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Sovits4.0_Femalesing_G_61000_model

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Sovits4.0_Femalesing_G_61000_model
File size: 133,668 Bytes 
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2023-05-11 17:28:27,327	44k	INFO	{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 400, 'learning_rate': 3e-05, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 4, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 10240, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'use_sr': True, 'max_speclen': 512, 'port': '8001', 'keep_ckpts': 3, 'all_in_mem': False}, 'data': {'training_files': 'filelists/train.txt', 'validation_files': 'filelists/val.txt', 'max_wav_value': 32768.0, 'sampling_rate': 44100, 'filter_length': 2048, 'hop_length': 512, 'win_length': 2048, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': 22050}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [8, 8, 2, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256, 'ssl_dim': 256, 'n_speakers': 1}, 'spk': {'femalesing': 0}, 'model_dir': './logs\\44k'}
2023-05-11 17:28:30,015	44k	INFO	emb_g.weight is not in the checkpoint
2023-05-11 17:28:30,071	44k	INFO	Loaded checkpoint './logs\44k\G_0.pth' (iteration 0)
2023-05-11 17:28:30,262	44k	INFO	Loaded checkpoint './logs\44k\D_0.pth' (iteration 0)
2023-05-11 17:30:19,678	44k	INFO	====> Epoch: 1, cost 112.35 s
2023-05-11 17:30:58,598	44k	INFO	Train Epoch: 2 [30%]
2023-05-11 17:30:58,599	44k	INFO	Losses: [2.459303379058838, 2.457939863204956, 11.619179725646973, 26.335830688476562, 1.3975931406021118], step: 200, lr: 2.999625e-05, reference_loss: 44.26984786987305
2023-05-11 17:31:48,086	44k	INFO	====> Epoch: 2, cost 88.41 s
2023-05-11 17:32:48,236	44k	INFO	Train Epoch: 3 [61%]
2023-05-11 17:32:48,237	44k	INFO	Losses: [2.3206796646118164, 2.5856924057006836, 10.067161560058594, 21.19685935974121, 0.9857438206672668], step: 400, lr: 2.999250046875e-05, reference_loss: 37.1561393737793
2023-05-11 17:33:16,501	44k	INFO	====> Epoch: 3, cost 88.41 s
2023-05-11 17:34:39,920	44k	INFO	Train Epoch: 4 [92%]
2023-05-11 17:34:39,920	44k	INFO	Losses: [2.1731808185577393, 2.8309507369995117, 11.149264335632324, 22.64315414428711, 1.362964391708374], step: 600, lr: 2.9988751406191403e-05, reference_loss: 40.159515380859375
2023-05-11 17:34:46,749	44k	INFO	====> Epoch: 4, cost 90.25 s
2023-05-11 17:36:18,290	44k	INFO	====> Epoch: 5, cost 91.54 s
2023-05-11 17:36:52,410	44k	INFO	Train Epoch: 6 [22%]
2023-05-11 17:36:52,410	44k	INFO	Losses: [2.551401376724243, 2.5483150482177734, 8.768655776977539, 16.717308044433594, 1.1908011436462402], step: 800, lr: 2.9981254686914092e-05, reference_loss: 31.77648162841797
2023-05-11 17:37:47,849	44k	INFO	====> Epoch: 6, cost 89.56 s
2023-05-11 17:38:44,016	44k	INFO	Train Epoch: 7 [53%]
2023-05-11 17:38:44,017	44k	INFO	Losses: [2.39756441116333, 2.3777523040771484, 10.29245662689209, 19.85750389099121, 1.1578614711761475], step: 1000, lr: 2.9977507030078226e-05, reference_loss: 36.08313751220703
2023-05-11 17:38:52,579	44k	INFO	Saving model and optimizer state at iteration 7 to ./logs\44k\G_1000.pth
2023-05-11 17:38:53,383	44k	INFO	Saving model and optimizer state at iteration 7 to ./logs\44k\D_1000.pth
2023-05-11 17:39:27,428	44k	INFO	====> Epoch: 7, cost 99.58 s
2023-05-11 17:40:44,520	44k	INFO	Train Epoch: 8 [84%]
2023-05-11 17:40:44,521	44k	INFO	Losses: [2.1175475120544434, 2.289700746536255, 12.374502182006836, 23.57455825805664, 1.5487251281738281], step: 1200, lr: 2.9973759841699464e-05, reference_loss: 41.905033111572266
2023-05-11 17:40:56,640	44k	INFO	====> Epoch: 8, cost 89.21 s
2023-05-11 17:42:24,787	44k	INFO	====> Epoch: 9, cost 88.15 s
2023-05-11 17:42:53,148	44k	INFO	Train Epoch: 10 [14%]
2023-05-11 17:42:53,149	44k	INFO	Losses: [2.2442078590393066, 2.628319025039673, 12.698528289794922, 21.054655075073242, 0.8923047780990601], step: 1400, lr: 2.996626687007903e-05, reference_loss: 39.51801300048828
2023-05-11 17:43:53,577	44k	INFO	====> Epoch: 10, cost 88.79 s
2023-05-11 17:44:44,237	44k	INFO	Train Epoch: 11 [45%]
2023-05-11 17:44:44,238	44k	INFO	Losses: [2.2357373237609863, 2.2374267578125, 16.44473648071289, 21.65203094482422, 1.452236533164978], step: 1600, lr: 2.996252108672027e-05, reference_loss: 44.02216720581055
2023-05-11 17:45:23,312	44k	INFO	====> Epoch: 11, cost 89.74 s
2023-05-11 17:46:34,958	44k	INFO	Train Epoch: 12 [76%]
2023-05-11 17:46:34,959	44k	INFO	Losses: [2.4033257961273193, 2.455310106277466, 15.984533309936523, 20.990253448486328, 0.9479538798332214], step: 1800, lr: 2.995877577158443e-05, reference_loss: 42.781375885009766
2023-05-11 17:46:52,783	44k	INFO	====> Epoch: 12, cost 89.47 s
2023-05-11 17:48:21,452	44k	INFO	====> Epoch: 13, cost 88.67 s
2023-05-11 17:48:44,209	44k	INFO	Train Epoch: 14 [7%]
2023-05-11 17:48:44,210	44k	INFO	Losses: [2.3698649406433105, 2.3059144020080566, 15.666203498840332, 19.114469528198242, 1.564429759979248], step: 2000, lr: 2.99512865457474e-05, reference_loss: 41.02088165283203
2023-05-11 17:48:49,992	44k	INFO	Saving model and optimizer state at iteration 14 to ./logs\44k\G_2000.pth
2023-05-11 17:48:50,932	44k	INFO	Saving model and optimizer state at iteration 14 to ./logs\44k\D_2000.pth
2023-05-11 17:49:56,815	44k	INFO	====> Epoch: 14, cost 95.36 s
2023-05-11 17:50:40,401	44k	INFO	Train Epoch: 15 [37%]
2023-05-11 17:50:40,402	44k	INFO	Losses: [2.0135385990142822, 2.7587971687316895, 13.319564819335938, 25.564069747924805, 1.4321262836456299], step: 2200, lr: 2.994754263492918e-05, reference_loss: 45.08809280395508
2023-05-11 17:51:24,677	44k	INFO	====> Epoch: 15, cost 87.86 s
2023-05-11 17:52:29,781	44k	INFO	Train Epoch: 16 [68%]
2023-05-11 17:52:29,782	44k	INFO	Losses: [2.4167895317077637, 2.6439528465270996, 12.859883308410645, 18.180147171020508, 1.3307610750198364], step: 2400, lr: 2.9943799192099815e-05, reference_loss: 37.43153381347656
2023-05-11 17:52:52,728	44k	INFO	====> Epoch: 16, cost 88.05 s
2023-05-11 17:54:19,088	44k	INFO	Train Epoch: 17 [99%]
2023-05-11 17:54:19,088	44k	INFO	Losses: [2.302527904510498, 2.3570075035095215, 11.310980796813965, 20.773296356201172, 1.221520185470581], step: 2600, lr: 2.99400562172008e-05, reference_loss: 37.96533203125
2023-05-11 17:54:20,755	44k	INFO	====> Epoch: 17, cost 88.03 s
2023-05-11 17:55:47,722	44k	INFO	====> Epoch: 18, cost 86.97 s
2023-05-11 17:56:25,856	44k	INFO	Train Epoch: 19 [29%]
2023-05-11 17:56:25,856	44k	INFO	Losses: [2.514249801635742, 1.9819296598434448, 18.588764190673828, 22.37004852294922, 1.2551637887954712], step: 2800, lr: 2.9932571670959876e-05, reference_loss: 46.71015930175781
2023-05-11 17:57:15,251	44k	INFO	====> Epoch: 19, cost 87.53 s
2023-05-11 17:58:14,432	44k	INFO	Train Epoch: 20 [60%]
2023-05-11 17:58:14,433	44k	INFO	Losses: [2.0786590576171875, 2.6004528999328613, 13.247485160827637, 22.567167282104492, 1.1914905309677124], step: 3000, lr: 2.9928830099501004e-05, reference_loss: 41.68525695800781
2023-05-11 17:58:20,030	44k	INFO	Saving model and optimizer state at iteration 20 to ./logs\44k\G_3000.pth
2023-05-11 17:58:20,862	44k	INFO	Saving model and optimizer state at iteration 20 to ./logs\44k\D_3000.pth
2023-05-11 17:58:49,526	44k	INFO	====> Epoch: 20, cost 94.28 s
2023-05-11 18:00:10,021	44k	INFO	Train Epoch: 21 [91%]
2023-05-11 18:00:10,022	44k	INFO	Losses: [2.1829042434692383, 2.4404072761535645, 16.241207122802734, 23.569766998291016, 1.1620146036148071], step: 3200, lr: 2.9925088995738566e-05, reference_loss: 45.5963020324707
2023-05-11 18:00:17,017	44k	INFO	====> Epoch: 21, cost 87.49 s
2023-05-11 18:01:44,094	44k	INFO	====> Epoch: 22, cost 87.08 s
2023-05-11 18:02:16,927	44k	INFO	Train Epoch: 23 [22%]
2023-05-11 18:02:16,928	44k	INFO	Losses: [2.1739773750305176, 2.542271137237549, 9.184977531433105, 20.572961807250977, 0.7886731624603271], step: 3400, lr: 2.9917608191069144e-05, reference_loss: 35.26286315917969
2023-05-11 18:03:11,647	44k	INFO	====> Epoch: 23, cost 87.55 s
2023-05-11 18:04:05,707	44k	INFO	Train Epoch: 24 [52%]
2023-05-11 18:04:05,707	44k	INFO	Losses: [2.245553731918335, 2.2225499153137207, 11.099966049194336, 21.631540298461914, 0.9529522061347961], step: 3600, lr: 2.9913868490045258e-05, reference_loss: 38.15256118774414
2023-05-11 18:04:39,317	44k	INFO	====> Epoch: 24, cost 87.67 s
2023-05-11 18:05:54,527	44k	INFO	Train Epoch: 25 [83%]
2023-05-11 18:05:54,528	44k	INFO	Losses: [2.236842632293701, 2.474482536315918, 12.405817031860352, 20.501174926757812, 1.236703872680664], step: 3800, lr: 2.9910129256484002e-05, reference_loss: 38.855018615722656
2023-05-11 18:06:07,854	44k	INFO	====> Epoch: 25, cost 88.54 s
2023-05-11 18:07:35,582	44k	INFO	====> Epoch: 26, cost 87.73 s
2023-05-11 18:08:02,893	44k	INFO	Train Epoch: 27 [14%]
2023-05-11 18:08:02,894	44k	INFO	Losses: [2.184093952178955, 2.6509127616882324, 10.350228309631348, 20.942798614501953, 1.1189231872558594], step: 4000, lr: 2.990265219151565e-05, reference_loss: 37.24695587158203
2023-05-11 18:08:08,561	44k	INFO	Saving model and optimizer state at iteration 27 to ./logs\44k\G_4000.pth
2023-05-11 18:08:09,357	44k	INFO	Saving model and optimizer state at iteration 27 to ./logs\44k\D_4000.pth
2023-05-11 18:08:10,086	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_1000.pth
2023-05-11 18:08:10,120	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_1000.pth
2023-05-11 18:09:10,210	44k	INFO	====> Epoch: 27, cost 94.63 s
2023-05-11 18:09:58,627	44k	INFO	Train Epoch: 28 [44%]
2023-05-11 18:09:58,627	44k	INFO	Losses: [2.2020976543426514, 2.4132113456726074, 12.796091079711914, 21.762636184692383, 1.3702045679092407], step: 4200, lr: 2.989891435999171e-05, reference_loss: 40.54423904418945
2023-05-11 18:10:37,649	44k	INFO	====> Epoch: 28, cost 87.44 s
2023-05-11 18:11:47,312	44k	INFO	Train Epoch: 29 [75%]
2023-05-11 18:11:47,312	44k	INFO	Losses: [2.3617758750915527, 1.72389817237854, 19.052396774291992, 22.682106018066406, 1.1705141067504883], step: 4400, lr: 2.9895176995696712e-05, reference_loss: 46.99068832397461
2023-05-11 18:12:05,196	44k	INFO	====> Epoch: 29, cost 87.55 s
2023-05-11 18:13:32,159	44k	INFO	====> Epoch: 30, cost 86.96 s
2023-05-11 18:13:54,383	44k	INFO	Train Epoch: 31 [6%]
2023-05-11 18:13:54,384	44k	INFO	Losses: [2.4064817428588867, 2.612220525741577, 11.427775382995605, 20.394603729248047, 1.16147780418396], step: 4600, lr: 2.9887703668559927e-05, reference_loss: 38.00255584716797
2023-05-11 18:14:59,912	44k	INFO	====> Epoch: 31, cost 87.75 s
2023-05-11 18:15:42,737	44k	INFO	Train Epoch: 32 [37%]
2023-05-11 18:15:42,738	44k	INFO	Losses: [2.6260833740234375, 2.144500255584717, 7.625936031341553, 18.192829132080078, 0.9529621005058289], step: 4800, lr: 2.9883967705601356e-05, reference_loss: 31.54231071472168
2023-05-11 18:16:27,097	44k	INFO	====> Epoch: 32, cost 87.19 s
2023-05-11 18:17:31,522	44k	INFO	Train Epoch: 33 [67%]
2023-05-11 18:17:31,523	44k	INFO	Losses: [2.3726367950439453, 2.149003028869629, 15.211962699890137, 23.032726287841797, 1.4929637908935547], step: 5000, lr: 2.9880232209638154e-05, reference_loss: 44.25929260253906
2023-05-11 18:17:36,966	44k	INFO	Saving model and optimizer state at iteration 33 to ./logs\44k\G_5000.pth
2023-05-11 18:17:37,757	44k	INFO	Saving model and optimizer state at iteration 33 to ./logs\44k\D_5000.pth
2023-05-11 18:17:38,437	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_2000.pth
2023-05-11 18:17:38,485	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_2000.pth
2023-05-11 18:18:01,515	44k	INFO	====> Epoch: 33, cost 94.42 s
2023-05-11 18:19:26,955	44k	INFO	Train Epoch: 34 [98%]
2023-05-11 18:19:26,956	44k	INFO	Losses: [2.371152400970459, 2.271916627883911, 9.877798080444336, 18.973604202270508, 1.3373123407363892], step: 5200, lr: 2.9876497180611947e-05, reference_loss: 34.831783294677734
2023-05-11 18:19:29,037	44k	INFO	====> Epoch: 34, cost 87.52 s
2023-05-11 18:20:55,986	44k	INFO	====> Epoch: 35, cost 86.95 s
2023-05-11 18:21:33,789	44k	INFO	Train Epoch: 36 [29%]
2023-05-11 18:21:33,790	44k	INFO	Losses: [2.339110851287842, 2.485027313232422, 13.222290992736816, 20.227033615112305, 1.1422102451324463], step: 5400, lr: 2.986902852313706e-05, reference_loss: 39.415672302246094
2023-05-11 18:22:23,762	44k	INFO	====> Epoch: 36, cost 87.78 s
2023-05-11 18:23:22,540	44k	INFO	Train Epoch: 37 [59%]
2023-05-11 18:23:22,540	44k	INFO	Losses: [2.252044200897217, 2.8541438579559326, 11.556214332580566, 22.706714630126953, 1.0304341316223145], step: 5600, lr: 2.9865294894571666e-05, reference_loss: 40.39955139160156
2023-05-11 18:23:51,284	44k	INFO	====> Epoch: 37, cost 87.52 s
2023-05-11 18:25:11,181	44k	INFO	Train Epoch: 38 [90%]
2023-05-11 18:25:11,182	44k	INFO	Losses: [2.7254021167755127, 2.0548441410064697, 10.065361022949219, 19.79765510559082, 1.0936174392700195], step: 5800, lr: 2.9861561732709844e-05, reference_loss: 35.736881256103516
2023-05-11 18:25:18,574	44k	INFO	====> Epoch: 38, cost 87.29 s
2023-05-11 18:26:45,553	44k	INFO	====> Epoch: 39, cost 86.98 s
2023-05-11 18:27:18,143	44k	INFO	Train Epoch: 40 [21%]
2023-05-11 18:27:18,143	44k	INFO	Losses: [2.298049211502075, 2.304781436920166, 15.834815979003906, 19.69129753112793, 0.9392275214195251], step: 6000, lr: 2.9854096808863564e-05, reference_loss: 41.068172454833984
2023-05-11 18:27:23,565	44k	INFO	Saving model and optimizer state at iteration 40 to ./logs\44k\G_6000.pth
2023-05-11 18:27:24,346	44k	INFO	Saving model and optimizer state at iteration 40 to ./logs\44k\D_6000.pth
2023-05-11 18:27:25,075	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_3000.pth
2023-05-11 18:27:25,123	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_3000.pth
2023-05-11 18:28:20,078	44k	INFO	====> Epoch: 40, cost 94.52 s
2023-05-11 18:29:13,590	44k	INFO	Train Epoch: 41 [52%]
2023-05-11 18:29:13,590	44k	INFO	Losses: [2.172698497772217, 2.508707046508789, 12.434700012207031, 20.388547897338867, 1.1035794019699097], step: 6200, lr: 2.9850365046762455e-05, reference_loss: 38.60823440551758
2023-05-11 18:29:47,668	44k	INFO	====> Epoch: 41, cost 87.59 s
2023-05-11 18:31:02,696	44k	INFO	Train Epoch: 42 [82%]
2023-05-11 18:31:02,697	44k	INFO	Losses: [2.413198947906494, 2.318309783935547, 9.818066596984863, 20.27875328063965, 1.2984932661056519], step: 6400, lr: 2.984663375113161e-05, reference_loss: 36.12682342529297
2023-05-11 18:31:15,560	44k	INFO	====> Epoch: 42, cost 87.89 s
2023-05-11 18:32:42,652	44k	INFO	====> Epoch: 43, cost 87.09 s
2023-05-11 18:33:09,513	44k	INFO	Train Epoch: 44 [13%]
2023-05-11 18:33:09,514	44k	INFO	Losses: [2.3417110443115234, 2.698680877685547, 11.552239418029785, 21.030609130859375, 0.9854516983032227], step: 6600, lr: 2.9839172559047475e-05, reference_loss: 38.60869216918945
2023-05-11 18:34:10,178	44k	INFO	====> Epoch: 44, cost 87.53 s
2023-05-11 18:34:58,239	44k	INFO	Train Epoch: 45 [44%]
2023-05-11 18:34:58,239	44k	INFO	Losses: [2.210618019104004, 2.452521800994873, 14.227374076843262, 21.104413986206055, 1.064041256904602], step: 6800, lr: 2.9835442662477594e-05, reference_loss: 41.05896759033203
2023-05-11 18:35:37,810	44k	INFO	====> Epoch: 45, cost 87.63 s
2023-05-11 18:36:47,011	44k	INFO	Train Epoch: 46 [75%]
2023-05-11 18:36:47,012	44k	INFO	Losses: [2.3212857246398926, 2.4168710708618164, 18.990123748779297, 21.611244201660156, 0.761496365070343], step: 7000, lr: 2.9831713232144785e-05, reference_loss: 46.10102081298828
2023-05-11 18:36:52,501	44k	INFO	Saving model and optimizer state at iteration 46 to ./logs\44k\G_7000.pth
2023-05-11 18:36:53,283	44k	INFO	Saving model and optimizer state at iteration 46 to ./logs\44k\D_7000.pth
2023-05-11 18:36:53,992	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_4000.pth
2023-05-11 18:36:54,059	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_4000.pth
2023-05-11 18:37:12,276	44k	INFO	====> Epoch: 46, cost 94.47 s
2023-05-11 18:38:39,461	44k	INFO	====> Epoch: 47, cost 87.18 s
2023-05-11 18:39:01,035	44k	INFO	Train Epoch: 48 [5%]
2023-05-11 18:39:01,035	44k	INFO	Losses: [2.366563320159912, 2.3221383094787598, 11.395698547363281, 22.63437843322754, 1.2375777959823608], step: 7200, lr: 2.9824255769957264e-05, reference_loss: 39.95635986328125
2023-05-11 18:40:07,208	44k	INFO	====> Epoch: 48, cost 87.75 s
2023-05-11 18:40:49,927	44k	INFO	Train Epoch: 49 [36%]
2023-05-11 18:40:49,927	44k	INFO	Losses: [1.917816162109375, 2.801903486251831, 13.9952974319458, 21.37693214416504, 0.8368502259254456], step: 7400, lr: 2.9820527737986018e-05, reference_loss: 40.92879867553711
2023-05-11 18:41:34,807	44k	INFO	====> Epoch: 49, cost 87.60 s
2023-05-11 18:42:38,739	44k	INFO	Train Epoch: 50 [67%]
2023-05-11 18:42:38,740	44k	INFO	Losses: [2.4722514152526855, 2.3414740562438965, 7.378017425537109, 21.898136138916016, 0.9776507019996643], step: 7600, lr: 2.9816800172018767e-05, reference_loss: 35.067527770996094
2023-05-11 18:43:02,384	44k	INFO	====> Epoch: 50, cost 87.58 s
2023-05-11 18:44:27,621	44k	INFO	Train Epoch: 51 [97%]
2023-05-11 18:44:27,622	44k	INFO	Losses: [2.574669122695923, 2.1439828872680664, 13.734928131103516, 23.297380447387695, 0.98489910364151], step: 7800, lr: 2.9813073071997262e-05, reference_loss: 42.73585891723633
2023-05-11 18:44:30,147	44k	INFO	====> Epoch: 51, cost 87.76 s
2023-05-11 18:45:57,248	44k	INFO	====> Epoch: 52, cost 87.10 s
2023-05-11 18:46:34,428	44k	INFO	Train Epoch: 53 [28%]
2023-05-11 18:46:34,428	44k	INFO	Losses: [2.2491679191589355, 2.8051514625549316, 10.986674308776855, 20.51974868774414, 1.1879740953445435], step: 8000, lr: 2.9805620269558528e-05, reference_loss: 37.748714447021484
2023-05-11 18:46:39,870	44k	INFO	Saving model and optimizer state at iteration 53 to ./logs\44k\G_8000.pth
2023-05-11 18:46:40,637	44k	INFO	Saving model and optimizer state at iteration 53 to ./logs\44k\D_8000.pth
2023-05-11 18:46:41,328	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_5000.pth
2023-05-11 18:46:41,384	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_5000.pth
2023-05-11 18:47:31,426	44k	INFO	====> Epoch: 53, cost 94.18 s
2023-05-11 18:48:29,589	44k	INFO	Train Epoch: 54 [59%]
2023-05-11 18:48:29,590	44k	INFO	Losses: [2.4061155319213867, 2.3861169815063477, 16.623397827148438, 22.733078002929688, 1.0733466148376465], step: 8200, lr: 2.980189456702483e-05, reference_loss: 45.22205352783203
2023-05-11 18:48:58,511	44k	INFO	====> Epoch: 54, cost 87.08 s
2023-05-11 18:50:17,689	44k	INFO	Train Epoch: 55 [90%]
2023-05-11 18:50:17,689	44k	INFO	Losses: [2.177870512008667, 2.5902280807495117, 9.996957778930664, 25.31020164489746, 1.3443069458007812], step: 8400, lr: 2.979816933020395e-05, reference_loss: 41.41956329345703
2023-05-11 18:50:25,550	44k	INFO	====> Epoch: 55, cost 87.04 s
2023-05-11 18:51:52,848	44k	INFO	====> Epoch: 56, cost 87.30 s
2023-05-11 18:52:24,812	44k	INFO	Train Epoch: 57 [20%]
2023-05-11 18:52:24,813	44k	INFO	Losses: [2.3480312824249268, 2.4328179359436035, 16.0323429107666, 22.88676643371582, 0.8386507034301758], step: 8600, lr: 2.9790720253467793e-05, reference_loss: 44.53860855102539
2023-05-11 18:53:20,641	44k	INFO	====> Epoch: 57, cost 87.79 s
2023-05-11 18:54:13,521	44k	INFO	Train Epoch: 58 [51%]
2023-05-11 18:54:13,521	44k	INFO	Losses: [2.6255438327789307, 2.2323849201202393, 9.145307540893555, 14.678163528442383, 1.0204851627349854], step: 8800, lr: 2.9786996413436108e-05, reference_loss: 29.701885223388672
2023-05-11 18:54:48,105	44k	INFO	====> Epoch: 58, cost 87.46 s
2023-05-11 18:56:01,926	44k	INFO	Train Epoch: 59 [82%]
2023-05-11 18:56:01,927	44k	INFO	Losses: [2.2011358737945557, 2.3508758544921875, 15.927428245544434, 19.570165634155273, 0.9381687045097351], step: 9000, lr: 2.9783273038884426e-05, reference_loss: 40.98777389526367
2023-05-11 18:56:07,433	44k	INFO	Saving model and optimizer state at iteration 59 to ./logs\44k\G_9000.pth
2023-05-11 18:56:08,293	44k	INFO	Saving model and optimizer state at iteration 59 to ./logs\44k\D_9000.pth
2023-05-11 18:56:08,964	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_6000.pth
2023-05-11 18:56:09,013	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_6000.pth
2023-05-11 18:56:22,005	44k	INFO	====> Epoch: 59, cost 93.90 s
2023-05-11 18:57:48,958	44k	INFO	====> Epoch: 60, cost 86.95 s
2023-05-11 18:58:15,278	44k	INFO	Train Epoch: 61 [12%]
2023-05-11 18:58:15,279	44k	INFO	Losses: [2.1734931468963623, 2.584578275680542, 11.054624557495117, 16.684263229370117, 0.951940655708313], step: 9200, lr: 2.9775827685988343e-05, reference_loss: 33.44890213012695
2023-05-11 18:59:16,156	44k	INFO	====> Epoch: 61, cost 87.20 s
2023-05-11 19:00:03,620	44k	INFO	Train Epoch: 62 [43%]
2023-05-11 19:00:03,621	44k	INFO	Losses: [2.3306589126586914, 2.431523084640503, 10.049124717712402, 19.96187400817871, 1.3222295045852661], step: 9400, lr: 2.9772105707527593e-05, reference_loss: 36.09541320800781
2023-05-11 19:00:43,601	44k	INFO	====> Epoch: 62, cost 87.44 s
2023-05-11 19:01:52,336	44k	INFO	Train Epoch: 63 [74%]
2023-05-11 19:01:52,337	44k	INFO	Losses: [2.3950185775756836, 2.203678846359253, 12.203329086303711, 18.860929489135742, 1.291874647140503], step: 9600, lr: 2.976838419431415e-05, reference_loss: 36.954830169677734
2023-05-11 19:02:11,088	44k	INFO	====> Epoch: 63, cost 87.49 s
2023-05-11 19:03:37,831	44k	INFO	====> Epoch: 64, cost 86.74 s
2023-05-11 19:03:58,879	44k	INFO	Train Epoch: 65 [5%]
2023-05-11 19:03:58,879	44k	INFO	Losses: [2.2784037590026855, 2.095527410507202, 15.206583976745605, 21.7014102935791, 0.9693368077278137], step: 9800, lr: 2.9760942563396572e-05, reference_loss: 42.25126266479492
2023-05-11 19:05:05,336	44k	INFO	====> Epoch: 65, cost 87.51 s
2023-05-11 19:05:47,432	44k	INFO	Train Epoch: 66 [35%]
2023-05-11 19:05:47,432	44k	INFO	Losses: [2.3025805950164795, 2.8782596588134766, 15.639361381530762, 19.169925689697266, 1.2433959245681763], step: 10000, lr: 2.9757222445576146e-05, reference_loss: 41.233524322509766
2023-05-11 19:05:52,892	44k	INFO	Saving model and optimizer state at iteration 66 to ./logs\44k\G_10000.pth
2023-05-11 19:05:53,797	44k	INFO	Saving model and optimizer state at iteration 66 to ./logs\44k\D_10000.pth
2023-05-11 19:05:54,473	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_7000.pth
2023-05-11 19:05:54,522	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_7000.pth
2023-05-11 19:06:39,537	44k	INFO	====> Epoch: 66, cost 94.20 s
2023-05-11 19:07:44,297	44k	INFO	Train Epoch: 67 [66%]
2023-05-11 19:07:44,298	44k	INFO	Losses: [2.392963171005249, 2.511087656021118, 8.105061531066895, 17.21589469909668, 0.5810514688491821], step: 10200, lr: 2.975350279277045e-05, reference_loss: 30.80605697631836
2023-05-11 19:08:08,457	44k	INFO	====> Epoch: 67, cost 88.92 s
2023-05-11 19:09:33,331	44k	INFO	Train Epoch: 68 [97%]
2023-05-11 19:09:33,331	44k	INFO	Losses: [2.5744566917419434, 2.324415683746338, 9.892423629760742, 19.85940170288086, 0.9389864802360535], step: 10400, lr: 2.974978360492135e-05, reference_loss: 35.589683532714844
2023-05-11 19:09:36,256	44k	INFO	====> Epoch: 68, cost 87.80 s
2023-05-11 19:11:03,181	44k	INFO	====> Epoch: 69, cost 86.93 s
2023-05-11 19:11:40,015	44k	INFO	Train Epoch: 70 [27%]
2023-05-11 19:11:40,016	44k	INFO	Losses: [2.488396644592285, 2.707859516143799, 14.608697891235352, 21.44941520690918, 1.1219513416290283], step: 10600, lr: 2.9742346623860485e-05, reference_loss: 42.37632369995117
2023-05-11 19:12:30,628	44k	INFO	====> Epoch: 70, cost 87.45 s
2023-05-11 19:13:28,481	44k	INFO	Train Epoch: 71 [58%]
2023-05-11 19:13:28,481	44k	INFO	Losses: [2.483287811279297, 2.5775985717773438, 10.276037216186523, 20.905624389648438, 0.6530118584632874], step: 10800, lr: 2.97386288305325e-05, reference_loss: 36.89555740356445
2023-05-11 19:13:58,002	44k	INFO	====> Epoch: 71, cost 87.37 s
2023-05-11 19:15:17,288	44k	INFO	Train Epoch: 72 [89%]
2023-05-11 19:15:17,288	44k	INFO	Losses: [2.332808256149292, 2.448483943939209, 10.965472221374512, 20.244462966918945, 0.8521516919136047], step: 11000, lr: 2.9734911501928684e-05, reference_loss: 36.84337615966797
2023-05-11 19:15:22,859	44k	INFO	Saving model and optimizer state at iteration 72 to ./logs\44k\G_11000.pth
2023-05-11 19:15:23,565	44k	INFO	Saving model and optimizer state at iteration 72 to ./logs\44k\D_11000.pth
2023-05-11 19:15:24,311	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_8000.pth
2023-05-11 19:15:24,376	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_8000.pth
2023-05-11 19:15:32,429	44k	INFO	====> Epoch: 72, cost 94.43 s
2023-05-11 19:16:59,201	44k	INFO	====> Epoch: 73, cost 86.77 s
2023-05-11 19:17:30,453	44k	INFO	Train Epoch: 74 [20%]
2023-05-11 19:17:30,453	44k	INFO	Losses: [2.266490936279297, 2.3601906299591064, 17.345029830932617, 20.298904418945312, 0.45651742815971375], step: 11200, lr: 2.9727478238661192e-05, reference_loss: 42.72713088989258
2023-05-11 19:18:26,748	44k	INFO	====> Epoch: 74, cost 87.55 s
2023-05-11 19:19:19,140	44k	INFO	Train Epoch: 75 [50%]
2023-05-11 19:19:19,140	44k	INFO	Losses: [2.2988176345825195, 2.9386768341064453, 9.981624603271484, 24.409568786621094, 1.1511999368667603], step: 11400, lr: 2.9723762303881358e-05, reference_loss: 40.77988815307617
2023-05-11 19:19:54,162	44k	INFO	====> Epoch: 75, cost 87.41 s
2023-05-11 19:21:07,995	44k	INFO	Train Epoch: 76 [81%]
2023-05-11 19:21:07,995	44k	INFO	Losses: [2.527557611465454, 2.5391311645507812, 13.923425674438477, 20.909971237182617, 0.9973414540290833], step: 11600, lr: 2.9720046833593373e-05, reference_loss: 40.89742660522461
2023-05-11 19:21:21,624	44k	INFO	====> Epoch: 76, cost 87.46 s
2023-05-11 19:22:48,916	44k	INFO	====> Epoch: 77, cost 87.29 s
2023-05-11 19:23:14,944	44k	INFO	Train Epoch: 78 [12%]
2023-05-11 19:23:14,944	44k	INFO	Losses: [2.127185344696045, 3.0148720741271973, 13.057185173034668, 21.26051139831543, 1.0786174535751343], step: 11800, lr: 2.9712617286260704e-05, reference_loss: 40.53837203979492
2023-05-11 19:24:16,477	44k	INFO	====> Epoch: 78, cost 87.56 s
2023-05-11 19:25:03,454	44k	INFO	Train Epoch: 79 [42%]
2023-05-11 19:25:03,455	44k	INFO	Losses: [2.5826191902160645, 2.7334704399108887, 11.021053314208984, 20.000476837158203, 1.2514795064926147], step: 12000, lr: 2.970890320909992e-05, reference_loss: 37.5890998840332
2023-05-11 19:25:08,989	44k	INFO	Saving model and optimizer state at iteration 79 to ./logs\44k\G_12000.pth
2023-05-11 19:25:09,758	44k	INFO	Saving model and optimizer state at iteration 79 to ./logs\44k\D_12000.pth
2023-05-11 19:25:10,427	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_9000.pth
2023-05-11 19:25:10,490	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_9000.pth
2023-05-11 19:25:50,533	44k	INFO	====> Epoch: 79, cost 94.06 s
2023-05-11 19:26:58,862	44k	INFO	Train Epoch: 80 [73%]
2023-05-11 19:26:58,863	44k	INFO	Losses: [2.1584227085113525, 2.5675315856933594, 14.528108596801758, 21.469886779785156, 1.04828941822052], step: 12200, lr: 2.970518959619878e-05, reference_loss: 41.772239685058594
2023-05-11 19:27:17,906	44k	INFO	====> Epoch: 80, cost 87.37 s
2023-05-11 19:28:44,748	44k	INFO	====> Epoch: 81, cost 86.84 s
2023-05-11 19:29:05,252	44k	INFO	Train Epoch: 82 [4%]
2023-05-11 19:29:05,253	44k	INFO	Losses: [2.5995869636535645, 2.3246142864227295, 17.80889892578125, 20.148639678955078, 0.9023404717445374], step: 12400, lr: 2.9697763762943315e-05, reference_loss: 43.784080505371094
2023-05-11 19:30:11,883	44k	INFO	====> Epoch: 82, cost 87.14 s
2023-05-11 19:30:53,748	44k	INFO	Train Epoch: 83 [35%]
2023-05-11 19:30:53,749	44k	INFO	Losses: [2.0636746883392334, 2.799551486968994, 14.208065032958984, 22.287092208862305, 1.1652652025222778], step: 12600, lr: 2.9694051542472947e-05, reference_loss: 42.52364730834961
2023-05-11 19:31:40,630	44k	INFO	====> Epoch: 83, cost 88.75 s
2023-05-11 19:32:44,546	44k	INFO	Train Epoch: 84 [65%]
2023-05-11 19:32:44,547	44k	INFO	Losses: [1.850412368774414, 2.7066690921783447, 12.541053771972656, 21.48491859436035, 1.3602120876312256], step: 12800, lr: 2.969033978603014e-05, reference_loss: 39.94326400756836
2023-05-11 19:33:09,279	44k	INFO	====> Epoch: 84, cost 88.65 s
2023-05-11 19:34:34,197	44k	INFO	Train Epoch: 85 [96%]
2023-05-11 19:34:34,197	44k	INFO	Losses: [2.495619773864746, 2.312445878982544, 10.466293334960938, 20.584941864013672, 1.1275739669799805], step: 13000, lr: 2.9686628493556884e-05, reference_loss: 36.986873626708984
2023-05-11 19:34:39,692	44k	INFO	Saving model and optimizer state at iteration 85 to ./logs\44k\G_13000.pth
2023-05-11 19:34:40,481	44k	INFO	Saving model and optimizer state at iteration 85 to ./logs\44k\D_13000.pth
2023-05-11 19:34:41,154	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_10000.pth
2023-05-11 19:34:41,208	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_10000.pth
2023-05-11 19:34:44,305	44k	INFO	====> Epoch: 85, cost 95.03 s
2023-05-11 19:36:12,496	44k	INFO	====> Epoch: 86, cost 88.19 s
2023-05-11 19:36:49,953	44k	INFO	Train Epoch: 87 [27%]
2023-05-11 19:36:49,953	44k	INFO	Losses: [2.5500364303588867, 1.8523938655853271, 14.750356674194336, 21.896915435791016, 1.2302916049957275], step: 13200, lr: 2.9679207300287062e-05, reference_loss: 42.27999496459961
2023-05-11 19:37:41,819	44k	INFO	====> Epoch: 87, cost 89.32 s
2023-05-11 19:38:40,093	44k	INFO	Train Epoch: 88 [58%]
2023-05-11 19:38:40,094	44k	INFO	Losses: [2.64554500579834, 2.655510425567627, 8.941330909729004, 19.124576568603516, 0.9901910424232483], step: 13400, lr: 2.9675497399374526e-05, reference_loss: 34.357154846191406
2023-05-11 19:39:10,403	44k	INFO	====> Epoch: 88, cost 88.58 s
2023-05-11 19:40:29,680	44k	INFO	Train Epoch: 89 [88%]
2023-05-11 19:40:29,681	44k	INFO	Losses: [2.1685872077941895, 2.8226051330566406, 9.624245643615723, 17.96548080444336, 1.2596955299377441], step: 13600, lr: 2.9671787962199603e-05, reference_loss: 33.840614318847656
2023-05-11 19:40:38,485	44k	INFO	====> Epoch: 89, cost 88.08 s
2023-05-11 19:42:06,129	44k	INFO	====> Epoch: 90, cost 87.64 s
2023-05-11 19:42:37,038	44k	INFO	Train Epoch: 91 [19%]
2023-05-11 19:42:37,039	44k	INFO	Losses: [2.3471243381500244, 2.4963676929473877, 14.549406051635742, 20.984949111938477, 0.8281876444816589], step: 13800, lr: 2.9664370478830735e-05, reference_loss: 41.206031799316406
2023-05-11 19:43:34,222	44k	INFO	====> Epoch: 91, cost 88.09 s
2023-05-11 19:44:26,720	44k	INFO	Train Epoch: 92 [50%]
2023-05-11 19:44:26,720	44k	INFO	Losses: [2.346712112426758, 2.598132848739624, 11.195423126220703, 21.27674102783203, 0.7020501494407654], step: 14000, lr: 2.966066243252088e-05, reference_loss: 38.119056701660156
2023-05-11 19:44:32,332	44k	INFO	Saving model and optimizer state at iteration 92 to ./logs\44k\G_14000.pth
2023-05-11 19:44:33,144	44k	INFO	Saving model and optimizer state at iteration 92 to ./logs\44k\D_14000.pth
2023-05-11 19:44:33,866	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_11000.pth
2023-05-11 19:44:33,911	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_11000.pth
2023-05-11 19:45:09,311	44k	INFO	====> Epoch: 92, cost 95.09 s
2023-05-11 19:46:23,090	44k	INFO	Train Epoch: 93 [80%]
2023-05-11 19:46:23,091	44k	INFO	Losses: [2.3515446186065674, 1.9654158353805542, 17.901376724243164, 19.525684356689453, 0.574507474899292], step: 14200, lr: 2.9656954849716813e-05, reference_loss: 42.31853103637695
2023-05-11 19:46:37,427	44k	INFO	====> Epoch: 93, cost 88.12 s
2023-05-11 19:48:04,411	44k	INFO	====> Epoch: 94, cost 86.98 s
2023-05-11 19:48:29,911	44k	INFO	Train Epoch: 95 [11%]
2023-05-11 19:48:29,912	44k	INFO	Losses: [2.6377267837524414, 1.9331278800964355, 11.104305267333984, 18.165645599365234, 0.9207220077514648], step: 14400, lr: 2.96495410743943e-05, reference_loss: 34.76152801513672
2023-05-11 19:49:31,785	44k	INFO	====> Epoch: 95, cost 87.37 s
2023-05-11 19:50:18,309	44k	INFO	Train Epoch: 96 [42%]
2023-05-11 19:50:18,310	44k	INFO	Losses: [2.4666552543640137, 2.3607218265533447, 15.385420799255371, 20.539506912231445, 0.9757711291313171], step: 14600, lr: 2.964583488176e-05, reference_loss: 41.72807693481445
2023-05-11 19:50:59,089	44k	INFO	====> Epoch: 96, cost 87.30 s
2023-05-11 19:52:06,944	44k	INFO	Train Epoch: 97 [73%]
2023-05-11 19:52:06,945	44k	INFO	Losses: [2.388150453567505, 2.35262393951416, 9.621209144592285, 18.28777503967285, 0.8167867064476013], step: 14800, lr: 2.964212915239978e-05, reference_loss: 33.46654510498047
2023-05-11 19:52:26,660	44k	INFO	====> Epoch: 97, cost 87.57 s
2023-05-11 19:53:53,595	44k	INFO	====> Epoch: 98, cost 86.93 s
2023-05-11 19:54:13,639	44k	INFO	Train Epoch: 99 [3%]
2023-05-11 19:54:13,640	44k	INFO	Losses: [1.984534740447998, 2.543687582015991, 15.23721694946289, 21.18869972229004, 1.470950722694397], step: 15000, lr: 2.9634719083269944e-05, reference_loss: 42.42509078979492
2023-05-11 19:54:19,066	44k	INFO	Saving model and optimizer state at iteration 99 to ./logs\44k\G_15000.pth
2023-05-11 19:54:19,911	44k	INFO	Saving model and optimizer state at iteration 99 to ./logs\44k\D_15000.pth
2023-05-11 19:54:20,620	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_12000.pth
2023-05-11 19:54:20,672	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_12000.pth
2023-05-11 19:55:27,566	44k	INFO	====> Epoch: 99, cost 93.97 s
2023-05-11 19:56:08,663	44k	INFO	Train Epoch: 100 [34%]
2023-05-11 19:56:08,664	44k	INFO	Losses: [2.5254507064819336, 2.147777795791626, 8.379581451416016, 16.67535972595215, 0.7880470752716064], step: 15200, lr: 2.9631014743384534e-05, reference_loss: 30.516216278076172
2023-05-11 19:56:54,799	44k	INFO	====> Epoch: 100, cost 87.23 s
2023-05-11 19:57:56,853	44k	INFO	Train Epoch: 101 [65%]
2023-05-11 19:57:56,854	44k	INFO	Losses: [2.240133762359619, 2.652489423751831, 9.347786903381348, 21.02147102355957, 1.0434813499450684], step: 15400, lr: 2.962731086654161e-05, reference_loss: 36.30535888671875
2023-05-11 19:58:21,835	44k	INFO	====> Epoch: 101, cost 87.04 s
2023-05-11 19:59:45,148	44k	INFO	Train Epoch: 102 [95%]
2023-05-11 19:59:45,148	44k	INFO	Losses: [2.4462976455688477, 2.6302003860473633, 8.536848068237305, 15.693955421447754, 0.7916440367698669], step: 15600, lr: 2.9623607452683292e-05, reference_loss: 30.09894371032715
2023-05-11 19:59:49,039	44k	INFO	====> Epoch: 102, cost 87.20 s
2023-05-11 20:01:15,908	44k	INFO	====> Epoch: 103, cost 86.87 s
2023-05-11 20:01:51,737	44k	INFO	Train Epoch: 104 [26%]
2023-05-11 20:01:51,738	44k	INFO	Losses: [2.699462413787842, 2.119377613067627, 8.909375190734863, 14.585592269897461, 1.0882903337478638], step: 15800, lr: 2.9616202013688986e-05, reference_loss: 29.402099609375
2023-05-11 20:02:43,470	44k	INFO	====> Epoch: 104, cost 87.56 s
2023-05-11 20:03:40,359	44k	INFO	Train Epoch: 105 [57%]
2023-05-11 20:03:40,359	44k	INFO	Losses: [2.6297519207000732, 2.1645867824554443, 11.145780563354492, 19.97608757019043, 1.0075565576553345], step: 16000, lr: 2.9612499988437273e-05, reference_loss: 36.923763275146484
2023-05-11 20:03:45,836	44k	INFO	Saving model and optimizer state at iteration 105 to ./logs\44k\G_16000.pth
2023-05-11 20:03:46,604	44k	INFO	Saving model and optimizer state at iteration 105 to ./logs\44k\D_16000.pth
2023-05-11 20:03:47,277	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_13000.pth
2023-05-11 20:03:47,328	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_13000.pth
2023-05-11 20:04:17,693	44k	INFO	====> Epoch: 105, cost 94.22 s
2023-05-11 20:05:35,560	44k	INFO	Train Epoch: 106 [88%]
2023-05-11 20:05:35,561	44k	INFO	Losses: [1.8554573059082031, 2.7442054748535156, 15.099529266357422, 21.0919246673584, 1.2479524612426758], step: 16200, lr: 2.9608798425938718e-05, reference_loss: 42.039066314697266
2023-05-11 20:05:44,910	44k	INFO	====> Epoch: 106, cost 87.22 s
2023-05-11 20:07:12,228	44k	INFO	====> Epoch: 107, cost 87.32 s
2023-05-11 20:07:42,475	44k	INFO	Train Epoch: 108 [18%]
2023-05-11 20:07:42,476	44k	INFO	Losses: [2.597095489501953, 2.517559289932251, 14.315872192382812, 20.4267520904541, 0.7586858868598938], step: 16400, lr: 2.9601396688969708e-05, reference_loss: 40.615962982177734
2023-05-11 20:08:39,468	44k	INFO	====> Epoch: 108, cost 87.24 s
2023-05-11 20:09:30,983	44k	INFO	Train Epoch: 109 [49%]
2023-05-11 20:09:30,984	44k	INFO	Losses: [2.188152313232422, 2.4814181327819824, 17.63176918029785, 21.54877281188965, 1.0282224416732788], step: 16600, lr: 2.9597696514383585e-05, reference_loss: 44.878334045410156
2023-05-11 20:10:06,850	44k	INFO	====> Epoch: 109, cost 87.38 s
2023-05-11 20:11:19,388	44k	INFO	Train Epoch: 110 [80%]
2023-05-11 20:11:19,388	44k	INFO	Losses: [1.9795849323272705, 2.3055872917175293, 17.153779983520508, 22.12401580810547, 0.7317075729370117], step: 16800, lr: 2.9593996802319285e-05, reference_loss: 44.294677734375
2023-05-11 20:11:34,109	44k	INFO	====> Epoch: 110, cost 87.26 s
2023-05-11 20:13:01,272	44k	INFO	====> Epoch: 111, cost 87.16 s
2023-05-11 20:13:26,312	44k	INFO	Train Epoch: 112 [10%]
2023-05-11 20:13:26,313	44k	INFO	Losses: [2.044874429702759, 3.0220160484313965, 12.554776191711426, 20.511953353881836, 1.0727452039718628], step: 17000, lr: 2.9586598765524905e-05, reference_loss: 39.20636749267578
2023-05-11 20:13:31,898	44k	INFO	Saving model and optimizer state at iteration 112 to ./logs\44k\G_17000.pth
2023-05-11 20:13:32,675	44k	INFO	Saving model and optimizer state at iteration 112 to ./logs\44k\D_17000.pth
2023-05-11 20:13:33,351	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_14000.pth
2023-05-11 20:13:33,407	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_14000.pth
2023-05-11 20:14:35,620	44k	INFO	====> Epoch: 112, cost 94.35 s
2023-05-11 20:15:21,915	44k	INFO	Train Epoch: 113 [41%]
2023-05-11 20:15:21,916	44k	INFO	Losses: [2.434295177459717, 2.4613468647003174, 12.294702529907227, 19.085464477539062, 0.938558042049408], step: 17200, lr: 2.9582900440679212e-05, reference_loss: 37.2143669128418
2023-05-11 20:16:03,071	44k	INFO	====> Epoch: 113, cost 87.45 s
2023-05-11 20:17:10,257	44k	INFO	Train Epoch: 114 [72%]
2023-05-11 20:17:10,257	44k	INFO	Losses: [2.215301990509033, 2.9431910514831543, 11.858352661132812, 22.097923278808594, 0.8659520149230957], step: 17400, lr: 2.9579202578124125e-05, reference_loss: 39.98072052001953
2023-05-11 20:17:30,308	44k	INFO	====> Epoch: 114, cost 87.24 s
2023-05-11 20:18:56,931	44k	INFO	====> Epoch: 115, cost 86.62 s
2023-05-11 20:19:16,680	44k	INFO	Train Epoch: 116 [3%]
2023-05-11 20:19:16,681	44k	INFO	Losses: [2.2416772842407227, 2.399442672729492, 10.596750259399414, 20.50092887878418, 0.9194076061248779], step: 17600, lr: 2.9571808239654632e-05, reference_loss: 36.658206939697266
2023-05-11 20:20:24,523	44k	INFO	====> Epoch: 116, cost 87.59 s
2023-05-11 20:21:05,027	44k	INFO	Train Epoch: 117 [33%]
2023-05-11 20:21:05,027	44k	INFO	Losses: [2.1417291164398193, 2.6440353393554688, 17.073688507080078, 21.75315284729004, 0.8988870978355408], step: 17800, lr: 2.9568111763624674e-05, reference_loss: 44.51149368286133
2023-05-11 20:21:51,795	44k	INFO	====> Epoch: 117, cost 87.27 s
2023-05-11 20:22:54,037	44k	INFO	Train Epoch: 118 [64%]
2023-05-11 20:22:54,038	44k	INFO	Losses: [2.687147855758667, 2.2581987380981445, 9.520541191101074, 17.402111053466797, 0.769197940826416], step: 18000, lr: 2.956441574965422e-05, reference_loss: 32.63719940185547
2023-05-11 20:22:59,496	44k	INFO	Saving model and optimizer state at iteration 118 to ./logs\44k\G_18000.pth
2023-05-11 20:23:00,419	44k	INFO	Saving model and optimizer state at iteration 118 to ./logs\44k\D_18000.pth
2023-05-11 20:23:01,156	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_15000.pth
2023-05-11 20:23:01,198	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_15000.pth
2023-05-11 20:23:26,576	44k	INFO	====> Epoch: 118, cost 94.78 s
2023-05-11 20:24:49,791	44k	INFO	Train Epoch: 119 [95%]
2023-05-11 20:24:49,791	44k	INFO	Losses: [2.2016706466674805, 2.342021942138672, 15.455516815185547, 21.393728256225586, 1.2339255809783936], step: 18200, lr: 2.956072019768551e-05, reference_loss: 42.626861572265625
2023-05-11 20:24:54,103	44k	INFO	====> Epoch: 119, cost 87.53 s
2023-05-11 20:26:21,161	44k	INFO	====> Epoch: 120, cost 87.06 s
2023-05-11 20:26:56,437	44k	INFO	Train Epoch: 121 [25%]
2023-05-11 20:26:56,437	44k	INFO	Losses: [2.3297619819641113, 2.582425832748413, 13.432904243469238, 20.049182891845703, 0.7440981268882751], step: 18400, lr: 2.955333047952234e-05, reference_loss: 39.13837432861328
2023-05-11 20:27:48,547	44k	INFO	====> Epoch: 121, cost 87.39 s
2023-05-11 20:28:44,925	44k	INFO	Train Epoch: 122 [56%]
2023-05-11 20:28:44,926	44k	INFO	Losses: [2.501075267791748, 2.19102144241333, 13.667943954467773, 19.5328426361084, 0.7769325375556946], step: 18600, lr: 2.95496363132124e-05, reference_loss: 38.66981506347656
2023-05-11 20:29:15,885	44k	INFO	====> Epoch: 122, cost 87.34 s
2023-05-11 20:30:33,638	44k	INFO	Train Epoch: 123 [87%]
2023-05-11 20:30:33,639	44k	INFO	Losses: [2.3140921592712402, 2.098410129547119, 10.938791275024414, 19.268470764160156, 0.7637777328491211], step: 18800, lr: 2.9545942608673247e-05, reference_loss: 35.383544921875
2023-05-11 20:30:43,311	44k	INFO	====> Epoch: 123, cost 87.43 s
2023-05-11 20:32:10,306	44k	INFO	====> Epoch: 124, cost 86.99 s
2023-05-11 20:32:40,448	44k	INFO	Train Epoch: 125 [18%]
2023-05-11 20:32:40,448	44k	INFO	Losses: [2.407294750213623, 2.710339307785034, 10.570150375366211, 18.655397415161133, 0.9011021852493286], step: 19000, lr: 2.953855658467643e-05, reference_loss: 35.244285583496094
2023-05-11 20:32:45,953	44k	INFO	Saving model and optimizer state at iteration 125 to ./logs\44k\G_19000.pth
2023-05-11 20:32:46,856	44k	INFO	Saving model and optimizer state at iteration 125 to ./logs\44k\D_19000.pth
2023-05-11 20:32:47,542	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_16000.pth
2023-05-11 20:32:47,592	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_16000.pth
2023-05-11 20:33:44,984	44k	INFO	====> Epoch: 125, cost 94.68 s
2023-05-11 20:34:36,290	44k	INFO	Train Epoch: 126 [48%]
2023-05-11 20:34:36,290	44k	INFO	Losses: [2.410686492919922, 2.1409695148468018, 11.722865104675293, 19.613075256347656, 1.1722275018692017], step: 19200, lr: 2.9534864265103344e-05, reference_loss: 37.05982208251953
2023-05-11 20:35:12,573	44k	INFO	====> Epoch: 126, cost 87.59 s
2023-05-11 20:36:24,759	44k	INFO	Train Epoch: 127 [79%]
2023-05-11 20:36:24,760	44k	INFO	Losses: [2.2939276695251465, 2.3239898681640625, 11.148547172546387, 20.177614212036133, 0.987168550491333], step: 19400, lr: 2.9531172407070204e-05, reference_loss: 36.931243896484375
2023-05-11 20:36:39,894	44k	INFO	====> Epoch: 127, cost 87.32 s
2023-05-11 20:38:06,742	44k	INFO	====> Epoch: 128, cost 86.85 s
2023-05-11 20:38:31,130	44k	INFO	Train Epoch: 129 [10%]
2023-05-11 20:38:31,131	44k	INFO	Losses: [2.185370922088623, 2.5441622734069824, 14.028510093688965, 20.407976150512695, 0.8030586838722229], step: 19600, lr: 2.9523790075393003e-05, reference_loss: 39.969078063964844
2023-05-11 20:39:33,973	44k	INFO	====> Epoch: 129, cost 87.23 s
2023-05-11 20:40:19,634	44k	INFO	Train Epoch: 130 [41%]
2023-05-11 20:40:19,634	44k	INFO	Losses: [1.8971433639526367, 2.641223430633545, 13.486212730407715, 22.607393264770508, 1.0836613178253174], step: 19800, lr: 2.9520099601633577e-05, reference_loss: 41.715633392333984
2023-05-11 20:41:01,428	44k	INFO	====> Epoch: 130, cost 87.46 s
2023-05-11 20:42:08,322	44k	INFO	Train Epoch: 131 [71%]
2023-05-11 20:42:08,322	44k	INFO	Losses: [2.403357744216919, 2.1612229347229004, 11.346234321594238, 21.16708755493164, 0.9038617610931396], step: 20000, lr: 2.951640958918337e-05, reference_loss: 37.98176574707031
2023-05-11 20:42:13,815	44k	INFO	Saving model and optimizer state at iteration 131 to ./logs\44k\G_20000.pth
2023-05-11 20:42:14,586	44k	INFO	Saving model and optimizer state at iteration 131 to ./logs\44k\D_20000.pth
2023-05-11 20:42:15,260	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_17000.pth
2023-05-11 20:42:15,324	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_17000.pth
2023-05-11 20:42:35,558	44k	INFO	====> Epoch: 131, cost 94.13 s
2023-05-11 20:44:02,788	44k	INFO	====> Epoch: 132, cost 87.23 s
2023-05-11 20:44:22,083	44k	INFO	Train Epoch: 133 [2%]
2023-05-11 20:44:22,084	44k	INFO	Losses: [2.41817045211792, 2.128247022628784, 11.941383361816406, 16.322542190551758, 0.667270839214325], step: 20200, lr: 2.9509030947979973e-05, reference_loss: 33.47761154174805
2023-05-11 20:45:30,287	44k	INFO	====> Epoch: 133, cost 87.50 s
2023-05-11 20:46:10,643	44k	INFO	Train Epoch: 134 [33%]
2023-05-11 20:46:10,644	44k	INFO	Losses: [2.2979674339294434, 2.006298065185547, 17.29484748840332, 19.201370239257812, 0.630429208278656], step: 20400, lr: 2.9505342319111476e-05, reference_loss: 41.430912017822266
2023-05-11 20:46:58,038	44k	INFO	====> Epoch: 134, cost 87.75 s
2023-05-11 20:47:59,432	44k	INFO	Train Epoch: 135 [63%]
2023-05-11 20:47:59,433	44k	INFO	Losses: [2.2095932960510254, 2.393463373184204, 11.581130027770996, 21.175304412841797, 1.135851502418518], step: 20600, lr: 2.9501654151321586e-05, reference_loss: 38.49534225463867
2023-05-11 20:48:25,206	44k	INFO	====> Epoch: 135, cost 87.17 s
2023-05-11 20:49:47,645	44k	INFO	Train Epoch: 136 [94%]
2023-05-11 20:49:47,646	44k	INFO	Losses: [2.673558235168457, 2.0885770320892334, 11.845332145690918, 21.09345817565918, 0.7915951013565063], step: 20800, lr: 2.949796644455267e-05, reference_loss: 38.492523193359375
2023-05-11 20:49:52,428	44k	INFO	====> Epoch: 136, cost 87.22 s
2023-05-11 20:51:19,686	44k	INFO	====> Epoch: 137, cost 87.26 s
2023-05-11 20:51:54,742	44k	INFO	Train Epoch: 138 [25%]
2023-05-11 20:51:54,743	44k	INFO	Losses: [2.5458080768585205, 2.4174704551696777, 7.571362495422363, 17.600116729736328, 0.9082613587379456], step: 21000, lr: 2.9490592413847257e-05, reference_loss: 31.043020248413086
2023-05-11 20:52:00,261	44k	INFO	Saving model and optimizer state at iteration 138 to ./logs\44k\G_21000.pth
2023-05-11 20:52:01,063	44k	INFO	Saving model and optimizer state at iteration 138 to ./logs\44k\D_21000.pth
2023-05-11 20:52:01,744	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_18000.pth
2023-05-11 20:52:01,792	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_18000.pth
2023-05-11 20:52:54,041	44k	INFO	====> Epoch: 138, cost 94.36 s
2023-05-11 20:53:50,425	44k	INFO	Train Epoch: 139 [56%]
2023-05-11 20:53:50,425	44k	INFO	Losses: [2.2571232318878174, 2.247736692428589, 16.057188034057617, 21.77541732788086, 0.7787254452705383], step: 21200, lr: 2.9486906089795525e-05, reference_loss: 43.116188049316406
2023-05-11 20:54:22,088	44k	INFO	====> Epoch: 139, cost 88.05 s
2023-05-11 20:55:39,949	44k	INFO	Train Epoch: 140 [86%]
2023-05-11 20:55:39,950	44k	INFO	Losses: [2.0789754390716553, 2.748399257659912, 12.256720542907715, 21.41007423400879, 0.893726646900177], step: 21400, lr: 2.94832202265343e-05, reference_loss: 39.38789749145508
2023-05-11 20:55:50,072	44k	INFO	====> Epoch: 140, cost 87.98 s
2023-05-11 20:57:17,515	44k	INFO	====> Epoch: 141, cost 87.44 s
2023-05-11 20:57:47,067	44k	INFO	Train Epoch: 142 [17%]
2023-05-11 20:57:47,068	44k	INFO	Losses: [2.4438860416412354, 2.4429829120635986, 16.231311798095703, 21.76428985595703, 0.7568286657333374], step: 21600, lr: 2.947584988215298e-05, reference_loss: 43.63929748535156
2023-05-11 20:58:44,909	44k	INFO	====> Epoch: 142, cost 87.39 s
2023-05-11 20:59:35,470	44k	INFO	Train Epoch: 143 [48%]
2023-05-11 20:59:35,470	44k	INFO	Losses: [2.232591390609741, 2.464632511138916, 12.822518348693848, 19.372709274291992, 0.6750560402870178], step: 21800, lr: 2.947216540091771e-05, reference_loss: 37.5675048828125
2023-05-11 21:00:12,213	44k	INFO	====> Epoch: 143, cost 87.30 s
2023-05-11 21:01:23,935	44k	INFO	Train Epoch: 144 [78%]
2023-05-11 21:01:23,935	44k	INFO	Losses: [2.406494379043579, 2.7598273754119873, 9.910408973693848, 20.712154388427734, 1.0561177730560303], step: 22000, lr: 2.9468481380242593e-05, reference_loss: 36.84500503540039
2023-05-11 21:01:29,590	44k	INFO	Saving model and optimizer state at iteration 144 to ./logs\44k\G_22000.pth
2023-05-11 21:01:30,388	44k	INFO	Saving model and optimizer state at iteration 144 to ./logs\44k\D_22000.pth
2023-05-11 21:01:31,078	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_19000.pth
2023-05-11 21:01:31,125	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_19000.pth
2023-05-11 21:01:46,501	44k	INFO	====> Epoch: 144, cost 94.29 s
2023-05-11 21:03:13,604	44k	INFO	====> Epoch: 145, cost 87.10 s
2023-05-11 21:03:37,913	44k	INFO	Train Epoch: 146 [9%]
2023-05-11 21:03:37,914	44k	INFO	Losses: [2.180478572845459, 2.70823073387146, 13.783332824707031, 19.746074676513672, 1.2353508472442627], step: 22200, lr: 2.946111472034255e-05, reference_loss: 39.65346908569336
2023-05-11 21:04:41,210	44k	INFO	====> Epoch: 146, cost 87.61 s
2023-05-11 21:05:26,399	44k	INFO	Train Epoch: 147 [40%]
2023-05-11 21:05:26,399	44k	INFO	Losses: [2.5843002796173096, 2.918128728866577, 11.671560287475586, 21.43267822265625, 1.379014015197754], step: 22400, lr: 2.9457432081002507e-05, reference_loss: 39.985679626464844
2023-05-11 21:06:08,445	44k	INFO	====> Epoch: 147, cost 87.24 s
2023-05-11 21:07:15,544	44k	INFO	Train Epoch: 148 [71%]
2023-05-11 21:07:15,545	44k	INFO	Losses: [2.504765748977661, 2.0900638103485107, 11.348179817199707, 22.14876937866211, 1.0332155227661133], step: 22600, lr: 2.945374990199238e-05, reference_loss: 39.12499237060547
2023-05-11 21:07:36,609	44k	INFO	====> Epoch: 148, cost 88.16 s
2023-05-11 21:09:03,510	44k	INFO	====> Epoch: 149, cost 86.90 s
2023-05-11 21:09:22,300	44k	INFO	Train Epoch: 150 [1%]
2023-05-11 21:09:22,301	44k	INFO	Losses: [2.3296217918395996, 2.0549073219299316, 18.788482666015625, 18.85059928894043, 1.0376532077789307], step: 22800, lr: 2.944638692473172e-05, reference_loss: 43.0612678527832
2023-05-11 21:10:31,081	44k	INFO	====> Epoch: 150, cost 87.57 s
2023-05-11 21:11:11,011	44k	INFO	Train Epoch: 151 [32%]
2023-05-11 21:11:11,012	44k	INFO	Losses: [2.4543569087982178, 1.9625674486160278, 16.84097671508789, 20.134233474731445, 0.5687814950942993], step: 23000, lr: 2.944270612636613e-05, reference_loss: 41.96091842651367
2023-05-11 21:11:16,442	44k	INFO	Saving model and optimizer state at iteration 151 to ./logs\44k\G_23000.pth
2023-05-11 21:11:17,214	44k	INFO	Saving model and optimizer state at iteration 151 to ./logs\44k\D_23000.pth
2023-05-11 21:11:17,896	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_20000.pth
2023-05-11 21:11:17,946	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_20000.pth
2023-05-11 21:12:05,384	44k	INFO	====> Epoch: 151, cost 94.30 s
2023-05-11 21:13:06,596	44k	INFO	Train Epoch: 152 [63%]
2023-05-11 21:13:06,597	44k	INFO	Losses: [2.2838151454925537, 2.441021680831909, 13.107950210571289, 18.88092041015625, 1.1365299224853516], step: 23200, lr: 2.9439025788100334e-05, reference_loss: 37.85023498535156
2023-05-11 21:13:33,008	44k	INFO	====> Epoch: 152, cost 87.62 s
2023-05-11 21:14:55,226	44k	INFO	Train Epoch: 153 [93%]
2023-05-11 21:14:55,226	44k	INFO	Losses: [2.525782346725464, 2.3542909622192383, 9.45370101928711, 20.078929901123047, 1.0055861473083496], step: 23400, lr: 2.943534590987682e-05, reference_loss: 35.41828918457031
2023-05-11 21:15:00,370	44k	INFO	====> Epoch: 153, cost 87.36 s
2023-05-11 21:16:27,225	44k	INFO	====> Epoch: 154, cost 86.85 s
2023-05-11 21:17:01,782	44k	INFO	Train Epoch: 155 [24%]
2023-05-11 21:17:01,783	44k	INFO	Losses: [2.23268985748291, 2.3809478282928467, 14.686380386352539, 21.40892791748047, 0.8026105761528015], step: 23600, lr: 2.942798753332663e-05, reference_loss: 41.511558532714844
2023-05-11 21:17:54,576	44k	INFO	====> Epoch: 155, cost 87.35 s
2023-05-11 21:18:49,948	44k	INFO	Train Epoch: 156 [55%]
2023-05-11 21:18:49,948	44k	INFO	Losses: [2.4280471801757812, 2.5859994888305664, 11.22673511505127, 15.86699390411377, 1.2461222410202026], step: 23800, lr: 2.942430903488496e-05, reference_loss: 33.35389709472656
2023-05-11 21:19:21,698	44k	INFO	====> Epoch: 156, cost 87.12 s
2023-05-11 21:20:38,334	44k	INFO	Train Epoch: 157 [86%]
2023-05-11 21:20:38,335	44k	INFO	Losses: [2.5375471115112305, 2.067962408065796, 12.566537857055664, 19.366064071655273, 0.6837486624717712], step: 24000, lr: 2.94206309962556e-05, reference_loss: 37.221858978271484
2023-05-11 21:20:43,750	44k	INFO	Saving model and optimizer state at iteration 157 to ./logs\44k\G_24000.pth
2023-05-11 21:20:44,758	44k	INFO	Saving model and optimizer state at iteration 157 to ./logs\44k\D_24000.pth
2023-05-11 21:20:45,437	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_21000.pth
2023-05-11 21:20:45,488	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_21000.pth
2023-05-11 21:20:55,830	44k	INFO	====> Epoch: 157, cost 94.13 s
2023-05-11 21:22:22,890	44k	INFO	====> Epoch: 158, cost 87.06 s
2023-05-11 21:22:51,958	44k	INFO	Train Epoch: 159 [16%]
2023-05-11 21:22:51,959	44k	INFO	Losses: [2.241414785385132, 2.9840853214263916, 11.527679443359375, 22.236251831054688, 0.9714987874031067], step: 24200, lr: 2.941327629820389e-05, reference_loss: 39.960933685302734
2023-05-11 21:23:50,193	44k	INFO	====> Epoch: 159, cost 87.30 s
2023-05-11 21:24:40,368	44k	INFO	Train Epoch: 160 [47%]
2023-05-11 21:24:40,368	44k	INFO	Losses: [2.3132245540618896, 2.156310558319092, 10.544333457946777, 20.26015853881836, 0.8702049851417542], step: 24400, lr: 2.9409599638666614e-05, reference_loss: 36.144229888916016
2023-05-11 21:25:17,569	44k	INFO	====> Epoch: 160, cost 87.38 s
2023-05-11 21:26:28,960	44k	INFO	Train Epoch: 161 [78%]
2023-05-11 21:26:28,961	44k	INFO	Losses: [2.6417489051818848, 2.1795549392700195, 7.683846950531006, 18.796051025390625, 0.8269001841545105], step: 24600, lr: 2.940592343871178e-05, reference_loss: 32.12810134887695
2023-05-11 21:26:44,825	44k	INFO	====> Epoch: 161, cost 87.26 s
2023-05-11 21:28:11,839	44k	INFO	====> Epoch: 162, cost 87.01 s
2023-05-11 21:28:35,619	44k	INFO	Train Epoch: 163 [8%]
2023-05-11 21:28:35,620	44k	INFO	Losses: [2.211031913757324, 2.4875597953796387, 13.958282470703125, 20.161800384521484, 0.749904990196228], step: 24800, lr: 2.9398572417319655e-05, reference_loss: 39.56857681274414
2023-05-11 21:29:39,357	44k	INFO	====> Epoch: 163, cost 87.52 s
2023-05-11 21:30:24,293	44k	INFO	Train Epoch: 164 [39%]
2023-05-11 21:30:24,294	44k	INFO	Losses: [2.052870512008667, 2.417069435119629, 14.692856788635254, 24.030372619628906, 0.9703827500343323], step: 25000, lr: 2.939489759576749e-05, reference_loss: 44.163551330566406
2023-05-11 21:30:29,798	44k	INFO	Saving model and optimizer state at iteration 164 to ./logs\44k\G_25000.pth
2023-05-11 21:30:30,566	44k	INFO	Saving model and optimizer state at iteration 164 to ./logs\44k\D_25000.pth
2023-05-11 21:30:31,314	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_22000.pth
2023-05-11 21:30:31,358	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_22000.pth
2023-05-11 21:31:13,938	44k	INFO	====> Epoch: 164, cost 94.58 s
2023-05-11 21:32:20,020	44k	INFO	Train Epoch: 165 [70%]
2023-05-11 21:32:20,020	44k	INFO	Losses: [2.481353282928467, 2.5482654571533203, 9.902636528015137, 19.371829986572266, 0.9272757172584534], step: 25200, lr: 2.9391223233568018e-05, reference_loss: 35.231361389160156
2023-05-11 21:32:41,490	44k	INFO	====> Epoch: 165, cost 87.55 s
2023-05-11 21:34:08,236	44k	INFO	====> Epoch: 166, cost 86.74 s
2023-05-11 21:34:26,508	44k	INFO	Train Epoch: 167 [1%]
2023-05-11 21:34:26,509	44k	INFO	Losses: [2.253011465072632, 2.2450759410858154, 15.501739501953125, 20.518815994262695, 0.5719788670539856], step: 25400, lr: 2.9383875886997486e-05, reference_loss: 41.09062194824219
2023-05-11 21:35:35,525	44k	INFO	====> Epoch: 167, cost 87.29 s
2023-05-11 21:36:14,975	44k	INFO	Train Epoch: 168 [31%]
2023-05-11 21:36:14,976	44k	INFO	Losses: [2.2571256160736084, 2.4889888763427734, 13.262822151184082, 19.51145362854004, 0.7072980403900146], step: 25600, lr: 2.938020290251161e-05, reference_loss: 38.227691650390625
2023-05-11 21:37:02,988	44k	INFO	====> Epoch: 168, cost 87.46 s
2023-05-11 21:38:03,715	44k	INFO	Train Epoch: 169 [62%]
2023-05-11 21:38:03,715	44k	INFO	Losses: [2.303880214691162, 2.658754587173462, 13.399310111999512, 20.27336311340332, 0.855845034122467], step: 25800, lr: 2.9376530377148793e-05, reference_loss: 39.491153717041016
2023-05-11 21:38:30,579	44k	INFO	====> Epoch: 169, cost 87.59 s
2023-05-11 21:39:52,506	44k	INFO	Train Epoch: 170 [93%]
2023-05-11 21:39:52,507	44k	INFO	Losses: [2.350327968597412, 2.634793996810913, 10.36052417755127, 20.960542678833008, 0.7704409956932068], step: 26000, lr: 2.937285831085165e-05, reference_loss: 37.076629638671875
2023-05-11 21:39:58,072	44k	INFO	Saving model and optimizer state at iteration 170 to ./logs\44k\G_26000.pth
2023-05-11 21:39:58,858	44k	INFO	Saving model and optimizer state at iteration 170 to ./logs\44k\D_26000.pth
2023-05-11 21:39:59,536	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_23000.pth
2023-05-11 21:39:59,586	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_23000.pth
2023-05-11 21:40:04,914	44k	INFO	====> Epoch: 170, cost 94.34 s
2023-05-11 21:41:32,078	44k	INFO	====> Epoch: 171, cost 87.16 s
2023-05-11 21:42:06,014	44k	INFO	Train Epoch: 172 [24%]
2023-05-11 21:42:06,014	44k	INFO	Losses: [2.156196117401123, 2.2004923820495605, 14.32460880279541, 21.6739444732666, 0.7178844809532166], step: 26200, lr: 2.936551555522484e-05, reference_loss: 41.073123931884766
2023-05-11 21:42:59,398	44k	INFO	====> Epoch: 172, cost 87.32 s
2023-05-11 21:43:54,580	44k	INFO	Train Epoch: 173 [54%]
2023-05-11 21:43:54,581	44k	INFO	Losses: [2.3695151805877686, 2.145268678665161, 14.655494689941406, 20.661605834960938, 0.6832132935523987], step: 26400, lr: 2.9361844865780437e-05, reference_loss: 40.515098571777344
2023-05-11 21:44:26,858	44k	INFO	====> Epoch: 173, cost 87.46 s
2023-05-11 21:45:42,960	44k	INFO	Train Epoch: 174 [85%]
2023-05-11 21:45:42,961	44k	INFO	Losses: [2.1927995681762695, 2.773047685623169, 14.40477180480957, 21.50453758239746, 0.8371394276618958], step: 26600, lr: 2.9358174635172214e-05, reference_loss: 41.71229553222656
2023-05-11 21:45:53,964	44k	INFO	====> Epoch: 174, cost 87.11 s
2023-05-11 21:47:20,875	44k	INFO	====> Epoch: 175, cost 86.91 s
2023-05-11 21:47:49,499	44k	INFO	Train Epoch: 176 [16%]
2023-05-11 21:47:49,500	44k	INFO	Losses: [2.150271415710449, 2.4814937114715576, 10.576351165771484, 21.112905502319336, 0.5675302147865295], step: 26800, lr: 2.93508355502349e-05, reference_loss: 36.888553619384766
2023-05-11 21:48:48,298	44k	INFO	====> Epoch: 176, cost 87.42 s
2023-05-11 21:49:38,089	44k	INFO	Train Epoch: 177 [46%]
2023-05-11 21:49:38,090	44k	INFO	Losses: [2.220341444015503, 2.3397107124328613, 17.20482635498047, 19.44502830505371, 1.3015373945236206], step: 27000, lr: 2.9347166695791118e-05, reference_loss: 42.511444091796875
2023-05-11 21:49:43,605	44k	INFO	Saving model and optimizer state at iteration 177 to ./logs\44k\G_27000.pth
2023-05-11 21:49:44,532	44k	INFO	Saving model and optimizer state at iteration 177 to ./logs\44k\D_27000.pth
2023-05-11 21:49:45,218	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_24000.pth
2023-05-11 21:49:45,267	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_24000.pth
2023-05-11 21:50:22,588	44k	INFO	====> Epoch: 177, cost 94.29 s
2023-05-11 21:51:33,862	44k	INFO	Train Epoch: 178 [77%]
2023-05-11 21:51:33,863	44k	INFO	Losses: [1.8780664205551147, 2.910325527191162, 13.378846168518066, 20.67080307006836, 0.9391260743141174], step: 27200, lr: 2.9343498299954142e-05, reference_loss: 39.77716827392578
2023-05-11 21:51:50,277	44k	INFO	====> Epoch: 178, cost 87.69 s
2023-05-11 21:53:17,257	44k	INFO	====> Epoch: 179, cost 86.98 s
2023-05-11 21:53:40,415	44k	INFO	Train Epoch: 180 [8%]
2023-05-11 21:53:40,416	44k	INFO	Losses: [2.2581627368927, 2.3214633464813232, 17.729576110839844, 21.39453125, 0.9237614870071411], step: 27400, lr: 2.933616288387131e-05, reference_loss: 44.627498626708984
2023-05-11 21:54:44,319	44k	INFO	====> Epoch: 180, cost 87.06 s
2023-05-11 21:55:28,316	44k	INFO	Train Epoch: 181 [39%]
2023-05-11 21:55:28,317	44k	INFO	Losses: [2.304253578186035, 2.7002696990966797, 12.313386917114258, 19.609540939331055, 0.5598008632659912], step: 27600, lr: 2.9332495863510825e-05, reference_loss: 37.48725128173828
2023-05-11 21:56:11,255	44k	INFO	====> Epoch: 181, cost 86.94 s
2023-05-11 21:57:16,470	44k	INFO	Train Epoch: 182 [69%]
2023-05-11 21:57:16,470	44k	INFO	Losses: [2.063203811645508, 2.258450508117676, 13.339643478393555, 15.154513359069824, 0.6263005137443542], step: 27800, lr: 2.9328829301527885e-05, reference_loss: 33.44211196899414
2023-05-11 21:57:38,385	44k	INFO	====> Epoch: 182, cost 87.13 s
2023-05-11 21:59:05,545	44k	INFO	====> Epoch: 183, cost 87.16 s
2023-05-11 21:59:23,525	44k	INFO	Train Epoch: 184 [0%]
2023-05-11 21:59:23,526	44k	INFO	Losses: [2.554588794708252, 2.476391077041626, 16.369321823120117, 21.40169334411621, 1.1655538082122803], step: 28000, lr: 2.9321497552465458e-05, reference_loss: 43.96754837036133
2023-05-11 21:59:29,212	44k	INFO	Saving model and optimizer state at iteration 184 to ./logs\44k\G_28000.pth
2023-05-11 21:59:29,985	44k	INFO	Saving model and optimizer state at iteration 184 to ./logs\44k\D_28000.pth
2023-05-11 21:59:30,732	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_25000.pth
2023-05-11 21:59:30,782	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_25000.pth
2023-05-11 22:00:40,108	44k	INFO	====> Epoch: 184, cost 94.56 s
2023-05-11 22:01:19,097	44k	INFO	Train Epoch: 185 [31%]
2023-05-11 22:01:19,098	44k	INFO	Losses: [2.575772285461426, 2.325673818588257, 10.136171340942383, 20.177270889282227, 0.8660500049591064], step: 28200, lr: 2.9317832365271398e-05, reference_loss: 36.08094024658203
2023-05-11 22:02:07,567	44k	INFO	====> Epoch: 185, cost 87.46 s
2023-05-11 22:03:07,620	44k	INFO	Train Epoch: 186 [61%]
2023-05-11 22:03:07,620	44k	INFO	Losses: [2.3224031925201416, 2.242901563644409, 11.168042182922363, 18.820533752441406, 0.8706357479095459], step: 28400, lr: 2.9314167636225736e-05, reference_loss: 35.42451477050781
2023-05-11 22:03:34,936	44k	INFO	====> Epoch: 186, cost 87.37 s
2023-05-11 22:04:55,956	44k	INFO	Train Epoch: 187 [92%]
2023-05-11 22:04:55,957	44k	INFO	Losses: [2.2574715614318848, 2.3387222290039062, 11.857097625732422, 18.84485626220703, 0.9323740601539612], step: 28600, lr: 2.9310503365271207e-05, reference_loss: 36.23052215576172
2023-05-11 22:05:01,930	44k	INFO	====> Epoch: 187, cost 86.99 s
2023-05-11 22:06:28,657	44k	INFO	====> Epoch: 188, cost 86.73 s
2023-05-11 22:07:02,868	44k	INFO	Train Epoch: 189 [23%]
2023-05-11 22:07:02,869	44k	INFO	Losses: [2.542555809020996, 2.307922840118408, 11.040369987487793, 20.292699813842773, 0.8018638491630554], step: 28800, lr: 2.9303176197406502e-05, reference_loss: 36.98541259765625
2023-05-11 22:07:56,862	44k	INFO	====> Epoch: 189, cost 88.20 s
2023-05-11 22:08:51,848	44k	INFO	Train Epoch: 190 [54%]
2023-05-11 22:08:51,848	44k	INFO	Losses: [2.517507553100586, 2.6499273777008057, 11.654401779174805, 19.997529983520508, 0.5024926662445068], step: 29000, lr: 2.9299513300381825e-05, reference_loss: 37.32185745239258
2023-05-11 22:08:57,360	44k	INFO	Saving model and optimizer state at iteration 190 to ./logs\44k\G_29000.pth
2023-05-11 22:08:58,128	44k	INFO	Saving model and optimizer state at iteration 190 to ./logs\44k\D_29000.pth
2023-05-11 22:08:58,801	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_26000.pth
2023-05-11 22:08:58,847	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_26000.pth
2023-05-11 22:09:31,309	44k	INFO	====> Epoch: 190, cost 94.45 s
2023-05-11 22:10:47,204	44k	INFO	Train Epoch: 191 [84%]
2023-05-11 22:10:47,205	44k	INFO	Losses: [2.4900734424591064, 1.9228662252426147, 13.46911907196045, 20.261192321777344, 1.1399946212768555], step: 29200, lr: 2.9295850861219277e-05, reference_loss: 39.28324508666992
2023-05-11 22:10:58,753	44k	INFO	====> Epoch: 191, cost 87.44 s
2023-05-11 22:12:25,906	44k	INFO	====> Epoch: 192, cost 87.15 s
2023-05-11 22:12:53,882	44k	INFO	Train Epoch: 193 [15%]
2023-05-11 22:12:53,883	44k	INFO	Losses: [2.251241683959961, 2.6943960189819336, 8.497387886047363, 21.89167594909668, 0.7860233783721924], step: 29400, lr: 2.9288527356251642e-05, reference_loss: 36.120723724365234
2023-05-11 22:13:53,015	44k	INFO	====> Epoch: 193, cost 87.11 s
2023-05-11 22:14:42,149	44k	INFO	Train Epoch: 194 [46%]
2023-05-11 22:14:42,150	44k	INFO	Losses: [2.4207398891448975, 2.4460959434509277, 11.235674858093262, 19.89182472229004, 0.7694849371910095], step: 29600, lr: 2.9284866290332108e-05, reference_loss: 36.76382064819336
2023-05-11 22:15:20,269	44k	INFO	====> Epoch: 194, cost 87.25 s
2023-05-11 22:16:30,503	44k	INFO	Train Epoch: 195 [76%]
2023-05-11 22:16:30,503	44k	INFO	Losses: [2.2829880714416504, 2.345679759979248, 12.105896949768066, 19.036376953125, 0.8311740159988403], step: 29800, lr: 2.9281205682045817e-05, reference_loss: 36.602115631103516
2023-05-11 22:16:47,327	44k	INFO	====> Epoch: 195, cost 87.06 s
2023-05-11 22:18:14,136	44k	INFO	====> Epoch: 196, cost 86.81 s
2023-05-11 22:18:37,034	44k	INFO	Train Epoch: 197 [7%]
2023-05-11 22:18:37,035	44k	INFO	Losses: [2.1603307723999023, 2.3721256256103516, 12.609691619873047, 19.45323944091797, 0.7062307000160217], step: 30000, lr: 2.9273885838144143e-05, reference_loss: 37.30161666870117
2023-05-11 22:18:42,409	44k	INFO	Saving model and optimizer state at iteration 197 to ./logs\44k\G_30000.pth
2023-05-11 22:18:43,318	44k	INFO	Saving model and optimizer state at iteration 197 to ./logs\44k\D_30000.pth
2023-05-11 22:18:43,990	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_27000.pth
2023-05-11 22:18:44,042	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_27000.pth
2023-05-11 22:19:48,230	44k	INFO	====> Epoch: 197, cost 94.09 s
2023-05-11 22:20:31,978	44k	INFO	Train Epoch: 198 [38%]
2023-05-11 22:20:31,979	44k	INFO	Losses: [2.564594030380249, 2.080162763595581, 12.063499450683594, 18.630136489868164, 0.593277096748352], step: 30200, lr: 2.9270226602414373e-05, reference_loss: 35.931671142578125
2023-05-11 22:21:15,462	44k	INFO	====> Epoch: 198, cost 87.23 s
2023-05-11 22:22:20,615	44k	INFO	Train Epoch: 199 [69%]
2023-05-11 22:22:20,615	44k	INFO	Losses: [1.9948943853378296, 2.776331901550293, 15.739766120910645, 20.25297737121582, 0.8072575330734253], step: 30400, lr: 2.926656782408907e-05, reference_loss: 41.57122802734375
2023-05-11 22:22:43,914	44k	INFO	====> Epoch: 199, cost 88.45 s
2023-05-11 22:24:09,676	44k	INFO	Train Epoch: 200 [99%]
2023-05-11 22:24:09,677	44k	INFO	Losses: [2.6933860778808594, 1.615329623222351, 23.930498123168945, 18.160158157348633, 0.9431588053703308], step: 30600, lr: 2.9262909503111057e-05, reference_loss: 47.342529296875
2023-05-11 22:24:10,903	44k	INFO	====> Epoch: 200, cost 86.99 s
2023-05-11 22:25:37,587	44k	INFO	====> Epoch: 201, cost 86.68 s
2023-05-11 22:26:15,707	44k	INFO	Train Epoch: 202 [30%]
2023-05-11 22:26:15,707	44k	INFO	Losses: [2.5334725379943848, 2.8622517585754395, 11.238937377929688, 19.802366256713867, 0.9019911289215088], step: 30800, lr: 2.925559423296824e-05, reference_loss: 37.339019775390625
2023-05-11 22:27:04,770	44k	INFO	====> Epoch: 202, cost 87.18 s
2023-05-11 22:28:04,234	44k	INFO	Train Epoch: 203 [61%]
2023-05-11 22:28:04,235	44k	INFO	Losses: [2.3597183227539062, 2.453036308288574, 10.415300369262695, 18.27770233154297, 0.40730226039886475], step: 31000, lr: 2.9251937283689116e-05, reference_loss: 33.91305923461914
2023-05-11 22:28:09,522	44k	INFO	Saving model and optimizer state at iteration 203 to ./logs\44k\G_31000.pth
2023-05-11 22:28:10,580	44k	INFO	Saving model and optimizer state at iteration 203 to ./logs\44k\D_31000.pth
2023-05-11 22:28:11,274	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_28000.pth
2023-05-11 22:28:11,325	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_28000.pth
2023-05-11 22:28:38,895	44k	INFO	====> Epoch: 203, cost 94.12 s
2023-05-11 22:29:59,760	44k	INFO	Train Epoch: 204 [92%]
2023-05-11 22:29:59,760	44k	INFO	Losses: [2.4534120559692383, 2.224238395690918, 11.809039115905762, 15.801896095275879, 0.9736963510513306], step: 31200, lr: 2.9248280791528655e-05, reference_loss: 33.26228332519531
2023-05-11 22:30:06,225	44k	INFO	====> Epoch: 204, cost 87.33 s
2023-05-11 22:31:33,143	44k	INFO	====> Epoch: 205, cost 86.92 s
2023-05-11 22:32:06,211	44k	INFO	Train Epoch: 206 [22%]
2023-05-11 22:32:06,212	44k	INFO	Losses: [2.18281888961792, 2.4331183433532715, 15.949410438537598, 19.590402603149414, 0.47911879420280457], step: 31400, lr: 2.924096917833516e-05, reference_loss: 40.63486862182617
2023-05-11 22:33:00,375	44k	INFO	====> Epoch: 206, cost 87.23 s
2023-05-11 22:33:54,603	44k	INFO	Train Epoch: 207 [53%]
2023-05-11 22:33:54,604	44k	INFO	Losses: [2.1853795051574707, 2.3957722187042236, 17.22293472290039, 23.4381103515625, 1.1737055778503418], step: 31600, lr: 2.9237314057187867e-05, reference_loss: 46.41590118408203
2023-05-11 22:34:27,601	44k	INFO	====> Epoch: 207, cost 87.23 s
2023-05-11 22:35:44,264	44k	INFO	Train Epoch: 208 [84%]
2023-05-11 22:35:44,264	44k	INFO	Losses: [2.34808087348938, 2.4908933639526367, 12.557831764221191, 21.80524444580078, 1.1822048425674438], step: 31800, lr: 2.9233659392930716e-05, reference_loss: 40.384254455566406
2023-05-11 22:35:56,570	44k	INFO	====> Epoch: 208, cost 88.97 s
2023-05-11 22:37:24,222	44k	INFO	====> Epoch: 209, cost 87.65 s
2023-05-11 22:37:52,213	44k	INFO	Train Epoch: 210 [14%]
2023-05-11 22:37:52,214	44k	INFO	Losses: [2.17327880859375, 2.190847635269165, 15.827834129333496, 20.284080505371094, 0.7204908132553101], step: 32000, lr: 2.922635143485841e-05, reference_loss: 41.196529388427734
2023-05-11 22:37:57,510	44k	INFO	Saving model and optimizer state at iteration 210 to ./logs\44k\G_32000.pth
2023-05-11 22:37:58,384	44k	INFO	Saving model and optimizer state at iteration 210 to ./logs\44k\D_32000.pth
2023-05-11 22:37:59,063	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_29000.pth
2023-05-11 22:37:59,105	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_29000.pth
2023-05-11 22:38:59,344	44k	INFO	====> Epoch: 210, cost 95.12 s
2023-05-11 22:39:48,693	44k	INFO	Train Epoch: 211 [45%]
2023-05-11 22:39:48,694	44k	INFO	Losses: [2.1462364196777344, 2.0116279125213623, 14.271591186523438, 21.358386993408203, 0.79221111536026], step: 32200, lr: 2.922269814092905e-05, reference_loss: 40.58005142211914
2023-05-11 22:40:27,794	44k	INFO	====> Epoch: 211, cost 88.45 s
2023-05-11 22:41:38,370	44k	INFO	Train Epoch: 212 [76%]
2023-05-11 22:41:38,370	44k	INFO	Losses: [2.7046608924865723, 2.0745532512664795, 13.485158920288086, 19.286104202270508, 0.5432848930358887], step: 32400, lr: 2.9219045303661433e-05, reference_loss: 38.0937614440918
2023-05-11 22:41:56,147	44k	INFO	====> Epoch: 212, cost 88.35 s
2023-05-11 22:43:23,971	44k	INFO	====> Epoch: 213, cost 87.82 s
2023-05-11 22:43:46,542	44k	INFO	Train Epoch: 214 [7%]
2023-05-11 22:43:46,543	44k	INFO	Losses: [2.3181324005126953, 2.3565571308135986, 11.260844230651855, 20.600004196166992, 0.7078282833099365], step: 32600, lr: 2.9211740998883098e-05, reference_loss: 37.24336624145508
2023-05-11 22:44:52,351	44k	INFO	====> Epoch: 214, cost 88.38 s
2023-05-11 22:45:36,230	44k	INFO	Train Epoch: 215 [37%]
2023-05-11 22:45:36,231	44k	INFO	Losses: [2.791977643966675, 1.7529821395874023, 12.317703247070312, 20.926084518432617, 0.5998483896255493], step: 32800, lr: 2.9208089531258237e-05, reference_loss: 38.38859939575195
2023-05-11 22:46:20,911	44k	INFO	====> Epoch: 215, cost 88.56 s
2023-05-11 22:47:26,074	44k	INFO	Train Epoch: 216 [68%]
2023-05-11 22:47:26,075	44k	INFO	Losses: [2.5244128704071045, 2.3450944423675537, 10.498457908630371, 20.899843215942383, 0.6350367665290833], step: 33000, lr: 2.9204438520066827e-05, reference_loss: 36.9028434753418
2023-05-11 22:47:31,708	44k	INFO	Saving model and optimizer state at iteration 216 to ./logs\44k\G_33000.pth
2023-05-11 22:47:32,535	44k	INFO	Saving model and optimizer state at iteration 216 to ./logs\44k\D_33000.pth
2023-05-11 22:47:33,218	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_30000.pth
2023-05-11 22:47:33,266	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_30000.pth
2023-05-11 22:47:55,988	44k	INFO	====> Epoch: 216, cost 95.08 s
2023-05-11 22:49:22,577	44k	INFO	Train Epoch: 217 [99%]
2023-05-11 22:49:22,578	44k	INFO	Losses: [2.087664842605591, 2.370191812515259, 14.999993324279785, 20.936115264892578, 0.9530125260353088], step: 33200, lr: 2.920078796525182e-05, reference_loss: 41.346981048583984
2023-05-11 22:49:24,229	44k	INFO	====> Epoch: 217, cost 88.24 s
2023-05-11 22:50:52,028	44k	INFO	====> Epoch: 218, cost 87.80 s
2023-05-11 22:51:30,127	44k	INFO	Train Epoch: 219 [29%]
2023-05-11 22:51:30,128	44k	INFO	Losses: [2.29052996635437, 2.473458766937256, 11.260251998901367, 19.897136688232422, 0.7827029824256897], step: 33400, lr: 2.9193488224522815e-05, reference_loss: 36.70408248901367
2023-05-11 22:52:19,411	44k	INFO	====> Epoch: 219, cost 87.38 s
2023-05-11 22:53:18,422	44k	INFO	Train Epoch: 220 [60%]
2023-05-11 22:53:18,422	44k	INFO	Losses: [2.350973129272461, 2.281623601913452, 7.568717956542969, 17.09041404724121, 0.8629797697067261], step: 33600, lr: 2.9189839038494747e-05, reference_loss: 30.154708862304688
2023-05-11 22:53:46,514	44k	INFO	====> Epoch: 220, cost 87.10 s
2023-05-11 22:55:06,685	44k	INFO	Train Epoch: 221 [91%]
2023-05-11 22:55:06,685	44k	INFO	Losses: [2.3576741218566895, 2.4093825817108154, 9.272815704345703, 19.84087371826172, 0.8007166981697083], step: 33800, lr: 2.9186190308614934e-05, reference_loss: 34.681461334228516
2023-05-11 22:55:13,628	44k	INFO	====> Epoch: 221, cost 87.11 s
2023-05-11 22:56:40,344	44k	INFO	====> Epoch: 222, cost 86.72 s
2023-05-11 22:57:12,921	44k	INFO	Train Epoch: 223 [22%]
2023-05-11 22:57:12,922	44k	INFO	Losses: [2.0258748531341553, 2.9286649227142334, 8.281425476074219, 19.124338150024414, 0.993285059928894], step: 34000, lr: 2.9178894217072e-05, reference_loss: 33.35359191894531
2023-05-11 22:57:18,353	44k	INFO	Saving model and optimizer state at iteration 223 to ./logs\44k\G_34000.pth
2023-05-11 22:57:19,134	44k	INFO	Saving model and optimizer state at iteration 223 to ./logs\44k\D_34000.pth
2023-05-11 22:57:19,811	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_31000.pth
2023-05-11 22:57:19,858	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_31000.pth
2023-05-11 22:58:14,171	44k	INFO	====> Epoch: 223, cost 93.83 s
2023-05-11 22:59:07,808	44k	INFO	Train Epoch: 224 [52%]
2023-05-11 22:59:07,808	44k	INFO	Losses: [2.0101354122161865, 2.7200112342834473, 13.931513786315918, 21.98060417175293, 0.7607918381690979], step: 34200, lr: 2.9175246855294863e-05, reference_loss: 41.40305709838867
2023-05-11 22:59:41,401	44k	INFO	====> Epoch: 224, cost 87.23 s
2023-05-11 23:00:55,934	44k	INFO	Train Epoch: 225 [83%]
2023-05-11 23:00:55,934	44k	INFO	Losses: [2.629448890686035, 2.2429330348968506, 12.29239273071289, 19.560827255249023, 0.8214043378829956], step: 34400, lr: 2.917159994943795e-05, reference_loss: 37.54700469970703
2023-05-11 23:01:08,256	44k	INFO	====> Epoch: 225, cost 86.85 s
2023-05-11 23:02:34,834	44k	INFO	====> Epoch: 226, cost 86.58 s
2023-05-11 23:03:02,104	44k	INFO	Train Epoch: 227 [14%]
2023-05-11 23:03:02,105	44k	INFO	Losses: [2.1601171493530273, 2.1038057804107666, 19.6684627532959, 19.231704711914062, 0.981499969959259], step: 34600, lr: 2.9164307505256837e-05, reference_loss: 44.14558792114258
2023-05-11 23:04:02,068	44k	INFO	====> Epoch: 227, cost 87.23 s
2023-05-11 23:04:50,256	44k	INFO	Train Epoch: 228 [44%]
2023-05-11 23:04:50,257	44k	INFO	Losses: [2.5843756198883057, 2.345271587371826, 8.238197326660156, 19.72162628173828, 0.7127050757408142], step: 34800, lr: 2.916066196681868e-05, reference_loss: 33.602176666259766
2023-05-11 23:05:28,998	44k	INFO	====> Epoch: 228, cost 86.93 s
2023-05-11 23:06:38,130	44k	INFO	Train Epoch: 229 [75%]
2023-05-11 23:06:38,130	44k	INFO	Losses: [2.583364486694336, 2.29083514213562, 10.543819427490234, 22.168258666992188, 0.4813070297241211], step: 35000, lr: 2.9157016884072827e-05, reference_loss: 38.06758499145508
2023-05-11 23:06:43,832	44k	INFO	Saving model and optimizer state at iteration 229 to ./logs\44k\G_35000.pth
2023-05-11 23:06:44,632	44k	INFO	Saving model and optimizer state at iteration 229 to ./logs\44k\D_35000.pth
2023-05-11 23:06:45,321	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_32000.pth
2023-05-11 23:06:45,390	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_32000.pth
2023-05-11 23:07:03,133	44k	INFO	====> Epoch: 229, cost 94.13 s
2023-05-11 23:08:29,638	44k	INFO	====> Epoch: 230, cost 86.51 s
2023-05-11 23:08:51,610	44k	INFO	Train Epoch: 231 [6%]
2023-05-11 23:08:51,611	44k	INFO	Losses: [2.318617820739746, 2.1824753284454346, 7.610252380371094, 20.95266342163086, 0.6841897964477539], step: 35200, lr: 2.9149728085430194e-05, reference_loss: 33.748199462890625
2023-05-11 23:09:56,594	44k	INFO	====> Epoch: 231, cost 86.96 s
2023-05-11 23:10:39,274	44k	INFO	Train Epoch: 232 [37%]
2023-05-11 23:10:39,275	44k	INFO	Losses: [1.9487130641937256, 2.582306146621704, 17.558088302612305, 22.907352447509766, 0.7167505621910095], step: 35400, lr: 2.9146084369419513e-05, reference_loss: 45.71321105957031
2023-05-11 23:11:23,614	44k	INFO	====> Epoch: 232, cost 87.02 s
2023-05-11 23:12:27,462	44k	INFO	Train Epoch: 233 [67%]
2023-05-11 23:12:27,462	44k	INFO	Losses: [2.434251308441162, 1.916774034500122, 14.019707679748535, 20.46570587158203, 0.696102499961853], step: 35600, lr: 2.9142441108873335e-05, reference_loss: 39.53254318237305
2023-05-11 23:12:50,725	44k	INFO	====> Epoch: 233, cost 87.11 s
2023-05-11 23:14:15,728	44k	INFO	Train Epoch: 234 [98%]
2023-05-11 23:14:15,729	44k	INFO	Losses: [2.373408317565918, 2.158862829208374, 15.192477226257324, 21.282258987426758, 1.1444936990737915], step: 35800, lr: 2.9138798303734726e-05, reference_loss: 42.1515007019043
2023-05-11 23:14:17,791	44k	INFO	====> Epoch: 234, cost 87.07 s
2023-05-11 23:15:44,221	44k	INFO	====> Epoch: 235, cost 86.43 s
2023-05-11 23:16:21,772	44k	INFO	Train Epoch: 236 [29%]
2023-05-11 23:16:21,772	44k	INFO	Losses: [2.328075647354126, 2.1455647945404053, 17.557395935058594, 20.413278579711914, 0.9318976402282715], step: 36000, lr: 2.9131514059452513e-05, reference_loss: 43.3762092590332
2023-05-11 23:16:27,178	44k	INFO	Saving model and optimizer state at iteration 236 to ./logs\44k\G_36000.pth
2023-05-11 23:16:27,947	44k	INFO	Saving model and optimizer state at iteration 236 to ./logs\44k\D_36000.pth
2023-05-11 23:16:28,626	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_33000.pth
2023-05-11 23:16:28,672	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_33000.pth
2023-05-11 23:17:17,991	44k	INFO	====> Epoch: 236, cost 93.77 s
2023-05-11 23:18:16,326	44k	INFO	Train Epoch: 237 [59%]
2023-05-11 23:18:16,326	44k	INFO	Losses: [1.9186285734176636, 2.3429036140441895, 15.22066879272461, 21.276222229003906, 1.1392505168914795], step: 36200, lr: 2.912787262019508e-05, reference_loss: 41.897674560546875
2023-05-11 23:18:44,912	44k	INFO	====> Epoch: 237, cost 86.92 s
2023-05-11 23:20:04,428	44k	INFO	Train Epoch: 238 [90%]
2023-05-11 23:20:04,428	44k	INFO	Losses: [2.264615058898926, 2.287299156188965, 16.440340042114258, 17.999305725097656, 0.6580404043197632], step: 36400, lr: 2.9124231636117555e-05, reference_loss: 39.649600982666016
2023-05-11 23:20:11,795	44k	INFO	====> Epoch: 238, cost 86.88 s
2023-05-11 23:21:38,421	44k	INFO	====> Epoch: 239, cost 86.63 s
2023-05-11 23:22:10,502	44k	INFO	Train Epoch: 240 [21%]
2023-05-11 23:22:10,503	44k	INFO	Losses: [2.2759435176849365, 2.249727487564087, 14.910801887512207, 18.91904640197754, 0.8311969637870789], step: 36600, lr: 2.9116951033274644e-05, reference_loss: 39.18671798706055
2023-05-11 23:23:05,565	44k	INFO	====> Epoch: 240, cost 87.14 s
2023-05-11 23:23:58,870	44k	INFO	Train Epoch: 241 [52%]
2023-05-11 23:23:58,870	44k	INFO	Losses: [2.496267080307007, 2.147951602935791, 13.372493743896484, 19.058626174926758, 0.30706867575645447], step: 36800, lr: 2.9113311414395485e-05, reference_loss: 37.382408142089844
2023-05-11 23:24:32,861	44k	INFO	====> Epoch: 241, cost 87.30 s
2023-05-11 23:25:46,908	44k	INFO	Train Epoch: 242 [82%]
2023-05-11 23:25:46,908	44k	INFO	Losses: [2.1299355030059814, 2.3770081996917725, 18.414464950561523, 21.180307388305664, 1.2796505689620972], step: 37000, lr: 2.9109672250468686e-05, reference_loss: 45.38136672973633
2023-05-11 23:25:52,460	44k	INFO	Saving model and optimizer state at iteration 242 to ./logs\44k\G_37000.pth
2023-05-11 23:25:53,177	44k	INFO	Saving model and optimizer state at iteration 242 to ./logs\44k\D_37000.pth
2023-05-11 23:25:53,876	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_34000.pth
2023-05-11 23:25:53,931	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_34000.pth
2023-05-11 23:26:06,680	44k	INFO	====> Epoch: 242, cost 93.82 s
2023-05-11 23:27:33,210	44k	INFO	====> Epoch: 243, cost 86.53 s
2023-05-11 23:27:59,748	44k	INFO	Train Epoch: 244 [13%]
2023-05-11 23:27:59,749	44k	INFO	Losses: [2.8545777797698975, 2.7850182056427, 7.647801399230957, 15.885904312133789, 0.8959618210792542], step: 37200, lr: 2.9102395287244696e-05, reference_loss: 30.069263458251953
2023-05-11 23:29:00,079	44k	INFO	====> Epoch: 244, cost 86.87 s
2023-05-11 23:29:47,888	44k	INFO	Train Epoch: 245 [44%]
2023-05-11 23:29:47,889	44k	INFO	Losses: [2.607884407043457, 2.2625949382781982, 9.111988067626953, 18.94312858581543, 0.978264570236206], step: 37400, lr: 2.909875748783379e-05, reference_loss: 33.90386199951172
2023-05-11 23:30:27,221	44k	INFO	====> Epoch: 245, cost 87.14 s
2023-05-11 23:31:37,147	44k	INFO	Train Epoch: 246 [75%]
2023-05-11 23:31:37,147	44k	INFO	Losses: [2.371624231338501, 2.3269622325897217, 14.278680801391602, 18.87295913696289, 0.7479438185691833], step: 37600, lr: 2.909512014314781e-05, reference_loss: 38.59817123413086
2023-05-11 23:31:55,708	44k	INFO	====> Epoch: 246, cost 88.49 s
2023-05-11 23:33:23,707	44k	INFO	====> Epoch: 247, cost 88.00 s
2023-05-11 23:33:45,138	44k	INFO	Train Epoch: 248 [5%]
2023-05-11 23:33:45,138	44k	INFO	Losses: [2.4249305725097656, 2.6680610179901123, 11.795964241027832, 18.1381778717041, 0.726823627948761], step: 37800, lr: 2.908784681772327e-05, reference_loss: 35.75395584106445
2023-05-11 23:34:50,822	44k	INFO	====> Epoch: 248, cost 87.12 s
2023-05-11 23:35:33,016	44k	INFO	Train Epoch: 249 [36%]
2023-05-11 23:35:33,016	44k	INFO	Losses: [2.571638345718384, 2.0839293003082275, 11.542834281921387, 18.88866424560547, 0.43505746126174927], step: 38000, lr: 2.9084210836871055e-05, reference_loss: 35.522125244140625
2023-05-11 23:35:38,572	44k	INFO	Saving model and optimizer state at iteration 249 to ./logs\44k\G_38000.pth
2023-05-11 23:35:39,384	44k	INFO	Saving model and optimizer state at iteration 249 to ./logs\44k\D_38000.pth
2023-05-11 23:35:40,165	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_35000.pth
2023-05-11 23:35:40,216	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_35000.pth
2023-05-11 23:36:24,791	44k	INFO	====> Epoch: 249, cost 93.97 s
2023-05-11 23:37:28,336	44k	INFO	Train Epoch: 250 [67%]
2023-05-11 23:37:28,336	44k	INFO	Losses: [2.3983511924743652, 2.6881916522979736, 7.036543846130371, 21.21124839782715, 0.9582434296607971], step: 38200, lr: 2.9080575310516446e-05, reference_loss: 34.292579650878906
2023-05-11 23:37:51,887	44k	INFO	====> Epoch: 250, cost 87.10 s
2023-05-11 23:39:16,330	44k	INFO	Train Epoch: 251 [97%]
2023-05-11 23:39:16,330	44k	INFO	Losses: [2.2132420539855957, 2.5108938217163086, 13.515555381774902, 21.54300308227539, 0.8297137022018433], step: 38400, lr: 2.907694023860263e-05, reference_loss: 40.612403869628906
2023-05-11 23:39:18,851	44k	INFO	====> Epoch: 251, cost 86.96 s
2023-05-11 23:40:45,916	44k	INFO	====> Epoch: 252, cost 87.06 s
2023-05-11 23:41:22,938	44k	INFO	Train Epoch: 253 [28%]
2023-05-11 23:41:22,939	44k	INFO	Losses: [2.296832323074341, 2.4653115272521973, 14.684825897216797, 21.370893478393555, 0.6395803093910217], step: 38600, lr: 2.906967145787017e-05, reference_loss: 41.45744323730469
2023-05-11 23:42:13,056	44k	INFO	====> Epoch: 253, cost 87.14 s
2023-05-11 23:43:11,132	44k	INFO	Train Epoch: 254 [59%]
2023-05-11 23:43:11,132	44k	INFO	Losses: [2.8358492851257324, 2.129021167755127, 8.167855262756348, 14.802287101745605, 0.7585254311561584], step: 38800, lr: 2.9066037748937933e-05, reference_loss: 28.693538665771484
2023-05-11 23:43:40,035	44k	INFO	====> Epoch: 254, cost 86.98 s
2023-05-11 23:44:58,951	44k	INFO	Train Epoch: 255 [90%]
2023-05-11 23:44:58,951	44k	INFO	Losses: [2.384014129638672, 2.609471321105957, 13.67310905456543, 20.50167465209961, 0.9759578108787537], step: 39000, lr: 2.9062404494219316e-05, reference_loss: 40.14422607421875
2023-05-11 23:45:04,485	44k	INFO	Saving model and optimizer state at iteration 255 to ./logs\44k\G_39000.pth
2023-05-11 23:45:05,258	44k	INFO	Saving model and optimizer state at iteration 255 to ./logs\44k\D_39000.pth
2023-05-11 23:45:05,938	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_36000.pth
2023-05-11 23:45:05,991	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_36000.pth
2023-05-11 23:45:13,530	44k	INFO	====> Epoch: 255, cost 93.49 s
2023-05-11 23:46:40,103	44k	INFO	====> Epoch: 256, cost 86.57 s
2023-05-11 23:47:11,698	44k	INFO	Train Epoch: 257 [20%]
2023-05-11 23:47:11,699	44k	INFO	Losses: [2.412679672241211, 2.4876222610473633, 10.623312950134277, 18.588048934936523, 0.9430463910102844], step: 39200, lr: 2.905513934719583e-05, reference_loss: 35.054710388183594
2023-05-11 23:48:06,964	44k	INFO	====> Epoch: 257, cost 86.86 s
2023-05-11 23:48:59,544	44k	INFO	Train Epoch: 258 [51%]
2023-05-11 23:48:59,545	44k	INFO	Losses: [2.6109132766723633, 2.576932668685913, 8.075935363769531, 16.961647033691406, 0.5622955560684204], step: 39400, lr: 2.9051507454777428e-05, reference_loss: 30.7877254486084
2023-05-11 23:49:33,809	44k	INFO	====> Epoch: 258, cost 86.85 s
2023-05-11 23:50:47,837	44k	INFO	Train Epoch: 259 [82%]
2023-05-11 23:50:47,838	44k	INFO	Losses: [2.4824814796447754, 2.4467413425445557, 14.783933639526367, 19.17391014099121, 0.9434327483177185], step: 39600, lr: 2.904787601634558e-05, reference_loss: 39.830501556396484
2023-05-11 23:51:01,044	44k	INFO	====> Epoch: 259, cost 87.23 s
2023-05-11 23:52:27,488	44k	INFO	====> Epoch: 260, cost 86.44 s
2023-05-11 23:52:53,831	44k	INFO	Train Epoch: 261 [12%]
2023-05-11 23:52:53,832	44k	INFO	Losses: [2.0811073780059814, 2.643122911453247, 11.60995864868164, 20.667049407958984, 0.9795186519622803], step: 39800, lr: 2.9040614501214555e-05, reference_loss: 37.98075485229492
2023-05-11 23:53:54,541	44k	INFO	====> Epoch: 261, cost 87.05 s
2023-05-11 23:54:41,763	44k	INFO	Train Epoch: 262 [43%]
2023-05-11 23:54:41,764	44k	INFO	Losses: [2.2680230140686035, 2.0158121585845947, 13.714014053344727, 20.011919021606445, 0.7242442965507507], step: 40000, lr: 2.90369844244019e-05, reference_loss: 38.7340087890625
2023-05-11 23:54:47,158	44k	INFO	Saving model and optimizer state at iteration 262 to ./logs\44k\G_40000.pth
2023-05-11 23:54:47,920	44k	INFO	Saving model and optimizer state at iteration 262 to ./logs\44k\D_40000.pth
2023-05-11 23:54:48,596	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_37000.pth
2023-05-11 23:54:48,643	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_37000.pth
2023-05-11 23:55:28,172	44k	INFO	====> Epoch: 262, cost 93.63 s
2023-05-11 23:56:36,433	44k	INFO	Train Epoch: 263 [74%]
2023-05-11 23:56:36,434	44k	INFO	Losses: [2.270467519760132, 2.1916332244873047, 12.428770065307617, 22.03148078918457, 0.7733843922615051], step: 40200, lr: 2.903335480134885e-05, reference_loss: 39.695735931396484
2023-05-11 23:56:55,056	44k	INFO	====> Epoch: 263, cost 86.88 s
2023-05-11 23:58:21,388	44k	INFO	====> Epoch: 264, cost 86.33 s
2023-05-11 23:58:42,315	44k	INFO	Train Epoch: 265 [5%]
2023-05-11 23:58:42,316	44k	INFO	Losses: [2.2979705333709717, 2.5276665687561035, 15.098774909973145, 20.4643611907959, 0.7607564330101013], step: 40400, lr: 2.9026096916294678e-05, reference_loss: 41.14952850341797
2023-05-11 23:59:48,509	44k	INFO	====> Epoch: 265, cost 87.12 s
2023-05-12 00:00:30,960	44k	INFO	Train Epoch: 266 [35%]
2023-05-12 00:00:30,961	44k	INFO	Losses: [2.3222877979278564, 2.3944623470306396, 12.199092864990234, 19.330812454223633, 0.7873807549476624], step: 40600, lr: 2.9022468654180138e-05, reference_loss: 37.03403854370117
2023-05-12 00:01:16,274	44k	INFO	====> Epoch: 266, cost 87.76 s
2023-05-12 00:02:19,493	44k	INFO	Train Epoch: 267 [66%]
2023-05-12 00:02:19,494	44k	INFO	Losses: [2.531327962875366, 2.6196436882019043, 7.450255393981934, 15.686241149902344, 0.8771728873252869], step: 40800, lr: 2.9018840845598365e-05, reference_loss: 29.164640426635742
2023-05-12 00:02:43,941	44k	INFO	====> Epoch: 267, cost 87.67 s
2023-05-12 00:04:07,895	44k	INFO	Train Epoch: 268 [97%]
2023-05-12 00:04:07,896	44k	INFO	Losses: [2.0768423080444336, 2.449065685272217, 14.927592277526855, 21.343576431274414, 0.6163033246994019], step: 41000, lr: 2.9015213490492665e-05, reference_loss: 41.41337966918945
2023-05-12 00:04:13,624	44k	INFO	Saving model and optimizer state at iteration 268 to ./logs\44k\G_41000.pth
2023-05-12 00:04:14,360	44k	INFO	Saving model and optimizer state at iteration 268 to ./logs\44k\D_41000.pth
2023-05-12 00:04:15,036	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_38000.pth
2023-05-12 00:04:15,090	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_38000.pth
2023-05-12 00:04:17,760	44k	INFO	====> Epoch: 268, cost 93.82 s
2023-05-12 00:05:44,723	44k	INFO	====> Epoch: 269, cost 86.96 s
2023-05-12 00:06:21,308	44k	INFO	Train Epoch: 270 [27%]
2023-05-12 00:06:21,308	44k	INFO	Losses: [2.1342616081237793, 2.8914928436279297, 12.985645294189453, 20.656923294067383, 1.0261586904525757], step: 41200, lr: 2.900796014048275e-05, reference_loss: 39.694480895996094
2023-05-12 00:07:11,763	44k	INFO	====> Epoch: 270, cost 87.04 s
2023-05-12 00:08:09,445	44k	INFO	Train Epoch: 271 [58%]
2023-05-12 00:08:09,445	44k	INFO	Losses: [2.667980194091797, 2.7980167865753174, 10.094583511352539, 19.34132957458496, 0.8694612383842468], step: 41400, lr: 2.900433414546519e-05, reference_loss: 35.77136993408203
2023-05-12 00:08:38,772	44k	INFO	====> Epoch: 271, cost 87.01 s
2023-05-12 00:09:57,600	44k	INFO	Train Epoch: 272 [89%]
2023-05-12 00:09:57,600	44k	INFO	Losses: [2.0318732261657715, 2.6755869388580322, 11.406761169433594, 15.29020881652832, 0.9756430983543396], step: 41600, lr: 2.9000708603697004e-05, reference_loss: 32.38007354736328
2023-05-12 00:10:05,831	44k	INFO	====> Epoch: 272, cost 87.06 s
2023-05-12 00:11:32,647	44k	INFO	====> Epoch: 273, cost 86.82 s
2023-05-12 00:12:03,602	44k	INFO	Train Epoch: 274 [20%]
2023-05-12 00:12:03,603	44k	INFO	Losses: [2.566847801208496, 2.239710569381714, 9.606109619140625, 20.148448944091797, 0.9577219486236572], step: 41800, lr: 2.899345887968215e-05, reference_loss: 35.51884078979492
2023-05-12 00:12:59,370	44k	INFO	====> Epoch: 274, cost 86.72 s
2023-05-12 00:13:51,538	44k	INFO	Train Epoch: 275 [50%]
2023-05-12 00:13:51,538	44k	INFO	Losses: [2.529519557952881, 2.3417234420776367, 9.40464973449707, 15.548064231872559, 0.7062731385231018], step: 42000, lr: 2.8989834697322186e-05, reference_loss: 30.530229568481445
2023-05-12 00:13:56,955	44k	INFO	Saving model and optimizer state at iteration 275 to ./logs\44k\G_42000.pth
2023-05-12 00:13:57,893	44k	INFO	Saving model and optimizer state at iteration 275 to ./logs\44k\D_42000.pth
2023-05-12 00:13:58,598	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_39000.pth
2023-05-12 00:13:58,646	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_39000.pth
2023-05-12 00:14:33,022	44k	INFO	====> Epoch: 275, cost 93.65 s
2023-05-12 00:15:46,056	44k	INFO	Train Epoch: 276 [81%]
2023-05-12 00:15:46,056	44k	INFO	Losses: [2.4142253398895264, 2.3950157165527344, 12.35134506225586, 19.385360717773438, 0.9850819706916809], step: 42200, lr: 2.8986210967985018e-05, reference_loss: 37.531028747558594
2023-05-12 00:15:59,824	44k	INFO	====> Epoch: 276, cost 86.80 s
2023-05-12 00:17:26,260	44k	INFO	====> Epoch: 277, cost 86.44 s
2023-05-12 00:17:52,136	44k	INFO	Train Epoch: 278 [12%]
2023-05-12 00:17:52,136	44k	INFO	Losses: [2.146235227584839, 2.4149203300476074, 11.63279914855957, 18.732440948486328, 0.7447122931480408], step: 42400, lr: 2.897896486815257e-05, reference_loss: 35.67110824584961
2023-05-12 00:18:53,435	44k	INFO	====> Epoch: 278, cost 87.17 s
2023-05-12 00:19:40,228	44k	INFO	Train Epoch: 279 [42%]
2023-05-12 00:19:40,228	44k	INFO	Losses: [2.163267135620117, 2.6091108322143555, 11.535022735595703, 19.45165252685547, 0.8022618889808655], step: 42600, lr: 2.8975342497544048e-05, reference_loss: 36.56131362915039
2023-05-12 00:20:20,517	44k	INFO	====> Epoch: 279, cost 87.08 s
2023-05-12 00:21:28,375	44k	INFO	Train Epoch: 280 [73%]
2023-05-12 00:21:28,375	44k	INFO	Losses: [2.1821250915527344, 2.3811721801757812, 14.84898567199707, 19.10666847229004, 1.2198735475540161], step: 42800, lr: 2.8971720579731854e-05, reference_loss: 39.738826751708984
2023-05-12 00:21:47,563	44k	INFO	====> Epoch: 280, cost 87.05 s
2023-05-12 00:23:13,913	44k	INFO	====> Epoch: 281, cost 86.35 s
2023-05-12 00:23:34,341	44k	INFO	Train Epoch: 282 [4%]
2023-05-12 00:23:34,341	44k	INFO	Losses: [2.436422109603882, 2.386256456375122, 11.608360290527344, 19.41828727722168, 0.9322484731674194], step: 43000, lr: 2.8964478102270053e-05, reference_loss: 36.78157424926758
2023-05-12 00:23:40,020	44k	INFO	Saving model and optimizer state at iteration 282 to ./logs\44k\G_43000.pth
2023-05-12 00:23:40,831	44k	INFO	Saving model and optimizer state at iteration 282 to ./logs\44k\D_43000.pth
2023-05-12 00:23:41,524	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_40000.pth
2023-05-12 00:23:41,571	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_40000.pth
2023-05-12 00:24:47,728	44k	INFO	====> Epoch: 282, cost 93.82 s
2023-05-12 00:25:29,129	44k	INFO	Train Epoch: 283 [35%]
2023-05-12 00:25:29,129	44k	INFO	Losses: [2.3282203674316406, 2.499232292175293, 11.087320327758789, 20.374372482299805, 1.0009374618530273], step: 43200, lr: 2.8960857542507267e-05, reference_loss: 37.29008483886719
2023-05-12 00:26:14,848	44k	INFO	====> Epoch: 283, cost 87.12 s
2023-05-12 00:27:17,414	44k	INFO	Train Epoch: 284 [65%]
2023-05-12 00:27:17,414	44k	INFO	Losses: [3.2481675148010254, 2.1694464683532715, 15.336135864257812, 19.12453842163086, 0.6457279324531555], step: 43400, lr: 2.8957237435314452e-05, reference_loss: 40.524017333984375
2023-05-12 00:27:42,011	44k	INFO	====> Epoch: 284, cost 87.16 s
2023-05-12 00:29:06,052	44k	INFO	Train Epoch: 285 [96%]
2023-05-12 00:29:06,052	44k	INFO	Losses: [2.5966134071350098, 1.9764971733093262, 11.448287010192871, 14.873833656311035, 0.9429264664649963], step: 43600, lr: 2.8953617780635037e-05, reference_loss: 31.83815574645996
2023-05-12 00:29:09,508	44k	INFO	====> Epoch: 285, cost 87.50 s
2023-05-12 00:30:35,868	44k	INFO	====> Epoch: 286, cost 86.36 s
2023-05-12 00:31:12,031	44k	INFO	Train Epoch: 287 [27%]
2023-05-12 00:31:12,032	44k	INFO	Losses: [2.3675150871276855, 2.597141981124878, 12.064946174621582, 18.58349609375, 0.8166589736938477], step: 43800, lr: 2.8946379828590154e-05, reference_loss: 36.42975616455078
2023-05-12 00:32:02,829	44k	INFO	====> Epoch: 287, cost 86.96 s
2023-05-12 00:32:59,645	44k	INFO	Train Epoch: 288 [58%]
2023-05-12 00:32:59,646	44k	INFO	Losses: [2.576910972595215, 2.197340726852417, 12.096631050109863, 20.428077697753906, 0.9696913361549377], step: 44000, lr: 2.894276153111158e-05, reference_loss: 38.268653869628906
2023-05-12 00:33:05,202	44k	INFO	Saving model and optimizer state at iteration 288 to ./logs\44k\G_44000.pth
2023-05-12 00:33:05,983	44k	INFO	Saving model and optimizer state at iteration 288 to ./logs\44k\D_44000.pth
2023-05-12 00:33:06,658	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_41000.pth
2023-05-12 00:33:06,695	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_41000.pth
2023-05-12 00:33:36,184	44k	INFO	====> Epoch: 288, cost 93.35 s
2023-05-12 00:34:54,184	44k	INFO	Train Epoch: 289 [88%]
2023-05-12 00:34:54,185	44k	INFO	Losses: [2.233393430709839, 2.3542733192443848, 12.026976585388184, 21.86504554748535, 1.0087814331054688], step: 44200, lr: 2.893914368592019e-05, reference_loss: 39.48847198486328
2023-05-12 00:35:02,987	44k	INFO	====> Epoch: 289, cost 86.80 s
2023-05-12 00:36:29,670	44k	INFO	====> Epoch: 290, cost 86.68 s
2023-05-12 00:37:00,382	44k	INFO	Train Epoch: 291 [19%]
2023-05-12 00:37:00,383	44k	INFO	Losses: [2.503129482269287, 2.6620848178863525, 12.32503604888916, 18.790834426879883, 1.2946611642837524], step: 44400, lr: 2.8931909352172828e-05, reference_loss: 37.57574462890625
2023-05-12 00:37:56,944	44k	INFO	====> Epoch: 291, cost 87.27 s
2023-05-12 00:38:48,948	44k	INFO	Train Epoch: 292 [50%]
2023-05-12 00:38:48,948	44k	INFO	Losses: [2.2488231658935547, 2.6991515159606934, 15.310731887817383, 19.656644821166992, 0.7508647441864014], step: 44600, lr: 2.8928292863503805e-05, reference_loss: 40.66621780395508
2023-05-12 00:39:24,133	44k	INFO	====> Epoch: 292, cost 87.19 s
2023-05-12 00:40:36,904	44k	INFO	Train Epoch: 293 [80%]
2023-05-12 00:40:36,904	44k	INFO	Losses: [2.274759292602539, 2.5190110206604004, 14.346514701843262, 17.961681365966797, 0.5254409313201904], step: 44800, lr: 2.8924676826895866e-05, reference_loss: 37.62740707397461
2023-05-12 00:40:51,057	44k	INFO	====> Epoch: 293, cost 86.92 s
2023-05-12 00:42:17,566	44k	INFO	====> Epoch: 294, cost 86.51 s
2023-05-12 00:42:42,906	44k	INFO	Train Epoch: 295 [11%]
2023-05-12 00:42:42,907	44k	INFO	Losses: [2.1780483722686768, 2.305142402648926, 12.447136878967285, 18.825618743896484, 0.5107586979866028], step: 45000, lr: 2.8917446109637215e-05, reference_loss: 36.26670455932617
2023-05-12 00:42:48,325	44k	INFO	Saving model and optimizer state at iteration 295 to ./logs\44k\G_45000.pth
2023-05-12 00:42:49,140	44k	INFO	Saving model and optimizer state at iteration 295 to ./logs\44k\D_45000.pth
2023-05-12 00:42:49,810	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_42000.pth
2023-05-12 00:42:49,854	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_42000.pth
2023-05-12 00:43:51,243	44k	INFO	====> Epoch: 295, cost 93.68 s
2023-05-12 00:44:37,622	44k	INFO	Train Epoch: 296 [42%]
2023-05-12 00:44:37,622	44k	INFO	Losses: [2.179664134979248, 2.6126747131347656, 13.71163558959961, 18.07395362854004, 0.6545605659484863], step: 45200, lr: 2.891383142887351e-05, reference_loss: 37.232486724853516
2023-05-12 00:45:18,392	44k	INFO	====> Epoch: 296, cost 87.15 s
2023-05-12 00:46:25,892	44k	INFO	Train Epoch: 297 [73%]
2023-05-12 00:46:25,892	44k	INFO	Losses: [2.4465785026550293, 2.7403557300567627, 11.507038116455078, 15.70568561553955, 0.9382854104042053], step: 45400, lr: 2.8910217199944898e-05, reference_loss: 33.33794403076172
2023-05-12 00:46:45,478	44k	INFO	====> Epoch: 297, cost 87.09 s
2023-05-12 00:48:12,077	44k	INFO	====> Epoch: 298, cost 86.60 s
2023-05-12 00:48:32,174	44k	INFO	Train Epoch: 299 [3%]
2023-05-12 00:48:32,174	44k	INFO	Losses: [1.9995447397232056, 2.6359925270080566, 15.022774696350098, 19.879331588745117, 0.8272438645362854], step: 45600, lr: 2.8902990097367054e-05, reference_loss: 40.36488723754883
2023-05-12 00:49:39,001	44k	INFO	====> Epoch: 299, cost 86.92 s
2023-05-12 00:50:19,889	44k	INFO	Train Epoch: 300 [34%]
2023-05-12 00:50:19,889	44k	INFO	Losses: [2.3646130561828613, 2.3081157207489014, 13.545132637023926, 19.039533615112305, 0.8943161368370056], step: 45800, lr: 2.889937722360488e-05, reference_loss: 38.151710510253906
2023-05-12 00:51:05,843	44k	INFO	====> Epoch: 300, cost 86.84 s
2023-05-12 00:52:07,801	44k	INFO	Train Epoch: 301 [65%]
2023-05-12 00:52:07,802	44k	INFO	Losses: [2.352902889251709, 2.4987077713012695, 15.375273704528809, 20.87496566772461, 0.5966988801956177], step: 46000, lr: 2.889576480145193e-05, reference_loss: 41.698551177978516
2023-05-12 00:52:13,274	44k	INFO	Saving model and optimizer state at iteration 301 to ./logs\44k\G_46000.pth
2023-05-12 00:52:14,222	44k	INFO	Saving model and optimizer state at iteration 301 to ./logs\44k\D_46000.pth
2023-05-12 00:52:14,916	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_43000.pth
2023-05-12 00:52:14,959	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_43000.pth
2023-05-12 00:52:39,610	44k	INFO	====> Epoch: 301, cost 93.77 s
2023-05-12 00:54:02,639	44k	INFO	Train Epoch: 302 [95%]
2023-05-12 00:54:02,639	44k	INFO	Losses: [2.4250588417053223, 2.498613119125366, 13.063399314880371, 19.875106811523438, 0.41463860869407654], step: 46200, lr: 2.8892152830851748e-05, reference_loss: 38.276817321777344
2023-05-12 00:54:06,440	44k	INFO	====> Epoch: 302, cost 86.83 s
2023-05-12 00:55:33,027	44k	INFO	====> Epoch: 303, cost 86.59 s
2023-05-12 00:56:08,422	44k	INFO	Train Epoch: 304 [26%]
2023-05-12 00:56:08,422	44k	INFO	Losses: [2.387110948562622, 2.7058818340301514, 14.592483520507812, 21.623506546020508, 0.9172285199165344], step: 46400, lr: 2.888493024408392e-05, reference_loss: 42.22621154785156
2023-05-12 00:56:59,821	44k	INFO	====> Epoch: 304, cost 86.79 s
2023-05-12 00:57:56,524	44k	INFO	Train Epoch: 305 [57%]
2023-05-12 00:57:56,524	44k	INFO	Losses: [2.4622392654418945, 2.3903815746307373, 10.271135330200195, 14.112380027770996, 0.3740549087524414], step: 46600, lr: 2.8881319627803408e-05, reference_loss: 29.610191345214844
2023-05-12 00:58:26,824	44k	INFO	====> Epoch: 305, cost 87.00 s
2023-05-12 00:59:44,598	44k	INFO	Train Epoch: 306 [88%]
2023-05-12 00:59:44,599	44k	INFO	Losses: [2.487091541290283, 2.387373685836792, 9.689733505249023, 17.634672164916992, 0.7646937370300293], step: 46800, lr: 2.887770946284993e-05, reference_loss: 32.963565826416016
2023-05-12 00:59:53,680	44k	INFO	====> Epoch: 306, cost 86.86 s
2023-05-12 01:01:20,127	44k	INFO	====> Epoch: 307, cost 86.45 s
2023-05-12 01:01:50,348	44k	INFO	Train Epoch: 308 [18%]
2023-05-12 01:01:50,349	44k	INFO	Losses: [2.3481314182281494, 2.5659570693969727, 7.266246795654297, 14.47097110748291, 0.808350682258606], step: 47000, lr: 2.8870490486698423e-05, reference_loss: 27.459657669067383
2023-05-12 01:01:55,905	44k	INFO	Saving model and optimizer state at iteration 308 to ./logs\44k\G_47000.pth
2023-05-12 01:01:56,718	44k	INFO	Saving model and optimizer state at iteration 308 to ./logs\44k\D_47000.pth
2023-05-12 01:01:57,409	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_44000.pth
2023-05-12 01:01:57,455	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_44000.pth
2023-05-12 01:02:54,072	44k	INFO	====> Epoch: 308, cost 93.95 s
2023-05-12 01:03:45,438	44k	INFO	Train Epoch: 309 [49%]
2023-05-12 01:03:45,438	44k	INFO	Losses: [2.4460787773132324, 2.30411434173584, 12.190338134765625, 20.029176712036133, 0.8841606974601746], step: 47200, lr: 2.8866881675387583e-05, reference_loss: 37.85386657714844
2023-05-12 01:04:21,154	44k	INFO	====> Epoch: 309, cost 87.08 s
2023-05-12 01:05:33,737	44k	INFO	Train Epoch: 310 [80%]
2023-05-12 01:05:33,738	44k	INFO	Losses: [2.3092551231384277, 2.3792567253112793, 14.208582878112793, 19.56374740600586, 0.978696346282959], step: 47400, lr: 2.886327331517816e-05, reference_loss: 39.439537048339844
2023-05-12 01:05:48,301	44k	INFO	====> Epoch: 310, cost 87.15 s
2023-05-12 01:07:15,531	44k	INFO	====> Epoch: 311, cost 87.23 s
2023-05-12 01:07:40,468	44k	INFO	Train Epoch: 312 [10%]
2023-05-12 01:07:40,469	44k	INFO	Losses: [2.330749988555908, 2.2947089672088623, 10.925325393676758, 20.311233520507812, 0.7993677258491516], step: 47600, lr: 2.8856057947838005e-05, reference_loss: 36.66138458251953
2023-05-12 01:08:42,644	44k	INFO	====> Epoch: 312, cost 87.11 s
2023-05-12 01:09:28,547	44k	INFO	Train Epoch: 313 [41%]
2023-05-12 01:09:28,548	44k	INFO	Losses: [2.5556211471557617, 2.1875720024108887, 11.887537002563477, 20.122758865356445, 0.9945183992385864], step: 47800, lr: 2.8852450940594525e-05, reference_loss: 37.74800491333008
2023-05-12 01:10:09,693	44k	INFO	====> Epoch: 313, cost 87.05 s
2023-05-12 01:11:16,820	44k	INFO	Train Epoch: 314 [72%]
2023-05-12 01:11:16,821	44k	INFO	Losses: [2.2254743576049805, 2.639667510986328, 10.683056831359863, 20.9825439453125, 0.4391290545463562], step: 48000, lr: 2.884884438422695e-05, reference_loss: 36.969871520996094
2023-05-12 01:11:22,327	44k	INFO	Saving model and optimizer state at iteration 314 to ./logs\44k\G_48000.pth
2023-05-12 01:11:23,154	44k	INFO	Saving model and optimizer state at iteration 314 to ./logs\44k\D_48000.pth
2023-05-12 01:11:23,835	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_45000.pth
2023-05-12 01:11:23,872	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_45000.pth
2023-05-12 01:11:43,537	44k	INFO	====> Epoch: 314, cost 93.84 s
2023-05-12 01:13:10,303	44k	INFO	====> Epoch: 315, cost 86.77 s
2023-05-12 01:13:29,999	44k	INFO	Train Epoch: 316 [3%]
2023-05-12 01:13:29,999	44k	INFO	Losses: [2.30355167388916, 2.469939947128296, 11.87990665435791, 18.41738510131836, 0.6748366355895996], step: 48200, lr: 2.8841632623894083e-05, reference_loss: 35.74562072753906
2023-05-12 01:14:37,554	44k	INFO	====> Epoch: 316, cost 87.25 s
2023-05-12 01:15:18,155	44k	INFO	Train Epoch: 317 [33%]
2023-05-12 01:15:18,156	44k	INFO	Losses: [2.3286733627319336, 2.447099447250366, 13.856201171875, 19.788793563842773, 0.4912005662918091], step: 48400, lr: 2.8838027419816096e-05, reference_loss: 38.91196823120117
2023-05-12 01:16:04,735	44k	INFO	====> Epoch: 317, cost 87.18 s
2023-05-12 01:17:06,433	44k	INFO	Train Epoch: 318 [64%]
2023-05-12 01:17:06,434	44k	INFO	Losses: [2.553659677505493, 2.232065200805664, 12.68171501159668, 18.623472213745117, 0.34664177894592285], step: 48600, lr: 2.883442266638862e-05, reference_loss: 36.43755340576172
2023-05-12 01:17:31,853	44k	INFO	====> Epoch: 318, cost 87.12 s
2023-05-12 01:18:54,509	44k	INFO	Train Epoch: 319 [95%]
2023-05-12 01:18:54,510	44k	INFO	Losses: [2.353644371032715, 2.110971450805664, 10.525450706481934, 18.927993774414062, 0.6254878044128418], step: 48800, lr: 2.883081836355532e-05, reference_loss: 34.543548583984375
2023-05-12 01:18:58,751	44k	INFO	====> Epoch: 319, cost 86.90 s
2023-05-12 01:20:25,568	44k	INFO	====> Epoch: 320, cost 86.82 s
2023-05-12 01:21:00,706	44k	INFO	Train Epoch: 321 [25%]
2023-05-12 01:21:00,706	44k	INFO	Losses: [2.8630709648132324, 2.2152042388916016, 8.358444213867188, 19.07183837890625, 0.3670879900455475], step: 49000, lr: 2.8823611109445964e-05, reference_loss: 32.875648498535156
2023-05-12 01:21:06,206	44k	INFO	Saving model and optimizer state at iteration 321 to ./logs\44k\G_49000.pth
2023-05-12 01:21:06,923	44k	INFO	Saving model and optimizer state at iteration 321 to ./logs\44k\D_49000.pth
2023-05-12 01:21:07,594	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_46000.pth
2023-05-12 01:21:07,638	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_46000.pth
2023-05-12 01:21:59,375	44k	INFO	====> Epoch: 321, cost 93.81 s
2023-05-12 01:22:55,624	44k	INFO	Train Epoch: 322 [56%]
2023-05-12 01:22:55,625	44k	INFO	Losses: [2.4059181213378906, 2.1029815673828125, 14.136219024658203, 20.452367782592773, 0.8831208348274231], step: 49200, lr: 2.882000815805728e-05, reference_loss: 39.98060989379883
2023-05-12 01:23:26,575	44k	INFO	====> Epoch: 322, cost 87.20 s
2023-05-12 01:24:44,016	44k	INFO	Train Epoch: 323 [87%]
2023-05-12 01:24:44,017	44k	INFO	Losses: [2.3768985271453857, 2.436417818069458, 13.863051414489746, 18.966707229614258, 0.7688087224960327], step: 49400, lr: 2.8816405657037522e-05, reference_loss: 38.41188430786133
2023-05-12 01:24:53,651	44k	INFO	====> Epoch: 323, cost 87.08 s
2023-05-12 01:26:20,075	44k	INFO	====> Epoch: 324, cost 86.42 s
2023-05-12 01:26:49,956	44k	INFO	Train Epoch: 325 [18%]
2023-05-12 01:26:49,956	44k	INFO	Losses: [2.3294930458068848, 2.436582565307617, 12.034727096557617, 19.019193649291992, 0.4922015070915222], step: 49600, lr: 2.8809202005879602e-05, reference_loss: 36.312198638916016
2023-05-12 01:27:47,111	44k	INFO	====> Epoch: 325, cost 87.04 s
2023-05-12 01:28:37,805	44k	INFO	Train Epoch: 326 [48%]
2023-05-12 01:28:37,805	44k	INFO	Losses: [2.3499183654785156, 2.2858476638793945, 14.409664154052734, 15.920552253723145, 0.7514058351516724], step: 49800, lr: 2.8805600855628865e-05, reference_loss: 35.71738815307617
2023-05-12 01:29:13,948	44k	INFO	====> Epoch: 326, cost 86.84 s
2023-05-12 01:30:26,142	44k	INFO	Train Epoch: 327 [79%]
2023-05-12 01:30:26,143	44k	INFO	Losses: [2.288236379623413, 2.291294574737549, 13.502463340759277, 20.392406463623047, 0.6512307524681091], step: 50000, lr: 2.880200015552191e-05, reference_loss: 39.12562942504883
2023-05-12 01:30:31,704	44k	INFO	Saving model and optimizer state at iteration 327 to ./logs\44k\G_50000.pth
2023-05-12 01:30:32,652	44k	INFO	Saving model and optimizer state at iteration 327 to ./logs\44k\D_50000.pth
2023-05-12 01:30:33,341	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_47000.pth
2023-05-12 01:30:33,385	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_47000.pth
2023-05-12 01:30:48,093	44k	INFO	====> Epoch: 327, cost 94.15 s
2023-05-12 01:32:14,785	44k	INFO	====> Epoch: 328, cost 86.69 s
2023-05-12 01:32:39,281	44k	INFO	Train Epoch: 329 [10%]
2023-05-12 01:32:39,281	44k	INFO	Losses: [2.5760297775268555, 2.0475826263427734, 8.679187774658203, 18.01605796813965, 0.6341844797134399], step: 50200, lr: 2.879480010551428e-05, reference_loss: 31.95304298400879
2023-05-12 01:33:41,846	44k	INFO	====> Epoch: 329, cost 87.06 s
2023-05-12 01:34:27,354	44k	INFO	Train Epoch: 330 [41%]
2023-05-12 01:34:27,355	44k	INFO	Losses: [2.511593818664551, 2.1043527126312256, 13.312424659729004, 20.48750877380371, 0.917515218257904], step: 50400, lr: 2.879120075550109e-05, reference_loss: 39.33339309692383
2023-05-12 01:35:08,859	44k	INFO	====> Epoch: 330, cost 87.01 s
2023-05-12 01:36:15,389	44k	INFO	Train Epoch: 331 [71%]
2023-05-12 01:36:15,389	44k	INFO	Losses: [2.3014283180236816, 2.235219955444336, 12.459945678710938, 21.13761329650879, 0.7915703654289246], step: 50600, lr: 2.8787601855406652e-05, reference_loss: 38.925777435302734
2023-05-12 01:36:35,845	44k	INFO	====> Epoch: 331, cost 86.99 s
2023-05-12 01:38:02,420	44k	INFO	====> Epoch: 332, cost 86.57 s
2023-05-12 01:38:21,436	44k	INFO	Train Epoch: 333 [2%]
2023-05-12 01:38:21,437	44k	INFO	Losses: [2.326077699661255, 2.612873077392578, 11.030153274536133, 17.739837646484375, 0.7160561084747314], step: 50800, lr: 2.878040540474908e-05, reference_loss: 34.42499923706055
2023-05-12 01:39:29,323	44k	INFO	====> Epoch: 333, cost 86.90 s
2023-05-12 01:40:09,620	44k	INFO	Train Epoch: 334 [33%]
2023-05-12 01:40:09,621	44k	INFO	Losses: [2.2525033950805664, 1.9147224426269531, 17.99275779724121, 18.474515914916992, 0.5406356453895569], step: 51000, lr: 2.8776807854073486e-05, reference_loss: 41.175132751464844
2023-05-12 01:40:15,069	44k	INFO	Saving model and optimizer state at iteration 334 to ./logs\44k\G_51000.pth
2023-05-12 01:40:15,889	44k	INFO	Saving model and optimizer state at iteration 334 to ./logs\44k\D_51000.pth
2023-05-12 01:40:16,578	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_48000.pth
2023-05-12 01:40:16,621	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_48000.pth
2023-05-12 01:41:03,320	44k	INFO	====> Epoch: 334, cost 94.00 s
2023-05-12 01:42:04,386	44k	INFO	Train Epoch: 335 [63%]
2023-05-12 01:42:04,386	44k	INFO	Losses: [2.64439058303833, 2.156479597091675, 10.21287727355957, 19.386377334594727, 0.8178606033325195], step: 51200, lr: 2.8773210753091726e-05, reference_loss: 35.21798324584961
2023-05-12 01:42:30,304	44k	INFO	====> Epoch: 335, cost 86.98 s
2023-05-12 01:43:52,594	44k	INFO	Train Epoch: 336 [94%]
2023-05-12 01:43:52,595	44k	INFO	Losses: [2.377340078353882, 2.4160428047180176, 12.378716468811035, 19.029603958129883, 1.0963490009307861], step: 51400, lr: 2.8769614101747588e-05, reference_loss: 37.29805374145508
2023-05-12 01:43:57,236	44k	INFO	====> Epoch: 336, cost 86.93 s
2023-05-12 01:45:23,761	44k	INFO	====> Epoch: 337, cost 86.52 s
2023-05-12 01:45:58,628	44k	INFO	Train Epoch: 338 [25%]
2023-05-12 01:45:58,628	44k	INFO	Losses: [2.4006423950195312, 2.4499778747558594, 6.625148296356201, 16.560646057128906, 0.5126820206642151], step: 51600, lr: 2.876242214774737e-05, reference_loss: 28.549097061157227
2023-05-12 01:46:50,855	44k	INFO	====> Epoch: 338, cost 87.09 s
2023-05-12 01:47:46,819	44k	INFO	Train Epoch: 339 [56%]
2023-05-12 01:47:46,820	44k	INFO	Losses: [2.4874658584594727, 2.2976598739624023, 5.2647271156311035, 19.872941970825195, 0.9726997017860413], step: 51800, lr: 2.87588268449789e-05, reference_loss: 30.89549446105957
2023-05-12 01:48:18,144	44k	INFO	====> Epoch: 339, cost 87.29 s
2023-05-12 01:49:35,389	44k	INFO	Train Epoch: 340 [86%]
2023-05-12 01:49:35,389	44k	INFO	Losses: [2.4471659660339355, 2.3027732372283936, 9.362944602966309, 19.69312286376953, 1.0759491920471191], step: 52000, lr: 2.8755231991623277e-05, reference_loss: 34.8819580078125
2023-05-12 01:49:40,985	44k	INFO	Saving model and optimizer state at iteration 340 to ./logs\44k\G_52000.pth
2023-05-12 01:49:41,749	44k	INFO	Saving model and optimizer state at iteration 340 to ./logs\44k\D_52000.pth
2023-05-12 01:49:42,429	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_49000.pth
2023-05-12 01:49:42,478	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_49000.pth
2023-05-12 01:49:52,376	44k	INFO	====> Epoch: 340, cost 94.23 s
2023-05-12 01:51:19,339	44k	INFO	====> Epoch: 341, cost 86.96 s
2023-05-12 01:51:48,886	44k	INFO	Train Epoch: 342 [17%]
2023-05-12 01:51:48,886	44k	INFO	Losses: [2.056257724761963, 2.6781301498413086, 11.904544830322266, 19.655420303344727, 0.4471868872642517], step: 52200, lr: 2.874804363292587e-05, reference_loss: 36.741539001464844
2023-05-12 01:52:46,626	44k	INFO	====> Epoch: 342, cost 87.29 s
2023-05-12 01:53:37,212	44k	INFO	Train Epoch: 343 [48%]
2023-05-12 01:53:37,213	44k	INFO	Losses: [2.4085354804992676, 2.0151638984680176, 14.059934616088867, 17.7779598236084, 0.9267661571502686], step: 52400, lr: 2.8744450127471752e-05, reference_loss: 37.18836212158203
2023-05-12 01:54:13,726	44k	INFO	====> Epoch: 343, cost 87.10 s
2023-05-12 01:55:25,273	44k	INFO	Train Epoch: 344 [78%]
2023-05-12 01:55:25,274	44k	INFO	Losses: [2.221299648284912, 2.4725427627563477, 15.116349220275879, 19.373258590698242, 0.903636634349823], step: 52600, lr: 2.8740857071205818e-05, reference_loss: 40.08708572387695
2023-05-12 01:55:40,690	44k	INFO	====> Epoch: 344, cost 86.96 s
2023-05-12 01:57:07,225	44k	INFO	====> Epoch: 345, cost 86.54 s
2023-05-12 01:57:31,280	44k	INFO	Train Epoch: 346 [9%]
2023-05-12 01:57:31,280	44k	INFO	Losses: [2.626565456390381, 2.385859251022339, 18.240093231201172, 22.404682159423828, 0.5306336879730225], step: 52800, lr: 2.8733672306013904e-05, reference_loss: 46.18783187866211
2023-05-12 01:58:34,193	44k	INFO	====> Epoch: 346, cost 86.97 s
2023-05-12 01:59:19,119	44k	INFO	Train Epoch: 347 [40%]
2023-05-12 01:59:19,120	44k	INFO	Losses: [2.2890186309814453, 2.8318262100219727, 11.400150299072266, 20.889436721801758, 0.9493915438652039], step: 53000, lr: 2.873008059697565e-05, reference_loss: 38.35982131958008
2023-05-12 01:59:24,897	44k	INFO	Saving model and optimizer state at iteration 347 to ./logs\44k\G_53000.pth
2023-05-12 01:59:25,592	44k	INFO	Saving model and optimizer state at iteration 347 to ./logs\44k\D_53000.pth
2023-05-12 01:59:26,293	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_50000.pth
2023-05-12 01:59:26,344	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_50000.pth
2023-05-12 02:00:08,121	44k	INFO	====> Epoch: 347, cost 93.93 s
2023-05-12 02:01:15,219	44k	INFO	Train Epoch: 348 [71%]
2023-05-12 02:01:15,249	44k	INFO	Losses: [2.135772228240967, 2.430205821990967, 13.827906608581543, 19.59593963623047, 0.6215983033180237], step: 53200, lr: 2.872648933690103e-05, reference_loss: 38.611419677734375
2023-05-12 02:01:36,625	44k	INFO	====> Epoch: 348, cost 88.50 s
2023-05-12 02:03:08,824	44k	INFO	====> Epoch: 349, cost 92.20 s
2023-05-12 02:03:29,335	44k	INFO	Train Epoch: 350 [1%]
2023-05-12 02:03:29,335	44k	INFO	Losses: [2.505711078643799, 2.1741676330566406, 14.022588729858398, 19.024606704711914, 0.5488510727882385], step: 53400, lr: 2.87193081634182e-05, reference_loss: 38.27592468261719
2023-05-12 02:04:42,226	44k	INFO	====> Epoch: 350, cost 93.40 s
2023-05-12 02:05:22,984	44k	INFO	Train Epoch: 351 [32%]
2023-05-12 02:05:22,985	44k	INFO	Losses: [2.6690385341644287, 1.7679072618484497, 7.874725818634033, 13.426702499389648, 0.4435964524745941], step: 53600, lr: 2.8715718249897772e-05, reference_loss: 26.181970596313477
2023-05-12 02:06:12,245	44k	INFO	====> Epoch: 351, cost 90.02 s
2023-05-12 02:07:17,161	44k	INFO	Train Epoch: 352 [63%]
2023-05-12 02:07:17,161	44k	INFO	Losses: [2.487330436706543, 2.7899012565612793, 12.667108535766602, 18.220800399780273, 1.3599427938461304], step: 53800, lr: 2.8712128785116532e-05, reference_loss: 37.525081634521484
2023-05-12 02:07:44,237	44k	INFO	====> Epoch: 352, cost 91.99 s
2023-05-12 02:09:10,263	44k	INFO	Train Epoch: 353 [93%]
2023-05-12 02:09:10,263	44k	INFO	Losses: [2.3179638385772705, 2.493180274963379, 12.37921142578125, 20.10038948059082, 0.9981839060783386], step: 54000, lr: 2.8708539769018392e-05, reference_loss: 38.2889289855957
2023-05-12 02:09:15,916	44k	INFO	Saving model and optimizer state at iteration 353 to ./logs\44k\G_54000.pth
2023-05-12 02:09:16,886	44k	INFO	Saving model and optimizer state at iteration 353 to ./logs\44k\D_54000.pth
2023-05-12 02:09:17,647	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_51000.pth
2023-05-12 02:09:17,695	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_51000.pth
2023-05-12 02:09:22,748	44k	INFO	====> Epoch: 353, cost 98.51 s
2023-05-12 02:10:51,117	44k	INFO	====> Epoch: 354, cost 88.37 s
2023-05-12 02:11:26,040	44k	INFO	Train Epoch: 355 [24%]
2023-05-12 02:11:26,041	44k	INFO	Losses: [2.1455252170562744, 2.470700263977051, 15.370835304260254, 23.028362274169922, 0.6955864429473877], step: 54200, lr: 2.870136308264707e-05, reference_loss: 43.71100997924805
2023-05-12 02:12:19,889	44k	INFO	====> Epoch: 355, cost 88.77 s
2023-05-12 02:13:16,123	44k	INFO	Train Epoch: 356 [55%]
2023-05-12 02:13:16,124	44k	INFO	Losses: [2.0428402423858643, 2.7300283908843994, 9.124566078186035, 20.02855682373047, 0.8733258843421936], step: 54400, lr: 2.8697775412261737e-05, reference_loss: 34.79931640625
2023-05-12 02:13:48,641	44k	INFO	====> Epoch: 356, cost 88.75 s
2023-05-12 02:15:06,563	44k	INFO	Train Epoch: 357 [86%]
2023-05-12 02:15:06,564	44k	INFO	Losses: [2.4102957248687744, 2.350048542022705, 9.982596397399902, 14.040148735046387, 0.6876527070999146], step: 54600, lr: 2.8694188190335202e-05, reference_loss: 29.470741271972656
2023-05-12 02:15:17,458	44k	INFO	====> Epoch: 357, cost 88.82 s
2023-05-12 02:16:45,755	44k	INFO	====> Epoch: 358, cost 88.30 s
2023-05-12 02:17:15,132	44k	INFO	Train Epoch: 359 [16%]
2023-05-12 02:17:15,132	44k	INFO	Losses: [2.596932888031006, 2.1161811351776123, 13.290535926818848, 19.867136001586914, 0.6504670977592468], step: 54800, lr: 2.8687015091634307e-05, reference_loss: 38.52125549316406
2023-05-12 02:18:14,495	44k	INFO	====> Epoch: 359, cost 88.74 s
2023-05-12 02:19:05,403	44k	INFO	Train Epoch: 360 [47%]
2023-05-12 02:19:05,404	44k	INFO	Losses: [2.4643959999084473, 2.1137897968292236, 16.21176528930664, 19.83914566040039, 0.9418043494224548], step: 55000, lr: 2.8683429214747853e-05, reference_loss: 41.570899963378906
2023-05-12 02:19:10,885	44k	INFO	Saving model and optimizer state at iteration 360 to ./logs\44k\G_55000.pth
2023-05-12 02:19:11,661	44k	INFO	Saving model and optimizer state at iteration 360 to ./logs\44k\D_55000.pth
2023-05-12 02:19:12,335	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_52000.pth
2023-05-12 02:19:12,384	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_52000.pth
2023-05-12 02:19:50,032	44k	INFO	====> Epoch: 360, cost 95.54 s
2023-05-12 02:21:04,059	44k	INFO	Train Epoch: 361 [78%]
2023-05-12 02:21:04,060	44k	INFO	Losses: [2.5475685596466064, 2.4578309059143066, 9.741727828979492, 20.154281616210938, 0.6961809396743774], step: 55200, lr: 2.8679843786096008e-05, reference_loss: 35.597591400146484
2023-05-12 02:21:20,229	44k	INFO	====> Epoch: 361, cost 90.20 s
2023-05-12 02:22:48,592	44k	INFO	====> Epoch: 362, cost 88.36 s
2023-05-12 02:23:12,610	44k	INFO	Train Epoch: 363 [8%]
2023-05-12 02:23:12,611	44k	INFO	Losses: [2.1323788166046143, 2.69551420211792, 14.48270034790039, 22.146411895751953, 1.365592122077942], step: 55400, lr: 2.867267427327204e-05, reference_loss: 42.82259750366211
2023-05-12 02:24:17,508	44k	INFO	====> Epoch: 363, cost 88.92 s
2023-05-12 02:25:02,968	44k	INFO	Train Epoch: 364 [39%]
2023-05-12 02:25:02,969	44k	INFO	Losses: [2.456886053085327, 2.774120807647705, 13.439095497131348, 20.270658493041992, 0.8473737835884094], step: 55600, lr: 2.866909018898788e-05, reference_loss: 39.78813171386719
2023-05-12 02:25:46,534	44k	INFO	====> Epoch: 364, cost 89.03 s
2023-05-12 02:26:53,429	44k	INFO	Train Epoch: 365 [70%]
2023-05-12 02:26:53,430	44k	INFO	Losses: [2.1103031635284424, 2.6911797523498535, 9.798227310180664, 16.85303497314453, 0.7356771230697632], step: 55800, lr: 2.8665506552714255e-05, reference_loss: 32.18842315673828
2023-05-12 02:27:15,273	44k	INFO	====> Epoch: 365, cost 88.74 s
2023-05-12 02:28:43,428	44k	INFO	====> Epoch: 366, cost 88.16 s
2023-05-12 02:29:01,862	44k	INFO	Train Epoch: 367 [1%]
2023-05-12 02:29:01,863	44k	INFO	Losses: [2.4494853019714355, 2.0860307216644287, 11.417633056640625, 13.177638053894043, 0.9124957323074341], step: 56000, lr: 2.8658340623974612e-05, reference_loss: 30.043283462524414
2023-05-12 02:29:07,468	44k	INFO	Saving model and optimizer state at iteration 367 to ./logs\44k\G_56000.pth
2023-05-12 02:29:08,254	44k	INFO	Saving model and optimizer state at iteration 367 to ./logs\44k\D_56000.pth
2023-05-12 02:29:08,936	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_53000.pth
2023-05-12 02:29:08,991	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_53000.pth
2023-05-12 02:30:19,073	44k	INFO	====> Epoch: 367, cost 95.64 s
2023-05-12 02:30:58,945	44k	INFO	Train Epoch: 368 [31%]
2023-05-12 02:30:58,946	44k	INFO	Losses: [2.0315427780151367, 2.8374533653259277, 14.525748252868652, 19.096439361572266, 0.7872524261474609], step: 56200, lr: 2.8654758331396613e-05, reference_loss: 39.27843475341797
2023-05-12 02:31:47,881	44k	INFO	====> Epoch: 368, cost 88.81 s
2023-05-12 02:32:49,455	44k	INFO	Train Epoch: 369 [62%]
2023-05-12 02:32:49,456	44k	INFO	Losses: [2.388775110244751, 2.0685250759124756, 8.523904800415039, 14.944770812988281, 0.9808571338653564], step: 56400, lr: 2.8651176486605187e-05, reference_loss: 28.90683364868164
2023-05-12 02:33:17,588	44k	INFO	====> Epoch: 369, cost 89.71 s
2023-05-12 02:34:40,738	44k	INFO	Train Epoch: 370 [93%]
2023-05-12 02:34:40,739	44k	INFO	Losses: [2.529674530029297, 2.3643620014190674, 8.816594123840332, 18.506458282470703, 0.8089593052864075], step: 56600, lr: 2.864759508954436e-05, reference_loss: 33.02604675292969
2023-05-12 02:34:46,425	44k	INFO	====> Epoch: 370, cost 88.84 s
2023-05-12 02:36:14,332	44k	INFO	====> Epoch: 371, cost 87.91 s
2023-05-12 02:36:48,274	44k	INFO	Train Epoch: 372 [24%]
2023-05-12 02:36:48,275	44k	INFO	Losses: [2.4553580284118652, 2.410719871520996, 11.060189247131348, 17.920082092285156, 0.912835955619812], step: 56800, lr: 2.864043363839064e-05, reference_loss: 34.759185791015625
2023-05-12 02:37:41,639	44k	INFO	====> Epoch: 372, cost 87.31 s
2023-05-12 02:38:36,735	44k	INFO	Train Epoch: 373 [54%]
2023-05-12 02:38:36,735	44k	INFO	Losses: [2.2265753746032715, 2.37687349319458, 10.90886116027832, 18.66537857055664, 0.7422361969947815], step: 57000, lr: 2.8636853584185842e-05, reference_loss: 34.919925689697266
2023-05-12 02:38:42,242	44k	INFO	Saving model and optimizer state at iteration 373 to ./logs\44k\G_57000.pth
2023-05-12 02:38:43,039	44k	INFO	Saving model and optimizer state at iteration 373 to ./logs\44k\D_57000.pth
2023-05-12 02:38:43,707	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_54000.pth
2023-05-12 02:38:43,761	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_54000.pth
2023-05-12 02:39:15,788	44k	INFO	====> Epoch: 373, cost 94.15 s
2023-05-12 02:40:32,230	44k	INFO	Train Epoch: 374 [85%]
2023-05-12 02:40:32,231	44k	INFO	Losses: [2.186521530151367, 2.876633882522583, 16.28428840637207, 22.0592041015625, 0.7332062125205994], step: 57200, lr: 2.8633273977487817e-05, reference_loss: 44.139854431152344
2023-05-12 02:40:43,415	44k	INFO	====> Epoch: 374, cost 87.63 s
2023-05-12 02:42:10,344	44k	INFO	====> Epoch: 375, cost 86.93 s
2023-05-12 02:42:39,339	44k	INFO	Train Epoch: 376 [16%]
2023-05-12 02:42:39,340	44k	INFO	Losses: [2.287039279937744, 2.543053388595581, 13.70235538482666, 19.574756622314453, 0.44993361830711365], step: 57400, lr: 2.862611610638835e-05, reference_loss: 38.55713653564453
2023-05-12 02:43:38,361	44k	INFO	====> Epoch: 376, cost 88.02 s
2023-05-12 02:44:28,168	44k	INFO	Train Epoch: 377 [46%]
2023-05-12 02:44:28,169	44k	INFO	Losses: [2.1254513263702393, 2.6186904907226562, 16.114530563354492, 21.063730239868164, 1.4693626165390015], step: 57600, lr: 2.862253784187505e-05, reference_loss: 43.39176559448242
2023-05-12 02:45:05,846	44k	INFO	====> Epoch: 377, cost 87.48 s
2023-05-12 02:46:16,454	44k	INFO	Train Epoch: 378 [77%]
2023-05-12 02:46:16,454	44k	INFO	Losses: [2.1241137981414795, 2.312547206878662, 20.073745727539062, 19.273548126220703, 0.7099340558052063], step: 57800, lr: 2.8618960024644812e-05, reference_loss: 44.49388885498047
2023-05-12 02:46:33,009	44k	INFO	====> Epoch: 378, cost 87.16 s
2023-05-12 02:48:00,759	44k	INFO	====> Epoch: 379, cost 87.75 s
2023-05-12 02:48:23,942	44k	INFO	Train Epoch: 380 [8%]
2023-05-12 02:48:23,942	44k	INFO	Losses: [2.456301689147949, 2.2326016426086426, 11.413169860839844, 18.76596450805664, 0.4634284973144531], step: 58000, lr: 2.86118057318099e-05, reference_loss: 35.33146667480469
2023-05-12 02:48:29,433	44k	INFO	Saving model and optimizer state at iteration 380 to ./logs\44k\G_58000.pth
2023-05-12 02:48:30,353	44k	INFO	Saving model and optimizer state at iteration 380 to ./logs\44k\D_58000.pth
2023-05-12 02:48:31,113	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_55000.pth
2023-05-12 02:48:31,170	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_55000.pth
2023-05-12 02:49:34,997	44k	INFO	====> Epoch: 380, cost 94.24 s
2023-05-12 02:50:19,439	44k	INFO	Train Epoch: 381 [39%]
2023-05-12 02:50:19,440	44k	INFO	Losses: [2.5525875091552734, 2.302884340286255, 6.546157360076904, 15.209617614746094, 0.8096770644187927], step: 58200, lr: 2.8608229256093423e-05, reference_loss: 27.420923233032227
2023-05-12 02:51:02,494	44k	INFO	====> Epoch: 381, cost 87.50 s
2023-05-12 02:52:08,041	44k	INFO	Train Epoch: 382 [69%]
2023-05-12 02:52:08,042	44k	INFO	Losses: [2.441138744354248, 2.3071632385253906, 13.418956756591797, 16.853052139282227, 0.6515924334526062], step: 58400, lr: 2.860465322743641e-05, reference_loss: 35.67190170288086
2023-05-12 02:52:29,817	44k	INFO	====> Epoch: 382, cost 87.32 s
2023-05-12 02:53:56,328	44k	INFO	====> Epoch: 383, cost 86.51 s
2023-05-12 02:54:14,257	44k	INFO	Train Epoch: 384 [0%]
2023-05-12 02:54:14,258	44k	INFO	Losses: [2.4921183586120605, 2.2718024253845215, 13.16602611541748, 21.242778778076172, 0.8981888890266418], step: 58600, lr: 2.8597502511077255e-05, reference_loss: 40.07091522216797
2023-05-12 02:55:23,718	44k	INFO	====> Epoch: 384, cost 87.39 s
2023-05-12 02:56:02,345	44k	INFO	Train Epoch: 385 [31%]
2023-05-12 02:56:02,346	44k	INFO	Losses: [2.5569381713867188, 2.3658721446990967, 9.402472496032715, 19.0131893157959, 0.6612781882286072], step: 58800, lr: 2.8593927823263368e-05, reference_loss: 33.99974822998047
2023-05-12 02:56:50,649	44k	INFO	====> Epoch: 385, cost 86.93 s
2023-05-12 02:57:50,732	44k	INFO	Train Epoch: 386 [61%]
2023-05-12 02:57:50,733	44k	INFO	Losses: [2.385152816772461, 2.594188690185547, 10.243889808654785, 20.528438568115234, 0.9784220457077026], step: 59000, lr: 2.859035358228546e-05, reference_loss: 36.7300910949707
2023-05-12 02:57:56,197	44k	INFO	Saving model and optimizer state at iteration 386 to ./logs\44k\G_59000.pth
2023-05-12 02:57:56,967	44k	INFO	Saving model and optimizer state at iteration 386 to ./logs\44k\D_59000.pth
2023-05-12 02:57:57,643	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_56000.pth
2023-05-12 02:57:57,697	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_56000.pth
2023-05-12 02:58:24,963	44k	INFO	====> Epoch: 386, cost 94.31 s
2023-05-12 02:59:46,166	44k	INFO	Train Epoch: 387 [92%]
2023-05-12 02:59:46,166	44k	INFO	Losses: [2.4257919788360596, 2.218857765197754, 9.705286979675293, 21.481491088867188, 0.7963300943374634], step: 59200, lr: 2.8586779788087672e-05, reference_loss: 36.62775802612305
2023-05-12 02:59:52,174	44k	INFO	====> Epoch: 387, cost 87.21 s
2023-05-12 03:01:19,425	44k	INFO	====> Epoch: 388, cost 87.25 s
2023-05-12 03:01:52,827	44k	INFO	Train Epoch: 389 [23%]
2023-05-12 03:01:52,828	44k	INFO	Losses: [2.321176052093506, 2.635291576385498, 11.58166217803955, 21.54326629638672, 0.7177306413650513], step: 59400, lr: 2.8579633539809083e-05, reference_loss: 38.799129486083984
2023-05-12 03:02:46,451	44k	INFO	====> Epoch: 389, cost 87.03 s
2023-05-12 03:03:40,930	44k	INFO	Train Epoch: 390 [54%]
2023-05-12 03:03:40,930	44k	INFO	Losses: [2.4746806621551514, 2.5311200618743896, 12.478462219238281, 16.906023025512695, 0.6712642312049866], step: 59600, lr: 2.8576061085616605e-05, reference_loss: 35.06155014038086
2023-05-12 03:04:13,536	44k	INFO	====> Epoch: 390, cost 87.08 s
2023-05-12 03:05:29,213	44k	INFO	Train Epoch: 391 [84%]
2023-05-12 03:05:29,214	44k	INFO	Losses: [2.4147493839263916, 2.478468656539917, 10.078948974609375, 18.84165382385254, 0.8695682287216187], step: 59800, lr: 2.8572489077980904e-05, reference_loss: 34.683387756347656
2023-05-12 03:05:40,681	44k	INFO	====> Epoch: 391, cost 87.14 s
2023-05-12 03:07:07,801	44k	INFO	====> Epoch: 392, cost 87.12 s
2023-05-12 03:07:35,856	44k	INFO	Train Epoch: 393 [15%]
2023-05-12 03:07:35,857	44k	INFO	Losses: [2.355435848236084, 2.3938512802124023, 12.078808784484863, 22.25308609008789, 0.7829247117042542], step: 60000, lr: 2.8565346402156547e-05, reference_loss: 39.86410903930664
2023-05-12 03:07:41,272	44k	INFO	Saving model and optimizer state at iteration 393 to ./logs\44k\G_60000.pth
2023-05-12 03:07:42,047	44k	INFO	Saving model and optimizer state at iteration 393 to ./logs\44k\D_60000.pth
2023-05-12 03:07:42,723	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_57000.pth
2023-05-12 03:07:42,773	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_57000.pth
2023-05-12 03:08:42,095	44k	INFO	====> Epoch: 393, cost 94.30 s
2023-05-12 03:09:31,322	44k	INFO	Train Epoch: 394 [46%]
2023-05-12 03:09:31,323	44k	INFO	Losses: [2.4283063411712646, 2.6148173809051514, 10.784454345703125, 20.74228858947754, 0.9343788623809814], step: 60200, lr: 2.8561775733856277e-05, reference_loss: 37.50424575805664
2023-05-12 03:10:09,395	44k	INFO	====> Epoch: 394, cost 87.30 s
2023-05-12 03:11:20,165	44k	INFO	Train Epoch: 395 [76%]
2023-05-12 03:11:20,165	44k	INFO	Losses: [2.466671943664551, 2.381155014038086, 14.714022636413574, 20.37222671508789, 0.7701204419136047], step: 60400, lr: 2.8558205511889543e-05, reference_loss: 40.704193115234375
2023-05-12 03:11:36,998	44k	INFO	====> Epoch: 395, cost 87.60 s
2023-05-12 03:13:03,779	44k	INFO	====> Epoch: 396, cost 86.78 s
2023-05-12 03:13:26,684	44k	INFO	Train Epoch: 397 [7%]
2023-05-12 03:13:26,684	44k	INFO	Losses: [1.855776071548462, 3.0590667724609375, 13.506698608398438, 20.01685333251953, 0.5135242938995361], step: 60600, lr: 2.8551066406733528e-05, reference_loss: 38.9519157409668
2023-05-12 03:14:31,014	44k	INFO	====> Epoch: 397, cost 87.23 s
2023-05-12 03:15:15,043	44k	INFO	Train Epoch: 398 [38%]
2023-05-12 03:15:15,044	44k	INFO	Losses: [2.3311688899993896, 2.753591299057007, 14.103012084960938, 19.344404220581055, 0.6492558717727661], step: 60800, lr: 2.8547497523432686e-05, reference_loss: 39.181434631347656
2023-05-12 03:15:58,459	44k	INFO	====> Epoch: 398, cost 87.45 s
2023-05-12 03:17:03,126	44k	INFO	Train Epoch: 399 [69%]
2023-05-12 03:17:03,127	44k	INFO	Losses: [2.0792133808135986, 2.83935284614563, 17.456817626953125, 21.017284393310547, 0.8417804837226868], step: 61000, lr: 2.8543929086242254e-05, reference_loss: 44.23445129394531
2023-05-12 03:17:08,663	44k	INFO	Saving model and optimizer state at iteration 399 to ./logs\44k\G_61000.pth
2023-05-12 03:17:09,446	44k	INFO	Saving model and optimizer state at iteration 399 to ./logs\44k\D_61000.pth
2023-05-12 03:17:10,116	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\G_58000.pth
2023-05-12 03:17:10,164	44k	INFO	.. Free up space by deleting ckpt ./logs\44k\D_58000.pth
2023-05-12 03:17:32,301	44k	INFO	====> Epoch: 399, cost 93.84 s
2023-05-12 03:18:58,526	44k	INFO	Train Epoch: 400 [99%]
2023-05-12 03:18:58,526	44k	INFO	Losses: [2.41349458694458, 2.4074997901916504, 10.494972229003906, 17.17674446105957, 1.1495909690856934], step: 61200, lr: 2.8540361095106474e-05, reference_loss: 33.64229965209961
2023-05-12 03:18:59,773	44k	INFO	====> Epoch: 400, cost 87.47 s