logs/Ajay-Pandey_A5000/train.log

2023-11-04 23:03:33,781	Ajay-Pandey_A5000	INFO	{'data': {'filter_length': 1024, 'hop_length': 320, 'max_wav_value': 32768.0, 'mel_fmax': None, 'mel_fmin': 0.0, 'n_mel_channels': 80, 'sampling_rate': 32000, 'win_length': 1024, 'training_files': './logs/Ajay-Pandey_A5000/filelist.txt'}, 'model': {'filter_channels': 768, 'gin_channels': 256, 'hidden_channels': 192, 'inter_channels': 192, 'kernel_size': 3, 'n_heads': 2, 'n_layers': 6, 'p_dropout': 0, 'resblock': '1', 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'resblock_kernel_sizes': [3, 7, 11], 'spk_embed_dim': 109, 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [20, 16, 4, 4], 'upsample_rates': [10, 8, 2, 2], 'use_spectral_norm': False}, 'train': {'batch_size': 12, 'betas': [0.8, 0.99], 'c_kl': 1.0, 'c_mel': 45, 'epochs': 20000, 'eps': 1e-09, 'fp16_run': True, 'init_lr_ratio': 1, 'learning_rate': 0.0001, 'log_interval': 200, 'lr_decay': 0.999875, 'seed': 1234, 'segment_size': 12800, 'warmup_epochs': 0}, 'model_dir': './logs/Ajay-Pandey_A5000', 'experiment_dir': './logs/Ajay-Pandey_A5000', 'save_every_epoch': 50, 'name': 'Ajay-Pandey_A5000', 'total_epoch': 200, 'pretrainG': 'assets/pretrained_v2/f0G32k.pth', 'pretrainD': 'assets/pretrained_v2/f0D32k.pth', 'version': 'v2', 'gpus': '0', 'sample_rate': '32k', 'if_f0': 1, 'if_latest': 1, 'save_every_weights': '1', 'if_cache_data_in_gpu': 0}
2023-11-04 23:03:35,404	Ajay-Pandey_A5000	INFO	loaded pretrained assets/pretrained_v2/f0G32k.pth
2023-11-04 23:03:36,160	Ajay-Pandey_A5000	INFO	<All keys matched successfully>
2023-11-04 23:03:36,160	Ajay-Pandey_A5000	INFO	loaded pretrained assets/pretrained_v2/f0D32k.pth
2023-11-04 23:03:37,540	Ajay-Pandey_A5000	INFO	<All keys matched successfully>
2023-11-04 23:03:51,133	Ajay-Pandey_A5000	INFO	Train Epoch: 1 [0%]
2023-11-04 23:03:51,133	Ajay-Pandey_A5000	INFO	[0, 0.0001]
2023-11-04 23:03:51,133	Ajay-Pandey_A5000	INFO	loss_disc=3.786, loss_gen=3.702, loss_fm=9.033,loss_mel=22.719, loss_kl=7.950
2023-11-04 23:04:26,118	Ajay-Pandey_A5000	INFO	====> Epoch: 1 [2023-11-04 23:04:26] | (0:00:40.061292)
2023-11-04 23:04:57,455	Ajay-Pandey_A5000	INFO	Train Epoch: 2 [94%]
2023-11-04 23:04:57,456	Ajay-Pandey_A5000	INFO	[200, 9.99875e-05]
2023-11-04 23:04:57,456	Ajay-Pandey_A5000	INFO	loss_disc=3.820, loss_gen=3.609, loss_fm=9.561,loss_mel=18.932, loss_kl=2.134
2023-11-04 23:04:59,337	Ajay-Pandey_A5000	INFO	====> Epoch: 2 [2023-11-04 23:04:59] | (0:00:33.210196)
2023-11-04 23:05:31,848	Ajay-Pandey_A5000	INFO	====> Epoch: 3 [2023-11-04 23:05:31] | (0:00:32.502743)
2023-11-04 23:06:00,998	Ajay-Pandey_A5000	INFO	Train Epoch: 4 [88%]
2023-11-04 23:06:00,999	Ajay-Pandey_A5000	INFO	[400, 9.996250468730469e-05]
2023-11-04 23:06:00,999	Ajay-Pandey_A5000	INFO	loss_disc=3.974, loss_gen=3.343, loss_fm=8.949,loss_mel=18.701, loss_kl=2.241
2023-11-04 23:06:05,208	Ajay-Pandey_A5000	INFO	====> Epoch: 4 [2023-11-04 23:06:05] | (0:00:33.354582)
2023-11-04 23:06:37,735	Ajay-Pandey_A5000	INFO	====> Epoch: 5 [2023-11-04 23:06:37] | (0:00:32.518665)
2023-11-04 23:07:05,377	Ajay-Pandey_A5000	INFO	Train Epoch: 6 [83%]
2023-11-04 23:07:05,378	Ajay-Pandey_A5000	INFO	[600, 9.993751562304699e-05]
2023-11-04 23:07:05,378	Ajay-Pandey_A5000	INFO	loss_disc=3.856, loss_gen=3.533, loss_fm=8.789,loss_mel=18.011, loss_kl=1.711
2023-11-04 23:07:11,061	Ajay-Pandey_A5000	INFO	====> Epoch: 6 [2023-11-04 23:07:11] | (0:00:33.320310)
2023-11-04 23:07:43,886	Ajay-Pandey_A5000	INFO	====> Epoch: 7 [2023-11-04 23:07:43] | (0:00:32.816590)
2023-11-04 23:08:09,524	Ajay-Pandey_A5000	INFO	Train Epoch: 8 [77%]
2023-11-04 23:08:09,525	Ajay-Pandey_A5000	INFO	[800, 9.991253280566489e-05]
2023-11-04 23:08:09,525	Ajay-Pandey_A5000	INFO	loss_disc=3.789, loss_gen=3.638, loss_fm=9.821,loss_mel=17.689, loss_kl=2.160
2023-11-04 23:12:07,731	Ajay-Pandey_A5000	INFO	{'data': {'filter_length': 1024, 'hop_length': 320, 'max_wav_value': 32768.0, 'mel_fmax': None, 'mel_fmin': 0.0, 'n_mel_channels': 80, 'sampling_rate': 32000, 'win_length': 1024, 'training_files': './logs/Ajay-Pandey_A5000/filelist.txt'}, 'model': {'filter_channels': 768, 'gin_channels': 256, 'hidden_channels': 192, 'inter_channels': 192, 'kernel_size': 3, 'n_heads': 2, 'n_layers': 6, 'p_dropout': 0, 'resblock': '1', 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'resblock_kernel_sizes': [3, 7, 11], 'spk_embed_dim': 109, 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [20, 16, 4, 4], 'upsample_rates': [10, 8, 2, 2], 'use_spectral_norm': False}, 'train': {'batch_size': 30, 'betas': [0.8, 0.99], 'c_kl': 1.0, 'c_mel': 45, 'epochs': 20000, 'eps': 1e-09, 'fp16_run': True, 'init_lr_ratio': 1, 'learning_rate': 0.0001, 'log_interval': 200, 'lr_decay': 0.999875, 'seed': 1234, 'segment_size': 12800, 'warmup_epochs': 0}, 'model_dir': './logs/Ajay-Pandey_A5000', 'experiment_dir': './logs/Ajay-Pandey_A5000', 'save_every_epoch': 50, 'name': 'Ajay-Pandey_A5000', 'total_epoch': 200, 'pretrainG': 'assets/pretrained_v2/f0G32k.pth', 'pretrainD': 'assets/pretrained_v2/f0D32k.pth', 'version': 'v2', 'gpus': '0', 'sample_rate': '32k', 'if_f0': 1, 'if_latest': 1, 'save_every_weights': '1', 'if_cache_data_in_gpu': 0}
2023-11-04 23:12:09,284	Ajay-Pandey_A5000	INFO	loaded pretrained assets/pretrained_v2/f0G32k.pth
2023-11-04 23:12:09,364	Ajay-Pandey_A5000	INFO	<All keys matched successfully>
2023-11-04 23:12:09,364	Ajay-Pandey_A5000	INFO	loaded pretrained assets/pretrained_v2/f0D32k.pth
2023-11-04 23:12:09,450	Ajay-Pandey_A5000	INFO	<All keys matched successfully>
2023-11-04 23:12:20,748	Ajay-Pandey_A5000	INFO	Train Epoch: 1 [0%]
2023-11-04 23:12:20,749	Ajay-Pandey_A5000	INFO	[0, 0.0001]
2023-11-04 23:12:20,749	Ajay-Pandey_A5000	INFO	loss_disc=3.720, loss_gen=3.597, loss_fm=9.126,loss_mel=22.488, loss_kl=8.173
2023-11-04 23:12:45,115	Ajay-Pandey_A5000	INFO	====> Epoch: 1 [2023-11-04 23:12:45] | (0:00:27.681448)
2023-11-04 23:13:08,674	Ajay-Pandey_A5000	INFO	====> Epoch: 2 [2023-11-04 23:13:08] | (0:00:23.550018)
2023-11-04 23:13:32,261	Ajay-Pandey_A5000	INFO	====> Epoch: 3 [2023-11-04 23:13:32] | (0:00:23.580945)
2023-11-04 23:13:56,107	Ajay-Pandey_A5000	INFO	====> Epoch: 4 [2023-11-04 23:13:56] | (0:00:23.840420)
2023-11-04 23:14:12,293	Ajay-Pandey_A5000	INFO	Train Epoch: 5 [65%]
2023-11-04 23:14:12,294	Ajay-Pandey_A5000	INFO	[200, 9.995000937421877e-05]
2023-11-04 23:14:12,294	Ajay-Pandey_A5000	INFO	loss_disc=3.970, loss_gen=3.112, loss_fm=8.101,loss_mel=18.416, loss_kl=2.152
2023-11-04 23:14:20,289	Ajay-Pandey_A5000	INFO	====> Epoch: 5 [2023-11-04 23:14:20] | (0:00:24.175916)
2023-11-04 23:16:26,326	Ajay-Pandey_A5000	INFO	{'data': {'filter_length': 1024, 'hop_length': 320, 'max_wav_value': 32768.0, 'mel_fmax': None, 'mel_fmin': 0.0, 'n_mel_channels': 80, 'sampling_rate': 32000, 'win_length': 1024, 'training_files': './logs/Ajay-Pandey_A5000/filelist.txt'}, 'model': {'filter_channels': 768, 'gin_channels': 256, 'hidden_channels': 192, 'inter_channels': 192, 'kernel_size': 3, 'n_heads': 2, 'n_layers': 6, 'p_dropout': 0, 'resblock': '1', 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'resblock_kernel_sizes': [3, 7, 11], 'spk_embed_dim': 109, 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [20, 16, 4, 4], 'upsample_rates': [10, 8, 2, 2], 'use_spectral_norm': False}, 'train': {'batch_size': 40, 'betas': [0.8, 0.99], 'c_kl': 1.0, 'c_mel': 45, 'epochs': 20000, 'eps': 1e-09, 'fp16_run': True, 'init_lr_ratio': 1, 'learning_rate': 0.0001, 'log_interval': 200, 'lr_decay': 0.999875, 'seed': 1234, 'segment_size': 12800, 'warmup_epochs': 0}, 'model_dir': './logs/Ajay-Pandey_A5000', 'experiment_dir': './logs/Ajay-Pandey_A5000', 'save_every_epoch': 50, 'name': 'Ajay-Pandey_A5000', 'total_epoch': 200, 'pretrainG': 'assets/pretrained_v2/f0G32k.pth', 'pretrainD': 'assets/pretrained_v2/f0D32k.pth', 'version': 'v2', 'gpus': '0', 'sample_rate': '32k', 'if_f0': 1, 'if_latest': 1, 'save_every_weights': '1', 'if_cache_data_in_gpu': 0}
2023-11-04 23:16:27,875	Ajay-Pandey_A5000	INFO	loaded pretrained assets/pretrained_v2/f0G32k.pth
2023-11-04 23:16:27,958	Ajay-Pandey_A5000	INFO	<All keys matched successfully>
2023-11-04 23:16:27,959	Ajay-Pandey_A5000	INFO	loaded pretrained assets/pretrained_v2/f0D32k.pth
2023-11-04 23:16:28,040	Ajay-Pandey_A5000	INFO	<All keys matched successfully>
2023-11-04 23:16:41,049	Ajay-Pandey_A5000	INFO	Train Epoch: 1 [0%]
2023-11-04 23:16:41,049	Ajay-Pandey_A5000	INFO	[0, 0.0001]
2023-11-04 23:16:41,049	Ajay-Pandey_A5000	INFO	loss_disc=3.787, loss_gen=3.568, loss_fm=8.879,loss_mel=22.452, loss_kl=8.227
2023-11-04 23:17:04,025	Ajay-Pandey_A5000	INFO	====> Epoch: 1 [2023-11-04 23:17:04] | (0:00:26.594052)
2023-11-04 23:17:26,515	Ajay-Pandey_A5000	INFO	====> Epoch: 2 [2023-11-04 23:17:26] | (0:00:22.481709)
2023-11-04 23:17:49,168	Ajay-Pandey_A5000	INFO	====> Epoch: 3 [2023-11-04 23:17:49] | (0:00:22.647142)
2023-11-04 23:18:11,948	Ajay-Pandey_A5000	INFO	====> Epoch: 4 [2023-11-04 23:18:11] | (0:00:22.774344)
2023-11-04 23:18:34,738	Ajay-Pandey_A5000	INFO	====> Epoch: 5 [2023-11-04 23:18:34] | (0:00:22.784068)
2023-11-04 23:18:57,490	Ajay-Pandey_A5000	INFO	====> Epoch: 6 [2023-11-04 23:18:57] | (0:00:22.745963)
2023-11-04 23:18:59,695	Ajay-Pandey_A5000	INFO	Train Epoch: 7 [6%]
2023-11-04 23:18:59,696	Ajay-Pandey_A5000	INFO	[200, 9.99250234335941e-05]
2023-11-04 23:18:59,696	Ajay-Pandey_A5000	INFO	loss_disc=3.908, loss_gen=3.459, loss_fm=10.414,loss_mel=18.404, loss_kl=2.150
2023-11-04 23:19:20,564	Ajay-Pandey_A5000	INFO	====> Epoch: 7 [2023-11-04 23:19:20] | (0:00:23.068058)
2023-11-04 23:19:43,401	Ajay-Pandey_A5000	INFO	====> Epoch: 8 [2023-11-04 23:19:43] | (0:00:22.829126)
2023-11-04 23:20:06,335	Ajay-Pandey_A5000	INFO	====> Epoch: 9 [2023-11-04 23:20:06] | (0:00:22.928696)
2023-11-04 23:20:29,371	Ajay-Pandey_A5000	INFO	====> Epoch: 10 [2023-11-04 23:20:29] | (0:00:23.030083)
2023-11-04 23:20:52,260	Ajay-Pandey_A5000	INFO	====> Epoch: 11 [2023-11-04 23:20:52] | (0:00:22.883100)
2023-11-04 23:21:15,061	Ajay-Pandey_A5000	INFO	====> Epoch: 12 [2023-11-04 23:21:15] | (0:00:22.795453)
2023-11-04 23:21:18,675	Ajay-Pandey_A5000	INFO	Train Epoch: 13 [12%]
2023-11-04 23:21:18,676	Ajay-Pandey_A5000	INFO	[400, 9.98501030820433e-05]
2023-11-04 23:21:18,676	Ajay-Pandey_A5000	INFO	loss_disc=4.196, loss_gen=3.239, loss_fm=9.372,loss_mel=19.249, loss_kl=1.871
2023-11-04 23:21:38,549	Ajay-Pandey_A5000	INFO	====> Epoch: 13 [2023-11-04 23:21:38] | (0:00:23.481934)
2023-11-04 23:22:01,457	Ajay-Pandey_A5000	INFO	====> Epoch: 14 [2023-11-04 23:22:01] | (0:00:22.899584)
2023-11-04 23:22:24,261	Ajay-Pandey_A5000	INFO	====> Epoch: 15 [2023-11-04 23:22:24] | (0:00:22.798218)
2023-11-04 23:22:47,142	Ajay-Pandey_A5000	INFO	====> Epoch: 16 [2023-11-04 23:22:47] | (0:00:22.875532)
2023-11-04 23:23:10,001	Ajay-Pandey_A5000	INFO	====> Epoch: 17 [2023-11-04 23:23:10] | (0:00:22.853215)
2023-11-04 23:23:32,863	Ajay-Pandey_A5000	INFO	====> Epoch: 18 [2023-11-04 23:23:32] | (0:00:22.856476)
2023-11-04 23:23:37,878	Ajay-Pandey_A5000	INFO	Train Epoch: 19 [18%]
2023-11-04 23:23:37,879	Ajay-Pandey_A5000	INFO	[600, 9.977523890319963e-05]
2023-11-04 23:23:37,879	Ajay-Pandey_A5000	INFO	loss_disc=3.847, loss_gen=3.483, loss_fm=8.952,loss_mel=17.905, loss_kl=1.825
2023-11-04 23:23:56,174	Ajay-Pandey_A5000	INFO	====> Epoch: 19 [2023-11-04 23:23:56] | (0:00:23.305072)
2023-11-04 23:24:18,982	Ajay-Pandey_A5000	INFO	====> Epoch: 20 [2023-11-04 23:24:18] | (0:00:22.799062)
2023-11-04 23:24:41,919	Ajay-Pandey_A5000	INFO	====> Epoch: 21 [2023-11-04 23:24:41] | (0:00:22.931149)
2023-11-04 23:25:04,674	Ajay-Pandey_A5000	INFO	====> Epoch: 22 [2023-11-04 23:25:04] | (0:00:22.749894)
2023-11-04 23:25:27,566	Ajay-Pandey_A5000	INFO	====> Epoch: 23 [2023-11-04 23:25:27] | (0:00:22.886374)
2023-11-04 23:25:50,558	Ajay-Pandey_A5000	INFO	====> Epoch: 24 [2023-11-04 23:25:50] | (0:00:22.985400)
2023-11-04 23:25:57,065	Ajay-Pandey_A5000	INFO	Train Epoch: 25 [24%]
2023-11-04 23:25:57,066	Ajay-Pandey_A5000	INFO	[800, 9.970043085494672e-05]
2023-11-04 23:25:57,066	Ajay-Pandey_A5000	INFO	loss_disc=3.664, loss_gen=3.644, loss_fm=10.307,loss_mel=18.468, loss_kl=1.708
2023-11-04 23:26:13,771	Ajay-Pandey_A5000	INFO	====> Epoch: 25 [2023-11-04 23:26:13] | (0:00:23.206968)
2023-11-04 23:26:36,600	Ajay-Pandey_A5000	INFO	====> Epoch: 26 [2023-11-04 23:26:36] | (0:00:22.821236)
2023-11-04 23:26:59,382	Ajay-Pandey_A5000	INFO	====> Epoch: 27 [2023-11-04 23:26:59] | (0:00:22.775678)
2023-11-04 23:27:22,267	Ajay-Pandey_A5000	INFO	====> Epoch: 28 [2023-11-04 23:27:22] | (0:00:22.879335)
2023-11-04 23:27:45,140	Ajay-Pandey_A5000	INFO	====> Epoch: 29 [2023-11-04 23:27:45] | (0:00:22.867398)
2023-11-04 23:28:07,974	Ajay-Pandey_A5000	INFO	====> Epoch: 30 [2023-11-04 23:28:07] | (0:00:22.828433)
2023-11-04 23:28:15,882	Ajay-Pandey_A5000	INFO	Train Epoch: 31 [30%]
2023-11-04 23:28:15,883	Ajay-Pandey_A5000	INFO	[1000, 9.962567889519979e-05]
2023-11-04 23:28:15,883	Ajay-Pandey_A5000	INFO	loss_disc=3.766, loss_gen=3.401, loss_fm=9.894,loss_mel=18.234, loss_kl=1.669
2023-11-04 23:28:31,296	Ajay-Pandey_A5000	INFO	====> Epoch: 31 [2023-11-04 23:28:31] | (0:00:23.315520)
2023-11-04 23:28:54,124	Ajay-Pandey_A5000	INFO	====> Epoch: 32 [2023-11-04 23:28:54] | (0:00:22.819762)
2023-11-04 23:29:16,985	Ajay-Pandey_A5000	INFO	====> Epoch: 33 [2023-11-04 23:29:16] | (0:00:22.855596)
2023-11-04 23:29:39,862	Ajay-Pandey_A5000	INFO	====> Epoch: 34 [2023-11-04 23:29:39] | (0:00:22.870549)
2023-11-04 23:30:02,775	Ajay-Pandey_A5000	INFO	====> Epoch: 35 [2023-11-04 23:30:02] | (0:00:22.907229)
2023-11-04 23:30:25,656	Ajay-Pandey_A5000	INFO	====> Epoch: 36 [2023-11-04 23:30:25] | (0:00:22.875968)
2023-11-04 23:30:34,895	Ajay-Pandey_A5000	INFO	Train Epoch: 37 [36%]
2023-11-04 23:30:34,896	Ajay-Pandey_A5000	INFO	[1200, 9.95509829819056e-05]
2023-11-04 23:30:34,896	Ajay-Pandey_A5000	INFO	loss_disc=3.914, loss_gen=3.415, loss_fm=9.049,loss_mel=17.777, loss_kl=1.364
2023-11-04 23:30:48,827	Ajay-Pandey_A5000	INFO	====> Epoch: 37 [2023-11-04 23:30:48] | (0:00:23.164846)
2023-11-04 23:31:11,714	Ajay-Pandey_A5000	INFO	====> Epoch: 38 [2023-11-04 23:31:11] | (0:00:22.877787)
2023-11-04 23:31:34,565	Ajay-Pandey_A5000	INFO	====> Epoch: 39 [2023-11-04 23:31:34] | (0:00:22.845310)
2023-11-04 23:31:57,306	Ajay-Pandey_A5000	INFO	====> Epoch: 40 [2023-11-04 23:31:57] | (0:00:22.735213)
2023-11-04 23:32:20,139	Ajay-Pandey_A5000	INFO	====> Epoch: 41 [2023-11-04 23:32:20] | (0:00:22.827448)
2023-11-04 23:32:42,955	Ajay-Pandey_A5000	INFO	====> Epoch: 42 [2023-11-04 23:32:42] | (0:00:22.810259)
2023-11-04 23:32:53,310	Ajay-Pandey_A5000	INFO	Train Epoch: 43 [42%]
2023-11-04 23:32:53,310	Ajay-Pandey_A5000	INFO	[1400, 9.947634307304244e-05]
2023-11-04 23:32:53,311	Ajay-Pandey_A5000	INFO	loss_disc=3.551, loss_gen=3.382, loss_fm=10.165,loss_mel=17.604, loss_kl=1.555
2023-11-04 23:33:06,199	Ajay-Pandey_A5000	INFO	====> Epoch: 43 [2023-11-04 23:33:06] | (0:00:23.238296)
2023-11-04 23:33:29,125	Ajay-Pandey_A5000	INFO	====> Epoch: 44 [2023-11-04 23:33:29] | (0:00:22.917144)
2023-11-04 23:33:51,943	Ajay-Pandey_A5000	INFO	====> Epoch: 45 [2023-11-04 23:33:51] | (0:00:22.811708)
2023-11-04 23:34:14,782	Ajay-Pandey_A5000	INFO	====> Epoch: 46 [2023-11-04 23:34:14] | (0:00:22.833785)
2023-11-04 23:34:37,563	Ajay-Pandey_A5000	INFO	====> Epoch: 47 [2023-11-04 23:34:37] | (0:00:22.775156)
2023-11-04 23:35:00,455	Ajay-Pandey_A5000	INFO	====> Epoch: 48 [2023-11-04 23:35:00] | (0:00:22.886509)
2023-11-04 23:35:12,395	Ajay-Pandey_A5000	INFO	Train Epoch: 49 [48%]
2023-11-04 23:35:12,395	Ajay-Pandey_A5000	INFO	[1600, 9.940175912662009e-05]
2023-11-04 23:35:12,395	Ajay-Pandey_A5000	INFO	loss_disc=4.002, loss_gen=3.420, loss_fm=8.967,loss_mel=17.586, loss_kl=1.421
2023-11-04 23:35:23,643	Ajay-Pandey_A5000	INFO	====> Epoch: 49 [2023-11-04 23:35:23] | (0:00:23.181479)
2023-11-04 23:35:46,518	Ajay-Pandey_A5000	INFO	Saving model and optimizer state at epoch 50 to ./logs/Ajay-Pandey_A5000/G_2333333.pth
2023-11-04 23:35:54,289	Ajay-Pandey_A5000	INFO	Saving model and optimizer state at epoch 50 to ./logs/Ajay-Pandey_A5000/D_2333333.pth
2023-11-04 23:36:08,327	Ajay-Pandey_A5000	INFO	saving ckpt Ajay-Pandey_A5000_e50:Success.
2023-11-04 23:36:08,328	Ajay-Pandey_A5000	INFO	====> Epoch: 50 [2023-11-04 23:36:08] | (0:00:44.677081)
2023-11-04 23:36:30,891	Ajay-Pandey_A5000	INFO	====> Epoch: 51 [2023-11-04 23:36:30] | (0:00:22.556344)
2023-11-04 23:36:53,682	Ajay-Pandey_A5000	INFO	====> Epoch: 52 [2023-11-04 23:36:53] | (0:00:22.785830)
2023-11-04 23:37:16,469	Ajay-Pandey_A5000	INFO	====> Epoch: 53 [2023-11-04 23:37:16] | (0:00:22.780890)
2023-11-04 23:37:39,326	Ajay-Pandey_A5000	INFO	====> Epoch: 54 [2023-11-04 23:37:39] | (0:00:22.851538)
2023-11-04 23:37:52,632	Ajay-Pandey_A5000	INFO	Train Epoch: 55 [55%]
2023-11-04 23:37:52,632	Ajay-Pandey_A5000	INFO	[1800, 9.932723110067987e-05]
2023-11-04 23:37:52,633	Ajay-Pandey_A5000	INFO	loss_disc=3.990, loss_gen=3.381, loss_fm=7.908,loss_mel=17.080, loss_kl=1.191
2023-11-04 23:38:02,523	Ajay-Pandey_A5000	INFO	====> Epoch: 55 [2023-11-04 23:38:02] | (0:00:23.191485)
2023-11-04 23:38:25,395	Ajay-Pandey_A5000	INFO	====> Epoch: 56 [2023-11-04 23:38:25] | (0:00:22.863796)
2023-11-04 23:38:48,203	Ajay-Pandey_A5000	INFO	====> Epoch: 57 [2023-11-04 23:38:48] | (0:00:22.802246)
2023-11-04 23:39:11,007	Ajay-Pandey_A5000	INFO	====> Epoch: 58 [2023-11-04 23:39:11] | (0:00:22.797809)
2023-11-04 23:39:33,902	Ajay-Pandey_A5000	INFO	====> Epoch: 59 [2023-11-04 23:39:33] | (0:00:22.889679)
2023-11-04 23:39:56,833	Ajay-Pandey_A5000	INFO	====> Epoch: 60 [2023-11-04 23:39:56] | (0:00:22.925816)
2023-11-04 23:40:11,324	Ajay-Pandey_A5000	INFO	Train Epoch: 61 [61%]
2023-11-04 23:40:11,325	Ajay-Pandey_A5000	INFO	[2000, 9.92527589532945e-05]
2023-11-04 23:40:11,325	Ajay-Pandey_A5000	INFO	loss_disc=3.861, loss_gen=3.293, loss_fm=9.002,loss_mel=17.121, loss_kl=1.345
2023-11-04 23:40:20,063	Ajay-Pandey_A5000	INFO	====> Epoch: 61 [2023-11-04 23:40:20] | (0:00:23.224424)
2023-11-04 23:40:42,906	Ajay-Pandey_A5000	INFO	====> Epoch: 62 [2023-11-04 23:40:42] | (0:00:22.833550)
2023-11-04 23:41:05,760	Ajay-Pandey_A5000	INFO	====> Epoch: 63 [2023-11-04 23:41:05] | (0:00:22.848346)
2023-11-04 23:41:28,638	Ajay-Pandey_A5000	INFO	====> Epoch: 64 [2023-11-04 23:41:28] | (0:00:22.872720)
2023-11-04 23:41:51,417	Ajay-Pandey_A5000	INFO	====> Epoch: 65 [2023-11-04 23:41:51] | (0:00:22.772879)
2023-11-04 23:42:14,328	Ajay-Pandey_A5000	INFO	====> Epoch: 66 [2023-11-04 23:42:14] | (0:00:22.905213)
2023-11-04 23:42:30,321	Ajay-Pandey_A5000	INFO	Train Epoch: 67 [67%]
2023-11-04 23:42:30,322	Ajay-Pandey_A5000	INFO	[2200, 9.917834264256819e-05]
2023-11-04 23:42:30,322	Ajay-Pandey_A5000	INFO	loss_disc=3.742, loss_gen=3.538, loss_fm=9.423,loss_mel=16.953, loss_kl=1.432
2023-11-04 23:42:37,547	Ajay-Pandey_A5000	INFO	====> Epoch: 67 [2023-11-04 23:42:37] | (0:00:23.214058)
2023-11-04 23:43:00,401	Ajay-Pandey_A5000	INFO	====> Epoch: 68 [2023-11-04 23:43:00] | (0:00:22.845379)
2023-11-04 23:43:23,233	Ajay-Pandey_A5000	INFO	====> Epoch: 69 [2023-11-04 23:43:23] | (0:00:22.826638)
2023-11-04 23:43:46,043	Ajay-Pandey_A5000	INFO	====> Epoch: 70 [2023-11-04 23:43:46] | (0:00:22.804358)
2023-11-04 23:44:08,894	Ajay-Pandey_A5000	INFO	====> Epoch: 71 [2023-11-04 23:44:08] | (0:00:22.844825)
2023-11-04 23:44:31,601	Ajay-Pandey_A5000	INFO	====> Epoch: 72 [2023-11-04 23:44:31] | (0:00:22.701248)
2023-11-04 23:44:48,997	Ajay-Pandey_A5000	INFO	Train Epoch: 73 [73%]
2023-11-04 23:44:48,997	Ajay-Pandey_A5000	INFO	[2400, 9.910398212663652e-05]
2023-11-04 23:44:48,998	Ajay-Pandey_A5000	INFO	loss_disc=3.772, loss_gen=3.597, loss_fm=9.290,loss_mel=16.905, loss_kl=1.505
2023-11-04 23:44:54,966	Ajay-Pandey_A5000	INFO	====> Epoch: 73 [2023-11-04 23:44:54] | (0:00:23.359444)
2023-11-04 23:45:17,823	Ajay-Pandey_A5000	INFO	====> Epoch: 74 [2023-11-04 23:45:17] | (0:00:22.849027)
2023-11-04 23:45:40,662	Ajay-Pandey_A5000	INFO	====> Epoch: 75 [2023-11-04 23:45:40] | (0:00:22.833663)
2023-11-04 23:46:03,576	Ajay-Pandey_A5000	INFO	====> Epoch: 76 [2023-11-04 23:46:03] | (0:00:22.908137)
2023-11-04 23:46:26,414	Ajay-Pandey_A5000	INFO	====> Epoch: 77 [2023-11-04 23:46:26] | (0:00:22.832327)
2023-11-04 23:46:49,371	Ajay-Pandey_A5000	INFO	====> Epoch: 78 [2023-11-04 23:46:49] | (0:00:22.951218)
2023-11-04 23:47:08,220	Ajay-Pandey_A5000	INFO	Train Epoch: 79 [79%]
2023-11-04 23:47:08,221	Ajay-Pandey_A5000	INFO	[2600, 9.902967736366644e-05]
2023-11-04 23:47:08,221	Ajay-Pandey_A5000	INFO	loss_disc=3.728, loss_gen=3.433, loss_fm=9.332,loss_mel=16.881, loss_kl=1.462
2023-11-04 23:47:12,626	Ajay-Pandey_A5000	INFO	====> Epoch: 79 [2023-11-04 23:47:12] | (0:00:23.248989)
2023-11-04 23:47:35,395	Ajay-Pandey_A5000	INFO	====> Epoch: 80 [2023-11-04 23:47:35] | (0:00:22.761023)
2023-11-04 23:47:58,245	Ajay-Pandey_A5000	INFO	====> Epoch: 81 [2023-11-04 23:47:58] | (0:00:22.844138)
2023-11-04 23:48:21,225	Ajay-Pandey_A5000	INFO	====> Epoch: 82 [2023-11-04 23:48:21] | (0:00:22.973984)
2023-11-04 23:48:44,088	Ajay-Pandey_A5000	INFO	====> Epoch: 83 [2023-11-04 23:48:44] | (0:00:22.857614)
2023-11-04 23:49:07,015	Ajay-Pandey_A5000	INFO	====> Epoch: 84 [2023-11-04 23:49:07] | (0:00:22.920629)
2023-11-04 23:49:27,119	Ajay-Pandey_A5000	INFO	Train Epoch: 85 [85%]
2023-11-04 23:49:27,120	Ajay-Pandey_A5000	INFO	[2800, 9.895542831185631e-05]
2023-11-04 23:49:27,120	Ajay-Pandey_A5000	INFO	loss_disc=3.842, loss_gen=3.359, loss_fm=9.221,loss_mel=17.573, loss_kl=1.393
2023-11-04 23:49:30,616	Ajay-Pandey_A5000	INFO	====> Epoch: 85 [2023-11-04 23:49:30] | (0:00:23.596089)
2023-11-04 23:49:53,373	Ajay-Pandey_A5000	INFO	====> Epoch: 86 [2023-11-04 23:49:53] | (0:00:22.747797)
2023-11-04 23:50:16,257	Ajay-Pandey_A5000	INFO	====> Epoch: 87 [2023-11-04 23:50:16] | (0:00:22.878182)
2023-11-04 23:50:39,075	Ajay-Pandey_A5000	INFO	====> Epoch: 88 [2023-11-04 23:50:39] | (0:00:22.812529)
2023-11-04 23:51:01,998	Ajay-Pandey_A5000	INFO	====> Epoch: 89 [2023-11-04 23:51:01] | (0:00:22.916868)
2023-11-04 23:51:24,829	Ajay-Pandey_A5000	INFO	====> Epoch: 90 [2023-11-04 23:51:24] | (0:00:22.825034)
2023-11-04 23:51:46,450	Ajay-Pandey_A5000	INFO	Train Epoch: 91 [91%]
2023-11-04 23:51:46,450	Ajay-Pandey_A5000	INFO	[3000, 9.888123492943583e-05]
2023-11-04 23:51:46,451	Ajay-Pandey_A5000	INFO	loss_disc=3.574, loss_gen=3.599, loss_fm=9.447,loss_mel=17.070, loss_kl=1.431
2023-11-04 23:51:48,113	Ajay-Pandey_A5000	INFO	====> Epoch: 91 [2023-11-04 23:51:48] | (0:00:23.279052)
2023-11-04 23:52:10,930	Ajay-Pandey_A5000	INFO	====> Epoch: 92 [2023-11-04 23:52:10] | (0:00:22.808739)
2023-11-04 23:52:33,944	Ajay-Pandey_A5000	INFO	====> Epoch: 93 [2023-11-04 23:52:33] | (0:00:23.008121)
2023-11-04 23:52:56,801	Ajay-Pandey_A5000	INFO	====> Epoch: 94 [2023-11-04 23:52:56] | (0:00:22.851592)
2023-11-04 23:53:19,731	Ajay-Pandey_A5000	INFO	====> Epoch: 95 [2023-11-04 23:53:19] | (0:00:22.924260)
2023-11-04 23:53:42,729	Ajay-Pandey_A5000	INFO	====> Epoch: 96 [2023-11-04 23:53:42] | (0:00:22.992440)
2023-11-04 23:54:05,560	Ajay-Pandey_A5000	INFO	Train Epoch: 97 [97%]
2023-11-04 23:54:05,561	Ajay-Pandey_A5000	INFO	[3200, 9.880709717466598e-05]
2023-11-04 23:54:05,561	Ajay-Pandey_A5000	INFO	loss_disc=3.808, loss_gen=3.522, loss_fm=8.647,loss_mel=16.730, loss_kl=1.142
2023-11-04 23:54:05,860	Ajay-Pandey_A5000	INFO	====> Epoch: 97 [2023-11-04 23:54:05] | (0:00:23.125019)
2023-11-04 23:54:28,721	Ajay-Pandey_A5000	INFO	====> Epoch: 98 [2023-11-04 23:54:28] | (0:00:22.853465)
2023-11-04 23:54:51,611	Ajay-Pandey_A5000	INFO	====> Epoch: 99 [2023-11-04 23:54:51] | (0:00:22.884853)
2023-11-04 23:55:14,416	Ajay-Pandey_A5000	INFO	Saving model and optimizer state at epoch 100 to ./logs/Ajay-Pandey_A5000/G_2333333.pth
2023-11-04 23:55:20,808	Ajay-Pandey_A5000	INFO	Saving model and optimizer state at epoch 100 to ./logs/Ajay-Pandey_A5000/D_2333333.pth
2023-11-04 23:55:35,499	Ajay-Pandey_A5000	INFO	saving ckpt Ajay-Pandey_A5000_e100:Success.
2023-11-04 23:55:35,500	Ajay-Pandey_A5000	INFO	====> Epoch: 100 [2023-11-04 23:55:35] | (0:00:43.882735)
2023-11-04 23:55:58,095	Ajay-Pandey_A5000	INFO	====> Epoch: 101 [2023-11-04 23:55:58] | (0:00:22.589119)
2023-11-04 23:56:20,824	Ajay-Pandey_A5000	INFO	====> Epoch: 102 [2023-11-04 23:56:20] | (0:00:22.723262)
2023-11-04 23:56:43,624	Ajay-Pandey_A5000	INFO	====> Epoch: 103 [2023-11-04 23:56:43] | (0:00:22.794056)
2023-11-04 23:56:45,316	Ajay-Pandey_A5000	INFO	Train Epoch: 104 [3%]
2023-11-04 23:56:45,317	Ajay-Pandey_A5000	INFO	[3400, 9.872067337896332e-05]
2023-11-04 23:56:45,317	Ajay-Pandey_A5000	INFO	loss_disc=3.751, loss_gen=3.625, loss_fm=9.873,loss_mel=17.249, loss_kl=1.298
2023-11-04 23:57:06,953	Ajay-Pandey_A5000	INFO	====> Epoch: 104 [2023-11-04 23:57:06] | (0:00:23.323054)
2023-11-04 23:57:29,742	Ajay-Pandey_A5000	INFO	====> Epoch: 105 [2023-11-04 23:57:29] | (0:00:22.781252)
2023-11-04 23:57:52,588	Ajay-Pandey_A5000	INFO	====> Epoch: 106 [2023-11-04 23:57:52] | (0:00:22.840464)
2023-11-04 23:58:15,447	Ajay-Pandey_A5000	INFO	====> Epoch: 107 [2023-11-04 23:58:15] | (0:00:22.853200)
2023-11-04 23:58:38,349	Ajay-Pandey_A5000	INFO	====> Epoch: 108 [2023-11-04 23:58:38] | (0:00:22.897473)
2023-11-04 23:59:01,232	Ajay-Pandey_A5000	INFO	====> Epoch: 109 [2023-11-04 23:59:01] | (0:00:22.877168)
2023-11-04 23:59:04,274	Ajay-Pandey_A5000	INFO	Train Epoch: 110 [9%]
2023-11-04 23:59:04,275	Ajay-Pandey_A5000	INFO	[3600, 9.864665600773098e-05]
2023-11-04 23:59:04,275	Ajay-Pandey_A5000	INFO	loss_disc=3.775, loss_gen=3.594, loss_fm=9.781,loss_mel=17.109, loss_kl=1.578
2023-11-04 23:59:24,422	Ajay-Pandey_A5000	INFO	====> Epoch: 110 [2023-11-04 23:59:24] | (0:00:23.184575)
2023-11-04 23:59:47,308	Ajay-Pandey_A5000	INFO	====> Epoch: 111 [2023-11-04 23:59:47] | (0:00:22.878125)
2023-11-05 00:00:10,145	Ajay-Pandey_A5000	INFO	====> Epoch: 112 [2023-11-05 00:00:10] | (0:00:22.830921)
2023-11-05 00:00:33,022	Ajay-Pandey_A5000	INFO	====> Epoch: 113 [2023-11-05 00:00:33] | (0:00:22.871466)
2023-11-05 00:00:55,740	Ajay-Pandey_A5000	INFO	====> Epoch: 114 [2023-11-05 00:00:55] | (0:00:22.712193)
2023-11-05 00:01:18,700	Ajay-Pandey_A5000	INFO	====> Epoch: 115 [2023-11-05 00:01:18] | (0:00:22.954302)
2023-11-05 00:01:23,078	Ajay-Pandey_A5000	INFO	Train Epoch: 116 [15%]
2023-11-05 00:01:23,078	Ajay-Pandey_A5000	INFO	[3800, 9.857269413218213e-05]
2023-11-05 00:01:23,078	Ajay-Pandey_A5000	INFO	loss_disc=3.433, loss_gen=3.899, loss_fm=10.853,loss_mel=16.731, loss_kl=0.885
2023-11-05 00:01:41,958	Ajay-Pandey_A5000	INFO	====> Epoch: 116 [2023-11-05 00:01:41] | (0:00:23.252840)
2023-11-05 00:02:04,783	Ajay-Pandey_A5000	INFO	====> Epoch: 117 [2023-11-05 00:02:04] | (0:00:22.817342)
2023-11-05 00:02:27,584	Ajay-Pandey_A5000	INFO	====> Epoch: 118 [2023-11-05 00:02:27] | (0:00:22.795033)
2023-11-05 00:02:50,455	Ajay-Pandey_A5000	INFO	====> Epoch: 119 [2023-11-05 00:02:50] | (0:00:22.864770)
2023-11-05 00:03:13,303	Ajay-Pandey_A5000	INFO	====> Epoch: 120 [2023-11-05 00:03:13] | (0:00:22.843084)
2023-11-05 00:03:36,114	Ajay-Pandey_A5000	INFO	====> Epoch: 121 [2023-11-05 00:03:36] | (0:00:22.805537)
2023-11-05 00:03:41,737	Ajay-Pandey_A5000	INFO	Train Epoch: 122 [21%]
2023-11-05 00:03:41,738	Ajay-Pandey_A5000	INFO	[4000, 9.8498787710708e-05]
2023-11-05 00:03:41,738	Ajay-Pandey_A5000	INFO	loss_disc=3.377, loss_gen=3.758, loss_fm=10.679,loss_mel=16.919, loss_kl=0.794
2023-11-05 00:03:59,480	Ajay-Pandey_A5000	INFO	====> Epoch: 122 [2023-11-05 00:03:59] | (0:00:23.358988)
2023-11-05 00:04:22,244	Ajay-Pandey_A5000	INFO	====> Epoch: 123 [2023-11-05 00:04:22] | (0:00:22.756945)
2023-11-05 00:04:45,300	Ajay-Pandey_A5000	INFO	====> Epoch: 124 [2023-11-05 00:04:45] | (0:00:23.050051)
2023-11-05 00:05:08,178	Ajay-Pandey_A5000	INFO	====> Epoch: 125 [2023-11-05 00:05:08] | (0:00:22.872352)
2023-11-05 00:05:30,974	Ajay-Pandey_A5000	INFO	====> Epoch: 126 [2023-11-05 00:05:30] | (0:00:22.790803)
2023-11-05 00:05:53,781	Ajay-Pandey_A5000	INFO	====> Epoch: 127 [2023-11-05 00:05:53] | (0:00:22.800674)
2023-11-05 00:06:00,780	Ajay-Pandey_A5000	INFO	Train Epoch: 128 [27%]
2023-11-05 00:06:00,781	Ajay-Pandey_A5000	INFO	[4200, 9.842493670173108e-05]
2023-11-05 00:06:00,781	Ajay-Pandey_A5000	INFO	loss_disc=3.827, loss_gen=3.574, loss_fm=8.813,loss_mel=17.144, loss_kl=1.167
2023-11-05 00:06:16,965	Ajay-Pandey_A5000	INFO	====> Epoch: 128 [2023-11-05 00:06:16] | (0:00:23.178656)
2023-11-05 00:06:39,716	Ajay-Pandey_A5000	INFO	====> Epoch: 129 [2023-11-05 00:06:39] | (0:00:22.742354)
2023-11-05 00:07:02,496	Ajay-Pandey_A5000	INFO	====> Epoch: 130 [2023-11-05 00:07:02] | (0:00:22.774633)
2023-11-05 00:07:25,331	Ajay-Pandey_A5000	INFO	====> Epoch: 131 [2023-11-05 00:07:25] | (0:00:22.829231)
2023-11-05 00:07:48,131	Ajay-Pandey_A5000	INFO	====> Epoch: 132 [2023-11-05 00:07:48] | (0:00:22.794170)
2023-11-05 00:08:11,026	Ajay-Pandey_A5000	INFO	====> Epoch: 133 [2023-11-05 00:08:11] | (0:00:22.888139)
2023-11-05 00:08:19,508	Ajay-Pandey_A5000	INFO	Train Epoch: 134 [33%]
2023-11-05 00:08:19,509	Ajay-Pandey_A5000	INFO	[4400, 9.835114106370493e-05]
2023-11-05 00:08:19,509	Ajay-Pandey_A5000	INFO	loss_disc=3.761, loss_gen=3.783, loss_fm=9.872,loss_mel=17.287, loss_kl=1.321
2023-11-05 00:08:34,329	Ajay-Pandey_A5000	INFO	====> Epoch: 134 [2023-11-05 00:08:34] | (0:00:23.297607)
2023-11-05 00:08:57,153	Ajay-Pandey_A5000	INFO	====> Epoch: 135 [2023-11-05 00:08:57] | (0:00:22.816208)
2023-11-05 00:09:20,085	Ajay-Pandey_A5000	INFO	====> Epoch: 136 [2023-11-05 00:09:20] | (0:00:22.925884)
2023-11-05 00:09:42,813	Ajay-Pandey_A5000	INFO	====> Epoch: 137 [2023-11-05 00:09:42] | (0:00:22.722310)
2023-11-05 00:10:05,722	Ajay-Pandey_A5000	INFO	====> Epoch: 138 [2023-11-05 00:10:05] | (0:00:22.902471)
2023-11-05 00:10:28,511	Ajay-Pandey_A5000	INFO	====> Epoch: 139 [2023-11-05 00:10:28] | (0:00:22.782845)
2023-11-05 00:10:38,180	Ajay-Pandey_A5000	INFO	Train Epoch: 140 [39%]
2023-11-05 00:10:38,181	Ajay-Pandey_A5000	INFO	[4600, 9.827740075511432e-05]
2023-11-05 00:10:38,181	Ajay-Pandey_A5000	INFO	loss_disc=3.695, loss_gen=3.762, loss_fm=10.210,loss_mel=16.900, loss_kl=1.238
2023-11-05 00:10:51,520	Ajay-Pandey_A5000	INFO	====> Epoch: 140 [2023-11-05 00:10:51] | (0:00:23.003916)
2023-11-05 00:11:14,330	Ajay-Pandey_A5000	INFO	====> Epoch: 141 [2023-11-05 00:11:14] | (0:00:22.801615)
2023-11-05 00:11:37,164	Ajay-Pandey_A5000	INFO	====> Epoch: 142 [2023-11-05 00:11:37] | (0:00:22.828460)
2023-11-05 00:11:59,979	Ajay-Pandey_A5000	INFO	====> Epoch: 143 [2023-11-05 00:11:59] | (0:00:22.809321)
2023-11-05 00:12:22,894	Ajay-Pandey_A5000	INFO	====> Epoch: 144 [2023-11-05 00:12:22] | (0:00:22.909194)
2023-11-05 00:12:45,715	Ajay-Pandey_A5000	INFO	====> Epoch: 145 [2023-11-05 00:12:45] | (0:00:22.815629)
2023-11-05 00:12:56,822	Ajay-Pandey_A5000	INFO	Train Epoch: 146 [45%]
2023-11-05 00:12:56,823	Ajay-Pandey_A5000	INFO	[4800, 9.820371573447515e-05]
2023-11-05 00:12:56,823	Ajay-Pandey_A5000	INFO	loss_disc=3.812, loss_gen=3.661, loss_fm=9.248,loss_mel=16.898, loss_kl=1.329
2023-11-05 00:13:09,097	Ajay-Pandey_A5000	INFO	====> Epoch: 146 [2023-11-05 00:13:09] | (0:00:23.376005)
2023-11-05 00:13:31,931	Ajay-Pandey_A5000	INFO	====> Epoch: 147 [2023-11-05 00:13:31] | (0:00:22.825565)
2023-11-05 00:13:54,649	Ajay-Pandey_A5000	INFO	====> Epoch: 148 [2023-11-05 00:13:54] | (0:00:22.712815)
2023-11-05 00:14:17,545	Ajay-Pandey_A5000	INFO	====> Epoch: 149 [2023-11-05 00:14:17] | (0:00:22.890707)
2023-11-05 00:14:40,373	Ajay-Pandey_A5000	INFO	Saving model and optimizer state at epoch 150 to ./logs/Ajay-Pandey_A5000/G_2333333.pth
2023-11-05 00:14:46,769	Ajay-Pandey_A5000	INFO	Saving model and optimizer state at epoch 150 to ./logs/Ajay-Pandey_A5000/D_2333333.pth
2023-11-05 00:15:02,580	Ajay-Pandey_A5000	INFO	saving ckpt Ajay-Pandey_A5000_e150:Success.
2023-11-05 00:15:02,580	Ajay-Pandey_A5000	INFO	====> Epoch: 150 [2023-11-05 00:15:02] | (0:00:45.029921)
2023-11-05 00:15:25,183	Ajay-Pandey_A5000	INFO	====> Epoch: 151 [2023-11-05 00:15:25] | (0:00:22.595876)
2023-11-05 00:15:37,702	Ajay-Pandey_A5000	INFO	Train Epoch: 152 [52%]
2023-11-05 00:15:37,703	Ajay-Pandey_A5000	INFO	[5000, 9.813008596033443e-05]
2023-11-05 00:15:37,703	Ajay-Pandey_A5000	INFO	loss_disc=3.733, loss_gen=3.267, loss_fm=9.690,loss_mel=16.781, loss_kl=1.101
2023-11-05 00:15:48,162	Ajay-Pandey_A5000	INFO	====> Epoch: 152 [2023-11-05 00:15:48] | (0:00:22.974181)
2023-11-05 00:16:10,943	Ajay-Pandey_A5000	INFO	====> Epoch: 153 [2023-11-05 00:16:10] | (0:00:22.772547)
2023-11-05 00:16:33,746	Ajay-Pandey_A5000	INFO	====> Epoch: 154 [2023-11-05 00:16:33] | (0:00:22.797435)
2023-11-05 00:16:56,542	Ajay-Pandey_A5000	INFO	====> Epoch: 155 [2023-11-05 00:16:56] | (0:00:22.789698)
2023-11-05 00:17:19,343	Ajay-Pandey_A5000	INFO	====> Epoch: 156 [2023-11-05 00:17:19] | (0:00:22.795960)
2023-11-05 00:17:42,282	Ajay-Pandey_A5000	INFO	====> Epoch: 157 [2023-11-05 00:17:42] | (0:00:22.932891)
2023-11-05 00:17:56,269	Ajay-Pandey_A5000	INFO	Train Epoch: 158 [58%]
2023-11-05 00:17:56,270	Ajay-Pandey_A5000	INFO	[5200, 9.80565113912702e-05]
2023-11-05 00:17:56,270	Ajay-Pandey_A5000	INFO	loss_disc=3.740, loss_gen=3.503, loss_fm=9.680,loss_mel=16.616, loss_kl=1.178
2023-11-05 00:18:06,131	Ajay-Pandey_A5000	INFO	====> Epoch: 158 [2023-11-05 00:18:06] | (0:00:23.843256)
2023-11-05 00:18:28,965	Ajay-Pandey_A5000	INFO	====> Epoch: 159 [2023-11-05 00:18:28] | (0:00:22.826470)
2023-11-05 00:18:51,794	Ajay-Pandey_A5000	INFO	====> Epoch: 160 [2023-11-05 00:18:51] | (0:00:22.823250)
2023-11-05 00:19:14,536	Ajay-Pandey_A5000	INFO	====> Epoch: 161 [2023-11-05 00:19:14] | (0:00:22.736406)
2023-11-05 00:19:37,409	Ajay-Pandey_A5000	INFO	====> Epoch: 162 [2023-11-05 00:19:37] | (0:00:22.867276)
2023-11-05 00:20:00,200	Ajay-Pandey_A5000	INFO	====> Epoch: 163 [2023-11-05 00:20:00] | (0:00:22.785334)
2023-11-05 00:20:15,493	Ajay-Pandey_A5000	INFO	Train Epoch: 164 [64%]
2023-11-05 00:20:15,494	Ajay-Pandey_A5000	INFO	[5400, 9.798299198589162e-05]
2023-11-05 00:20:15,494	Ajay-Pandey_A5000	INFO	loss_disc=3.691, loss_gen=3.500, loss_fm=10.249,loss_mel=16.866, loss_kl=1.159
2023-11-05 00:20:23,669	Ajay-Pandey_A5000	INFO	====> Epoch: 164 [2023-11-05 00:20:23] | (0:00:23.463470)
2023-11-05 00:20:46,482	Ajay-Pandey_A5000	INFO	====> Epoch: 165 [2023-11-05 00:20:46] | (0:00:22.805375)
2023-11-05 00:21:09,226	Ajay-Pandey_A5000	INFO	====> Epoch: 166 [2023-11-05 00:21:09] | (0:00:22.739365)
2023-11-05 00:21:32,088	Ajay-Pandey_A5000	INFO	====> Epoch: 167 [2023-11-05 00:21:32] | (0:00:22.856104)
2023-11-05 00:21:54,852	Ajay-Pandey_A5000	INFO	====> Epoch: 168 [2023-11-05 00:21:54] | (0:00:22.758063)
2023-11-05 00:22:17,618	Ajay-Pandey_A5000	INFO	====> Epoch: 169 [2023-11-05 00:22:17] | (0:00:22.760144)
2023-11-05 00:22:34,404	Ajay-Pandey_A5000	INFO	Train Epoch: 170 [70%]
2023-11-05 00:22:34,404	Ajay-Pandey_A5000	INFO	[5600, 9.790952770283884e-05]
2023-11-05 00:22:34,404	Ajay-Pandey_A5000	INFO	loss_disc=3.531, loss_gen=3.599, loss_fm=10.300,loss_mel=16.736, loss_kl=0.791
2023-11-05 00:22:40,759	Ajay-Pandey_A5000	INFO	====> Epoch: 170 [2023-11-05 00:22:40] | (0:00:23.136333)
2023-11-05 00:23:03,558	Ajay-Pandey_A5000	INFO	====> Epoch: 171 [2023-11-05 00:23:03] | (0:00:22.790795)
2023-11-05 00:23:26,469	Ajay-Pandey_A5000	INFO	====> Epoch: 172 [2023-11-05 00:23:26] | (0:00:22.905419)
2023-11-05 00:23:49,340	Ajay-Pandey_A5000	INFO	====> Epoch: 173 [2023-11-05 00:23:49] | (0:00:22.865242)
2023-11-05 00:24:12,164	Ajay-Pandey_A5000	INFO	====> Epoch: 174 [2023-11-05 00:24:12] | (0:00:22.818543)
2023-11-05 00:24:35,013	Ajay-Pandey_A5000	INFO	====> Epoch: 175 [2023-11-05 00:24:35] | (0:00:22.843645)
2023-11-05 00:24:53,146	Ajay-Pandey_A5000	INFO	Train Epoch: 176 [76%]
2023-11-05 00:24:53,146	Ajay-Pandey_A5000	INFO	[5800, 9.783611850078301e-05]
2023-11-05 00:24:53,147	Ajay-Pandey_A5000	INFO	loss_disc=3.529, loss_gen=3.749, loss_fm=9.505,loss_mel=16.022, loss_kl=0.548
2023-11-05 00:24:58,174	Ajay-Pandey_A5000	INFO	====> Epoch: 176 [2023-11-05 00:24:58] | (0:00:23.155080)
2023-11-05 00:25:20,998	Ajay-Pandey_A5000	INFO	====> Epoch: 177 [2023-11-05 00:25:20] | (0:00:22.815831)
2023-11-05 00:25:43,764	Ajay-Pandey_A5000	INFO	====> Epoch: 178 [2023-11-05 00:25:43] | (0:00:22.761218)
2023-11-05 00:26:06,489	Ajay-Pandey_A5000	INFO	====> Epoch: 179 [2023-11-05 00:26:06] | (0:00:22.719080)
2023-11-05 00:26:29,206	Ajay-Pandey_A5000	INFO	====> Epoch: 180 [2023-11-05 00:26:29] | (0:00:22.712014)
2023-11-05 00:26:52,072	Ajay-Pandey_A5000	INFO	====> Epoch: 181 [2023-11-05 00:26:52] | (0:00:22.860395)
2023-11-05 00:27:11,478	Ajay-Pandey_A5000	INFO	Train Epoch: 182 [82%]
2023-11-05 00:27:11,479	Ajay-Pandey_A5000	INFO	[6000, 9.776276433842631e-05]
2023-11-05 00:27:11,479	Ajay-Pandey_A5000	INFO	loss_disc=3.678, loss_gen=3.582, loss_fm=9.247,loss_mel=16.496, loss_kl=1.117
2023-11-05 00:27:15,210	Ajay-Pandey_A5000	INFO	====> Epoch: 182 [2023-11-05 00:27:15] | (0:00:23.132259)
2023-11-05 00:27:38,132	Ajay-Pandey_A5000	INFO	====> Epoch: 183 [2023-11-05 00:27:38] | (0:00:22.914165)
2023-11-05 00:28:00,840	Ajay-Pandey_A5000	INFO	====> Epoch: 184 [2023-11-05 00:28:00] | (0:00:22.701643)
2023-11-05 00:28:23,670	Ajay-Pandey_A5000	INFO	====> Epoch: 185 [2023-11-05 00:28:23] | (0:00:22.825025)
2023-11-05 00:28:46,427	Ajay-Pandey_A5000	INFO	====> Epoch: 186 [2023-11-05 00:28:46] | (0:00:22.750885)
2023-11-05 00:29:09,293	Ajay-Pandey_A5000	INFO	====> Epoch: 187 [2023-11-05 00:29:09] | (0:00:22.861411)
2023-11-05 00:29:30,105	Ajay-Pandey_A5000	INFO	Train Epoch: 188 [88%]
2023-11-05 00:29:30,106	Ajay-Pandey_A5000	INFO	[6200, 9.768946517450186e-05]
2023-11-05 00:29:30,106	Ajay-Pandey_A5000	INFO	loss_disc=3.434, loss_gen=3.577, loss_fm=9.818,loss_mel=16.039, loss_kl=0.532
2023-11-05 00:29:32,570	Ajay-Pandey_A5000	INFO	====> Epoch: 188 [2023-11-05 00:29:32] | (0:00:23.270988)
2023-11-05 00:29:55,470	Ajay-Pandey_A5000	INFO	====> Epoch: 189 [2023-11-05 00:29:55] | (0:00:22.891330)
2023-11-05 00:30:18,283	Ajay-Pandey_A5000	INFO	====> Epoch: 190 [2023-11-05 00:30:18] | (0:00:22.807743)
2023-11-05 00:30:41,106	Ajay-Pandey_A5000	INFO	====> Epoch: 191 [2023-11-05 00:30:41] | (0:00:22.818090)
2023-11-05 00:31:03,981	Ajay-Pandey_A5000	INFO	====> Epoch: 192 [2023-11-05 00:31:03] | (0:00:22.869071)
2023-11-05 00:31:26,890	Ajay-Pandey_A5000	INFO	====> Epoch: 193 [2023-11-05 00:31:26] | (0:00:22.902973)
2023-11-05 00:31:48,994	Ajay-Pandey_A5000	INFO	Train Epoch: 194 [94%]
2023-11-05 00:31:48,995	Ajay-Pandey_A5000	INFO	[6400, 9.761622096777372e-05]
2023-11-05 00:31:48,995	Ajay-Pandey_A5000	INFO	loss_disc=3.477, loss_gen=3.934, loss_fm=10.371,loss_mel=16.356, loss_kl=0.678
2023-11-05 00:31:49,985	Ajay-Pandey_A5000	INFO	====> Epoch: 194 [2023-11-05 00:31:49] | (0:00:23.089119)
2023-11-05 00:32:12,849	Ajay-Pandey_A5000	INFO	====> Epoch: 195 [2023-11-05 00:32:12] | (0:00:22.856533)
2023-11-05 00:32:35,603	Ajay-Pandey_A5000	INFO	====> Epoch: 196 [2023-11-05 00:32:35] | (0:00:22.748233)
2023-11-05 00:32:58,412	Ajay-Pandey_A5000	INFO	====> Epoch: 197 [2023-11-05 00:32:58] | (0:00:22.803447)
2023-11-05 00:33:21,206	Ajay-Pandey_A5000	INFO	====> Epoch: 198 [2023-11-05 00:33:21] | (0:00:22.788428)
2023-11-05 00:33:43,982	Ajay-Pandey_A5000	INFO	====> Epoch: 199 [2023-11-05 00:33:43] | (0:00:22.770707)
2023-11-05 00:34:06,894	Ajay-Pandey_A5000	INFO	Saving model and optimizer state at epoch 200 to ./logs/Ajay-Pandey_A5000/G_2333333.pth
2023-11-05 00:34:14,598	Ajay-Pandey_A5000	INFO	Saving model and optimizer state at epoch 200 to ./logs/Ajay-Pandey_A5000/D_2333333.pth
2023-11-05 00:34:29,437	Ajay-Pandey_A5000	INFO	saving ckpt Ajay-Pandey_A5000_e200:Success.
2023-11-05 00:34:29,437	Ajay-Pandey_A5000	INFO	====> Epoch: 200 [2023-11-05 00:34:29] | (0:00:45.450064)
2023-11-05 00:34:29,437	Ajay-Pandey_A5000	INFO	Training is done. The program is closed.
2023-11-05 00:34:30,493	Ajay-Pandey_A5000	INFO	saving final ckpt:Success.