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2023-02-22 14:12:56,950 32k INFO {'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 10000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 6, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 17920, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'use_sr': True, 'max_speclen': 384, 'port': '8001'}, 'data': {'training_files': 'filelists/train.txt', 'validation_files': 'filelists/val.txt', 'max_wav_value': 32768.0, 'sampling_rate': 32000, 'filter_length': 1280, 'hop_length': 320, 'win_length': 1280, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256, 'ssl_dim': 256, 'n_speakers': 2}, 'spk': {'saika': 0}, 'model_dir': './logs\\32k'}
2023-02-22 14:12:56,950 32k WARNING K:\AI\so-vits-svc-32k is not a git repository, therefore hash value comparison will be ignored.
2023-02-22 14:13:01,617 32k INFO Loaded checkpoint './logs\32k\G_0.pth' (iteration 1)
2023-02-22 14:13:02,013 32k INFO Loaded checkpoint './logs\32k\D_0.pth' (iteration 1)
2023-02-22 14:13:28,354 32k INFO Train Epoch: 1 [0%]
2023-02-22 14:13:28,355 32k INFO [3.187079668045044, 3.543747663497925, 12.749074935913086, 35.17381286621094, 6.83956241607666, 0, 0.0001]
2023-02-22 14:13:34,228 32k INFO Saving model and optimizer state at iteration 1 to ./logs\32k\G_0.pth
2023-02-22 14:13:52,172 32k INFO Saving model and optimizer state at iteration 1 to ./logs\32k\D_0.pth
2023-02-22 14:15:03,077 32k INFO ====> Epoch: 1
2023-02-22 14:16:31,043 32k INFO ====> Epoch: 2
2023-02-22 14:17:26,851 32k INFO Train Epoch: 3 [50%]
2023-02-22 14:17:26,851 32k INFO [2.488687515258789, 2.5710129737854004, 14.215274810791016, 26.32855796813965, 1.4047647714614868, 200, 9.99750015625e-05]
2023-02-22 14:17:59,730 32k INFO ====> Epoch: 3
2023-02-22 14:19:27,494 32k INFO ====> Epoch: 4
2023-02-22 14:20:55,315 32k INFO ====> Epoch: 5
2023-02-22 14:21:17,292 32k INFO Train Epoch: 6 [0%]
2023-02-22 14:21:17,292 32k INFO [2.2817749977111816, 2.477022171020508, 12.80789852142334, 22.15078353881836, 1.1265417337417603, 400, 9.993751562304699e-05]
2023-02-22 14:32:12,662 32k INFO {'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 10000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 5, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 17920, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'use_sr': True, 'max_speclen': 384, 'port': '8001'}, 'data': {'training_files': 'filelists/train.txt', 'validation_files': 'filelists/val.txt', 'max_wav_value': 32768.0, 'sampling_rate': 32000, 'filter_length': 1280, 'hop_length': 320, 'win_length': 1280, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256, 'ssl_dim': 256, 'n_speakers': 2}, 'spk': {'saika': 0}, 'model_dir': './logs\\32k'}
2023-02-22 14:32:12,663 32k WARNING K:\AI\so-vits-svc-32k is not a git repository, therefore hash value comparison will be ignored.
2023-02-22 14:32:17,462 32k INFO Loaded checkpoint './logs\32k\G_0.pth' (iteration 1)
2023-02-22 14:32:17,863 32k INFO Loaded checkpoint './logs\32k\D_0.pth' (iteration 1)
2023-02-22 14:32:43,402 32k INFO Train Epoch: 1 [0%]
2023-02-22 14:32:43,402 32k INFO [3.086385726928711, 3.1004512310028076, 11.565768241882324, 32.38859558105469, 5.992624759674072, 0, 0.0001]
2023-02-22 14:32:49,281 32k INFO Saving model and optimizer state at iteration 1 to ./logs\32k\G_0.pth
2023-02-22 14:33:08,839 32k INFO Saving model and optimizer state at iteration 1 to ./logs\32k\D_0.pth
2023-02-22 14:34:22,487 32k INFO ====> Epoch: 1
2023-02-22 14:35:53,637 32k INFO ====> Epoch: 2
2023-02-22 14:36:21,152 32k INFO Train Epoch: 3 [8%]
2023-02-22 14:36:21,152 32k INFO [2.3054869174957275, 2.327169418334961, 12.3760347366333, 22.735485076904297, 0.9988258481025696, 200, 9.99750015625e-05]
2023-02-22 14:37:24,967 32k INFO ====> Epoch: 3
2023-02-22 14:38:56,168 32k INFO ====> Epoch: 4
2023-02-22 14:39:29,664 32k INFO Train Epoch: 5 [17%]
2023-02-22 14:39:29,664 32k INFO [2.247507095336914, 2.4475936889648438, 12.479228019714355, 23.749866485595703, 1.3646601438522339, 400, 9.995000937421877e-05]
2023-02-22 14:40:27,690 32k INFO ====> Epoch: 5
2023-02-22 14:41:58,975 32k INFO ====> Epoch: 6
2023-02-22 14:42:38,309 32k INFO Train Epoch: 7 [25%]
2023-02-22 14:42:38,310 32k INFO [2.720693349838257, 2.3375821113586426, 9.826765060424805, 21.648380279541016, 0.9433642625808716, 600, 9.99250234335941e-05]
2023-02-22 14:43:30,606 32k INFO ====> Epoch: 7
2023-02-22 14:45:01,819 32k INFO ====> Epoch: 8
2023-02-22 14:45:47,085 32k INFO Train Epoch: 9 [33%]
2023-02-22 14:45:47,085 32k INFO [2.5194616317749023, 2.6869425773620605, 12.535841941833496, 22.44904327392578, 1.2266863584518433, 800, 9.990004373906418e-05]
2023-02-22 14:46:33,458 32k INFO ====> Epoch: 9
2023-02-22 14:48:04,723 32k INFO ====> Epoch: 10
2023-02-22 14:48:55,750 32k INFO Train Epoch: 11 [42%]
2023-02-22 14:48:55,750 32k INFO [2.049856424331665, 3.2148919105529785, 9.496326446533203, 15.099220275878906, 1.1717641353607178, 1000, 9.987507028906759e-05]
2023-02-22 14:49:00,183 32k INFO Saving model and optimizer state at iteration 11 to ./logs\32k\G_1000.pth
2023-02-22 14:49:19,296 32k INFO Saving model and optimizer state at iteration 11 to ./logs\32k\D_1000.pth
2023-02-22 14:50:03,757 32k INFO ====> Epoch: 11
2023-02-22 14:51:35,495 32k INFO ====> Epoch: 12
2023-02-22 14:52:32,553 32k INFO Train Epoch: 13 [50%]
2023-02-22 14:52:32,554 32k INFO [2.489741802215576, 2.4319345951080322, 11.793535232543945, 20.218076705932617, 0.7845316529273987, 1200, 9.98501030820433e-05]
2023-02-22 14:53:07,458 32k INFO ====> Epoch: 13
2023-02-22 14:54:39,323 32k INFO ====> Epoch: 14
2023-02-22 14:55:42,302 32k INFO Train Epoch: 15 [58%]
2023-02-22 14:55:42,302 32k INFO [2.609837055206299, 2.1415061950683594, 8.502999305725098, 19.083311080932617, 1.204352855682373, 1400, 9.982514211643064e-05]
2023-02-22 14:56:11,452 32k INFO ====> Epoch: 15
2023-02-22 14:57:43,335 32k INFO ====> Epoch: 16
2023-02-22 14:58:52,204 32k INFO Train Epoch: 17 [67%]
2023-02-22 14:58:52,205 32k INFO [2.5788638591766357, 2.1364264488220215, 7.731012344360352, 15.810824394226074, 1.110003113746643, 1600, 9.980018739066937e-05]
2023-02-22 14:59:15,498 32k INFO ====> Epoch: 17
2023-02-22 15:00:47,193 32k INFO ====> Epoch: 18
2023-02-22 15:02:01,857 32k INFO Train Epoch: 19 [75%]
2023-02-22 15:02:01,857 32k INFO [2.5087671279907227, 2.266523838043213, 9.564532279968262, 18.576448440551758, 0.7115161418914795, 1800, 9.977523890319963e-05]
2023-02-22 15:02:19,244 32k INFO ====> Epoch: 19
2023-02-22 15:03:51,055 32k INFO ====> Epoch: 20
2023-02-22 15:05:11,654 32k INFO Train Epoch: 21 [83%]
2023-02-22 15:05:11,655 32k INFO [2.3199269771575928, 2.477095603942871, 11.856741905212402, 20.60849952697754, 0.9765581488609314, 2000, 9.975029665246193e-05]
2023-02-22 15:05:16,169 32k INFO Saving model and optimizer state at iteration 21 to ./logs\32k\G_2000.pth
2023-02-22 15:05:35,247 32k INFO Saving model and optimizer state at iteration 21 to ./logs\32k\D_2000.pth
2023-02-22 15:05:50,320 32k INFO ====> Epoch: 21
2023-02-22 15:07:22,122 32k INFO ====> Epoch: 22
2023-02-22 15:08:48,724 32k INFO Train Epoch: 23 [92%]
2023-02-22 15:08:48,724 32k INFO [2.5126163959503174, 2.3070528507232666, 11.5335693359375, 21.152307510375977, 1.1387696266174316, 2200, 9.972536063689719e-05]
2023-02-22 15:08:54,325 32k INFO ====> Epoch: 23
2023-02-22 15:10:26,193 32k INFO ====> Epoch: 24
2023-02-22 15:11:58,042 32k INFO ====> Epoch: 25
2023-02-22 15:12:19,978 32k INFO Train Epoch: 26 [0%]
2023-02-22 15:12:19,978 32k INFO [2.566260814666748, 2.118185520172119, 8.801782608032227, 16.81813621520996, 0.8712365627288818, 2400, 9.968796830108985e-05]
2023-02-22 15:13:30,299 32k INFO ====> Epoch: 26
2023-02-22 15:15:02,065 32k INFO ====> Epoch: 27
2023-02-22 15:15:29,847 32k INFO Train Epoch: 28 [8%]
2023-02-22 15:15:29,847 32k INFO [2.5252060890197754, 2.0401153564453125, 10.247071266174316, 18.943756103515625, 1.3569800853729248, 2600, 9.966304786663908e-05]
2023-02-22 15:16:34,164 32k INFO ====> Epoch: 28
2023-02-22 15:18:06,132 32k INFO ====> Epoch: 29
2023-02-22 15:18:39,775 32k INFO Train Epoch: 30 [17%]
2023-02-22 15:18:39,775 32k INFO [2.5057239532470703, 2.326035976409912, 11.950654983520508, 22.501440048217773, 1.2382237911224365, 2800, 9.963813366190753e-05]
2023-02-22 15:19:38,222 32k INFO ====> Epoch: 30
2023-02-22 15:21:10,107 32k INFO ====> Epoch: 31
2023-02-22 15:21:49,589 32k INFO Train Epoch: 32 [25%]
2023-02-22 15:21:49,590 32k INFO [2.2636756896972656, 2.373335123062134, 11.810818672180176, 19.981029510498047, 0.858932614326477, 3000, 9.961322568533789e-05]
2023-02-22 15:21:54,053 32k INFO Saving model and optimizer state at iteration 32 to ./logs\32k\G_3000.pth
2023-02-22 15:22:11,823 32k INFO Saving model and optimizer state at iteration 32 to ./logs\32k\D_3000.pth
2023-02-22 15:23:07,665 32k INFO ====> Epoch: 32
2023-02-22 15:24:39,609 32k INFO ====> Epoch: 33
2023-02-22 15:25:25,049 32k INFO Train Epoch: 34 [33%]
2023-02-22 15:25:25,050 32k INFO [2.5494279861450195, 2.0830795764923096, 6.602403163909912, 10.558989524841309, 1.0258899927139282, 3200, 9.95883239353732e-05]
2023-02-22 15:26:11,828 32k INFO ====> Epoch: 34
2023-02-22 15:27:43,763 32k INFO ====> Epoch: 35
2023-02-22 15:28:35,139 32k INFO Train Epoch: 36 [42%]
2023-02-22 15:28:35,139 32k INFO [2.4735586643218994, 2.1442575454711914, 10.77430248260498, 18.345321655273438, 0.9167714715003967, 3400, 9.956342841045691e-05]
2023-02-22 15:29:16,168 32k INFO ====> Epoch: 36
2023-02-22 15:30:48,154 32k INFO ====> Epoch: 37
2023-02-22 15:31:45,388 32k INFO Train Epoch: 38 [50%]
2023-02-22 15:31:45,388 32k INFO [2.1438865661621094, 2.6590867042541504, 13.766039848327637, 20.467525482177734, 1.1156392097473145, 3600, 9.953853910903285e-05]
2023-02-22 15:32:20,434 32k INFO ====> Epoch: 38
2023-02-22 15:33:52,419 32k INFO ====> Epoch: 39
2023-02-22 15:34:55,633 32k INFO Train Epoch: 40 [58%]
2023-02-22 15:34:55,634 32k INFO [2.2264719009399414, 2.578108549118042, 13.543416023254395, 20.043352127075195, 1.2697389125823975, 3800, 9.951365602954526e-05]
2023-02-22 15:35:24,767 32k INFO ====> Epoch: 40
2023-02-22 15:36:56,696 32k INFO ====> Epoch: 41
2023-02-22 15:38:05,727 32k INFO Train Epoch: 42 [67%]
2023-02-22 15:38:05,727 32k INFO [2.699327230453491, 2.1295037269592285, 6.064660549163818, 14.428650856018066, 1.158591628074646, 4000, 9.948877917043875e-05]
2023-02-22 15:38:10,077 32k INFO Saving model and optimizer state at iteration 42 to ./logs\32k\G_4000.pth
2023-02-22 15:38:26,694 32k INFO Saving model and optimizer state at iteration 42 to ./logs\32k\D_4000.pth
2023-02-22 15:38:53,288 32k INFO ====> Epoch: 42
2023-02-22 15:40:25,213 32k INFO ====> Epoch: 43
2023-02-22 15:41:40,124 32k INFO Train Epoch: 44 [75%]
2023-02-22 15:41:40,125 32k INFO [2.5202181339263916, 2.263179063796997, 8.506352424621582, 14.219698905944824, 1.1474385261535645, 4200, 9.94639085301583e-05]
2023-02-22 15:41:57,522 32k INFO ====> Epoch: 44
2023-02-22 15:43:29,518 32k INFO ====> Epoch: 45
2023-02-22 15:44:50,330 32k INFO Train Epoch: 46 [83%]
2023-02-22 15:44:50,331 32k INFO [2.5390665531158447, 2.3581087589263916, 10.267776489257812, 18.579225540161133, 0.5731378197669983, 4400, 9.943904410714931e-05]
2023-02-22 15:45:01,966 32k INFO ====> Epoch: 46
2023-02-22 15:46:34,021 32k INFO ====> Epoch: 47
2023-02-22 15:48:00,727 32k INFO Train Epoch: 48 [92%]
2023-02-22 15:48:00,727 32k INFO [2.515454053878784, 2.529177188873291, 9.766312599182129, 17.621761322021484, 0.8474573493003845, 4600, 9.941418589985758e-05]
2023-02-22 15:48:06,337 32k INFO ====> Epoch: 48
2023-02-22 15:49:38,320 32k INFO ====> Epoch: 49
2023-02-22 15:51:10,201 32k INFO ====> Epoch: 50
2023-02-22 15:51:32,250 32k INFO Train Epoch: 51 [0%]
2023-02-22 15:51:32,251 32k INFO [2.3931424617767334, 2.356489419937134, 9.818400382995605, 17.91476821899414, 0.9206458926200867, 4800, 9.937691023999092e-05]
2023-02-22 15:52:42,572 32k INFO ====> Epoch: 51
2023-02-22 15:54:14,584 32k INFO ====> Epoch: 52
2023-02-22 15:54:42,402 32k INFO Train Epoch: 53 [8%]
2023-02-22 15:54:42,403 32k INFO [2.62162184715271, 2.1928069591522217, 7.006716251373291, 12.615202903747559, 1.3347645998001099, 5000, 9.935206756519513e-05]
2023-02-22 15:54:46,954 32k INFO Saving model and optimizer state at iteration 53 to ./logs\32k\G_5000.pth
2023-02-22 15:55:04,806 32k INFO Saving model and optimizer state at iteration 53 to ./logs\32k\D_5000.pth
2023-02-22 15:56:12,484 32k INFO ====> Epoch: 53
2023-02-22 15:57:44,459 32k INFO ====> Epoch: 54
2023-02-22 15:58:18,146 32k INFO Train Epoch: 55 [17%]
2023-02-22 15:58:18,146 32k INFO [2.3371574878692627, 2.5377357006073, 12.064924240112305, 20.312028884887695, 0.8844712376594543, 5200, 9.932723110067987e-05]
2023-02-22 15:59:16,702 32k INFO ====> Epoch: 55
2023-02-22 16:00:48,683 32k INFO ====> Epoch: 56
2023-02-22 16:01:28,287 32k INFO Train Epoch: 57 [25%]
2023-02-22 16:01:28,287 32k INFO [2.4237263202667236, 2.382598876953125, 9.18662166595459, 19.957326889038086, 0.973038375377655, 5400, 9.930240084489267e-05]
2023-02-22 16:02:21,032 32k INFO ====> Epoch: 57
2023-02-22 16:03:53,053 32k INFO ====> Epoch: 58
2023-02-22 16:04:38,512 32k INFO Train Epoch: 59 [33%]
2023-02-22 16:04:38,513 32k INFO [2.5449366569519043, 2.398916006088257, 6.566847801208496, 14.815089225769043, 0.9515616297721863, 5600, 9.927757679628145e-05]
2023-02-22 16:05:25,239 32k INFO ====> Epoch: 59
2023-02-22 16:06:57,184 32k INFO ====> Epoch: 60
2023-02-22 16:07:48,540 32k INFO Train Epoch: 61 [42%]
2023-02-22 16:07:48,541 32k INFO [2.401327610015869, 2.294501781463623, 10.175949096679688, 17.809703826904297, 0.2573431134223938, 5800, 9.92527589532945e-05]
2023-02-22 16:08:29,513 32k INFO ====> Epoch: 61
2023-02-22 16:10:01,428 32k INFO ====> Epoch: 62
2023-02-22 16:10:58,728 32k INFO Train Epoch: 63 [50%]
2023-02-22 16:10:58,728 32k INFO [2.3318843841552734, 2.3909454345703125, 14.289694786071777, 23.690601348876953, 0.8774771094322205, 6000, 9.922794731438052e-05]
2023-02-22 16:11:03,111 32k INFO Saving model and optimizer state at iteration 63 to ./logs\32k\G_6000.pth
2023-02-22 16:11:21,087 32k INFO Saving model and optimizer state at iteration 63 to ./logs\32k\D_6000.pth
2023-02-22 16:11:59,465 32k INFO ====> Epoch: 63
2023-02-22 16:13:31,525 32k INFO ====> Epoch: 64
2023-02-22 16:14:34,657 32k INFO Train Epoch: 65 [58%]
2023-02-22 16:14:34,658 32k INFO [2.5927109718322754, 1.9995574951171875, 10.218186378479004, 17.972421646118164, 0.97355717420578, 6200, 9.92031418779886e-05]
2023-02-22 16:15:03,864 32k INFO ====> Epoch: 65
2023-02-22 16:16:35,954 32k INFO ====> Epoch: 66
2023-02-22 16:17:44,886 32k INFO Train Epoch: 67 [67%]
2023-02-22 16:17:44,886 32k INFO [2.424114942550659, 2.504781484603882, 8.676969528198242, 19.212587356567383, 0.6396912336349487, 6400, 9.917834264256819e-05]
2023-02-22 16:18:08,323 32k INFO ====> Epoch: 67
2023-02-22 16:19:40,252 32k INFO ====> Epoch: 68
2023-02-22 16:20:55,170 32k INFO Train Epoch: 69 [75%]
2023-02-22 16:20:55,170 32k INFO [2.1533024311065674, 3.0644826889038086, 7.629947662353516, 12.209115982055664, 0.5737940669059753, 6600, 9.915354960656915e-05]
2023-02-22 16:21:12,576 32k INFO ====> Epoch: 69
2023-02-22 16:22:44,491 32k INFO ====> Epoch: 70
2023-02-22 16:24:05,302 32k INFO Train Epoch: 71 [83%]
2023-02-22 16:24:05,303 32k INFO [2.5728468894958496, 2.255802631378174, 12.372926712036133, 19.72517204284668, 0.4394569396972656, 6800, 9.912876276844171e-05]
2023-02-22 16:24:16,802 32k INFO ====> Epoch: 71
2023-02-22 16:25:48,812 32k INFO ====> Epoch: 72
2023-02-22 16:27:15,565 32k INFO Train Epoch: 73 [92%]
2023-02-22 16:27:15,566 32k INFO [2.4174983501434326, 2.583244800567627, 12.01104736328125, 20.709869384765625, 0.8593897223472595, 7000, 9.910398212663652e-05]
2023-02-22 16:27:19,933 32k INFO Saving model and optimizer state at iteration 73 to ./logs\32k\G_7000.pth
2023-02-22 16:27:36,201 32k INFO Saving model and optimizer state at iteration 73 to ./logs\32k\D_7000.pth
2023-02-22 16:27:45,345 32k INFO ====> Epoch: 73
2023-02-22 16:29:17,311 32k INFO ====> Epoch: 74
2023-02-22 16:30:49,193 32k INFO ====> Epoch: 75
2023-02-22 16:31:11,286 32k INFO Train Epoch: 76 [0%]
2023-02-22 16:31:11,286 32k INFO [2.4050168991088867, 2.314572334289551, 10.949235916137695, 17.868207931518555, 0.8503013849258423, 7200, 9.906682277864462e-05]
2023-02-22 16:32:21,498 32k INFO ====> Epoch: 76
2023-02-22 16:33:53,639 32k INFO ====> Epoch: 77
2023-02-22 16:34:21,492 32k INFO Train Epoch: 78 [8%]
2023-02-22 16:34:21,492 32k INFO [2.33305025100708, 2.5026371479034424, 10.88790225982666, 19.406280517578125, 0.8907907605171204, 7400, 9.904205762086905e-05]
2023-02-22 16:35:25,844 32k INFO ====> Epoch: 78
2023-02-22 16:36:57,756 32k INFO ====> Epoch: 79
2023-02-22 16:37:33,287 32k INFO Train Epoch: 80 [17%]
2023-02-22 16:37:33,287 32k INFO [2.3774352073669434, 2.40655517578125, 11.575504302978516, 19.511062622070312, 0.7897243499755859, 7600, 9.901729865399597e-05]
2023-02-22 16:38:33,509 32k INFO ====> Epoch: 80
2023-02-22 16:40:21,757 32k INFO ====> Epoch: 81
2023-02-22 16:41:05,284 32k INFO Train Epoch: 82 [25%]
2023-02-22 16:41:05,285 32k INFO [2.507054090499878, 2.5407822132110596, 10.627754211425781, 19.242189407348633, 1.1186254024505615, 7800, 9.899254587647776e-05]
2023-02-22 16:42:05,985 32k INFO ====> Epoch: 82
2023-02-22 16:43:40,273 32k INFO ====> Epoch: 83
2023-02-22 16:44:26,718 32k INFO Train Epoch: 84 [33%]
2023-02-22 16:44:26,718 32k INFO [2.372248649597168, 2.335797071456909, 10.346333503723145, 19.8045597076416, 0.8870834708213806, 8000, 9.896779928676716e-05]
2023-02-22 16:44:31,079 32k INFO Saving model and optimizer state at iteration 84 to ./logs\32k\G_8000.pth
2023-02-22 16:44:47,704 32k INFO Saving model and optimizer state at iteration 84 to ./logs\32k\D_8000.pth
2023-02-22 16:45:39,633 32k INFO ====> Epoch: 84
2023-02-22 16:47:14,215 32k INFO ====> Epoch: 85
2023-02-22 16:48:06,579 32k INFO Train Epoch: 86 [42%]
2023-02-22 16:48:06,580 32k INFO [2.71091628074646, 1.917865514755249, 6.362136363983154, 12.128801345825195, 0.7704624533653259, 8200, 9.894305888331732e-05]
2023-02-22 16:48:48,895 32k INFO ====> Epoch: 86
2023-02-22 16:50:23,435 32k INFO ====> Epoch: 87
2023-02-22 16:51:21,956 32k INFO Train Epoch: 88 [50%]
2023-02-22 16:51:21,956 32k INFO [2.347158193588257, 2.519123077392578, 13.479973793029785, 21.263261795043945, 1.0561842918395996, 8400, 9.891832466458178e-05]
2023-02-22 16:51:58,188 32k INFO ====> Epoch: 88
2023-02-22 16:53:32,713 32k INFO ====> Epoch: 89
2023-02-22 16:54:37,198 32k INFO Train Epoch: 90 [58%]
2023-02-22 16:54:37,198 32k INFO [2.253192901611328, 2.7299721240997314, 10.998817443847656, 17.6474552154541, 0.6397795081138611, 8600, 9.889359662901445e-05]
2023-02-22 16:55:07,253 32k INFO ====> Epoch: 90
2023-02-22 16:56:41,772 32k INFO ====> Epoch: 91
2023-02-22 16:57:52,446 32k INFO Train Epoch: 92 [67%]
2023-02-22 16:57:52,446 32k INFO [2.1650004386901855, 2.9927978515625, 12.249756813049316, 19.009756088256836, 0.5815404653549194, 8800, 9.886887477506964e-05]
2023-02-22 16:58:16,630 32k INFO ====> Epoch: 92
2023-02-22 16:59:51,089 32k INFO ====> Epoch: 93
2023-02-22 17:01:07,832 32k INFO Train Epoch: 94 [75%]
2023-02-22 17:01:07,832 32k INFO [2.2091586589813232, 2.7259390354156494, 8.377230644226074, 15.831489562988281, 1.1868693828582764, 9000, 9.884415910120204e-05]
2023-02-22 17:01:12,237 32k INFO Saving model and optimizer state at iteration 94 to ./logs\32k\G_9000.pth
2023-02-22 17:01:29,650 32k INFO Saving model and optimizer state at iteration 94 to ./logs\32k\D_9000.pth
2023-02-22 17:01:51,234 32k INFO ====> Epoch: 94
2023-02-22 17:03:26,924 32k INFO ====> Epoch: 95
2023-02-22 17:04:49,734 32k INFO Train Epoch: 96 [83%]
2023-02-22 17:04:49,734 32k INFO [2.2579903602600098, 2.5196046829223633, 11.29547119140625, 19.78851318359375, 0.7442747950553894, 9200, 9.881944960586671e-05]
2023-02-22 17:05:01,727 32k INFO ====> Epoch: 96
2023-02-22 17:06:36,234 32k INFO ====> Epoch: 97
2023-02-22 17:08:05,105 32k INFO Train Epoch: 98 [92%]
2023-02-22 17:08:05,106 32k INFO [2.2475061416625977, 2.572089195251465, 12.223832130432129, 19.65192413330078, 1.1417388916015625, 9400, 9.879474628751914e-05]
2023-02-22 17:08:10,877 32k INFO ====> Epoch: 98
2023-02-22 17:09:45,334 32k INFO ====> Epoch: 99
2023-02-22 17:11:19,697 32k INFO ====> Epoch: 100
2023-02-22 17:11:41,688 32k INFO Train Epoch: 101 [0%]
2023-02-22 17:11:41,688 32k INFO [2.349648952484131, 2.544644594192505, 11.396925926208496, 19.187210083007812, 1.01069974899292, 9600, 9.875770288847208e-05]
2023-02-22 17:12:54,275 32k INFO ====> Epoch: 101
2023-02-22 17:14:28,617 32k INFO ====> Epoch: 102
2023-02-22 17:14:56,638 32k INFO Train Epoch: 103 [8%]
2023-02-22 17:14:56,639 32k INFO [2.373283863067627, 2.405756711959839, 11.242820739746094, 19.008630752563477, 0.8255038857460022, 9800, 9.873301500583906e-05]
2023-02-22 17:16:03,251 32k INFO ====> Epoch: 103
2023-02-22 17:17:37,617 32k INFO ====> Epoch: 104
2023-02-22 17:18:11,823 32k INFO Train Epoch: 105 [17%]
2023-02-22 17:18:11,823 32k INFO [2.284367084503174, 2.3137102127075195, 11.732841491699219, 19.72892951965332, 0.8187623620033264, 10000, 9.870833329479095e-05]
2023-02-22 17:18:16,173 32k INFO Saving model and optimizer state at iteration 105 to ./logs\32k\G_10000.pth
2023-02-22 17:18:35,785 32k INFO Saving model and optimizer state at iteration 105 to ./logs\32k\D_10000.pth
2023-02-22 17:19:39,979 32k INFO ====> Epoch: 105
2023-02-22 17:21:14,353 32k INFO ====> Epoch: 106
2023-02-22 17:21:54,670 32k INFO Train Epoch: 107 [25%]
2023-02-22 17:21:54,670 32k INFO [2.573239326477051, 2.3250515460968018, 10.18419361114502, 19.073320388793945, 1.2266535758972168, 10200, 9.868365775378495e-05]
2023-02-22 17:22:49,113 32k INFO ====> Epoch: 107
2023-02-22 17:24:23,459 32k INFO ====> Epoch: 108
2023-02-22 17:25:09,774 32k INFO Train Epoch: 109 [33%]
2023-02-22 17:25:09,775 32k INFO [2.383540153503418, 2.1890156269073486, 9.045347213745117, 16.33897590637207, 1.013568639755249, 10400, 9.865898838127865e-05]
2023-02-22 17:25:58,126 32k INFO ====> Epoch: 109
2023-02-22 17:27:32,628 32k INFO ====> Epoch: 110
2023-02-22 17:28:24,990 32k INFO Train Epoch: 111 [42%]
2023-02-22 17:28:24,990 32k INFO [2.5534281730651855, 2.1356728076934814, 6.74716854095459, 11.141881942749023, 0.9786153435707092, 10600, 9.863432517573002e-05]
2023-02-22 17:29:07,375 32k INFO ====> Epoch: 111
2023-02-22 17:30:41,812 32k INFO ====> Epoch: 112
2023-02-22 17:31:40,243 32k INFO Train Epoch: 113 [50%]
2023-02-22 17:31:40,243 32k INFO [2.333615779876709, 2.469421863555908, 11.403718948364258, 18.24078941345215, 0.8930609822273254, 10800, 9.86096681355974e-05]
2023-02-22 17:32:16,374 32k INFO ====> Epoch: 113
2023-02-22 17:33:50,757 32k INFO ====> Epoch: 114
2023-02-22 17:34:55,259 32k INFO Train Epoch: 115 [58%]
2023-02-22 17:34:55,260 32k INFO [2.597790241241455, 2.1551156044006348, 10.270503997802734, 16.67560577392578, 1.3888392448425293, 11000, 9.858501725933955e-05]
2023-02-22 17:34:59,644 32k INFO Saving model and optimizer state at iteration 115 to ./logs\32k\G_11000.pth
2023-02-22 17:35:17,175 32k INFO Saving model and optimizer state at iteration 115 to ./logs\32k\D_11000.pth
2023-02-22 17:35:54,062 32k INFO ====> Epoch: 115
2023-02-22 20:31:20,713 32k INFO ====> Epoch: 116
2023-02-22 20:32:30,093 32k INFO Train Epoch: 117 [67%]
2023-02-22 20:32:30,094 32k INFO [2.4348371028900146, 2.0384914875030518, 10.057577133178711, 16.99835205078125, 0.528782844543457, 11200, 9.85603725454156e-05]
2023-02-22 20:32:53,867 32k INFO ====> Epoch: 117
2023-02-22 20:34:28,874 32k INFO ====> Epoch: 118
2023-02-22 20:35:45,963 32k INFO Train Epoch: 119 [75%]
2023-02-22 20:35:45,963 32k INFO [2.6818912029266357, 2.2558794021606445, 8.338019371032715, 15.641912460327148, 0.7577197551727295, 11400, 9.853573399228505e-05]
2023-02-22 20:36:03,813 32k INFO ====> Epoch: 119
2023-02-22 20:37:37,151 32k INFO ====> Epoch: 120
2023-02-22 20:39:00,221 32k INFO Train Epoch: 121 [83%]
2023-02-22 20:39:00,221 32k INFO [2.2360901832580566, 2.620755910873413, 12.849711418151855, 21.679330825805664, 0.5196329355239868, 11600, 9.851110159840781e-05]
2023-02-22 20:39:12,031 32k INFO ====> Epoch: 121
2023-02-22 20:40:47,542 32k INFO ====> Epoch: 122
2023-02-22 20:42:17,956 32k INFO Train Epoch: 123 [92%]
2023-02-22 20:42:17,956 32k INFO [2.399332046508789, 2.413424253463745, 10.66106128692627, 20.046344757080078, 0.6961185336112976, 11800, 9.848647536224416e-05]
2023-02-22 20:42:23,805 32k INFO ====> Epoch: 123
2023-02-22 20:44:01,725 32k INFO ====> Epoch: 124
2023-02-22 20:45:38,751 32k INFO ====> Epoch: 125
2023-02-22 20:46:00,717 32k INFO Train Epoch: 126 [0%]
2023-02-22 20:46:00,717 32k INFO [2.8306925296783447, 2.608029842376709, 6.2529497146606445, 12.364657402038574, 0.8958999514579773, 12000, 9.84495475503445e-05]
2023-02-22 20:46:05,062 32k INFO Saving model and optimizer state at iteration 126 to ./logs\32k\G_12000.pth
2023-02-22 20:46:22,876 32k INFO Saving model and optimizer state at iteration 126 to ./logs\32k\D_12000.pth
2023-02-22 20:47:49,445 32k INFO ====> Epoch: 126
2023-02-22 20:49:39,187 32k INFO ====> Epoch: 127
2023-02-22 20:50:07,537 32k INFO Train Epoch: 128 [8%]
2023-02-22 20:50:07,538 32k INFO [2.4325919151306152, 2.298684597015381, 8.939014434814453, 12.424883842468262, 0.7497723698616028, 12200, 9.842493670173108e-05]
2023-02-22 20:51:19,370 32k INFO ====> Epoch: 128
2023-02-22 20:52:52,991 32k INFO ====> Epoch: 129
2023-02-22 20:53:26,740 32k INFO Train Epoch: 130 [17%]
2023-02-22 20:53:26,740 32k INFO [2.4256911277770996, 2.498311996459961, 11.079325675964355, 18.753610610961914, 0.739328145980835, 12400, 9.840033200544528e-05]
2023-02-22 20:54:26,818 32k INFO ====> Epoch: 130
2023-02-22 20:56:01,178 32k INFO ====> Epoch: 131
2023-02-22 20:56:41,144 32k INFO Train Epoch: 132 [25%]
2023-02-22 20:56:41,145 32k INFO [2.4430596828460693, 2.443613052368164, 9.05742359161377, 17.19443702697754, 0.7620078921318054, 12600, 9.837573345994909e-05]
2023-02-22 20:57:35,413 32k INFO ====> Epoch: 132
2023-02-22 20:59:09,120 32k INFO ====> Epoch: 133
2023-02-22 20:59:55,044 32k INFO Train Epoch: 134 [33%]
2023-02-22 20:59:55,045 32k INFO [2.505936622619629, 2.3898284435272217, 7.810985088348389, 13.378456115722656, 1.2783924341201782, 12800, 9.835114106370493e-05]
2023-02-22 21:00:43,179 32k INFO ====> Epoch: 134
2023-02-22 21:02:16,908 32k INFO ====> Epoch: 135
2023-02-22 21:03:08,902 32k INFO Train Epoch: 136 [42%]
2023-02-22 21:03:08,902 32k INFO [2.4402434825897217, 2.1326770782470703, 10.419414520263672, 17.756248474121094, 0.7173585295677185, 13000, 9.832655481517557e-05]
2023-02-22 21:03:13,205 32k INFO Saving model and optimizer state at iteration 136 to ./logs\32k\G_13000.pth
2023-02-22 21:03:30,811 32k INFO Saving model and optimizer state at iteration 136 to ./logs\32k\D_13000.pth
2023-02-22 21:04:16,487 32k INFO ====> Epoch: 136
2023-02-22 21:05:50,181 32k INFO ====> Epoch: 137
2023-02-22 21:06:48,153 32k INFO Train Epoch: 138 [50%]
2023-02-22 21:06:48,153 32k INFO [2.360225200653076, 2.247342109680176, 11.932147026062012, 19.808679580688477, 0.7805557250976562, 13200, 9.830197471282419e-05]
2023-02-22 21:07:24,075 32k INFO ====> Epoch: 138
2023-02-22 21:08:57,845 32k INFO ====> Epoch: 139
2023-02-22 21:10:01,976 32k INFO Train Epoch: 140 [58%]
2023-02-22 21:10:01,977 32k INFO [2.3206355571746826, 2.3782708644866943, 10.206865310668945, 16.233327865600586, 1.0171841382980347, 13400, 9.827740075511432e-05]
2023-02-22 21:10:31,906 32k INFO ====> Epoch: 140
2023-02-22 21:12:05,629 32k INFO ====> Epoch: 141
2023-02-22 21:13:15,714 32k INFO Train Epoch: 142 [67%]
2023-02-22 21:13:15,714 32k INFO [2.479469060897827, 2.4788477420806885, 9.181254386901855, 18.939329147338867, 0.5550024509429932, 13600, 9.825283294050992e-05]
2023-02-22 21:13:39,694 32k INFO ====> Epoch: 142
2023-02-22 21:15:13,374 32k INFO ====> Epoch: 143
2023-02-22 21:16:29,548 32k INFO Train Epoch: 144 [75%]
2023-02-22 21:16:29,548 32k INFO [2.6104512214660645, 2.257268190383911, 8.792437553405762, 15.681217193603516, 0.7313880324363708, 13800, 9.822827126747529e-05]
2023-02-22 21:16:47,390 32k INFO ====> Epoch: 144
2023-02-22 21:18:20,999 32k INFO ====> Epoch: 145
2023-02-22 21:19:43,366 32k INFO Train Epoch: 146 [83%]
2023-02-22 21:19:43,366 32k INFO [2.349297523498535, 2.540470600128174, 9.31801700592041, 17.564865112304688, 0.844805121421814, 14000, 9.820371573447515e-05]
2023-02-22 21:19:47,730 32k INFO Saving model and optimizer state at iteration 146 to ./logs\32k\G_14000.pth
2023-02-22 21:20:06,766 32k INFO Saving model and optimizer state at iteration 146 to ./logs\32k\D_14000.pth
2023-02-22 21:20:22,632 32k INFO ====> Epoch: 146
2023-02-22 21:21:56,366 32k INFO ====> Epoch: 147
2023-02-22 21:23:24,644 32k INFO Train Epoch: 148 [92%]
2023-02-22 21:23:24,644 32k INFO [2.459839344024658, 2.3918144702911377, 10.237080574035645, 19.57539176940918, 0.8234599232673645, 14200, 9.817916633997459e-05]
2023-02-22 21:23:30,381 32k INFO ====> Epoch: 148
2023-02-22 21:25:04,056 32k INFO ====> Epoch: 149
2023-02-22 21:26:43,871 32k INFO ====> Epoch: 150
2023-02-22 21:27:05,974 32k INFO Train Epoch: 151 [0%]
2023-02-22 21:27:05,974 32k INFO [2.3207051753997803, 2.562465190887451, 11.952434539794922, 18.7629337310791, 0.7440965175628662, 14400, 9.814235375455375e-05]
2023-02-22 21:28:21,242 32k INFO ====> Epoch: 151
2023-02-22 21:29:56,786 32k INFO ====> Epoch: 152
2023-02-22 21:30:24,915 32k INFO Train Epoch: 153 [8%]
2023-02-22 21:30:24,915 32k INFO [2.3596057891845703, 2.2290072441101074, 12.462300300598145, 16.245037078857422, 0.7593880891799927, 14600, 9.811781969958938e-05]
2023-02-22 21:31:32,555 32k INFO ====> Epoch: 153
2023-02-22 21:33:08,028 32k INFO ====> Epoch: 154
2023-02-22 21:33:42,295 32k INFO Train Epoch: 155 [17%]
2023-02-22 21:33:42,295 32k INFO [2.2800114154815674, 2.362840175628662, 14.557291030883789, 21.61530876159668, 0.5335739254951477, 14800, 9.809329177775541e-05]
2023-02-22 21:34:43,650 32k INFO ====> Epoch: 155
2023-02-22 21:36:27,381 32k INFO ====> Epoch: 156
2023-02-22 21:37:10,436 32k INFO Train Epoch: 157 [25%]
2023-02-22 21:37:10,436 32k INFO [2.6323020458221436, 2.181378126144409, 8.393657684326172, 14.980151176452637, 0.9145171046257019, 15000, 9.806876998751865e-05]
2023-02-22 21:37:14,832 32k INFO Saving model and optimizer state at iteration 157 to ./logs\32k\G_15000.pth
2023-02-22 21:37:33,451 32k INFO Saving model and optimizer state at iteration 157 to ./logs\32k\D_15000.pth
2023-02-22 21:38:35,506 32k INFO ====> Epoch: 157
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