032, 2.577960729598999, 22.258501052856445, 1.7860854864120483, 1.5884227752685547, 16600, 0.00019942578993363514]
2023-01-27 08:59:17,974	9nineM	INFO	Train Epoch: 20 [70%]
2023-01-27 08:59:17,975	9nineM	INFO	[2.5190656185150146, 2.161292552947998, 4.299125671386719, 24.388322830200195, 1.8102023601531982, 1.8811415433883667, 16800, 0.00019942578993363514]
2023-01-27 08:59:41,933	9nineM	INFO	Saving model and optimizer state at iteration 20 to ./logs\9nineM\G_16800.pth
2023-01-27 08:59:42,645	9nineM	INFO	Saving model and optimizer state at iteration 20 to ./logs\9nineM\D_16800.pth
2023-01-27 09:02:31,134	9nineM	INFO	Train Epoch: 20 [93%]
2023-01-27 09:02:31,134	9nineM	INFO	[2.8164849281311035, 1.896257996559143, 2.8522329330444336, 21.2325496673584, 1.7639973163604736, 1.490799903869629, 17000, 0.00019942578993363514]
2023-01-27 09:03:22,220	9nineM	INFO	====> Epoch: 20
2023-01-27 09:05:39,499	9nineM	INFO	Train Epoch: 21 [16%]
2023-01-27 09:05:39,499	9nineM	INFO	[2.772402286529541, 1.900153398513794, 3.176760196685791, 24.0812931060791, 1.7919937372207642, 2.015469789505005, 17200, 0.00019940086170989343]
2023-01-27 09:06:03,219	9nineM	INFO	Saving model and optimizer state at iteration 21 to ./logs\9nineM\G_17200.pth
2023-01-27 09:06:03,932	9nineM	INFO	Saving model and optimizer state at iteration 21 to ./logs\9nineM\D_17200.pth
2023-01-27 09:08:54,501	9nineM	INFO	Train Epoch: 21 [40%]
2023-01-27 09:08:54,501	9nineM	INFO	[2.5729994773864746, 2.1857287883758545, 4.042057991027832, 25.70033073425293, 1.777273416519165, 1.5419124364852905, 17400, 0.00019940086170989343]
2023-01-27 09:11:42,668	9nineM	INFO	Train Epoch: 21 [63%]
2023-01-27 09:11:42,669	9nineM	INFO	[2.6897244453430176, 1.9821608066558838, 3.606863021850586, 24.428430557250977, 1.7553237676620483, 1.764305830001831, 17600, 0.00019940086170989343]
2023-01-27 09:12:05,022	9nineM	INFO	Saving model and optimizer state at iteration 21 to ./logs\9nineM\G_17600.pth
2023-01-27 09:12:05,752	9nineM	INFO	Saving model and optimizer state at iteration 21 to ./logs\9nineM\D_17600.pth
2023-01-27 09:14:54,081	9nineM	INFO	Train Epoch: 21 [87%]
2023-01-27 09:14:54,081	9nineM	INFO	[2.6521155834198, 2.0298845767974854, 3.739675283432007, 22.376190185546875, 1.7662222385406494, 1.4541441202163696, 17800, 0.00019940086170989343]
2023-01-27 09:16:29,852	9nineM	INFO	====> Epoch: 21
2023-01-27 09:18:03,846	9nineM	INFO	Train Epoch: 22 [10%]
2023-01-27 09:18:03,847	9nineM	INFO	[2.406970262527466, 2.1758666038513184, 5.130042552947998, 26.4575138092041, 1.676621437072754, 1.8340210914611816, 18000, 0.0001993759366021797]
2023-01-27 09:18:25,337	9nineM	INFO	Saving model and optimizer state at iteration 22 to ./logs\9nineM\G_18000.pth
2023-01-27 09:18:26,045	9nineM	INFO	Saving model and optimizer state at iteration 22 to ./logs\9nineM\D_18000.pth
2023-01-27 09:21:17,570	9nineM	INFO	Train Epoch: 22 [34%]
2023-01-27 09:21:17,571	9nineM	INFO	[2.5022988319396973, 2.1709604263305664, 3.877980947494507, 22.339065551757812, 1.8137295246124268, 1.437728762626648, 18200, 0.0001993759366021797]
2023-01-27 09:24:04,864	9nineM	INFO	Train Epoch: 22 [57%]
2023-01-27 09:24:04,865	9nineM	INFO	[2.3194479942321777, 2.346053123474121, 5.446766376495361, 26.25181007385254, 1.7403613328933716, 1.8677756786346436, 18400, 0.0001993759366021797]
2023-01-27 09:24:26,720	9nineM	INFO	Saving model and optimizer state at iteration 22 to ./logs\9nineM\G_18400.pth
2023-01-27 09:24:27,402	9nineM	INFO	Saving model and optimizer state at iteration 22 to ./logs\9nineM\D_18400.pth
2023-01-27 09:27:16,868	9nineM	INFO	Train Epoch: 22 [81%]
2023-01-27 09:27:16,868	9nineM	INFO	[2.452756881713867, 2.172793388366699, 4.119320869445801, 23.355058670043945, 1.8487279415130615, 1.761566162109375, 18600, 0.0001993759366021797]
2023-01-27 09:29:35,014	9nineM	INFO	====> Epoch: 22
2023-01-27 09:30:23,489	9nineM	INFO	Train Epoch: 23 [4%]
2023-01-27 09:30:23,489	9nineM	INFO	[2.792853832244873, 1.8062174320220947, 3.4824717044830322, 23.77733039855957, 1.964911699295044, 1.4758468866348267, 18800, 0.00019935101461010442]
2023-01-27 09:30:44,870	9nineM	INFO	Saving model and optimizer state at iteration 23 to ./logs\9nineM\G_18800.pth
2023-01-27 09:30:45,742	9nineM	INFO	Saving model and optimizer state at iteration 23 to ./logs\9nineM\D_18800.pth
2023-01-27 09:33:33,331	9nineM	INFO	Train Epoch: 23 [27%]
2023-01-27 09:33:33,332	9nineM	INFO	[2.721318244934082, 1.8487977981567383, 2.9894800186157227, 22.064241409301758, 1.7476164102554321, 1.894697904586792, 19000, 0.00019935101461010442]
2023-01-27 09:36:22,533	9nineM	INFO	Train Epoch: 23 [51%]
2023-01-27 09:36:22,534	9nineM	INFO	[2.6044092178344727, 2.000493288040161, 3.9952263832092285, 24.704246520996094, 1.8112146854400635, 1.7995251417160034, 19200, 0.00019935101461010442]
2023-01-27 09:36:43,078	9nineM	INFO	Saving model and optimizer state at iteration 23 to ./logs\9nineM\G_19200.pth
2023-01-27 09:36:43,770	9nineM	INFO	Saving model and optimizer state at iteration 23 to ./logs\9nineM\D_19200.pth
2023-01-27 09:39:35,010	9nineM	INFO	Train Epoch: 23 [74%]
2023-01-27 09:39:35,010	9nineM	INFO	[2.6385550498962402, 2.076610803604126, 3.4242939949035645, 17.827404022216797, 1.7784342765808105, 1.388757348060608, 19400, 0.00019935101461010442]
2023-01-27 09:42:22,759	9nineM	INFO	Train Epoch: 23 [98%]
2023-01-27 09:42:22,759	9nineM	INFO	[2.553217887878418, 2.038116216659546, 4.58839750289917, 25.605993270874023, 1.7224760055541992, 1.8490962982177734, 19600, 0.00019935101461010442]
2023-01-27 09:42:44,576	9nineM	INFO	Saving model and optimizer state at iteration 23 to ./logs\9nineM\G_19600.pth
2023-01-27 09:42:45,389	9nineM	INFO	Saving model and optimizer state at iteration 23 to ./logs\9nineM\D_19600.pth
2023-01-27 09:43:01,903	9nineM	INFO	====> Epoch: 23
2023-01-27 09:45:49,362	9nineM	INFO	Train Epoch: 24 [21%]
2023-01-27 09:45:49,362	9nineM	INFO	[2.6483659744262695, 2.3957860469818115, 4.525054454803467, 27.254854202270508, 1.6894183158874512, 1.9978209733963013, 19800, 0.00019932609573327815]
2023-01-27 09:48:37,543	9nineM	INFO	Train Epoch: 24 [45%]
2023-01-27 09:48:37,543	9nineM	INFO	[2.5882065296173096, 1.9280962944030762, 4.218741416931152, 23.399566650390625, 1.7521426677703857, 1.6448408365249634, 20000, 0.00019932609573327815]
2023-01-27 09:48:58,253	9nineM	INFO	Saving model and optimizer state at iteration 24 to ./logs\9nineM\G_20000.pth
2023-01-27 09:48:58,918	9nineM	INFO	Saving model and optimizer state at iteration 24 to ./logs\9nineM\D_20000.pth
2023-01-30 13:59:29,423	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 16, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-01-30 13:59:38,603	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_20000.pth' (iteration 24)
2023-01-30 13:59:39,032	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_20000.pth' (iteration 24)
2023-01-30 14:03:00,845	9nineM	INFO	Train Epoch: 24 [21%]
2023-01-30 14:03:00,846	9nineM	INFO	[2.4233226776123047, 2.264484405517578, 5.42818546295166, 26.408262252807617, 1.6991338729858398, 1.9326978921890259, 19800, 0.0001993011799713115]
2023-01-30 14:05:55,926	9nineM	INFO	Train Epoch: 24 [45%]
2023-01-30 14:05:55,926	9nineM	INFO	[2.7016305923461914, 2.134594678878784, 3.7914786338806152, 24.01327896118164, 1.7582862377166748, 1.6192069053649902, 20000, 0.0001993011799713115]
2023-01-30 14:06:17,885	9nineM	INFO	Saving model and optimizer state at iteration 24 to ./logs\9nineM\G_20000.pth
2023-01-30 14:06:18,616	9nineM	INFO	Saving model and optimizer state at iteration 24 to ./logs\9nineM\D_20000.pth
2023-01-30 14:09:10,456	9nineM	INFO	Train Epoch: 24 [68%]
2023-01-30 14:09:10,457	9nineM	INFO	[2.496549606323242, 2.2131459712982178, 4.638711929321289, 24.81015968322754, 1.9151177406311035, 1.8024846315383911, 20200, 0.0001993011799713115]
2023-01-30 14:11:55,194	9nineM	INFO	Train Epoch: 24 [92%]
2023-01-30 14:11:55,195	9nineM	INFO	[2.6104557514190674, 2.0642175674438477, 3.8007540702819824, 22.306468963623047, 1.720705270767212, 1.5101583003997803, 20400, 0.0001993011799713115]
2023-01-30 14:12:15,118	9nineM	INFO	Saving model and optimizer state at iteration 24 to ./logs\9nineM\G_20400.pth
2023-01-30 14:12:15,871	9nineM	INFO	Saving model and optimizer state at iteration 24 to ./logs\9nineM\D_20400.pth
2023-01-30 14:13:16,359	9nineM	INFO	====> Epoch: 24
2023-01-30 14:15:21,547	9nineM	INFO	Train Epoch: 25 [15%]
2023-01-30 14:15:21,548	9nineM	INFO	[2.5959115028381348, 2.238276481628418, 5.503964424133301, 27.154827117919922, 2.0218310356140137, 1.794956922531128, 20600, 0.00019927626732381507]
2023-01-30 14:18:07,501	9nineM	INFO	Train Epoch: 25 [38%]
2023-01-30 14:18:07,502	9nineM	INFO	[2.6357550621032715, 2.1467175483703613, 3.890899658203125, 20.90275764465332, 1.7875596284866333, 1.3034027814865112, 20800, 0.00019927626732381507]
2023-01-30 14:18:27,806	9nineM	INFO	Saving model and optimizer state at iteration 25 to ./logs\9nineM\G_20800.pth
2023-01-30 14:18:28,838	9nineM	INFO	Saving model and optimizer state at iteration 25 to ./logs\9nineM\D_20800.pth
2023-01-30 14:21:14,504	9nineM	INFO	Train Epoch: 25 [62%]
2023-01-30 14:21:14,504	9nineM	INFO	[2.5597102642059326, 1.9738388061523438, 4.298656940460205, 26.072538375854492, 1.8264048099517822, 1.645263671875, 21000, 0.00019927626732381507]
2023-01-30 14:23:56,732	9nineM	INFO	Train Epoch: 25 [85%]
2023-01-30 14:23:56,733	9nineM	INFO	[2.357044219970703, 2.2680459022521973, 5.406231880187988, 26.98268699645996, 1.8424121141433716, 1.744455337524414, 21200, 0.00019927626732381507]
2023-01-30 14:24:16,887	9nineM	INFO	Saving model and optimizer state at iteration 25 to ./logs\9nineM\G_21200.pth
2023-01-30 14:24:17,524	9nineM	INFO	Saving model and optimizer state at iteration 25 to ./logs\9nineM\D_21200.pth
2023-01-30 14:26:00,682	9nineM	INFO	====> Epoch: 25
2023-01-30 14:27:20,457	9nineM	INFO	Train Epoch: 26 [9%]
2023-01-30 14:27:20,457	9nineM	INFO	[2.513702392578125, 2.582909107208252, 5.313809394836426, 26.997928619384766, 1.891054630279541, 1.5602864027023315, 21400, 0.00019925135779039958]
2023-01-30 18:10:59,516	9nineM	INFO	Train Epoch: 26 [32%]
2023-01-30 18:10:59,517	9nineM	INFO	[2.7052407264709473, 1.8598670959472656, 3.4029574394226074, 23.73880958557129, 1.822087287902832, 1.5161125659942627, 21600, 0.00019925135779039958]
2023-01-30 18:11:20,473	9nineM	INFO	Saving model and optimizer state at iteration 26 to ./logs\9nineM\G_21600.pth
2023-01-30 18:11:21,309	9nineM	INFO	Saving model and optimizer state at iteration 26 to ./logs\9nineM\D_21600.pth
2023-01-30 18:14:08,306	9nineM	INFO	Train Epoch: 26 [56%]
2023-01-30 18:14:08,306	9nineM	INFO	[2.6186649799346924, 2.2027549743652344, 4.938816547393799, 26.00452423095703, 1.8225845098495483, 1.6558605432510376, 21800, 0.00019925135779039958]
2023-01-30 18:16:57,734	9nineM	INFO	Train Epoch: 26 [79%]
2023-01-30 18:16:57,735	9nineM	INFO	[2.551978588104248, 2.255690336227417, 4.471135139465332, 23.771936416625977, 1.763396143913269, 2.0592684745788574, 22000, 0.00019925135779039958]
2023-01-30 18:17:20,708	9nineM	INFO	Saving model and optimizer state at iteration 26 to ./logs\9nineM\G_22000.pth
2023-01-30 18:17:21,406	9nineM	INFO	Saving model and optimizer state at iteration 26 to ./logs\9nineM\D_22000.pth
2023-01-30 18:19:51,123	9nineM	INFO	====> Epoch: 26
2023-01-30 18:20:29,464	9nineM	INFO	Train Epoch: 27 [3%]
2023-01-30 18:20:29,465	9nineM	INFO	[2.6391866207122803, 2.0543909072875977, 3.5250117778778076, 20.959144592285156, 1.9019776582717896, 1.7802704572677612, 22200, 0.00019922645137067577]
2023-01-30 18:23:15,861	9nineM	INFO	Train Epoch: 27 [26%]
2023-01-30 18:23:15,861	9nineM	INFO	[2.5170674324035645, 2.090766191482544, 4.516193866729736, 24.13702964782715, 1.7424182891845703, 1.6825942993164062, 22400, 0.00019922645137067577]
2023-01-30 18:23:39,074	9nineM	INFO	Saving model and optimizer state at iteration 27 to ./logs\9nineM\G_22400.pth
2023-01-30 18:23:39,826	9nineM	INFO	Saving model and optimizer state at iteration 27 to ./logs\9nineM\D_22400.pth
2023-01-30 18:26:23,799	9nineM	INFO	Train Epoch: 27 [49%]
2023-01-30 18:26:23,800	9nineM	INFO	[2.547278881072998, 1.9589873552322388, 4.607811450958252, 25.4031982421875, 1.9924721717834473, 1.5493937730789185, 22600, 0.00019922645137067577]
2023-01-30 18:29:08,934	9nineM	INFO	Train Epoch: 27 [73%]
2023-01-30 18:29:08,935	9nineM	INFO	[2.5946264266967773, 2.019632339477539, 3.988851547241211, 23.66800308227539, 1.797306776046753, 1.6523672342300415, 22800, 0.00019922645137067577]
2023-01-30 18:29:32,238	9nineM	INFO	Saving model and optimizer state at iteration 27 to ./logs\9nineM\G_22800.pth
2023-01-30 18:29:32,841	9nineM	INFO	Saving model and optimizer state at iteration 27 to ./logs\9nineM\D_22800.pth
2023-01-30 18:32:17,705	9nineM	INFO	Train Epoch: 27 [96%]
2023-01-30 18:32:17,705	9nineM	INFO	[2.547029733657837, 2.055783987045288, 4.41702127456665, 23.861553192138672, 1.7669410705566406, 1.7388036251068115, 23000, 0.00019922645137067577]
2023-01-30 18:32:43,688	9nineM	INFO	====> Epoch: 27
2023-01-30 18:35:21,166	9nineM	INFO	Train Epoch: 28 [20%]
2023-01-30 18:35:21,167	9nineM	INFO	[2.7444093227386475, 1.7981352806091309, 3.0811824798583984, 20.980642318725586, 1.913151502609253, 1.5842145681381226, 23200, 0.00019920154806425444]
2023-01-30 18:35:41,774	9nineM	INFO	Saving model and optimizer state at iteration 28 to ./logs\9nineM\G_23200.pth
2023-01-30 18:35:42,381	9nineM	INFO	Saving model and optimizer state at iteration 28 to ./logs\9nineM\D_23200.pth
2023-01-30 18:38:26,005	9nineM	INFO	Train Epoch: 28 [43%]
2023-01-30 18:38:26,006	9nineM	INFO	[2.6017751693725586, 2.223775625228882, 3.6733932495117188, 22.91482162475586, 1.9081027507781982, 1.4144500494003296, 23400, 0.00019920154806425444]
2023-01-30 18:41:10,378	9nineM	INFO	Train Epoch: 28 [67%]
2023-01-30 18:41:10,379	9nineM	INFO	[2.670208692550659, 1.9337886571884155, 4.112267017364502, 26.20232582092285, 1.8177591562271118, 1.6691386699676514, 23600, 0.00019920154806425444]
2023-01-30 18:41:31,000	9nineM	INFO	Saving model and optimizer state at iteration 28 to ./logs\9nineM\G_23600.pth
2023-01-30 18:41:31,643	9nineM	INFO	Saving model and optimizer state at iteration 28 to ./logs\9nineM\D_23600.pth
2023-01-30 18:44:14,911	9nineM	INFO	Train Epoch: 28 [90%]
2023-01-30 18:44:15,550	9nineM	INFO	[2.633009672164917, 1.9814497232437134, 3.7151012420654297, 22.778528213500977, 1.764923095703125, 1.6637474298477173, 23800, 0.00019920154806425444]
2023-01-30 18:45:25,479	9nineM	INFO	====> Epoch: 28
2023-01-30 18:47:21,988	9nineM	INFO	Train Epoch: 29 [14%]
2023-01-30 18:47:21,988	9nineM	INFO	[2.649714469909668, 2.1912989616394043, 4.456567764282227, 26.76620101928711, 1.807680606842041, 1.6745903491973877, 24000, 0.0001991766478707464]
2023-01-30 18:47:42,427	9nineM	INFO	Saving model and optimizer state at iteration 29 to ./logs\9nineM\G_24000.pth
2023-01-30 18:47:43,051	9nineM	INFO	Saving model and optimizer state at iteration 29 to ./logs\9nineM\D_24000.pth
2023-01-30 18:50:28,999	9nineM	INFO	Train Epoch: 29 [37%]
2023-01-30 18:50:28,999	9nineM	INFO	[2.6999549865722656, 1.72980535030365, 3.750908613204956, 21.631378173828125, 1.8146204948425293, 1.8793796300888062, 24200, 0.0001991766478707464]
2023-01-30 18:53:16,206	9nineM	INFO	Train Epoch: 29 [60%]
2023-01-30 18:53:16,207	9nineM	INFO	[2.6130964756011963, 2.2319231033325195, 3.7719619274139404, 23.3356990814209, 1.9559910297393799, 1.5747816562652588, 24400, 0.0001991766478707464]
2023-01-30 18:53:37,035	9nineM	INFO	Saving model and optimizer state at iteration 29 to ./logs\9nineM\G_24400.pth
2023-01-30 18:53:37,742	9nineM	INFO	Saving model and optimizer state at iteration 29 to ./logs\9nineM\D_24400.pth
2023-01-30 18:56:24,358	9nineM	INFO	Train Epoch: 29 [84%]
2023-01-30 18:56:24,359	9nineM	INFO	[2.4868788719177246, 2.1619656085968018, 3.933049440383911, 22.357912063598633, 1.8085817098617554, 1.6935052871704102, 24600, 0.0001991766478707464]
2023-01-30 18:58:19,433	9nineM	INFO	====> Epoch: 29
2023-01-30 18:59:31,794	9nineM	INFO	Train Epoch: 30 [7%]
2023-01-30 18:59:31,795	9nineM	INFO	[2.499490261077881, 2.3587687015533447, 5.103172779083252, 25.08675193786621, 1.7192392349243164, 1.5048335790634155, 24800, 0.00019915175078976256]
2023-01-30 18:59:52,771	9nineM	INFO	Saving model and optimizer state at iteration 30 to ./logs\9nineM\G_24800.pth
2023-01-30 18:59:53,387	9nineM	INFO	Saving model and optimizer state at iteration 30 to ./logs\9nineM\D_24800.pth
2023-01-30 19:02:38,186	9nineM	INFO	Train Epoch: 30 [31%]
2023-01-30 19:02:38,186	9nineM	INFO	[2.583420753479004, 2.1125028133392334, 3.964524984359741, 23.267152786254883, 1.8850966691970825, 1.6562895774841309, 25000, 0.00019915175078976256]
2023-01-31 04:49:25,531	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 16, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-01-31 04:49:35,110	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_24800.pth' (iteration 30)
2023-01-31 04:49:35,569	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_24800.pth' (iteration 30)
2023-01-31 04:51:15,260	9nineM	INFO	Train Epoch: 30 [7%]
2023-01-31 04:51:15,260	9nineM	INFO	[2.6226367950439453, 2.27891206741333, 4.0941691398620605, 23.037940979003906, 1.7086595296859741, 1.4919545650482178, 24800, 0.00019912685682091382]
2023-01-31 04:51:36,640	9nineM	INFO	Saving model and optimizer state at iteration 30 to ./logs\9nineM\G_24800.pth
2023-01-31 04:51:37,318	9nineM	INFO	Saving model and optimizer state at iteration 30 to ./logs\9nineM\D_24800.pth
2023-01-31 04:54:43,694	9nineM	INFO	Train Epoch: 30 [31%]
2023-01-31 04:54:43,695	9nineM	INFO	[2.5988283157348633, 1.9622220993041992, 4.1986165046691895, 24.72119140625, 1.8875558376312256, 1.4754257202148438, 25000, 0.00019912685682091382]
2023-01-31 04:57:37,570	9nineM	INFO	Train Epoch: 30 [54%]
2023-01-31 04:57:37,570	9nineM	INFO	[2.561371088027954, 2.0544097423553467, 4.946720600128174, 25.388317108154297, 1.6937508583068848, 1.4395828247070312, 25200, 0.00019912685682091382]
2023-01-31 04:57:57,142	9nineM	INFO	Saving model and optimizer state at iteration 30 to ./logs\9nineM\G_25200.pth
2023-01-31 04:57:57,831	9nineM	INFO	Saving model and optimizer state at iteration 30 to ./logs\9nineM\D_25200.pth
2023-01-31 05:00:46,785	9nineM	INFO	Train Epoch: 30 [78%]
2023-01-31 05:00:46,786	9nineM	INFO	[2.680049180984497, 1.9173710346221924, 3.4602537155151367, 21.217208862304688, 1.7393698692321777, 1.491133213043213, 25400, 0.00019912685682091382]
2023-01-31 05:03:25,215	9nineM	INFO	====> Epoch: 30
2023-01-31 05:03:54,977	9nineM	INFO	Train Epoch: 31 [1%]
2023-01-31 05:03:54,978	9nineM	INFO	[2.5413079261779785, 2.105044364929199, 5.600437164306641, 25.1304874420166, 1.7264471054077148, 1.8673486709594727, 25600, 0.0001991019659638112]
2023-01-31 05:04:16,603	9nineM	INFO	Saving model and optimizer state at iteration 31 to ./logs\9nineM\G_25600.pth
2023-01-31 05:04:17,299	9nineM	INFO	Saving model and optimizer state at iteration 31 to ./logs\9nineM\D_25600.pth
2023-01-31 05:07:05,801	9nineM	INFO	Train Epoch: 31 [25%]
2023-01-31 05:07:05,802	9nineM	INFO	[2.3959808349609375, 2.241203784942627, 5.791626453399658, 25.418806076049805, 1.9717110395431519, 1.7215012311935425, 25800, 0.0001991019659638112]
2023-01-31 05:09:51,162	9nineM	INFO	Train Epoch: 31 [48%]
2023-01-31 05:09:51,162	9nineM	INFO	[2.6000561714172363, 2.079279661178589, 4.181294918060303, 22.890228271484375, 1.8438432216644287, 1.5096122026443481, 26000, 0.0001991019659638112]
2023-01-31 05:10:11,010	9nineM	INFO	Saving model and optimizer state at iteration 31 to ./logs\9nineM\G_26000.pth
2023-01-31 05:10:11,637	9nineM	INFO	Saving model and optimizer state at iteration 31 to ./logs\9nineM\D_26000.pth
2023-01-31 05:12:59,049	9nineM	INFO	Train Epoch: 31 [72%]
2023-01-31 05:12:59,049	9nineM	INFO	[2.6699235439300537, 2.1806726455688477, 5.055631160736084, 24.23531723022461, 1.797062635421753, 1.7649749517440796, 26200, 0.0001991019659638112]
2023-01-31 05:15:46,363	9nineM	INFO	Train Epoch: 31 [95%]
2023-01-31 05:15:46,363	9nineM	INFO	[2.6502323150634766, 2.0901808738708496, 3.862999200820923, 22.471010208129883, 1.7703263759613037, 1.6136788129806519, 26400, 0.0001991019659638112]
2023-01-31 05:16:06,340	9nineM	INFO	Saving model and optimizer state at iteration 31 to ./logs\9nineM\G_26400.pth
2023-01-31 05:16:06,965	9nineM	INFO	Saving model and optimizer state at iteration 31 to ./logs\9nineM\D_26400.pth
2023-01-31 05:16:42,029	9nineM	INFO	====> Epoch: 31
2023-01-31 05:19:12,147	9nineM	INFO	Train Epoch: 32 [18%]
2023-01-31 05:19:12,147	9nineM	INFO	[2.6070947647094727, 2.0558505058288574, 4.700134754180908, 25.00912094116211, 1.792651653289795, 1.6968674659729004, 26600, 0.0001990770782180657]
2023-01-31 05:21:57,844	9nineM	INFO	Train Epoch: 32 [42%]
2023-01-31 05:21:57,845	9nineM	INFO	[2.65460467338562, 2.012608051300049, 3.73614501953125, 22.191423416137695, 1.8420199155807495, 1.6775685548782349, 26800, 0.0001990770782180657]
2023-01-31 05:22:17,933	9nineM	INFO	Saving model and optimizer state at iteration 32 to ./logs\9nineM\G_26800.pth
2023-01-31 05:22:18,570	9nineM	INFO	Saving model and optimizer state at iteration 32 to ./logs\9nineM\D_26800.pth
2023-01-31 05:25:05,714	9nineM	INFO	Train Epoch: 32 [65%]
2023-01-31 05:25:05,715	9nineM	INFO	[2.508659839630127, 1.9928182363510132, 4.465345859527588, 23.401477813720703, 1.8576054573059082, 1.9069682359695435, 27000, 0.0001990770782180657]
2023-01-31 05:27:48,723	9nineM	INFO	Train Epoch: 32 [89%]
2023-01-31 05:27:48,724	9nineM	INFO	[2.682878255844116, 2.067652940750122, 5.124716758728027, 24.11802101135254, 1.7524895668029785, 1.6737695932388306, 27200, 0.0001990770782180657]
2023-01-31 05:28:09,228	9nineM	INFO	Saving model and optimizer state at iteration 32 to ./logs\9nineM\G_27200.pth
2023-01-31 05:28:09,926	9nineM	INFO	Saving model and optimizer state at iteration 32 to ./logs\9nineM\D_27200.pth
2023-01-31 05:29:29,049	9nineM	INFO	====> Epoch: 32
2023-01-31 14:47:22,857	9nineM	INFO	Train Epoch: 33 [12%]
2023-01-31 14:47:22,857	9nineM	INFO	[2.700671911239624, 2.1198341846466064, 3.753757953643799, 20.68313980102539, 1.7996970415115356, 1.574100136756897, 27400, 0.00019905219358328844]
2023-02-01 04:21:25,016	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 16, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-02-01 04:21:33,771	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_27200.pth' (iteration 32)
2023-02-01 04:21:34,210	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_27200.pth' (iteration 32)
2023-02-01 04:24:26,163	9nineM	INFO	Train Epoch: 32 [18%]
2023-02-01 04:24:26,163	9nineM	INFO	[2.48793363571167, 2.2525389194488525, 4.615845680236816, 23.471406936645508, 1.8075923919677734, 1.2398854494094849, 26600, 0.00019905219358328844]
2023-02-01 04:27:17,258	9nineM	INFO	Train Epoch: 32 [42%]
2023-02-01 04:27:17,258	9nineM	INFO	[2.8085086345672607, 1.9309682846069336, 3.242536783218384, 19.992431640625, 1.8259313106536865, 1.75313138961792, 26800, 0.00019905219358328844]
2023-02-01 04:27:36,984	9nineM	INFO	Saving model and optimizer state at iteration 32 to ./logs\9nineM\G_26800.pth
2023-02-01 04:27:37,607	9nineM	INFO	Saving model and optimizer state at iteration 32 to ./logs\9nineM\D_26800.pth
2023-02-01 04:30:27,759	9nineM	INFO	Train Epoch: 32 [65%]
2023-02-01 04:30:27,760	9nineM	INFO	[2.512181520462036, 2.1234545707702637, 4.441719055175781, 23.193981170654297, 1.8304362297058105, 1.2039990425109863, 27000, 0.00019905219358328844]
2023-02-01 04:33:11,405	9nineM	INFO	Train Epoch: 32 [89%]
2023-02-01 04:33:11,406	9nineM	INFO	[2.4839420318603516, 2.347658395767212, 5.918729782104492, 24.70970916748047, 1.751023530960083, 1.626118540763855, 27200, 0.00019905219358328844]
2023-02-01 04:33:31,473	9nineM	INFO	Saving model and optimizer state at iteration 32 to ./logs\9nineM\G_27200.pth
2023-02-01 04:33:32,109	9nineM	INFO	Saving model and optimizer state at iteration 32 to ./logs\9nineM\D_27200.pth
2023-02-01 04:34:50,506	9nineM	INFO	====> Epoch: 32
2023-02-01 04:36:34,629	9nineM	INFO	Train Epoch: 33 [12%]
2023-02-01 04:36:34,629	9nineM	INFO	[2.789337396621704, 1.9480953216552734, 3.569427013397217, 19.851818084716797, 1.7902283668518066, 1.5726020336151123, 27400, 0.0001990273120590905]
2023-02-01 04:39:19,633	9nineM	INFO	Train Epoch: 33 [36%]
2023-02-01 04:39:19,633	9nineM	INFO	[2.5463850498199463, 2.106318473815918, 4.98954439163208, 23.31874656677246, 1.740237832069397, 1.4912023544311523, 27600, 0.0001990273120590905]
2023-02-01 04:39:39,767	9nineM	INFO	Saving model and optimizer state at iteration 33 to ./logs\9nineM\G_27600.pth
2023-02-01 04:39:40,460	9nineM	INFO	Saving model and optimizer state at iteration 33 to ./logs\9nineM\D_27600.pth
2023-02-01 04:42:24,582	9nineM	INFO	Train Epoch: 33 [59%]
2023-02-01 04:42:24,583	9nineM	INFO	[2.5366666316986084, 2.304074764251709, 5.535372734069824, 25.677494049072266, 1.8105485439300537, 1.6906741857528687, 27800, 0.0001990273120590905]
2023-02-01 04:45:10,402	9nineM	INFO	Train Epoch: 33 [83%]
2023-02-01 04:45:10,402	9nineM	INFO	[2.5908730030059814, 2.0369601249694824, 3.4531235694885254, 21.35690689086914, 1.712050437927246, 1.7326159477233887, 28000, 0.0001990273120590905]
2023-02-01 04:45:30,840	9nineM	INFO	Saving model and optimizer state at iteration 33 to ./logs\9nineM\G_28000.pth
2023-02-01 04:45:31,536	9nineM	INFO	Saving model and optimizer state at iteration 33 to ./logs\9nineM\D_28000.pth
2023-02-01 04:47:34,384	9nineM	INFO	====> Epoch: 33
2023-02-01 04:48:34,814	9nineM	INFO	Train Epoch: 34 [6%]
2023-02-01 04:48:34,814	9nineM	INFO	[2.682081937789917, 2.1056137084960938, 3.03806209564209, 20.2428035736084, 1.8532049655914307, 1.7690595388412476, 28200, 0.00019900243364508313]
2023-02-01 04:51:19,132	9nineM	INFO	Train Epoch: 34 [29%]
2023-02-01 04:51:19,133	9nineM	INFO	[2.638190507888794, 1.9988296031951904, 3.910902738571167, 21.806364059448242, 1.6923742294311523, 1.890233039855957, 28400, 0.00019900243364508313]
2023-02-01 04:51:39,019	9nineM	INFO	Saving model and optimizer state at iteration 34 to ./logs\9nineM\G_28400.pth
2023-02-01 04:51:39,655	9nineM	INFO	Saving model and optimizer state at iteration 34 to ./logs\9nineM\D_28400.pth
2023-02-01 04:54:26,885	9nineM	INFO	Train Epoch: 34 [53%]
2023-02-01 04:54:26,885	9nineM	INFO	[2.4265389442443848, 2.2317376136779785, 5.2667341232299805, 23.620227813720703, 1.7587745189666748, 1.4747239351272583, 28600, 0.00019900243364508313]
2023-02-01 04:57:10,543	9nineM	INFO	Train Epoch: 34 [76%]
2023-02-01 04:57:10,544	9nineM	INFO	[2.699652910232544, 2.020946502685547, 3.3295412063598633, 21.935319900512695, 2.068636178970337, 1.361405611038208, 28800, 0.00019900243364508313]
2023-02-01 04:57:30,489	9nineM	INFO	Saving model and optimizer state at iteration 34 to ./logs\9nineM\G_28800.pth
2023-02-01 04:57:31,198	9nineM	INFO	Saving model and optimizer state at iteration 34 to ./logs\9nineM\D_28800.pth
2023-02-01 05:00:15,492	9nineM	INFO	Train Epoch: 34 [100%]
2023-02-01 05:00:15,494	9nineM	INFO	[2.6213345527648926, 2.156693935394287, 4.387364864349365, 21.24164390563965, 1.7850232124328613, 1.6613390445709229, 29000, 0.00019900243364508313]
2023-02-01 05:00:17,261	9nineM	INFO	====> Epoch: 34
2023-02-01 05:03:20,006	9nineM	INFO	Train Epoch: 35 [23%]
2023-02-01 05:03:20,007	9nineM	INFO	[2.516507625579834, 2.2165496349334717, 5.759872913360596, 24.848791122436523, 1.8999265432357788, 1.5627009868621826, 29200, 0.0001989775583408775]
2023-02-01 05:03:39,809	9nineM	INFO	Saving model and optimizer state at iteration 35 to ./logs\9nineM\G_29200.pth
2023-02-01 05:03:40,426	9nineM	INFO	Saving model and optimizer state at iteration 35 to ./logs\9nineM\D_29200.pth
2023-02-01 12:33:05,510	9nineM	INFO	Train Epoch: 35 [47%]
2023-02-01 12:33:05,510	9nineM	INFO	[2.5423824787139893, 2.025073528289795, 3.994418144226074, 22.05137825012207, 1.7776260375976562, 1.5611302852630615, 29400, 0.0001989775583408775]
2023-02-01 12:35:52,822	9nineM	INFO	Train Epoch: 35 [70%]
2023-02-01 12:35:52,823	9nineM	INFO	[2.6309142112731934, 1.976047396659851, 5.686556816101074, 24.51500129699707, 1.7515478134155273, 1.64219069480896, 29600, 0.0001989775583408775]
2023-02-01 12:36:20,975	9nineM	INFO	Saving model and optimizer state at iteration 35 to ./logs\9nineM\G_29600.pth
2023-02-01 12:36:21,668	9nineM	INFO	Saving model and optimizer state at iteration 35 to ./logs\9nineM\D_29600.pth
2023-02-01 12:39:09,483	9nineM	INFO	Train Epoch: 35 [94%]
2023-02-01 12:39:09,483	9nineM	INFO	[2.6399784088134766, 2.0212554931640625, 4.624053955078125, 24.235794067382812, 1.6122325658798218, 1.8134409189224243, 29800, 0.0001989775583408775]
2023-02-01 12:39:55,536	9nineM	INFO	====> Epoch: 35
2023-02-01 12:42:17,621	9nineM	INFO	Train Epoch: 36 [17%]
2023-02-01 12:42:17,622	9nineM	INFO	[2.7085700035095215, 1.9565938711166382, 3.421661376953125, 20.876976013183594, 1.7802507877349854, 1.489966630935669, 30000, 0.00019895268614608487]
2023-02-01 12:42:41,751	9nineM	INFO	Saving model and optimizer state at iteration 36 to ./logs\9nineM\G_30000.pth
2023-02-01 12:42:42,555	9nineM	INFO	Saving model and optimizer state at iteration 36 to ./logs\9nineM\D_30000.pth
2023-02-01 12:45:30,464	9nineM	INFO	Train Epoch: 36 [40%]
2023-02-01 12:45:30,464	9nineM	INFO	[2.437509536743164, 2.3491921424865723, 5.127066135406494, 25.726490020751953, 1.7633036375045776, 1.4489428997039795, 30200, 0.00019895268614608487]
2023-02-01 12:48:16,161	9nineM	INFO	Train Epoch: 36 [64%]
2023-02-01 12:48:16,162	9nineM	INFO	[2.3928329944610596, 2.101041555404663, 5.352329254150391, 27.370100021362305, 1.8160617351531982, 1.6697053909301758, 30400, 0.00019895268614608487]
2023-02-01 12:48:39,509	9nineM	INFO	Saving model and optimizer state at iteration 36 to ./logs\9nineM\G_30400.pth
2023-02-01 12:48:40,196	9nineM	INFO	Saving model and optimizer state at iteration 36 to ./logs\9nineM\D_30400.pth
2023-02-01 12:51:27,729	9nineM	INFO	Train Epoch: 36 [87%]
2023-02-01 12:51:27,729	9nineM	INFO	[2.61594557762146, 2.1400556564331055, 5.137139797210693, 23.10220718383789, 1.6802095174789429, 1.7627167701721191, 30600, 0.00019895268614608487]
2023-02-01 12:52:59,177	9nineM	INFO	====> Epoch: 36
2023-02-01 12:54:35,488	9nineM	INFO	Train Epoch: 37 [11%]
2023-02-01 12:54:35,488	9nineM	INFO	[2.5741822719573975, 2.1620121002197266, 4.317616939544678, 22.92330551147461, 1.829906940460205, 1.4284659624099731, 30800, 0.0001989278170603166]
2023-02-01 12:54:57,689	9nineM	INFO	Saving model and optimizer state at iteration 37 to ./logs\9nineM\G_30800.pth
2023-02-01 12:54:58,437	9nineM	INFO	Saving model and optimizer state at iteration 37 to ./logs\9nineM\D_30800.pth
2023-02-01 12:57:45,024	9nineM	INFO	Train Epoch: 37 [34%]
2023-02-01 12:57:45,025	9nineM	INFO	[2.6818103790283203, 1.954439640045166, 3.375948905944824, 20.640331268310547, 1.8592307567596436, 1.7136640548706055, 31000, 0.0001989278170603166]
2023-02-01 13:00:32,094	9nineM	INFO	Train Epoch: 37 [58%]
2023-02-01 13:00:32,095	9nineM	INFO	[2.459219455718994, 2.320885181427002, 5.924901008605957, 26.83432960510254, 1.7563282251358032, 1.726936936378479, 31200, 0.0001989278170603166]
2023-02-01 17:01:39,949	9nineM	INFO	Saving model and optimizer state at iteration 37 to ./logs\9nineM\G_31200.pth
2023-02-01 17:01:40,916	9nineM	INFO	Saving model and optimizer state at iteration 37 to ./logs\9nineM\D_31200.pth
2023-02-01 17:04:25,245	9nineM	INFO	Train Epoch: 37 [81%]
2023-02-01 17:04:25,246	9nineM	INFO	[2.669224977493286, 1.9848904609680176, 4.381429672241211, 21.905603408813477, 1.6953556537628174, 1.6629891395568848, 31400, 0.0001989278170603166]
2023-02-01 17:06:48,635	9nineM	INFO	====> Epoch: 37
2023-02-01 17:07:50,247	9nineM	INFO	Train Epoch: 38 [5%]
2023-02-01 17:07:50,248	9nineM	INFO	[2.744645118713379, 1.8825947046279907, 3.460026264190674, 19.298295974731445, 1.788069248199463, 1.6396377086639404, 31600, 0.00019890295108318404]
2023-02-01 17:08:15,740	9nineM	INFO	Saving model and optimizer state at iteration 38 to ./logs\9nineM\G_31600.pth
2023-02-01 17:08:16,556	9nineM	INFO	Saving model and optimizer state at iteration 38 to ./logs\9nineM\D_31600.pth
2023-02-01 17:11:31,453	9nineM	INFO	Train Epoch: 38 [28%]
2023-02-01 17:11:31,453	9nineM	INFO	[2.6138646602630615, 2.050747871398926, 4.864589691162109, 22.69951820373535, 1.6681349277496338, 1.475082516670227, 31800, 0.00019890295108318404]
2023-02-01 17:14:45,203	9nineM	INFO	Train Epoch: 38 [51%]
2023-02-01 17:14:45,204	9nineM	INFO	[2.683239698410034, 1.9788589477539062, 4.138528347015381, 21.01311492919922, 1.7413430213928223, 1.6159683465957642, 32000, 0.00019890295108318404]
2023-02-01 17:15:09,399	9nineM	INFO	Saving model and optimizer state at iteration 38 to ./logs\9nineM\G_32000.pth
2023-02-01 17:15:10,172	9nineM	INFO	Saving model and optimizer state at iteration 38 to ./logs\9nineM\D_32000.pth
2023-02-01 17:18:25,226	9nineM	INFO	Train Epoch: 38 [75%]
2023-02-01 17:18:25,227	9nineM	INFO	[2.2311863899230957, 2.3713438510894775, 7.4914231300354, 26.72603416442871, 1.717178463935852, 1.9362727403640747, 32200, 0.00019890295108318404]
2023-02-01 17:21:38,370	9nineM	INFO	Train Epoch: 38 [98%]
2023-02-01 17:21:38,370	9nineM	INFO	[2.2777528762817383, 2.499821901321411, 5.831307411193848, 25.2869873046875, 1.7486741542816162, 1.70828378200531, 32400, 0.00019890295108318404]
2023-02-01 17:22:02,852	9nineM	INFO	Saving model and optimizer state at iteration 38 to ./logs\9nineM\G_32400.pth
2023-02-01 17:22:03,619	9nineM	INFO	Saving model and optimizer state at iteration 38 to ./logs\9nineM\D_32400.pth
2023-02-01 17:22:18,040	9nineM	INFO	====> Epoch: 38
2023-02-01 17:25:41,201	9nineM	INFO	Train Epoch: 39 [22%]
2023-02-01 17:25:41,201	9nineM	INFO	[2.454498529434204, 2.2587172985076904, 4.199381351470947, 20.6919002532959, 1.872959852218628, 1.6013412475585938, 32600, 0.00019887808821429862]
2023-02-01 17:28:52,987	9nineM	INFO	Train Epoch: 39 [45%]
2023-02-01 17:28:52,988	9nineM	INFO	[2.5843074321746826, 2.146446943283081, 4.491590976715088, 22.461898803710938, 1.7938328981399536, 1.3982316255569458, 32800, 0.00019887808821429862]
2023-02-01 17:29:17,756	9nineM	INFO	Saving model and optimizer state at iteration 39 to ./logs\9nineM\G_32800.pth
2023-02-01 17:29:18,657	9nineM	INFO	Saving model and optimizer state at iteration 39 to ./logs\9nineM\D_32800.pth
2023-02-01 17:32:34,733	9nineM	INFO	Train Epoch: 39 [69%]
2023-02-01 17:32:34,734	9nineM	INFO	[2.636389970779419, 1.8629508018493652, 3.6903533935546875, 20.31201171875, 1.9865062236785889, 1.7532310485839844, 33000, 0.00019887808821429862]
2023-02-01 17:35:51,704	9nineM	INFO	Train Epoch: 39 [92%]
2023-02-01 17:35:51,704	9nineM	INFO	[2.5792219638824463, 2.140162467956543, 4.547505855560303, 22.884021759033203, 1.7655047178268433, 1.5471705198287964, 33200, 0.00019887808821429862]
2023-02-01 17:36:16,461	9nineM	INFO	Saving model and optimizer state at iteration 39 to ./logs\9nineM\G_33200.pth
2023-02-01 17:36:17,207	9nineM	INFO	Saving model and optimizer state at iteration 39 to ./logs\9nineM\D_33200.pth
2023-02-01 17:37:24,421	9nineM	INFO	====> Epoch: 39
2023-02-01 17:39:57,213	9nineM	INFO	Train Epoch: 40 [16%]
2023-02-01 17:39:57,213	9nineM	INFO	[2.6288318634033203, 2.0972135066986084, 4.934540748596191, 21.877552032470703, 1.8201842308044434, 1.7888994216918945, 33400, 0.00019885322845327182]
2023-02-01 17:43:11,434	9nineM	INFO	Train Epoch: 40 [39%]
2023-02-01 17:43:11,434	9nineM	INFO	[2.658141613006592, 2.331437587738037, 4.835916519165039, 24.727418899536133, 1.7370905876159668, 1.5689709186553955, 33600, 0.00019885322845327182]
2023-02-01 17:43:35,679	9nineM	INFO	Saving model and optimizer state at iteration 40 to ./logs\9nineM\G_33600.pth
2023-02-01 17:43:36,435	9nineM	INFO	Saving model and optimizer state at iteration 40 to ./logs\9nineM\D_33600.pth
2023-02-01 17:46:51,670	9nineM	INFO	Train Epoch: 40 [62%]
2023-02-01 17:46:51,670	9nineM	INFO	[2.719942569732666, 1.9539000988006592, 4.045953750610352, 21.547697067260742, 1.72672700881958, 1.4675304889678955, 33800, 0.00019885322845327182]
2023-02-01 17:50:06,556	9nineM	INFO	Train Epoch: 40 [86%]
2023-02-01 17:50:06,557	9nineM	INFO	[2.674190044403076, 1.8533728122711182, 4.508209228515625, 24.51169776916504, 1.9194777011871338, 1.4392437934875488, 34000, 0.00019885322845327182]
2023-02-01 17:50:30,976	9nineM	INFO	Saving model and optimizer state at iteration 40 to ./logs\9nineM\G_34000.pth
2023-02-01 17:50:31,753	9nineM	INFO	Saving model and optimizer state at iteration 40 to ./logs\9nineM\D_34000.pth
2023-02-01 17:52:28,580	9nineM	INFO	====> Epoch: 40
2023-02-01 17:54:10,333	9nineM	INFO	Train Epoch: 41 [9%]
2023-02-01 17:54:10,334	9nineM	INFO	[2.4937329292297363, 2.29134464263916, 5.422130584716797, 26.12571144104004, 1.6666078567504883, 1.6672056913375854, 34200, 0.00019882837179971516]
2023-02-01 17:57:26,955	9nineM	INFO	Train Epoch: 41 [33%]
2023-02-01 17:57:26,955	9nineM	INFO	[2.5611343383789062, 2.043212652206421, 4.211092472076416, 21.851240158081055, 1.88693106174469, 1.5488057136535645, 34400, 0.00019882837179971516]
2023-02-01 17:57:51,881	9nineM	INFO	Saving model and optimizer state at iteration 41 to ./logs\9nineM\G_34400.pth
2023-02-01 17:57:52,685	9nineM	INFO	Saving model and optimizer state at iteration 41 to ./logs\9nineM\D_34400.pth
2023-02-01 18:01:07,449	9nineM	INFO	Train Epoch: 41 [56%]
2023-02-01 18:01:07,450	9nineM	INFO	[2.7365357875823975, 2.3190486431121826, 5.0319600105285645, 24.26772689819336, 1.9242149591445923, 1.8268693685531616, 34600, 0.00019882837179971516]
2023-02-01 18:04:22,110	9nineM	INFO	Train Epoch: 41 [80%]
2023-02-01 18:04:22,110	9nineM	INFO	[2.6296262741088867, 2.133437156677246, 3.676952600479126, 22.365764617919922, 1.8542792797088623, 1.6401487588882446, 34800, 0.00019882837179971516]
2023-02-01 18:04:46,390	9nineM	INFO	Saving model and optimizer state at iteration 41 to ./logs\9nineM\G_34800.pth
2023-02-01 18:04:47,172	9nineM	INFO	Saving model and optimizer state at iteration 41 to ./logs\9nineM\D_34800.pth
2023-02-01 18:07:36,276	9nineM	INFO	====> Epoch: 41
2023-02-01 18:08:26,099	9nineM	INFO	Train Epoch: 42 [3%]
2023-02-01 18:08:26,099	9nineM	INFO	[2.49212384223938, 2.24872088432312, 5.995089530944824, 25.848262786865234, 1.8010799884796143, 1.7120336294174194, 35000, 0.00019880351825324018]
2023-02-01 18:11:40,918	9nineM	INFO	Train Epoch: 42 [27%]
2023-02-01 18:11:40,919	9nineM	INFO	[2.537590503692627, 2.167124032974243, 5.7935333251953125, 25.775712966918945, 1.7429431676864624, 1.6175198554992676, 35200, 0.00019880351825324018]
2023-02-01 18:12:05,791	9nineM	INFO	Saving model and optimizer state at iteration 42 to ./logs\9nineM\G_35200.pth
2023-02-01 18:12:06,605	9nineM	INFO	Saving model and optimizer state at iteration 42 to ./logs\9nineM\D_35200.pth
2023-02-01 18:15:22,961	9nineM	INFO	Train Epoch: 42 [50%]
2023-02-01 18:15:22,962	9nineM	INFO	[2.3782966136932373, 2.4973931312561035, 4.8738603591918945, 22.93027687072754, 1.7586393356323242, 2.159142255783081, 35400, 0.00019880351825324018]
2023-02-01 18:18:23,070	9nineM	INFO	Train Epoch: 42 [74%]
2023-02-01 18:18:23,070	9nineM	INFO	[2.4745311737060547, 2.271057605743408, 5.654489040374756, 24.812362670898438, 1.8334579467773438, 1.743791937828064, 35600, 0.00019880351825324018]
2023-02-01 18:18:45,126	9nineM	INFO	Saving model and optimizer state at iteration 42 to ./logs\9nineM\G_35600.pth
2023-02-01 18:18:45,801	9nineM	INFO	Saving model and optimizer state at iteration 42 to ./logs\9nineM\D_35600.pth
2023-02-01 18:21:42,106	9nineM	INFO	Train Epoch: 42 [97%]
2023-02-01 18:21:42,106	9nineM	INFO	[2.4542994499206543, 2.2062954902648926, 4.680228233337402, 24.260759353637695, 1.9141931533813477, 1.696622610092163, 35800, 0.00019880351825324018]
2023-02-01 18:22:04,385	9nineM	INFO	====> Epoch: 42
2023-02-01 18:24:54,179	9nineM	INFO	Train Epoch: 43 [20%]
2023-02-01 18:24:54,179	9nineM	INFO	[2.4901843070983887, 2.1824638843536377, 4.524713039398193, 23.826526641845703, 1.8937201499938965, 1.5252604484558105, 36000, 0.00019877866781345852]
2023-02-01 18:25:15,459	9nineM	INFO	Saving model and optimizer state at iteration 43 to ./logs\9nineM\G_36000.pth
2023-02-01 18:25:16,122	9nineM	INFO	Saving model and optimizer state at iteration 43 to ./logs\9nineM\D_36000.pth
2023-02-01 18:28:11,499	9nineM	INFO	Train Epoch: 43 [44%]
2023-02-01 18:28:11,500	9nineM	INFO	[2.5362308025360107, 2.1723272800445557, 4.864365100860596, 25.04405403137207, 1.7278116941452026, 1.450219750404358, 36200, 0.00019877866781345852]
2023-02-01 18:31:04,060	9nineM	INFO	Train Epoch: 43 [67%]
2023-02-01 18:31:04,061	9nineM	INFO	[2.588315486907959, 2.1376588344573975, 4.551021575927734, 23.533817291259766, 1.7103817462921143, 1.5531283617019653, 36400, 0.00019877866781345852]
2023-02-01 18:31:25,618	9nineM	INFO	Saving model and optimizer state at iteration 43 to ./logs\9nineM\G_36400.pth
2023-02-01 18:31:26,369	9nineM	INFO	Saving model and optimizer state at iteration 43 to ./logs\9nineM\D_36400.pth
2023-02-01 18:34:22,241	9nineM	INFO	Train Epoch: 43 [91%]
2023-02-01 18:34:22,241	9nineM	INFO	[2.6047894954681396, 2.174082040786743, 4.949742317199707, 22.14706039428711, 1.8383907079696655, 1.641648530960083, 36600, 0.00019877866781345852]
2023-02-01 18:35:30,868	9nineM	INFO	====> Epoch: 43
2023-02-01 18:37:37,461	9nineM	INFO	Train Epoch: 44 [14%]
2023-02-01 18:37:37,462	9nineM	INFO	[2.572986125946045, 2.136593818664551, 4.04355525970459, 21.91054916381836, 1.7879250049591064, 1.7294100522994995, 36800, 0.00019875382047998183]
2023-02-01 18:37:58,884	9nineM	INFO	Saving model and optimizer state at iteration 44 to ./logs\9nineM\G_36800.pth
2023-02-01 18:37:59,543	9nineM	INFO	Saving model and optimizer state at iteration 44 to ./logs\9nineM\D_36800.pth
2023-02-01 18:40:53,316	9nineM	INFO	Train Epoch: 44 [38%]
2023-02-01 18:40:53,317	9nineM	INFO	[2.443532705307007, 2.1952812671661377, 4.759227275848389, 23.227327346801758, 1.9656598567962646, 1.3196086883544922, 37000, 0.00019875382047998183]
2023-02-01 18:43:46,101	9nineM	INFO	Train Epoch: 44 [61%]
2023-02-01 18:43:46,101	9nineM	INFO	[2.671976327896118, 2.075054407119751, 3.9347307682037354, 20.804964065551758, 1.7300915718078613, 1.7508121728897095, 37200, 0.00019875382047998183]
2023-02-01 18:44:07,502	9nineM	INFO	Saving model and optimizer state at iteration 44 to ./logs\9nineM\G_37200.pth
2023-02-01 18:44:08,267	9nineM	INFO	Saving model and optimizer state at iteration 44 to ./logs\9nineM\D_37200.pth
2023-02-01 18:47:02,250	9nineM	INFO	Train Epoch: 44 [85%]
2023-02-01 18:47:02,250	9nineM	INFO	[2.498908519744873, 2.361504554748535, 4.3354291915893555, 23.576732635498047, 1.9297654628753662, 1.4986674785614014, 37400, 0.00019875382047998183]
2023-02-01 18:48:56,808	9nineM	INFO	====> Epoch: 44
2023-02-01 18:50:15,677	9nineM	INFO	Train Epoch: 45 [8%]
2023-02-01 18:50:15,678	9nineM	INFO	[2.5694923400878906, 2.2049150466918945, 5.820436954498291, 25.611148834228516, 1.7650712728500366, 1.8910866975784302, 37600, 0.00019872897625242182]
2023-02-01 18:50:36,934	9nineM	INFO	Saving model and optimizer state at iteration 45 to ./logs\9nineM\G_37600.pth
2023-02-01 18:50:37,594	9nineM	INFO	Saving model and optimizer state at iteration 45 to ./logs\9nineM\D_37600.pth
2023-02-01 18:53:30,854	9nineM	INFO	Train Epoch: 45 [31%]
2023-02-01 18:53:30,855	9nineM	INFO	[2.5845606327056885, 2.144784450531006, 4.971654415130615, 23.590980529785156, 1.735672116279602, 1.156941294670105, 37800, 0.00019872897625242182]
2023-02-01 18:56:23,275	9nineM	INFO	Train Epoch: 45 [55%]
2023-02-01 18:56:23,276	9nineM	INFO	[2.5556178092956543, 2.0318026542663574, 4.260959148406982, 22.016450881958008, 1.7320380210876465, 1.5642647743225098, 38000, 0.00019872897625242182]
2023-02-01 18:56:44,886	9nineM	INFO	Saving model and optimizer state at iteration 45 to ./logs\9nineM\G_38000.pth
2023-02-01 18:56:45,540	9nineM	INFO	Saving model and optimizer state at iteration 45 to ./logs\9nineM\D_38000.pth
2023-02-01 18:59:42,477	9nineM	INFO	Train Epoch: 45 [78%]
2023-02-01 18:59:42,478	9nineM	INFO	[2.6331942081451416, 1.9731080532073975, 4.094152450561523, 20.55365562438965, 1.7299214601516724, 1.466010332107544, 38200, 0.00019872897625242182]
2023-02-01 19:02:22,842	9nineM	INFO	====> Epoch: 45
2023-02-01 19:02:56,955	9nineM	INFO	Train Epoch: 46 [2%]
2023-02-01 19:02:56,956	9nineM	INFO	[2.580018997192383, 1.909645438194275, 4.006155014038086, 20.815174102783203, 1.6976667642593384, 1.8680051565170288, 38400, 0.00019870413513039026]
2023-02-01 19:03:18,363	9nineM	INFO	Saving model and optimizer state at iteration 46 to ./logs\9nineM\G_38400.pth
2023-02-01 19:03:19,018	9nineM	INFO	Saving model and optimizer state at iteration 46 to ./logs\9nineM\D_38400.pth
2023-02-01 19:06:14,736	9nineM	INFO	Train Epoch: 46 [25%]
2023-02-01 19:06:14,737	9nineM	INFO	[2.4910054206848145, 2.1749205589294434, 5.119393348693848, 24.179704666137695, 1.8285729885101318, 1.8427361249923706, 38600, 0.00019870413513039026]
2023-02-02 14:19:19,757	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 16, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-02-02 14:19:27,564	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_38400.pth' (iteration 46)
2023-02-02 14:19:28,037	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_38400.pth' (iteration 46)
2023-02-02 14:20:19,238	9nineM	INFO	Train Epoch: 46 [2%]
2023-02-02 14:20:19,238	9nineM	INFO	[2.5456185340881348, 1.9604990482330322, 4.332867622375488, 21.53057289123535, 1.6935052871704102, 1.8282264471054077, 38400, 0.00019867929711349895]
2023-02-02 14:20:48,380	9nineM	INFO	Saving model and optimizer state at iteration 46 to ./logs\9nineM\G_38400.pth
2023-02-02 14:20:49,168	9nineM	INFO	Saving model and optimizer state at iteration 46 to ./logs\9nineM\D_38400.pth
2023-02-02 14:24:21,456	9nineM	INFO	Train Epoch: 46 [25%]
2023-02-02 14:24:21,457	9nineM	INFO	[2.6468706130981445, 2.0880415439605713, 4.406847953796387, 23.967500686645508, 1.8634170293807983, 1.6117606163024902, 38600, 0.00019867929711349895]
2023-02-02 14:27:22,687	9nineM	INFO	Train Epoch: 46 [49%]
2023-02-02 14:27:22,688	9nineM	INFO	[2.638824939727783, 2.0292012691497803, 3.1536033153533936, 19.555471420288086, 1.7480350732803345, 1.6857563257217407, 38800, 0.00019867929711349895]
2023-02-02 14:27:47,089	9nineM	INFO	Saving model and optimizer state at iteration 46 to ./logs\9nineM\G_38800.pth
2023-02-02 14:27:47,835	9nineM	INFO	Saving model and optimizer state at iteration 46 to ./logs\9nineM\D_38800.pth
2023-02-02 14:30:40,719	9nineM	INFO	Train Epoch: 46 [72%]
2023-02-02 14:30:40,719	9nineM	INFO	[2.6516051292419434, 2.1540942192077637, 3.694066047668457, 22.016237258911133, 1.843416690826416, 1.5230393409729004, 39000, 0.00019867929711349895]
2023-02-02 14:33:35,763	9nineM	INFO	Train Epoch: 46 [96%]
2023-02-02 14:33:35,764	9nineM	INFO	[2.5915274620056152, 2.1095948219299316, 4.336780071258545, 22.916271209716797, 1.8784198760986328, 1.7309505939483643, 39200, 0.00019867929711349895]
2023-02-02 14:34:00,397	9nineM	INFO	Saving model and optimizer state at iteration 46 to ./logs\9nineM\G_39200.pth
2023-02-02 14:34:01,110	9nineM	INFO	Saving model and optimizer state at iteration 46 to ./logs\9nineM\D_39200.pth
2023-02-02 14:34:34,594	9nineM	INFO	====> Epoch: 46
2023-02-02 14:37:22,242	9nineM	INFO	Train Epoch: 47 [19%]
2023-02-02 14:37:22,242	9nineM	INFO	[2.527169704437256, 2.1185073852539062, 4.635430812835693, 22.395965576171875, 1.7306945323944092, 1.831665277481079, 39400, 0.00019865446220135974]
2023-02-02 14:40:43,044	9nineM	INFO	Train Epoch: 47 [42%]
2023-02-02 14:40:43,044	9nineM	INFO	[2.4761626720428467, 2.311478614807129, 4.725570201873779, 22.31679916381836, 1.7371221780776978, 1.631006121635437, 39600, 0.00019865446220135974]
2023-02-02 14:41:13,167	9nineM	INFO	Saving model and optimizer state at iteration 47 to ./logs\9nineM\G_39600.pth
2023-02-02 14:41:14,127	9nineM	INFO	Saving model and optimizer state at iteration 47 to ./logs\9nineM\D_39600.pth
2023-02-02 14:44:29,374	9nineM	INFO	Train Epoch: 47 [66%]
2023-02-02 14:44:29,375	9nineM	INFO	[2.6012582778930664, 2.1873228549957275, 4.013382434844971, 21.424766540527344, 1.859406590461731, 1.5569621324539185, 39800, 0.00019865446220135974]
2023-02-02 14:47:40,416	9nineM	INFO	Train Epoch: 47 [89%]
2023-02-02 14:47:40,416	9nineM	INFO	[2.537325143814087, 2.2917749881744385, 4.962913513183594, 22.40337562561035, 1.802056908607483, 1.8988395929336548, 40000, 0.00019865446220135974]
2023-02-02 14:48:10,030	9nineM	INFO	Saving model and optimizer state at iteration 47 to ./logs\9nineM\G_40000.pth
2023-02-02 14:48:10,831	9nineM	INFO	Saving model and optimizer state at iteration 47 to ./logs\9nineM\D_40000.pth
2023-02-02 14:49:39,030	9nineM	INFO	====> Epoch: 47
2023-02-02 14:51:56,765	9nineM	INFO	Train Epoch: 48 [13%]
2023-02-02 14:51:56,775	9nineM	INFO	[2.460188150405884, 2.198483943939209, 5.61447811126709, 24.503917694091797, 1.6865628957748413, 1.7873073816299438, 40200, 0.00019862963039358455]
2023-02-02 14:55:12,982	9nineM	INFO	Train Epoch: 48 [36%]
2023-02-02 14:55:12,983	9nineM	INFO	[2.6686158180236816, 2.1743640899658203, 3.8630940914154053, 21.379125595092773, 1.75010085105896, 1.4420665502548218, 40400, 0.00019862963039358455]
2023-02-02 14:55:42,607	9nineM	INFO	Saving model and optimizer state at iteration 48 to ./logs\9nineM\G_40400.pth
2023-02-02 14:55:43,445	9nineM	INFO	Saving model and optimizer state at iteration 48 to ./logs\9nineM\D_40400.pth
2023-02-02 14:58:58,566	9nineM	INFO	Train Epoch: 48 [60%]
2023-02-02 14:58:58,567	9nineM	INFO	[2.4863743782043457, 2.1956119537353516, 4.977295398712158, 24.05885124206543, 1.7768304347991943, 1.7557754516601562, 40600, 0.00019862963039358455]
2023-02-02 15:02:19,720	9nineM	INFO	Train Epoch: 48 [83%]
2023-02-02 15:02:19,720	9nineM	INFO	[2.5187461376190186, 2.2432589530944824, 5.117112636566162, 24.116090774536133, 1.727491021156311, 1.378271460533142, 40800, 0.00019862963039358455]
2023-02-02 15:02:49,673	9nineM	INFO	Saving model and optimizer state at iteration 48 to ./logs\9nineM\G_40800.pth
2023-02-02 15:02:50,489	9nineM	INFO	Saving model and optimizer state at iteration 48 to ./logs\9nineM\D_40800.pth
2023-02-02 15:05:16,480	9nineM	INFO	====> Epoch: 48
2023-02-02 15:06:41,482	9nineM	INFO	Train Epoch: 49 [7%]
2023-02-02 15:06:41,483	9nineM	INFO	[2.1785848140716553, 2.7064008712768555, 8.207569122314453, 29.388254165649414, 1.765810489654541, 1.8694885969161987, 41000, 0.00019860480168978534]
2023-02-02 15:10:02,709	9nineM	INFO	Train Epoch: 49 [30%]
2023-02-02 15:10:02,710	9nineM	INFO	[2.3721823692321777, 2.299171209335327, 5.626714706420898, 26.651338577270508, 1.777482271194458, 1.8020421266555786, 41200, 0.00019860480168978534]
2023-02-02 15:10:32,740	9nineM	INFO	Saving model and optimizer state at iteration 49 to ./logs\9nineM\G_41200.pth
2023-02-02 15:10:33,604	9nineM	INFO	Saving model and optimizer state at iteration 49 to ./logs\9nineM\D_41200.pth
2023-02-02 15:13:33,381	9nineM	INFO	Train Epoch: 49 [53%]
2023-02-02 15:13:33,381	9nineM	INFO	[2.486915349960327, 2.3128888607025146, 4.383050441741943, 20.96324920654297, 1.733113408088684, 1.8083713054656982, 41400, 0.00019860480168978534]
2023-02-02 15:16:16,956	9nineM	INFO	Train Epoch: 49 [77%]
2023-02-02 15:16:16,957	9nineM	INFO	[2.6879286766052246, 2.271017074584961, 4.922100067138672, 24.012542724609375, 1.7113662958145142, 1.7479090690612793, 41600, 0.00019860480168978534]
2023-02-02 15:16:42,055	9nineM	INFO	Saving model and optimizer state at iteration 49 to ./logs\9nineM\G_41600.pth
2023-02-02 15:16:42,691	9nineM	INFO	Saving model and optimizer state at iteration 49 to ./logs\9nineM\D_41600.pth
2023-02-02 15:19:24,612	9nineM	INFO	====> Epoch: 49
2023-02-02 15:19:51,775	9nineM	INFO	Train Epoch: 50 [0%]
2023-02-02 15:19:51,777	9nineM	INFO	[2.463775157928467, 2.184429407119751, 4.749098300933838, 24.9190673828125, 1.793853521347046, 1.369109869003296, 41800, 0.0001985799760895741]
2023-02-02 15:22:35,769	9nineM	INFO	Train Epoch: 50 [24%]
2023-02-02 15:22:35,770	9nineM	INFO	[2.6144039630889893, 2.0969908237457275, 4.495172023773193, 22.01717758178711, 1.685788631439209, 1.6401894092559814, 42000, 0.0001985799760895741]
2023-02-02 15:23:00,837	9nineM	INFO	Saving model and optimizer state at iteration 50 to ./logs\9nineM\G_42000.pth
2023-02-02 15:23:01,489	9nineM	INFO	Saving model and optimizer state at iteration 50 to ./logs\9nineM\D_42000.pth
2023-02-02 15:25:43,864	9nineM	INFO	Train Epoch: 50 [47%]
2023-02-02 15:25:43,865	9nineM	INFO	[2.700957775115967, 2.116952657699585, 4.502313613891602, 23.029130935668945, 1.7644517421722412, 1.8445117473602295, 42200, 0.0001985799760895741]
2023-02-02 15:28:29,857	9nineM	INFO	Train Epoch: 50 [71%]
2023-02-02 15:28:29,858	9nineM	INFO	[2.456376552581787, 2.299602746963501, 6.077450275421143, 25.025371551513672, 1.7823113203048706, 1.8349579572677612, 42400, 0.0001985799760895741]
2023-02-02 15:28:57,158	9nineM	INFO	Saving model and optimizer state at iteration 50 to ./logs\9nineM\G_42400.pth
2023-02-02 15:28:57,897	9nineM	INFO	Saving model and optimizer state at iteration 50 to ./logs\9nineM\D_42400.pth
2023-02-02 15:31:44,944	9nineM	INFO	Train Epoch: 50 [94%]
2023-02-02 15:31:44,945	9nineM	INFO	[2.4654319286346436, 2.4112114906311035, 6.451958656311035, 26.50853729248047, 1.706529140472412, 1.7248282432556152, 42600, 0.0001985799760895741]
2023-02-02 15:32:27,113	9nineM	INFO	====> Epoch: 50
2023-02-02 15:34:55,644	9nineM	INFO	Train Epoch: 51 [18%]
2023-02-02 15:34:55,645	9nineM	INFO	[2.805753231048584, 2.028660297393799, 3.341474771499634, 20.90137481689453, 1.753252625465393, 1.6976696252822876, 42800, 0.0001985551535925629]
2023-02-02 15:35:22,106	9nineM	INFO	Saving model and optimizer state at iteration 51 to ./logs\9nineM\G_42800.pth
2023-02-02 15:35:22,773	9nineM	INFO	Saving model and optimizer state at iteration 51 to ./logs\9nineM\D_42800.pth
2023-02-02 15:38:08,535	9nineM	INFO	Train Epoch: 51 [41%]
2023-02-02 15:38:08,536	9nineM	INFO	[2.664698839187622, 1.9130167961120605, 4.023746967315674, 20.181114196777344, 1.710791826248169, 1.5688831806182861, 43000, 0.0001985551535925629]
2023-02-02 15:40:55,351	9nineM	INFO	Train Epoch: 51 [64%]
2023-02-02 15:40:55,353	9nineM	INFO	[2.577136754989624, 2.080090284347534, 4.574312210083008, 24.65957260131836, 1.8054012060165405, 1.6363075971603394, 43200, 0.0001985551535925629]
2023-02-02 15:41:22,338	9nineM	INFO	Saving model and optimizer state at iteration 51 to ./logs\9nineM\G_43200.pth
2023-02-02 15:41:23,084	9nineM	INFO	Saving model and optimizer state at iteration 51 to ./logs\9nineM\D_43200.pth
2023-02-02 15:44:10,433	9nineM	INFO	Train Epoch: 51 [88%]
2023-02-02 15:44:10,433	9nineM	INFO	[2.5996923446655273, 2.2468984127044678, 4.06203031539917, 20.609617233276367, 1.8627171516418457, 1.5727742910385132, 43400, 0.0001985551535925629]
2023-02-02 15:45:35,675	9nineM	INFO	====> Epoch: 51
2023-02-02 15:47:21,283	9nineM	INFO	Train Epoch: 52 [11%]
2023-02-02 15:47:21,293	9nineM	INFO	[2.6132054328918457, 2.051703929901123, 4.673154830932617, 24.30799674987793, 1.7467679977416992, 1.7793018817901611, 43600, 0.00019853033419836382]
2023-02-02 15:47:48,595	9nineM	INFO	Saving model and optimizer state at iteration 52 to ./logs\9nineM\G_43600.pth
2023-02-02 15:47:49,360	9nineM	INFO	Saving model and optimizer state at iteration 52 to ./logs\9nineM\D_43600.pth
2023-02-02 15:50:36,771	9nineM	INFO	Train Epoch: 52 [35%]
2023-02-02 15:50:36,771	9nineM	INFO	[2.6676881313323975, 1.9795176982879639, 3.616584062576294, 19.46588706970215, 1.839368224143982, 1.296882152557373, 43800, 0.00019853033419836382]
2023-02-02 15:53:20,658	9nineM	INFO	Train Epoch: 52 [58%]
2023-02-02 15:53:20,659	9nineM	INFO	[2.509068250656128, 2.095923900604248, 5.1803879737854, 22.69829750061035, 1.7495630979537964, 1.5732603073120117, 44000, 0.00019853033419836382]
2023-02-02 15:53:47,135	9nineM	INFO	Saving model and optimizer state at iteration 52 to ./logs\9nineM\G_44000.pth
2023-02-02 15:53:47,808	9nineM	INFO	Saving model and optimizer state at iteration 52 to ./logs\9nineM\D_44000.pth
2023-02-02 15:56:33,551	9nineM	INFO	Train Epoch: 52 [82%]
2023-02-02 15:56:33,551	9nineM	INFO	[2.5284931659698486, 2.1809816360473633, 4.142852783203125, 20.85040855407715, 1.8455588817596436, 1.4270213842391968, 44200, 0.00019853033419836382]
2023-02-02 15:58:42,860	9nineM	INFO	====> Epoch: 52
2023-02-02 15:59:44,790	9nineM	INFO	Train Epoch: 53 [5%]
2023-02-02 15:59:44,791	9nineM	INFO	[2.564565896987915, 2.054443597793579, 4.55912971496582, 23.13440704345703, 1.6704975366592407, 1.541869044303894, 44400, 0.000198505517906589]
2023-02-02 16:00:11,151	9nineM	INFO	Saving model and optimizer state at iteration 53 to ./logs\9nineM\G_44400.pth
2023-02-02 16:00:11,901	9nineM	INFO	Saving model and optimizer state at iteration 53 to ./logs\9nineM\D_44400.pth
2023-02-02 16:02:57,194	9nineM	INFO	Train Epoch: 53 [29%]
2023-02-02 16:02:57,204	9nineM	INFO	[2.3977904319763184, 2.3497087955474854, 6.685423851013184, 27.520832061767578, 1.7616844177246094, 1.935625433921814, 44600, 0.000198505517906589]
2023-02-02 16:05:41,516	9nineM	INFO	Train Epoch: 53 [52%]
2023-02-02 16:05:41,516	9nineM	INFO	[2.6922078132629395, 2.2271242141723633, 4.273469924926758, 20.765108108520508, 1.725816249847412, 1.4365458488464355, 44800, 0.000198505517906589]
2023-02-02 16:06:07,955	9nineM	INFO	Saving model and optimizer state at iteration 53 to ./logs\9nineM\G_44800.pth
2023-02-02 16:06:08,650	9nineM	INFO	Saving model and optimizer state at iteration 53 to ./logs\9nineM\D_44800.pth
2023-02-02 16:08:54,321	9nineM	INFO	Train Epoch: 53 [75%]
2023-02-02 16:08:54,321	9nineM	INFO	[2.4816393852233887, 2.250178098678589, 4.750300407409668, 23.00159454345703, 1.9175653457641602, 1.7297017574310303, 45000, 0.000198505517906589]
2023-02-02 16:11:41,810	9nineM	INFO	Train Epoch: 53 [99%]
2023-02-02 16:11:41,810	9nineM	INFO	[2.644486665725708, 2.002166986465454, 3.7238545417785645, 20.601802825927734, 1.9655804634094238, 1.1942297220230103, 45200, 0.000198505517906589]
2023-02-02 16:12:10,558	9nineM	INFO	Saving model and optimizer state at iteration 53 to ./logs\9nineM\G_45200.pth
2023-02-02 16:12:11,255	9nineM	INFO	Saving model and optimizer state at iteration 53 to ./logs\9nineM\D_45200.pth
2023-02-02 16:12:19,688	9nineM	INFO	====> Epoch: 53
2023-02-02 16:15:24,771	9nineM	INFO	Train Epoch: 54 [22%]
2023-02-02 16:15:24,782	9nineM	INFO	[1.9965319633483887, 2.8392884731292725, 8.502004623413086, 29.19854164123535, 2.0257582664489746, 2.058742046356201, 45400, 0.00019848070471685067]
2023-02-02 16:18:13,134	9nineM	INFO	Train Epoch: 54 [46%]
2023-02-02 16:18:13,135	9nineM	INFO	[2.5347115993499756, 2.2828731536865234, 4.994711399078369, 22.087730407714844, 1.8718558549880981, 1.5664105415344238, 45600, 0.00019848070471685067]
2023-02-02 16:18:40,828	9nineM	INFO	Saving model and optimizer state at iteration 54 to ./logs\9nineM\G_45600.pth
2023-02-02 16:18:41,505	9nineM	INFO	Saving model and optimizer state at iteration 54 to ./logs\9nineM\D_45600.pth
2023-02-02 16:21:28,503	9nineM	INFO	Train Epoch: 54 [69%]
2023-02-02 16:21:28,503	9nineM	INFO	[2.6793789863586426, 2.0097861289978027, 3.7003061771392822, 18.602724075317383, 1.7506279945373535, 1.499576449394226, 45800, 0.00019848070471685067]
2023-02-02 16:24:16,524	9nineM	INFO	Train Epoch: 54 [93%]
2023-02-02 16:24:16,526	9nineM	INFO	[2.4813101291656494, 2.2298691272735596, 4.734545707702637, 22.057920455932617, 1.744640827178955, 1.5977402925491333, 46000, 0.00019848070471685067]
2023-02-02 16:24:44,547	9nineM	INFO	Saving model and optimizer state at iteration 54 to ./logs\9nineM\G_46000.pth
2023-02-02 16:24:45,243	9nineM	INFO	Saving model and optimizer state at iteration 54 to ./logs\9nineM\D_46000.pth
2023-02-02 16:25:36,975	9nineM	INFO	====> Epoch: 54
2023-02-02 16:27:57,670	9nineM	INFO	Train Epoch: 55 [16%]
2023-02-02 16:27:57,670	9nineM	INFO	[2.5409350395202637, 2.2759337425231934, 5.337271213531494, 23.66328239440918, 1.7852931022644043, 1.6941461563110352, 46200, 0.00019845589462876104]
2023-02-02 16:30:45,982	9nineM	INFO	Train Epoch: 55 [40%]
2023-02-02 16:30:45,982	9nineM	INFO	[2.5152130126953125, 2.3854804039001465, 4.660080909729004, 22.114763259887695, 1.690419316291809, 1.7361944913864136, 46400, 0.00019845589462876104]
2023-02-02 16:31:13,172	9nineM	INFO	Saving model and optimizer state at iteration 55 to ./logs\9nineM\G_46400.pth
2023-02-02 16:31:14,013	9nineM	INFO	Saving model and optimizer state at iteration 55 to ./logs\9nineM\D_46400.pth
2023-02-02 16:34:01,754	9nineM	INFO	Train Epoch: 55 [63%]
2023-02-02 16:34:01,755	9nineM	INFO	[2.653305768966675, 2.309873104095459, 3.7192981243133545, 17.845861434936523, 1.8192013502120972, 1.4677693843841553, 46600, 0.00019845589462876104]
2023-02-02 16:36:46,198	9nineM	INFO	Train Epoch: 55 [87%]
2023-02-02 16:36:46,198	9nineM	INFO	[2.3867712020874023, 2.7563436031341553, 5.9804511070251465, 20.136432647705078, 1.6614503860473633, 1.5255028009414673, 46800, 0.00019845589462876104]
2023-02-02 16:37:12,981	9nineM	INFO	Saving model and optimizer state at iteration 55 to ./logs\9nineM\G_46800.pth
2023-02-02 16:37:13,670	9nineM	INFO	Saving model and optimizer state at iteration 55 to ./logs\9nineM\D_46800.pth
2023-02-02 16:38:48,470	9nineM	INFO	====> Epoch: 55
2023-02-02 16:40:25,286	9nineM	INFO	Train Epoch: 56 [10%]
2023-02-02 16:40:25,287	9nineM	INFO	[2.5249319076538086, 2.1532249450683594, 3.879249095916748, 21.559656143188477, 1.8102107048034668, 1.5574270486831665, 47000, 0.00019843108764193245]
2023-02-02 16:43:10,479	9nineM	INFO	Train Epoch: 56 [33%]
2023-02-02 16:43:10,479	9nineM	INFO	[2.5880095958709717, 1.922254204750061, 4.0028252601623535, 20.93564796447754, 1.9858158826828003, 1.760013222694397, 47200, 0.00019843108764193245]
2023-02-02 16:43:37,053	9nineM	INFO	Saving model and optimizer state at iteration 56 to ./logs\9nineM\G_47200.pth
2023-02-02 16:43:37,741	9nineM	INFO	Saving model and optimizer state at iteration 56 to ./logs\9nineM\D_47200.pth
2023-02-02 16:46:22,741	9nineM	INFO	Train Epoch: 56 [57%]
2023-02-02 16:46:22,741	9nineM	INFO	[2.9637508392333984, 2.096416711807251, 4.352644920349121, 20.849790573120117, 1.6902706623077393, 1.75706946849823, 47400, 0.00019843108764193245]
2023-02-02 16:49:07,118	9nineM	INFO	Train Epoch: 56 [80%]
2023-02-02 16:49:07,118	9nineM	INFO	[2.1476147174835205, 2.6701338291168213, 6.902968406677246, 24.535120010375977, 1.9021955728530884, 1.9492253065109253, 47600, 0.00019843108764193245]
2023-02-02 16:49:33,816	9nineM	INFO	Saving model and optimizer state at iteration 56 to ./logs\9nineM\G_47600.pth
2023-02-02 16:49:34,491	9nineM	INFO	Saving model and optimizer state at iteration 56 to ./logs\9nineM\D_47600.pth
2023-02-02 16:51:55,017	9nineM	INFO	====> Epoch: 56
2023-02-02 16:52:46,283	9nineM	INFO	Train Epoch: 57 [4%]
2023-02-02 16:52:46,284	9nineM	INFO	[2.5692505836486816, 1.8915231227874756, 3.525790214538574, 16.598825454711914, 1.866289496421814, 1.5789271593093872, 47800, 0.0001984062837559772]
2023-02-03 00:59:09,197	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 16, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-02-03 00:59:19,434	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_47600.pth' (iteration 56)
2023-02-03 00:59:20,042	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_47600.pth' (iteration 56)
2023-02-03 01:01:32,258	9nineM	INFO	Train Epoch: 56 [10%]
2023-02-03 01:01:32,259	9nineM	INFO	[2.672912120819092, 2.103388547897339, 3.3316500186920166, 18.46944236755371, 1.8204302787780762, 1.5436434745788574, 47000, 0.0001984062837559772]
2023-02-03 01:04:51,809	9nineM	INFO	Train Epoch: 56 [33%]
2023-02-03 01:04:51,810	9nineM	INFO	[2.5974044799804688, 2.219480514526367, 4.528825759887695, 22.80307388305664, 1.9853324890136719, 1.827863335609436, 47200, 0.0001984062837559772]
2023-02-03 01:05:26,880	9nineM	INFO	Saving model and optimizer state at iteration 56 to ./logs\9nineM\G_47200.pth
2023-02-03 01:05:27,870	9nineM	INFO	Saving model and optimizer state at iteration 56 to ./logs\9nineM\D_47200.pth
2023-02-03 01:08:37,022	9nineM	INFO	Train Epoch: 56 [57%]
2023-02-03 01:08:37,022	9nineM	INFO	[2.5025136470794678, 2.3158249855041504, 5.260532855987549, 23.464736938476562, 1.7083802223205566, 1.42533540725708, 47400, 0.0001984062837559772]
2023-02-03 01:11:50,836	9nineM	INFO	Train Epoch: 56 [80%]
2023-02-03 01:11:50,837	9nineM	INFO	[2.3016281127929688, 2.4068126678466797, 6.510300636291504, 24.71748924255371, 1.8946081399917603, 1.96099853515625, 47600, 0.0001984062837559772]
2023-02-03 01:12:27,402	9nineM	INFO	Saving model and optimizer state at iteration 56 to ./logs\9nineM\G_47600.pth
2023-02-03 01:12:28,293	9nineM	INFO	Saving model and optimizer state at iteration 56 to ./logs\9nineM\D_47600.pth
2023-02-03 01:15:08,052	9nineM	INFO	====> Epoch: 56
2023-02-03 01:16:11,617	9nineM	INFO	Train Epoch: 57 [4%]
2023-02-03 01:16:11,618	9nineM	INFO	[2.4532408714294434, 2.4832754135131836, 4.645760536193848, 20.386123657226562, 1.8714056015014648, 1.524889588356018, 47800, 0.00019838148297050769]
2023-02-03 01:19:25,368	9nineM	INFO	Train Epoch: 57 [27%]
2023-02-03 01:19:25,369	9nineM	INFO	[2.6601028442382812, 2.1023452281951904, 2.7675955295562744, 17.59121322631836, 1.9114729166030884, 1.8272740840911865, 48000, 0.00019838148297050769]
2023-02-03 01:20:02,274	9nineM	INFO	Saving model and optimizer state at iteration 57 to ./logs\9nineM\G_48000.pth
2023-02-03 01:20:03,225	9nineM	INFO	Saving model and optimizer state at iteration 57 to ./logs\9nineM\D_48000.pth
2023-02-03 01:23:17,264	9nineM	INFO	Train Epoch: 57 [51%]
2023-02-03 01:23:17,265	9nineM	INFO	[2.4948978424072266, 2.387098789215088, 4.183628082275391, 21.69224739074707, 2.01405668258667, 1.340806484222412, 48200, 0.00019838148297050769]
2023-02-03 01:26:39,774	9nineM	INFO	Train Epoch: 57 [74%]
2023-02-03 01:26:39,775	9nineM	INFO	[2.624905824661255, 1.9847757816314697, 4.182816982269287, 19.71246910095215, 1.7404658794403076, 1.610998272895813, 48400, 0.00019838148297050769]
2023-02-03 01:27:16,349	9nineM	INFO	Saving model and optimizer state at iteration 57 to ./logs\9nineM\G_48400.pth
2023-02-03 01:27:17,311	9nineM	INFO	Saving model and optimizer state at iteration 57 to ./logs\9nineM\D_48400.pth
2023-02-03 01:30:29,876	9nineM	INFO	Train Epoch: 57 [98%]
2023-02-03 01:30:29,876	9nineM	INFO	[2.5206167697906494, 2.4818015098571777, 5.280219554901123, 23.578548431396484, 1.8270213603973389, 1.692426323890686, 48600, 0.00019838148297050769]
2023-02-03 01:30:51,035	9nineM	INFO	====> Epoch: 57
2023-02-03 01:34:17,897	9nineM	INFO	Train Epoch: 58 [21%]
2023-02-03 01:34:17,898	9nineM	INFO	[2.44883394241333, 2.3168745040893555, 5.455172061920166, 23.473800659179688, 1.6408716440200806, 1.8296802043914795, 48800, 0.00019835668528513637]
2023-02-03 01:34:53,578	9nineM	INFO	Saving model and optimizer state at iteration 58 to ./logs\9nineM\G_48800.pth
2023-02-03 01:34:54,574	9nineM	INFO	Saving model and optimizer state at iteration 58 to ./logs\9nineM\D_48800.pth
2023-02-03 01:38:07,164	9nineM	INFO	Train Epoch: 58 [44%]
2023-02-03 01:38:07,164	9nineM	INFO	[2.432213544845581, 2.2860658168792725, 4.691568374633789, 20.705219268798828, 1.737753987312317, 1.2836068868637085, 49000, 0.00019835668528513637]
2023-02-03 01:41:24,273	9nineM	INFO	Train Epoch: 58 [68%]
2023-02-03 01:41:24,275	9nineM	INFO	[2.493086814880371, 2.4042367935180664, 5.666842460632324, 23.14779281616211, 1.7413671016693115, 1.5422581434249878, 49200, 0.00019835668528513637]
2023-02-03 01:42:00,153	9nineM	INFO	Saving model and optimizer state at iteration 58 to ./logs\9nineM\G_49200.pth
2023-02-03 01:42:01,223	9nineM	INFO	Saving model and optimizer state at iteration 58 to ./logs\9nineM\D_49200.pth
2023-02-03 01:45:15,474	9nineM	INFO	Train Epoch: 58 [91%]
2023-02-03 01:45:15,475	9nineM	INFO	[2.4014031887054443, 2.3078725337982178, 5.170658111572266, 22.265106201171875, 1.8241097927093506, 1.5589284896850586, 49400, 0.00019835668528513637]
2023-02-03 01:46:30,030	9nineM	INFO	====> Epoch: 58
2023-02-03 01:49:06,827	9nineM	INFO	Train Epoch: 59 [15%]
2023-02-03 01:49:06,828	9nineM	INFO	[2.2942590713500977, 2.28958797454834, 6.129242420196533, 24.966899871826172, 1.9432786703109741, 1.4881407022476196, 49600, 0.00019833189069947573]
2023-02-03 01:49:42,533	9nineM	INFO	Saving model and optimizer state at iteration 59 to ./logs\9nineM\G_49600.pth
2023-02-03 01:49:43,509	9nineM	INFO	Saving model and optimizer state at iteration 59 to ./logs\9nineM\D_49600.pth
2023-02-03 01:52:55,392	9nineM	INFO	Train Epoch: 59 [38%]
2023-02-03 01:52:55,393	9nineM	INFO	[2.5896387100219727, 2.2113804817199707, 4.515007495880127, 21.540569305419922, 1.9031330347061157, 1.8028725385665894, 49800, 0.00019833189069947573]
2023-02-03 01:56:10,170	9nineM	INFO	Train Epoch: 59 [62%]
2023-02-03 01:56:10,171	9nineM	INFO	[2.4506797790527344, 2.2908849716186523, 5.1710357666015625, 23.37103843688965, 1.758582353591919, 1.8202123641967773, 50000, 0.00019833189069947573]
2023-02-03 01:56:46,124	9nineM	INFO	Saving model and optimizer state at iteration 59 to ./logs\9nineM\G_50000.pth
2023-02-03 01:56:47,149	9nineM	INFO	Saving model and optimizer state at iteration 59 to ./logs\9nineM\D_50000.pth
2023-02-03 01:59:59,819	9nineM	INFO	Train Epoch: 59 [85%]
2023-02-03 01:59:59,820	9nineM	INFO	[2.5517823696136475, 2.0422005653381348, 4.879603385925293, 22.73113441467285, 1.7835543155670166, 1.543338656425476, 50200, 0.00019833189069947573]
2023-02-03 02:02:04,251	9nineM	INFO	====> Epoch: 59
2023-02-03 02:03:50,099	9nineM	INFO	Train Epoch: 60 [9%]
2023-02-03 02:03:50,100	9nineM	INFO	[2.3278772830963135, 2.625412940979004, 5.421267032623291, 24.34024429321289, 1.9122364521026611, 1.6058098077774048, 50400, 0.0001983070992131383]
2023-02-03 02:04:27,039	9nineM	INFO	Saving model and optimizer state at iteration 60 to ./logs\9nineM\G_50400.pth
2023-02-03 02:04:28,004	9nineM	INFO	Saving model and optimizer state at iteration 60 to ./logs\9nineM\D_50400.pth
2023-02-03 02:07:39,388	9nineM	INFO	Train Epoch: 60 [32%]
2023-02-03 02:07:39,388	9nineM	INFO	[2.5196664333343506, 2.361819267272949, 4.481662750244141, 19.837209701538086, 1.731720209121704, 1.2567310333251953, 50600, 0.0001983070992131383]
2023-02-03 02:10:55,322	9nineM	INFO	Train Epoch: 60 [55%]
2023-02-03 02:10:55,322	9nineM	INFO	[2.6364035606384277, 2.042539119720459, 4.1252899169921875, 19.209779739379883, 1.7461036443710327, 1.5589686632156372, 50800, 0.0001983070992131383]
2023-02-03 02:11:31,920	9nineM	INFO	Saving model and optimizer state at iteration 60 to ./logs\9nineM\G_50800.pth
2023-02-03 02:11:32,960	9nineM	INFO	Saving model and optimizer state at iteration 60 to ./logs\9nineM\D_50800.pth
2023-02-03 02:14:46,326	9nineM	INFO	Train Epoch: 60 [79%]
2023-02-03 02:14:46,336	9nineM	INFO	[2.5692458152770996, 2.1167807579040527, 4.07194709777832, 21.36824607849121, 1.70513916015625, 1.6159950494766235, 51000, 0.0001983070992131383]
2023-02-03 02:17:44,816	9nineM	INFO	====> Epoch: 60
2023-02-03 02:18:39,025	9nineM	INFO	Train Epoch: 61 [2%]
2023-02-03 02:18:39,026	9nineM	INFO	[2.3709635734558105, 2.7240004539489746, 5.342936992645264, 23.202199935913086, 1.8721204996109009, 1.9001024961471558, 51200, 0.00019828231082573666]
2023-02-03 02:19:16,138	9nineM	INFO	Saving model and optimizer state at iteration 61 to ./logs\9nineM\G_51200.pth
2023-02-03 02:19:17,256	9nineM	INFO	Saving model and optimizer state at iteration 61 to ./logs\9nineM\D_51200.pth
2023-02-03 02:22:28,102	9nineM	INFO	Train Epoch: 61 [26%]
2023-02-03 02:22:28,103	9nineM	INFO	[2.1359126567840576, 2.51208758354187, 6.858147621154785, 24.276992797851562, 1.6832128763198853, 1.4411396980285645, 51400, 0.00019828231082573666]
2023-02-03 02:25:43,105	9nineM	INFO	Train Epoch: 61 [49%]
2023-02-03 02:25:43,106	9nineM	INFO	[2.5365309715270996, 1.978432536125183, 4.31061315536499, 19.38656997680664, 1.7489607334136963, 1.7873587608337402, 51600, 0.00019828231082573666]
2023-02-03 02:26:18,993	9nineM	INFO	Saving model and optimizer state at iteration 61 to ./logs\9nineM\G_51600.pth
2023-02-03 02:26:19,943	9nineM	INFO	Saving model and optimizer state at iteration 61 to ./logs\9nineM\D_51600.pth
2023-02-03 02:29:31,466	9nineM	INFO	Train Epoch: 61 [73%]
2023-02-03 02:29:31,467	9nineM	INFO	[2.633056163787842, 2.2176268100738525, 4.984248638153076, 22.168758392333984, 1.791223168373108, 1.8201674222946167, 51800, 0.00019828231082573666]
2023-02-03 02:32:45,473	9nineM	INFO	Train Epoch: 61 [96%]
2023-02-03 02:32:45,474	9nineM	INFO	[2.523571491241455, 2.285471200942993, 4.605067729949951, 22.316648483276367, 1.8400073051452637, 1.5887786149978638, 52000, 0.00019828231082573666]
2023-02-03 02:33:22,300	9nineM	INFO	Saving model and optimizer state at iteration 61 to ./logs\9nineM\G_52000.pth
2023-02-03 02:33:23,304	9nineM	INFO	Saving model and optimizer state at iteration 61 to ./logs\9nineM\D_52000.pth
2023-02-03 02:33:55,802	9nineM	INFO	====> Epoch: 61
2023-02-03 02:37:06,959	9nineM	INFO	Train Epoch: 62 [20%]
2023-02-03 02:37:06,959	9nineM	INFO	[2.5635805130004883, 2.379089593887329, 6.037509918212891, 22.901443481445312, 1.7330048084259033, 1.8591387271881104, 52200, 0.00019825752553688343]
2023-02-03 02:40:20,118	9nineM	INFO	Train Epoch: 62 [43%]
2023-02-03 02:40:20,118	9nineM	INFO	[2.1720409393310547, 2.5727460384368896, 5.852151870727539, 22.293659210205078, 1.8660407066345215, 1.5443339347839355, 52400, 0.00019825752553688343]
2023-02-03 02:40:55,967	9nineM	INFO	Saving model and optimizer state at iteration 62 to ./logs\9nineM\G_52400.pth
2023-02-03 02:40:56,945	9nineM	INFO	Saving model and optimizer state at iteration 62 to ./logs\9nineM\D_52400.pth
2023-02-03 02:44:09,537	9nineM	INFO	Train Epoch: 62 [66%]
2023-02-03 02:44:09,539	9nineM	INFO	[2.4269766807556152, 2.2607569694519043, 5.32930326461792, 22.98223114013672, 1.7921234369277954, 1.46768057346344, 52600, 0.00019825752553688343]
2023-02-03 02:47:25,697	9nineM	INFO	Train Epoch: 62 [90%]
2023-02-03 02:47:25,698	9nineM	INFO	[2.4384925365448, 2.3430049419403076, 4.934988498687744, 22.603134155273438, 1.7610344886779785, 1.4807937145233154, 52800, 0.00019825752553688343]
2023-02-03 02:48:02,559	9nineM	INFO	Saving model and optimizer state at iteration 62 to ./logs\9nineM\G_52800.pth
2023-02-03 02:48:03,513	9nineM	INFO	Saving model and optimizer state at iteration 62 to ./logs\9nineM\D_52800.pth
2023-02-03 02:49:26,324	9nineM	INFO	====> Epoch: 62
2023-02-03 02:51:48,737	9nineM	INFO	Train Epoch: 63 [13%]
2023-02-03 02:51:48,738	9nineM	INFO	[2.3474180698394775, 2.426311731338501, 5.142326831817627, 23.166309356689453, 1.6758217811584473, 1.5445367097854614, 53000, 0.0001982327433461913]
2023-02-03 02:55:02,542	9nineM	INFO	Train Epoch: 63 [37%]
2023-02-03 02:55:02,543	9nineM	INFO	[2.5135583877563477, 2.421907424926758, 4.6314616203308105, 20.88935089111328, 1.7283380031585693, 1.6252825260162354, 53200, 0.0001982327433461913]
2023-02-03 02:55:39,117	9nineM	INFO	Saving model and optimizer state at iteration 63 to ./logs\9nineM\G_53200.pth
2023-02-03 02:55:40,072	9nineM	INFO	Saving model and optimizer state at iteration 63 to ./logs\9nineM\D_53200.pth
2023-02-03 02:58:51,720	9nineM	INFO	Train Epoch: 63 [60%]
2023-02-03 02:58:51,722	9nineM	INFO	[2.370335102081299, 2.406524658203125, 5.648592948913574, 22.969852447509766, 1.8121955394744873, 1.631996989250183, 53400, 0.0001982327433461913]
2023-02-03 03:02:08,206	9nineM	INFO	Train Epoch: 63 [84%]
2023-02-03 03:02:08,206	9nineM	INFO	[2.431915521621704, 2.2778375148773193, 5.556666851043701, 24.222270965576172, 1.6881029605865479, 1.5792791843414307, 53600, 0.0001982327433461913]
2023-02-03 03:02:45,504	9nineM	INFO	Saving model and optimizer state at iteration 63 to ./logs\9nineM\G_53600.pth
2023-02-03 03:02:46,490	9nineM	INFO	Saving model and optimizer state at iteration 63 to ./logs\9nineM\D_53600.pth
2023-02-03 03:05:00,571	9nineM	INFO	====> Epoch: 63
2023-02-03 03:06:33,216	9nineM	INFO	Train Epoch: 64 [7%]
2023-02-03 03:06:33,217	9nineM	INFO	[2.5584421157836914, 2.261146068572998, 5.403614044189453, 21.70271110534668, 3.9270589351654053, 1.7977157831192017, 53800, 0.00019820796425327303]
2023-02-03 03:09:45,697	9nineM	INFO	Train Epoch: 64 [31%]
2023-02-03 03:09:45,697	9nineM	INFO	[2.506709575653076, 2.453068733215332, 6.043850421905518, 24.06352996826172, 1.7487577199935913, 1.6727933883666992, 54000, 0.00019820796425327303]
2023-02-03 03:10:22,174	9nineM	INFO	Saving model and optimizer state at iteration 64 to ./logs\9nineM\G_54000.pth
2023-02-03 03:10:23,220	9nineM	INFO	Saving model and optimizer state at iteration 64 to ./logs\9nineM\D_54000.pth
2023-02-03 03:13:34,178	9nineM	INFO	Train Epoch: 64 [54%]
2023-02-03 03:13:34,178	9nineM	INFO	[2.5988712310791016, 2.013223171234131, 3.8378477096557617, 19.70365333557129, 1.9744824171066284, 1.527276873588562, 54200, 0.00019820796425327303]
2023-02-03 03:16:50,298	9nineM	INFO	Train Epoch: 64 [77%]
2023-02-03 03:16:50,298	9nineM	INFO	[2.5508663654327393, 2.197441816329956, 5.278398513793945, 21.889907836914062, 1.6981452703475952, 1.7705457210540771, 54400, 0.00019820796425327303]
2023-02-03 03:17:30,770	9nineM	INFO	Saving model and optimizer state at iteration 64 to ./logs\9nineM\G_54400.pth
2023-02-03 03:17:31,579	9nineM	INFO	Saving model and optimizer state at iteration 64 to ./logs\9nineM\D_54400.pth
2023-02-03 03:21:41,911	9nineM	INFO	====> Epoch: 64
2023-02-03 03:22:22,015	9nineM	INFO	Train Epoch: 65 [1%]
2023-02-03 03:22:22,016	9nineM	INFO	[2.11804461479187, 2.680095911026001, 5.810821056365967, 20.727031707763672, 1.8702524900436401, 1.68907630443573, 54600, 0.00019818318825774137]
2023-02-03 03:27:20,692	9nineM	INFO	Train Epoch: 65 [24%]
2023-02-03 03:27:20,693	9nineM	INFO	[2.377493143081665, 2.5573155879974365, 5.29105806350708, 23.006086349487305, 3.8652234077453613, 1.7418180704116821, 54800, 0.00019818318825774137]
2023-02-03 03:27:56,525	9nineM	INFO	Saving model and optimizer state at iteration 65 to ./logs\9nineM\G_54800.pth
2023-02-03 03:27:57,351	9nineM	INFO	Saving model and optimizer state at iteration 65 to ./logs\9nineM\D_54800.pth
2023-02-03 03:32:47,303	9nineM	INFO	Train Epoch: 65 [48%]
2023-02-03 03:32:47,304	9nineM	INFO	[2.51495623588562, 2.165210247039795, 4.879878044128418, 22.3475399017334, 1.8575648069381714, 2.0317447185516357, 55000, 0.00019818318825774137]
2023-02-03 03:36:22,977	9nineM	INFO	Train Epoch: 65 [71%]
2023-02-03 03:36:22,978	9nineM	INFO	[2.4218292236328125, 2.371192693710327, 5.4800286293029785, 21.835460662841797, 1.8553683757781982, 1.3339478969573975, 55200, 0.00019818318825774137]
2023-02-03 03:36:57,075	9nineM	INFO	Saving model and optimizer state at iteration 65 to ./logs\9nineM\G_55200.pth
2023-02-03 03:36:58,130	9nineM	INFO	Saving model and optimizer state at iteration 65 to ./logs\9nineM\D_55200.pth
2023-02-03 03:41:02,853	9nineM	INFO	Train Epoch: 65 [95%]
2023-02-03 03:41:02,854	9nineM	INFO	[2.4818830490112305, 2.2685413360595703, 5.177450180053711, 21.700761795043945, 1.832390308380127, 1.9992364645004272, 55400, 0.00019818318825774137]
2023-02-03 03:41:47,561	9nineM	INFO	====> Epoch: 65
2023-02-03 03:44:49,439	9nineM	INFO	Train Epoch: 66 [18%]
2023-02-03 03:44:49,439	9nineM	INFO	[2.459707260131836, 2.284942150115967, 4.610323905944824, 20.99444007873535, 1.7494850158691406, 1.8644267320632935, 55600, 0.00019815841535920914]
2023-02-03 03:45:24,611	9nineM	INFO	Saving model and optimizer state at iteration 66 to ./logs\9nineM\G_55600.pth
2023-02-03 03:45:25,573	9nineM	INFO	Saving model and optimizer state at iteration 66 to ./logs\9nineM\D_55600.pth
2023-02-03 03:48:38,191	9nineM	INFO	Train Epoch: 66 [42%]
2023-02-03 03:48:38,192	9nineM	INFO	[2.7035176753997803, 2.3940021991729736, 4.859534740447998, 21.582319259643555, 1.8283841609954834, 1.7707816362380981, 55800, 0.00019815841535920914]
2023-02-03 03:51:49,359	9nineM	INFO	Train Epoch: 66 [65%]
2023-02-03 03:51:49,359	9nineM	INFO	[2.607867479324341, 2.1679699420928955, 4.986110210418701, 22.950368881225586, 1.8008973598480225, 1.8243170976638794, 56000, 0.00019815841535920914]
2023-02-03 03:52:25,199	9nineM	INFO	Saving model and optimizer state at iteration 66 to ./logs\9nineM\G_56000.pth
2023-02-03 03:52:26,192	9nineM	INFO	Saving model and optimizer state at iteration 66 to ./logs\9nineM\D_56000.pth
2023-02-03 03:55:37,026	9nineM	INFO	Train Epoch: 66 [89%]
2023-02-03 03:55:37,036	9nineM	INFO	[2.4055895805358887, 2.4035286903381348, 5.224339962005615, 23.526596069335938, 1.7499163150787354, 1.6318963766098022, 56200, 0.00019815841535920914]
2023-02-03 03:57:10,552	9nineM	INFO	====> Epoch: 66
2023-02-03 03:59:20,747	9nineM	INFO	Train Epoch: 67 [12%]
2023-02-03 03:59:20,748	9nineM	INFO	[2.2657783031463623, 2.4371931552886963, 7.117774486541748, 25.306419372558594, 1.7295277118682861, 1.7502403259277344, 56400, 0.00019813364555728923]
2023-02-03 03:59:56,552	9nineM	INFO	Saving model and optimizer state at iteration 67 to ./logs\9nineM\G_56400.pth
2023-02-03 03:59:57,508	9nineM	INFO	Saving model and optimizer state at iteration 67 to ./logs\9nineM\D_56400.pth
2023-02-03 04:03:09,072	9nineM	INFO	Train Epoch: 67 [35%]
2023-02-03 04:03:09,073	9nineM	INFO	[2.767900228500366, 2.1692662239074707, 4.149256229400635, 21.174406051635742, 1.8470003604888916, 1.7838845252990723, 56600, 0.00019813364555728923]
2023-02-03 04:06:18,640	9nineM	INFO	Train Epoch: 67 [59%]
2023-02-03 04:06:18,641	9nineM	INFO	[2.5033888816833496, 2.0516786575317383, 4.635260105133057, 20.66300392150879, 1.9004969596862793, 1.2426483631134033, 56800, 0.00019813364555728923]
2023-02-03 04:06:54,574	9nineM	INFO	Saving model and optimizer state at iteration 67 to ./logs\9nineM\G_56800.pth
2023-02-03 04:06:55,602	9nineM	INFO	Saving model and optimizer state at iteration 67 to ./logs\9nineM\D_56800.pth
2023-02-03 04:10:05,886	9nineM	INFO	Train Epoch: 67 [82%]
2023-02-03 04:10:05,886	9nineM	INFO	[2.275343894958496, 2.5893187522888184, 6.625726699829102, 25.04363250732422, 1.7368674278259277, 1.6008716821670532, 57000, 0.00019813364555728923]
2023-02-03 04:12:30,861	9nineM	INFO	====> Epoch: 67
2023-02-03 04:13:50,275	9nineM	INFO	Train Epoch: 68 [6%]
2023-02-03 04:13:50,276	9nineM	INFO	[2.5386765003204346, 2.440680980682373, 5.077262878417969, 22.269128799438477, 1.749283790588379, 1.5236108303070068, 57200, 0.00019810887885159456]
2023-02-03 04:14:25,787	9nineM	INFO	Saving model and optimizer state at iteration 68 to ./logs\9nineM\G_57200.pth
2023-02-03 04:14:26,752	9nineM	INFO	Saving model and optimizer state at iteration 68 to ./logs\9nineM\D_57200.pth
2023-02-03 04:17:38,378	9nineM	INFO	Train Epoch: 68 [29%]
2023-02-03 04:17:38,379	9nineM	INFO	[2.5833661556243896, 2.1460273265838623, 5.135639190673828, 23.69635581970215, 1.7779978513717651, 1.9164893627166748, 57400, 0.00019810887885159456]
2023-02-03 04:20:50,177	9nineM	INFO	Train Epoch: 68 [53%]
2023-02-03 04:20:50,177	9nineM	INFO	[2.4862895011901855, 2.279574394226074, 5.097471237182617, 21.17926788330078, 1.7066378593444824, 1.8012689352035522, 57600, 0.00019810887885159456]
2023-02-03 04:21:26,004	9nineM	INFO	Saving model and optimizer state at iteration 68 to ./logs\9nineM\G_57600.pth
2023-02-03 04:21:26,997	9nineM	INFO	Saving model and optimizer state at iteration 68 to ./logs\9nineM\D_57600.pth
2023-02-03 04:24:39,212	9nineM	INFO	Train Epoch: 68 [76%]
2023-02-03 04:24:39,213	9nineM	INFO	[2.193986415863037, 2.6489603519439697, 6.275017261505127, 23.127561569213867, 1.6875288486480713, 1.6145249605178833, 57800, 0.00019810887885159456]
2023-02-03 04:27:49,754	9nineM	INFO	Train Epoch: 68 [100%]
2023-02-03 04:27:49,756	9nineM	INFO	[2.584716796875, 2.1586058139801025, 3.7279787063598633, 19.764524459838867, 1.6812318563461304, 1.5582759380340576, 58000, 0.00019810887885159456]
2023-02-03 04:28:25,577	9nineM	INFO	Saving model and optimizer state at iteration 68 to ./logs\9nineM\G_58000.pth
2023-02-03 04:28:26,556	9nineM	INFO	Saving model and optimizer state at iteration 68 to ./logs\9nineM\D_58000.pth
2023-02-03 04:28:31,711	9nineM	INFO	====> Epoch: 68
2023-02-03 04:32:12,824	9nineM	INFO	Train Epoch: 69 [23%]
2023-02-03 04:32:12,825	9nineM	INFO	[2.393617868423462, 2.3776895999908447, 5.664454936981201, 23.724445343017578, 1.8494908809661865, 1.3909265995025635, 58200, 0.0001980841152417381]
2023-02-03 04:35:23,554	9nineM	INFO	Train Epoch: 69 [46%]
2023-02-03 04:35:23,554	9nineM	INFO	[2.5609912872314453, 2.114701509475708, 4.657586097717285, 21.051551818847656, 1.6989542245864868, 1.7439806461334229, 58400, 0.0001980841152417381]
2023-02-03 04:35:59,512	9nineM	INFO	Saving model and optimizer state at iteration 69 to ./logs\9nineM\G_58400.pth
2023-02-03 04:36:00,491	9nineM	INFO	Saving model and optimizer state at iteration 69 to ./logs\9nineM\D_58400.pth
2023-02-03 04:39:10,453	9nineM	INFO	Train Epoch: 69 [70%]
2023-02-03 04:39:10,453	9nineM	INFO	[2.5410313606262207, 2.229185104370117, 5.6162109375, 21.478355407714844, 1.8260700702667236, 1.6734628677368164, 58600, 0.0001980841152417381]
2023-02-03 04:42:20,309	9nineM	INFO	Train Epoch: 69 [93%]
2023-02-03 04:42:20,310	9nineM	INFO	[2.5465710163116455, 2.2258176803588867, 4.023758411407471, 19.937156677246094, 1.7602260112762451, 1.5172138214111328, 58800, 0.0001980841152417381]
2023-02-03 04:42:56,481	9nineM	INFO	Saving model and optimizer state at iteration 69 to ./logs\9nineM\G_58800.pth
2023-02-03 04:42:57,493	9nineM	INFO	Saving model and optimizer state at iteration 69 to ./logs\9nineM\D_58800.pth
2023-02-03 04:43:52,221	9nineM	INFO	====> Epoch: 69
2023-02-03 04:46:41,280	9nineM	INFO	Train Epoch: 70 [17%]
2023-02-03 04:46:41,281	9nineM	INFO	[2.4627819061279297, 2.3296258449554443, 5.925930023193359, 24.470354080200195, 1.8671823740005493, 1.89864182472229, 59000, 0.00019805935472733287]
2023-02-03 04:49:51,875	9nineM	INFO	Train Epoch: 70 [40%]
2023-02-03 04:49:51,876	9nineM	INFO	[2.6727185249328613, 2.013561964035034, 3.91961669921875, 19.693506240844727, 1.796967625617981, 1.5389909744262695, 59200, 0.00019805935472733287]
2023-02-03 04:50:27,592	9nineM	INFO	Saving model and optimizer state at iteration 70 to ./logs\9nineM\G_59200.pth
2023-02-03 04:50:28,535	9nineM	INFO	Saving model and optimizer state at iteration 70 to ./logs\9nineM\D_59200.pth
2023-02-03 04:53:32,963	9nineM	INFO	Train Epoch: 70 [64%]
2023-02-03 04:53:32,964	9nineM	INFO	[2.6429226398468018, 2.2939488887786865, 5.161586284637451, 22.10187530517578, 1.583906650543213, 1.728223204612732, 59400, 0.00019805935472733287]
2023-02-03 04:56:17,586	9nineM	INFO	Train Epoch: 70 [87%]
2023-02-03 04:56:17,586	9nineM	INFO	[2.4202473163604736, 2.5460360050201416, 5.590799808502197, 22.982948303222656, 1.7700634002685547, 1.489729642868042, 59600, 0.00019805935472733287]
2023-02-03 04:56:44,645	9nineM	INFO	Saving model and optimizer state at iteration 70 to ./logs\9nineM\G_59600.pth
2023-02-03 04:56:45,298	9nineM	INFO	Saving model and optimizer state at iteration 70 to ./logs\9nineM\D_59600.pth
2023-02-03 04:58:17,075	9nineM	INFO	====> Epoch: 70
2023-02-03 04:59:58,463	9nineM	INFO	Train Epoch: 71 [11%]
2023-02-03 04:59:58,463	9nineM	INFO	[2.582427740097046, 2.1536905765533447, 4.7381911277771, 20.809873580932617, 1.6572215557098389, 1.4732290506362915, 59800, 0.00019803459730799195]
2023-02-03 05:02:45,830	9nineM	INFO	Train Epoch: 71 [34%]
2023-02-03 05:02:45,831	9nineM	INFO	[2.4081552028656006, 2.325221538543701, 5.1794538497924805, 22.750572204589844, 1.6821101903915405, 1.5753097534179688, 60000, 0.00019803459730799195]
2023-02-03 05:03:13,356	9nineM	INFO	Saving model and optimizer state at iteration 71 to ./logs\9nineM\G_60000.pth
2023-02-03 05:03:14,019	9nineM	INFO	Saving model and optimizer state at iteration 71 to ./logs\9nineM\D_60000.pth
2023-02-03 05:06:00,180	9nineM	INFO	Train Epoch: 71 [57%]
2023-02-03 05:06:00,180	9nineM	INFO	[2.515235185623169, 2.389220952987671, 4.70564079284668, 21.365650177001953, 1.8769023418426514, 1.3444002866744995, 60200, 0.00019803459730799195]
2023-02-03 05:08:45,422	9nineM	INFO	Train Epoch: 71 [81%]
2023-02-03 05:08:45,432	9nineM	INFO	[2.3964056968688965, 2.4605460166931152, 5.22156286239624, 22.29313087463379, 1.717556118965149, 1.6100229024887085, 60400, 0.00019803459730799195]
2023-02-03 05:09:12,854	9nineM	INFO	Saving model and optimizer state at iteration 71 to ./logs\9nineM\G_60400.pth
2023-02-03 05:09:13,518	9nineM	INFO	Saving model and optimizer state at iteration 71 to ./logs\9nineM\D_60400.pth
2023-02-03 05:11:30,482	9nineM	INFO	====> Epoch: 71
2023-02-03 05:12:27,666	9nineM	INFO	Train Epoch: 72 [4%]
2023-02-03 05:12:27,667	9nineM	INFO	[2.5781455039978027, 2.2156596183776855, 4.438287258148193, 21.295211791992188, 1.7262805700302124, 1.6773481369018555, 60600, 0.00019800984298332845]
2023-02-03 05:15:14,714	9nineM	INFO	Train Epoch: 72 [28%]
2023-02-03 05:15:14,714	9nineM	INFO	[2.0034523010253906, 2.7177186012268066, 8.564760208129883, 24.744157791137695, 1.79685378074646, 2.0481743812561035, 60800, 0.00019800984298332845]
2023-02-03 05:15:42,508	9nineM	INFO	Saving model and optimizer state at iteration 72 to ./logs\9nineM\G_60800.pth
2023-02-03 05:15:43,369	9nineM	INFO	Saving model and optimizer state at iteration 72 to ./logs\9nineM\D_60800.pth
2023-02-03 05:18:28,279	9nineM	INFO	Train Epoch: 72 [51%]
2023-02-03 05:18:28,280	9nineM	INFO	[2.4995293617248535, 2.5850839614868164, 5.889671325683594, 23.41088104248047, 1.725574254989624, 1.8313080072402954, 61000, 0.00019800984298332845]
2023-02-03 05:21:15,809	9nineM	INFO	Train Epoch: 72 [75%]
2023-02-03 05:21:15,810	9nineM	INFO	[2.5919060707092285, 2.217766046524048, 4.825982093811035, 21.60723114013672, 1.6928209066390991, 1.6144503355026245, 61200, 0.00019800984298332845]
2023-02-03 05:21:43,645	9nineM	INFO	Saving model and optimizer state at iteration 72 to ./logs\9nineM\G_61200.pth
2023-02-03 05:21:44,298	9nineM	INFO	Saving model and optimizer state at iteration 72 to ./logs\9nineM\D_61200.pth
2023-02-03 19:58:13,560	9nineM	INFO	Train Epoch: 72 [98%]
2023-02-03 19:58:13,561	9nineM	INFO	[2.799675703048706, 1.876345157623291, 2.7222440242767334, 17.285810470581055, 1.807011604309082, 1.583828091621399, 61400, 0.00019800984298332845]
2023-02-03 19:58:29,596	9nineM	INFO	====> Epoch: 72
2023-02-06 04:19:23,087	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 16, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-02-06 04:19:33,701	9nineM	INFO	Loaded checkpoint './logs\9nineM\G_61200.pth' (iteration 72)
2023-02-06 04:19:34,481	9nineM	INFO	Loaded checkpoint './logs\9nineM\D_61200.pth' (iteration 72)
2023-02-06 04:20:52,238	9nineM	INFO	Train Epoch: 72 [4%]
2023-02-06 04:20:52,240	9nineM	INFO	[2.4905245304107666, 2.4353814125061035, 4.857059478759766, 21.026994705200195, 1.728440523147583, 1.6196600198745728, 60600, 0.00019798509175295552]
2023-02-06 04:23:55,642	9nineM	INFO	Train Epoch: 72 [28%]
2023-02-06 04:23:55,643	9nineM	INFO	[2.456995725631714, 2.3115909099578857, 6.684133529663086, 24.83147621154785, 1.795435905456543, 1.773382544517517, 60800, 0.00019798509175295552]
2023-02-06 04:24:29,246	9nineM	INFO	Saving model and optimizer state at iteration 72 to ./logs\9nineM\G_60800.pth
2023-02-06 04:24:30,145	9nineM	INFO	Saving model and optimizer state at iteration 72 to ./logs\9nineM\D_60800.pth
2023-02-06 04:27:24,219	9nineM	INFO	Train Epoch: 72 [51%]
2023-02-06 04:27:24,220	9nineM	INFO	[2.3354060649871826, 2.769453287124634, 5.869713306427002, 22.62506103515625, 1.706385850906372, 1.8073004484176636, 61000, 0.00019798509175295552]
2023-02-06 04:30:18,799	9nineM	INFO	Train Epoch: 72 [75%]
2023-02-06 04:30:18,799	9nineM	INFO	[2.2391738891601562, 2.6108973026275635, 5.128167629241943, 21.239099502563477, 1.7100787162780762, 1.8996784687042236, 61200, 0.00019798509175295552]
2023-02-06 04:30:51,424	9nineM	INFO	Saving model and optimizer state at iteration 72 to ./logs\9nineM\G_61200.pth
2023-02-06 04:30:52,136	9nineM	INFO	Saving model and optimizer state at iteration 72 to ./logs\9nineM\D_61200.pth
2023-02-06 04:33:40,605	9nineM	INFO	Train Epoch: 72 [98%]
2023-02-06 04:33:40,606	9nineM	INFO	[2.6712112426757812, 2.091658353805542, 2.7821426391601562, 17.237686157226562, 1.82709801197052, 1.3094412088394165, 61400, 0.00019798509175295552]
2023-02-06 04:33:54,254	9nineM	INFO	====> Epoch: 72
2023-02-06 04:36:58,123	9nineM	INFO	Train Epoch: 73 [22%]
2023-02-06 04:36:58,124	9nineM	INFO	[2.4204890727996826, 2.2256619930267334, 5.238700866699219, 21.909423828125, 1.688030481338501, 1.5041248798370361, 61600, 0.0001979603436164864]
2023-02-06 04:37:31,074	9nineM	INFO	Saving model and optimizer state at iteration 73 to ./logs\9nineM\G_61600.pth
2023-02-06 04:37:31,913	9nineM	INFO	Saving model and optimizer state at iteration 73 to ./logs\9nineM\D_61600.pth
2023-02-06 04:40:20,691	9nineM	INFO	Train Epoch: 73 [45%]
2023-02-06 04:40:20,692	9nineM	INFO	[2.297163724899292, 2.347593069076538, 5.843701362609863, 21.70340919494629, 1.6715729236602783, 1.7778856754302979, 61800, 0.0001979603436164864]
2023-02-06 04:43:07,830	9nineM	INFO	Train Epoch: 73 [68%]
2023-02-06 04:43:07,830	9nineM	INFO	[2.466874122619629, 2.3205671310424805, 5.398853302001953, 22.586332321166992, 1.7785080671310425, 1.6443525552749634, 62000, 0.0001979603436164864]
2023-02-06 04:43:39,933	9nineM	INFO	Saving model and optimizer state at iteration 73 to ./logs\9nineM\G_62000.pth
2023-02-06 04:43:40,965	9nineM	INFO	Saving model and optimizer state at iteration 73 to ./logs\9nineM\D_62000.pth
2023-02-06 04:46:26,421	9nineM	INFO	Train Epoch: 73 [92%]
2023-02-06 04:46:26,422	9nineM	INFO	[2.499178886413574, 2.3824784755706787, 4.614241123199463, 20.497652053833008, 1.9082872867584229, 1.589255452156067, 62200, 0.0001979603436164864]
2023-02-06 04:47:24,497	9nineM	INFO	====> Epoch: 73
2023-02-06 04:49:43,316	9nineM	INFO	Train Epoch: 74 [15%]
2023-02-06 04:49:43,316	9nineM	INFO	[2.432863473892212, 2.816837787628174, 5.711406230926514, 22.893400192260742, 1.7619438171386719, 1.6729869842529297, 62400, 0.00019793559857353432]
2023-02-06 04:50:14,830	9nineM	INFO	Saving model and optimizer state at iteration 74 to ./logs\9nineM\G_62400.pth
2023-02-06 04:50:15,554	9nineM	INFO	Saving model and optimizer state at iteration 74 to ./logs\9nineM\D_62400.pth
2023-02-06 04:53:00,016	9nineM	INFO	Train Epoch: 74 [39%]
2023-02-06 04:53:00,016	9nineM	INFO	[2.2945990562438965, 2.665768623352051, 6.332032203674316, 23.053686141967773, 1.8312345743179321, 1.5201756954193115, 62600, 0.00019793559857353432]
2023-02-06 04:55:44,533	9nineM	INFO	Train Epoch: 74 [62%]
2023-02-06 04:55:44,533	9nineM	INFO	[2.482102155685425, 2.410092830657959, 5.942013263702393, 22.24520492553711, 1.692725419998169, 1.5181009769439697, 62800, 0.00019793559857353432]
2023-02-06 04:56:14,794	9nineM	INFO	Saving model and optimizer state at iteration 74 to ./logs\9nineM\G_62800.pth
2023-02-06 04:56:15,479	9nineM	INFO	Saving model and optimizer state at iteration 74 to ./logs\9nineM\D_62800.pth
2023-02-06 04:59:02,260	9nineM	INFO	Train Epoch: 74 [86%]
2023-02-06 04:59:02,260	9nineM	INFO	[2.519771099090576, 2.0773379802703857, 4.821554660797119, 21.217731475830078, 1.8580095767974854, 1.7496412992477417, 63000, 0.00019793559857353432]
2023-02-06 05:00:43,224	9nineM	INFO	====> Epoch: 74
2023-02-06 05:02:16,834	9nineM	INFO	Train Epoch: 75 [9%]
2023-02-06 05:02:16,835	9nineM	INFO	[2.4103803634643555, 2.195044755935669, 4.877587795257568, 21.299474716186523, 1.725413203239441, 1.654306411743164, 63200, 0.00019791085662371262]
2023-02-06 05:02:48,357	9nineM	INFO	Saving model and optimizer state at iteration 75 to ./logs\9nineM\G_63200.pth
2023-02-06 05:02:49,051	9nineM	INFO	Saving model and optimizer state at iteration 75 to ./logs\9nineM\D_63200.pth
2023-02-06 05:05:34,596	9nineM	INFO	Train Epoch: 75 [33%]
2023-02-06 05:05:34,597	9nineM	INFO	[2.401853084564209, 2.258467674255371, 5.803826808929443, 21.338125228881836, 1.8000590801239014, 1.4500749111175537, 63400, 0.00019791085662371262]
2023-02-06 05:08:19,457	9nineM	INFO	Train Epoch: 75 [56%]
2023-02-06 05:08:19,457	9nineM	INFO	[2.5368406772613525, 2.3413407802581787, 6.009054183959961, 23.420373916625977, 1.695863962173462, 1.942280650138855, 63600, 0.00019791085662371262]
2023-02-06 05:08:50,372	9nineM	INFO	Saving model and optimizer state at iteration 75 to ./logs\9nineM\G_63600.pth
2023-02-06 05:08:51,405	9nineM	INFO	Saving model and optimizer state at iteration 75 to ./logs\9nineM\D_63600.pth
2023-02-06 05:11:38,046	9nineM	INFO	Train Epoch: 75 [79%]
2023-02-06 05:11:38,047	9nineM	INFO	[2.731710433959961, 2.398693561553955, 4.9033613204956055, 20.635700225830078, 1.6762090921401978, 1.7057929039001465, 63800, 0.00019791085662371262]
2023-02-06 05:14:04,588	9nineM	INFO	====> Epoch: 75
2023-02-06 05:14:56,290	9nineM	INFO	Train Epoch: 76 [3%]
2023-02-06 05:14:56,291	9nineM	INFO	[2.266551971435547, 2.4041476249694824, 6.241879940032959, 20.23375701904297, 1.739053726196289, 1.4617226123809814, 64000, 0.00019788611776663464]
2023-02-06 05:15:28,171	9nineM	INFO	Saving model and optimizer state at iteration 76 to ./logs\9nineM\G_64000.pth
2023-02-06 05:15:28,900	9nineM	INFO	Saving model and optimizer state at iteration 76 to ./logs\9nineM\D_64000.pth
2023-02-06 05:18:13,967	9nineM	INFO	Train Epoch: 76 [26%]
2023-02-06 05:18:13,967	9nineM	INFO	[2.608781099319458, 2.4489901065826416, 4.1126251220703125, 19.619564056396484, 1.7689703702926636, 1.865809440612793, 64200, 0.00019788611776663464]
2023-02-06 05:20:56,605	9nineM	INFO	Train Epoch: 76 [50%]
2023-02-06 05:20:56,606	9nineM	INFO	[2.385148525238037, 2.502060890197754, 6.575152397155762, 24.20307159423828, 1.674390196800232, 1.6329617500305176, 64400, 0.00019788611776663464]
2023-02-06 05:21:25,733	9nineM	INFO	Saving model and optimizer state at iteration 76 to ./logs\9nineM\G_64400.pth
2023-02-06 05:21:26,481	9nineM	INFO	Saving model and optimizer state at iteration 76 to ./logs\9nineM\D_64400.pth
2023-02-06 05:24:10,848	9nineM	INFO	Train Epoch: 76 [73%]
2023-02-06 05:24:10,848	9nineM	INFO	[2.4705684185028076, 2.2331924438476562, 4.316597938537598, 21.17183494567871, 1.8557251691818237, 1.450272798538208, 64600, 0.00019788611776663464]
2023-02-06 05:26:54,935	9nineM	INFO	Train Epoch: 76 [97%]
2023-02-06 05:26:54,936	9nineM	INFO	[2.601595878601074, 2.2771596908569336, 5.144861221313477, 22.146696090698242, 1.7484124898910522, 1.5043407678604126, 64800, 0.00019788611776663464]
2023-02-06 05:27:23,905	9nineM	INFO	Saving model and optimizer state at iteration 76 to ./logs\9nineM\G_64800.pth
2023-02-06 05:27:24,936	9nineM	INFO	Saving model and optimizer state at iteration 76 to ./logs\9nineM\D_64800.pth
2023-02-06 05:27:48,334	9nineM	INFO	====> Epoch: 76
2023-02-06 05:30:37,137	9nineM	INFO	Train Epoch: 77 [20%]
2023-02-06 05:30:37,137	9nineM	INFO	[2.365074634552002, 2.463613271713257, 5.400785446166992, 20.98668098449707, 1.7013943195343018, 1.6169242858886719, 65000, 0.0001978613820019138]
2023-02-06 05:33:20,757	9nineM	INFO	Train Epoch: 77 [44%]
2023-02-06 05:33:20,758	9nineM	INFO	[2.445028066635132, 2.237590789794922, 5.2281293869018555, 23.237245559692383, 1.736968755722046, 1.720275640487671, 65200, 0.0001978613820019138]
2023-02-06 05:33:50,107	9nineM	INFO	Saving model and optimizer state at iteration 77 to ./logs\9nineM\G_65200.pth
2023-02-06 05:33:50,773	9nineM	INFO	Saving model and optimizer state at iteration 77 to ./logs\9nineM\D_65200.pth
2023-02-06 05:36:35,113	9nineM	INFO	Train Epoch: 77 [67%]
2023-02-06 05:36:35,114	9nineM	INFO	[2.5210564136505127, 2.193607807159424, 4.394340991973877, 21.00632095336914, 1.795645833015442, 1.6523388624191284, 65400, 0.0001978613820019138]
2023-02-06 05:39:18,849	9nineM	INFO	Train Epoch: 77 [91%]
2023-02-06 05:39:18,849	9nineM	INFO	[2.5398499965667725, 2.335365056991577, 4.490217208862305, 19.484638214111328, 1.7037937641143799, 1.7897189855575562, 65600, 0.0001978613820019138]
2023-02-06 05:39:48,452	9nineM	INFO	Saving model and optimizer state at iteration 77 to ./logs\9nineM\G_65600.pth
2023-02-06 05:39:49,125	9nineM	INFO	Saving model and optimizer state at iteration 77 to ./logs\9nineM\D_65600.pth
2023-02-06 05:40:55,486	9nineM	INFO	====> Epoch: 77
2023-02-06 05:42:59,001	9nineM	INFO	Train Epoch: 78 [14%]
2023-02-06 05:42:59,003	9nineM	INFO	[2.4388952255249023, 2.405015230178833, 4.805449962615967, 20.763015747070312, 1.807286024093628, 1.7616719007492065, 65800, 0.00019783664932916355]
2023-02-06 05:45:43,988	9nineM	INFO	Train Epoch: 78 [37%]
2023-02-06 05:45:43,988	9nineM	INFO	[2.264955759048462, 2.2813100814819336, 5.926263332366943, 24.083023071289062, 1.579649806022644, 1.7028638124465942, 66000, 0.00019783664932916355]
2023-02-06 05:46:14,480	9nineM	INFO	Saving model and optimizer state at iteration 78 to ./logs\9nineM\G_66000.pth
2023-02-06 05:46:15,162	9nineM	INFO	Saving model and optimizer state at iteration 78 to ./logs\9nineM\D_66000.pth
2023-02-06 05:49:00,678	9nineM	INFO	Train Epoch: 78 [61%]
2023-02-06 05:49:00,679	9nineM	INFO	[2.3051817417144775, 2.6702542304992676, 5.46689510345459, 22.072662353515625, 1.9787356853485107, 1.7422808408737183, 66200, 0.00019783664932916355]
2023-02-06 05:51:43,708	9nineM	INFO	Train Epoch: 78 [84%]
2023-02-06 05:51:43,709	9nineM	INFO	[2.4244790077209473, 2.3375325202941895, 5.385674953460693, 21.36229133605957, 1.8320544958114624, 1.6734129190444946, 66400, 0.00019783664932916355]
2023-02-06 05:52:12,773	9nineM	INFO	Saving model and optimizer state at iteration 78 to ./logs\9nineM\G_66400.pth
2023-02-06 05:52:13,541	9nineM	INFO	Saving model and optimizer state at iteration 78 to ./logs\9nineM\D_66400.pth
2023-02-06 05:54:03,122	9nineM	INFO	====> Epoch: 78
2023-02-06 05:55:26,532	9nineM	INFO	Train Epoch: 79 [8%]
2023-02-06 05:55:26,532	9nineM	INFO	[2.3645448684692383, 2.5583982467651367, 5.855003833770752, 21.44668197631836, 1.8052489757537842, 1.861608862876892, 66600, 0.0001978119197479974]
2023-02-06 05:58:09,323	9nineM	INFO	Train Epoch: 79 [31%]
2023-02-06 05:58:09,324	9nineM	INFO	[2.2633349895477295, 2.7029590606689453, 6.055595397949219, 20.4661865234375, 1.68825101852417, 1.40994131565094, 66800, 0.0001978119197479974]
2023-02-06 05:58:38,869	9nineM	INFO	Saving model and optimizer state at iteration 79 to ./logs\9nineM\G_66800.pth
2023-02-06 05:58:39,561	9nineM	INFO	Saving model and optimizer state at iteration 79 to ./logs\9nineM\D_66800.pth
2023-02-06 06:01:24,574	9nineM	INFO	Train Epoch: 79 [55%]
2023-02-06 06:01:24,575	9nineM	INFO	[2.553617238998413, 2.3292808532714844, 5.63338041305542, 22.44329071044922, 1.7927372455596924, 1.6714777946472168, 67000, 0.0001978119197479974]
2023-02-06 06:04:09,185	9nineM	INFO	Train Epoch: 79 [78%]
2023-02-06 06:04:09,186	9nineM	INFO	[2.2242395877838135, 2.42453670501709, 6.259720802307129, 24.094356536865234, 1.759538173675537, 2.102372169494629, 67200, 0.0001978119197479974]
2023-02-06 06:04:39,911	9nineM	INFO	Saving model and optimizer state at iteration 79 to ./logs\9nineM\G_67200.pth
2023-02-06 06:04:40,945	9nineM	INFO	Saving model and optimizer state at iteration 79 to ./logs\9nineM\D_67200.pth
2023-02-06 06:07:13,955	9nineM	INFO	====> Epoch: 79
2023-02-06 06:07:52,662	9nineM	INFO	Train Epoch: 80 [2%]
2023-02-06 06:07:52,663	9nineM	INFO	[2.4591546058654785, 2.247199535369873, 4.015508651733398, 19.516265869140625, 1.7036457061767578, 1.6470491886138916, 67400, 0.0001977871932580289]
2023-02-06 06:10:36,108	9nineM	INFO	Train Epoch: 80 [25%]
2023-02-06 06:10:36,109	9nineM	INFO	[2.5015718936920166, 2.36966872215271, 5.009028434753418, 20.039779663085938, 1.8621348142623901, 1.8031896352767944, 67600, 0.0001977871932580289]
2023-02-06 06:11:06,229	9nineM	INFO	Saving model and optimizer state at iteration 80 to ./logs\9nineM\G_67600.pth
2023-02-06 06:11:06,887	9nineM	INFO	Saving model and optimizer state at iteration 80 to ./logs\9nineM\D_67600.pth
2023-02-06 06:13:50,944	9nineM	INFO	Train Epoch: 80 [48%]
2023-02-06 06:13:50,945	9nineM	INFO	[2.483105182647705, 2.1891396045684814, 4.582153797149658, 20.420331954956055, 1.7401020526885986, 1.8074232339859009, 67800, 0.0001977871932580289]
2023-02-06 06:16:34,914	9nineM	INFO	Train Epoch: 80 [72%]
2023-02-06 06:16:34,915	9nineM	INFO	[2.465446949005127, 2.326713800430298, 4.555657386779785, 19.09385871887207, 1.7095659971237183, 1.7812799215316772, 68000, 0.0001977871932580289]
2023-02-06 06:17:04,264	9nineM	INFO	Saving model and optimizer state at iteration 80 to ./logs\9nineM\G_68000.pth
2023-02-06 06:17:04,974	9nineM	INFO	Saving model and optimizer state at iteration 80 to ./logs\9nineM\D_68000.pth
2023-02-06 06:19:49,384	9nineM	INFO	Train Epoch: 80 [95%]
2023-02-06 06:19:49,385	9nineM	INFO	[2.534393548965454, 2.290717363357544, 4.47852897644043, 18.6915283203125, 1.8048498630523682, 1.5194993019104004, 68200, 0.0001977871932580289]
2023-02-06 06:20:22,954	9nineM	INFO	====> Epoch: 80
2023-02-06 06:23:01,154	9nineM	INFO	Train Epoch: 81 [19%]
2023-02-06 06:23:01,155	9nineM	INFO	[2.447075843811035, 2.4602949619293213, 5.389459133148193, 22.743417739868164, 1.6735265254974365, 1.9042701721191406, 68400, 0.00019776246985887165]
2023-02-06 06:23:30,658	9nineM	INFO	Saving model and optimizer state at iteration 81 to ./logs\9nineM\G_68400.pth
2023-02-06 06:23:31,317	9nineM	INFO	Saving model and optimizer state at iteration 81 to ./logs\9nineM\D_68400.pth
2023-02-06 06:26:15,683	9nineM	INFO	Train Epoch: 81 [42%]
2023-02-06 06:26:15,683	9nineM	INFO	[2.463613986968994, 2.263181686401367, 5.198321342468262, 20.553791046142578, 1.7596567869186401, 1.6983942985534668, 68600, 0.00019776246985887165]
2023-02-06 06:28:59,102	9nineM	INFO	Train Epoch: 81 [66%]
2023-02-06 06:28:59,102	9nineM	INFO	[2.4809608459472656, 2.0485968589782715, 5.3793439865112305, 21.732845306396484, 1.7214068174362183, 1.644992470741272, 68800, 0.00019776246985887165]
2023-02-06 06:29:29,318	9nineM	INFO	Saving model and optimizer state at iteration 81 to ./logs\9nineM\G_68800.pth
2023-02-06 06:29:30,299	9nineM	INFO	Saving model and optimizer state at iteration 81 to ./logs\9nineM\D_68800.pth
2023-02-06 06:32:15,266	9nineM	INFO	Train Epoch: 81 [89%]
2023-02-06 06:32:15,266	9nineM	INFO	[2.6072030067443848, 2.166703939437866, 4.1110992431640625, 22.301462173461914, 1.8661930561065674, 1.7933987379074097, 69000, 0.00019776246985887165]
2023-02-06 06:33:32,306	9nineM	INFO	====> Epoch: 81
2023-02-06 06:35:29,074	9nineM	INFO	Train Epoch: 82 [13%]
2023-02-06 06:35:29,075	9nineM	INFO	[2.3665108680725098, 2.451719284057617, 5.408698558807373, 22.32443618774414, 1.7192881107330322, 1.540388584136963, 69200, 0.0001977377495501393]
2023-02-06 06:35:58,332	9nineM	INFO	Saving model and optimizer state at iteration 82 to ./logs\9nineM\G_69200.pth
2023-02-06 06:35:59,293	9nineM	INFO	Saving model and optimizer state at iteration 82 to ./logs\9nineM\D_69200.pth
2023-02-06 06:38:42,664	9nineM	INFO	Train Epoch: 82 [36%]
2023-02-06 06:38:42,665	9nineM	INFO	[2.7151167392730713, 2.011469841003418, 5.684447765350342, 22.217403411865234, 1.6232354640960693, 1.2984273433685303, 69400, 0.0001977377495501393]
2023-02-06 06:41:27,151	9nineM	INFO	Train Epoch: 82 [59%]
2023-02-06 06:41:27,152	9nineM	INFO	[2.4808833599090576, 2.1504311561584473, 4.597093105316162, 23.039443969726562, 1.7188286781311035, 1.7281453609466553, 69600, 0.0001977377495501393]
2023-02-06 06:41:56,782	9nineM	INFO	Saving model and optimizer state at iteration 82 to ./logs\9nineM\G_69600.pth
2023-02-06 06:41:57,829	9nineM	INFO	Saving model and optimizer state at iteration 82 to ./logs\9nineM\D_69600.pth
2023-02-06 06:44:41,047	9nineM	INFO	Train Epoch: 82 [83%]
2023-02-06 06:44:41,048	9nineM	INFO	[2.5977725982666016, 2.1633665561676025, 4.614894866943359, 20.658193588256836, 1.7138280868530273, 1.6857067346572876, 69800, 0.0001977377495501393]
2023-02-06 06:46:41,369	9nineM	INFO	====> Epoch: 82
2023-02-06 06:47:53,130	9nineM	INFO	Train Epoch: 83 [6%]
2023-02-06 06:47:53,131	9nineM	INFO	[2.5026674270629883, 2.5217862129211426, 5.649263381958008, 22.40220069885254, 1.8129355907440186, 1.6959840059280396, 70000, 0.0001977130323314455]
2023-02-06 06:48:23,258	9nineM	INFO	Saving model and optimizer state at iteration 83 to ./logs\9nineM\G_70000.pth
2023-02-06 06:48:24,297	9nineM	INFO	Saving model and optimizer state at iteration 83 to ./logs\9nineM\D_70000.pth
2023-02-06 06:51:08,155	9nineM	INFO	Train Epoch: 83 [30%]
2023-02-06 06:51:08,155	9nineM	INFO	[2.1798133850097656, 2.7249562740325928, 6.645028114318848, 22.770557403564453, 1.7452046871185303, 1.8580926656723022, 70200, 0.0001977130323314455]
2023-02-06 06:53:53,498	9nineM	INFO	Train Epoch: 83 [53%]
2023-02-06 06:53:53,498	9nineM	INFO	[2.541210174560547, 2.201444625854492, 4.370961666107178, 19.41265296936035, 1.7169926166534424, 1.755746841430664, 70400, 0.0001977130323314455]
2023-02-06 06:54:22,407	9nineM	INFO	Saving model and optimizer state at iteration 83 to ./logs\9nineM\G_70400.pth
2023-02-06 06:54:23,076	9nineM	INFO	Saving model and optimizer state at iteration 83 to ./logs\9nineM\D_70400.pth
2023-02-06 06:57:05,720	9nineM	INFO	Train Epoch: 83 [77%]
2023-02-06 06:57:05,720	9nineM	INFO	[2.431915044784546, 2.4835550785064697, 5.7723283767700195, 21.41901969909668, 1.6493549346923828, 1.791164517402649, 70600, 0.0001977130323314455]
2023-02-06 06:59:49,534	9nineM	INFO	====> Epoch: 83
2023-02-06 07:00:18,748	9nineM	INFO	Train Epoch: 84 [0%]
2023-02-06 07:00:18,749	9nineM	INFO	[2.513869285583496, 2.107764959335327, 4.408920764923096, 19.62989044189453, 1.6258065700531006, 1.6767607927322388, 70800, 0.00019768831820240408]
2023-02-06 07:00:48,180	9nineM	INFO	Saving model and optimizer state at iteration 84 to ./logs\9nineM\G_70800.pth
2023-02-06 07:00:49,224	9nineM	INFO	Saving model and optimizer state at iteration 84 to ./logs\9nineM\D_70800.pth
2023-02-06 07:03:32,265	9nineM	INFO	Train Epoch: 84 [24%]
2023-02-06 07:03:32,265	9nineM	INFO	[2.4345879554748535, 2.309798002243042, 4.741629123687744, 21.760465621948242, 1.7242400646209717, 1.506618857383728, 71000, 0.00019768831820240408]
2023-02-06 07:06:16,502	9nineM	INFO	Train Epoch: 84 [47%]
2023-02-06 07:06:16,502	9nineM	INFO	[2.479665756225586, 2.433314085006714, 5.1933674812316895, 21.31283187866211, 1.6841895580291748, 1.7562897205352783, 71200, 0.00019768831820240408]
2023-02-06 07:06:46,812	9nineM	INFO	Saving model and optimizer state at iteration 84 to ./logs\9nineM\G_71200.pth
2023-02-06 07:06:47,500	9nineM	INFO	Saving model and optimizer state at iteration 84 to ./logs\9nineM\D_71200.pth
2023-02-06 07:09:32,538	9nineM	INFO	Train Epoch: 84 [70%]
2023-02-06 07:09:32,539	9nineM	INFO	[2.40413236618042, 2.5912506580352783, 6.041769981384277, 22.648101806640625, 1.771620512008667, 1.703296422958374, 71400, 0.00019768831820240408]
2023-02-06 07:12:17,435	9nineM	INFO	Train Epoch: 84 [94%]
2023-02-06 07:12:17,436	9nineM	INFO	[2.358267068862915, 2.385530710220337, 5.9982075691223145, 22.88961410522461, 1.7426775693893433, 1.8333910703659058, 71600, 0.00019768831820240408]
2023-02-06 07:12:47,102	9nineM	INFO	Saving model and optimizer state at iteration 84 to ./logs\9nineM\G_71600.pth
2023-02-06 07:12:47,766	9nineM	INFO	Saving model and optimizer state at iteration 84 to ./logs\9nineM\D_71600.pth
2023-02-06 07:13:30,563	9nineM	INFO	====> Epoch: 84
2023-02-06 07:16:01,426	9nineM	INFO	Train Epoch: 85 [17%]
2023-02-06 07:16:01,427	9nineM	INFO	[2.3528549671173096, 2.277402400970459, 5.613468647003174, 22.561620712280273, 1.7338169813156128, 1.8296408653259277, 71800, 0.00019766360716262876]
2023-02-06 07:18:45,800	9nineM	INFO	Train Epoch: 85 [41%]
2023-02-06 07:18:45,801	9nineM	INFO	[2.4195868968963623, 2.400357484817505, 6.125772953033447, 21.994230270385742, 1.966027021408081, 1.4489802122116089, 72000, 0.00019766360716262876]
2023-02-06 07:19:15,482	9nineM	INFO	Saving model and optimizer state at iteration 85 to ./logs\9nineM\G_72000.pth
2023-02-06 07:19:16,251	9nineM	INFO	Saving model and optimizer state at iteration 85 to ./logs\9nineM\D_72000.pth
2023-02-06 07:21:59,420	9nineM	INFO	Train Epoch: 85 [64%]
2023-02-06 07:21:59,421	9nineM	INFO	[2.51851487159729, 2.247016429901123, 6.0481486320495605, 23.90782928466797, 1.729480266571045, 1.576174020767212, 72200, 0.00019766360716262876]
2023-02-06 07:24:43,265	9nineM	INFO	Train Epoch: 85 [88%]
2023-02-06 07:24:43,266	9nineM	INFO	[2.529348850250244, 2.436415910720825, 4.762678146362305, 20.736583709716797, 1.6964658498764038, 1.4529114961624146, 72400, 0.00019766360716262876]
2023-02-06 07:25:13,730	9nineM	INFO	Saving model and optimizer state at iteration 85 to ./logs\9nineM\G_72400.pth
2023-02-06 07:25:14,397	9nineM	INFO	Saving model and optimizer state at iteration 85 to ./logs\9nineM\D_72400.pth
2023-02-06 07:26:40,149	9nineM	INFO	====> Epoch: 85
2023-02-06 07:28:25,427	9nineM	INFO	Train Epoch: 86 [11%]
2023-02-06 07:28:25,428	9nineM	INFO	[2.436279535293579, 2.2832374572753906, 6.255619525909424, 22.62698745727539, 1.695105791091919, 1.2563732862472534, 72600, 0.00019763889921173343]
2023-02-06 07:31:09,401	9nineM	INFO	Train Epoch: 86 [35%]
2023-02-06 07:31:09,401	9nineM	INFO	[2.3377299308776855, 2.6488444805145264, 6.051377773284912, 24.113723754882812, 1.6612577438354492, 1.7706013917922974, 72800, 0.00019763889921173343]
2023-02-06 07:31:39,220	9nineM	INFO	Saving model and optimizer state at iteration 86 to ./logs\9nineM\G_72800.pth
2023-02-06 07:31:39,893	9nineM	INFO	Saving model and optimizer state at iteration 86 to ./logs\9nineM\D_72800.pth
2023-02-06 07:34:23,301	9nineM	INFO	Train Epoch: 86 [58%]
2023-02-06 07:34:23,302	9nineM	INFO	[2.406329870223999, 2.486889123916626, 5.256746292114258, 21.62246322631836, 1.7571786642074585, 1.7853766679763794, 73000, 0.00019763889921173343]
2023-02-06 07:37:07,826	9nineM	INFO	Train Epoch: 86 [81%]
2023-02-06 07:37:07,827	9nineM	INFO	[2.551205635070801, 2.0159339904785156, 4.293013572692871, 18.935142517089844, 1.712545394897461, 1.5677807331085205, 73200, 0.00019763889921173343]
2023-02-06 07:37:37,650	9nineM	INFO	Saving model and optimizer state at iteration 86 to ./logs\9nineM\G_73200.pth
2023-02-06 07:37:38,325	9nineM	INFO	Saving model and optimizer state at iteration 86 to ./logs\9nineM\D_73200.pth
2023-02-06 07:39:48,837	9nineM	INFO	====> Epoch: 86
2023-02-06 07:40:51,655	9nineM	INFO	Train Epoch: 87 [5%]
2023-02-06 07:40:51,655	9nineM	INFO	[2.459545612335205, 2.432029962539673, 5.8289079666137695, 23.371789932250977, 1.6886625289916992, 2.1385974884033203, 73400, 0.00019761419434933197]
2023-02-06 07:43:35,967	9nineM	INFO	Train Epoch: 87 [28%]
2023-02-06 07:43:35,968	9nineM	INFO	[2.5478644371032715, 2.123600959777832, 4.178177356719971, 21.52782440185547, 1.669135570526123, 1.7438825368881226, 73600, 0.00019761419434933197]
2023-02-06 07:44:06,519	9nineM	INFO	Saving model and optimizer state at iteration 87 to ./logs\9nineM\G_73600.pth
2023-02-06 07:44:07,198	9nineM	INFO	Saving model and optimizer state at iteration 87 to ./logs\9nineM\D_73600.pth
2023-02-06 07:46:52,105	9nineM	INFO	Train Epoch: 87 [52%]
2023-02-06 07:46:52,105	9nineM	INFO	[2.4402291774749756, 2.3444480895996094, 5.813377857208252, 22.064144134521484, 1.8148679733276367, 1.6917070150375366, 73800, 0.00019761419434933197]
2023-02-06 07:49:35,273	9nineM	INFO	Train Epoch: 87 [75%]
2023-02-06 07:49:35,273	9nineM	INFO	[2.453408718109131, 2.390099048614502, 6.011960029602051, 23.739017486572266, 1.6957061290740967, 1.9181777238845825, 74000, 0.00019761419434933197]
2023-02-06 07:50:04,951	9nineM	INFO	Saving model and optimizer state at iteration 87 to ./logs\9nineM\G_74000.pth
2023-02-06 07:50:05,616	9nineM	INFO	Saving model and optimizer state at iteration 87 to ./logs\9nineM\D_74000.pth
2023-02-06 07:52:49,629	9nineM	INFO	Train Epoch: 87 [99%]
2023-02-06 07:52:49,630	9nineM	INFO	[2.774932861328125, 2.2087159156799316, 4.179932117462158, 20.815813064575195, 1.735036849975586, 1.7144614458084106, 74200, 0.00019761419434933197]
2023-02-06 07:52:58,863	9nineM	INFO	====> Epoch: 87
2023-02-06 07:56:01,332	9nineM	INFO	Train Epoch: 88 [22%]
2023-02-06 07:56:01,333	9nineM	INFO	[2.351933002471924, 2.399723768234253, 5.7615180015563965, 21.04006576538086, 1.8368992805480957, 1.5686800479888916, 74400, 0.0001975894925750383]
2023-02-06 07:56:31,382	9nineM	INFO	Saving model and optimizer state at iteration 88 to ./logs\9nineM\G_74400.pth
2023-02-06 07:56:32,418	9nineM	INFO	Saving model and optimizer state at iteration 88 to ./logs\9nineM\D_74400.pth
2023-02-06 07:59:17,214	9nineM	INFO	Train Epoch: 88 [46%]
2023-02-06 07:59:17,214	9nineM	INFO	[2.4161877632141113, 2.6639819145202637, 6.529877185821533, 22.935834884643555, 1.7379610538482666, 2.1611557006835938, 74600, 0.0001975894925750383]
2023-02-06 08:02:00,819	9nineM	INFO	Train Epoch: 88 [69%]
2023-02-06 08:02:00,819	9nineM	INFO	[2.620955467224121, 2.19480562210083, 3.8729798793792725, 18.966899871826172, 1.7245399951934814, 1.749035120010376, 74800, 0.0001975894925750383]
2023-02-06 08:02:31,484	9nineM	INFO	Saving model and optimizer state at iteration 88 to ./logs\9nineM\G_74800.pth
2023-02-06 08:02:32,289	9nineM	INFO	Saving model and optimizer state at iteration 88 to ./logs\9nineM\D_74800.pth
2023-02-06 08:05:16,380	9nineM	INFO	Train Epoch: 88 [92%]
2023-02-06 08:05:16,381	9nineM	INFO	[2.3153486251831055, 2.869502067565918, 6.9400739669799805, 25.257213592529297, 1.8956434726715088, 1.7915812730789185, 75000, 0.0001975894925750383]
2023-02-06 08:06:10,217	9nineM	INFO	====> Epoch: 88
2023-02-06 08:08:29,207	9nineM	INFO	Train Epoch: 89 [16%]
2023-02-06 08:08:29,207	9nineM	INFO	[2.563227891921997, 2.303346872329712, 5.9095845222473145, 20.591371536254883, 1.6575027704238892, 1.8249729871749878, 75200, 0.0001975647938884664]
2023-02-06 08:08:59,182	9nineM	INFO	Saving model and optimizer state at iteration 89 to ./logs\9nineM\G_75200.pth
2023-02-06 08:09:00,160	9nineM	INFO	Saving model and optimizer state at iteration 89 to ./logs\9nineM\D_75200.pth
2023-02-06 08:11:46,003	9nineM	INFO	Train Epoch: 89 [39%]
2023-02-06 08:11:46,004	9nineM	INFO	[2.429751396179199, 2.1531074047088623, 5.851095199584961, 21.706199645996094, 1.6220355033874512, 1.6162998676300049, 75400, 0.0001975647938884664]
2023-02-06 08:14:29,994	9nineM	INFO	Train Epoch: 89 [63%]
2023-02-06 08:14:30,004	9nineM	INFO	[2.330639123916626, 2.474106788635254, 6.4344162940979, 22.50442123413086, 1.6688852310180664, 1.5176169872283936, 75600, 0.0001975647938884664]
2023-02-06 08:15:00,097	9nineM	INFO	Saving model and optimizer state at iteration 89 to ./logs\9nineM\G_75600.pth
2023-02-06 08:15:01,127	9nineM	INFO	Saving model and optimizer state at iteration 89 to ./logs\9nineM\D_75600.pth
2023-02-06 08:17:44,416	9nineM	INFO	Train Epoch: 89 [86%]
2023-02-06 08:17:44,416	9nineM	INFO	[2.6924614906311035, 2.412978172302246, 5.988645076751709, 21.709091186523438, 1.6463394165039062, 1.858162522315979, 75800, 0.0001975647938884664]
2023-02-06 08:19:20,462	9nineM	INFO	====> Epoch: 89
2023-02-06 08:20:56,935	9nineM	INFO	Train Epoch: 90 [10%]
2023-02-06 08:20:56,936	9nineM	INFO	[2.7380805015563965, 2.1342973709106445, 4.8604416847229, 22.41645050048828, 1.649432897567749, 1.7473390102386475, 76000, 0.00019754009828923033]
2023-02-06 08:21:27,354	9nineM	INFO	Saving model and optimizer state at iteration 90 to ./logs\9nineM\G_76000.pth
2023-02-06 08:21:28,043	9nineM	INFO	Saving model and optimizer state at iteration 90 to ./logs\9nineM\D_76000.pth
2023-02-06 08:24:14,115	9nineM	INFO	Train Epoch: 90 [33%]
2023-02-06 08:24:14,115	9nineM	INFO	[2.4273974895477295, 2.4092748165130615, 5.792497634887695, 22.798677444458008, 1.831376314163208, 1.3821916580200195, 76200, 0.00019754009828923033]
2023-02-06 08:26:57,187	9nineM	INFO	Train Epoch: 90 [57%]
2023-02-06 08:26:57,188	9nineM	INFO	[2.442150831222534, 2.240342617034912, 3.9635114669799805, 19.100793838500977, 1.736262321472168, 1.6014679670333862, 76400, 0.00019754009828923033]
2023-02-06 08:27:27,431	9nineM	INFO	Saving model and optimizer state at iteration 90 to ./logs\9nineM\G_76400.pth
2023-02-06 08:27:28,107	9nineM	INFO	Saving model and optimizer state at iteration 90 to ./logs\9nineM\D_76400.pth
2023-02-06 08:30:12,423	9nineM	INFO	Train Epoch: 90 [80%]
2023-02-06 08:30:12,423	9nineM	INFO	[2.235164165496826, 2.598625421524048, 7.3009233474731445, 23.685441970825195, 1.9746477603912354, 1.9208588600158691, 76600, 0.00019754009828923033]
2023-02-06 08:32:31,914	9nineM	INFO	====> Epoch: 90
2023-02-06 08:33:24,576	9nineM	INFO	Train Epoch: 91 [4%]
2023-02-06 08:33:24,576	9nineM	INFO	[2.332494020462036, 2.453765630722046, 6.486380577087402, 23.615463256835938, 1.828294038772583, 1.5180131196975708, 76800, 0.00019751540577694416]
2023-02-06 08:33:54,087	9nineM	INFO	Saving model and optimizer state at iteration 91 to ./logs\9nineM\G_76800.pth
2023-02-06 08:33:54,749	9nineM	INFO	Saving model and optimizer state at iteration 91 to ./logs\9nineM\D_76800.pth
2023-02-06 08:36:39,783	9nineM	INFO	Train Epoch: 91 [27%]
2023-02-06 08:36:39,784	9nineM	INFO	[2.502366542816162, 2.4421446323394775, 5.533163070678711, 21.886863708496094, 1.6957695484161377, 1.537204623222351, 77000, 0.00019751540577694416]
2023-02-06 08:39:23,860	9nineM	INFO	Train Epoch: 91 [50%]
2023-02-06 08:39:23,861	9nineM	INFO	[2.708211660385132, 2.3591372966766357, 4.701547622680664, 20.629417419433594, 1.7782450914382935, 1.5841456651687622, 77200, 0.00019751540577694416]
2023-02-06 08:39:54,615	9nineM	INFO	Saving model and optimizer state at iteration 91 to ./logs\9nineM\G_77200.pth
2023-02-06 08:39:55,312	9nineM	INFO	Saving model and optimizer state at iteration 91 to ./logs\9nineM\D_77200.pth
2023-02-06 08:42:39,685	9nineM	INFO	Train Epoch: 91 [74%]
2023-02-06 08:42:39,685	9nineM	INFO	[2.6561498641967773, 1.8691446781158447, 4.050014019012451, 16.30718231201172, 1.6753971576690674, 1.5077694654464722, 77400, 0.00019751540577694416]
2023-02-06 08:45:24,048	9nineM	INFO	Train Epoch: 91 [97%]
2023-02-06 08:45:24,049	9nineM	INFO	[2.4711616039276123, 2.310570478439331, 5.5823845863342285, 21.722213745117188, 1.644073724746704, 1.7697749137878418, 77600, 0.00019751540577694416]
2023-02-06 08:45:53,976	9nineM	INFO	Saving model and optimizer state at iteration 91 to ./logs\9nineM\G_77600.pth
2023-02-06 08:45:54,647	9nineM	INFO	Saving model and optimizer state at iteration 91 to ./logs\9nineM\D_77600.pth
2023-02-06 08:46:14,032	9nineM	INFO	====> Epoch: 91
2023-02-06 08:49:07,467	9nineM	INFO	Train Epoch: 92 [21%]
2023-02-06 08:49:07,468	9nineM	INFO	[2.2348618507385254, 2.5985894203186035, 6.874838829040527, 24.005840301513672, 1.7192668914794922, 1.6330294609069824, 77800, 0.00019749071635122203]
2023-02-06 08:51:51,630	9nineM	INFO	Train Epoch: 92 [44%]
2023-02-06 08:51:51,631	9nineM	INFO	[2.4240803718566895, 2.4423389434814453, 5.2924299240112305, 21.001216888427734, 1.645182728767395, 1.7892088890075684, 78000, 0.00019749071635122203]
2023-02-06 08:52:22,287	9nineM	INFO	Saving model and optimizer state at iteration 92 to ./logs\9nineM\G_78000.pth
2023-02-06 08:52:22,971	9nineM	INFO	Saving model and optimizer state at iteration 92 to ./logs\9nineM\D_78000.pth
2023-02-06 08:55:07,023	9nineM	INFO	Train Epoch: 92 [68%]
2023-02-06 08:55:07,023	9nineM	INFO	[2.5800209045410156, 2.1491897106170654, 4.399610996246338, 18.640945434570312, 1.7993099689483643, 1.4998753070831299, 78200, 0.00019749071635122203]
2023-02-06 08:57:52,510	9nineM	INFO	Train Epoch: 92 [91%]
2023-02-06 08:57:52,511	9nineM	INFO	[2.5566086769104004, 2.0559134483337402, 4.5262346267700195, 19.169645309448242, 1.6868771314620972, 1.8564404249191284, 78400, 0.00019749071635122203]
2023-02-06 08:58:22,538	9nineM	INFO	Saving model and optimizer state at iteration 92 to ./logs\9nineM\G_78400.pth
2023-02-06 08:58:23,313	9nineM	INFO	Saving model and optimizer state at iteration 92 to ./logs\9nineM\D_78400.pth
2023-02-06 08:59:24,804	9nineM	INFO	====> Epoch: 92
2023-02-06 09:01:36,233	9nineM	INFO	Train Epoch: 93 [15%]
2023-02-06 09:01:36,234	9nineM	INFO	[2.39662504196167, 2.420403480529785, 5.744348526000977, 21.538177490234375, 1.8771326541900635, 1.5871466398239136, 78600, 0.00019746603001167813]
2023-02-06 09:04:20,741	9nineM	INFO	Train Epoch: 93 [38%]
2023-02-06 09:04:20,742	9nineM	INFO	[2.543275833129883, 2.5176210403442383, 5.027650833129883, 20.407011032104492, 1.7027983665466309, 1.605425238609314, 78800, 0.00019746603001167813]
2023-02-06 09:04:50,775	9nineM	INFO	Saving model and optimizer state at iteration 93 to ./logs\9nineM\G_78800.pth
2023-02-06 09:04:51,442	9nineM	INFO	Saving model and optimizer state at iteration 93 to ./logs\9nineM\D_78800.pth
2023-02-06 09:07:35,022	9nineM	INFO	Train Epoch: 93 [61%]
2023-02-06 09:07:35,023	9nineM	INFO	[2.6210103034973145, 2.4276318550109863, 4.3305768966674805, 19.075326919555664, 1.7570873498916626, 1.3267184495925903, 79000, 0.00019746603001167813]
2023-02-06 09:10:19,949	9nineM	INFO	Train Epoch: 93 [85%]
2023-02-06 09:10:19,950	9nineM	INFO	[2.3554506301879883, 2.321150064468384, 5.2854533195495605, 20.60268783569336, 1.6685529947280884, 1.5909291505813599, 79200, 0.00019746603001167813]
2023-02-06 09:10:50,190	9nineM	INFO	Saving model and optimizer state at iteration 93 to ./logs\9nineM\G_79200.pth
2023-02-06 09:10:51,238	9nineM	INFO	Saving model and optimizer state at iteration 93 to ./logs\9nineM\D_79200.pth
2023-02-06 09:12:36,594	9nineM	INFO	====> Epoch: 93
2023-02-06 09:14:02,167	9nineM	INFO	Train Epoch: 94 [8%]
2023-02-06 09:14:02,168	9nineM	INFO	[2.474219799041748, 2.1666572093963623, 5.405589580535889, 20.69824981689453, 1.6610714197158813, 1.8200420141220093, 79400, 0.00019744134675792665]
2023-02-06 09:16:46,176	9nineM	INFO	Train Epoch: 94 [32%]
2023-02-06 09:16:46,176	9nineM	INFO	[2.2707855701446533, 2.6161155700683594, 6.605481147766113, 23.567001342773438, 1.6379531621932983, 1.573609709739685, 79600, 0.00019744134675792665]
2023-02-06 09:17:16,412	9nineM	INFO	Saving model and optimizer state at iteration 94 to ./logs\9nineM\G_79600.pth
2023-02-06 09:17:17,085	9nineM	INFO	Saving model and optimizer state at iteration 94 to ./logs\9nineM\D_79600.pth
2023-02-06 09:20:02,914	9nineM	INFO	Train Epoch: 94 [55%]
2023-02-06 09:20:02,915	9nineM	INFO	[2.358057975769043, 2.419687271118164, 6.182150840759277, 21.989639282226562, 1.6308257579803467, 1.7845832109451294, 79800, 0.00019744134675792665]
2023-02-06 09:22:46,788	9nineM	INFO	Train Epoch: 94 [79%]
2023-02-06 09:22:46,788	9nineM	INFO	[2.5282747745513916, 2.2075276374816895, 5.014464378356934, 23.92791748046875, 1.7892478704452515, 1.9707386493682861, 80000, 0.00019744134675792665]
2023-02-06 09:23:16,660	9nineM	INFO	Saving model and optimizer state at iteration 94 to ./logs\9nineM\G_80000.pth
2023-02-06 09:23:17,635	9nineM	INFO	Saving model and optimizer state at iteration 94 to ./logs\9nineM\D_80000.pth
2023-02-06 09:25:47,060	9nineM	INFO	====> Epoch: 94
2023-02-06 09:26:31,328	9nineM	INFO	Train Epoch: 95 [2%]
2023-02-06 09:26:31,329	9nineM	INFO	[2.611557960510254, 2.1368024349212646, 4.674160957336426, 21.47587013244629, 1.7486618757247925, 1.8024684190750122, 80200, 0.0001974166665895819]
2023-02-06 09:29:14,949	9nineM	INFO	Train Epoch: 95 [26%]
2023-02-06 09:29:14,949	9nineM	INFO	[2.3544092178344727, 2.420233964920044, 4.87743616104126, 20.30710792541504, 1.7553374767303467, 1.753144383430481, 80400, 0.0001974166665895819]
2023-02-06 09:29:46,319	9nineM	INFO	Saving model and optimizer state at iteration 95 to ./logs\9nineM\G_80400.pth
2023-02-06 09:29:46,998	9nineM	INFO	Saving model and optimizer state at iteration 95 to ./logs\9nineM\D_80400.pth
2023-02-06 09:32:33,227	9nineM	INFO	Train Epoch: 95 [49%]
2023-02-06 09:32:33,227	9nineM	INFO	[2.563666582107544, 2.3308403491973877, 3.933803081512451, 18.542442321777344, 1.7422237396240234, 1.398514747619629, 80600, 0.0001974166665895819]
2023-02-06 09:35:17,038	9nineM	INFO	Train Epoch: 95 [72%]
2023-02-06 09:35:17,038	9nineM	INFO	[2.4261467456817627, 2.45843243598938, 6.599765777587891, 22.300697326660156, 1.5651326179504395, 2.066063404083252, 80800, 0.0001974166665895819]
2023-02-06 09:35:46,870	9nineM	INFO	Saving model and optimizer state at iteration 95 to ./logs\9nineM\G_80800.pth
2023-02-06 09:35:47,901	9nineM	INFO	Saving model and optimizer state at iteration 95 to ./logs\9nineM\D_80800.pth
2023-02-06 09:38:32,362	9nineM	INFO	Train Epoch: 95 [96%]
2023-02-06 09:38:32,363	9nineM	INFO	[2.578087091445923, 2.2593815326690674, 5.092343807220459, 20.626312255859375, 1.7683870792388916, 1.6862581968307495, 81000, 0.0001974166665895819]
2023-02-06 09:39:00,580	9nineM	INFO	====> Epoch: 95
2023-02-06 09:41:43,540	9nineM	INFO	Train Epoch: 96 [19%]
2023-02-06 09:41:43,541	9nineM	INFO	[2.463958740234375, 2.409057855606079, 4.879076957702637, 21.166793823242188, 1.8808834552764893, 1.5445358753204346, 81200, 0.0001973919895062582]
2023-02-06 09:42:14,429	9nineM	INFO	Saving model and optimizer state at iteration 96 to ./logs\9nineM\G_81200.pth
2023-02-06 09:42:15,461	9nineM	INFO	Saving model and optimizer state at iteration 96 to ./logs\9nineM\D_81200.pth
2023-02-06 09:44:59,900	9nineM	INFO	Train Epoch: 96 [43%]
2023-02-06 09:44:59,901	9nineM	INFO	[2.601001739501953, 2.3067445755004883, 4.806454658508301, 19.276342391967773, 1.7806379795074463, 1.5881966352462769, 81400, 0.0001973919895062582]
2023-02-06 09:47:43,682	9nineM	INFO	Train Epoch: 96 [66%]
2023-02-06 09:47:43,683	9nineM	INFO	[2.5201852321624756, 2.24310040473938, 5.889530181884766, 22.60037612915039, 1.6959882974624634, 1.7985490560531616, 81600, 0.0001973919895062582]
2023-02-06 09:48:13,153	9nineM	INFO	Saving model and optimizer state at iteration 96 to ./logs\9nineM\G_81600.pth
2023-02-06 09:48:13,962	9nineM	INFO	Saving model and optimizer state at iteration 96 to ./logs\9nineM\D_81600.pth
2023-02-06 09:50:59,027	9nineM	INFO	Train Epoch: 96 [90%]
2023-02-06 09:50:59,028	9nineM	INFO	[2.223468780517578, 2.3834099769592285, 5.985912799835205, 22.880109786987305, 1.9438378810882568, 1.3537657260894775, 81800, 0.0001973919895062582]
2023-02-06 09:52:12,250	9nineM	INFO	====> Epoch: 96
2023-02-06 09:54:13,665	9nineM	INFO	Train Epoch: 97 [13%]
2023-02-06 09:54:13,666	9nineM	INFO	[2.352487087249756, 2.4814560413360596, 5.062458515167236, 19.829917907714844, 1.7631676197052002, 1.4059443473815918, 82000, 0.0001973673155075699]
2023-02-06 09:54:43,761	9nineM	INFO	Saving model and optimizer state at iteration 97 to ./logs\9nineM\G_82000.pth
2023-02-06 09:54:44,436	9nineM	INFO	Saving model and optimizer state at iteration 97 to ./logs\9nineM\D_82000.pth
2023-02-06 09:57:27,479	9nineM	INFO	Train Epoch: 97 [37%]
2023-02-06 09:57:27,479	9nineM	INFO	[2.4364724159240723, 2.3127033710479736, 5.209924697875977, 20.141944885253906, 1.8136754035949707, 1.963226318359375, 82200, 0.0001973673155075699]
2023-02-06 10:00:12,229	9nineM	INFO	Train Epoch: 97 [60%]
2023-02-06 10:00:12,230	9nineM	INFO	[2.397002696990967, 2.158003330230713, 5.6529860496521, 23.534862518310547, 1.837640643119812, 2.124126434326172, 82400, 0.0001973673155075699]
2023-02-06 10:00:43,447	9nineM	INFO	Saving model and optimizer state at iteration 97 to ./logs\9nineM\G_82400.pth
2023-02-06 10:00:44,131	9nineM	INFO	Saving model and optimizer state at iteration 97 to ./logs\9nineM\D_82400.pth
2023-02-06 10:03:27,934	9nineM	INFO	Train Epoch: 97 [83%]
2023-02-06 10:03:27,934	9nineM	INFO	[2.4804859161376953, 2.191072940826416, 4.700316429138184, 19.811946868896484, 1.827562689781189, 1.6359989643096924, 82600, 0.0001973673155075699]
2023-02-06 10:05:24,542	9nineM	INFO	====> Epoch: 97
2023-02-06 10:06:41,042	9nineM	INFO	Train Epoch: 98 [7%]
2023-02-06 10:06:41,043	9nineM	INFO	[2.589195966720581, 2.1672840118408203, 3.9097087383270264, 15.982277870178223, 1.690781593322754, 1.3834786415100098, 82800, 0.00019734264459313146]
2023-02-06 10:07:10,698	9nineM	INFO	Saving model and optimizer state at iteration 98 to ./logs\9nineM\G_82800.pth
2023-02-06 10:07:11,388	9nineM	INFO	Saving model and optimizer state at iteration 98 to ./logs\9nineM\D_82800.pth
2023-02-06 10:09:56,132	9nineM	INFO	Train Epoch: 98 [30%]
2023-02-06 10:09:56,133	9nineM	INFO	[2.2744922637939453, 2.516529083251953, 6.178014278411865, 23.27471923828125, 1.8042044639587402, 1.5633985996246338, 83000, 0.00019734264459313146]
2023-02-06 10:12:39,711	9nineM	INFO	Train Epoch: 98 [54%]
2023-02-06 10:12:39,712	9nineM	INFO	[2.3667120933532715, 2.5111308097839355, 5.213499069213867, 19.3061466217041, 1.6293022632598877, 1.5213712453842163, 83200, 0.00019734264459313146]
2023-02-06 10:13:11,009	9nineM	INFO	Saving model and optimizer state at iteration 98 to ./logs\9nineM\G_83200.pth
2023-02-06 10:13:12,080	9nineM	INFO	Saving model and optimizer state at iteration 98 to ./logs\9nineM\D_83200.pth
2023-02-06 10:15:57,460	9nineM	INFO	Train Epoch: 98 [77%]
2023-02-06 10:15:57,461	9nineM	INFO	[2.1953697204589844, 2.7360687255859375, 6.203606128692627, 22.292343139648438, 1.657147765159607, 1.4958841800689697, 83400, 0.00019734264459313146]
2023-02-06 10:18:36,765	9nineM	INFO	====> Epoch: 98
2023-02-06 10:19:11,281	9nineM	INFO	Train Epoch: 99 [1%]
2023-02-06 10:19:11,282	9nineM	INFO	[2.451085329055786, 2.4639837741851807, 5.215527534484863, 22.481882095336914, 1.674523115158081, 1.8604766130447388, 83600, 0.0001973179767625573]
2023-02-06 10:19:40,733	9nineM	INFO	Saving model and optimizer state at iteration 99 to ./logs\9nineM\G_83600.pth
2023-02-06 10:19:41,516	9nineM	INFO	Saving model and optimizer state at iteration 99 to ./logs\9nineM\D_83600.pth
2023-02-06 10:22:25,452	9nineM	INFO	Train Epoch: 99 [24%]
2023-02-06 10:22:25,453	9nineM	INFO	[2.4752984046936035, 2.3966166973114014, 5.918449878692627, 21.627058029174805, 1.71543550491333, 1.565459132194519, 83800, 0.0001973179767625573]
2023-02-06 10:25:09,570	9nineM	INFO	Train Epoch: 99 [48%]
2023-02-06 10:25:09,570	9nineM	INFO	[2.568911075592041, 2.5234763622283936, 5.772751331329346, 21.747419357299805, 1.6511496305465698, 1.1468724012374878, 84000, 0.0001973179767625573]
2023-02-06 10:25:39,863	9nineM	INFO	Saving model and optimizer state at iteration 99 to ./logs\9nineM\G_84000.pth
2023-02-06 10:25:40,858	9nineM	INFO	Saving model and optimizer state at iteration 99 to ./logs\9nineM\D_84000.pth
2023-02-06 10:28:24,806	9nineM	INFO	Train Epoch: 99 [71%]
2023-02-06 10:28:24,806	9nineM	INFO	[2.125399589538574, 2.816816806793213, 6.9142374992370605, 25.68486213684082, 1.7990564107894897, 1.9879125356674194, 84200, 0.0001973179767625573]
2023-02-06 10:31:09,724	9nineM	INFO	Train Epoch: 99 [94%]
2023-02-06 10:31:09,725	9nineM	INFO	[2.2676405906677246, 2.59442400932312, 5.924431800842285, 22.553234100341797, 1.7911489009857178, 1.6102948188781738, 84400, 0.0001973179767625573]
2023-02-06 10:31:40,127	9nineM	INFO	Saving model and optimizer state at iteration 99 to ./logs\9nineM\G_84400.pth
2023-02-06 10:31:40,816	9nineM	INFO	Saving model and optimizer state at iteration 99 to ./logs\9nineM\D_84400.pth
2023-02-06 10:32:20,165	9nineM	INFO	====> Epoch: 99
2023-02-06 10:34:54,257	9nineM	INFO	Train Epoch: 100 [18%]
2023-02-06 10:34:54,258	9nineM	INFO	[2.5476250648498535, 2.2353858947753906, 4.74211311340332, 20.432907104492188, 1.6521961688995361, 1.5227948427200317, 84600, 0.00019729331201546197]
2023-02-06 10:37:37,164	9nineM	INFO	Train Epoch: 100 [41%]
2023-02-06 10:37:37,164	9nineM	INFO	[2.3216915130615234, 2.4710023403167725, 6.245323657989502, 24.969099044799805, 1.5494719743728638, 1.6234177350997925, 84800, 0.00019729331201546197]
2023-02-06 10:38:07,297	9nineM	INFO	Saving model and optimizer state at iteration 100 to ./logs\9nineM\G_84800.pth
2023-02-06 10:38:08,000	9nineM	INFO	Saving model and optimizer state at iteration 100 to ./logs\9nineM\D_84800.pth
2023-02-06 10:40:52,533	9nineM	INFO	Train Epoch: 100 [65%]
2023-02-06 10:40:52,533	9nineM	INFO	[2.5477421283721924, 2.298691511154175, 5.10249662399292, 21.817508697509766, 1.777747631072998, 1.809820294380188, 85000, 0.00019729331201546197]
2023-02-06 10:43:37,482	9nineM	INFO	Train Epoch: 100 [88%]
2023-02-06 10:43:37,482	9nineM	INFO	[2.5234744548797607, 2.2988555431365967, 4.506878852844238, 18.725780487060547, 1.8095089197158813, 1.669141173362732, 85200, 0.00019729331201546197]
2023-02-06 10:44:09,203	9nineM	INFO	Saving model and optimizer state at iteration 100 to ./logs\9nineM\G_85200.pth
2023-02-06 10:44:10,236	9nineM	INFO	Saving model and optimizer state at iteration 100 to ./logs\9nineM\D_85200.pth
2023-02-06 10:45:33,612	9nineM	INFO	====> Epoch: 100
2023-02-06 10:47:25,153	9nineM	INFO	Train Epoch: 101 [12%]
2023-02-06 10:47:25,153	9nineM	INFO	[2.544187545776367, 2.4020485877990723, 6.031364917755127, 22.315113067626953, 1.7466915845870972, 1.7877157926559448, 85400, 0.00019726865035146003]
2023-02-06 10:50:08,879	9nineM	INFO	Train Epoch: 101 [35%]
2023-02-06 10:50:08,880	9nineM	INFO	[2.6537857055664062, 2.2612950801849365, 4.77888822555542, 20.681739807128906, 1.6496939659118652, 1.7405048608779907, 85600, 0.00019726865035146003]
2023-02-06 10:50:39,052	9nineM	INFO	Saving model and optimizer state at iteration 101 to ./logs\9nineM\G_85600.pth
2023-02-06 10:50:39,716	9nineM	INFO	Saving model and optimizer state at iteration 101 to ./logs\9nineM\D_85600.pth
2023-02-06 10:53:23,840	9nineM	INFO	Train Epoch: 101 [59%]
2023-02-06 10:53:23,841	9nineM	INFO	[2.3079352378845215, 2.533984661102295, 5.961873531341553, 22.472530364990234, 1.8380146026611328, 1.473942518234253, 85800, 0.00019726865035146003]
2023-02-06 10:56:09,476	9nineM	INFO	Train Epoch: 101 [82%]
2023-02-06 10:56:09,476	9nineM	INFO	[2.5508816242218018, 2.2959938049316406, 5.255324363708496, 22.835617065429688, 1.8479453325271606, 1.771566390991211, 86000, 0.00019726865035146003]
2023-02-06 10:56:40,434	9nineM	INFO	Saving model and optimizer state at iteration 101 to ./logs\9nineM\G_86000.pth
2023-02-06 10:56:41,133	9nineM	INFO	Saving model and optimizer state at iteration 101 to ./logs\9nineM\D_86000.pth
2023-02-06 10:58:46,783	9nineM	INFO	====> Epoch: 101
2023-02-06 10:59:55,812	9nineM	INFO	Train Epoch: 102 [6%]
2023-02-06 10:59:55,813	9nineM	INFO	[2.6004433631896973, 2.0733160972595215, 5.038445949554443, 20.638139724731445, 1.6360429525375366, 1.7312970161437988, 86200, 0.0001972439917701661]
2023-02-06 11:02:40,275	9nineM	INFO	Train Epoch: 102 [29%]
2023-02-06 11:02:40,276	9nineM	INFO	[2.5770530700683594, 2.3011891841888428, 6.0666046142578125, 22.05961036682129, 1.729824185371399, 1.7705416679382324, 86400, 0.0001972439917701661]
2023-02-06 11:03:10,492	9nineM	INFO	Saving model and optimizer state at iteration 102 to ./logs\9nineM\G_86400.pth
2023-02-06 11:03:11,262	9nineM	INFO	Saving model and optimizer state at iteration 102 to ./logs\9nineM\D_86400.pth
2023-02-06 11:05:56,035	9nineM	INFO	Train Epoch: 102 [52%]
2023-02-06 11:05:56,036	9nineM	INFO	[2.349095344543457, 2.5271549224853516, 6.557182788848877, 22.814111709594727, 1.86641526222229, 1.6259549856185913, 86600, 0.0001972439917701661]
2023-02-06 11:08:41,047	9nineM	INFO	Train Epoch: 102 [76%]
2023-02-06 11:08:41,047	9nineM	INFO	[2.524496555328369, 2.219241142272949, 5.192203998565674, 20.76837921142578, 1.6769731044769287, 1.737959384918213, 86800, 0.0001972439917701661]
2023-02-06 11:09:12,287	9nineM	INFO	Saving model and optimizer state at iteration 102 to ./logs\9nineM\G_86800.pth
2023-02-06 11:09:13,205	9nineM	INFO	Saving model and optimizer state at iteration 102 to ./logs\9nineM\D_86800.pth
2023-02-06 11:11:56,898	9nineM	INFO	Train Epoch: 102 [99%]
2023-02-06 11:11:56,898	9nineM	INFO	[2.205711603164673, 2.617997169494629, 6.884082794189453, 25.529481887817383, 1.7504960298538208, 1.672400951385498, 87000, 0.0001972439917701661]
2023-02-06 11:12:02,213	9nineM	INFO	====> Epoch: 102
2023-02-06 11:15:09,764	9nineM	INFO	Train Epoch: 103 [23%]
2023-02-06 11:15:09,764	9nineM	INFO	[2.2377357482910156, 2.602341890335083, 7.447323799133301, 23.61313247680664, 1.7152796983718872, 1.8794821500778198, 87200, 0.0001972193362711948]
2023-02-06 11:15:40,223	9nineM	INFO	Saving model and optimizer state at iteration 103 to ./logs\9nineM\G_87200.pth
2023-02-06 11:15:41,168	9nineM	INFO	Saving model and optimizer state at iteration 103 to ./logs\9nineM\D_87200.pth
2023-02-06 11:18:27,520	9nineM	INFO	Train Epoch: 103 [46%]
2023-02-06 11:18:27,521	9nineM	INFO	[2.712226390838623, 2.2979068756103516, 5.092637062072754, 20.449615478515625, 1.737058162689209, 1.4950884580612183, 87400, 0.0001972193362711948]
2023-02-06 11:21:12,014	9nineM	INFO	Train Epoch: 103 [70%]
2023-02-06 11:21:12,014	9nineM	INFO	[2.30623197555542, 2.5487325191497803, 5.575582504272461, 20.675832748413086, 1.706954836845398, 1.6465661525726318, 87600, 0.0001972193362711948]
2023-02-06 11:21:43,820	9nineM	INFO	Saving model and optimizer state at iteration 103 to ./logs\9nineM\G_87600.pth
2023-02-06 11:21:44,853	9nineM	INFO	Saving model and optimizer state at iteration 103 to ./logs\9nineM\D_87600.pth
2023-02-06 11:24:28,298	9nineM	INFO	Train Epoch: 103 [93%]
2023-02-06 11:24:28,299	9nineM	INFO	[2.4253954887390137, 2.36098313331604, 5.977612495422363, 21.248291015625, 1.8056401014328003, 1.7103567123413086, 87800, 0.0001972193362711948]
2023-02-06 11:25:17,552	9nineM	INFO	====> Epoch: 103
2023-02-06 11:27:41,207	9nineM	INFO	Train Epoch: 104 [17%]
2023-02-06 11:27:41,207	9nineM	INFO	[2.463886260986328, 2.316082715988159, 5.195700168609619, 20.788217544555664, 1.651336431503296, 1.5984183549880981, 88000, 0.0001971946838541609]
2023-02-06 11:28:11,486	9nineM	INFO	Saving model and optimizer state at iteration 104 to ./logs\9nineM\G_88000.pth
2023-02-06 11:28:12,165	9nineM	INFO	Saving model and optimizer state at iteration 104 to ./logs\9nineM\D_88000.pth
2023-02-06 11:30:56,757	9nineM	INFO	Train Epoch: 104 [40%]
2023-02-06 11:30:56,758	9nineM	INFO	[2.375288963317871, 2.3273239135742188, 4.723942279815674, 19.1896915435791, 1.7673020362854004, 1.876954197883606, 88200, 0.0001971946838541609]
2023-02-06 11:33:42,344	9nineM	INFO	Train Epoch: 104 [63%]
2023-02-06 11:33:42,345	9nineM	INFO	[2.212533950805664, 2.5205368995666504, 7.182621955871582, 23.782886505126953, 1.7014200687408447, 1.5421793460845947, 88400, 0.0001971946838541609]
2023-02-06 11:34:12,802	9nineM	INFO	Saving model and optimizer state at iteration 104 to ./logs\9nineM\G_88400.pth
2023-02-06 11:34:13,530	9nineM	INFO	Saving model and optimizer state at iteration 104 to ./logs\9nineM\D_88400.pth
2023-02-06 11:36:58,686	9nineM	INFO	Train Epoch: 104 [87%]
2023-02-06 11:36:58,688	9nineM	INFO	[2.6404221057891846, 1.999783992767334, 3.515745162963867, 18.34442138671875, 1.7381060123443604, 1.2916051149368286, 88600, 0.0001971946838541609]
2023-02-06 11:38:30,380	9nineM	INFO	====> Epoch: 104
2023-02-06 11:40:11,306	9nineM	INFO	Train Epoch: 105 [10%]
2023-02-06 11:40:11,307	9nineM	INFO	[2.5333781242370605, 2.0580761432647705, 4.338613510131836, 18.535072326660156, 1.7914912700653076, 1.4338421821594238, 88800, 0.0001971700345186791]
2023-02-06 11:40:42,688	9nineM	INFO	Saving model and optimizer state at iteration 105 to ./logs\9nineM\G_88800.pth
2023-02-06 11:40:43,373	9nineM	INFO	Saving model and optimizer state at iteration 105 to ./logs\9nineM\D_88800.pth
2023-02-06 11:43:28,822	9nineM	INFO	Train Epoch: 105 [34%]
2023-02-06 11:43:28,823	9nineM	INFO	[2.6348657608032227, 2.2804720401763916, 5.731025695800781, 21.585073471069336, 1.744161605834961, 1.906490683555603, 89000, 0.0001971700345186791]
2023-02-06 11:46:13,883	9nineM	INFO	Train Epoch: 105 [57%]
2023-02-06 11:46:13,884	9nineM	INFO	[2.4561171531677246, 2.150024890899658, 6.180589199066162, 22.93134307861328, 2.06330943107605, 1.433523178100586, 89200, 0.0001971700345186791]
2023-02-06 11:46:44,083	9nineM	INFO	Saving model and optimizer state at iteration 105 to ./logs\9nineM\G_89200.pth
2023-02-06 11:46:45,111	9nineM	INFO	Saving model and optimizer state at iteration 105 to ./logs\9nineM\D_89200.pth
2023-02-06 11:49:28,921	9nineM	INFO	Train Epoch: 105 [81%]
2023-02-06 11:49:28,922	9nineM	INFO	[2.183551073074341, 2.5984156131744385, 6.716160774230957, 23.298635482788086, 1.7402210235595703, 1.5968148708343506, 89400, 0.0001971700345186791]
2023-02-06 11:51:44,434	9nineM	INFO	====> Epoch: 105
2023-02-06 11:52:41,462	9nineM	INFO	Train Epoch: 106 [4%]
2023-02-06 11:52:41,463	9nineM	INFO	[2.3252651691436768, 2.640533924102783, 6.423140525817871, 23.449329376220703, 1.690205454826355, 1.4696669578552246, 89600, 0.00019714538826436426]
2023-02-06 11:53:12,433	9nineM	INFO	Saving model and optimizer state at iteration 106 to ./logs\9nineM\G_89600.pth
2023-02-06 11:53:13,138	9nineM	INFO	Saving model and optimizer state at iteration 106 to ./logs\9nineM\D_89600.pth
2023-02-06 11:55:56,804	9nineM	INFO	Train Epoch: 106 [28%]
2023-02-06 11:55:56,804	9nineM	INFO	[2.674956798553467, 2.393597364425659, 4.778692245483398, 18.844938278198242, 1.786001205444336, 1.6210120916366577, 89800, 0.00019714538826436426]
2023-02-06 11:58:42,274	9nineM	INFO	Train Epoch: 106 [51%]
2023-02-06 11:58:42,274	9nineM	INFO	[2.336738109588623, 2.489057779312134, 6.216240882873535, 22.527603149414062, 1.7865468263626099, 1.4562931060791016, 90000, 0.00019714538826436426]
2023-02-06 11:59:13,143	9nineM	INFO	Saving model and optimizer state at iteration 106 to ./logs\9nineM\G_90000.pth
2023-02-06 11:59:14,176	9nineM	INFO	Saving model and optimizer state at iteration 106 to ./logs\9nineM\D_90000.pth
2023-02-06 12:01:58,936	9nineM	INFO	Train Epoch: 106 [74%]
2023-02-06 12:01:58,937	9nineM	INFO	[2.3444700241088867, 2.7502689361572266, 6.141520023345947, 23.710206985473633, 1.6360828876495361, 2.0136559009552, 90200, 0.00019714538826436426]
2023-02-06 12:04:43,804	9nineM	INFO	Train Epoch: 106 [98%]
2023-02-06 12:04:43,804	9nineM	INFO	[2.321829319000244, 2.5711233615875244, 7.130553245544434, 23.442434310913086, 1.7535964250564575, 1.7496147155761719, 90400, 0.00019714538826436426]
2023-02-06 12:05:15,078	9nineM	INFO	Saving model and optimizer state at iteration 106 to ./logs\9nineM\G_90400.pth
2023-02-06 12:05:15,750	9nineM	INFO	Saving model and optimizer state at iteration 106 to ./logs\9nineM\D_90400.pth
2023-02-06 12:05:31,205	9nineM	INFO	====> Epoch: 106
2023-02-06 12:08:29,964	9nineM	INFO	Train Epoch: 107 [21%]
2023-02-06 12:08:29,964	9nineM	INFO	[2.4372658729553223, 2.724229335784912, 7.476496696472168, 24.135536193847656, 1.7371110916137695, 1.520024299621582, 90600, 0.0001971207450908312]
2023-02-06 12:11:14,222	9nineM	INFO	Train Epoch: 107 [45%]
2023-02-06 12:11:14,223	9nineM	INFO	[2.4366061687469482, 2.343618154525757, 6.166101455688477, 22.922292709350586, 1.7660292387008667, 1.7507487535476685, 90800, 0.0001971207450908312]
2023-02-06 12:11:44,831	9nineM	INFO	Saving model and optimizer state at iteration 107 to ./logs\9nineM\G_90800.pth
2023-02-06 12:11:45,517	9nineM	INFO	Saving model and optimizer state at iteration 107 to ./logs\9nineM\D_90800.pth
2023-02-06 12:14:29,985	9nineM	INFO	Train Epoch: 107 [68%]
2023-02-06 12:14:29,986	9nineM	INFO	[2.506448745727539, 2.181760311126709, 5.925235271453857, 22.16648292541504, 1.6654726266860962, 1.3967851400375366, 91000, 0.0001971207450908312]
2023-02-06 12:17:14,777	9nineM	INFO	Train Epoch: 107 [92%]
2023-02-06 12:17:14,778	9nineM	INFO	[2.42924165725708, 2.3328113555908203, 6.019453048706055, 21.61944007873535, 1.754049301147461, 1.4748058319091797, 91200, 0.0001971207450908312]
2023-02-06 12:17:45,318	9nineM	INFO	Saving model and optimizer state at iteration 107 to ./logs\9nineM\G_91200.pth
2023-02-06 12:17:46,004	9nineM	INFO	Saving model and optimizer state at iteration 107 to ./logs\9nineM\D_91200.pth
2023-02-06 12:18:45,653	9nineM	INFO	====> Epoch: 107
2023-02-06 12:21:05,160	9nineM	INFO	Train Epoch: 108 [15%]
2023-02-06 12:21:05,161	9nineM	INFO	[2.4319915771484375, 2.3685550689697266, 4.853661060333252, 20.543039321899414, 1.7073560953140259, 1.7163294553756714, 91400, 0.00019709610499769482]
2023-02-06 12:23:47,605	9nineM	INFO	Train Epoch: 108 [39%]
2023-02-06 12:23:47,605	9nineM	INFO	[2.5256752967834473, 2.322812080383301, 4.907132625579834, 20.325536727905273, 1.7290232181549072, 1.8438165187835693, 91600, 0.00019709610499769482]
2023-02-06 12:24:18,913	9nineM	INFO	Saving model and optimizer state at iteration 108 to ./logs\9nineM\G_91600.pth
2023-02-06 12:24:19,584	9nineM	INFO	Saving model and optimizer state at iteration 108 to ./logs\9nineM\D_91600.pth
2023-02-06 12:27:05,811	9nineM	INFO	Train Epoch: 108 [62%]
2023-02-06 12:27:05,812	9nineM	INFO	[2.1529364585876465, 2.707568645477295, 7.620291233062744, 24.264650344848633, 1.7756242752075195, 1.9135087728500366, 91800, 0.00019709610499769482]
2023-02-06 12:29:50,634	9nineM	INFO	Train Epoch: 108 [85%]
2023-02-06 12:29:50,634	9nineM	INFO	[2.622178077697754, 2.3537964820861816, 5.093014240264893, 20.53378677368164, 1.6982512474060059, 1.4778978824615479, 92000, 0.00019709610499769482]
2023-02-06 12:30:22,090	9nineM	INFO	Saving model and optimizer state at iteration 108 to ./logs\9nineM\G_92000.pth
2023-02-06 12:30:22,786	9nineM	INFO	Saving model and optimizer state at iteration 108 to ./logs\9nineM\D_92000.pth
2023-02-06 12:32:07,275	9nineM	INFO	====> Epoch: 108
2023-02-06 12:33:41,777	9nineM	INFO	Train Epoch: 109 [9%]
2023-02-06 12:33:41,778	9nineM	INFO	[2.635251760482788, 2.060101270675659, 4.255732536315918, 20.782381057739258, 1.6539850234985352, 1.4945626258850098, 92200, 0.0001970714679845701]
2023-02-06 12:36:27,527	9nineM	INFO	Train Epoch: 109 [32%]
2023-02-06 12:36:27,528	9nineM	INFO	[2.5063834190368652, 2.531637191772461, 5.950955867767334, 21.967214584350586, 1.7070696353912354, 1.0353264808654785, 92400, 0.0001970714679845701]
2023-02-06 12:36:59,546	9nineM	INFO	Saving model and optimizer state at iteration 109 to ./logs\9nineM\G_92400.pth
2023-02-06 12:37:00,238	9nineM	INFO	Saving model and optimizer state at iteration 109 to ./logs\9nineM\D_92400.pth
2023-02-06 12:39:46,307	9nineM	INFO	Train Epoch: 109 [56%]
2023-02-06 12:39:46,308	9nineM	INFO	[2.151048183441162, 2.8025808334350586, 6.490227699279785, 20.46746063232422, 1.7056280374526978, 1.7053507566452026, 92600, 0.0001970714679845701]
2023-02-06 12:42:30,182	9nineM	INFO	Train Epoch: 109 [79%]
2023-02-06 12:42:30,183	9nineM	INFO	[2.2614662647247314, 2.6110925674438477, 7.116613388061523, 22.354225158691406, 1.7279560565948486, 1.4162933826446533, 92800, 0.0001970714679845701]
2023-02-06 12:43:03,633	9nineM	INFO	Saving model and optimizer state at iteration 109 to ./logs\9nineM\G_92800.pth
2023-02-06 12:43:04,517	9nineM	INFO	Saving model and optimizer state at iteration 109 to ./logs\9nineM\D_92800.pth
2023-02-06 12:45:34,237	9nineM	INFO	====> Epoch: 109
2023-02-06 12:46:24,617	9nineM	INFO	Train Epoch: 110 [3%]
2023-02-06 12:46:24,617	9nineM	INFO	[2.337944507598877, 2.3767123222351074, 5.4418044090271, 19.818981170654297, 1.6453347206115723, 1.761839747428894, 93000, 0.000197046834051072]
2023-02-06 12:49:11,570	9nineM	INFO	Train Epoch: 110 [26%]
2023-02-06 12:49:11,570	9nineM	INFO	[2.3932392597198486, 2.3815081119537354, 5.581759452819824, 20.538192749023438, 1.703857421875, 1.7869685888290405, 93200, 0.000197046834051072]
2023-02-06 12:49:44,055	9nineM	INFO	Saving model and optimizer state at iteration 110 to ./logs\9nineM\G_93200.pth
2023-02-06 12:49:44,781	9nineM	INFO	Saving model and optimizer state at iteration 110 to ./logs\9nineM\D_93200.pth
2023-02-06 12:52:32,172	9nineM	INFO	Train Epoch: 110 [50%]
2023-02-06 12:52:32,173	9nineM	INFO	[2.3217198848724365, 2.69116473197937, 5.505145072937012, 21.991470336914062, 1.768148422241211, 1.7189995050430298, 93400, 0.000197046834051072]
2023-02-06 12:55:21,886	9nineM	INFO	Train Epoch: 110 [73%]
2023-02-06 12:55:21,887	9nineM	INFO	[2.1904287338256836, 2.523667097091675, 6.984142303466797, 22.651687622070312, 1.6384049654006958, 1.5759012699127197, 93600, 0.000197046834051072]
2023-02-06 12:55:56,524	9nineM	INFO	Saving model and optimizer state at iteration 110 to ./logs\9nineM\G_93600.pth
2023-02-06 12:55:57,264	9nineM	INFO	Saving model and optimizer state at iteration 110 to ./logs\9nineM\D_93600.pth
2023-02-06 12:58:45,262	9nineM	INFO	Train Epoch: 110 [96%]
2023-02-06 12:58:45,262	9nineM	INFO	[2.44917893409729, 2.738584518432617, 5.793365955352783, 22.983779907226562, 1.9288597106933594, 1.8642157316207886, 93800, 0.000197046834051072]
2023-02-06 12:59:10,786	9nineM	INFO	====> Epoch: 110
2023-02-06 13:02:05,416	9nineM	INFO	Train Epoch: 111 [20%]
2023-02-06 13:02:05,417	9nineM	INFO	[2.508176803588867, 2.2645320892333984, 5.212980270385742, 20.7646541595459, 1.8853695392608643, 1.7219749689102173, 94000, 0.00019702220319681561]
2023-02-06 13:02:37,861	9nineM	INFO	Saving model and optimizer state at iteration 111 to ./logs\9nineM\G_94000.pth
2023-02-06 13:02:38,555	9nineM	INFO	Saving model and optimizer state at iteration 111 to ./logs\9nineM\D_94000.pth
2023-02-06 13:05:26,720	9nineM	INFO	Train Epoch: 111 [43%]
2023-02-06 13:05:26,721	9nineM	INFO	[2.611619710922241, 2.063815116882324, 4.077986717224121, 18.16786766052246, 1.6656677722930908, 1.9092652797698975, 94200, 0.00019702220319681561]
2023-02-06 13:08:15,293	9nineM	INFO	Train Epoch: 111 [67%]
2023-02-06 13:08:15,294	9nineM	INFO	[2.3580873012542725, 2.61769700050354, 6.616842269897461, 22.40196990966797, 1.7497141361236572, 1.3369446992874146, 94400, 0.00019702220319681561]
2023-02-06 13:08:49,762	9nineM	INFO	Saving model and optimizer state at iteration 111 to ./logs\9nineM\G_94400.pth
2023-02-06 13:08:50,490	9nineM	INFO	Saving model and optimizer state at iteration 111 to ./logs\9nineM\D_94400.pth
2023-02-06 13:11:38,113	9nineM	INFO	Train Epoch: 111 [90%]
2023-02-06 13:11:38,113	9nineM	INFO	[2.413390636444092, 2.509127616882324, 4.37823486328125, 19.72787857055664, 1.701365351676941, 1.420450210571289, 94600, 0.00019702220319681561]
2023-02-06 13:12:47,771	9nineM	INFO	====> Epoch: 111
2023-02-06 13:14:56,897	9nineM	INFO	Train Epoch: 112 [14%]
2023-02-06 13:14:56,898	9nineM	INFO	[2.484596014022827, 2.232524871826172, 5.295563220977783, 19.982742309570312, 1.745281457901001, 1.5976684093475342, 94800, 0.000196997575421416]
2023-02-06 13:15:29,617	9nineM	INFO	Saving model and optimizer state at iteration 112 to ./logs\9nineM\G_94800.pth
2023-02-06 13:15:30,380	9nineM	INFO	Saving model and optimizer state at iteration 112 to ./logs\9nineM\D_94800.pth
2023-02-06 13:18:18,410	9nineM	INFO	Train Epoch: 112 [37%]
2023-02-06 13:18:18,411	9nineM	INFO	[2.456583023071289, 2.3107943534851074, 6.071109771728516, 22.921361923217773, 1.7969210147857666, 1.6460708379745483, 95000, 0.000196997575421416]
2023-02-06 13:21:05,725	9nineM	INFO	Train Epoch: 112 [61%]
2023-02-06 13:21:05,727	9nineM	INFO	[2.469888210296631, 2.4473538398742676, 5.119750022888184, 21.343137741088867, 1.671108603477478, 1.7484978437423706, 95200, 0.000196997575421416]
2023-02-06 13:21:39,301	9nineM	INFO	Saving model and optimizer state at iteration 112 to ./logs\9nineM\G_95200.pth
2023-02-06 13:21:40,111	9nineM	INFO	Saving model and optimizer state at iteration 112 to ./logs\9nineM\D_95200.pth
2023-02-06 13:24:25,441	9nineM	INFO	Train Epoch: 112 [84%]
2023-02-06 13:24:25,442	9nineM	INFO	[2.55717396736145, 2.1455161571502686, 5.304982662200928, 21.301620483398438, 1.604736089706421, 1.5033036470413208, 95400, 0.000196997575421416]
2023-02-06 13:26:17,275	9nineM	INFO	====> Epoch: 112
2023-02-06 13:27:38,968	9nineM	INFO	Train Epoch: 113 [8%]
2023-02-06 13:27:38,969	9nineM	INFO	[2.587958335876465, 1.9178141355514526, 3.5232930183410645, 16.94198989868164, 1.8393373489379883, 1.5986642837524414, 95600, 0.00019697295072448832]
2023-02-06 13:28:09,748	9nineM	INFO	Saving model and optimizer state at iteration 113 to ./logs\9nineM\G_95600.pth
2023-02-06 13:28:10,541	9nineM	INFO	Saving model and optimizer state at iteration 113 to ./logs\9nineM\D_95600.pth
2023-02-06 13:30:56,682	9nineM	INFO	Train Epoch: 113 [31%]
2023-02-06 13:30:56,682	9nineM	INFO	[2.498879909515381, 2.2045531272888184, 6.230116367340088, 22.36961555480957, 1.9318259954452515, 1.512890338897705, 95800, 0.00019697295072448832]
2023-02-06 13:33:43,018	9nineM	INFO	Train Epoch: 113 [54%]
2023-02-06 13:33:43,018	9nineM	INFO	[2.413757801055908, 2.5063464641571045, 5.826871395111084, 22.346698760986328, 1.5606420040130615, 1.8357735872268677, 96000, 0.00019697295072448832]
2023-02-06 13:34:15,067	9nineM	INFO	Saving model and optimizer state at iteration 113 to ./logs\9nineM\G_96000.pth
2023-02-06 13:34:15,788	9nineM	INFO	Saving model and optimizer state at iteration 113 to ./logs\9nineM\D_96000.pth
2023-02-06 13:36:59,900	9nineM	INFO	Train Epoch: 113 [78%]
2023-02-06 13:36:59,900	9nineM	INFO	[2.3261818885803223, 2.487793207168579, 7.112005710601807, 23.60846519470215, 1.6689367294311523, 1.6204299926757812, 96200, 0.00019697295072448832]
2023-02-06 13:39:35,420	9nineM	INFO	====> Epoch: 113
2023-02-06 13:40:14,850	9nineM	INFO	Train Epoch: 114 [1%]
2023-02-06 13:40:14,851	9nineM	INFO	[2.3594369888305664, 2.57433819770813, 5.664788722991943, 22.25078582763672, 1.9012060165405273, 1.2977750301361084, 96400, 0.00019694832910564775]
2023-02-06 13:40:45,516	9nineM	INFO	Saving model and optimizer state at iteration 114 to ./logs\9nineM\G_96400.pth
2023-02-06 13:40:46,209	9nineM	INFO	Saving model and optimizer state at iteration 114 to ./logs\9nineM\D_96400.pth
2023-02-06 13:43:32,605	9nineM	INFO	Train Epoch: 114 [25%]
2023-02-06 13:43:32,606	9nineM	INFO	[2.386523962020874, 2.780449628829956, 7.271634101867676, 24.21062660217285, 1.8169474601745605, 1.6657459735870361, 96600, 0.00019694832910564775]
2023-02-06 13:46:17,214	9nineM	INFO	Train Epoch: 114 [48%]
2023-02-06 13:46:17,215	9nineM	INFO	[2.5572080612182617, 2.2631192207336426, 5.437740802764893, 22.049312591552734, 1.6838626861572266, 1.687936782836914, 96800, 0.00019694832910564775]
2023-02-06 13:46:49,216	9nineM	INFO	Saving model and optimizer state at iteration 114 to ./logs\9nineM\G_96800.pth
2023-02-06 13:46:49,891	9nineM	INFO	Saving model and optimizer state at iteration 114 to ./logs\9nineM\D_96800.pth
2023-02-06 13:49:34,885	9nineM	INFO	Train Epoch: 114 [72%]
2023-02-06 13:49:34,886	9nineM	INFO	[2.509824752807617, 2.1153953075408936, 4.205113887786865, 18.1639404296875, 1.7349073886871338, 1.8490338325500488, 97000, 0.00019694832910564775]
2023-02-06 13:52:19,032	9nineM	INFO	Train Epoch: 114 [95%]
2023-02-06 13:52:19,032	9nineM	INFO	[2.557098388671875, 2.4876413345336914, 6.374693870544434, 23.068641662597656, 1.7634309530258179, 2.146819829940796, 97200, 0.00019694832910564775]
2023-02-06 13:52:50,423	9nineM	INFO	Saving model and optimizer state at iteration 114 to ./logs\9nineM\G_97200.pth
2023-02-06 13:52:51,119	9nineM	INFO	Saving model and optimizer state at iteration 114 to ./logs\9nineM\D_97200.pth
2023-02-06 13:53:25,705	9nineM	INFO	====> Epoch: 114
2023-02-06 13:56:05,556	9nineM	INFO	Train Epoch: 115 [19%]
2023-02-06 13:56:05,556	9nineM	INFO	[2.4791998863220215, 2.470241069793701, 5.086457252502441, 22.2614803314209, 1.7222354412078857, 1.655585765838623, 97400, 0.00019692371056450955]
2023-02-06 13:58:49,903	9nineM	INFO	Train Epoch: 115 [42%]
2023-02-06 13:58:49,904	9nineM	INFO	[2.315728187561035, 2.4930951595306396, 6.787493705749512, 21.897361755371094, 1.6553869247436523, 1.5442155599594116, 97600, 0.00019692371056450955]
2023-02-06 13:59:21,449	9nineM	INFO	Saving model and optimizer state at iteration 115 to ./logs\9nineM\G_97600.pth
2023-02-06 13:59:22,120	9nineM	INFO	Saving model and optimizer state at iteration 115 to ./logs\9nineM\D_97600.pth
2023-02-06 14:02:07,861	9nineM	INFO	Train Epoch: 115 [65%]
2023-02-06 14:02:07,862	9nineM	INFO	[2.396742582321167, 2.444382667541504, 5.668606281280518, 21.09869384765625, 1.8376652002334595, 2.2215919494628906, 97800, 0.00019692371056450955]
2023-02-06 14:04:53,754	9nineM	INFO	Train Epoch: 115 [89%]
2023-02-06 14:04:53,754	9nineM	INFO	[2.4273695945739746, 2.435178279876709, 5.798398494720459, 22.221467971801758, 1.5377154350280762, 1.521401047706604, 98000, 0.00019692371056450955]
2023-02-06 14:05:25,646	9nineM	INFO	Saving model and optimizer state at iteration 115 to ./logs\9nineM\G_98000.pth
2023-02-06 14:05:26,321	9nineM	INFO	Saving model and optimizer state at iteration 115 to ./logs\9nineM\D_98000.pth
2023-02-06 14:06:44,849	9nineM	INFO	====> Epoch: 115
2023-02-06 14:08:39,868	9nineM	INFO	Train Epoch: 116 [12%]
2023-02-06 14:08:39,869	9nineM	INFO	[2.7019729614257812, 2.1025826930999756, 3.5376508235931396, 18.070817947387695, 1.7493133544921875, 1.4884207248687744, 98200, 0.000196899095100689]
2023-02-06 14:11:25,999	9nineM	INFO	Train Epoch: 116 [36%]
2023-02-06 14:11:26,001	9nineM	INFO	[2.3110673427581787, 2.503537893295288, 6.2430267333984375, 22.04073143005371, 1.6430292129516602, 1.535827875137329, 98400, 0.000196899095100689]
2023-02-06 14:11:57,174	9nineM	INFO	Saving model and optimizer state at iteration 116 to ./logs\9nineM\G_98400.pth
2023-02-06 14:11:57,896	9nineM	INFO	Saving model and optimizer state at iteration 116 to ./logs\9nineM\D_98400.pth
2023-02-06 14:14:42,464	9nineM	INFO	Train Epoch: 116 [59%]
2023-02-06 14:14:42,465	9nineM	INFO	[2.4880621433258057, 2.404099941253662, 5.671602725982666, 21.134979248046875, 1.6529762744903564, 1.822348952293396, 98600, 0.000196899095100689]
2023-02-06 14:17:27,938	9nineM	INFO	Train Epoch: 116 [83%]
2023-02-06 14:17:27,938	9nineM	INFO	[2.503242254257202, 2.505859851837158, 5.302490234375, 20.080013275146484, 1.6597877740859985, 1.8725287914276123, 98800, 0.000196899095100689]
2023-02-06 14:17:59,644	9nineM	INFO	Saving model and optimizer state at iteration 116 to ./logs\9nineM\G_98800.pth
2023-02-06 14:18:00,367	9nineM	INFO	Saving model and optimizer state at iteration 116 to ./logs\9nineM\D_98800.pth
2023-02-06 14:20:02,752	9nineM	INFO	====> Epoch: 116
2023-02-06 14:21:15,069	9nineM	INFO	Train Epoch: 117 [6%]
2023-02-06 14:21:15,069	9nineM	INFO	[2.4922256469726562, 2.3742361068725586, 5.965278625488281, 21.643754959106445, 1.6999168395996094, 1.4700614213943481, 99000, 0.0001968744827138014]
2023-02-06 14:23:59,952	9nineM	INFO	Train Epoch: 117 [30%]
2023-02-06 14:23:59,953	9nineM	INFO	[2.36883544921875, 2.564002513885498, 5.826452732086182, 21.186851501464844, 1.6937975883483887, 1.5655131340026855, 99200, 0.0001968744827138014]
2023-02-06 14:24:31,005	9nineM	INFO	Saving model and optimizer state at iteration 117 to ./logs\9nineM\G_99200.pth
2023-02-06 14:24:31,700	9nineM	INFO	Saving model and optimizer state at iteration 117 to ./logs\9nineM\D_99200.pth
2023-02-06 14:27:16,673	9nineM	INFO	Train Epoch: 117 [53%]
2023-02-06 14:27:16,673	9nineM	INFO	[2.366628408432007, 2.5843231678009033, 5.344743728637695, 20.844276428222656, 1.721157193183899, 1.6528679132461548, 99400, 0.0001968744827138014]
2023-02-06 14:30:02,394	9nineM	INFO	Train Epoch: 117 [76%]
2023-02-06 14:30:02,395	9nineM	INFO	[2.2989799976348877, 2.538928985595703, 6.5035834312438965, 21.046674728393555, 1.7636724710464478, 1.4543215036392212, 99600, 0.0001968744827138014]
2023-02-06 14:30:34,651	9nineM	INFO	Saving model and optimizer state at iteration 117 to ./logs\9nineM\G_99600.pth
2023-02-06 14:30:35,349	9nineM	INFO	Saving model and optimizer state at iteration 117 to ./logs\9nineM\D_99600.pth
2023-02-06 14:33:21,323	9nineM	INFO	Train Epoch: 117 [100%]
2023-02-06 14:33:21,323	9nineM	INFO	[2.1168360710144043, 2.7229878902435303, 6.997582912445068, 23.13353729248047, 1.692934513092041, 1.757822871208191, 99800, 0.0001968744827138014]
2023-02-06 14:33:22,488	9nineM	INFO	====> Epoch: 117
2023-02-06 14:36:37,198	9nineM	INFO	Train Epoch: 118 [23%]
2023-02-06 14:36:37,198	9nineM	INFO	[2.463253974914551, 2.4275407791137695, 6.569629192352295, 22.935827255249023, 1.9200811386108398, 1.3774988651275635, 100000, 0.00019684987340346216]
2023-02-06 14:37:08,509	9nineM	INFO	Saving model and optimizer state at iteration 118 to ./logs\9nineM\G_100000.pth
2023-02-06 14:37:09,182	9nineM	INFO	Saving model and optimizer state at iteration 118 to ./logs\9nineM\D_100000.pth
2023-02-06 14:39:54,174	9nineM	INFO	Train Epoch: 118 [47%]
2023-02-06 14:39:54,175	9nineM	INFO	[2.4459586143493652, 2.2267520427703857, 5.4457106590271, 19.94850730895996, 1.9416693449020386, 1.846510648727417, 100200, 0.00019684987340346216]
2023-02-06 14:42:38,436	9nineM	INFO	Train Epoch: 118 [70%]
2023-02-06 14:42:38,437	9nineM	INFO	[2.0921056270599365, 2.9189417362213135, 7.457575798034668, 22.23969078063965, 1.8530688285827637, 1.4119536876678467, 100400, 0.00019684987340346216]
2023-02-06 14:43:10,184	9nineM	INFO	Saving model and optimizer state at iteration 118 to ./logs\9nineM\G_100400.pth
2023-02-06 14:43:10,874	9nineM	INFO	Saving model and optimizer state at iteration 118 to ./logs\9nineM\D_100400.pth
2023-02-06 14:45:56,413	9nineM	INFO	Train Epoch: 118 [94%]
2023-02-06 14:45:56,414	9nineM	INFO	[2.5850701332092285, 2.1893467903137207, 4.486823081970215, 19.829696655273438, 1.7508349418640137, 1.3020449876785278, 100600, 0.00019684987340346216]
2023-02-06 14:46:41,157	9nineM	INFO	====> Epoch: 118
2023-02-06 14:49:12,134	9nineM	INFO	Train Epoch: 119 [17%]
2023-02-06 14:49:12,134	9nineM	INFO	[2.463219165802002, 2.3701207637786865, 4.950770378112793, 19.350027084350586, 1.7054181098937988, 1.643091082572937, 100800, 0.00019682526716928672]
2023-02-06 14:49:44,155	9nineM	INFO	Saving model and optimizer state at iteration 119 to ./logs\9nineM\G_100800.pth
2023-02-06 14:49:44,866	9nineM	INFO	Saving model and optimizer state at iteration 119 to ./logs\9nineM\D_100800.pth
2023-02-06 14:52:31,408	9nineM	INFO	Train Epoch: 119 [41%]
2023-02-06 14:52:31,409	9nineM	INFO	[2.4125354290008545, 2.588454484939575, 5.436824798583984, 22.007740020751953, 1.7436957359313965, 1.6960844993591309, 101000, 0.00019682526716928672]
2023-02-06 14:55:15,157	9nineM	INFO	Train Epoch: 119 [64%]
2023-02-06 14:55:15,157	9nineM	INFO	[2.3535709381103516, 2.5076091289520264, 5.693776607513428, 19.578813552856445, 1.7230958938598633, 1.789415955543518, 101200, 0.00019682526716928672]
2023-02-06 14:55:46,342	9nineM	INFO	Saving model and optimizer state at iteration 119 to ./logs\9nineM\G_101200.pth
2023-02-06 14:55:47,136	9nineM	INFO	Saving model and optimizer state at iteration 119 to ./logs\9nineM\D_101200.pth
2023-02-06 14:58:31,073	9nineM	INFO	Train Epoch: 119 [87%]
2023-02-06 14:58:31,074	9nineM	INFO	[2.305410385131836, 2.6288323402404785, 6.146034240722656, 23.32713508605957, 1.765282154083252, 1.5977996587753296, 101400, 0.00019682526716928672]
2023-02-06 15:00:00,036	9nineM	INFO	====> Epoch: 119
2023-02-06 15:01:46,563	9nineM	INFO	Train Epoch: 120 [11%]
2023-02-06 15:01:46,564	9nineM	INFO	[2.2018096446990967, 2.7710883617401123, 7.08325719833374, 22.080549240112305, 1.9377415180206299, 1.6101778745651245, 101600, 0.00019680066401089056]
2023-02-06 15:02:18,483	9nineM	INFO	Saving model and optimizer state at iteration 120 to ./logs\9nineM\G_101600.pth
2023-02-06 15:02:19,174	9nineM	INFO	Saving model and optimizer state at iteration 120 to ./logs\9nineM\D_101600.pth
2023-02-06 15:05:03,431	9nineM	INFO	Train Epoch: 120 [34%]
2023-02-06 15:05:03,432	9nineM	INFO	[2.2975335121154785, 2.515549421310425, 6.2778425216674805, 22.98143196105957, 1.5956683158874512, 1.819651484489441, 101800, 0.00019680066401089056]
2023-02-06 15:07:51,652	9nineM	INFO	Train Epoch: 120 [58%]
2023-02-06 15:07:51,652	9nineM	INFO	[2.500098466873169, 2.4463696479797363, 5.057762145996094, 19.23154640197754, 1.7394850254058838, 1.7072340250015259, 102000, 0.00019680066401089056]
2023-02-06 15:08:24,001	9nineM	INFO	Saving model and optimizer state at iteration 120 to ./logs\9nineM\G_102000.pth
2023-02-06 15:08:24,697	9nineM	INFO	Saving model and optimizer state at iteration 120 to ./logs\9nineM\D_102000.pth
2023-02-06 15:11:08,275	9nineM	INFO	Train Epoch: 120 [81%]
2023-02-06 15:11:08,276	9nineM	INFO	[2.571516990661621, 2.3051207065582275, 3.9737179279327393, 19.891653060913086, 1.8753881454467773, 1.9612761735916138, 102200, 0.00019680066401089056]
2023-02-06 15:13:20,459	9nineM	INFO	====> Epoch: 120
2023-02-06 15:14:23,344	9nineM	INFO	Train Epoch: 121 [5%]
2023-02-06 15:14:23,345	9nineM	INFO	[2.510283946990967, 2.2863705158233643, 4.1958327293396, 19.206239700317383, 1.6095335483551025, 1.7505130767822266, 102400, 0.00019677606392788917]
2023-02-06 15:14:54,450	9nineM	INFO	Saving model and optimizer state at iteration 121 to ./logs\9nineM\G_102400.pth
2023-02-06 15:14:55,142	9nineM	INFO	Saving model and optimizer state at iteration 121 to ./logs\9nineM\D_102400.pth
2023-02-06 15:17:39,837	9nineM	INFO	Train Epoch: 121 [28%]
2023-02-06 15:17:39,837	9nineM	INFO	[2.541640043258667, 2.1485772132873535, 4.516676425933838, 20.732175827026367, 1.6872812509536743, 1.5659551620483398, 102600, 0.00019677606392788917]
2023-02-06 15:20:24,949	9nineM	INFO	Train Epoch: 121 [52%]
2023-02-06 15:20:24,949	9nineM	INFO	[2.328838348388672, 2.1609835624694824, 6.217496395111084, 20.118305206298828, 1.651740550994873, 1.891235113143921, 102800, 0.00019677606392788917]
2023-02-06 15:20:57,629	9nineM	INFO	Saving model and optimizer state at iteration 121 to ./logs\9nineM\G_102800.pth
2023-02-06 15:20:58,321	9nineM	INFO	Saving model and optimizer state at iteration 121 to ./logs\9nineM\D_102800.pth
2023-02-06 15:23:43,852	9nineM	INFO	Train Epoch: 121 [75%]
2023-02-06 15:23:43,853	9nineM	INFO	[2.2651047706604004, 2.775912284851074, 5.114157676696777, 20.266437530517578, 1.821028709411621, 1.757179617881775, 103000, 0.00019677606392788917]
2023-02-06 15:26:30,090	9nineM	INFO	Train Epoch: 121 [98%]
2023-02-06 15:26:30,090	9nineM	INFO	[2.5284314155578613, 2.1871793270111084, 5.4745073318481445, 19.901260375976562, 1.8009440898895264, 1.846165418624878, 103200, 0.00019677606392788917]
2023-02-06 15:27:02,475	9nineM	INFO	Saving model and optimizer state at iteration 121 to ./logs\9nineM\G_103200.pth
2023-02-06 15:27:03,194	9nineM	INFO	Saving model and optimizer state at iteration 121 to ./logs\9nineM\D_103200.pth
2023-02-06 15:27:14,424	9nineM	INFO	====> Epoch: 121
2023-02-06 15:30:18,024	9nineM	INFO	Train Epoch: 122 [22%]
2023-02-06 15:30:18,025	9nineM	INFO	[2.3980889320373535, 2.2477893829345703, 5.920403957366943, 21.125410079956055, 1.651360034942627, 1.4833674430847168, 103400, 0.00019675146691989817]
2023-02-06 15:33:03,224	9nineM	INFO	Train Epoch: 122 [45%]
2023-02-06 15:33:03,224	9nineM	INFO	[2.30232572555542, 2.4761180877685547, 6.809429168701172, 24.03131103515625, 1.5712530612945557, 1.9463590383529663, 103600, 0.00019675146691989817]
2023-02-06 15:33:34,309	9nineM	INFO	Saving model and optimizer state at iteration 122 to ./logs\9nineM\G_103600.pth
2023-02-06 15:33:34,996	9nineM	INFO	Saving model and optimizer state at iteration 122 to ./logs\9nineM\D_103600.pth
2023-02-06 15:36:21,012	9nineM	INFO	Train Epoch: 122 [69%]
2023-02-06 15:36:21,013	9nineM	INFO	[2.5232338905334473, 2.344912528991699, 4.960516452789307, 21.083236694335938, 1.7441201210021973, 1.6607543230056763, 103800, 0.00019675146691989817]
2023-02-06 15:39:05,829	9nineM	INFO	Train Epoch: 122 [92%]
2023-02-06 15:39:05,829	9nineM	INFO	[2.47275710105896, 2.1884095668792725, 5.5966010093688965, 21.980180740356445, 1.6928645372390747, 2.009143352508545, 104000, 0.00019675146691989817]
2023-02-06 15:39:37,939	9nineM	INFO	Saving model and optimizer state at iteration 122 to ./logs\9nineM\G_104000.pth
2023-02-06 15:39:38,714	9nineM	INFO	Saving model and optimizer state at iteration 122 to ./logs\9nineM\D_104000.pth
2023-02-06 15:40:33,552	9nineM	INFO	====> Epoch: 122
2023-02-06 15:42:55,043	9nineM	INFO	Train Epoch: 123 [16%]
2023-02-06 15:42:55,044	9nineM	INFO	[2.498145580291748, 2.2360188961029053, 5.111078262329102, 19.09475326538086, 1.7608081102371216, 1.4617615938186646, 104200, 0.00019672687298653317]
2023-02-06 15:45:40,140	9nineM	INFO	Train Epoch: 123 [39%]
2023-02-06 15:45:40,141	9nineM	INFO	[2.4925827980041504, 2.1025991439819336, 4.783213138580322, 19.508392333984375, 1.7997462749481201, 1.593095302581787, 104400, 0.00019672687298653317]
2023-02-06 15:46:11,404	9nineM	INFO	Saving model and optimizer state at iteration 123 to ./logs\9nineM\G_104400.pth
2023-02-06 15:46:12,095	9nineM	INFO	Saving model and optimizer state at iteration 123 to ./logs\9nineM\D_104400.pth
2023-02-06 15:48:57,344	9nineM	INFO	Train Epoch: 123 [63%]
2023-02-06 15:48:57,345	9nineM	INFO	[2.4662418365478516, 2.7075507640838623, 6.420268535614014, 22.104938507080078, 1.8007514476776123, 1.8012120723724365, 104600, 0.00019672687298653317]
2023-02-06 15:51:42,027	9nineM	INFO	Train Epoch: 123 [86%]
2023-02-06 15:51:42,028	9nineM	INFO	[2.616326093673706, 2.269937038421631, 4.204921722412109, 20.067710876464844, 1.6697479486465454, 1.74994957447052, 104800, 0.00019672687298653317]
2023-02-06 15:52:13,001	9nineM	INFO	Saving model and optimizer state at iteration 123 to ./logs\9nineM\G_104800.pth
2023-02-06 15:52:13,679	9nineM	INFO	Saving model and optimizer state at iteration 123 to ./logs\9nineM\D_104800.pth
2023-02-06 15:53:51,452	9nineM	INFO	====> Epoch: 123
2023-02-06 15:55:28,143	9nineM	INFO	Train Epoch: 124 [9%]
2023-02-06 15:55:28,143	9nineM	INFO	[2.438673257827759, 2.386467695236206, 6.2910895347595215, 22.673343658447266, 1.7006206512451172, 1.5440673828125, 105000, 0.00019670228212740986]
2023-02-06 15:58:12,658	9nineM	INFO	Train Epoch: 124 [33%]
2023-02-06 15:58:12,659	9nineM	INFO	[2.281498670578003, 2.406327724456787, 6.589284420013428, 22.119091033935547, 1.9388227462768555, 1.598183274269104, 105200, 0.00019670228212740986]
2023-02-06 15:58:44,440	9nineM	INFO	Saving model and optimizer state at iteration 124 to ./logs\9nineM\G_105200.pth
2023-02-06 15:58:45,132	9nineM	INFO	Saving model and optimizer state at iteration 124 to ./logs\9nineM\D_105200.pth
2023-02-06 16:01:30,510	9nineM	INFO	Train Epoch: 124 [56%]
2023-02-06 16:01:30,511	9nineM	INFO	[2.3354380130767822, 2.402249336242676, 7.290963172912598, 23.93175506591797, 1.6598782539367676, 1.8917102813720703, 105400, 0.00019670228212740986]
2023-02-06 16:04:16,120	9nineM	INFO	Train Epoch: 124 [80%]
2023-02-06 16:04:16,121	9nineM	INFO	[2.357271432876587, 2.5641093254089355, 6.540933132171631, 23.41145133972168, 1.8118276596069336, 1.4825334548950195, 105600, 0.00019670228212740986]
2023-02-06 16:04:47,242	9nineM	INFO	Saving model and optimizer state at iteration 124 to ./logs\9nineM\G_105600.pth
2023-02-06 16:04:47,923	9nineM	INFO	Saving model and optimizer state at iteration 124 to ./logs\9nineM\D_105600.pth
2023-02-06 16:07:10,698	9nineM	INFO	====> Epoch: 124
2023-02-06 16:08:03,503	9nineM	INFO	Train Epoch: 125 [3%]
2023-02-06 16:08:03,503	9nineM	INFO	[2.448438882827759, 2.445228099822998, 5.618696212768555, 20.60164451599121, 1.66410231590271, 1.615474820137024, 105800, 0.00019667769434214392]
2023-02-06 16:10:49,168	9nineM	INFO	Train Epoch: 125 [27%]
2023-02-06 16:10:49,168	9nineM	INFO	[2.325075626373291, 2.5221643447875977, 5.33622932434082, 20.46728515625, 1.6575069427490234, 1.6003532409667969, 106000, 0.00019667769434214392]
2023-02-06 16:11:21,217	9nineM	INFO	Saving model and optimizer state at iteration 125 to ./logs\9nineM\G_106000.pth
2023-02-06 16:11:21,902	9nineM	INFO	Saving model and optimizer state at iteration 125 to ./logs\9nineM\D_106000.pth
2023-02-06 16:14:07,608	9nineM	INFO	Train Epoch: 125 [50%]
2023-02-06 16:14:07,609	9nineM	INFO	[2.4673702716827393, 2.565077066421509, 6.060758590698242, 23.33299446105957, 1.8389701843261719, 1.6925863027572632, 106200, 0.00019667769434214392]
2023-02-06 16:16:53,934	9nineM	INFO	Train Epoch: 125 [74%]
2023-02-06 16:16:53,934	9nineM	INFO	[2.4451231956481934, 2.3460519313812256, 4.507089138031006, 17.921092987060547, 1.7477185726165771, 1.6921159029006958, 106400, 0.00019667769434214392]
2023-02-06 16:17:26,437	9nineM	INFO	Saving model and optimizer state at iteration 125 to ./logs\9nineM\G_106400.pth
2023-02-06 16:17:27,130	9nineM	INFO	Saving model and optimizer state at iteration 125 to ./logs\9nineM\D_106400.pth
2023-02-06 16:20:12,115	9nineM	INFO	Train Epoch: 125 [97%]
2023-02-06 16:20:12,115	9nineM	INFO	[2.3526041507720947, 2.144291639328003, 5.205575466156006, 19.205556869506836, 1.7281032800674438, 1.7087838649749756, 106600, 0.00019667769434214392]
2023-02-06 16:20:33,330	9nineM	INFO	====> Epoch: 125
2023-02-06 16:23:29,219	9nineM	INFO	Train Epoch: 126 [21%]
2023-02-06 16:23:29,219	9nineM	INFO	[2.557781457901001, 2.014836311340332, 4.775179862976074, 17.935400009155273, 1.715360164642334, 1.7885620594024658, 106800, 0.00019665310963035113]
2023-02-06 16:24:00,707	9nineM	INFO	Saving model and optimizer state at iteration 126 to ./logs\9nineM\G_106800.pth
2023-02-06 16:24:01,491	9nineM	INFO	Saving model and optimizer state at iteration 126 to ./logs\9nineM\D_106800.pth
2023-02-06 16:26:46,610	9nineM	INFO	Train Epoch: 126 [44%]
2023-02-06 16:26:46,610	9nineM	INFO	[2.5940823554992676, 2.119807720184326, 5.177199840545654, 22.355192184448242, 1.7283027172088623, 2.107990026473999, 107000, 0.00019665310963035113]
2023-02-06 16:29:31,484	9nineM	INFO	Train Epoch: 126 [67%]
2023-02-06 16:29:31,485	9nineM	INFO	[2.445890426635742, 2.2680559158325195, 5.12460470199585, 19.459461212158203, 1.7874096632003784, 1.5999054908752441, 107200, 0.00019665310963035113]
2023-02-06 16:30:03,402	9nineM	INFO	Saving model and optimizer state at iteration 126 to ./logs\9nineM\G_107200.pth
2023-02-06 16:30:04,094	9nineM	INFO	Saving model and optimizer state at iteration 126 to ./logs\9nineM\D_107200.pth
2023-02-06 16:32:49,551	9nineM	INFO	Train Epoch: 126 [91%]
2023-02-06 16:32:49,552	9nineM	INFO	[2.4641480445861816, 2.220811605453491, 5.251368045806885, 20.558815002441406, 1.601214051246643, 1.5639407634735107, 107400, 0.00019665310963035113]
2023-02-06 16:33:54,242	9nineM	INFO	====> Epoch: 126
2023-02-06 16:36:05,336	9nineM	INFO	Train Epoch: 127 [14%]
2023-02-06 16:36:05,337	9nineM	INFO	[1.9362939596176147, 3.120637893676758, 8.201459884643555, 25.22907066345215, 1.7208821773529053, 1.6794835329055786, 107600, 0.00019662852799164733]
2023-02-06 16:36:37,122	9nineM	INFO	Saving model and optimizer state at iteration 127 to ./logs\9nineM\G_107600.pth
2023-02-06 16:36:37,809	9nineM	INFO	Saving model and optimizer state at iteration 127 to ./logs\9nineM\D_107600.pth
2023-02-06 16:39:23,674	9nineM	INFO	Train Epoch: 127 [38%]
2023-02-06 16:39:23,675	9nineM	INFO	[2.6253600120544434, 2.2207937240600586, 5.682074546813965, 22.05364227294922, 1.7517821788787842, 1.6732871532440186, 107800, 0.00019662852799164733]
2023-02-06 16:42:08,220	9nineM	INFO	Train Epoch: 127 [61%]
2023-02-06 16:42:08,221	9nineM	INFO	[2.2905819416046143, 2.337268114089966, 6.093254089355469, 21.193681716918945, 1.7052127122879028, 1.2583754062652588, 108000, 0.00019662852799164733]
2023-02-06 16:42:39,774	9nineM	INFO	Saving model and optimizer state at iteration 127 to ./logs\9nineM\G_108000.pth
2023-02-06 16:42:40,471	9nineM	INFO	Saving model and optimizer state at iteration 127 to ./logs\9nineM\D_108000.pth
2023-02-06 16:45:26,187	9nineM	INFO	Train Epoch: 127 [85%]
2023-02-06 16:45:26,187	9nineM	INFO	[2.3456192016601562, 2.675173044204712, 7.440110683441162, 22.693382263183594, 1.7892179489135742, 1.4919089078903198, 108200, 0.00019662852799164733]
2023-02-06 16:47:14,916	9nineM	INFO	====> Epoch: 127
2023-02-06 16:48:43,682	9nineM	INFO	Train Epoch: 128 [8%]
2023-02-06 16:48:43,683	9nineM	INFO	[2.614778995513916, 2.1944501399993896, 4.002857208251953, 18.55801010131836, 1.7237768173217773, 1.4934300184249878, 108400, 0.00019660394942564837]
2023-02-06 16:49:15,370	9nineM	INFO	Saving model and optimizer state at iteration 128 to ./logs\9nineM\G_108400.pth
2023-02-06 16:49:16,058	9nineM	INFO	Saving model and optimizer state at iteration 128 to ./logs\9nineM\D_108400.pth
2023-02-06 16:52:01,377	9nineM	INFO	Train Epoch: 128 [32%]
2023-02-06 16:52:01,378	9nineM	INFO	[2.3290157318115234, 2.4676098823547363, 5.933804988861084, 21.577899932861328, 1.8265401124954224, 1.89597487449646, 108600, 0.00019660394942564837]
2023-02-06 16:54:47,001	9nineM	INFO	Train Epoch: 128 [55%]
2023-02-06 16:54:47,002	9nineM	INFO	[2.540832996368408, 2.246537208557129, 4.1585917472839355, 18.283985137939453, 1.700262188911438, 1.7168816328048706, 108800, 0.00019660394942564837]
2023-02-06 16:55:19,135	9nineM	INFO	Saving model and optimizer state at iteration 128 to ./logs\9nineM\G_108800.pth
2023-02-06 16:55:19,944	9nineM	INFO	Saving model and optimizer state at iteration 128 to ./logs\9nineM\D_108800.pth
2023-02-06 16:58:05,218	9nineM	INFO	Train Epoch: 128 [78%]
2023-02-06 16:58:05,218	9nineM	INFO	[2.343088150024414, 2.3620457649230957, 6.226370334625244, 21.107290267944336, 1.7152656316757202, 1.6601958274841309, 109000, 0.00019660394942564837]
2023-02-06 17:00:36,881	9nineM	INFO	====> Epoch: 128
2023-02-06 17:01:20,561	9nineM	INFO	Train Epoch: 129 [2%]
2023-02-06 17:01:20,561	9nineM	INFO	[2.516071319580078, 2.467613935470581, 4.537166118621826, 19.915565490722656, 1.7546274662017822, 1.5628968477249146, 109200, 0.00019657937393197016]
2023-02-06 17:01:52,074	9nineM	INFO	Saving model and optimizer state at iteration 129 to ./logs\9nineM\G_109200.pth
2023-02-06 17:01:52,769	9nineM	INFO	Saving model and optimizer state at iteration 129 to ./logs\9nineM\D_109200.pth
2023-02-06 17:04:38,635	9nineM	INFO	Train Epoch: 129 [25%]
2023-02-06 17:04:38,636	9nineM	INFO	[2.5061702728271484, 2.3820605278015137, 5.687960624694824, 21.9094295501709, 1.6847442388534546, 1.6685965061187744, 109400, 0.00019657937393197016]
2023-02-06 17:07:23,668	9nineM	INFO	Train Epoch: 129 [49%]
2023-02-06 17:07:23,669	9nineM	INFO	[2.2507522106170654, 2.5004069805145264, 7.823785305023193, 22.741954803466797, 1.8799254894256592, 1.5477299690246582, 109600, 0.00019657937393197016]
2023-02-06 17:07:55,442	9nineM	INFO	Saving model and optimizer state at iteration 129 to ./logs\9nineM\G_109600.pth
2023-02-06 17:07:56,139	9nineM	INFO	Saving model and optimizer state at iteration 129 to ./logs\9nineM\D_109600.pth
2023-02-06 17:10:41,579	9nineM	INFO	Train Epoch: 129 [72%]
2023-02-06 17:10:41,580	9nineM	INFO	[2.576294422149658, 2.466991901397705, 5.959920883178711, 19.854829788208008, 1.6014974117279053, 1.8656115531921387, 109800, 0.00019657937393197016]
2023-02-06 17:13:26,784	9nineM	INFO	Train Epoch: 129 [96%]
2023-02-06 17:13:26,784	9nineM	INFO	[2.1566967964172363, 2.796489953994751, 8.104927062988281, 25.290363311767578, 1.677327036857605, 1.7374876737594604, 110000, 0.00019657937393197016]
2023-02-06 17:13:59,809	9nineM	INFO	Saving model and optimizer state at iteration 129 to ./logs\9nineM\G_110000.pth
2023-02-06 17:14:00,551	9nineM	INFO	Saving model and optimizer state at iteration 129 to ./logs\9nineM\D_110000.pth
2023-02-06 17:14:32,121	9nineM	INFO	====> Epoch: 129
2023-02-06 17:17:17,773	9nineM	INFO	Train Epoch: 130 [19%]
2023-02-06 17:17:17,774	9nineM	INFO	[2.3088245391845703, 2.8287353515625, 6.850808143615723, 22.376914978027344, 1.720123529434204, 1.552506923675537, 110200, 0.00019655480151022865]
2023-02-06 17:20:04,569	9nineM	INFO	Train Epoch: 130 [43%]
2023-02-06 17:20:04,570	9nineM	INFO	[2.5641283988952637, 2.157201051712036, 6.115917682647705, 20.03248405456543, 1.7070456743240356, 1.195562720298767, 110400, 0.00019655480151022865]
2023-02-06 17:20:38,558	9nineM	INFO	Saving model and optimizer state at iteration 130 to ./logs\9nineM\G_110400.pth
2023-02-06 17:20:39,287	9nineM	INFO	Saving model and optimizer state at iteration 130 to ./logs\9nineM\D_110400.pth
2023-02-06 17:23:26,196	9nineM	INFO	Train Epoch: 130 [66%]
2023-02-06 17:23:26,196	9nineM	INFO	[2.4797720909118652, 2.3528714179992676, 6.306701183319092, 20.948516845703125, 1.6772387027740479, 1.6101850271224976, 110600, 0.00019655480151022865]
2023-02-06 17:26:11,355	9nineM	INFO	Train Epoch: 130 [89%]
2023-02-06 17:26:11,356	9nineM	INFO	[2.730914831161499, 1.92982816696167, 3.5945303440093994, 16.298423767089844, 1.6480116844177246, 1.6665343046188354, 110800, 0.00019655480151022865]
2023-02-06 17:26:43,293	9nineM	INFO	Saving model and optimizer state at iteration 130 to ./logs\9nineM\G_110800.pth
2023-02-06 17:26:44,109	9nineM	INFO	Saving model and optimizer state at iteration 130 to ./logs\9nineM\D_110800.pth
2023-02-06 17:27:58,664	9nineM	INFO	====> Epoch: 130
2023-02-06 17:30:00,534	9nineM	INFO	Train Epoch: 131 [13%]
2023-02-06 17:30:00,535	9nineM	INFO	[2.685152053833008, 2.0549843311309814, 5.298932075500488, 20.420000076293945, 1.5637484788894653, 1.7170839309692383, 111000, 0.00019653023216003985]
2023-02-06 17:32:47,125	9nineM	INFO	Train Epoch: 131 [36%]
2023-02-06 17:32:47,126	9nineM	INFO	[2.3477985858917236, 2.4249043464660645, 5.269962310791016, 20.208158493041992, 1.755613923072815, 1.6324561834335327, 111200, 0.00019653023216003985]
2023-02-06 17:33:18,966	9nineM	INFO	Saving model and optimizer state at iteration 131 to ./logs\9nineM\G_111200.pth
2023-02-06 17:33:19,669	9nineM	INFO	Saving model and optimizer state at iteration 131 to ./logs\9nineM\D_111200.pth
2023-02-06 17:36:06,284	9nineM	INFO	Train Epoch: 131 [60%]
2023-02-06 17:36:06,285	9nineM	INFO	[2.260867118835449, 2.4859883785247803, 6.8141188621521, 21.756410598754883, 1.6294654607772827, 1.3097648620605469, 111400, 0.00019653023216003985]
2023-02-06 17:38:51,314	9nineM	INFO	Train Epoch: 131 [83%]
2023-02-06 17:38:51,315	9nineM	INFO	[2.321812152862549, 2.5985615253448486, 5.669463157653809, 20.308734893798828, 1.6229777336120605, 1.3409274816513062, 111600, 0.00019653023216003985]
2023-02-06 17:39:23,773	9nineM	INFO	Saving model and optimizer state at iteration 131 to ./logs\9nineM\G_111600.pth
2023-02-06 17:39:24,562	9nineM	INFO	Saving model and optimizer state at iteration 131 to ./logs\9nineM\D_111600.pth
2023-02-06 17:41:23,863	9nineM	INFO	====> Epoch: 131
2023-02-06 17:42:41,670	9nineM	INFO	Train Epoch: 132 [7%]
2023-02-06 17:42:41,671	9nineM	INFO	[2.269984006881714, 2.3962604999542236, 6.287789821624756, 22.223419189453125, 1.7952971458435059, 1.4477769136428833, 111800, 0.00019650566588101984]
2023-02-06 17:45:27,035	9nineM	INFO	Train Epoch: 132 [30%]
2023-02-06 17:45:27,036	9nineM	INFO	[2.577596664428711, 2.2556490898132324, 4.243098735809326, 20.36516761779785, 1.7083340883255005, 1.563464641571045, 112000, 0.00019650566588101984]
2023-02-06 17:46:00,148	9nineM	INFO	Saving model and optimizer state at iteration 132 to ./logs\9nineM\G_112000.pth
2023-02-06 17:46:00,859	9nineM	INFO	Saving model and optimizer state at iteration 132 to ./logs\9nineM\D_112000.pth
2023-02-06 17:48:46,899	9nineM	INFO	Train Epoch: 132 [54%]
2023-02-06 17:48:46,900	9nineM	INFO	[2.3364675045013428, 2.4299540519714355, 5.966333866119385, 21.793182373046875, 1.6928566694259644, 1.7479687929153442, 112200, 0.00019650566588101984]
2023-02-06 17:51:32,487	9nineM	INFO	Train Epoch: 132 [77%]
2023-02-06 17:51:32,488	9nineM	INFO	[2.6574320793151855, 2.086085796356201, 5.10287618637085, 21.37195587158203, 1.6615488529205322, 1.5229588747024536, 112400, 0.00019650566588101984]
2023-02-06 17:52:06,033	9nineM	INFO	Saving model and optimizer state at iteration 132 to ./logs\9nineM\G_112400.pth
2023-02-06 17:52:06,732	9nineM	INFO	Saving model and optimizer state at iteration 132 to ./logs\9nineM\D_112400.pth
2023-02-06 17:54:50,218	9nineM	INFO	====> Epoch: 132
2023-02-06 17:55:25,129	9nineM	INFO	Train Epoch: 133 [0%]
2023-02-06 17:55:25,130	9nineM	INFO	[2.3558051586151123, 2.649467945098877, 6.2440876960754395, 21.53974723815918, 1.7715338468551636, 1.7623863220214844, 112600, 0.0001964811026727847]
2023-02-06 17:58:11,248	9nineM	INFO	Train Epoch: 133 [24%]
2023-02-06 17:58:11,248	9nineM	INFO	[2.2452285289764404, 2.6025023460388184, 5.581013202667236, 19.501935958862305, 1.7821968793869019, 1.6202852725982666, 112800, 0.0001964811026727847]
2023-02-06 17:58:43,256	9nineM	INFO	Saving model and optimizer state at iteration 133 to ./logs\9nineM\G_112800.pth
2023-02-06 17:58:43,945	9nineM	INFO	Saving model and optimizer state at iteration 133 to ./logs\9nineM\D_112800.pth
2023-02-06 18:01:31,218	9nineM	INFO	Train Epoch: 133 [47%]
2023-02-06 18:01:31,219	9nineM	INFO	[2.321185827255249, 2.5362143516540527, 5.924492359161377, 22.061859130859375, 1.688535451889038, 1.394166350364685, 113000, 0.0001964811026727847]
2023-02-06 18:04:17,458	9nineM	INFO	Train Epoch: 133 [71%]
2023-02-06 18:04:17,459	9nineM	INFO	[2.319377899169922, 2.3305535316467285, 6.212714195251465, 21.521169662475586, 1.711829662322998, 1.8327008485794067, 113200, 0.0001964811026727847]
2023-02-06 18:04:49,789	9nineM	INFO	Saving model and optimizer state at iteration 133 to ./logs\9nineM\G_113200.pth
2023-02-06 18:04:50,480	9nineM	INFO	Saving model and optimizer state at iteration 133 to ./logs\9nineM\D_113200.pth
2023-02-06 18:07:35,937	9nineM	INFO	Train Epoch: 133 [94%]
2023-02-06 18:07:35,938	9nineM	INFO	[2.408998727798462, 2.5829079151153564, 7.041913986206055, 23.381765365600586, 1.790878176689148, 1.6280030012130737, 113400, 0.0001964811026727847]
2023-02-06 18:08:16,834	9nineM	INFO	====> Epoch: 133
2023-02-06 18:10:51,925	9nineM	INFO	Train Epoch: 134 [18%]
2023-02-06 18:10:51,925	9nineM	INFO	[2.243528366088867, 2.692565679550171, 7.503571510314941, 22.869403839111328, 1.6828540563583374, 1.642391562461853, 113600, 0.00019645654253495058]
2023-02-06 18:11:24,191	9nineM	INFO	Saving model and optimizer state at iteration 134 to ./logs\9nineM\G_113600.pth
2023-02-06 18:11:24,885	9nineM	INFO	Saving model and optimizer state at iteration 134 to ./logs\9nineM\D_113600.pth
2023-02-06 18:14:12,477	9nineM	INFO	Train Epoch: 134 [41%]
2023-02-06 18:14:12,477	9nineM	INFO	[2.3350560665130615, 2.5503907203674316, 6.156712532043457, 22.925025939941406, 1.7280542850494385, 1.8451484441757202, 113800, 0.00019645654253495058]
2023-02-06 18:16:57,382	9nineM	INFO	Train Epoch: 134 [65%]
2023-02-06 18:16:57,382	9nineM	INFO	[2.29552960395813, 2.376685857772827, 6.592720985412598, 21.430940628051758, 1.8966145515441895, 1.5641173124313354, 114000, 0.00019645654253495058]
2023-02-06 18:17:31,183	9nineM	INFO	Saving model and optimizer state at iteration 134 to ./logs\9nineM\G_114000.pth
2023-02-06 18:17:31,902	9nineM	INFO	Saving model and optimizer state at iteration 134 to ./logs\9nineM\D_114000.pth
2023-02-06 18:20:19,220	9nineM	INFO	Train Epoch: 134 [88%]
2023-02-06 18:20:19,221	9nineM	INFO	[2.537724733352661, 2.1297531127929688, 4.756051063537598, 17.612483978271484, 1.6361194849014282, 1.7162665128707886, 114200, 0.00019645654253495058]
2023-02-06 18:21:44,252	9nineM	INFO	====> Epoch: 134
2023-02-06 18:23:37,755	9nineM	INFO	Train Epoch: 135 [11%]
2023-02-06 18:23:37,755	9nineM	INFO	[2.5274243354797363, 2.2241621017456055, 4.527782917022705, 19.2587890625, 1.734229564666748, 1.5080584287643433, 114400, 0.0001964319854671337]
2023-02-06 18:24:11,163	9nineM	INFO	Saving model and optimizer state at iteration 135 to ./logs\9nineM\G_114400.pth
2023-02-06 18:24:11,953	9nineM	INFO	Saving model and optimizer state at iteration 135 to ./logs\9nineM\D_114400.pth
2023-02-06 18:26:59,118	9nineM	INFO	Train Epoch: 135 [35%]
2023-02-06 18:26:59,118	9nineM	INFO	[2.228125810623169, 2.656797170639038, 7.3901801109313965, 23.070409774780273, 1.762709379196167, 1.3937914371490479, 114600, 0.0001964319854671337]
2023-02-06 18:29:44,905	9nineM	INFO	Train Epoch: 135 [58%]
2023-02-06 18:29:44,905	9nineM	INFO	[2.4320075511932373, 2.4277989864349365, 5.85286283493042, 21.0933780670166, 1.7470276355743408, 1.7924855947494507, 114800, 0.0001964319854671337]
2023-02-06 18:30:17,356	9nineM	INFO	Saving model and optimizer state at iteration 135 to ./logs\9nineM\G_114800.pth
2023-02-06 18:30:18,055	9nineM	INFO	Saving model and optimizer state at iteration 135 to ./logs\9nineM\D_114800.pth
2023-02-06 18:33:03,621	9nineM	INFO	Train Epoch: 135 [82%]
2023-02-06 18:33:03,622	9nineM	INFO	[2.143054962158203, 2.655668258666992, 6.541446208953857, 22.054094314575195, 1.766592264175415, 1.7490730285644531, 115000, 0.0001964319854671337]
2023-02-06 18:35:12,686	9nineM	INFO	====> Epoch: 135
2023-02-06 18:36:20,672	9nineM	INFO	Train Epoch: 136 [5%]
2023-02-06 18:36:20,673	9nineM	INFO	[2.2677929401397705, 2.3687334060668945, 6.2986249923706055, 20.939075469970703, 1.697746992111206, 1.8127354383468628, 115200, 0.0001964074314689503]
2023-02-06 18:36:53,092	9nineM	INFO	Saving model and optimizer state at iteration 136 to ./logs\9nineM\G_115200.pth
2023-02-06 18:36:53,898	9nineM	INFO	Saving model and optimizer state at iteration 136 to ./logs\9nineM\D_115200.pth
2023-02-06 18:39:41,740	9nineM	INFO	Train Epoch: 136 [29%]
2023-02-06 18:39:41,741	9nineM	INFO	[2.3394155502319336, 2.6773366928100586, 6.513527870178223, 22.537111282348633, 1.6556422710418701, 1.5885149240493774, 115400, 0.0001964074314689503]
2023-02-06 18:42:27,365	9nineM	INFO	Train Epoch: 136 [52%]
2023-02-06 18:42:27,365	9nineM	INFO	[2.4375386238098145, 2.6626136302948, 5.572325229644775, 19.88722038269043, 1.7356163263320923, 2.05466365814209, 115600, 0.0001964074314689503]
2023-02-06 18:42:59,269	9nineM	INFO	Saving model and optimizer state at iteration 136 to ./logs\9nineM\G_115600.pth
2023-02-06 18:42:59,970	9nineM	INFO	Saving model and optimizer state at iteration 136 to ./logs\9nineM\D_115600.pth
2023-02-06 18:45:45,968	9nineM	INFO	Train Epoch: 136 [76%]
2023-02-06 18:45:45,969	9nineM	INFO	[2.44460391998291, 2.4632773399353027, 5.772214889526367, 21.629426956176758, 1.7663202285766602, 2.0208678245544434, 115800, 0.0001964074314689503]
2023-02-06 18:48:30,844	9nineM	INFO	Train Epoch: 136 [99%]
2023-02-06 18:48:30,845	9nineM	INFO	[2.4162187576293945, 2.2298314571380615, 5.3683671951293945, 21.47169303894043, 1.6094458103179932, 1.774322748184204, 116000, 0.0001964074314689503]
2023-02-06 18:49:03,370	9nineM	INFO	Saving model and optimizer state at iteration 136 to ./logs\9nineM\G_116000.pth
2023-02-12 04:37:29,614	9nineM	INFO	{'train': {'log_interval': 200, 'eval_interval': 400, 'seed': 1234, 'epochs': 1000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 16, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/9nine_multi/filelists/MultiNoHaru_train.txt.cleaned', 'validation_files': 'filelists/9nine_multi/filelists/MultiNoHaru_valid.txt.cleaned', 'text_cleaners': ['japanese_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 5, 'cleaned_text': True}, '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': [8, 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}, 'model_dir': './logs\\9nineM', 'ckptG': None, 'ckptD': None}
2023-02-12 04:38:05,317	9nineM	INFO	Train Epoch: 1 [0%]
2023-02-12 04:38:05,318	9nineM	INFO	[6.0741496086120605, 4.674299240112305, 0.37357205152511597, 100.2466049194336, 1.9271368980407715, 206.81471252441406, 0, 0.0002]
2023-02-12 04:38:26,136	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\G_0.pth
2023-02-12 04:38:26,864	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\D_0.pth
2023-02-12 04:41:31,297	9nineM	INFO	Train Epoch: 1 [23%]
2023-02-12 04:41:31,298	9nineM	INFO	[1.8814308643341064, 3.0982019901275635, 5.636070251464844, 43.64947509765625, 1.9057422876358032, 1.7150471210479736, 200, 0.0002]
2023-02-12 04:44:25,929	9nineM	INFO	Train Epoch: 1 [47%]
2023-02-12 04:44:25,930	9nineM	INFO	[2.2280142307281494, 2.190523386001587, 3.9681339263916016, 37.336788177490234, 1.9838364124298096, 1.3402962684631348, 400, 0.0002]
2023-02-12 04:44:48,338	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\G_400.pth
2023-02-12 04:44:49,018	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\D_400.pth
2023-02-12 04:47:41,530	9nineM	INFO	Train Epoch: 1 [70%]
2023-02-12 04:47:41,530	9nineM	INFO	[2.1953139305114746, 2.7316408157348633, 4.507357597351074, 36.56730651855469, 2.1782724857330322, 1.5445265769958496, 600, 0.0002]
2023-02-12 04:50:29,804	9nineM	INFO	Train Epoch: 1 [94%]
2023-02-12 04:50:29,804	9nineM	INFO	[1.9672067165374756, 2.559593677520752, 4.635627746582031, 34.88198471069336, 2.085712432861328, 1.6550763845443726, 800, 0.0002]
2023-02-12 04:50:50,643	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\G_800.pth
2023-02-12 04:50:51,384	9nineM	INFO	Saving model and optimizer state at iteration 1 to ./logs\9nineM\D_800.pth
2023-02-12 04:51:35,762	9nineM	INFO	====> Epoch: 1
2023-02-12 04:53:58,110	9nineM	INFO	Train Epoch: 2 [17%]
2023-02-12 04:53:58,110	9nineM	INFO	[2.1823103427886963, 2.9389171600341797, 4.653263568878174, 33.464107513427734, 2.0744001865386963, 1.5382697582244873, 1000, 0.000199975]
2023-02-12 04:56:43,337	9nineM	INFO	Train Epoch: 2 [41%]
2023-02-12 04:56:43,337	9nineM	INFO	[2.1907596588134766, 2.2755777835845947, 4.492942810058594, 33.94969940185547, 2.1231160163879395, 1.3922680616378784, 1200, 0.000199975]
2023-02-12 04:57:03,865	9nineM	INFO	Saving model and optimizer state at iteration 2 to ./logs\9nineM\G_1200.pth
2023-02-12 04:57:04,477	9nineM	INFO	Saving model and optimizer state at iteration 2 to ./logs\9nineM\D_1200.pth
2023-02-12 04:59:49,597	9nineM	INFO	Train Epoch: 2 [64%]
2023-02-12 04:59:49,598	9nineM	INFO	[2.227170467376709, 2.6497111320495605, 4.81112003326416, 32.33095932006836, 1.9701876640319824, 1.3651307821273804, 1400, 0.000199975]
2023-02-12 05:02:37,286	9nineM	INFO	Train Epoch: 2 [88%]
2023-02-12 05:02:37,286	9nineM	INFO	[2.4975926876068115, 2.5202813148498535, 3.5076069831848145, 36.55912399291992, 2.0596163272857666, 1.4623568058013916, 1600, 0.000199975]
2023-02-12 05:02:57,631	9nineM	INFO	Saving model and optimizer state at iteration 2 to ./logs\9nineM\G_1600.pth
2023-02-12 05:02:58,242	9nineM	INFO	Saving model and optimizer state at iteration 2 to ./logs\9nineM\D_1600.pth
2023-02-12 05:04:25,186	9nineM	INFO	====> Epoch: 2
2023-02-12 05:06:03,591	9nineM	INFO	Train Epoch: 3 [11%]
2023-02-12 05:06:03,592	9nineM	INFO	[2.7553861141204834, 2.0805437564849854, 2.5315897464752197, 28.083301544189453, 2.1212515830993652, 1.276499629020691, 1800, 0.000199950003125]
2023-02-12 14:23:49,269	9nineM	INFO	Train Epoch: 3 [34%]
2023-02-12 14:23:49,279	9nineM	INFO	[2.103278160095215, 2.5340070724487305, 4.954019546508789, 36.43415832519531, 2.1033124923706055, 1.9096229076385498, 2000, 0.000199950003125]
2023-02-12 14:24:11,096	9nineM	INFO	Saving model and optimizer state at iteration 3 to ./logs\9nineM\G_2000.pth
2023-02-12 14:24:11,851	9nineM	INFO	Saving model and optimizer state at iteration 3 to ./logs\9nineM\D_2000.pth