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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} |
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2023-11-04 23:03:35,404 Ajay-Pandey_A5000 INFO loaded pretrained assets/pretrained_v2/f0G32k.pth |
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2023-11-04 23:03:36,160 Ajay-Pandey_A5000 INFO <All keys matched successfully> |
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2023-11-04 23:03:37,540 Ajay-Pandey_A5000 INFO <All keys matched successfully> |
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2023-11-04 23:03:51,133 Ajay-Pandey_A5000 INFO Train Epoch: 1 [0%] |
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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 |
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2023-11-04 23:04:26,118 Ajay-Pandey_A5000 INFO ====> Epoch: 1 [2023-11-04 23:04:26] | (0:00:40.061292) |
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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 |
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2023-11-04 23:04:59,337 Ajay-Pandey_A5000 INFO ====> Epoch: 2 [2023-11-04 23:04:59] | (0:00:33.210196) |
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2023-11-04 23:06:05,208 Ajay-Pandey_A5000 INFO ====> Epoch: 4 [2023-11-04 23:06:05] | (0:00:33.354582) |
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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 |
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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 |
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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} |
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2023-11-04 23:12:09,284 Ajay-Pandey_A5000 INFO loaded pretrained assets/pretrained_v2/f0G32k.pth |
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2023-11-04 23:12:09,364 Ajay-Pandey_A5000 INFO <All keys matched successfully> |
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2023-11-04 23:12:09,364 Ajay-Pandey_A5000 INFO loaded pretrained assets/pretrained_v2/f0D32k.pth |
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2023-11-04 23:12:09,450 Ajay-Pandey_A5000 INFO <All keys matched successfully> |
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2023-11-04 23:12:20,748 Ajay-Pandey_A5000 INFO Train Epoch: 1 [0%] |
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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 |
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2023-11-04 23:14:12,293 Ajay-Pandey_A5000 INFO Train Epoch: 5 [65%] |
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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 |
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2023-11-04 23:14:20,289 Ajay-Pandey_A5000 INFO ====> Epoch: 5 [2023-11-04 23:14:20] | (0:00:24.175916) |
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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} |
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2023-11-04 23:16:27,875 Ajay-Pandey_A5000 INFO loaded pretrained assets/pretrained_v2/f0G32k.pth |
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2023-11-04 23:16:27,958 Ajay-Pandey_A5000 INFO <All keys matched successfully> |
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2023-11-04 23:16:28,040 Ajay-Pandey_A5000 INFO <All keys matched successfully> |
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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 |
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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 |
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2023-11-04 23:19:20,564 Ajay-Pandey_A5000 INFO ====> Epoch: 7 [2023-11-04 23:19:20] | (0:00:23.068058) |
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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 |
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2023-11-04 23:23:37,879 Ajay-Pandey_A5000 INFO [600, 9.977523890319963e-05] |
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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 |
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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 |
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2023-11-04 23:28:15,883 Ajay-Pandey_A5000 INFO [1000, 9.962567889519979e-05] |
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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 |
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2023-11-04 23:30:34,896 Ajay-Pandey_A5000 INFO [1200, 9.95509829819056e-05] |
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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 |
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2023-11-04 23:32:53,310 Ajay-Pandey_A5000 INFO Train Epoch: 43 [42%] |
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2023-11-04 23:32:53,310 Ajay-Pandey_A5000 INFO [1400, 9.947634307304244e-05] |
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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 |
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2023-11-04 23:34:37,563 Ajay-Pandey_A5000 INFO ====> Epoch: 47 [2023-11-04 23:34:37] | (0:00:22.775156) |
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2023-11-04 23:35:00,455 Ajay-Pandey_A5000 INFO ====> Epoch: 48 [2023-11-04 23:35:00] | (0:00:22.886509) |
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2023-11-04 23:35:12,395 Ajay-Pandey_A5000 INFO Train Epoch: 49 [48%] |
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2023-11-04 23:35:12,395 Ajay-Pandey_A5000 INFO [1600, 9.940175912662009e-05] |
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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 |
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2023-11-04 23:35:23,643 Ajay-Pandey_A5000 INFO ====> Epoch: 49 [2023-11-04 23:35:23] | (0:00:23.181479) |
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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 |
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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 |
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2023-11-04 23:36:08,327 Ajay-Pandey_A5000 INFO saving ckpt Ajay-Pandey_A5000_e50:Success. |
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2023-11-04 23:36:08,328 Ajay-Pandey_A5000 INFO ====> Epoch: 50 [2023-11-04 23:36:08] | (0:00:44.677081) |
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2023-11-04 23:36:30,891 Ajay-Pandey_A5000 INFO ====> Epoch: 51 [2023-11-04 23:36:30] | (0:00:22.556344) |
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2023-11-04 23:36:53,682 Ajay-Pandey_A5000 INFO ====> Epoch: 52 [2023-11-04 23:36:53] | (0:00:22.785830) |
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2023-11-04 23:37:16,469 Ajay-Pandey_A5000 INFO ====> Epoch: 53 [2023-11-04 23:37:16] | (0:00:22.780890) |
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2023-11-04 23:37:39,326 Ajay-Pandey_A5000 INFO ====> Epoch: 54 [2023-11-04 23:37:39] | (0:00:22.851538) |
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2023-11-04 23:37:52,632 Ajay-Pandey_A5000 INFO Train Epoch: 55 [55%] |
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2023-11-04 23:37:52,632 Ajay-Pandey_A5000 INFO [1800, 9.932723110067987e-05] |
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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 |
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2023-11-04 23:38:02,523 Ajay-Pandey_A5000 INFO ====> Epoch: 55 [2023-11-04 23:38:02] | (0:00:23.191485) |
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2023-11-04 23:38:25,395 Ajay-Pandey_A5000 INFO ====> Epoch: 56 [2023-11-04 23:38:25] | (0:00:22.863796) |
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2023-11-04 23:38:48,203 Ajay-Pandey_A5000 INFO ====> Epoch: 57 [2023-11-04 23:38:48] | (0:00:22.802246) |
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2023-11-04 23:39:11,007 Ajay-Pandey_A5000 INFO ====> Epoch: 58 [2023-11-04 23:39:11] | (0:00:22.797809) |
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2023-11-04 23:39:33,902 Ajay-Pandey_A5000 INFO ====> Epoch: 59 [2023-11-04 23:39:33] | (0:00:22.889679) |
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2023-11-04 23:39:56,833 Ajay-Pandey_A5000 INFO ====> Epoch: 60 [2023-11-04 23:39:56] | (0:00:22.925816) |
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2023-11-04 23:40:11,324 Ajay-Pandey_A5000 INFO Train Epoch: 61 [61%] |
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2023-11-04 23:40:11,325 Ajay-Pandey_A5000 INFO [2000, 9.92527589532945e-05] |
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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 |
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2023-11-04 23:40:20,063 Ajay-Pandey_A5000 INFO ====> Epoch: 61 [2023-11-04 23:40:20] | (0:00:23.224424) |
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2023-11-04 23:40:42,906 Ajay-Pandey_A5000 INFO ====> Epoch: 62 [2023-11-04 23:40:42] | (0:00:22.833550) |
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2023-11-04 23:41:05,760 Ajay-Pandey_A5000 INFO ====> Epoch: 63 [2023-11-04 23:41:05] | (0:00:22.848346) |
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2023-11-04 23:41:28,638 Ajay-Pandey_A5000 INFO ====> Epoch: 64 [2023-11-04 23:41:28] | (0:00:22.872720) |
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2023-11-04 23:41:51,417 Ajay-Pandey_A5000 INFO ====> Epoch: 65 [2023-11-04 23:41:51] | (0:00:22.772879) |
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2023-11-04 23:42:14,328 Ajay-Pandey_A5000 INFO ====> Epoch: 66 [2023-11-04 23:42:14] | (0:00:22.905213) |
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2023-11-04 23:42:30,321 Ajay-Pandey_A5000 INFO Train Epoch: 67 [67%] |
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2023-11-04 23:42:30,322 Ajay-Pandey_A5000 INFO [2200, 9.917834264256819e-05] |
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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 |
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2023-11-04 23:42:37,547 Ajay-Pandey_A5000 INFO ====> Epoch: 67 [2023-11-04 23:42:37] | (0:00:23.214058) |
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2023-11-04 23:43:00,401 Ajay-Pandey_A5000 INFO ====> Epoch: 68 [2023-11-04 23:43:00] | (0:00:22.845379) |
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2023-11-04 23:43:23,233 Ajay-Pandey_A5000 INFO ====> Epoch: 69 [2023-11-04 23:43:23] | (0:00:22.826638) |
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2023-11-04 23:43:46,043 Ajay-Pandey_A5000 INFO ====> Epoch: 70 [2023-11-04 23:43:46] | (0:00:22.804358) |
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2023-11-04 23:44:08,894 Ajay-Pandey_A5000 INFO ====> Epoch: 71 [2023-11-04 23:44:08] | (0:00:22.844825) |
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2023-11-04 23:44:31,601 Ajay-Pandey_A5000 INFO ====> Epoch: 72 [2023-11-04 23:44:31] | (0:00:22.701248) |
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2023-11-04 23:44:48,997 Ajay-Pandey_A5000 INFO Train Epoch: 73 [73%] |
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2023-11-04 23:44:48,997 Ajay-Pandey_A5000 INFO [2400, 9.910398212663652e-05] |
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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 |
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2023-11-04 23:44:54,966 Ajay-Pandey_A5000 INFO ====> Epoch: 73 [2023-11-04 23:44:54] | (0:00:23.359444) |
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2023-11-04 23:45:17,823 Ajay-Pandey_A5000 INFO ====> Epoch: 74 [2023-11-04 23:45:17] | (0:00:22.849027) |
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2023-11-04 23:45:40,662 Ajay-Pandey_A5000 INFO ====> Epoch: 75 [2023-11-04 23:45:40] | (0:00:22.833663) |
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2023-11-04 23:46:03,576 Ajay-Pandey_A5000 INFO ====> Epoch: 76 [2023-11-04 23:46:03] | (0:00:22.908137) |
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2023-11-04 23:46:26,414 Ajay-Pandey_A5000 INFO ====> Epoch: 77 [2023-11-04 23:46:26] | (0:00:22.832327) |
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2023-11-04 23:46:49,371 Ajay-Pandey_A5000 INFO ====> Epoch: 78 [2023-11-04 23:46:49] | (0:00:22.951218) |
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2023-11-04 23:47:08,220 Ajay-Pandey_A5000 INFO Train Epoch: 79 [79%] |
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2023-11-04 23:47:08,221 Ajay-Pandey_A5000 INFO [2600, 9.902967736366644e-05] |
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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 |
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2023-11-04 23:47:12,626 Ajay-Pandey_A5000 INFO ====> Epoch: 79 [2023-11-04 23:47:12] | (0:00:23.248989) |
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2023-11-04 23:47:35,395 Ajay-Pandey_A5000 INFO ====> Epoch: 80 [2023-11-04 23:47:35] | (0:00:22.761023) |
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2023-11-04 23:47:58,245 Ajay-Pandey_A5000 INFO ====> Epoch: 81 [2023-11-04 23:47:58] | (0:00:22.844138) |
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2023-11-04 23:48:21,225 Ajay-Pandey_A5000 INFO ====> Epoch: 82 [2023-11-04 23:48:21] | (0:00:22.973984) |
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2023-11-04 23:48:44,088 Ajay-Pandey_A5000 INFO ====> Epoch: 83 [2023-11-04 23:48:44] | (0:00:22.857614) |
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2023-11-04 23:49:07,015 Ajay-Pandey_A5000 INFO ====> Epoch: 84 [2023-11-04 23:49:07] | (0:00:22.920629) |
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2023-11-04 23:49:27,119 Ajay-Pandey_A5000 INFO Train Epoch: 85 [85%] |
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2023-11-04 23:49:27,120 Ajay-Pandey_A5000 INFO [2800, 9.895542831185631e-05] |
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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 |
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2023-11-04 23:49:30,616 Ajay-Pandey_A5000 INFO ====> Epoch: 85 [2023-11-04 23:49:30] | (0:00:23.596089) |
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2023-11-04 23:49:53,373 Ajay-Pandey_A5000 INFO ====> Epoch: 86 [2023-11-04 23:49:53] | (0:00:22.747797) |
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2023-11-04 23:50:16,257 Ajay-Pandey_A5000 INFO ====> Epoch: 87 [2023-11-04 23:50:16] | (0:00:22.878182) |
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2023-11-04 23:50:39,075 Ajay-Pandey_A5000 INFO ====> Epoch: 88 [2023-11-04 23:50:39] | (0:00:22.812529) |
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2023-11-04 23:51:01,998 Ajay-Pandey_A5000 INFO ====> Epoch: 89 [2023-11-04 23:51:01] | (0:00:22.916868) |
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2023-11-04 23:51:24,829 Ajay-Pandey_A5000 INFO ====> Epoch: 90 [2023-11-04 23:51:24] | (0:00:22.825034) |
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2023-11-04 23:51:46,450 Ajay-Pandey_A5000 INFO Train Epoch: 91 [91%] |
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2023-11-04 23:51:46,450 Ajay-Pandey_A5000 INFO [3000, 9.888123492943583e-05] |
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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 |
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2023-11-04 23:51:48,113 Ajay-Pandey_A5000 INFO ====> Epoch: 91 [2023-11-04 23:51:48] | (0:00:23.279052) |
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2023-11-04 23:52:10,930 Ajay-Pandey_A5000 INFO ====> Epoch: 92 [2023-11-04 23:52:10] | (0:00:22.808739) |
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2023-11-04 23:52:33,944 Ajay-Pandey_A5000 INFO ====> Epoch: 93 [2023-11-04 23:52:33] | (0:00:23.008121) |
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2023-11-04 23:52:56,801 Ajay-Pandey_A5000 INFO ====> Epoch: 94 [2023-11-04 23:52:56] | (0:00:22.851592) |
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2023-11-04 23:53:19,731 Ajay-Pandey_A5000 INFO ====> Epoch: 95 [2023-11-04 23:53:19] | (0:00:22.924260) |
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2023-11-04 23:53:42,729 Ajay-Pandey_A5000 INFO ====> Epoch: 96 [2023-11-04 23:53:42] | (0:00:22.992440) |
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2023-11-04 23:54:05,560 Ajay-Pandey_A5000 INFO Train Epoch: 97 [97%] |
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2023-11-04 23:54:05,561 Ajay-Pandey_A5000 INFO [3200, 9.880709717466598e-05] |
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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 |
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2023-11-04 23:54:05,860 Ajay-Pandey_A5000 INFO ====> Epoch: 97 [2023-11-04 23:54:05] | (0:00:23.125019) |
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2023-11-04 23:54:28,721 Ajay-Pandey_A5000 INFO ====> Epoch: 98 [2023-11-04 23:54:28] | (0:00:22.853465) |
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2023-11-04 23:54:51,611 Ajay-Pandey_A5000 INFO ====> Epoch: 99 [2023-11-04 23:54:51] | (0:00:22.884853) |
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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 |
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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 |
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2023-11-04 23:55:35,499 Ajay-Pandey_A5000 INFO saving ckpt Ajay-Pandey_A5000_e100:Success. |
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2023-11-04 23:55:35,500 Ajay-Pandey_A5000 INFO ====> Epoch: 100 [2023-11-04 23:55:35] | (0:00:43.882735) |
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2023-11-04 23:55:58,095 Ajay-Pandey_A5000 INFO ====> Epoch: 101 [2023-11-04 23:55:58] | (0:00:22.589119) |
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2023-11-04 23:56:20,824 Ajay-Pandey_A5000 INFO ====> Epoch: 102 [2023-11-04 23:56:20] | (0:00:22.723262) |
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2023-11-04 23:56:43,624 Ajay-Pandey_A5000 INFO ====> Epoch: 103 [2023-11-04 23:56:43] | (0:00:22.794056) |
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2023-11-04 23:56:45,316 Ajay-Pandey_A5000 INFO Train Epoch: 104 [3%] |
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2023-11-04 23:56:45,317 Ajay-Pandey_A5000 INFO [3400, 9.872067337896332e-05] |
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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 |
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2023-11-04 23:57:06,953 Ajay-Pandey_A5000 INFO ====> Epoch: 104 [2023-11-04 23:57:06] | (0:00:23.323054) |
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2023-11-04 23:57:29,742 Ajay-Pandey_A5000 INFO ====> Epoch: 105 [2023-11-04 23:57:29] | (0:00:22.781252) |
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2023-11-04 23:57:52,588 Ajay-Pandey_A5000 INFO ====> Epoch: 106 [2023-11-04 23:57:52] | (0:00:22.840464) |
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2023-11-04 23:58:15,447 Ajay-Pandey_A5000 INFO ====> Epoch: 107 [2023-11-04 23:58:15] | (0:00:22.853200) |
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2023-11-04 23:58:38,349 Ajay-Pandey_A5000 INFO ====> Epoch: 108 [2023-11-04 23:58:38] | (0:00:22.897473) |
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2023-11-04 23:59:01,232 Ajay-Pandey_A5000 INFO ====> Epoch: 109 [2023-11-04 23:59:01] | (0:00:22.877168) |
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2023-11-04 23:59:04,274 Ajay-Pandey_A5000 INFO Train Epoch: 110 [9%] |
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2023-11-04 23:59:04,275 Ajay-Pandey_A5000 INFO [3600, 9.864665600773098e-05] |
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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 |
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2023-11-04 23:59:24,422 Ajay-Pandey_A5000 INFO ====> Epoch: 110 [2023-11-04 23:59:24] | (0:00:23.184575) |
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2023-11-04 23:59:47,308 Ajay-Pandey_A5000 INFO ====> Epoch: 111 [2023-11-04 23:59:47] | (0:00:22.878125) |
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2023-11-05 00:00:10,145 Ajay-Pandey_A5000 INFO ====> Epoch: 112 [2023-11-05 00:00:10] | (0:00:22.830921) |
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2023-11-05 00:00:33,022 Ajay-Pandey_A5000 INFO ====> Epoch: 113 [2023-11-05 00:00:33] | (0:00:22.871466) |
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2023-11-05 00:00:55,740 Ajay-Pandey_A5000 INFO ====> Epoch: 114 [2023-11-05 00:00:55] | (0:00:22.712193) |
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2023-11-05 00:01:18,700 Ajay-Pandey_A5000 INFO ====> Epoch: 115 [2023-11-05 00:01:18] | (0:00:22.954302) |
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2023-11-05 00:01:23,078 Ajay-Pandey_A5000 INFO Train Epoch: 116 [15%] |
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2023-11-05 00:01:23,078 Ajay-Pandey_A5000 INFO [3800, 9.857269413218213e-05] |
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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 |
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2023-11-05 00:01:41,958 Ajay-Pandey_A5000 INFO ====> Epoch: 116 [2023-11-05 00:01:41] | (0:00:23.252840) |
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2023-11-05 00:02:04,783 Ajay-Pandey_A5000 INFO ====> Epoch: 117 [2023-11-05 00:02:04] | (0:00:22.817342) |
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2023-11-05 00:02:27,584 Ajay-Pandey_A5000 INFO ====> Epoch: 118 [2023-11-05 00:02:27] | (0:00:22.795033) |
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2023-11-05 00:02:50,455 Ajay-Pandey_A5000 INFO ====> Epoch: 119 [2023-11-05 00:02:50] | (0:00:22.864770) |
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2023-11-05 00:03:13,303 Ajay-Pandey_A5000 INFO ====> Epoch: 120 [2023-11-05 00:03:13] | (0:00:22.843084) |
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2023-11-05 00:03:36,114 Ajay-Pandey_A5000 INFO ====> Epoch: 121 [2023-11-05 00:03:36] | (0:00:22.805537) |
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2023-11-05 00:03:41,737 Ajay-Pandey_A5000 INFO Train Epoch: 122 [21%] |
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2023-11-05 00:03:41,738 Ajay-Pandey_A5000 INFO [4000, 9.8498787710708e-05] |
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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 |
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2023-11-05 00:03:59,480 Ajay-Pandey_A5000 INFO ====> Epoch: 122 [2023-11-05 00:03:59] | (0:00:23.358988) |
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2023-11-05 00:04:22,244 Ajay-Pandey_A5000 INFO ====> Epoch: 123 [2023-11-05 00:04:22] | (0:00:22.756945) |
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2023-11-05 00:04:45,300 Ajay-Pandey_A5000 INFO ====> Epoch: 124 [2023-11-05 00:04:45] | (0:00:23.050051) |
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2023-11-05 00:05:08,178 Ajay-Pandey_A5000 INFO ====> Epoch: 125 [2023-11-05 00:05:08] | (0:00:22.872352) |
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2023-11-05 00:05:30,974 Ajay-Pandey_A5000 INFO ====> Epoch: 126 [2023-11-05 00:05:30] | (0:00:22.790803) |
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2023-11-05 00:05:53,781 Ajay-Pandey_A5000 INFO ====> Epoch: 127 [2023-11-05 00:05:53] | (0:00:22.800674) |
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2023-11-05 00:06:00,780 Ajay-Pandey_A5000 INFO Train Epoch: 128 [27%] |
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2023-11-05 00:06:00,781 Ajay-Pandey_A5000 INFO [4200, 9.842493670173108e-05] |
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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 |
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2023-11-05 00:06:16,965 Ajay-Pandey_A5000 INFO ====> Epoch: 128 [2023-11-05 00:06:16] | (0:00:23.178656) |
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2023-11-05 00:06:39,716 Ajay-Pandey_A5000 INFO ====> Epoch: 129 [2023-11-05 00:06:39] | (0:00:22.742354) |
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2023-11-05 00:07:02,496 Ajay-Pandey_A5000 INFO ====> Epoch: 130 [2023-11-05 00:07:02] | (0:00:22.774633) |
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2023-11-05 00:07:25,331 Ajay-Pandey_A5000 INFO ====> Epoch: 131 [2023-11-05 00:07:25] | (0:00:22.829231) |
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2023-11-05 00:07:48,131 Ajay-Pandey_A5000 INFO ====> Epoch: 132 [2023-11-05 00:07:48] | (0:00:22.794170) |
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2023-11-05 00:08:11,026 Ajay-Pandey_A5000 INFO ====> Epoch: 133 [2023-11-05 00:08:11] | (0:00:22.888139) |
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2023-11-05 00:08:19,508 Ajay-Pandey_A5000 INFO Train Epoch: 134 [33%] |
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2023-11-05 00:08:19,509 Ajay-Pandey_A5000 INFO [4400, 9.835114106370493e-05] |
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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 |
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2023-11-05 00:08:34,329 Ajay-Pandey_A5000 INFO ====> Epoch: 134 [2023-11-05 00:08:34] | (0:00:23.297607) |
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2023-11-05 00:08:57,153 Ajay-Pandey_A5000 INFO ====> Epoch: 135 [2023-11-05 00:08:57] | (0:00:22.816208) |
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2023-11-05 00:09:20,085 Ajay-Pandey_A5000 INFO ====> Epoch: 136 [2023-11-05 00:09:20] | (0:00:22.925884) |
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2023-11-05 00:09:42,813 Ajay-Pandey_A5000 INFO ====> Epoch: 137 [2023-11-05 00:09:42] | (0:00:22.722310) |
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2023-11-05 00:10:05,722 Ajay-Pandey_A5000 INFO ====> Epoch: 138 [2023-11-05 00:10:05] | (0:00:22.902471) |
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2023-11-05 00:10:28,511 Ajay-Pandey_A5000 INFO ====> Epoch: 139 [2023-11-05 00:10:28] | (0:00:22.782845) |
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2023-11-05 00:10:38,180 Ajay-Pandey_A5000 INFO Train Epoch: 140 [39%] |
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2023-11-05 00:10:38,181 Ajay-Pandey_A5000 INFO [4600, 9.827740075511432e-05] |
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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 |
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2023-11-05 00:10:51,520 Ajay-Pandey_A5000 INFO ====> Epoch: 140 [2023-11-05 00:10:51] | (0:00:23.003916) |
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2023-11-05 00:11:14,330 Ajay-Pandey_A5000 INFO ====> Epoch: 141 [2023-11-05 00:11:14] | (0:00:22.801615) |
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2023-11-05 00:11:37,164 Ajay-Pandey_A5000 INFO ====> Epoch: 142 [2023-11-05 00:11:37] | (0:00:22.828460) |
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2023-11-05 00:11:59,979 Ajay-Pandey_A5000 INFO ====> Epoch: 143 [2023-11-05 00:11:59] | (0:00:22.809321) |
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2023-11-05 00:12:22,894 Ajay-Pandey_A5000 INFO ====> Epoch: 144 [2023-11-05 00:12:22] | (0:00:22.909194) |
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2023-11-05 00:12:45,715 Ajay-Pandey_A5000 INFO ====> Epoch: 145 [2023-11-05 00:12:45] | (0:00:22.815629) |
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2023-11-05 00:12:56,822 Ajay-Pandey_A5000 INFO Train Epoch: 146 [45%] |
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2023-11-05 00:12:56,823 Ajay-Pandey_A5000 INFO [4800, 9.820371573447515e-05] |
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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 |
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2023-11-05 00:13:09,097 Ajay-Pandey_A5000 INFO ====> Epoch: 146 [2023-11-05 00:13:09] | (0:00:23.376005) |
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2023-11-05 00:13:31,931 Ajay-Pandey_A5000 INFO ====> Epoch: 147 [2023-11-05 00:13:31] | (0:00:22.825565) |
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2023-11-05 00:13:54,649 Ajay-Pandey_A5000 INFO ====> Epoch: 148 [2023-11-05 00:13:54] | (0:00:22.712815) |
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2023-11-05 00:14:17,545 Ajay-Pandey_A5000 INFO ====> Epoch: 149 [2023-11-05 00:14:17] | (0:00:22.890707) |
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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 |
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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 |
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2023-11-05 00:15:02,580 Ajay-Pandey_A5000 INFO saving ckpt Ajay-Pandey_A5000_e150:Success. |
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2023-11-05 00:15:02,580 Ajay-Pandey_A5000 INFO ====> Epoch: 150 [2023-11-05 00:15:02] | (0:00:45.029921) |
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2023-11-05 00:15:25,183 Ajay-Pandey_A5000 INFO ====> Epoch: 151 [2023-11-05 00:15:25] | (0:00:22.595876) |
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2023-11-05 00:15:37,702 Ajay-Pandey_A5000 INFO Train Epoch: 152 [52%] |
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2023-11-05 00:15:37,703 Ajay-Pandey_A5000 INFO [5000, 9.813008596033443e-05] |
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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 |
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2023-11-05 00:15:48,162 Ajay-Pandey_A5000 INFO ====> Epoch: 152 [2023-11-05 00:15:48] | (0:00:22.974181) |
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2023-11-05 00:16:10,943 Ajay-Pandey_A5000 INFO ====> Epoch: 153 [2023-11-05 00:16:10] | (0:00:22.772547) |
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2023-11-05 00:16:33,746 Ajay-Pandey_A5000 INFO ====> Epoch: 154 [2023-11-05 00:16:33] | (0:00:22.797435) |
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2023-11-05 00:16:56,542 Ajay-Pandey_A5000 INFO ====> Epoch: 155 [2023-11-05 00:16:56] | (0:00:22.789698) |
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2023-11-05 00:17:19,343 Ajay-Pandey_A5000 INFO ====> Epoch: 156 [2023-11-05 00:17:19] | (0:00:22.795960) |
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2023-11-05 00:17:42,282 Ajay-Pandey_A5000 INFO ====> Epoch: 157 [2023-11-05 00:17:42] | (0:00:22.932891) |
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2023-11-05 00:17:56,269 Ajay-Pandey_A5000 INFO Train Epoch: 158 [58%] |
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2023-11-05 00:17:56,270 Ajay-Pandey_A5000 INFO [5200, 9.80565113912702e-05] |
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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 |
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2023-11-05 00:18:06,131 Ajay-Pandey_A5000 INFO ====> Epoch: 158 [2023-11-05 00:18:06] | (0:00:23.843256) |
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2023-11-05 00:18:28,965 Ajay-Pandey_A5000 INFO ====> Epoch: 159 [2023-11-05 00:18:28] | (0:00:22.826470) |
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2023-11-05 00:18:51,794 Ajay-Pandey_A5000 INFO ====> Epoch: 160 [2023-11-05 00:18:51] | (0:00:22.823250) |
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2023-11-05 00:19:14,536 Ajay-Pandey_A5000 INFO ====> Epoch: 161 [2023-11-05 00:19:14] | (0:00:22.736406) |
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2023-11-05 00:19:37,409 Ajay-Pandey_A5000 INFO ====> Epoch: 162 [2023-11-05 00:19:37] | (0:00:22.867276) |
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2023-11-05 00:20:00,200 Ajay-Pandey_A5000 INFO ====> Epoch: 163 [2023-11-05 00:20:00] | (0:00:22.785334) |
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2023-11-05 00:20:15,493 Ajay-Pandey_A5000 INFO Train Epoch: 164 [64%] |
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2023-11-05 00:20:15,494 Ajay-Pandey_A5000 INFO [5400, 9.798299198589162e-05] |
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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 |
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2023-11-05 00:20:23,669 Ajay-Pandey_A5000 INFO ====> Epoch: 164 [2023-11-05 00:20:23] | (0:00:23.463470) |
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2023-11-05 00:20:46,482 Ajay-Pandey_A5000 INFO ====> Epoch: 165 [2023-11-05 00:20:46] | (0:00:22.805375) |
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2023-11-05 00:21:09,226 Ajay-Pandey_A5000 INFO ====> Epoch: 166 [2023-11-05 00:21:09] | (0:00:22.739365) |
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2023-11-05 00:21:32,088 Ajay-Pandey_A5000 INFO ====> Epoch: 167 [2023-11-05 00:21:32] | (0:00:22.856104) |
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2023-11-05 00:21:54,852 Ajay-Pandey_A5000 INFO ====> Epoch: 168 [2023-11-05 00:21:54] | (0:00:22.758063) |
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2023-11-05 00:22:17,618 Ajay-Pandey_A5000 INFO ====> Epoch: 169 [2023-11-05 00:22:17] | (0:00:22.760144) |
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2023-11-05 00:22:34,404 Ajay-Pandey_A5000 INFO Train Epoch: 170 [70%] |
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2023-11-05 00:22:34,404 Ajay-Pandey_A5000 INFO [5600, 9.790952770283884e-05] |
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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 |
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2023-11-05 00:22:40,759 Ajay-Pandey_A5000 INFO ====> Epoch: 170 [2023-11-05 00:22:40] | (0:00:23.136333) |
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2023-11-05 00:23:03,558 Ajay-Pandey_A5000 INFO ====> Epoch: 171 [2023-11-05 00:23:03] | (0:00:22.790795) |
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2023-11-05 00:23:26,469 Ajay-Pandey_A5000 INFO ====> Epoch: 172 [2023-11-05 00:23:26] | (0:00:22.905419) |
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2023-11-05 00:23:49,340 Ajay-Pandey_A5000 INFO ====> Epoch: 173 [2023-11-05 00:23:49] | (0:00:22.865242) |
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2023-11-05 00:24:12,164 Ajay-Pandey_A5000 INFO ====> Epoch: 174 [2023-11-05 00:24:12] | (0:00:22.818543) |
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2023-11-05 00:24:35,013 Ajay-Pandey_A5000 INFO ====> Epoch: 175 [2023-11-05 00:24:35] | (0:00:22.843645) |
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2023-11-05 00:24:53,146 Ajay-Pandey_A5000 INFO Train Epoch: 176 [76%] |
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2023-11-05 00:24:53,146 Ajay-Pandey_A5000 INFO [5800, 9.783611850078301e-05] |
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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 |
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2023-11-05 00:24:58,174 Ajay-Pandey_A5000 INFO ====> Epoch: 176 [2023-11-05 00:24:58] | (0:00:23.155080) |
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2023-11-05 00:25:20,998 Ajay-Pandey_A5000 INFO ====> Epoch: 177 [2023-11-05 00:25:20] | (0:00:22.815831) |
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2023-11-05 00:25:43,764 Ajay-Pandey_A5000 INFO ====> Epoch: 178 [2023-11-05 00:25:43] | (0:00:22.761218) |
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2023-11-05 00:26:06,489 Ajay-Pandey_A5000 INFO ====> Epoch: 179 [2023-11-05 00:26:06] | (0:00:22.719080) |
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2023-11-05 00:26:29,206 Ajay-Pandey_A5000 INFO ====> Epoch: 180 [2023-11-05 00:26:29] | (0:00:22.712014) |
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2023-11-05 00:26:52,072 Ajay-Pandey_A5000 INFO ====> Epoch: 181 [2023-11-05 00:26:52] | (0:00:22.860395) |
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2023-11-05 00:27:11,478 Ajay-Pandey_A5000 INFO Train Epoch: 182 [82%] |
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2023-11-05 00:27:11,479 Ajay-Pandey_A5000 INFO [6000, 9.776276433842631e-05] |
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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 |
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2023-11-05 00:27:15,210 Ajay-Pandey_A5000 INFO ====> Epoch: 182 [2023-11-05 00:27:15] | (0:00:23.132259) |
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2023-11-05 00:27:38,132 Ajay-Pandey_A5000 INFO ====> Epoch: 183 [2023-11-05 00:27:38] | (0:00:22.914165) |
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2023-11-05 00:28:00,840 Ajay-Pandey_A5000 INFO ====> Epoch: 184 [2023-11-05 00:28:00] | (0:00:22.701643) |
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2023-11-05 00:28:23,670 Ajay-Pandey_A5000 INFO ====> Epoch: 185 [2023-11-05 00:28:23] | (0:00:22.825025) |
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2023-11-05 00:28:46,427 Ajay-Pandey_A5000 INFO ====> Epoch: 186 [2023-11-05 00:28:46] | (0:00:22.750885) |
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2023-11-05 00:29:09,293 Ajay-Pandey_A5000 INFO ====> Epoch: 187 [2023-11-05 00:29:09] | (0:00:22.861411) |
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2023-11-05 00:29:30,105 Ajay-Pandey_A5000 INFO Train Epoch: 188 [88%] |
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2023-11-05 00:29:30,106 Ajay-Pandey_A5000 INFO [6200, 9.768946517450186e-05] |
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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 |
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2023-11-05 00:29:32,570 Ajay-Pandey_A5000 INFO ====> Epoch: 188 [2023-11-05 00:29:32] | (0:00:23.270988) |
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2023-11-05 00:29:55,470 Ajay-Pandey_A5000 INFO ====> Epoch: 189 [2023-11-05 00:29:55] | (0:00:22.891330) |
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2023-11-05 00:30:18,283 Ajay-Pandey_A5000 INFO ====> Epoch: 190 [2023-11-05 00:30:18] | (0:00:22.807743) |
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2023-11-05 00:30:41,106 Ajay-Pandey_A5000 INFO ====> Epoch: 191 [2023-11-05 00:30:41] | (0:00:22.818090) |
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2023-11-05 00:31:03,981 Ajay-Pandey_A5000 INFO ====> Epoch: 192 [2023-11-05 00:31:03] | (0:00:22.869071) |
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2023-11-05 00:31:26,890 Ajay-Pandey_A5000 INFO ====> Epoch: 193 [2023-11-05 00:31:26] | (0:00:22.902973) |
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2023-11-05 00:31:48,994 Ajay-Pandey_A5000 INFO Train Epoch: 194 [94%] |
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2023-11-05 00:31:48,995 Ajay-Pandey_A5000 INFO [6400, 9.761622096777372e-05] |
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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 |
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2023-11-05 00:31:49,985 Ajay-Pandey_A5000 INFO ====> Epoch: 194 [2023-11-05 00:31:49] | (0:00:23.089119) |
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2023-11-05 00:32:12,849 Ajay-Pandey_A5000 INFO ====> Epoch: 195 [2023-11-05 00:32:12] | (0:00:22.856533) |
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2023-11-05 00:32:35,603 Ajay-Pandey_A5000 INFO ====> Epoch: 196 [2023-11-05 00:32:35] | (0:00:22.748233) |
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2023-11-05 00:32:58,412 Ajay-Pandey_A5000 INFO ====> Epoch: 197 [2023-11-05 00:32:58] | (0:00:22.803447) |
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2023-11-05 00:33:21,206 Ajay-Pandey_A5000 INFO ====> Epoch: 198 [2023-11-05 00:33:21] | (0:00:22.788428) |
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2023-11-05 00:33:43,982 Ajay-Pandey_A5000 INFO ====> Epoch: 199 [2023-11-05 00:33:43] | (0:00:22.770707) |
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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 |
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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 |
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2023-11-05 00:34:29,437 Ajay-Pandey_A5000 INFO saving ckpt Ajay-Pandey_A5000_e200:Success. |
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2023-11-05 00:34:29,437 Ajay-Pandey_A5000 INFO ====> Epoch: 200 [2023-11-05 00:34:29] | (0:00:45.450064) |
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2023-11-05 00:34:29,437 Ajay-Pandey_A5000 INFO Training is done. The program is closed. |
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2023-11-05 00:34:30,493 Ajay-Pandey_A5000 INFO saving final ckpt:Success. |
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