2023-02-22 00:08:12,618	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': {'est': 0}, 'model_dir': './logs\\32k'}
2023-02-22 00:08:12,618	32k	WARNING	K:\AI\so-vits-svc-32k is not a git repository, therefore hash value comparison will be ignored.
2023-02-22 00:08:34,870	32k	INFO	Loaded checkpoint './logs\32k\G_0.pth' (iteration 1)
2023-02-22 00:08:37,960	32k	INFO	Loaded checkpoint './logs\32k\D_0.pth' (iteration 1)
2023-02-22 00:09:12,596	32k	INFO	Train Epoch: 1 [0%]
2023-02-22 00:09:12,597	32k	INFO	[2.145352363586426, 3.4001522064208984, 12.26406478881836, 40.874549865722656, 8.646808624267578, 0, 0.0001]
2023-02-22 00:09:19,053	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\G_0.pth
2023-02-22 00:09:37,859	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\D_0.pth
2023-02-22 00:11:10,285	32k	INFO	====> Epoch: 1
2023-02-22 00:12:56,112	32k	INFO	====> Epoch: 2
2023-02-22 00:13:21,893	32k	INFO	Train Epoch: 3 [4%]
2023-02-22 00:13:21,893	32k	INFO	[2.3486380577087402, 2.4642438888549805, 14.349164009094238, 24.486454010009766, 1.6935454607009888, 200, 9.99750015625e-05]
2023-02-22 00:14:42,277	32k	INFO	====> Epoch: 3
2023-02-22 00:16:27,846	32k	INFO	====> Epoch: 4
2023-02-22 00:16:56,860	32k	INFO	Train Epoch: 5 [8%]
2023-02-22 00:16:56,860	32k	INFO	[2.4858646392822266, 2.255676746368408, 11.70196533203125, 19.060020446777344, 1.3148207664489746, 400, 9.995000937421877e-05]
2023-02-22 00:18:13,793	32k	INFO	====> Epoch: 5
2023-02-22 00:19:59,483	32k	INFO	====> Epoch: 6
2023-02-22 00:20:31,940	32k	INFO	Train Epoch: 7 [12%]
2023-02-22 00:20:31,940	32k	INFO	[2.3629703521728516, 2.449742078781128, 9.971107482910156, 18.171764373779297, 1.2438346147537231, 600, 9.99250234335941e-05]
2023-02-22 00:21:45,560	32k	INFO	====> Epoch: 7
2023-02-22 00:23:31,255	32k	INFO	====> Epoch: 8
2023-02-22 00:24:07,127	32k	INFO	Train Epoch: 9 [16%]
2023-02-22 00:24:07,127	32k	INFO	[2.7334389686584473, 2.1502294540405273, 7.149779319763184, 18.11358642578125, 1.2457014322280884, 800, 9.990004373906418e-05]
2023-02-22 00:25:17,128	32k	INFO	====> Epoch: 9
2023-02-22 00:27:02,598	32k	INFO	====> Epoch: 10
2023-02-22 00:27:41,816	32k	INFO	Train Epoch: 11 [20%]
2023-02-22 00:27:41,816	32k	INFO	[2.525851011276245, 2.173820734024048, 10.240619659423828, 18.13275146484375, 1.0487183332443237, 1000, 9.987507028906759e-05]
2023-02-22 00:27:46,068	32k	INFO	Saving model and optimizer state at iteration 11 to ./logs\32k\G_1000.pth
2023-02-22 00:28:05,134	32k	INFO	Saving model and optimizer state at iteration 11 to ./logs\32k\D_1000.pth
2023-02-22 00:29:14,629	32k	INFO	====> Epoch: 11
2023-02-22 00:31:00,159	32k	INFO	====> Epoch: 12
2023-02-22 00:31:42,863	32k	INFO	Train Epoch: 13 [24%]
2023-02-22 00:31:42,863	32k	INFO	[2.4192304611206055, 2.4427719116210938, 12.2838773727417, 23.12200164794922, 1.0217249393463135, 1200, 9.98501030820433e-05]
2023-02-22 00:32:46,074	32k	INFO	====> Epoch: 13
2023-02-22 00:34:31,694	32k	INFO	====> Epoch: 14
2023-02-22 00:35:17,797	32k	INFO	Train Epoch: 15 [29%]
2023-02-22 00:35:17,798	32k	INFO	[2.5181407928466797, 2.393437385559082, 8.553373336791992, 21.508071899414062, 0.9627037048339844, 1400, 9.982514211643064e-05]
2023-02-22 00:36:17,539	32k	INFO	====> Epoch: 15
2023-02-22 00:38:03,121	32k	INFO	====> Epoch: 16
2023-02-22 00:38:52,596	32k	INFO	Train Epoch: 17 [33%]
2023-02-22 00:38:52,597	32k	INFO	[2.3772032260894775, 2.1716203689575195, 12.80620002746582, 22.022525787353516, 1.2130091190338135, 1600, 9.980018739066937e-05]
2023-02-22 00:39:48,945	32k	INFO	====> Epoch: 17
2023-02-22 00:41:34,608	32k	INFO	====> Epoch: 18
2023-02-22 00:42:27,609	32k	INFO	Train Epoch: 19 [37%]
2023-02-22 00:42:27,609	32k	INFO	[2.588810920715332, 2.084688901901245, 10.23686408996582, 17.19050407409668, 1.0559662580490112, 1800, 9.977523890319963e-05]
2023-02-22 00:43:20,562	32k	INFO	====> Epoch: 19
2023-02-22 00:45:06,198	32k	INFO	====> Epoch: 20
2023-02-22 00:46:02,554	32k	INFO	Train Epoch: 21 [41%]
2023-02-22 00:46:02,555	32k	INFO	[2.3476009368896484, 2.4465882778167725, 14.103896141052246, 22.818317413330078, 0.7795078158378601, 2000, 9.975029665246193e-05]
2023-02-22 00:46:06,816	32k	INFO	Saving model and optimizer state at iteration 21 to ./logs\32k\G_2000.pth
2023-02-22 00:46:24,690	32k	INFO	Saving model and optimizer state at iteration 21 to ./logs\32k\D_2000.pth
2023-02-22 00:47:17,669	32k	INFO	====> Epoch: 21
2023-02-22 00:49:03,347	32k	INFO	====> Epoch: 22
2023-02-22 00:50:03,181	32k	INFO	Train Epoch: 23 [45%]
2023-02-22 00:50:03,181	32k	INFO	[2.331178903579712, 2.411133289337158, 13.773752212524414, 21.044940948486328, 1.075492262840271, 2200, 9.972536063689719e-05]
2023-02-22 00:50:49,196	32k	INFO	====> Epoch: 23
2023-02-22 00:52:35,089	32k	INFO	====> Epoch: 24
2023-02-22 00:53:38,492	32k	INFO	Train Epoch: 25 [49%]
2023-02-22 00:53:38,492	32k	INFO	[2.7379379272460938, 2.1680490970611572, 10.426996231079102, 19.272850036621094, 1.2769395112991333, 2400, 9.970043085494672e-05]
2023-02-22 00:54:21,188	32k	INFO	====> Epoch: 25
2023-02-22 00:56:06,784	32k	INFO	====> Epoch: 26
2023-02-22 00:57:13,707	32k	INFO	Train Epoch: 27 [53%]
2023-02-22 00:57:13,707	32k	INFO	[2.4311702251434326, 2.5075151920318604, 9.771134376525879, 13.715150833129883, 0.9923850297927856, 2600, 9.967550730505221e-05]
2023-02-22 00:57:53,034	32k	INFO	====> Epoch: 27
2023-02-22 00:59:38,682	32k	INFO	====> Epoch: 28
2023-02-22 01:00:48,916	32k	INFO	Train Epoch: 29 [57%]
2023-02-22 01:00:48,916	32k	INFO	[2.397207736968994, 2.2835323810577393, 11.884821891784668, 21.50246810913086, 0.7772465944290161, 2800, 9.965058998565574e-05]
2023-02-22 01:01:24,697	32k	INFO	====> Epoch: 29
2023-02-22 01:03:10,447	32k	INFO	====> Epoch: 30
2023-02-22 01:04:23,993	32k	INFO	Train Epoch: 31 [61%]
2023-02-22 01:04:23,994	32k	INFO	[2.4665157794952393, 2.223632574081421, 10.100894927978516, 15.292652130126953, 1.0024449825286865, 3000, 9.962567889519979e-05]
2023-02-22 01:04:28,221	32k	INFO	Saving model and optimizer state at iteration 31 to ./logs\32k\G_3000.pth
2023-02-22 01:04:48,543	32k	INFO	Saving model and optimizer state at iteration 31 to ./logs\32k\D_3000.pth
2023-02-22 01:05:24,206	32k	INFO	====> Epoch: 31
2023-02-22 01:07:09,674	32k	INFO	====> Epoch: 32
2023-02-22 01:08:26,794	32k	INFO	Train Epoch: 33 [65%]
2023-02-22 01:08:26,795	32k	INFO	[2.4395065307617188, 2.381229877471924, 11.58455753326416, 21.415176391601562, 1.0025029182434082, 3200, 9.960077403212722e-05]
2023-02-22 01:08:55,697	32k	INFO	====> Epoch: 33
2023-02-22 01:10:41,472	32k	INFO	====> Epoch: 34
2023-02-22 01:12:02,104	32k	INFO	Train Epoch: 35 [69%]
2023-02-22 01:12:02,105	32k	INFO	[2.388833522796631, 2.4029440879821777, 9.948843002319336, 17.525562286376953, 0.9836262464523315, 3400, 9.957587539488128e-05]
2023-02-22 01:12:27,570	32k	INFO	====> Epoch: 35
2023-02-22 01:14:13,128	32k	INFO	====> Epoch: 36
2023-02-22 01:15:37,186	32k	INFO	Train Epoch: 37 [73%]
2023-02-22 01:15:37,187	32k	INFO	[2.396942615509033, 2.3084261417388916, 7.296802997589111, 13.69768238067627, 0.9189913868904114, 3600, 9.95509829819056e-05]
2023-02-22 01:15:59,261	32k	INFO	====> Epoch: 37
2023-02-22 01:17:45,166	32k	INFO	====> Epoch: 38
2023-02-22 01:19:12,693	32k	INFO	Train Epoch: 39 [78%]
2023-02-22 01:19:12,694	32k	INFO	[2.34450626373291, 2.3164803981781006, 13.175307273864746, 21.369274139404297, 0.5636721849441528, 3800, 9.952609679164422e-05]
2023-02-22 01:19:31,254	32k	INFO	====> Epoch: 39
2023-02-22 01:21:17,022	32k	INFO	====> Epoch: 40
2023-02-22 01:22:47,780	32k	INFO	Train Epoch: 41 [82%]
2023-02-22 01:22:47,781	32k	INFO	[2.6599762439727783, 2.186920642852783, 8.917391777038574, 14.608092308044434, 0.7955180406570435, 4000, 9.950121682254156e-05]
2023-02-22 01:22:52,052	32k	INFO	Saving model and optimizer state at iteration 41 to ./logs\32k\G_4000.pth
2023-02-22 01:23:13,030	32k	INFO	Saving model and optimizer state at iteration 41 to ./logs\32k\D_4000.pth
2023-02-22 01:23:31,585	32k	INFO	====> Epoch: 41
2023-02-22 01:25:17,001	32k	INFO	====> Epoch: 42
2023-02-22 01:26:51,140	32k	INFO	Train Epoch: 43 [86%]
2023-02-22 01:26:51,141	32k	INFO	[2.218780994415283, 2.8232128620147705, 10.92943286895752, 15.00414752960205, 0.885425865650177, 4200, 9.947634307304244e-05]
2023-02-22 01:27:02,817	32k	INFO	====> Epoch: 43
2023-02-22 01:28:48,594	32k	INFO	====> Epoch: 44
2023-02-22 01:30:26,338	32k	INFO	Train Epoch: 45 [90%]
2023-02-22 01:30:26,338	32k	INFO	[2.6101627349853516, 2.4599862098693848, 10.045958518981934, 18.106704711914062, 0.9387855529785156, 4400, 9.945147554159202e-05]
2023-02-22 01:30:34,593	32k	INFO	====> Epoch: 45
2023-02-22 01:32:20,323	32k	INFO	====> Epoch: 46
2023-02-22 01:34:01,568	32k	INFO	Train Epoch: 47 [94%]
2023-02-22 01:34:01,569	32k	INFO	[2.4062795639038086, 2.434760093688965, 9.70323371887207, 17.096527099609375, 0.6637702584266663, 4600, 9.942661422663591e-05]
2023-02-22 01:34:06,513	32k	INFO	====> Epoch: 47
2023-02-22 01:35:52,323	32k	INFO	====> Epoch: 48
2023-02-22 01:37:36,966	32k	INFO	Train Epoch: 49 [98%]
2023-02-22 01:37:36,967	32k	INFO	[2.4078311920166016, 2.423760175704956, 11.222769737243652, 20.222986221313477, 0.9975738525390625, 4800, 9.940175912662009e-05]
2023-02-22 01:37:38,357	32k	INFO	====> Epoch: 49
2023-02-22 01:39:23,989	32k	INFO	====> Epoch: 50
2023-02-22 01:41:09,562	32k	INFO	====> Epoch: 51
2023-02-22 01:41:33,357	32k	INFO	Train Epoch: 52 [2%]
2023-02-22 01:41:33,358	32k	INFO	[2.568455934524536, 2.097076177597046, 8.081390380859375, 16.72420310974121, 1.0670697689056396, 5000, 9.936448812621091e-05]
2023-02-22 01:41:37,575	32k	INFO	Saving model and optimizer state at iteration 52 to ./logs\32k\G_5000.pth
2023-02-22 01:41:53,583	32k	INFO	Saving model and optimizer state at iteration 52 to ./logs\32k\D_5000.pth
2023-02-22 01:43:19,034	32k	INFO	====> Epoch: 52
2023-02-22 01:45:04,531	32k	INFO	====> Epoch: 53
2023-02-22 01:45:31,828	32k	INFO	Train Epoch: 54 [6%]
2023-02-22 01:45:31,829	32k	INFO	[2.367290735244751, 2.359792947769165, 12.402170181274414, 22.279163360595703, 0.5312451124191284, 5200, 9.933964855674948e-05]
2023-02-22 01:46:50,519	32k	INFO	====> Epoch: 54
2023-02-22 01:48:36,114	32k	INFO	====> Epoch: 55
2023-02-22 01:49:06,731	32k	INFO	Train Epoch: 56 [10%]
2023-02-22 01:49:06,731	32k	INFO	[2.4941694736480713, 2.2833311557769775, 11.451539039611816, 18.980377197265625, 1.122371792793274, 5400, 9.931481519679228e-05]
2023-02-22 01:50:22,005	32k	INFO	====> Epoch: 56
2023-02-22 01:52:08,000	32k	INFO	====> Epoch: 57
2023-02-22 01:52:43,577	32k	INFO	Train Epoch: 58 [14%]
2023-02-22 01:52:43,577	32k	INFO	[2.5777227878570557, 2.013221025466919, 7.400770664215088, 16.267370223999023, 0.9109489917755127, 5600, 9.928998804478705e-05]
2023-02-22 01:53:55,400	32k	INFO	====> Epoch: 58
2023-02-22 01:55:41,267	32k	INFO	====> Epoch: 59
2023-02-22 01:56:18,836	32k	INFO	Train Epoch: 60 [18%]
2023-02-22 01:56:18,837	32k	INFO	[2.3286633491516113, 2.273066282272339, 11.276134490966797, 19.17591667175293, 0.6657251715660095, 5800, 9.926516709918191e-05]
2023-02-22 01:57:27,294	32k	INFO	====> Epoch: 60
2023-02-22 01:59:12,967	32k	INFO	====> Epoch: 61
2023-02-22 01:59:53,907	32k	INFO	Train Epoch: 62 [22%]
2023-02-22 01:59:53,907	32k	INFO	[2.572532892227173, 2.336395025253296, 12.095869064331055, 18.98446273803711, 0.7074256539344788, 6000, 9.924035235842533e-05]
2023-02-22 01:59:58,246	32k	INFO	Saving model and optimizer state at iteration 62 to ./logs\32k\G_6000.pth
2023-02-22 02:00:15,073	32k	INFO	Saving model and optimizer state at iteration 62 to ./logs\32k\D_6000.pth
2023-02-22 02:01:23,134	32k	INFO	====> Epoch: 62
2023-02-22 02:03:08,840	32k	INFO	====> Epoch: 63
2023-02-22 02:03:53,319	32k	INFO	Train Epoch: 64 [27%]
2023-02-22 02:03:53,320	32k	INFO	[2.5473315715789795, 2.3198702335357666, 8.785454750061035, 16.218992233276367, 0.8188357949256897, 6200, 9.921554382096622e-05]
2023-02-22 02:04:54,908	32k	INFO	====> Epoch: 64
2023-02-22 02:06:40,700	32k	INFO	====> Epoch: 65
2023-02-22 02:07:28,567	32k	INFO	Train Epoch: 66 [31%]
2023-02-22 02:07:28,567	32k	INFO	[2.507612705230713, 2.3138248920440674, 6.625302791595459, 13.481208801269531, 0.4462297260761261, 6400, 9.919074148525384e-05]
2023-02-22 02:08:26,757	32k	INFO	====> Epoch: 66
2023-02-22 02:10:12,508	32k	INFO	====> Epoch: 67
2023-02-22 02:11:03,725	32k	INFO	Train Epoch: 68 [35%]
2023-02-22 02:11:03,725	32k	INFO	[2.5980536937713623, 2.279015064239502, 7.950907230377197, 13.451935768127441, 1.1401939392089844, 6600, 9.916594534973787e-05]
2023-02-22 02:11:58,445	32k	INFO	====> Epoch: 68
2023-02-22 02:13:44,135	32k	INFO	====> Epoch: 69
2023-02-22 02:14:38,891	32k	INFO	Train Epoch: 70 [39%]
2023-02-22 02:14:38,892	32k	INFO	[2.5319972038269043, 2.51550030708313, 10.939152717590332, 19.677751541137695, 0.63681960105896, 6800, 9.914115541286833e-05]
2023-02-22 02:15:30,175	32k	INFO	====> Epoch: 70
2023-02-22 02:17:15,908	32k	INFO	====> Epoch: 71
2023-02-22 02:18:14,245	32k	INFO	Train Epoch: 72 [43%]
2023-02-22 02:18:14,245	32k	INFO	[2.5482029914855957, 2.192294120788574, 9.581657409667969, 15.53216552734375, 1.2906405925750732, 7000, 9.911637167309565e-05]
2023-02-22 02:18:18,620	32k	INFO	Saving model and optimizer state at iteration 72 to ./logs\32k\G_7000.pth
2023-02-22 02:18:35,298	32k	INFO	Saving model and optimizer state at iteration 72 to ./logs\32k\D_7000.pth
2023-02-22 02:19:26,420	32k	INFO	====> Epoch: 72
2023-02-22 02:21:12,370	32k	INFO	====> Epoch: 73
2023-02-22 02:22:13,800	32k	INFO	Train Epoch: 74 [47%]
2023-02-22 02:22:13,801	32k	INFO	[2.5285887718200684, 2.162809371948242, 13.120260238647461, 21.690521240234375, 0.7244228720664978, 7200, 9.909159412887068e-05]
2023-02-22 02:22:58,230	32k	INFO	====> Epoch: 74
2023-02-22 02:24:44,154	32k	INFO	====> Epoch: 75
2023-02-22 02:25:49,172	32k	INFO	Train Epoch: 76 [51%]
2023-02-22 02:25:49,172	32k	INFO	[2.3859612941741943, 2.5308663845062256, 9.781866073608398, 18.245580673217773, 0.9907944798469543, 7400, 9.906682277864462e-05]
2023-02-22 02:26:30,190	32k	INFO	====> Epoch: 76
2023-02-22 02:28:15,895	32k	INFO	====> Epoch: 77
2023-02-22 02:29:24,473	32k	INFO	Train Epoch: 78 [55%]
2023-02-22 02:29:24,473	32k	INFO	[2.386472702026367, 2.3571693897247314, 11.112114906311035, 19.415468215942383, 0.8537010550498962, 7600, 9.904205762086905e-05]
2023-02-22 02:30:01,938	32k	INFO	====> Epoch: 78
2023-02-22 02:31:47,642	32k	INFO	====> Epoch: 79
2023-02-22 02:32:59,591	32k	INFO	Train Epoch: 80 [59%]
2023-02-22 02:32:59,592	32k	INFO	[2.4535465240478516, 2.43351411819458, 10.742626190185547, 20.20539093017578, 0.905364990234375, 7800, 9.901729865399597e-05]
2023-02-22 02:33:33,554	32k	INFO	====> Epoch: 80
2023-02-22 02:35:19,249	32k	INFO	====> Epoch: 81
2023-02-22 02:36:34,659	32k	INFO	Train Epoch: 82 [63%]
2023-02-22 02:36:34,659	32k	INFO	[2.5064964294433594, 2.268216848373413, 9.974581718444824, 17.910846710205078, 0.9886245727539062, 8000, 9.899254587647776e-05]
2023-02-22 02:36:38,899	32k	INFO	Saving model and optimizer state at iteration 82 to ./logs\32k\G_8000.pth
2023-02-22 02:36:55,742	32k	INFO	Saving model and optimizer state at iteration 82 to ./logs\32k\D_8000.pth
2023-02-22 02:37:29,423	32k	INFO	====> Epoch: 82
2023-02-22 02:39:15,168	32k	INFO	====> Epoch: 83
2023-02-22 02:40:34,013	32k	INFO	Train Epoch: 84 [67%]
2023-02-22 02:40:34,013	32k	INFO	[2.248044490814209, 2.346158266067505, 11.082698822021484, 14.95010757446289, 0.6171810626983643, 8200, 9.896779928676716e-05]
2023-02-22 02:41:01,209	32k	INFO	====> Epoch: 84
2023-02-22 02:42:47,112	32k	INFO	====> Epoch: 85
2023-02-22 02:44:09,353	32k	INFO	Train Epoch: 86 [71%]
2023-02-22 02:44:09,353	32k	INFO	[2.6061596870422363, 2.314436912536621, 10.66403865814209, 19.200468063354492, 1.07802414894104, 8400, 9.894305888331732e-05]
2023-02-22 02:44:33,096	32k	INFO	====> Epoch: 86
2023-02-22 02:46:18,750	32k	INFO	====> Epoch: 87
2023-02-22 02:47:44,525	32k	INFO	Train Epoch: 88 [76%]
2023-02-22 02:47:44,526	32k	INFO	[2.4097466468811035, 2.220452308654785, 11.689645767211914, 18.19406509399414, 0.7397383451461792, 8600, 9.891832466458178e-05]
2023-02-22 02:48:04,901	32k	INFO	====> Epoch: 88
2023-02-22 02:49:50,659	32k	INFO	====> Epoch: 89
2023-02-22 02:51:19,746	32k	INFO	Train Epoch: 90 [80%]
2023-02-22 02:51:19,746	32k	INFO	[2.4018168449401855, 2.383319139480591, 12.725435256958008, 18.570293426513672, 1.2559199333190918, 8800, 9.889359662901445e-05]
2023-02-22 02:51:36,642	32k	INFO	====> Epoch: 90
2023-02-22 02:53:22,585	32k	INFO	====> Epoch: 91
2023-02-22 02:54:55,326	32k	INFO	Train Epoch: 92 [84%]
2023-02-22 02:54:55,327	32k	INFO	[2.290731430053711, 2.6917805671691895, 11.489081382751465, 20.181421279907227, 0.704178512096405, 9000, 9.886887477506964e-05]
2023-02-22 02:54:59,569	32k	INFO	Saving model and optimizer state at iteration 92 to ./logs\32k\G_9000.pth
2023-02-22 02:55:15,826	32k	INFO	Saving model and optimizer state at iteration 92 to ./logs\32k\D_9000.pth
2023-02-22 02:55:32,580	32k	INFO	====> Epoch: 92
2023-02-22 02:57:18,717	32k	INFO	====> Epoch: 93
2023-02-22 02:58:55,426	32k	INFO	Train Epoch: 94 [88%]
2023-02-22 02:58:55,426	32k	INFO	[2.7609176635742188, 2.471208333969116, 5.6250128746032715, 12.03889274597168, 0.7381411790847778, 9200, 9.884415910120204e-05]
2023-02-22 02:59:05,407	32k	INFO	====> Epoch: 94
2023-02-22 03:00:51,801	32k	INFO	====> Epoch: 95
2023-02-22 03:02:31,827	32k	INFO	Train Epoch: 96 [92%]
2023-02-22 03:02:31,827	32k	INFO	[2.406148672103882, 2.274200677871704, 11.835630416870117, 21.682048797607422, 1.1413294076919556, 9400, 9.881944960586671e-05]
2023-02-22 03:02:38,366	32k	INFO	====> Epoch: 96
2023-02-22 03:04:24,238	32k	INFO	====> Epoch: 97
2023-02-22 03:06:07,737	32k	INFO	Train Epoch: 98 [96%]
2023-02-22 03:06:07,737	32k	INFO	[2.4189469814300537, 2.4262475967407227, 7.4442033767700195, 12.63837718963623, 0.5815107822418213, 9600, 9.879474628751914e-05]
2023-02-22 03:06:10,846	32k	INFO	====> Epoch: 98
2023-02-22 03:07:57,269	32k	INFO	====> Epoch: 99
2023-02-22 03:09:42,957	32k	INFO	====> Epoch: 100
2023-02-22 03:10:05,045	32k	INFO	Train Epoch: 101 [0%]
2023-02-22 03:10:05,046	32k	INFO	[2.5269906520843506, 2.3146581649780273, 7.8620123863220215, 17.898523330688477, 0.5046048760414124, 9800, 9.875770288847208e-05]
2023-02-22 03:11:28,848	32k	INFO	====> Epoch: 101
2023-02-22 03:13:14,566	32k	INFO	====> Epoch: 102
2023-02-22 03:13:40,056	32k	INFO	Train Epoch: 103 [4%]
2023-02-22 03:13:40,057	32k	INFO	[2.1958470344543457, 2.465301752090454, 14.825515747070312, 22.445404052734375, 0.4519413709640503, 10000, 9.873301500583906e-05]
2023-02-22 03:13:44,302	32k	INFO	Saving model and optimizer state at iteration 103 to ./logs\32k\G_10000.pth
2023-02-22 03:14:01,957	32k	INFO	Saving model and optimizer state at iteration 103 to ./logs\32k\D_10000.pth
2023-02-22 03:15:25,803	32k	INFO	====> Epoch: 103
2023-02-22 03:17:12,136	32k	INFO	====> Epoch: 104
2023-02-22 03:17:41,752	32k	INFO	Train Epoch: 105 [8%]
2023-02-22 03:17:41,752	32k	INFO	[2.530261993408203, 2.3227694034576416, 11.736129760742188, 16.371919631958008, 0.7204845547676086, 10200, 9.870833329479095e-05]
2023-02-22 03:18:58,780	32k	INFO	====> Epoch: 105
2023-02-22 03:20:45,072	32k	INFO	====> Epoch: 106
2023-02-22 03:21:18,158	32k	INFO	Train Epoch: 107 [12%]
2023-02-22 03:21:18,159	32k	INFO	[2.4681787490844727, 2.8919472694396973, 8.824729919433594, 16.09588623046875, 0.8613712787628174, 10400, 9.868365775378495e-05]
2023-02-22 03:22:31,624	32k	INFO	====> Epoch: 107
2023-02-22 03:24:17,336	32k	INFO	====> Epoch: 108
2023-02-22 03:24:53,255	32k	INFO	Train Epoch: 109 [16%]
2023-02-22 03:24:53,256	32k	INFO	[2.483661413192749, 2.4146034717559814, 9.786486625671387, 18.913461685180664, 1.075326919555664, 10600, 9.865898838127865e-05]
2023-02-22 03:26:03,360	32k	INFO	====> Epoch: 109
2023-02-22 03:27:49,697	32k	INFO	====> Epoch: 110
2023-02-22 03:28:29,576	32k	INFO	Train Epoch: 111 [20%]
2023-02-22 03:28:29,577	32k	INFO	[2.538566827774048, 2.12762713432312, 7.408393859863281, 13.515085220336914, 0.8555375933647156, 10800, 9.863432517573002e-05]
2023-02-22 03:29:36,385	32k	INFO	====> Epoch: 111
2023-02-22 03:31:22,092	32k	INFO	====> Epoch: 112
2023-02-22 03:32:04,865	32k	INFO	Train Epoch: 113 [24%]
2023-02-22 03:32:04,866	32k	INFO	[2.1984810829162598, 2.4401934146881104, 14.276609420776367, 22.693824768066406, 0.9264913201332092, 11000, 9.86096681355974e-05]
2023-02-22 03:32:09,113	32k	INFO	Saving model and optimizer state at iteration 113 to ./logs\32k\G_11000.pth
2023-02-22 03:32:25,992	32k	INFO	Saving model and optimizer state at iteration 113 to ./logs\32k\D_11000.pth
2023-02-22 03:33:32,900	32k	INFO	====> Epoch: 113
2023-02-22 03:35:19,193	32k	INFO	====> Epoch: 114
2023-02-22 03:36:06,007	32k	INFO	Train Epoch: 115 [29%]
2023-02-22 03:36:06,008	32k	INFO	[2.3687469959259033, 2.8906643390655518, 9.432950019836426, 19.32032585144043, 0.8109574913978577, 11200, 9.858501725933955e-05]
2023-02-22 03:37:05,975	32k	INFO	====> Epoch: 115
2023-02-22 03:38:52,586	32k	INFO	====> Epoch: 116
2023-02-22 03:39:42,332	32k	INFO	Train Epoch: 117 [33%]
2023-02-22 03:39:42,333	32k	INFO	[2.178363561630249, 2.667116641998291, 13.681983947753906, 20.458284378051758, 0.8319520950317383, 11400, 9.85603725454156e-05]
2023-02-22 03:40:38,811	32k	INFO	====> Epoch: 117
2023-02-22 03:42:24,730	32k	INFO	====> Epoch: 118
2023-02-22 03:43:19,888	32k	INFO	Train Epoch: 119 [37%]
2023-02-22 03:43:19,889	32k	INFO	[2.546008586883545, 2.2007601261138916, 10.31205940246582, 18.787328720092773, 1.2723021507263184, 11600, 9.853573399228505e-05]
2023-02-22 03:44:12,958	32k	INFO	====> Epoch: 119
2023-02-22 03:45:58,715	32k	INFO	====> Epoch: 120
2023-02-22 03:46:55,149	32k	INFO	Train Epoch: 121 [41%]
2023-02-22 03:46:55,149	32k	INFO	[2.446214437484741, 2.449553966522217, 13.851907730102539, 21.115680694580078, 0.7339575886726379, 11800, 9.851110159840781e-05]
2023-02-22 03:47:44,775	32k	INFO	====> Epoch: 121
2023-02-22 03:49:30,581	32k	INFO	====> Epoch: 122
2023-02-22 03:50:30,560	32k	INFO	Train Epoch: 123 [45%]
2023-02-22 03:50:30,560	32k	INFO	[2.35149884223938, 2.75274658203125, 12.845666885375977, 18.79739761352539, 1.1703294515609741, 12000, 9.848647536224416e-05]
2023-02-22 03:50:34,776	32k	INFO	Saving model and optimizer state at iteration 123 to ./logs\32k\G_12000.pth
2023-02-22 03:50:53,144	32k	INFO	Saving model and optimizer state at iteration 123 to ./logs\32k\D_12000.pth
2023-02-22 03:51:42,693	32k	INFO	====> Epoch: 123
2023-02-22 03:53:28,929	32k	INFO	====> Epoch: 124
2023-02-22 03:54:32,842	32k	INFO	Train Epoch: 125 [49%]
2023-02-22 03:54:32,842	32k	INFO	[2.589078664779663, 2.1445438861846924, 11.166776657104492, 17.973941802978516, 0.7241864204406738, 12200, 9.846185528225477e-05]
2023-02-22 03:55:15,637	32k	INFO	====> Epoch: 125
2023-02-22 03:57:01,184	32k	INFO	====> Epoch: 126
2023-02-22 03:58:08,640	32k	INFO	Train Epoch: 127 [53%]
2023-02-22 03:58:08,640	32k	INFO	[2.5327906608581543, 2.081197500228882, 7.769866943359375, 14.17745590209961, 0.6943719983100891, 12400, 9.84372413569007e-05]
2023-02-22 03:58:47,757	32k	INFO	====> Epoch: 127
2023-02-22 04:00:34,155	32k	INFO	====> Epoch: 128
2023-02-22 04:01:44,324	32k	INFO	Train Epoch: 129 [57%]
2023-02-22 04:01:44,325	32k	INFO	[2.5065693855285645, 2.289240837097168, 8.885828971862793, 15.302033424377441, 1.1030964851379395, 12600, 9.841263358464336e-05]
2023-02-22 04:02:20,017	32k	INFO	====> Epoch: 129
2023-02-22 04:04:05,745	32k	INFO	====> Epoch: 130
2023-02-22 04:05:19,448	32k	INFO	Train Epoch: 131 [61%]
2023-02-22 04:05:19,448	32k	INFO	[2.339315414428711, 2.6337029933929443, 12.177719116210938, 20.183080673217773, 1.1095930337905884, 12800, 9.838803196394459e-05]
2023-02-22 04:05:51,845	32k	INFO	====> Epoch: 131
2023-02-22 04:07:37,384	32k	INFO	====> Epoch: 132
2023-02-22 04:08:54,557	32k	INFO	Train Epoch: 133 [65%]
2023-02-22 04:08:54,557	32k	INFO	[2.3692660331726074, 2.2918972969055176, 13.822396278381348, 20.760438919067383, 0.7944438457489014, 13000, 9.836343649326659e-05]
2023-02-22 04:08:58,801	32k	INFO	Saving model and optimizer state at iteration 133 to ./logs\32k\G_13000.pth
2023-02-22 04:09:17,244	32k	INFO	Saving model and optimizer state at iteration 133 to ./logs\32k\D_13000.pth
2023-02-22 04:09:49,268	32k	INFO	====> Epoch: 133
2023-02-22 04:11:35,690	32k	INFO	====> Epoch: 134
2023-02-22 04:12:56,725	32k	INFO	Train Epoch: 135 [69%]
2023-02-22 04:12:56,725	32k	INFO	[2.538072109222412, 2.147736072540283, 8.285018920898438, 15.206883430480957, 0.571492075920105, 13200, 9.833884717107196e-05]
2023-02-22 04:13:22,345	32k	INFO	====> Epoch: 135
2023-02-22 04:15:08,661	32k	INFO	====> Epoch: 136
2023-02-22 04:16:32,598	32k	INFO	Train Epoch: 137 [73%]
2023-02-22 04:16:32,599	32k	INFO	[2.5354621410369873, 2.3016741275787354, 11.92038345336914, 18.641353607177734, 0.539569616317749, 13400, 9.831426399582366e-05]
2023-02-22 04:16:54,692	32k	INFO	====> Epoch: 137
2023-02-22 04:18:41,307	32k	INFO	====> Epoch: 138
2023-02-22 04:20:09,435	32k	INFO	Train Epoch: 139 [78%]
2023-02-22 04:20:09,436	32k	INFO	[2.333071231842041, 2.484257221221924, 12.461816787719727, 19.274198532104492, 0.8236677050590515, 13600, 9.828968696598508e-05]
2023-02-22 04:20:28,071	32k	INFO	====> Epoch: 139
2023-02-22 04:22:14,167	32k	INFO	====> Epoch: 140
2023-02-22 04:23:45,593	32k	INFO	Train Epoch: 141 [82%]
2023-02-22 04:23:45,594	32k	INFO	[2.4791781902313232, 2.1751325130462646, 10.909151077270508, 14.634515762329102, 0.7781238555908203, 13800, 9.826511608001993e-05]
2023-02-22 04:24:00,820	32k	INFO	====> Epoch: 141
2023-02-22 04:25:46,692	32k	INFO	====> Epoch: 142
2023-02-22 04:27:20,993	32k	INFO	Train Epoch: 143 [86%]
2023-02-22 04:27:20,993	32k	INFO	[2.346167802810669, 2.548734188079834, 13.352293014526367, 18.923927307128906, 0.5950165390968323, 14000, 9.824055133639235e-05]
2023-02-22 04:27:25,245	32k	INFO	Saving model and optimizer state at iteration 143 to ./logs\32k\G_14000.pth
2023-02-22 04:27:45,494	32k	INFO	Saving model and optimizer state at iteration 143 to ./logs\32k\D_14000.pth
2023-02-22 04:28:00,501	32k	INFO	====> Epoch: 143
2023-02-22 04:29:46,683	32k	INFO	====> Epoch: 144
2023-02-22 04:31:25,056	32k	INFO	Train Epoch: 145 [90%]
2023-02-22 04:31:25,056	32k	INFO	[2.4927594661712646, 2.3070590496063232, 10.073404312133789, 16.529218673706055, 0.670913815498352, 14200, 9.821599273356685e-05]
2023-02-22 04:31:33,427	32k	INFO	====> Epoch: 145
2023-02-22 04:33:19,691	32k	INFO	====> Epoch: 146
2023-02-22 04:35:00,838	32k	INFO	Train Epoch: 147 [94%]
2023-02-22 04:35:00,839	32k	INFO	[2.4546353816986084, 2.278806686401367, 8.069828987121582, 13.182048797607422, 0.5054904222488403, 14400, 9.819144027000834e-05]
2023-02-22 04:35:05,693	32k	INFO	====> Epoch: 147
2023-02-22 04:36:51,295	32k	INFO	====> Epoch: 148
2023-02-22 04:38:35,846	32k	INFO	Train Epoch: 149 [98%]
2023-02-22 04:38:35,847	32k	INFO	[2.5683984756469727, 2.2057595252990723, 10.475971221923828, 16.20850944519043, 0.9734923839569092, 14600, 9.816689394418209e-05]
2023-02-22 04:38:37,247	32k	INFO	====> Epoch: 149
2023-02-22 04:40:25,138	32k	INFO	====> Epoch: 150
2023-02-22 04:42:11,207	32k	INFO	====> Epoch: 151
2023-02-22 04:42:35,029	32k	INFO	Train Epoch: 152 [2%]
2023-02-22 04:42:35,030	32k	INFO	[2.4951038360595703, 2.260463237762451, 11.500944137573242, 17.902042388916016, 0.9977881908416748, 14800, 9.813008596033443e-05]
2023-02-22 04:43:57,118	32k	INFO	====> Epoch: 152
2023-02-22 04:45:42,690	32k	INFO	====> Epoch: 153
2023-02-22 04:46:10,019	32k	INFO	Train Epoch: 154 [6%]
2023-02-22 04:46:10,019	32k	INFO	[2.4445221424102783, 2.4485650062561035, 12.310842514038086, 20.25748634338379, 0.7647718191146851, 15000, 9.810555497212693e-05]
2023-02-22 04:46:14,290	32k	INFO	Saving model and optimizer state at iteration 154 to ./logs\32k\G_15000.pth
2023-02-22 04:46:31,659	32k	INFO	Saving model and optimizer state at iteration 154 to ./logs\32k\D_15000.pth
2023-02-22 04:47:53,918	32k	INFO	====> Epoch: 154
2023-02-22 04:49:40,479	32k	INFO	====> Epoch: 155
2023-02-22 04:50:11,813	32k	INFO	Train Epoch: 156 [10%]
2023-02-22 04:50:11,813	32k	INFO	[2.5242230892181396, 2.2266323566436768, 12.2184419631958, 17.383615493774414, 1.0418349504470825, 15200, 9.808103011628319e-05]
2023-02-22 04:51:27,234	32k	INFO	====> Epoch: 156
2023-02-22 04:53:13,568	32k	INFO	====> Epoch: 157
2023-02-22 04:53:47,515	32k	INFO	Train Epoch: 158 [14%]
2023-02-22 04:53:47,516	32k	INFO	[2.5447096824645996, 2.3157331943511963, 8.80300521850586, 14.484112739562988, 0.7142147421836853, 15400, 9.80565113912702e-05]
2023-02-22 04:54:59,247	32k	INFO	====> Epoch: 158
2023-02-22 04:56:44,971	32k	INFO	====> Epoch: 159
2023-02-22 04:57:22,561	32k	INFO	Train Epoch: 160 [18%]
2023-02-22 04:57:22,561	32k	INFO	[2.3957338333129883, 2.372086524963379, 8.605619430541992, 15.040207862854004, 0.9432356357574463, 15600, 9.803199879555537e-05]
2023-02-22 04:58:30,960	32k	INFO	====> Epoch: 160
2023-02-22 05:00:16,754	32k	INFO	====> Epoch: 161
2023-02-22 05:00:57,776	32k	INFO	Train Epoch: 162 [22%]
2023-02-22 05:00:57,776	32k	INFO	[2.501303195953369, 2.3233895301818848, 9.497570991516113, 15.891914367675781, 0.9494279026985168, 15800, 9.800749232760646e-05]
2023-02-22 05:02:02,727	32k	INFO	====> Epoch: 162
2023-02-22 05:03:48,404	32k	INFO	====> Epoch: 163
2023-02-22 05:04:32,896	32k	INFO	Train Epoch: 164 [27%]
2023-02-22 05:04:32,896	32k	INFO	[2.362159013748169, 2.503201484680176, 10.656201362609863, 16.783613204956055, 0.9532788395881653, 16000, 9.798299198589162e-05]
2023-02-22 05:04:37,788	32k	INFO	Saving model and optimizer state at iteration 164 to ./logs\32k\G_16000.pth
2023-02-22 05:04:56,829	32k	INFO	Saving model and optimizer state at iteration 164 to ./logs\32k\D_16000.pth
2023-02-22 05:06:01,710	32k	INFO	====> Epoch: 164
2023-02-22 05:07:48,176	32k	INFO	====> Epoch: 165
2023-02-22 05:08:36,653	32k	INFO	Train Epoch: 166 [31%]
2023-02-22 05:08:36,653	32k	INFO	[2.57973575592041, 1.983064889907837, 8.993478775024414, 16.000688552856445, 0.700424075126648, 16200, 9.795849776887939e-05]
2023-02-22 05:09:34,858	32k	INFO	====> Epoch: 166
2023-02-22 05:11:21,054	32k	INFO	====> Epoch: 167
2023-02-22 05:12:13,078	32k	INFO	Train Epoch: 168 [35%]
2023-02-22 05:12:13,079	32k	INFO	[2.464907646179199, 2.1761608123779297, 8.09338665008545, 13.37960433959961, 0.97138512134552, 16400, 9.79340096750387e-05]
2023-02-22 05:13:07,694	32k	INFO	====> Epoch: 168
2023-02-22 05:14:53,372	32k	INFO	====> Epoch: 169
2023-02-22 05:15:48,194	32k	INFO	Train Epoch: 170 [39%]
2023-02-22 05:15:48,195	32k	INFO	[2.4897146224975586, 2.3846330642700195, 9.467925071716309, 17.97328758239746, 0.2975856363773346, 16600, 9.790952770283884e-05]
2023-02-22 05:16:39,376	32k	INFO	====> Epoch: 170
2023-02-22 05:18:24,901	32k	INFO	====> Epoch: 171
2023-02-22 05:19:22,981	32k	INFO	Train Epoch: 172 [43%]
2023-02-22 05:19:22,981	32k	INFO	[2.409517288208008, 2.347320795059204, 13.86928939819336, 19.764402389526367, 0.5637670159339905, 16800, 9.78850518507495e-05]
2023-02-22 05:20:10,773	32k	INFO	====> Epoch: 172
2023-02-22 05:21:56,270	32k	INFO	====> Epoch: 173
2023-02-22 05:22:57,877	32k	INFO	Train Epoch: 174 [47%]
2023-02-22 05:22:57,877	32k	INFO	[2.4215376377105713, 2.1729211807250977, 11.39505386352539, 18.73835563659668, 0.5306751728057861, 17000, 9.786058211724074e-05]
2023-02-22 05:23:02,291	32k	INFO	Saving model and optimizer state at iteration 174 to ./logs\32k\G_17000.pth
2023-02-22 05:23:19,621	32k	INFO	Saving model and optimizer state at iteration 174 to ./logs\32k\D_17000.pth
2023-02-22 05:24:07,507	32k	INFO	====> Epoch: 174
2023-02-22 05:25:53,899	32k	INFO	====> Epoch: 175
2023-02-22 05:26:59,648	32k	INFO	Train Epoch: 176 [51%]
2023-02-22 05:26:59,648	32k	INFO	[2.41857647895813, 2.1925084590911865, 10.57753849029541, 18.43206214904785, 0.6052053570747375, 17200, 9.783611850078301e-05]
2023-02-22 05:27:40,697	32k	INFO	====> Epoch: 176
2023-02-22 05:29:27,079	32k	INFO	====> Epoch: 177
2023-02-22 05:30:35,514	32k	INFO	Train Epoch: 178 [55%]
2023-02-22 05:30:35,514	32k	INFO	[2.3244147300720215, 2.360485315322876, 14.300114631652832, 19.833555221557617, 0.5028417110443115, 17400, 9.781166099984716e-05]
2023-02-22 05:31:12,982	32k	INFO	====> Epoch: 178
2023-02-22 05:33:00,756	32k	INFO	====> Epoch: 179
2023-02-22 05:34:14,763	32k	INFO	Train Epoch: 180 [59%]
2023-02-22 05:34:14,763	32k	INFO	[2.428579807281494, 2.262065887451172, 10.987186431884766, 19.099437713623047, 0.6582584381103516, 17600, 9.778720961290439e-05]
2023-02-22 05:34:48,821	32k	INFO	====> Epoch: 180
2023-02-22 05:36:34,639	32k	INFO	====> Epoch: 181
2023-02-22 05:37:49,982	32k	INFO	Train Epoch: 182 [63%]
2023-02-22 05:37:49,983	32k	INFO	[2.61875581741333, 1.9758424758911133, 9.652741432189941, 14.875738143920898, 0.9741345643997192, 17800, 9.776276433842631e-05]
2023-02-22 05:38:20,692	32k	INFO	====> Epoch: 182
2023-02-22 05:40:06,124	32k	INFO	====> Epoch: 183
2023-02-22 05:41:24,889	32k	INFO	Train Epoch: 184 [67%]
2023-02-22 05:41:24,890	32k	INFO	[2.540966033935547, 2.3001551628112793, 9.484389305114746, 17.637712478637695, 0.7832726240158081, 18000, 9.773832517488488e-05]
2023-02-22 05:41:29,138	32k	INFO	Saving model and optimizer state at iteration 184 to ./logs\32k\G_18000.pth
2023-02-22 05:41:45,744	32k	INFO	Saving model and optimizer state at iteration 184 to ./logs\32k\D_18000.pth
2023-02-22 05:42:16,267	32k	INFO	====> Epoch: 184
2023-02-22 05:44:02,354	32k	INFO	====> Epoch: 185
2023-02-22 05:45:25,035	32k	INFO	Train Epoch: 186 [71%]
2023-02-22 05:45:25,035	32k	INFO	[2.5191123485565186, 2.5359508991241455, 11.501497268676758, 19.635244369506836, 0.6616455912590027, 18200, 9.771389212075249e-05]
2023-02-22 05:45:48,797	32k	INFO	====> Epoch: 186
2023-02-22 05:47:34,913	32k	INFO	====> Epoch: 187
2023-02-22 05:49:00,561	32k	INFO	Train Epoch: 188 [76%]
2023-02-22 05:49:00,562	32k	INFO	[2.280853748321533, 2.274311065673828, 13.668123245239258, 18.913005828857422, 1.0380589962005615, 18400, 9.768946517450186e-05]
2023-02-22 05:49:20,932	32k	INFO	====> Epoch: 188
2023-02-22 05:51:06,481	32k	INFO	====> Epoch: 189
2023-02-22 05:52:35,577	32k	INFO	Train Epoch: 190 [80%]
2023-02-22 05:52:35,577	32k	INFO	[2.2568392753601074, 2.6230015754699707, 11.525728225708008, 18.298168182373047, 0.6746451258659363, 18600, 9.766504433460612e-05]
2023-02-22 05:52:52,435	32k	INFO	====> Epoch: 190
2023-02-22 05:54:38,241	32k	INFO	====> Epoch: 191
2023-02-22 05:56:10,787	32k	INFO	Train Epoch: 192 [84%]
2023-02-22 05:56:10,788	32k	INFO	[2.5578360557556152, 2.209872007369995, 8.583542823791504, 16.00850486755371, 1.0789265632629395, 18800, 9.764062959953878e-05]
2023-02-22 05:56:24,223	32k	INFO	====> Epoch: 192
2023-02-22 05:58:09,905	32k	INFO	====> Epoch: 193
2023-02-22 05:59:45,738	32k	INFO	Train Epoch: 194 [88%]
2023-02-22 05:59:45,738	32k	INFO	[2.387702703475952, 2.4445672035217285, 13.355128288269043, 16.8066463470459, 1.147564172744751, 19000, 9.761622096777372e-05]
2023-02-22 05:59:50,090	32k	INFO	Saving model and optimizer state at iteration 194 to ./logs\32k\G_19000.pth
2023-02-22 06:00:07,465	32k	INFO	Saving model and optimizer state at iteration 194 to ./logs\32k\D_19000.pth
2023-02-22 06:00:21,346	32k	INFO	====> Epoch: 194
2023-02-22 06:02:07,550	32k	INFO	====> Epoch: 195
2023-02-22 06:03:47,560	32k	INFO	Train Epoch: 196 [92%]
2023-02-22 06:03:47,561	32k	INFO	[2.5213208198547363, 2.257534980773926, 12.258462905883789, 19.621543884277344, 0.6611289978027344, 19200, 9.759181843778522e-05]
2023-02-22 06:03:54,101	32k	INFO	====> Epoch: 196
2023-02-22 06:05:40,426	32k	INFO	====> Epoch: 197
2023-02-22 06:07:23,844	32k	INFO	Train Epoch: 198 [96%]
2023-02-22 06:07:23,845	32k	INFO	[2.470740795135498, 2.21482253074646, 9.043266296386719, 14.386473655700684, 0.9298809766769409, 19400, 9.756742200804793e-05]
2023-02-22 06:07:26,950	32k	INFO	====> Epoch: 198
2023-02-22 06:09:12,577	32k	INFO	====> Epoch: 199
2023-02-22 06:10:58,804	32k	INFO	====> Epoch: 200
2023-02-22 06:11:21,552	32k	INFO	Train Epoch: 201 [0%]
2023-02-22 06:11:21,553	32k	INFO	[2.2393460273742676, 2.660759210586548, 12.342625617980957, 18.233539581298828, 0.6276586651802063, 19600, 9.753083879807726e-05]
2023-02-22 06:12:45,383	32k	INFO	====> Epoch: 201
2023-02-22 06:14:31,637	32k	INFO	====> Epoch: 202
2023-02-22 06:14:57,801	32k	INFO	Train Epoch: 203 [4%]
2023-02-22 06:14:57,801	32k	INFO	[2.072805166244507, 2.761627435684204, 14.632217407226562, 19.264434814453125, 0.6756956577301025, 19800, 9.750645761229709e-05]
2023-02-22 06:16:18,193	32k	INFO	====> Epoch: 203
2023-02-22 06:18:03,843	32k	INFO	====> Epoch: 204
2023-02-22 06:18:32,695	32k	INFO	Train Epoch: 205 [8%]
2023-02-22 06:18:32,695	32k	INFO	[2.238548994064331, 2.5923948287963867, 13.83581829071045, 18.70966148376465, 0.808910071849823, 20000, 9.748208252143241e-05]
2023-02-22 06:18:36,991	32k	INFO	Saving model and optimizer state at iteration 205 to ./logs\32k\G_20000.pth
2023-02-22 06:18:52,780	32k	INFO	Saving model and optimizer state at iteration 205 to ./logs\32k\D_20000.pth
2023-02-22 06:20:13,632	32k	INFO	====> Epoch: 205
2023-02-22 06:21:59,799	32k	INFO	====> Epoch: 206
2023-02-22 06:22:32,683	32k	INFO	Train Epoch: 207 [12%]
2023-02-22 06:22:32,684	32k	INFO	[2.494340181350708, 2.35404372215271, 10.402792930603027, 18.646995544433594, 1.194170594215393, 20200, 9.745771352395957e-05]
2023-02-22 06:23:46,237	32k	INFO	====> Epoch: 207
2023-02-22 06:25:31,755	32k	INFO	====> Epoch: 208
2023-02-22 06:26:07,498	32k	INFO	Train Epoch: 209 [16%]
2023-02-22 06:26:07,499	32k	INFO	[2.5353317260742188, 2.2308082580566406, 10.610563278198242, 16.8080997467041, 0.9148491621017456, 20400, 9.743335061835535e-05]
2023-02-22 06:27:17,681	32k	INFO	====> Epoch: 209
2023-02-22 06:29:03,252	32k	INFO	====> Epoch: 210
2023-02-22 06:29:42,394	32k	INFO	Train Epoch: 211 [20%]
2023-02-22 06:29:42,395	32k	INFO	[2.6447272300720215, 1.964892864227295, 8.727736473083496, 12.838239669799805, 0.6997866630554199, 20600, 9.740899380309685e-05]
2023-02-22 06:30:49,054	32k	INFO	====> Epoch: 211
2023-02-22 06:32:35,297	32k	INFO	====> Epoch: 212
2023-02-22 06:33:18,576	32k	INFO	Train Epoch: 213 [24%]
2023-02-22 06:33:18,577	32k	INFO	[2.2379984855651855, 2.403615713119507, 15.184333801269531, 22.139081954956055, 0.9633049368858337, 20800, 9.73846430766616e-05]
2023-02-22 06:34:21,815	32k	INFO	====> Epoch: 213
2023-02-22 06:36:08,032	32k	INFO	====> Epoch: 214
2023-02-22 06:36:54,126	32k	INFO	Train Epoch: 215 [29%]
2023-02-22 06:36:54,127	32k	INFO	[2.6470189094543457, 2.246066093444824, 8.519152641296387, 15.820573806762695, 1.0386731624603271, 21000, 9.736029843752747e-05]
2023-02-22 06:36:58,320	32k	INFO	Saving model and optimizer state at iteration 215 to ./logs\32k\G_21000.pth
2023-02-22 06:37:15,347	32k	INFO	Saving model and optimizer state at iteration 215 to ./logs\32k\D_21000.pth
2023-02-22 06:38:18,371	32k	INFO	====> Epoch: 215
2023-02-22 06:40:04,492	32k	INFO	====> Epoch: 216
2023-02-22 06:40:54,670	32k	INFO	Train Epoch: 217 [33%]
2023-02-22 06:40:54,670	32k	INFO	[2.090405225753784, 2.5237374305725098, 15.738249778747559, 21.418203353881836, 1.2358826398849487, 21200, 9.733595988417275e-05]
2023-02-22 06:41:51,113	32k	INFO	====> Epoch: 217
2023-02-22 06:43:37,251	32k	INFO	====> Epoch: 218
2023-02-22 06:44:30,781	32k	INFO	Train Epoch: 219 [37%]
2023-02-22 06:44:30,781	32k	INFO	[2.5889697074890137, 2.2686333656311035, 8.668608665466309, 14.998424530029297, 1.0810593366622925, 21400, 9.731162741507607e-05]
2023-02-22 06:45:23,689	32k	INFO	====> Epoch: 219
2023-02-22 06:47:09,292	32k	INFO	====> Epoch: 220
2023-02-22 06:48:06,268	32k	INFO	Train Epoch: 221 [41%]
2023-02-22 06:48:06,269	32k	INFO	[2.2671685218811035, 2.67838978767395, 14.996197700500488, 21.1551570892334, 0.7494913339614868, 21600, 9.728730102871649e-05]
2023-02-22 06:48:55,957	32k	INFO	====> Epoch: 221
2023-02-22 06:50:42,311	32k	INFO	====> Epoch: 222
2023-02-22 06:51:42,046	32k	INFO	Train Epoch: 223 [45%]
2023-02-22 06:51:42,046	32k	INFO	[2.547105312347412, 2.134889841079712, 9.186394691467285, 14.266695022583008, 0.6058226823806763, 21800, 9.726298072357337e-05]
2023-02-22 06:52:28,072	32k	INFO	====> Epoch: 223
2023-02-22 06:54:14,252	32k	INFO	====> Epoch: 224
2023-02-22 06:55:18,050	32k	INFO	Train Epoch: 225 [49%]
2023-02-22 06:55:18,050	32k	INFO	[2.3165359497070312, 2.48864483833313, 13.522871971130371, 20.89539337158203, 0.46696582436561584, 22000, 9.723866649812655e-05]
2023-02-22 06:55:22,919	32k	INFO	Saving model and optimizer state at iteration 225 to ./logs\32k\G_22000.pth
2023-02-22 06:55:42,032	32k	INFO	Saving model and optimizer state at iteration 225 to ./logs\32k\D_22000.pth
2023-02-22 06:56:28,028	32k	INFO	====> Epoch: 225
2023-02-22 06:58:14,309	32k	INFO	====> Epoch: 226
2023-02-22 06:59:21,533	32k	INFO	Train Epoch: 227 [53%]
2023-02-22 06:59:21,534	32k	INFO	[2.635965347290039, 2.3602662086486816, 8.628167152404785, 12.540104866027832, 0.9171032309532166, 22200, 9.721435835085619e-05]
2023-02-22 07:00:00,662	32k	INFO	====> Epoch: 227
2023-02-22 07:01:46,728	32k	INFO	====> Epoch: 228
2023-02-22 07:02:57,519	32k	INFO	Train Epoch: 229 [57%]
2023-02-22 07:02:57,519	32k	INFO	[2.310483932495117, 2.573824405670166, 13.390860557556152, 19.26698112487793, 0.859022855758667, 22400, 9.719005628024282e-05]
2023-02-22 07:03:33,283	32k	INFO	====> Epoch: 229
2023-02-22 07:05:18,825	32k	INFO	====> Epoch: 230
2023-02-22 07:06:32,406	32k	INFO	Train Epoch: 231 [61%]
2023-02-22 07:06:32,406	32k	INFO	[2.4883522987365723, 2.472439765930176, 11.817012786865234, 18.11069107055664, 0.8754430413246155, 22600, 9.716576028476738e-05]
2023-02-22 07:07:04,836	32k	INFO	====> Epoch: 231
2023-02-22 07:08:50,484	32k	INFO	====> Epoch: 232
2023-02-22 07:10:07,417	32k	INFO	Train Epoch: 233 [65%]
2023-02-22 07:10:07,418	32k	INFO	[2.2918412685394287, 2.6064612865448, 12.61550235748291, 19.839508056640625, 0.7568845748901367, 22800, 9.714147036291117e-05]
2023-02-22 07:10:36,292	32k	INFO	====> Epoch: 233
2023-02-22 07:12:21,934	32k	INFO	====> Epoch: 234
2023-02-22 07:13:42,479	32k	INFO	Train Epoch: 235 [69%]
2023-02-22 07:13:42,479	32k	INFO	[2.367769479751587, 2.290179967880249, 12.814183235168457, 18.604658126831055, 0.7774146199226379, 23000, 9.711718651315591e-05]
2023-02-22 07:13:46,725	32k	INFO	Saving model and optimizer state at iteration 235 to ./logs\32k\G_23000.pth
2023-02-22 07:14:02,024	32k	INFO	Saving model and optimizer state at iteration 235 to ./logs\32k\D_23000.pth
2023-02-22 07:14:31,102	32k	INFO	====> Epoch: 235
2023-02-22 07:16:17,362	32k	INFO	====> Epoch: 236
2023-02-22 07:17:41,855	32k	INFO	Train Epoch: 237 [73%]
2023-02-22 07:17:41,855	32k	INFO	[2.2795772552490234, 2.5844802856445312, 11.45567512512207, 18.593366622924805, 0.8924825191497803, 23200, 9.709290873398365e-05]
2023-02-22 07:18:03,931	32k	INFO	====> Epoch: 237
2023-02-22 07:19:50,029	32k	INFO	====> Epoch: 238
2023-02-22 07:21:17,892	32k	INFO	Train Epoch: 239 [78%]
2023-02-22 07:21:17,893	32k	INFO	[2.455188274383545, 2.681325912475586, 12.097657203674316, 20.17988395690918, 1.3684245347976685, 23400, 9.706863702387684e-05]
2023-02-22 07:21:36,551	32k	INFO	====> Epoch: 239
2023-02-22 07:23:24,284	32k	INFO	====> Epoch: 240
2023-02-22 07:24:57,015	32k	INFO	Train Epoch: 241 [82%]
2023-02-22 07:24:57,016	32k	INFO	[2.629354953765869, 2.118459701538086, 10.275418281555176, 14.83414363861084, 0.5261375904083252, 23600, 9.704437138131832e-05]
2023-02-22 07:25:12,296	32k	INFO	====> Epoch: 241
2023-02-22 07:26:57,752	32k	INFO	====> Epoch: 242
2023-02-22 07:28:32,000	32k	INFO	Train Epoch: 243 [86%]
2023-02-22 07:28:32,001	32k	INFO	[2.329456329345703, 2.3450889587402344, 12.364802360534668, 16.953144073486328, 0.7070972919464111, 23800, 9.702011180479129e-05]
2023-02-22 07:28:43,709	32k	INFO	====> Epoch: 243
2023-02-22 07:30:29,209	32k	INFO	====> Epoch: 244
2023-02-22 07:32:06,746	32k	INFO	Train Epoch: 245 [90%]
2023-02-22 07:32:06,747	32k	INFO	[2.4288482666015625, 2.3079452514648438, 14.041245460510254, 19.745018005371094, 0.862689733505249, 24000, 9.699585829277933e-05]
2023-02-22 07:32:10,956	32k	INFO	Saving model and optimizer state at iteration 245 to ./logs\32k\G_24000.pth
2023-02-22 07:32:29,071	32k	INFO	Saving model and optimizer state at iteration 245 to ./logs\32k\D_24000.pth
2023-02-22 07:32:40,767	32k	INFO	====> Epoch: 245
2023-02-22 07:34:26,808	32k	INFO	====> Epoch: 246
2023-02-22 07:36:08,402	32k	INFO	Train Epoch: 247 [94%]
2023-02-22 07:36:08,403	32k	INFO	[2.373241901397705, 2.098410129547119, 10.478768348693848, 16.175146102905273, 0.6502178311347961, 24200, 9.69716108437664e-05]
2023-02-22 07:36:13,231	32k	INFO	====> Epoch: 247
2023-02-22 07:37:59,442	32k	INFO	====> Epoch: 248
2023-02-22 07:39:43,876	32k	INFO	Train Epoch: 249 [98%]
2023-02-22 07:39:43,877	32k	INFO	[2.40415096282959, 2.40627121925354, 10.043416976928711, 15.431482315063477, 0.813330888748169, 24400, 9.694736945623688e-05]
2023-02-22 07:39:45,264	32k	INFO	====> Epoch: 249
2023-02-22 07:41:31,487	32k	INFO	====> Epoch: 250
2023-02-22 07:43:17,279	32k	INFO	====> Epoch: 251
2023-02-22 07:43:40,973	32k	INFO	Train Epoch: 252 [2%]
2023-02-22 07:43:40,973	32k	INFO	[2.2679550647735596, 2.6712074279785156, 11.691126823425293, 17.59365463256836, 0.4011988639831543, 24600, 9.691101873690936e-05]
2023-02-22 07:45:03,101	32k	INFO	====> Epoch: 252
2023-02-22 07:46:48,461	32k	INFO	====> Epoch: 253
2023-02-22 07:47:15,562	32k	INFO	Train Epoch: 254 [6%]
2023-02-22 07:47:15,562	32k	INFO	[2.176159381866455, 2.6822993755340576, 14.428181648254395, 21.809728622436523, 0.8452849984169006, 24800, 9.68867924964598e-05]
2023-02-22 07:48:34,159	32k	INFO	====> Epoch: 254
2023-02-22 07:50:19,905	32k	INFO	====> Epoch: 255
2023-02-22 07:50:51,111	32k	INFO	Train Epoch: 256 [10%]
2023-02-22 07:50:51,111	32k	INFO	[2.5852203369140625, 2.461092710494995, 10.04835319519043, 14.898118019104004, 0.956852376461029, 25000, 9.68625723121918e-05]
2023-02-22 07:50:55,927	32k	INFO	Saving model and optimizer state at iteration 256 to ./logs\32k\G_25000.pth
2023-02-22 07:51:13,413	32k	INFO	Saving model and optimizer state at iteration 256 to ./logs\32k\D_25000.pth
2023-02-22 07:52:32,056	32k	INFO	====> Epoch: 256
2023-02-22 07:54:18,097	32k	INFO	====> Epoch: 257
2023-02-22 07:54:52,734	32k	INFO	Train Epoch: 258 [14%]
2023-02-22 07:54:52,734	32k	INFO	[2.432253837585449, 2.456174850463867, 9.509150505065918, 16.501110076904297, 0.4222906529903412, 25200, 9.683835818259144e-05]
2023-02-22 07:56:04,434	32k	INFO	====> Epoch: 258
2023-02-22 07:57:50,485	32k	INFO	====> Epoch: 259
2023-02-22 07:58:27,976	32k	INFO	Train Epoch: 260 [18%]
2023-02-22 07:58:27,977	32k	INFO	[2.4247806072235107, 2.345371723175049, 8.857375144958496, 15.63666820526123, 0.7407233119010925, 25400, 9.681415010614512e-05]
2023-02-22 07:59:36,335	32k	INFO	====> Epoch: 260
2023-02-22 08:01:21,939	32k	INFO	====> Epoch: 261
2023-02-22 08:02:02,960	32k	INFO	Train Epoch: 262 [22%]
2023-02-22 08:02:02,960	32k	INFO	[2.6320114135742188, 2.4106760025024414, 8.685118675231934, 12.927850723266602, 0.9680966138839722, 25600, 9.678994808133967e-05]
2023-02-22 08:03:07,846	32k	INFO	====> Epoch: 262
2023-02-22 08:04:53,437	32k	INFO	====> Epoch: 263
2023-02-22 08:05:37,784	32k	INFO	Train Epoch: 264 [27%]
2023-02-22 08:05:37,784	32k	INFO	[2.500497341156006, 2.2675929069519043, 8.80232048034668, 15.311875343322754, 0.8597989678382874, 25800, 9.676575210666227e-05]
2023-02-22 08:06:39,268	32k	INFO	====> Epoch: 264
2023-02-22 08:08:24,850	32k	INFO	====> Epoch: 265
2023-02-22 08:09:12,688	32k	INFO	Train Epoch: 266 [31%]
2023-02-22 08:09:12,688	32k	INFO	[2.3594794273376465, 2.2052268981933594, 10.455811500549316, 16.885915756225586, 0.6565972566604614, 26000, 9.674156218060047e-05]
2023-02-22 08:09:17,007	32k	INFO	Saving model and optimizer state at iteration 266 to ./logs\32k\G_26000.pth
2023-02-22 08:09:29,919	32k	INFO	Saving model and optimizer state at iteration 266 to ./logs\32k\D_26000.pth
2023-02-22 08:10:31,024	32k	INFO	====> Epoch: 266
2023-02-22 08:12:17,253	32k	INFO	====> Epoch: 267
2023-02-22 08:13:09,136	32k	INFO	Train Epoch: 268 [35%]
2023-02-22 08:13:09,137	32k	INFO	[2.6458592414855957, 2.1084747314453125, 10.409239768981934, 15.455072402954102, 0.5523946285247803, 26200, 9.671737830164223e-05]
2023-02-22 08:14:03,759	32k	INFO	====> Epoch: 268
2023-02-22 08:15:49,415	32k	INFO	====> Epoch: 269
2023-02-22 08:16:44,117	32k	INFO	Train Epoch: 270 [39%]
2023-02-22 08:16:44,118	32k	INFO	[2.1286776065826416, 2.643979549407959, 11.154251098632812, 16.767776489257812, 0.3980034291744232, 26400, 9.669320046827584e-05]
2023-02-22 08:17:35,389	32k	INFO	====> Epoch: 270
2023-02-22 08:19:21,150	32k	INFO	====> Epoch: 271
2023-02-22 08:20:19,919	32k	INFO	Train Epoch: 272 [43%]
2023-02-22 08:20:19,919	32k	INFO	[2.36246919631958, 2.305928945541382, 13.173051834106445, 20.20313262939453, 0.4515596628189087, 26600, 9.666902867899003e-05]
2023-02-22 08:21:07,775	32k	INFO	====> Epoch: 272
2023-02-22 08:22:54,059	32k	INFO	====> Epoch: 273
2023-02-22 08:23:55,545	32k	INFO	Train Epoch: 274 [47%]
2023-02-22 08:23:55,545	32k	INFO	[2.1859402656555176, 2.502265214920044, 10.459367752075195, 15.742925643920898, 0.7773081660270691, 26800, 9.664486293227385e-05]
2023-02-22 08:24:39,934	32k	INFO	====> Epoch: 274
2023-02-22 08:26:25,586	32k	INFO	====> Epoch: 275
2023-02-22 08:27:30,547	32k	INFO	Train Epoch: 276 [51%]
2023-02-22 08:27:30,548	32k	INFO	[2.3840584754943848, 2.286221742630005, 10.370285034179688, 17.517276763916016, 0.36077797412872314, 27000, 9.662070322661676e-05]
2023-02-22 08:27:34,765	32k	INFO	Saving model and optimizer state at iteration 276 to ./logs\32k\G_27000.pth
2023-02-22 08:27:49,261	32k	INFO	Saving model and optimizer state at iteration 276 to ./logs\32k\D_27000.pth
2023-02-22 08:28:33,782	32k	INFO	====> Epoch: 276
2023-02-22 08:30:20,077	32k	INFO	====> Epoch: 277
2023-02-22 08:31:29,161	32k	INFO	Train Epoch: 278 [55%]
2023-02-22 08:31:29,161	32k	INFO	[2.207501173019409, 2.513786792755127, 13.21751880645752, 19.042682647705078, 0.7013548612594604, 27200, 9.659654956050859e-05]
2023-02-22 08:32:06,611	32k	INFO	====> Epoch: 278
2023-02-22 08:33:52,136	32k	INFO	====> Epoch: 279
2023-02-22 08:35:04,124	32k	INFO	Train Epoch: 280 [59%]
2023-02-22 08:35:04,124	32k	INFO	[2.2693753242492676, 2.6720073223114014, 12.635223388671875, 20.047088623046875, 1.1133509874343872, 27400, 9.657240193243954e-05]
2023-02-22 08:35:38,250	32k	INFO	====> Epoch: 280
2023-02-22 08:37:23,913	32k	INFO	====> Epoch: 281
2023-02-22 08:38:39,215	32k	INFO	Train Epoch: 282 [63%]
2023-02-22 08:38:39,216	32k	INFO	[2.389529228210449, 2.2568767070770264, 10.048675537109375, 14.323448181152344, 0.7161829471588135, 27600, 9.65482603409002e-05]
2023-02-22 08:39:09,969	32k	INFO	====> Epoch: 282
2023-02-22 08:40:56,377	32k	INFO	====> Epoch: 283
2023-02-22 08:42:15,609	32k	INFO	Train Epoch: 284 [67%]
2023-02-22 08:42:15,609	32k	INFO	[2.511157751083374, 2.453148603439331, 11.416619300842285, 17.989450454711914, 0.6057873964309692, 27800, 9.652412478438153e-05]
2023-02-22 08:42:42,783	32k	INFO	====> Epoch: 284
2023-02-22 08:44:28,460	32k	INFO	====> Epoch: 285
2023-02-22 08:45:50,789	32k	INFO	Train Epoch: 286 [71%]
2023-02-22 08:45:50,789	32k	INFO	[2.419379472732544, 2.3715896606445312, 8.623769760131836, 15.313409805297852, 0.5617188811302185, 28000, 9.649999526137489e-05]
2023-02-22 08:45:55,739	32k	INFO	Saving model and optimizer state at iteration 286 to ./logs\32k\G_28000.pth
2023-02-22 08:46:09,553	32k	INFO	Saving model and optimizer state at iteration 286 to ./logs\32k\D_28000.pth
2023-02-22 08:46:37,027	32k	INFO	====> Epoch: 286
2023-02-22 08:48:23,304	32k	INFO	====> Epoch: 287
2023-02-22 08:49:49,517	32k	INFO	Train Epoch: 288 [76%]
2023-02-22 08:49:49,518	32k	INFO	[2.231926202774048, 2.57316255569458, 16.306894302368164, 19.932767868041992, 0.9207838773727417, 28200, 9.647587177037196e-05]
2023-02-22 08:50:09,780	32k	INFO	====> Epoch: 288
2023-02-22 08:51:56,021	32k	INFO	====> Epoch: 289
2023-02-22 08:53:25,110	32k	INFO	Train Epoch: 290 [80%]
2023-02-22 08:53:25,110	32k	INFO	[2.5337061882019043, 2.4603958129882812, 10.723613739013672, 16.972007751464844, 0.9773488640785217, 28400, 9.645175430986486e-05]
2023-02-22 08:53:41,993	32k	INFO	====> Epoch: 290
2023-02-22 08:55:27,579	32k	INFO	====> Epoch: 291
2023-02-22 08:57:00,042	32k	INFO	Train Epoch: 292 [84%]
2023-02-22 08:57:00,043	32k	INFO	[2.457164764404297, 2.5140910148620605, 12.109970092773438, 19.576763153076172, 0.6455909609794617, 28600, 9.642764287834605e-05]
2023-02-22 08:57:13,617	32k	INFO	====> Epoch: 292
2023-02-22 08:58:59,241	32k	INFO	====> Epoch: 293
2023-02-22 09:00:35,167	32k	INFO	Train Epoch: 294 [88%]
2023-02-22 09:00:35,167	32k	INFO	[3.1267271041870117, 1.7442620992660522, 5.101763725280762, 9.992081642150879, 0.8443043231964111, 28800, 9.640353747430838e-05]
2023-02-22 09:00:45,190	32k	INFO	====> Epoch: 294
2023-02-22 09:02:30,950	32k	INFO	====> Epoch: 295
2023-02-22 09:04:10,463	32k	INFO	Train Epoch: 296 [92%]
2023-02-22 09:04:10,463	32k	INFO	[2.4258294105529785, 2.153702735900879, 11.16634464263916, 18.30190658569336, 0.6709051728248596, 29000, 9.637943809624507e-05]
2023-02-22 09:04:14,772	32k	INFO	Saving model and optimizer state at iteration 296 to ./logs\32k\G_29000.pth
2023-02-22 09:04:30,920	32k	INFO	Saving model and optimizer state at iteration 296 to ./logs\32k\D_29000.pth
2023-02-22 09:04:41,056	32k	INFO	====> Epoch: 296
2023-02-22 09:06:27,402	32k	INFO	====> Epoch: 297
2023-02-22 09:08:10,882	32k	INFO	Train Epoch: 298 [96%]
2023-02-22 09:08:10,882	32k	INFO	[2.3428242206573486, 2.506030559539795, 9.039055824279785, 12.474124908447266, 0.5565758347511292, 29200, 9.635534474264972e-05]
2023-02-22 09:08:13,993	32k	INFO	====> Epoch: 298
2023-02-22 09:10:00,361	32k	INFO	====> Epoch: 299
2023-02-22 09:11:46,836	32k	INFO	====> Epoch: 300
2023-02-22 09:12:10,849	32k	INFO	Train Epoch: 301 [0%]
2023-02-22 09:12:10,849	32k	INFO	[2.0102734565734863, 3.098827838897705, 12.834500312805176, 17.658754348754883, 0.8110590577125549, 29400, 9.631921600483981e-05]
2023-02-22 09:13:34,929	32k	INFO	====> Epoch: 301
2023-02-22 09:15:22,579	32k	INFO	====> Epoch: 302
2023-02-22 09:15:48,125	32k	INFO	Train Epoch: 303 [4%]
2023-02-22 09:15:48,125	32k	INFO	[2.292261838912964, 2.6530299186706543, 15.810569763183594, 19.79923439025879, 0.8924477100372314, 29600, 9.629513770582634e-05]
2023-02-22 09:17:08,489	32k	INFO	====> Epoch: 303
2023-02-22 09:18:54,037	32k	INFO	====> Epoch: 304
2023-02-22 09:19:22,932	32k	INFO	Train Epoch: 305 [8%]
2023-02-22 09:19:22,933	32k	INFO	[2.2535953521728516, 2.7421841621398926, 14.76373291015625, 17.443092346191406, 0.9546372294425964, 29800, 9.627106542601141e-05]
2023-02-22 09:20:39,815	32k	INFO	====> Epoch: 305
2023-02-22 09:22:25,311	32k	INFO	====> Epoch: 306
2023-02-22 09:22:57,677	32k	INFO	Train Epoch: 307 [12%]
2023-02-22 09:22:57,677	32k	INFO	[2.326064109802246, 2.3965041637420654, 7.343259811401367, 12.741463661193848, 0.6292210817337036, 30000, 9.62469991638903e-05]
2023-02-22 09:23:01,921	32k	INFO	Saving model and optimizer state at iteration 307 to ./logs\32k\G_30000.pth
2023-02-22 09:23:20,758	32k	INFO	Saving model and optimizer state at iteration 307 to ./logs\32k\D_30000.pth
2023-02-22 09:24:37,562	32k	INFO	====> Epoch: 307
2023-02-22 09:26:23,740	32k	INFO	====> Epoch: 308
2023-02-22 09:26:59,601	32k	INFO	Train Epoch: 309 [16%]
2023-02-22 09:26:59,601	32k	INFO	[2.4903805255889893, 2.4432358741760254, 9.264269828796387, 16.382070541381836, 0.8371724486351013, 30200, 9.622293891795867e-05]
2023-02-22 09:28:09,664	32k	INFO	====> Epoch: 309
2023-02-22 09:29:55,317	32k	INFO	====> Epoch: 310
2023-02-22 09:30:34,487	32k	INFO	Train Epoch: 311 [20%]
2023-02-22 09:30:34,487	32k	INFO	[2.6089067459106445, 2.180260181427002, 6.335816860198975, 10.976472854614258, 0.98526930809021, 30400, 9.619888468671259e-05]
2023-02-22 09:31:41,120	32k	INFO	====> Epoch: 311
2023-02-22 09:33:27,469	32k	INFO	====> Epoch: 312
2023-02-22 09:34:10,970	32k	INFO	Train Epoch: 313 [24%]
2023-02-22 09:34:10,970	32k	INFO	[2.2308130264282227, 2.525303363800049, 13.083917617797852, 19.732345581054688, 0.6941409707069397, 30600, 9.617483646864849e-05]
2023-02-22 09:35:14,173	32k	INFO	====> Epoch: 313
2023-02-22 09:36:59,697	32k	INFO	====> Epoch: 314
2023-02-22 09:37:45,817	32k	INFO	Train Epoch: 315 [29%]
2023-02-22 09:37:45,818	32k	INFO	[2.5213077068328857, 2.46886944770813, 10.760324478149414, 19.334060668945312, 0.5704622268676758, 30800, 9.615079426226314e-05]
2023-02-22 09:38:45,598	32k	INFO	====> Epoch: 315
2023-02-22 09:40:31,200	32k	INFO	====> Epoch: 316
2023-02-22 09:41:21,493	32k	INFO	Train Epoch: 317 [33%]
2023-02-22 09:41:21,493	32k	INFO	[2.1243271827697754, 2.5788512229919434, 12.918538093566895, 20.69605827331543, 0.9645518064498901, 31000, 9.612675806605373e-05]
2023-02-22 09:41:26,457	32k	INFO	Saving model and optimizer state at iteration 317 to ./logs\32k\G_31000.pth
2023-02-22 09:41:44,385	32k	INFO	Saving model and optimizer state at iteration 317 to ./logs\32k\D_31000.pth
2023-02-22 09:42:44,191	32k	INFO	====> Epoch: 317
2023-02-22 09:44:30,505	32k	INFO	====> Epoch: 318
2023-02-22 09:45:24,342	32k	INFO	Train Epoch: 319 [37%]
2023-02-22 09:45:24,343	32k	INFO	[2.4621365070343018, 2.3512632846832275, 11.532454490661621, 16.673147201538086, 1.0516586303710938, 31200, 9.61027278785178e-05]
2023-02-22 09:46:17,300	32k	INFO	====> Epoch: 319
2023-02-22 09:48:02,873	32k	INFO	====> Epoch: 320
2023-02-22 09:48:59,267	32k	INFO	Train Epoch: 321 [41%]
2023-02-22 09:48:59,267	32k	INFO	[2.293076992034912, 2.460491180419922, 15.437559127807617, 19.99898910522461, 0.8674603700637817, 31400, 9.60787036981533e-05]
2023-02-22 09:49:48,764	32k	INFO	====> Epoch: 321
2023-02-22 09:51:34,708	32k	INFO	====> Epoch: 322
2023-02-22 09:52:34,630	32k	INFO	Train Epoch: 323 [45%]
2023-02-22 09:52:34,630	32k	INFO	[2.3757669925689697, 2.392949104309082, 14.556235313415527, 18.955732345581055, 0.8770878911018372, 31600, 9.60546855234585e-05]
2023-02-22 09:53:20,914	32k	INFO	====> Epoch: 323
2023-02-22 09:55:07,269	32k	INFO	====> Epoch: 324
2023-02-22 09:56:10,506	32k	INFO	Train Epoch: 325 [49%]
2023-02-22 09:56:10,507	32k	INFO	[2.3360633850097656, 2.545222520828247, 11.59161376953125, 17.103670120239258, 0.7123858332633972, 31800, 9.603067335293209e-05]
2023-02-22 09:56:53,220	32k	INFO	====> Epoch: 325
2023-02-22 09:58:38,902	32k	INFO	====> Epoch: 326
2023-02-22 09:59:45,549	32k	INFO	Train Epoch: 327 [53%]
2023-02-22 09:59:45,549	32k	INFO	[2.3887226581573486, 2.382225275039673, 9.169524192810059, 15.562906265258789, 0.9378204345703125, 32000, 9.600666718507311e-05]
2023-02-22 09:59:50,519	32k	INFO	Saving model and optimizer state at iteration 327 to ./logs\32k\G_32000.pth
2023-02-22 10:00:08,092	32k	INFO	Saving model and optimizer state at iteration 327 to ./logs\32k\D_32000.pth
2023-02-22 10:00:50,689	32k	INFO	====> Epoch: 327
2023-02-22 10:02:36,996	32k	INFO	====> Epoch: 328
2023-02-22 10:03:47,898	32k	INFO	Train Epoch: 329 [57%]
2023-02-22 10:03:47,899	32k	INFO	[2.1435623168945312, 2.491894483566284, 13.545025825500488, 17.95233726501465, 0.8276446461677551, 32200, 9.5982667018381e-05]
2023-02-22 10:04:23,585	32k	INFO	====> Epoch: 329
2023-02-22 10:06:09,160	32k	INFO	====> Epoch: 330
2023-02-22 10:07:22,888	32k	INFO	Train Epoch: 331 [61%]
2023-02-22 10:07:22,889	32k	INFO	[2.53352952003479, 2.79293155670166, 10.536802291870117, 17.276477813720703, 0.7348306179046631, 32400, 9.595867285135558e-05]
2023-02-22 10:07:55,166	32k	INFO	====> Epoch: 331
2023-02-22 10:09:54,170	32k	INFO	====> Epoch: 332
2023-02-22 10:11:11,362	32k	INFO	Train Epoch: 333 [65%]
2023-02-22 10:11:11,362	32k	INFO	[2.3337302207946777, 2.2436773777008057, 11.43968391418457, 16.059717178344727, 0.6464142203330994, 32600, 9.5934684682497e-05]
2023-02-22 10:11:40,327	32k	INFO	====> Epoch: 333
2023-02-22 10:13:26,239	32k	INFO	====> Epoch: 334
2023-02-22 10:14:46,735	32k	INFO	Train Epoch: 335 [69%]
2023-02-22 10:14:46,736	32k	INFO	[2.341135025024414, 2.178755044937134, 12.009360313415527, 17.662372589111328, 0.6575217247009277, 32800, 9.591070251030582e-05]
2023-02-22 10:15:12,226	32k	INFO	====> Epoch: 335
2023-02-22 10:16:58,071	32k	INFO	====> Epoch: 336
2023-02-22 10:18:22,210	32k	INFO	Train Epoch: 337 [73%]
2023-02-22 10:18:22,210	32k	INFO	[2.5522103309631348, 2.188314914703369, 10.32480525970459, 15.917875289916992, 0.5481040477752686, 33000, 9.588672633328296e-05]
2023-02-22 10:18:26,497	32k	INFO	Saving model and optimizer state at iteration 337 to ./logs\32k\G_33000.pth
2023-02-22 10:18:44,754	32k	INFO	Saving model and optimizer state at iteration 337 to ./logs\32k\D_33000.pth
2023-02-22 10:19:10,032	32k	INFO	====> Epoch: 337
2023-02-22 10:20:56,519	32k	INFO	====> Epoch: 338
2023-02-22 10:22:23,859	32k	INFO	Train Epoch: 339 [78%]
2023-02-22 10:22:23,859	32k	INFO	[2.4190073013305664, 2.2712206840515137, 11.071868896484375, 18.608346939086914, 1.2736413478851318, 33200, 9.586275614992974e-05]
2023-02-22 10:22:42,496	32k	INFO	====> Epoch: 339
2023-02-22 10:24:28,908	32k	INFO	====> Epoch: 340
2023-02-22 10:26:00,569	32k	INFO	Train Epoch: 341 [82%]
2023-02-22 10:26:00,569	32k	INFO	[2.5759196281433105, 2.485172748565674, 11.334334373474121, 16.11148452758789, 0.9113945364952087, 33400, 9.583879195874782e-05]
2023-02-22 10:26:15,792	32k	INFO	====> Epoch: 341
2023-02-22 10:28:02,420	32k	INFO	====> Epoch: 342
2023-02-22 10:29:37,733	32k	INFO	Train Epoch: 343 [86%]
2023-02-22 10:29:37,733	32k	INFO	[2.478440046310425, 2.6277501583099365, 11.949339866638184, 17.164081573486328, 0.7420394420623779, 33600, 9.581483375823925e-05]
2023-02-22 10:29:49,553	32k	INFO	====> Epoch: 343
2023-02-22 10:31:35,370	32k	INFO	====> Epoch: 344
2023-02-22 10:33:13,278	32k	INFO	Train Epoch: 345 [90%]
2023-02-22 10:33:13,278	32k	INFO	[2.514538288116455, 2.42301344871521, 11.596924781799316, 17.29451560974121, 0.6897502541542053, 33800, 9.579088154690645e-05]
2023-02-22 10:33:21,550	32k	INFO	====> Epoch: 345
2023-02-22 10:35:07,455	32k	INFO	====> Epoch: 346
2023-02-22 10:36:48,752	32k	INFO	Train Epoch: 347 [94%]
2023-02-22 10:36:48,752	32k	INFO	[2.37970232963562, 2.336655378341675, 12.431614875793457, 18.605751037597656, 0.8811375498771667, 34000, 9.576693532325224e-05]
2023-02-22 10:36:53,130	32k	INFO	Saving model and optimizer state at iteration 347 to ./logs\32k\G_34000.pth
2023-02-22 10:37:10,041	32k	INFO	Saving model and optimizer state at iteration 347 to ./logs\32k\D_34000.pth
2023-02-22 10:37:18,304	32k	INFO	====> Epoch: 347
2023-02-22 10:39:05,169	32k	INFO	====> Epoch: 348
2023-02-22 10:40:49,972	32k	INFO	Train Epoch: 349 [98%]
2023-02-22 10:40:49,972	32k	INFO	[2.4378786087036133, 2.316551446914673, 10.715349197387695, 14.96591854095459, 0.5559961199760437, 34200, 9.574299508577979e-05]
2023-02-22 10:40:51,354	32k	INFO	====> Epoch: 349
2023-02-22 10:42:37,890	32k	INFO	====> Epoch: 350
2023-02-22 10:44:24,654	32k	INFO	====> Epoch: 351
2023-02-22 10:44:49,299	32k	INFO	Train Epoch: 352 [2%]
2023-02-22 10:44:49,300	32k	INFO	[2.4335520267486572, 2.271144151687622, 9.197824478149414, 14.361316680908203, 0.9935851693153381, 34400, 9.570709595038851e-05]
2023-02-22 10:46:11,605	32k	INFO	====> Epoch: 352
2023-02-22 10:47:58,244	32k	INFO	====> Epoch: 353
2023-02-22 10:48:25,603	32k	INFO	Train Epoch: 354 [6%]
2023-02-22 10:48:25,604	32k	INFO	[2.503721237182617, 2.299598217010498, 11.784101486206055, 17.45063018798828, 0.7507224678993225, 34600, 9.568317067182427e-05]
2023-02-22 10:49:44,510	32k	INFO	====> Epoch: 354
2023-02-22 10:51:30,297	32k	INFO	====> Epoch: 355
2023-02-22 10:52:01,064	32k	INFO	Train Epoch: 356 [10%]
2023-02-22 10:52:01,064	32k	INFO	[2.358137369155884, 2.391530990600586, 12.17978572845459, 17.948204040527344, 0.6102503538131714, 34800, 9.565925137420586e-05]
2023-02-22 10:53:16,260	32k	INFO	====> Epoch: 356
2023-02-22 10:55:05,634	32k	INFO	====> Epoch: 357
2023-02-22 10:55:40,768	32k	INFO	Train Epoch: 358 [14%]
2023-02-22 10:55:40,768	32k	INFO	[2.742542028427124, 2.216801166534424, 8.76644515991211, 14.839630126953125, 0.49059024453163147, 35000, 9.56353380560381e-05]
2023-02-22 10:55:45,046	32k	INFO	Saving model and optimizer state at iteration 358 to ./logs\32k\G_35000.pth
2023-02-22 10:56:01,246	32k	INFO	Saving model and optimizer state at iteration 358 to ./logs\32k\D_35000.pth
2023-02-22 10:57:17,536	32k	INFO	====> Epoch: 358