[2023-08-15 13:03:31,782 INFO] Use GPU: 2 for training
[2023-08-15 13:03:36,301 INFO] unlabeled data number: 7000, labeled data number 100
[2023-08-15 13:03:36,301 INFO] Create train and test data loaders
[2023-08-15 13:03:38,997 INFO] [!] data loader keys: dict_keys(['train_lb', 'train_ulb', 'eval', 'test'])
[2023-08-15 13:04:11,886 INFO] Create optimizer and scheduler
[2023-08-15 13:04:13,924 INFO] Number of Trainable Params: 94969994
[2023-08-15 13:04:14,227 INFO] Arguments: Namespace(save_dir='/liuzicheng/jwy/saved_models/usb_audio', save_name='softmatch_gtzan_100_0', resume=True, load_path='/liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth', overwrite=True, use_tensorboard=True, use_wandb=False, use_aim=False, epoch=100, num_train_iter=102400, num_warmup_iter=5120, num_eval_iter=2048, num_log_iter=256, num_labels=100, batch_size=8, uratio=1, eval_batch_size=16, ema_m=0.0, ulb_loss_ratio=1.0, optim='AdamW', lr=2e-05, momentum=0.9, weight_decay=2e-05, layer_decay=1.0, net='wave2vecv2_base', net_from_name=False, use_pretrain=False, pretrain_path='', algorithm='softmatch', use_cat=False, amp=False, clip_grad=0, imb_algorithm=None, data_dir='/liuzicheng/data/data', dataset='gtzan', num_classes=10, train_sampler='RandomSampler', num_workers=4, include_lb_to_ulb=True, lb_imb_ratio=1, ulb_imb_ratio=1, ulb_num_labels=None, img_size=32, crop_ratio=0.875, max_length=512, max_length_seconds=3.0, sample_rate=16000, world_size=1, rank=0, dist_url='tcp://127.0.0.1:29183', dist_backend='nccl', seed=0, gpu=2, multiprocessing_distributed=False, c='/liuzicheng/jwy/otherbaseline-main2/config/usb_audio/softmatch/softmatch_gtzan_100_0.yaml', hard_label=True, T=0.5, dist_align=True, dist_uniform=True, ema_p=0.999, n_sigma=2, per_class=False, clip=0.0, distributed=False, ulb_dest_len=7000, lb_dest_len=100)
[2023-08-15 13:04:14,227 INFO] Resume load path /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth does not exist
[2023-08-15 13:04:14,227 INFO] Model training
[2023-08-15 13:07:35,534 INFO] 256 iteration USE_EMA: False, train/sup_loss: 2.3156, train/unsup_loss: 2.0332, train/total_loss: 4.3488, train/util_ratio: 1.0000, train/run_time: 0.7379, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 13:10:49,737 INFO] 512 iteration USE_EMA: False, train/sup_loss: 2.4218, train/unsup_loss: 1.1553, train/total_loss: 3.5771, train/util_ratio: 1.0000, train/run_time: 0.7031, lr: 0.0000, train/prefecth_time: 0.0057 
[2023-08-15 13:14:05,195 INFO] 768 iteration USE_EMA: False, train/sup_loss: 2.9127, train/unsup_loss: 1.1987, train/total_loss: 4.1113, train/util_ratio: 1.0000, train/run_time: 0.7244, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 13:17:18,256 INFO] 1024 iteration USE_EMA: False, train/sup_loss: 2.4288, train/unsup_loss: 0.5818, train/total_loss: 3.0106, train/util_ratio: 0.9997, train/run_time: 0.7247, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 13:20:32,284 INFO] 1280 iteration USE_EMA: False, train/sup_loss: 2.3064, train/unsup_loss: 0.4553, train/total_loss: 2.7617, train/util_ratio: 0.9666, train/run_time: 0.7105, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 13:23:46,294 INFO] 1536 iteration USE_EMA: False, train/sup_loss: 2.3760, train/unsup_loss: 0.3015, train/total_loss: 2.6775, train/util_ratio: 0.9903, train/run_time: 0.7242, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 13:26:59,335 INFO] 1792 iteration USE_EMA: False, train/sup_loss: 2.3961, train/unsup_loss: 0.8097, train/total_loss: 3.2058, train/util_ratio: 0.9293, train/run_time: 0.7662, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 13:30:13,813 INFO] validating...
[2023-08-15 13:30:30,153 INFO] confusion matrix:
[[0.         0.         0.         0.         0.68       0.
  0.26666667 0.         0.         0.05333333]
 [0.         0.         0.         0.         0.29333333 0.
  0.70666667 0.         0.         0.        ]
 [0.         0.         0.         0.         0.58666667 0.
  0.38       0.         0.         0.03333333]
 [0.         0.         0.         0.         0.75333333 0.
  0.23333333 0.         0.         0.01333333]
 [0.         0.         0.         0.         0.98       0.
  0.02       0.         0.         0.        ]
 [0.         0.         0.         0.         0.6        0.
  0.38666667 0.         0.         0.01333333]
 [0.         0.         0.         0.         0.3        0.
  0.68666667 0.         0.         0.01333333]
 [0.         0.         0.         0.         0.82666667 0.
  0.16666667 0.         0.         0.00666667]
 [0.00666667 0.         0.         0.         0.90666667 0.
  0.06666667 0.         0.         0.02      ]
 [0.         0.         0.         0.         0.44       0.
  0.54       0.         0.         0.02      ]]
[2023-08-15 13:30:32,204 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 13:30:34,167 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 13:30:34,169 INFO] 2048 iteration, USE_EMA: False, train/sup_loss: 2.4739, train/unsup_loss: 1.1370, train/total_loss: 3.6109, train/util_ratio: 0.9445, train/run_time: 0.6898, eval/loss: 2.6118, eval/top-1-acc: 0.1687, eval/balanced_acc: 0.1687, eval/precision: 0.0468, eval/recall: 0.1687, eval/F1: 0.0609, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.1687, at 2048 iters
[2023-08-15 13:33:50,512 INFO] 2304 iteration USE_EMA: False, train/sup_loss: 2.2255, train/unsup_loss: 0.8296, train/total_loss: 3.0551, train/util_ratio: 0.9257, train/run_time: 0.7185, lr: 0.0000, train/prefecth_time: 0.0069 
[2023-08-15 13:37:01,640 INFO] 2560 iteration USE_EMA: False, train/sup_loss: 1.8562, train/unsup_loss: 1.3760, train/total_loss: 3.2323, train/util_ratio: 0.9999, train/run_time: 0.6806, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 13:40:15,365 INFO] 2816 iteration USE_EMA: False, train/sup_loss: 2.4885, train/unsup_loss: 1.6637, train/total_loss: 4.1522, train/util_ratio: 0.9969, train/run_time: 0.7235, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 13:43:29,246 INFO] 3072 iteration USE_EMA: False, train/sup_loss: 2.0720, train/unsup_loss: 1.5759, train/total_loss: 3.6479, train/util_ratio: 0.9832, train/run_time: 0.6603, lr: 0.0000, train/prefecth_time: 0.0048 
[2023-08-15 13:46:44,811 INFO] 3328 iteration USE_EMA: False, train/sup_loss: 1.2383, train/unsup_loss: 0.6312, train/total_loss: 1.8695, train/util_ratio: 0.9624, train/run_time: 0.7425, lr: 0.0000, train/prefecth_time: 0.0054 
[2023-08-15 13:49:57,709 INFO] 3584 iteration USE_EMA: False, train/sup_loss: 1.0166, train/unsup_loss: 0.9849, train/total_loss: 2.0014, train/util_ratio: 0.9222, train/run_time: 0.7026, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 13:53:11,542 INFO] 3840 iteration USE_EMA: False, train/sup_loss: 1.1982, train/unsup_loss: 0.9961, train/total_loss: 2.1943, train/util_ratio: 1.0000, train/run_time: 0.7147, lr: 0.0000, train/prefecth_time: 0.0058 
[2023-08-15 13:56:24,126 INFO] validating...
[2023-08-15 13:56:41,127 INFO] confusion matrix:
[[0.30666667 0.09333333 0.21333333 0.14       0.         0.
  0.04666667 0.13333333 0.06666667 0.        ]
 [0.00666667 0.64666667 0.02666667 0.         0.         0.31333333
  0.00666667 0.         0.         0.        ]
 [0.26       0.08666667 0.38666667 0.10666667 0.         0.02
  0.02       0.08       0.03333333 0.00666667]
 [0.06       0.01333333 0.01333333 0.39333333 0.17333333 0.
  0.1        0.04666667 0.2        0.        ]
 [0.01333333 0.00666667 0.00666667 0.02666667 0.82       0.
  0.02666667 0.00666667 0.09333333 0.        ]
 [0.03333333 0.26       0.11333333 0.         0.01333333 0.44
  0.08666667 0.04       0.01333333 0.        ]
 [0.02       0.         0.         0.03333333 0.00666667 0.01333333
  0.86666667 0.02666667 0.03333333 0.        ]
 [0.09333333 0.04       0.06666667 0.18666667 0.33333333 0.00666667
  0.04       0.08       0.15333333 0.        ]
 [0.03333333 0.03333333 0.02666667 0.14666667 0.28       0.00666667
  0.01333333 0.02666667 0.43333333 0.        ]
 [0.28       0.04666667 0.08666667 0.2        0.01333333 0.04666667
  0.18       0.07333333 0.07333333 0.        ]]
[2023-08-15 13:56:42,982 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 13:56:44,776 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 13:56:44,777 INFO] 4096 iteration, USE_EMA: False, train/sup_loss: 0.8028, train/unsup_loss: 1.9917, train/total_loss: 2.7945, train/util_ratio: 0.9292, train/run_time: 0.4804, eval/loss: 2.0870, eval/top-1-acc: 0.4373, eval/balanced_acc: 0.4373, eval/precision: 0.3729, eval/recall: 0.4373, eval/F1: 0.3965, lr: 0.0000, train/prefecth_time: 0.0066 BEST_EVAL_ACC: 0.4373, at 4096 iters
[2023-08-15 14:00:00,018 INFO] 4352 iteration USE_EMA: False, train/sup_loss: 0.9766, train/unsup_loss: 0.6550, train/total_loss: 1.6316, train/util_ratio: 1.0000, train/run_time: 0.6981, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 14:03:14,019 INFO] 4608 iteration USE_EMA: False, train/sup_loss: 0.5029, train/unsup_loss: 0.5368, train/total_loss: 1.0397, train/util_ratio: 0.6746, train/run_time: 0.7184, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 14:06:25,646 INFO] 4864 iteration USE_EMA: False, train/sup_loss: 0.3741, train/unsup_loss: 0.9898, train/total_loss: 1.3639, train/util_ratio: 0.9671, train/run_time: 0.7057, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 14:09:39,252 INFO] 5120 iteration USE_EMA: False, train/sup_loss: 0.1574, train/unsup_loss: 0.3927, train/total_loss: 0.5501, train/util_ratio: 0.8977, train/run_time: 0.7153, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 14:12:54,542 INFO] 5376 iteration USE_EMA: False, train/sup_loss: 0.0688, train/unsup_loss: 0.4507, train/total_loss: 0.5195, train/util_ratio: 0.7057, train/run_time: 0.7445, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 14:16:08,995 INFO] 5632 iteration USE_EMA: False, train/sup_loss: 0.5069, train/unsup_loss: 0.7098, train/total_loss: 1.2167, train/util_ratio: 0.8078, train/run_time: 0.7201, lr: 0.0000, train/prefecth_time: 0.0069 
[2023-08-15 14:19:23,570 INFO] 5888 iteration USE_EMA: False, train/sup_loss: 0.0537, train/unsup_loss: 0.2442, train/total_loss: 0.2979, train/util_ratio: 0.8237, train/run_time: 0.6864, lr: 0.0000, train/prefecth_time: 0.0206 
[2023-08-15 14:22:34,575 INFO] validating...
[2023-08-15 14:22:51,877 INFO] confusion matrix:
[[0.12666667 0.00666667 0.15333333 0.38       0.         0.04
  0.06666667 0.         0.14666667 0.08      ]
 [0.02666667 0.68       0.06       0.01333333 0.         0.16666667
  0.00666667 0.         0.         0.04666667]
 [0.12666667 0.00666667 0.47333333 0.25333333 0.         0.00666667
  0.01333333 0.         0.08666667 0.03333333]
 [0.         0.         0.01333333 0.8        0.07333333 0.01333333
  0.04       0.         0.04       0.02      ]
 [0.02       0.         0.00666667 0.20666667 0.70666667 0.
  0.00666667 0.         0.05333333 0.        ]
 [0.08       0.06       0.06       0.12       0.01333333 0.48
  0.07333333 0.         0.01333333 0.1       ]
 [0.         0.         0.00666667 0.17333333 0.00666667 0.
  0.80666667 0.         0.         0.00666667]
 [0.02666667 0.00666667 0.05333333 0.55333333 0.22666667 0.01333333
  0.01333333 0.05333333 0.02       0.03333333]
 [0.01333333 0.00666667 0.01333333 0.34       0.16       0.00666667
  0.01333333 0.         0.43333333 0.01333333]
 [0.00666667 0.         0.14666667 0.47333333 0.00666667 0.02666667
  0.16       0.01333333 0.04       0.12666667]]
[2023-08-15 14:22:53,666 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 14:22:55,612 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 14:22:55,614 INFO] 6144 iteration, USE_EMA: False, train/sup_loss: 0.0781, train/unsup_loss: 0.9602, train/total_loss: 1.0383, train/util_ratio: 0.8755, train/run_time: 0.6806, eval/loss: 2.7624, eval/top-1-acc: 0.4687, eval/balanced_acc: 0.4687, eval/precision: 0.5402, eval/recall: 0.4687, eval/F1: 0.4466, lr: 0.0000, train/prefecth_time: 0.0070 BEST_EVAL_ACC: 0.4687, at 6144 iters
[2023-08-15 14:26:10,643 INFO] 6400 iteration USE_EMA: False, train/sup_loss: 0.4600, train/unsup_loss: 0.5444, train/total_loss: 1.0044, train/util_ratio: 0.8750, train/run_time: 0.7282, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 14:29:24,276 INFO] 6656 iteration USE_EMA: False, train/sup_loss: 0.4308, train/unsup_loss: 0.9439, train/total_loss: 1.3747, train/util_ratio: 0.9314, train/run_time: 0.7216, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 14:32:38,298 INFO] 6912 iteration USE_EMA: False, train/sup_loss: 0.0376, train/unsup_loss: 0.3204, train/total_loss: 0.3580, train/util_ratio: 0.7102, train/run_time: 0.7256, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 14:35:48,059 INFO] 7168 iteration USE_EMA: False, train/sup_loss: 0.0407, train/unsup_loss: 0.6003, train/total_loss: 0.6410, train/util_ratio: 0.7508, train/run_time: 0.7215, lr: 0.0000, train/prefecth_time: 0.0053 
[2023-08-15 14:39:04,004 INFO] 7424 iteration USE_EMA: False, train/sup_loss: 0.0727, train/unsup_loss: 1.2326, train/total_loss: 1.3053, train/util_ratio: 0.8658, train/run_time: 0.6682, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-15 14:42:18,984 INFO] 7680 iteration USE_EMA: False, train/sup_loss: 0.0284, train/unsup_loss: 0.9108, train/total_loss: 0.9391, train/util_ratio: 0.9655, train/run_time: 0.6871, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 14:45:32,567 INFO] 7936 iteration USE_EMA: False, train/sup_loss: 0.0136, train/unsup_loss: 0.5444, train/total_loss: 0.5581, train/util_ratio: 1.0000, train/run_time: 0.7059, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 14:48:44,239 INFO] validating...
[2023-08-15 14:49:01,244 INFO] confusion matrix:
[[0.38       0.01333333 0.08666667 0.04       0.04666667 0.01333333
  0.08       0.13333333 0.20666667 0.        ]
 [0.02666667 0.76666667 0.02       0.         0.         0.13333333
  0.01333333 0.02       0.         0.02      ]
 [0.21333333 0.00666667 0.47333333 0.06       0.05333333 0.00666667
  0.00666667 0.06       0.10666667 0.01333333]
 [0.00666667 0.         0.00666667 0.06666667 0.47333333 0.00666667
  0.         0.26       0.17333333 0.00666667]
 [0.02       0.         0.00666667 0.         0.88       0.
  0.         0.03333333 0.06       0.        ]
 [0.14       0.03333333 0.02666667 0.02       0.1        0.56
  0.04666667 0.04       0.01333333 0.02      ]
 [0.00666667 0.         0.00666667 0.03333333 0.2        0.
  0.72       0.03333333 0.         0.        ]
 [0.08666667 0.00666667 0.02666667 0.00666667 0.44666667 0.00666667
  0.         0.28666667 0.13333333 0.        ]
 [0.06       0.         0.01333333 0.01333333 0.33333333 0.
  0.         0.02666667 0.55333333 0.        ]
 [0.08       0.02       0.13333333 0.11333333 0.09333333 0.01333333
  0.16       0.23333333 0.12       0.03333333]]
[2023-08-15 14:49:03,203 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 14:49:05,042 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 14:49:05,043 INFO] 8192 iteration, USE_EMA: False, train/sup_loss: 0.3694, train/unsup_loss: 0.8692, train/total_loss: 1.2386, train/util_ratio: 0.8712, train/run_time: 0.6697, eval/loss: 3.1124, eval/top-1-acc: 0.4720, eval/balanced_acc: 0.4720, eval/precision: 0.4868, eval/recall: 0.4720, eval/F1: 0.4469, lr: 0.0000, train/prefecth_time: 0.0070 BEST_EVAL_ACC: 0.4720, at 8192 iters
[2023-08-15 14:52:20,317 INFO] 8448 iteration USE_EMA: False, train/sup_loss: 0.0109, train/unsup_loss: 0.8561, train/total_loss: 0.8670, train/util_ratio: 0.6329, train/run_time: 0.7471, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 14:55:34,985 INFO] 8704 iteration USE_EMA: False, train/sup_loss: 0.0148, train/unsup_loss: 0.8321, train/total_loss: 0.8469, train/util_ratio: 0.8531, train/run_time: 0.6996, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 14:58:48,169 INFO] 8960 iteration USE_EMA: False, train/sup_loss: 0.0091, train/unsup_loss: 1.2387, train/total_loss: 1.2478, train/util_ratio: 0.7961, train/run_time: 0.7325, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 15:01:59,948 INFO] 9216 iteration USE_EMA: False, train/sup_loss: 0.0095, train/unsup_loss: 1.5160, train/total_loss: 1.5255, train/util_ratio: 0.8710, train/run_time: 0.6909, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 15:05:13,069 INFO] 9472 iteration USE_EMA: False, train/sup_loss: 0.0096, train/unsup_loss: 0.2698, train/total_loss: 0.2794, train/util_ratio: 0.6043, train/run_time: 0.7408, lr: 0.0000, train/prefecth_time: 0.0118 
[2023-08-15 15:08:24,991 INFO] 9728 iteration USE_EMA: False, train/sup_loss: 0.0063, train/unsup_loss: 0.6890, train/total_loss: 0.6953, train/util_ratio: 0.8603, train/run_time: 0.6854, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 15:11:38,250 INFO] 9984 iteration USE_EMA: False, train/sup_loss: 0.0084, train/unsup_loss: 0.0625, train/total_loss: 0.0709, train/util_ratio: 0.8272, train/run_time: 0.7138, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 15:14:50,307 INFO] validating...
[2023-08-15 15:15:07,429 INFO] confusion matrix:
[[0.44       0.01333333 0.20666667 0.14       0.         0.04
  0.01333333 0.04666667 0.07333333 0.02666667]
 [0.00666667 0.84666667 0.         0.00666667 0.         0.08666667
  0.02       0.02666667 0.         0.00666667]
 [0.24       0.04       0.56       0.06666667 0.         0.01333333
  0.00666667 0.02666667 0.03333333 0.01333333]
 [0.00666667 0.         0.05333333 0.53333333 0.04       0.00666667
  0.         0.1        0.24666667 0.01333333]
 [0.02       0.         0.02       0.02666667 0.41333333 0.
  0.         0.06       0.46       0.        ]
 [0.09333333 0.1        0.04       0.03333333 0.01333333 0.56
  0.01333333 0.02       0.05333333 0.07333333]
 [0.02       0.         0.09333333 0.24       0.01333333 0.
  0.56666667 0.04       0.02666667 0.        ]
 [0.05333333 0.02       0.14       0.09333333 0.07333333 0.02666667
  0.00666667 0.24       0.34666667 0.        ]
 [0.05333333 0.         0.06666667 0.06       0.02       0.
  0.         0.02       0.76666667 0.01333333]
 [0.08       0.02666667 0.41333333 0.25333333 0.         0.
  0.08       0.06666667 0.04666667 0.03333333]]
[2023-08-15 15:15:09,419 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 15:15:11,506 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 15:15:11,508 INFO] 10240 iteration, USE_EMA: False, train/sup_loss: 0.0134, train/unsup_loss: 0.1541, train/total_loss: 0.1676, train/util_ratio: 0.9540, train/run_time: 0.6938, eval/loss: 2.7601, eval/top-1-acc: 0.4960, eval/balanced_acc: 0.4960, eval/precision: 0.5178, eval/recall: 0.4960, eval/F1: 0.4817, lr: 0.0000, train/prefecth_time: 0.0071 BEST_EVAL_ACC: 0.4960, at 10240 iters
[2023-08-15 15:18:26,217 INFO] 10496 iteration USE_EMA: False, train/sup_loss: 0.0154, train/unsup_loss: 0.1985, train/total_loss: 0.2140, train/util_ratio: 0.4246, train/run_time: 0.7513, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 15:21:40,813 INFO] 10752 iteration USE_EMA: False, train/sup_loss: 0.0113, train/unsup_loss: 0.8993, train/total_loss: 0.9106, train/util_ratio: 0.7674, train/run_time: 0.6977, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-15 15:24:54,616 INFO] 11008 iteration USE_EMA: False, train/sup_loss: 0.0139, train/unsup_loss: 1.3281, train/total_loss: 1.3420, train/util_ratio: 0.7475, train/run_time: 0.6966, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 15:28:08,335 INFO] 11264 iteration USE_EMA: False, train/sup_loss: 0.0053, train/unsup_loss: 0.7267, train/total_loss: 0.7320, train/util_ratio: 0.6856, train/run_time: 0.7450, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 15:31:23,509 INFO] 11520 iteration USE_EMA: False, train/sup_loss: 0.1134, train/unsup_loss: 0.8685, train/total_loss: 0.9820, train/util_ratio: 0.8631, train/run_time: 0.7819, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 15:34:38,247 INFO] 11776 iteration USE_EMA: False, train/sup_loss: 0.0250, train/unsup_loss: 0.9387, train/total_loss: 0.9637, train/util_ratio: 0.9710, train/run_time: 0.7337, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 15:37:49,187 INFO] 12032 iteration USE_EMA: False, train/sup_loss: 0.0079, train/unsup_loss: 0.6089, train/total_loss: 0.6168, train/util_ratio: 0.8760, train/run_time: 0.7321, lr: 0.0000, train/prefecth_time: 0.0139 
[2023-08-15 15:41:01,240 INFO] validating...
[2023-08-15 15:41:18,510 INFO] confusion matrix:
[[0.54       0.02       0.10666667 0.14       0.         0.04
  0.01333333 0.02       0.05333333 0.06666667]
 [0.00666667 0.92       0.01333333 0.         0.         0.05333333
  0.00666667 0.         0.         0.        ]
 [0.33333333 0.04666667 0.46666667 0.08       0.         0.01333333
  0.         0.         0.03333333 0.02666667]
 [0.01333333 0.         0.03333333 0.66666667 0.06       0.00666667
  0.02       0.06666667 0.08666667 0.04666667]
 [0.03333333 0.         0.00666667 0.12       0.64       0.
  0.         0.07333333 0.12666667 0.        ]
 [0.10666667 0.10666667 0.00666667 0.01333333 0.02666667 0.69333333
  0.01333333 0.         0.         0.03333333]
 [0.02666667 0.         0.04666667 0.08       0.00666667 0.
  0.57333333 0.02       0.00666667 0.24      ]
 [0.07333333 0.02666667 0.13333333 0.22666667 0.17333333 0.01333333
  0.00666667 0.28       0.05333333 0.01333333]
 [0.08666667 0.         0.02666667 0.10666667 0.06666667 0.02
  0.         0.04666667 0.63333333 0.01333333]
 [0.07333333 0.06       0.35333333 0.22       0.         0.00666667
  0.02       0.07333333 0.02666667 0.16666667]]
[2023-08-15 15:41:20,563 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 15:41:22,451 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 15:41:22,452 INFO] 12288 iteration, USE_EMA: False, train/sup_loss: 0.0165, train/unsup_loss: 0.2229, train/total_loss: 0.2394, train/util_ratio: 0.7275, train/run_time: 0.7232, eval/loss: 2.5183, eval/top-1-acc: 0.5580, eval/balanced_acc: 0.5580, eval/precision: 0.5724, eval/recall: 0.5580, eval/F1: 0.5525, lr: 0.0000, train/prefecth_time: 0.0070 BEST_EVAL_ACC: 0.5580, at 12288 iters
[2023-08-15 15:44:37,928 INFO] 12544 iteration USE_EMA: False, train/sup_loss: 0.0048, train/unsup_loss: 0.2892, train/total_loss: 0.2941, train/util_ratio: 0.7373, train/run_time: 0.7003, lr: 0.0000, train/prefecth_time: 0.0059 
[2023-08-15 15:47:51,931 INFO] 12800 iteration USE_EMA: False, train/sup_loss: 0.0053, train/unsup_loss: 0.3347, train/total_loss: 0.3400, train/util_ratio: 0.5456, train/run_time: 0.7179, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 15:51:05,408 INFO] 13056 iteration USE_EMA: False, train/sup_loss: 0.0114, train/unsup_loss: 0.5216, train/total_loss: 0.5330, train/util_ratio: 0.8644, train/run_time: 0.7337, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 15:54:17,693 INFO] 13312 iteration USE_EMA: False, train/sup_loss: 0.0291, train/unsup_loss: 0.1613, train/total_loss: 0.1904, train/util_ratio: 0.4579, train/run_time: 0.7157, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 15:57:33,400 INFO] 13568 iteration USE_EMA: False, train/sup_loss: 0.0040, train/unsup_loss: 0.1787, train/total_loss: 0.1827, train/util_ratio: 0.5156, train/run_time: 0.7630, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 16:00:48,934 INFO] 13824 iteration USE_EMA: False, train/sup_loss: 0.0042, train/unsup_loss: 0.0873, train/total_loss: 0.0915, train/util_ratio: 0.7524, train/run_time: 0.7019, lr: 0.0000, train/prefecth_time: 0.0053 
[2023-08-15 16:04:03,133 INFO] 14080 iteration USE_EMA: False, train/sup_loss: 0.0049, train/unsup_loss: 0.4749, train/total_loss: 0.4798, train/util_ratio: 0.6648, train/run_time: 0.7166, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 16:07:13,473 INFO] validating...
[2023-08-15 16:07:30,663 INFO] confusion matrix:
[[0.56       0.         0.1        0.02       0.         0.03333333
  0.06666667 0.09333333 0.08666667 0.04      ]
 [0.01333333 0.75333333 0.         0.         0.         0.16
  0.03333333 0.03333333 0.         0.00666667]
 [0.29333333 0.00666667 0.51333333 0.00666667 0.         0.02
  0.02       0.08       0.02       0.04      ]
 [0.05333333 0.         0.09333333 0.18       0.11333333 0.
  0.06       0.3        0.19333333 0.00666667]
 [0.04666667 0.         0.         0.00666667 0.68       0.
  0.         0.05333333 0.21333333 0.        ]
 [0.08       0.02666667 0.00666667 0.         0.02666667 0.76666667
  0.05333333 0.02       0.00666667 0.01333333]
 [0.02       0.         0.04666667 0.00666667 0.02666667 0.
  0.86666667 0.02       0.00666667 0.00666667]
 [0.12666667 0.00666667 0.10666667 0.         0.13333333 0.01333333
  0.02       0.38       0.20666667 0.00666667]
 [0.1        0.         0.03333333 0.01333333 0.04666667 0.01333333
  0.01333333 0.04       0.74       0.        ]
 [0.11333333 0.         0.27333333 0.03333333 0.         0.00666667
  0.2        0.2        0.06666667 0.10666667]]
[2023-08-15 16:07:32,813 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 16:07:32,816 INFO] 14336 iteration, USE_EMA: False, train/sup_loss: 0.0135, train/unsup_loss: 0.6783, train/total_loss: 0.6918, train/util_ratio: 0.7074, train/run_time: 0.7072, eval/loss: 2.4769, eval/top-1-acc: 0.5547, eval/balanced_acc: 0.5547, eval/precision: 0.5792, eval/recall: 0.5547, eval/F1: 0.5337, lr: 0.0000, train/prefecth_time: 0.0034 BEST_EVAL_ACC: 0.5580, at 12288 iters
[2023-08-15 16:10:47,703 INFO] 14592 iteration USE_EMA: False, train/sup_loss: 0.0045, train/unsup_loss: 0.5161, train/total_loss: 0.5206, train/util_ratio: 0.8697, train/run_time: 0.7080, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 16:14:03,384 INFO] 14848 iteration USE_EMA: False, train/sup_loss: 0.0046, train/unsup_loss: 0.6794, train/total_loss: 0.6839, train/util_ratio: 0.8730, train/run_time: 0.7213, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 16:17:17,138 INFO] 15104 iteration USE_EMA: False, train/sup_loss: 0.0042, train/unsup_loss: 0.5278, train/total_loss: 0.5321, train/util_ratio: 0.8750, train/run_time: 0.7269, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 16:20:30,611 INFO] 15360 iteration USE_EMA: False, train/sup_loss: 0.0107, train/unsup_loss: 0.3557, train/total_loss: 0.3664, train/util_ratio: 0.5017, train/run_time: 0.7177, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 16:23:45,614 INFO] 15616 iteration USE_EMA: False, train/sup_loss: 0.0023, train/unsup_loss: 0.6178, train/total_loss: 0.6202, train/util_ratio: 0.7501, train/run_time: 0.7466, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 16:27:00,943 INFO] 15872 iteration USE_EMA: False, train/sup_loss: 0.0032, train/unsup_loss: 0.6364, train/total_loss: 0.6396, train/util_ratio: 0.7002, train/run_time: 0.7366, lr: 0.0000, train/prefecth_time: 0.0069 
[2023-08-15 16:30:29,643 INFO] 16128 iteration USE_EMA: False, train/sup_loss: 0.0042, train/unsup_loss: 0.2553, train/total_loss: 0.2595, train/util_ratio: 0.7502, train/run_time: 0.8281, lr: 0.0000, train/prefecth_time: 0.0057 
[2023-08-15 16:34:17,695 INFO] validating...
[2023-08-15 16:34:34,206 INFO] confusion matrix:
[[0.28666667 0.         0.13333333 0.08       0.03333333 0.06666667
  0.00666667 0.22666667 0.16       0.00666667]
 [0.01333333 0.72       0.01333333 0.         0.         0.15333333
  0.02       0.04       0.         0.04      ]
 [0.13333333 0.         0.57333333 0.10666667 0.00666667 0.02
  0.00666667 0.1        0.04       0.01333333]
 [0.00666667 0.         0.01333333 0.22666667 0.12       0.
  0.00666667 0.58666667 0.04       0.        ]
 [0.02       0.         0.00666667 0.         0.82       0.
  0.         0.12666667 0.02666667 0.        ]
 [0.02       0.02666667 0.03333333 0.         0.04666667 0.72666667
  0.03333333 0.1        0.00666667 0.00666667]
 [0.         0.         0.02       0.04666667 0.02666667 0.
  0.66666667 0.16666667 0.01333333 0.06      ]
 [0.02666667 0.00666667 0.07333333 0.04       0.20666667 0.
  0.         0.61333333 0.02       0.01333333]
 [0.01333333 0.         0.03333333 0.06       0.26       0.00666667
  0.         0.06666667 0.53333333 0.02666667]
 [0.00666667 0.         0.21333333 0.19333333 0.06       0.
  0.03333333 0.34666667 0.05333333 0.09333333]]
[2023-08-15 16:34:36,135 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 16:34:36,136 INFO] 16384 iteration, USE_EMA: False, train/sup_loss: 0.0479, train/unsup_loss: 0.1605, train/total_loss: 0.2084, train/util_ratio: 0.6253, train/run_time: 0.6914, eval/loss: 3.1932, eval/top-1-acc: 0.5260, eval/balanced_acc: 0.5260, eval/precision: 0.5658, eval/recall: 0.5260, eval/F1: 0.5197, lr: 0.0000, train/prefecth_time: 0.0036 BEST_EVAL_ACC: 0.5580, at 12288 iters
[2023-08-15 16:38:23,759 INFO] 16640 iteration USE_EMA: False, train/sup_loss: 0.0040, train/unsup_loss: 1.8844, train/total_loss: 1.8883, train/util_ratio: 0.9995, train/run_time: 0.8987, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 16:42:13,819 INFO] 16896 iteration USE_EMA: False, train/sup_loss: 0.0026, train/unsup_loss: 0.2848, train/total_loss: 0.2874, train/util_ratio: 0.6286, train/run_time: 0.8566, lr: 0.0000, train/prefecth_time: 0.0115 
[2023-08-15 16:46:02,913 INFO] 17152 iteration USE_EMA: False, train/sup_loss: 0.0026, train/unsup_loss: 0.3168, train/total_loss: 0.3194, train/util_ratio: 0.8109, train/run_time: 0.8694, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-15 16:49:49,545 INFO] 17408 iteration USE_EMA: False, train/sup_loss: 0.0075, train/unsup_loss: 0.2975, train/total_loss: 0.3050, train/util_ratio: 0.8751, train/run_time: 0.8667, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 16:53:38,479 INFO] 17664 iteration USE_EMA: False, train/sup_loss: 0.0042, train/unsup_loss: 0.4113, train/total_loss: 0.4156, train/util_ratio: 0.7398, train/run_time: 0.8159, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 16:57:22,090 INFO] 17920 iteration USE_EMA: False, train/sup_loss: 0.0050, train/unsup_loss: 0.3809, train/total_loss: 0.3859, train/util_ratio: 0.7729, train/run_time: 0.7811, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 17:00:47,087 INFO] 18176 iteration USE_EMA: False, train/sup_loss: 0.0035, train/unsup_loss: 0.7241, train/total_loss: 0.7276, train/util_ratio: 0.6122, train/run_time: 0.7607, lr: 0.0000, train/prefecth_time: 0.0052 
[2023-08-15 17:04:08,386 INFO] validating...
[2023-08-15 17:04:23,018 INFO] confusion matrix:
[[0.43333333 0.01333333 0.00666667 0.01333333 0.00666667 0.08
  0.04666667 0.06666667 0.20666667 0.12666667]
 [0.00666667 0.89333333 0.         0.         0.         0.03333333
  0.02       0.02       0.         0.02666667]
 [0.37333333 0.00666667 0.31333333 0.         0.00666667 0.02666667
  0.00666667 0.03333333 0.11333333 0.12      ]
 [0.02666667 0.         0.02       0.19333333 0.17333333 0.00666667
  0.02       0.33333333 0.14       0.08666667]
 [0.03333333 0.         0.         0.01333333 0.9        0.
  0.00666667 0.03333333 0.01333333 0.        ]
 [0.04       0.06666667 0.         0.         0.01333333 0.80666667
  0.02666667 0.02       0.         0.02666667]
 [0.02666667 0.         0.01333333 0.02666667 0.02666667 0.
  0.76666667 0.02       0.00666667 0.11333333]
 [0.08       0.02666667 0.04       0.00666667 0.30666667 0.01333333
  0.01333333 0.41333333 0.08666667 0.01333333]
 [0.06       0.         0.01333333 0.01333333 0.34666667 0.01333333
  0.         0.02666667 0.50666667 0.02      ]
 [0.14666667 0.00666667 0.13333333 0.04666667 0.04666667 0.02
  0.07333333 0.1        0.09333333 0.33333333]]
[2023-08-15 17:04:25,001 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 17:04:25,002 INFO] 18432 iteration, USE_EMA: False, train/sup_loss: 0.0038, train/unsup_loss: 0.1705, train/total_loss: 0.1743, train/util_ratio: 0.7484, train/run_time: 0.7704, eval/loss: 2.4577, eval/top-1-acc: 0.5560, eval/balanced_acc: 0.5560, eval/precision: 0.5720, eval/recall: 0.5560, eval/F1: 0.5421, lr: 0.0000, train/prefecth_time: 0.0076 BEST_EVAL_ACC: 0.5580, at 12288 iters
[2023-08-15 17:07:50,216 INFO] 18688 iteration USE_EMA: False, train/sup_loss: 0.0039, train/unsup_loss: 1.1129, train/total_loss: 1.1167, train/util_ratio: 0.6251, train/run_time: 0.7571, lr: 0.0000, train/prefecth_time: 0.0065 
[2023-08-15 17:11:13,726 INFO] 18944 iteration USE_EMA: False, train/sup_loss: 0.0019, train/unsup_loss: 0.2481, train/total_loss: 0.2500, train/util_ratio: 0.9108, train/run_time: 0.7118, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 17:14:37,577 INFO] 19200 iteration USE_EMA: False, train/sup_loss: 0.0030, train/unsup_loss: 0.3719, train/total_loss: 0.3749, train/util_ratio: 1.0000, train/run_time: 0.7202, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 17:17:59,281 INFO] 19456 iteration USE_EMA: False, train/sup_loss: 0.0034, train/unsup_loss: 0.5339, train/total_loss: 0.5373, train/util_ratio: 0.7451, train/run_time: 0.7399, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 17:21:23,531 INFO] 19712 iteration USE_EMA: False, train/sup_loss: 0.0052, train/unsup_loss: 0.2009, train/total_loss: 0.2061, train/util_ratio: 0.8751, train/run_time: 0.7089, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 17:24:47,737 INFO] 19968 iteration USE_EMA: False, train/sup_loss: 0.0020, train/unsup_loss: 1.3344, train/total_loss: 1.3364, train/util_ratio: 0.7399, train/run_time: 0.7597, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 17:28:13,578 INFO] 20224 iteration USE_EMA: False, train/sup_loss: 0.0052, train/unsup_loss: 0.2654, train/total_loss: 0.2705, train/util_ratio: 0.7863, train/run_time: 0.7826, lr: 0.0000, train/prefecth_time: 0.0075 
[2023-08-15 17:31:35,998 INFO] validating...
[2023-08-15 17:31:50,605 INFO] confusion matrix:
[[0.32666667 0.03333333 0.12666667 0.15333333 0.         0.10666667
  0.02       0.12       0.08666667 0.02666667]
 [0.         0.92666667 0.         0.         0.         0.04666667
  0.01333333 0.01333333 0.         0.        ]
 [0.17333333 0.07333333 0.5        0.04666667 0.         0.03333333
  0.00666667 0.08       0.02666667 0.06      ]
 [0.         0.00666667 0.02666667 0.2        0.10666667 0.00666667
  0.         0.55333333 0.1        0.        ]
 [0.01333333 0.00666667 0.01333333 0.00666667 0.76666667 0.
  0.         0.12       0.07333333 0.        ]
 [0.04       0.08       0.         0.         0.01333333 0.72666667
  0.05333333 0.06       0.         0.02666667]
 [0.         0.         0.01333333 0.08666667 0.00666667 0.
  0.78       0.08       0.01333333 0.02      ]
 [0.02666667 0.04       0.06666667 0.02       0.20666667 0.00666667
  0.00666667 0.58666667 0.01333333 0.02666667]
 [0.02666667 0.         0.06       0.05333333 0.1        0.03333333
  0.00666667 0.06       0.64666667 0.01333333]
 [0.04666667 0.04666667 0.15333333 0.17333333 0.01333333 0.01333333
  0.09333333 0.21333333 0.02666667 0.22      ]]
[2023-08-15 17:31:52,436 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 17:31:54,216 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 17:31:54,217 INFO] 20480 iteration, USE_EMA: False, train/sup_loss: 0.0017, train/unsup_loss: 0.1290, train/total_loss: 0.1307, train/util_ratio: 0.9052, train/run_time: 0.7626, eval/loss: 2.7269, eval/top-1-acc: 0.5680, eval/balanced_acc: 0.5680, eval/precision: 0.5755, eval/recall: 0.5680, eval/F1: 0.5563, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.5680, at 20480 iters
[2023-08-15 17:35:18,700 INFO] 20736 iteration USE_EMA: False, train/sup_loss: 0.0041, train/unsup_loss: 0.4948, train/total_loss: 0.4989, train/util_ratio: 1.0000, train/run_time: 0.8246, lr: 0.0000, train/prefecth_time: 0.0057 
[2023-08-15 17:38:44,596 INFO] 20992 iteration USE_EMA: False, train/sup_loss: 0.0021, train/unsup_loss: 0.6851, train/total_loss: 0.6872, train/util_ratio: 0.8806, train/run_time: 0.7451, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 17:42:10,972 INFO] 21248 iteration USE_EMA: False, train/sup_loss: 0.0084, train/unsup_loss: 0.0200, train/total_loss: 0.0284, train/util_ratio: 0.8677, train/run_time: 0.7197, lr: 0.0000, train/prefecth_time: 0.0051 
[2023-08-15 17:45:38,064 INFO] 21504 iteration USE_EMA: False, train/sup_loss: 0.0037, train/unsup_loss: 0.2496, train/total_loss: 0.2533, train/util_ratio: 0.7843, train/run_time: 0.7480, lr: 0.0000, train/prefecth_time: 0.0054 
[2023-08-15 17:49:02,256 INFO] 21760 iteration USE_EMA: False, train/sup_loss: 0.0120, train/unsup_loss: 0.2226, train/total_loss: 0.2346, train/util_ratio: 0.9010, train/run_time: 0.7554, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 17:52:26,759 INFO] 22016 iteration USE_EMA: False, train/sup_loss: 0.0086, train/unsup_loss: 0.1598, train/total_loss: 0.1684, train/util_ratio: 0.9370, train/run_time: 0.6433, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 17:55:49,899 INFO] 22272 iteration USE_EMA: False, train/sup_loss: 0.0018, train/unsup_loss: 0.4671, train/total_loss: 0.4689, train/util_ratio: 0.7897, train/run_time: 0.7393, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-15 17:59:11,947 INFO] validating...
[2023-08-15 17:59:26,330 INFO] confusion matrix:
[[0.26666667 0.02       0.28       0.14666667 0.         0.03333333
  0.06       0.06       0.08666667 0.04666667]
 [0.00666667 0.9        0.         0.         0.         0.02666667
  0.03333333 0.03333333 0.         0.        ]
 [0.01333333 0.00666667 0.75333333 0.12666667 0.         0.01333333
  0.02666667 0.03333333 0.02       0.00666667]
 [0.         0.         0.03333333 0.52       0.00666667 0.
  0.03333333 0.25333333 0.15333333 0.        ]
 [0.         0.         0.02666667 0.09333333 0.46666667 0.
  0.00666667 0.12       0.28666667 0.        ]
 [0.02666667 0.07333333 0.04       0.02666667 0.         0.68666667
  0.06666667 0.05333333 0.         0.02666667]
 [0.         0.         0.00666667 0.09333333 0.         0.
  0.87333333 0.01333333 0.01333333 0.        ]
 [0.02666667 0.00666667 0.09333333 0.12       0.1        0.
  0.02       0.44666667 0.18       0.00666667]
 [0.00666667 0.         0.09333333 0.06       0.04666667 0.00666667
  0.01333333 0.06       0.7        0.01333333]
 [0.00666667 0.02       0.23333333 0.27333333 0.         0.
  0.20666667 0.11333333 0.06       0.08666667]]
[2023-08-15 17:59:28,239 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 17:59:30,140 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 17:59:30,141 INFO] 22528 iteration, USE_EMA: False, train/sup_loss: 0.0032, train/unsup_loss: 0.4664, train/total_loss: 0.4697, train/util_ratio: 0.8236, train/run_time: 0.7570, eval/loss: 2.9736, eval/top-1-acc: 0.5700, eval/balanced_acc: 0.5700, eval/precision: 0.6078, eval/recall: 0.5700, eval/F1: 0.5508, lr: 0.0000, train/prefecth_time: 0.0041 BEST_EVAL_ACC: 0.5700, at 22528 iters
[2023-08-15 18:02:55,919 INFO] 22784 iteration USE_EMA: False, train/sup_loss: 0.0017, train/unsup_loss: 1.2239, train/total_loss: 1.2255, train/util_ratio: 0.7564, train/run_time: 0.8714, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 18:06:17,541 INFO] 23040 iteration USE_EMA: False, train/sup_loss: 0.0158, train/unsup_loss: 0.0934, train/total_loss: 0.1092, train/util_ratio: 0.8734, train/run_time: 0.7445, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-15 18:09:39,351 INFO] 23296 iteration USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.1264, train/total_loss: 0.1277, train/util_ratio: 0.7355, train/run_time: 0.6884, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 18:13:03,911 INFO] 23552 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.6905, train/total_loss: 0.6917, train/util_ratio: 0.6925, train/run_time: 0.7015, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 18:16:29,612 INFO] 23808 iteration USE_EMA: False, train/sup_loss: 0.0024, train/unsup_loss: 0.2073, train/total_loss: 0.2097, train/util_ratio: 0.6454, train/run_time: 0.7024, lr: 0.0000, train/prefecth_time: 0.0057 
[2023-08-15 18:19:53,870 INFO] 24064 iteration USE_EMA: False, train/sup_loss: 0.0020, train/unsup_loss: 0.1471, train/total_loss: 0.1491, train/util_ratio: 0.7500, train/run_time: 0.7612, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-15 18:23:16,949 INFO] 24320 iteration USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.1083, train/total_loss: 0.1098, train/util_ratio: 0.6891, train/run_time: 0.7986, lr: 0.0000, train/prefecth_time: 0.0055 
[2023-08-15 18:26:43,118 INFO] validating...
[2023-08-15 18:26:57,636 INFO] confusion matrix:
[[0.42666667 0.00666667 0.11333333 0.04       0.         0.05333333
  0.03333333 0.14666667 0.08       0.1       ]
 [0.00666667 0.84       0.         0.         0.         0.11333333
  0.00666667 0.02       0.         0.01333333]
 [0.2        0.01333333 0.47333333 0.02666667 0.         0.02666667
  0.00666667 0.11333333 0.00666667 0.13333333]
 [0.         0.         0.01333333 0.22666667 0.00666667 0.01333333
  0.03333333 0.56666667 0.12       0.02      ]
 [0.02666667 0.         0.         0.08666667 0.22       0.
  0.         0.11333333 0.55333333 0.        ]
 [0.04666667 0.04666667 0.         0.01333333 0.         0.82666667
  0.02       0.04       0.         0.00666667]
 [0.02       0.         0.00666667 0.01333333 0.         0.
  0.76       0.09333333 0.         0.10666667]
 [0.04666667 0.00666667 0.04666667 0.02666667 0.00666667 0.01333333
  0.02       0.58       0.21333333 0.04      ]
 [0.05333333 0.         0.02       0.06666667 0.00666667 0.02666667
  0.         0.08666667 0.72       0.02      ]
 [0.07333333 0.01333333 0.10666667 0.07333333 0.         0.02
  0.06666667 0.28666667 0.06666667 0.29333333]]
[2023-08-15 18:26:59,497 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 18:26:59,498 INFO] 24576 iteration, USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.4681, train/total_loss: 0.4694, train/util_ratio: 0.7498, train/run_time: 0.7586, eval/loss: 3.3880, eval/top-1-acc: 0.5367, eval/balanced_acc: 0.5367, eval/precision: 0.5951, eval/recall: 0.5367, eval/F1: 0.5307, lr: 0.0000, train/prefecth_time: 0.0070 BEST_EVAL_ACC: 0.5700, at 22528 iters
[2023-08-15 18:30:28,084 INFO] 24832 iteration USE_EMA: False, train/sup_loss: 0.0023, train/unsup_loss: 0.1492, train/total_loss: 0.1515, train/util_ratio: 0.8545, train/run_time: 0.7496, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 18:33:53,079 INFO] 25088 iteration USE_EMA: False, train/sup_loss: 0.0020, train/unsup_loss: 0.1036, train/total_loss: 0.1055, train/util_ratio: 0.7500, train/run_time: 0.7584, lr: 0.0000, train/prefecth_time: 0.0047 
[2023-08-15 18:37:14,240 INFO] 25344 iteration USE_EMA: False, train/sup_loss: 0.0018, train/unsup_loss: 0.8439, train/total_loss: 0.8457, train/util_ratio: 0.6370, train/run_time: 0.7537, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 18:40:40,059 INFO] 25600 iteration USE_EMA: False, train/sup_loss: 0.0018, train/unsup_loss: 0.6639, train/total_loss: 0.6657, train/util_ratio: 1.0000, train/run_time: 0.7554, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 18:44:05,300 INFO] 25856 iteration USE_EMA: False, train/sup_loss: 0.0022, train/unsup_loss: 0.3633, train/total_loss: 0.3655, train/util_ratio: 1.0000, train/run_time: 0.7473, lr: 0.0000, train/prefecth_time: 0.0075 
[2023-08-15 18:47:31,206 INFO] 26112 iteration USE_EMA: False, train/sup_loss: 0.0232, train/unsup_loss: 0.1658, train/total_loss: 0.1889, train/util_ratio: 0.5683, train/run_time: 0.7686, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 18:50:57,251 INFO] 26368 iteration USE_EMA: False, train/sup_loss: 0.0147, train/unsup_loss: 0.5983, train/total_loss: 0.6130, train/util_ratio: 0.8772, train/run_time: 0.7516, lr: 0.0000, train/prefecth_time: 0.0061 
[2023-08-15 18:54:20,694 INFO] validating...
[2023-08-15 18:54:35,230 INFO] confusion matrix:
[[0.35333333 0.01333333 0.24666667 0.08666667 0.         0.03333333
  0.00666667 0.04666667 0.2        0.01333333]
 [0.00666667 0.88666667 0.02666667 0.         0.         0.06
  0.00666667 0.         0.         0.01333333]
 [0.11333333 0.01333333 0.73333333 0.02666667 0.         0.01333333
  0.         0.         0.1        0.        ]
 [0.00666667 0.00666667 0.10666667 0.52666667 0.07333333 0.
  0.01333333 0.13333333 0.12666667 0.00666667]
 [0.01333333 0.00666667 0.01333333 0.04       0.65333333 0.00666667
  0.         0.06       0.20666667 0.        ]
 [0.04       0.05333333 0.03333333 0.00666667 0.         0.78
  0.00666667 0.05333333 0.02       0.00666667]
 [0.02       0.         0.14       0.06       0.03333333 0.
  0.71333333 0.00666667 0.01333333 0.01333333]
 [0.02666667 0.02666667 0.18       0.04       0.15333333 0.
  0.00666667 0.48666667 0.08       0.        ]
 [0.04666667 0.         0.05333333 0.02666667 0.05333333 0.00666667
  0.         0.06       0.74666667 0.00666667]
 [0.03333333 0.00666667 0.59333333 0.12666667 0.00666667 0.00666667
  0.05333333 0.06       0.09333333 0.02      ]]
[2023-08-15 18:54:37,408 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 18:54:39,421 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 18:54:39,423 INFO] 26624 iteration, USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.1673, train/total_loss: 0.1688, train/util_ratio: 0.9901, train/run_time: 0.7769, eval/loss: 2.6279, eval/top-1-acc: 0.5900, eval/balanced_acc: 0.5900, eval/precision: 0.5989, eval/recall: 0.5900, eval/F1: 0.5713, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.5900, at 26624 iters
[2023-08-15 18:58:07,262 INFO] 26880 iteration USE_EMA: False, train/sup_loss: 0.0019, train/unsup_loss: 0.1088, train/total_loss: 0.1107, train/util_ratio: 1.0000, train/run_time: 0.7636, lr: 0.0000, train/prefecth_time: 0.0067 
[2023-08-15 19:01:31,391 INFO] 27136 iteration USE_EMA: False, train/sup_loss: 0.1119, train/unsup_loss: 1.0737, train/total_loss: 1.1856, train/util_ratio: 0.3807, train/run_time: 0.7781, lr: 0.0000, train/prefecth_time: 0.0055 
[2023-08-15 19:04:56,596 INFO] 27392 iteration USE_EMA: False, train/sup_loss: 0.0017, train/unsup_loss: 0.3150, train/total_loss: 0.3167, train/util_ratio: 1.0000, train/run_time: 0.8065, lr: 0.0000, train/prefecth_time: 0.0127 
[2023-08-15 19:08:19,570 INFO] 27648 iteration USE_EMA: False, train/sup_loss: 0.0018, train/unsup_loss: 0.6133, train/total_loss: 0.6152, train/util_ratio: 0.7808, train/run_time: 0.7742, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-15 19:11:46,480 INFO] 27904 iteration USE_EMA: False, train/sup_loss: 0.0031, train/unsup_loss: 0.4630, train/total_loss: 0.4661, train/util_ratio: 0.7808, train/run_time: 0.6880, lr: 0.0000, train/prefecth_time: 0.0069 
[2023-08-15 19:15:11,273 INFO] 28160 iteration USE_EMA: False, train/sup_loss: 0.0173, train/unsup_loss: 0.3523, train/total_loss: 0.3696, train/util_ratio: 0.7414, train/run_time: 0.6952, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 19:18:35,902 INFO] 28416 iteration USE_EMA: False, train/sup_loss: 0.0016, train/unsup_loss: 0.1779, train/total_loss: 0.1795, train/util_ratio: 0.7124, train/run_time: 0.7256, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 19:21:59,050 INFO] validating...
[2023-08-15 19:22:13,576 INFO] confusion matrix:
[[0.18666667 0.01333333 0.14       0.15333333 0.         0.1
  0.09333333 0.06       0.16666667 0.08666667]
 [0.00666667 0.90666667 0.         0.         0.         0.06666667
  0.00666667 0.00666667 0.         0.00666667]
 [0.06       0.02       0.60666667 0.14       0.         0.02
  0.         0.04666667 0.06666667 0.04      ]
 [0.         0.         0.04       0.64666667 0.05333333 0.00666667
  0.04       0.14666667 0.04666667 0.02      ]
 [0.00666667 0.         0.01333333 0.14       0.62666667 0.01333333
  0.01333333 0.08666667 0.1        0.        ]
 [0.00666667 0.06       0.02       0.         0.         0.84666667
  0.02       0.02666667 0.01333333 0.00666667]
 [0.01333333 0.         0.00666667 0.07333333 0.         0.
  0.80666667 0.05333333 0.         0.04666667]
 [0.01333333 0.00666667 0.1        0.19333333 0.1        0.00666667
  0.01333333 0.49333333 0.02       0.05333333]
 [0.01333333 0.         0.08666667 0.18666667 0.06       0.02666667
  0.         0.03333333 0.58666667 0.00666667]
 [0.00666667 0.04666667 0.2        0.26666667 0.         0.00666667
  0.12666667 0.09333333 0.05333333 0.2       ]]
[2023-08-15 19:22:15,553 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 19:22:17,365 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 19:22:17,366 INFO] 28672 iteration, USE_EMA: False, train/sup_loss: 0.0020, train/unsup_loss: 0.8311, train/total_loss: 0.8331, train/util_ratio: 0.8719, train/run_time: 0.7289, eval/loss: 2.6200, eval/top-1-acc: 0.5907, eval/balanced_acc: 0.5907, eval/precision: 0.6013, eval/recall: 0.5907, eval/F1: 0.5755, lr: 0.0000, train/prefecth_time: 0.0055 BEST_EVAL_ACC: 0.5907, at 28672 iters
[2023-08-15 19:25:45,747 INFO] 28928 iteration USE_EMA: False, train/sup_loss: 0.0020, train/unsup_loss: 1.0640, train/total_loss: 1.0660, train/util_ratio: 0.7789, train/run_time: 0.7698, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-15 19:29:11,482 INFO] 29184 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.5857, train/total_loss: 0.5867, train/util_ratio: 0.8399, train/run_time: 0.8057, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 19:32:37,816 INFO] 29440 iteration USE_EMA: False, train/sup_loss: 0.0021, train/unsup_loss: 0.7745, train/total_loss: 0.7765, train/util_ratio: 0.8752, train/run_time: 0.6980, lr: 0.0000, train/prefecth_time: 0.0045 
[2023-08-15 19:36:02,286 INFO] 29696 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.1856, train/total_loss: 0.1868, train/util_ratio: 0.7538, train/run_time: 0.7038, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 19:39:27,059 INFO] 29952 iteration USE_EMA: False, train/sup_loss: 0.0031, train/unsup_loss: 0.2072, train/total_loss: 0.2103, train/util_ratio: 0.8526, train/run_time: 0.7865, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 19:42:52,283 INFO] 30208 iteration USE_EMA: False, train/sup_loss: 0.0394, train/unsup_loss: 0.1185, train/total_loss: 0.1579, train/util_ratio: 0.9994, train/run_time: 0.7065, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 19:46:16,117 INFO] 30464 iteration USE_EMA: False, train/sup_loss: 0.0027, train/unsup_loss: 0.3959, train/total_loss: 0.3986, train/util_ratio: 0.6762, train/run_time: 0.7937, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-15 19:49:39,957 INFO] validating...
[2023-08-15 19:49:54,574 INFO] confusion matrix:
[[0.41333333 0.01333333 0.04       0.20666667 0.         0.00666667
  0.08666667 0.05333333 0.10666667 0.07333333]
 [0.         0.88666667 0.         0.         0.         0.06
  0.00666667 0.01333333 0.         0.03333333]
 [0.15333333 0.00666667 0.26       0.18666667 0.         0.00666667
  0.01333333 0.02       0.01333333 0.34      ]
 [0.00666667 0.         0.00666667 0.59333333 0.09333333 0.
  0.01333333 0.22       0.04666667 0.02      ]
 [0.01333333 0.         0.         0.06       0.83333333 0.
  0.         0.06       0.02666667 0.00666667]
 [0.05333333 0.04       0.         0.00666667 0.01333333 0.79333333
  0.02       0.04       0.         0.03333333]
 [0.02       0.         0.         0.08666667 0.01333333 0.
  0.81333333 0.02666667 0.         0.04      ]
 [0.04       0.00666667 0.04666667 0.18       0.20666667 0.
  0.00666667 0.38       0.01333333 0.12      ]
 [0.04666667 0.         0.01333333 0.17333333 0.14666667 0.01333333
  0.00666667 0.02666667 0.54666667 0.02666667]
 [0.02       0.01333333 0.07333333 0.29333333 0.02       0.
  0.13333333 0.09333333 0.04       0.31333333]]
[2023-08-15 19:49:56,479 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 19:49:56,481 INFO] 30720 iteration, USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.6401, train/total_loss: 0.6412, train/util_ratio: 0.6277, train/run_time: 0.7949, eval/loss: 2.8138, eval/top-1-acc: 0.5833, eval/balanced_acc: 0.5833, eval/precision: 0.6056, eval/recall: 0.5833, eval/F1: 0.5807, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.5907, at 28672 iters
[2023-08-15 19:53:22,981 INFO] 30976 iteration USE_EMA: False, train/sup_loss: 0.0035, train/unsup_loss: 0.4612, train/total_loss: 0.4648, train/util_ratio: 0.7573, train/run_time: 0.7618, lr: 0.0000, train/prefecth_time: 0.0048 
[2023-08-15 19:56:47,047 INFO] 31232 iteration USE_EMA: False, train/sup_loss: 0.0039, train/unsup_loss: 0.9278, train/total_loss: 0.9316, train/util_ratio: 1.0000, train/run_time: 0.7609, lr: 0.0000, train/prefecth_time: 0.0075 
[2023-08-15 20:00:10,865 INFO] 31488 iteration USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.2612, train/total_loss: 0.2625, train/util_ratio: 0.9191, train/run_time: 0.7618, lr: 0.0000, train/prefecth_time: 0.0075 
[2023-08-15 20:03:37,007 INFO] 31744 iteration USE_EMA: False, train/sup_loss: 0.0016, train/unsup_loss: 0.0344, train/total_loss: 0.0360, train/util_ratio: 1.0000, train/run_time: 0.7588, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 20:07:02,447 INFO] 32000 iteration USE_EMA: False, train/sup_loss: 0.0059, train/unsup_loss: 0.1503, train/total_loss: 0.1563, train/util_ratio: 0.6533, train/run_time: 0.7363, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-15 20:10:26,880 INFO] 32256 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.1366, train/total_loss: 0.1374, train/util_ratio: 0.6338, train/run_time: 0.7523, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-15 20:13:51,594 INFO] 32512 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.7285, train/total_loss: 0.7292, train/util_ratio: 0.7829, train/run_time: 0.7815, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 20:17:16,217 INFO] validating...
[2023-08-15 20:17:30,957 INFO] confusion matrix:
[[0.43333333 0.02       0.12       0.15333333 0.         0.02
  0.19333333 0.         0.05333333 0.00666667]
 [0.         0.9        0.         0.00666667 0.         0.04
  0.04       0.         0.         0.01333333]
 [0.13333333 0.00666667 0.62       0.10666667 0.         0.00666667
  0.09333333 0.         0.00666667 0.02666667]
 [0.00666667 0.         0.02       0.64       0.07333333 0.00666667
  0.21333333 0.         0.03333333 0.00666667]
 [0.02666667 0.         0.00666667 0.10666667 0.75333333 0.
  0.02666667 0.03333333 0.04666667 0.        ]
 [0.06666667 0.07333333 0.01333333 0.00666667 0.         0.73333333
  0.09333333 0.         0.         0.01333333]
 [0.         0.         0.         0.02666667 0.         0.
  0.97333333 0.         0.         0.        ]
 [0.04666667 0.01333333 0.15333333 0.21333333 0.16666667 0.
  0.14       0.22666667 0.         0.04      ]
 [0.06       0.         0.03333333 0.11333333 0.11333333 0.01333333
  0.05333333 0.04       0.57333333 0.        ]
 [0.04       0.00666667 0.21333333 0.16666667 0.01333333 0.00666667
  0.45333333 0.00666667 0.02       0.07333333]]
[2023-08-15 20:17:32,938 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 20:17:34,814 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 20:17:34,816 INFO] 32768 iteration, USE_EMA: False, train/sup_loss: 0.3326, train/unsup_loss: 0.5834, train/total_loss: 0.9160, train/util_ratio: 0.8711, train/run_time: 0.7302, eval/loss: 2.2386, eval/top-1-acc: 0.5927, eval/balanced_acc: 0.5927, eval/precision: 0.6271, eval/recall: 0.5927, eval/F1: 0.5682, lr: 0.0000, train/prefecth_time: 0.0070 BEST_EVAL_ACC: 0.5927, at 32768 iters
[2023-08-15 20:21:00,257 INFO] 33024 iteration USE_EMA: False, train/sup_loss: 0.0317, train/unsup_loss: 0.2022, train/total_loss: 0.2339, train/util_ratio: 0.7623, train/run_time: 0.7199, lr: 0.0000, train/prefecth_time: 0.0069 
[2023-08-15 20:24:25,485 INFO] 33280 iteration USE_EMA: False, train/sup_loss: 0.0183, train/unsup_loss: 0.5058, train/total_loss: 0.5242, train/util_ratio: 0.8785, train/run_time: 0.7013, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 20:27:51,595 INFO] 33536 iteration USE_EMA: False, train/sup_loss: 0.0018, train/unsup_loss: 1.0465, train/total_loss: 1.0483, train/util_ratio: 0.7941, train/run_time: 0.7986, lr: 0.0000, train/prefecth_time: 0.0055 
[2023-08-15 20:31:15,310 INFO] 33792 iteration USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.4615, train/total_loss: 0.4631, train/util_ratio: 0.8432, train/run_time: 0.7422, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-15 20:34:40,133 INFO] 34048 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.0306, train/total_loss: 0.0316, train/util_ratio: 0.7500, train/run_time: 0.8400, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 20:38:02,827 INFO] 34304 iteration USE_EMA: False, train/sup_loss: 0.0038, train/unsup_loss: 0.1882, train/total_loss: 0.1920, train/util_ratio: 0.7750, train/run_time: 0.6376, lr: 0.0000, train/prefecth_time: 0.0094 
[2023-08-15 20:41:29,857 INFO] 34560 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.3584, train/total_loss: 0.3593, train/util_ratio: 0.8612, train/run_time: 0.7590, lr: 0.0000, train/prefecth_time: 0.0053 
[2023-08-15 20:44:53,110 INFO] validating...
[2023-08-15 20:45:07,709 INFO] confusion matrix:
[[0.41333333 0.02666667 0.36666667 0.08       0.         0.00666667
  0.02666667 0.05333333 0.00666667 0.02      ]
 [0.         0.91333333 0.         0.         0.         0.08
  0.00666667 0.         0.         0.        ]
 [0.07333333 0.01333333 0.78666667 0.02666667 0.         0.01333333
  0.00666667 0.04666667 0.         0.03333333]
 [0.         0.00666667 0.07333333 0.48       0.04       0.
  0.00666667 0.34       0.04666667 0.00666667]
 [0.         0.         0.03333333 0.06       0.71333333 0.
  0.         0.12666667 0.05333333 0.01333333]
 [0.02666667 0.04666667 0.02       0.         0.00666667 0.85333333
  0.01333333 0.02666667 0.         0.00666667]
 [0.01333333 0.         0.02666667 0.06666667 0.01333333 0.
  0.82666667 0.03333333 0.         0.02      ]
 [0.02666667 0.00666667 0.11333333 0.00666667 0.07333333 0.00666667
  0.00666667 0.73333333 0.         0.02666667]
 [0.03333333 0.         0.19333333 0.00666667 0.07333333 0.02
  0.00666667 0.11333333 0.54666667 0.00666667]
 [0.03333333 0.03333333 0.36666667 0.12666667 0.         0.00666667
  0.11333333 0.15333333 0.02       0.14666667]]
[2023-08-15 20:45:09,596 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 20:45:11,623 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 20:45:11,624 INFO] 34816 iteration, USE_EMA: False, train/sup_loss: 0.0021, train/unsup_loss: 0.3091, train/total_loss: 0.3112, train/util_ratio: 0.8754, train/run_time: 0.7325, eval/loss: 2.0982, eval/top-1-acc: 0.6413, eval/balanced_acc: 0.6413, eval/precision: 0.6742, eval/recall: 0.6413, eval/F1: 0.6313, lr: 0.0000, train/prefecth_time: 0.0070 BEST_EVAL_ACC: 0.6413, at 34816 iters
[2023-08-15 20:48:38,007 INFO] 35072 iteration USE_EMA: False, train/sup_loss: 0.0020, train/unsup_loss: 0.2771, train/total_loss: 0.2790, train/util_ratio: 1.0000, train/run_time: 0.8265, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-15 20:52:02,492 INFO] 35328 iteration USE_EMA: False, train/sup_loss: 0.0019, train/unsup_loss: 0.5526, train/total_loss: 0.5545, train/util_ratio: 0.6907, train/run_time: 0.7727, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-15 20:55:26,186 INFO] 35584 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.6872, train/total_loss: 0.6879, train/util_ratio: 0.7536, train/run_time: 0.7817, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 20:58:50,467 INFO] 35840 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.2505, train/total_loss: 0.2511, train/util_ratio: 0.7773, train/run_time: 0.7772, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-15 21:02:15,641 INFO] 36096 iteration USE_EMA: False, train/sup_loss: 0.0029, train/unsup_loss: 0.4750, train/total_loss: 0.4779, train/util_ratio: 0.4882, train/run_time: 0.7790, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 21:05:40,100 INFO] 36352 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.0166, train/total_loss: 0.0174, train/util_ratio: 0.8750, train/run_time: 0.8290, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-15 21:09:03,752 INFO] 36608 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.2428, train/total_loss: 0.2435, train/util_ratio: 1.0000, train/run_time: 0.7877, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-15 21:12:26,537 INFO] validating...
[2023-08-15 21:12:41,157 INFO] confusion matrix:
[[0.36       0.01333333 0.26       0.07333333 0.         0.05333333
  0.         0.04666667 0.09333333 0.1       ]
 [0.         0.89333333 0.         0.         0.         0.06
  0.00666667 0.00666667 0.         0.03333333]
 [0.09333333 0.00666667 0.74       0.02666667 0.         0.04
  0.         0.02       0.00666667 0.06666667]
 [0.         0.         0.08       0.51333333 0.05333333 0.
  0.01333333 0.22666667 0.06       0.05333333]
 [0.00666667 0.         0.01333333 0.06666667 0.78       0.00666667
  0.00666667 0.08666667 0.02       0.01333333]
 [0.02666667 0.04       0.02666667 0.         0.         0.9
  0.         0.         0.         0.00666667]
 [0.02       0.         0.02666667 0.04       0.         0.07333333
  0.74       0.         0.         0.1       ]
 [0.03333333 0.01333333 0.18666667 0.04       0.13333333 0.
  0.00666667 0.50666667 0.00666667 0.07333333]
 [0.04666667 0.         0.10666667 0.02666667 0.10666667 0.02
  0.00666667 0.04666667 0.64       0.        ]
 [0.04666667 0.00666667 0.28666667 0.09333333 0.01333333 0.06666667
  0.05333333 0.07333333 0.02666667 0.33333333]]
[2023-08-15 21:12:43,168 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 21:12:43,169 INFO] 36864 iteration, USE_EMA: False, train/sup_loss: 0.0081, train/unsup_loss: 0.8166, train/total_loss: 0.8246, train/util_ratio: 0.8117, train/run_time: 0.8108, eval/loss: 2.2454, eval/top-1-acc: 0.6407, eval/balanced_acc: 0.6407, eval/precision: 0.6519, eval/recall: 0.6407, eval/F1: 0.6369, lr: 0.0000, train/prefecth_time: 0.0055 BEST_EVAL_ACC: 0.6413, at 34816 iters
[2023-08-15 21:16:08,373 INFO] 37120 iteration USE_EMA: False, train/sup_loss: 0.0255, train/unsup_loss: 0.0927, train/total_loss: 0.1182, train/util_ratio: 0.6281, train/run_time: 0.7269, lr: 0.0000, train/prefecth_time: 0.0045 
[2023-08-15 21:19:30,280 INFO] 37376 iteration USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.4892, train/total_loss: 0.4903, train/util_ratio: 0.7450, train/run_time: 0.7512, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 21:22:54,403 INFO] 37632 iteration USE_EMA: False, train/sup_loss: 0.0017, train/unsup_loss: 0.1460, train/total_loss: 0.1477, train/util_ratio: 0.8751, train/run_time: 0.8160, lr: 0.0000, train/prefecth_time: 0.0051 
[2023-08-15 21:26:17,724 INFO] 37888 iteration USE_EMA: False, train/sup_loss: 0.0027, train/unsup_loss: 0.2068, train/total_loss: 0.2096, train/util_ratio: 0.8752, train/run_time: 0.7660, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-15 21:29:42,270 INFO] 38144 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.2893, train/total_loss: 0.2903, train/util_ratio: 0.9192, train/run_time: 0.7508, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-15 21:33:05,415 INFO] 38400 iteration USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.6088, train/total_loss: 0.6101, train/util_ratio: 0.8690, train/run_time: 0.7271, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 21:36:28,473 INFO] 38656 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.0233, train/total_loss: 0.0245, train/util_ratio: 0.7616, train/run_time: 0.8094, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-15 21:39:50,291 INFO] validating...
[2023-08-15 21:40:05,051 INFO] confusion matrix:
[[0.56666667 0.01333333 0.02666667 0.11333333 0.         0.00666667
  0.05333333 0.06666667 0.10666667 0.04666667]
 [0.00666667 0.90666667 0.         0.         0.         0.04666667
  0.00666667 0.00666667 0.         0.02666667]
 [0.29333333 0.01333333 0.42666667 0.08666667 0.         0.01333333
  0.00666667 0.04       0.01333333 0.10666667]
 [0.02       0.         0.00666667 0.56666667 0.06666667 0.
  0.03333333 0.21333333 0.08       0.01333333]
 [0.04666667 0.         0.         0.06666667 0.72666667 0.
  0.00666667 0.08       0.06666667 0.00666667]
 [0.06       0.04       0.         0.         0.         0.84666667
  0.02666667 0.01333333 0.         0.01333333]
 [0.02666667 0.         0.         0.03333333 0.         0.
  0.9        0.00666667 0.00666667 0.02666667]
 [0.06666667 0.00666667 0.03333333 0.02       0.12       0.
  0.03333333 0.66666667 0.02       0.03333333]
 [0.06666667 0.         0.         0.02       0.07333333 0.01333333
  0.00666667 0.08666667 0.72666667 0.00666667]
 [0.09333333 0.00666667 0.1        0.12666667 0.         0.02666667
  0.19333333 0.14666667 0.08       0.22666667]]
[2023-08-15 21:40:06,852 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 21:40:08,655 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 21:40:08,656 INFO] 38912 iteration, USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.3958, train/total_loss: 0.3971, train/util_ratio: 0.8888, train/run_time: 0.7417, eval/loss: 2.1837, eval/top-1-acc: 0.6560, eval/balanced_acc: 0.6560, eval/precision: 0.6587, eval/recall: 0.6560, eval/F1: 0.6469, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.6560, at 38912 iters
[2023-08-15 21:43:34,724 INFO] 39168 iteration USE_EMA: False, train/sup_loss: 0.0020, train/unsup_loss: 0.5218, train/total_loss: 0.5238, train/util_ratio: 0.6569, train/run_time: 0.8353, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 21:46:57,147 INFO] 39424 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.0507, train/total_loss: 0.0513, train/util_ratio: 0.8288, train/run_time: 0.7414, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 21:50:21,870 INFO] 39680 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.1623, train/total_loss: 0.1629, train/util_ratio: 0.8457, train/run_time: 0.7389, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 21:53:46,159 INFO] 39936 iteration USE_EMA: False, train/sup_loss: 0.0065, train/unsup_loss: 0.2767, train/total_loss: 0.2832, train/util_ratio: 0.7501, train/run_time: 0.7451, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 21:57:10,406 INFO] 40192 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.1205, train/total_loss: 0.1213, train/util_ratio: 0.7535, train/run_time: 0.7602, lr: 0.0000, train/prefecth_time: 0.0054 
[2023-08-15 22:00:36,222 INFO] 40448 iteration USE_EMA: False, train/sup_loss: 0.0025, train/unsup_loss: 0.0140, train/total_loss: 0.0165, train/util_ratio: 1.0000, train/run_time: 0.7086, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 22:03:58,638 INFO] 40704 iteration USE_EMA: False, train/sup_loss: 0.0149, train/unsup_loss: 0.1258, train/total_loss: 0.1407, train/util_ratio: 0.6293, train/run_time: 0.7636, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 22:07:22,855 INFO] validating...
[2023-08-15 22:07:37,316 INFO] confusion matrix:
[[0.44       0.         0.02       0.06       0.04       0.07333333
  0.08666667 0.06       0.11333333 0.10666667]
 [0.         0.76       0.         0.         0.         0.17333333
  0.02       0.00666667 0.         0.04      ]
 [0.18       0.00666667 0.56666667 0.06       0.         0.02666667
  0.04       0.04666667 0.00666667 0.06666667]
 [0.00666667 0.         0.01333333 0.34       0.10666667 0.02
  0.04666667 0.37333333 0.06666667 0.02666667]
 [0.02       0.         0.         0.02666667 0.81333333 0.
  0.00666667 0.08666667 0.03333333 0.01333333]
 [0.03333333 0.02       0.00666667 0.         0.01333333 0.85333333
  0.02666667 0.02666667 0.         0.02      ]
 [0.         0.         0.         0.00666667 0.03333333 0.
  0.92       0.00666667 0.         0.03333333]
 [0.06       0.00666667 0.03333333 0.00666667 0.24       0.
  0.01333333 0.54666667 0.02666667 0.06666667]
 [0.06       0.         0.01333333 0.01333333 0.10666667 0.02666667
  0.00666667 0.08       0.69333333 0.        ]
 [0.05333333 0.         0.14       0.05333333 0.06666667 0.
  0.19333333 0.15333333 0.04666667 0.29333333]]
[2023-08-15 22:07:39,385 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 22:07:39,386 INFO] 40960 iteration, USE_EMA: False, train/sup_loss: 0.0085, train/unsup_loss: 0.1565, train/total_loss: 0.1650, train/util_ratio: 0.6339, train/run_time: 0.7712, eval/loss: 2.2860, eval/top-1-acc: 0.6227, eval/balanced_acc: 0.6227, eval/precision: 0.6301, eval/recall: 0.6227, eval/F1: 0.6134, lr: 0.0000, train/prefecth_time: 0.0041 BEST_EVAL_ACC: 0.6560, at 38912 iters
[2023-08-15 22:11:05,009 INFO] 41216 iteration USE_EMA: False, train/sup_loss: 0.0062, train/unsup_loss: 0.2835, train/total_loss: 0.2897, train/util_ratio: 0.9152, train/run_time: 0.7783, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 22:14:28,655 INFO] 41472 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.7769, train/total_loss: 0.7778, train/util_ratio: 0.8106, train/run_time: 0.7477, lr: 0.0000, train/prefecth_time: 0.0047 
[2023-08-15 22:17:55,533 INFO] 41728 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.3937, train/total_loss: 0.3947, train/util_ratio: 0.8750, train/run_time: 0.8127, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-15 22:21:18,963 INFO] 41984 iteration USE_EMA: False, train/sup_loss: 0.0030, train/unsup_loss: 0.1569, train/total_loss: 0.1599, train/util_ratio: 0.9885, train/run_time: 0.7889, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-15 22:24:45,244 INFO] 42240 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.0888, train/total_loss: 0.0898, train/util_ratio: 0.9329, train/run_time: 0.7791, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 22:28:08,518 INFO] 42496 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.1940, train/total_loss: 0.1951, train/util_ratio: 0.7516, train/run_time: 0.7400, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 22:31:33,575 INFO] 42752 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.3054, train/total_loss: 0.3058, train/util_ratio: 0.7758, train/run_time: 0.7485, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 22:34:58,335 INFO] validating...
[2023-08-15 22:35:12,920 INFO] confusion matrix:
[[0.52666667 0.         0.14666667 0.14666667 0.         0.03333333
  0.         0.00666667 0.08666667 0.05333333]
 [0.         0.82666667 0.         0.00666667 0.         0.13333333
  0.00666667 0.02       0.         0.00666667]
 [0.12       0.01333333 0.72       0.09333333 0.         0.01333333
  0.         0.         0.01333333 0.02666667]
 [0.01333333 0.         0.01333333 0.81333333 0.04       0.
  0.         0.03333333 0.06666667 0.02      ]
 [0.02666667 0.         0.         0.06666667 0.78666667 0.
  0.         0.05333333 0.06666667 0.        ]
 [0.06666667 0.01333333 0.02666667 0.03333333 0.         0.80666667
  0.00666667 0.02666667 0.         0.02      ]
 [0.00666667 0.         0.04       0.13333333 0.         0.
  0.60666667 0.         0.00666667 0.20666667]
 [0.06666667 0.00666667 0.12666667 0.08666667 0.22666667 0.
  0.         0.41333333 0.02666667 0.04666667]
 [0.06       0.         0.04       0.04666667 0.09333333 0.01333333
  0.00666667 0.02       0.71333333 0.00666667]
 [0.06666667 0.         0.25333333 0.19333333 0.02       0.00666667
  0.04       0.03333333 0.05333333 0.33333333]]
[2023-08-15 22:35:15,234 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 22:35:15,237 INFO] 43008 iteration, USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.3589, train/total_loss: 0.3593, train/util_ratio: 0.8751, train/run_time: 0.7914, eval/loss: 2.3859, eval/top-1-acc: 0.6547, eval/balanced_acc: 0.6547, eval/precision: 0.6763, eval/recall: 0.6547, eval/F1: 0.6519, lr: 0.0000, train/prefecth_time: 0.0117 BEST_EVAL_ACC: 0.6560, at 38912 iters
[2023-08-15 22:38:40,901 INFO] 43264 iteration USE_EMA: False, train/sup_loss: 0.0019, train/unsup_loss: 0.0572, train/total_loss: 0.0591, train/util_ratio: 0.7461, train/run_time: 0.7270, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 22:42:05,635 INFO] 43520 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.1480, train/total_loss: 0.1487, train/util_ratio: 0.7630, train/run_time: 0.7793, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 22:45:28,439 INFO] 43776 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.1943, train/total_loss: 0.1947, train/util_ratio: 0.6100, train/run_time: 0.7752, lr: 0.0000, train/prefecth_time: 0.0055 
[2023-08-15 22:48:53,085 INFO] 44032 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.0674, train/total_loss: 0.0680, train/util_ratio: 0.6264, train/run_time: 0.7599, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 22:52:19,654 INFO] 44288 iteration USE_EMA: False, train/sup_loss: 0.0021, train/unsup_loss: 0.1651, train/total_loss: 0.1672, train/util_ratio: 0.6252, train/run_time: 0.7147, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 22:55:43,414 INFO] 44544 iteration USE_EMA: False, train/sup_loss: 0.0052, train/unsup_loss: 0.4978, train/total_loss: 0.5030, train/util_ratio: 0.8815, train/run_time: 0.7881, lr: 0.0000, train/prefecth_time: 0.0052 
[2023-08-15 22:59:08,847 INFO] 44800 iteration USE_EMA: False, train/sup_loss: 0.0160, train/unsup_loss: 0.4503, train/total_loss: 0.4663, train/util_ratio: 0.7656, train/run_time: 0.7806, lr: 0.0000, train/prefecth_time: 0.0057 
[2023-08-15 23:02:35,612 INFO] validating...
[2023-08-15 23:02:49,612 INFO] confusion matrix:
[[0.42       0.00666667 0.02666667 0.20666667 0.         0.02666667
  0.         0.09333333 0.1        0.12      ]
 [0.         0.82       0.         0.00666667 0.         0.11333333
  0.00666667 0.02666667 0.         0.02666667]
 [0.11333333 0.00666667 0.52       0.18666667 0.         0.02666667
  0.         0.02       0.02       0.10666667]
 [0.00666667 0.         0.         0.59333333 0.06666667 0.00666667
  0.02666667 0.25333333 0.04       0.00666667]
 [0.01333333 0.         0.         0.04       0.81333333 0.
  0.00666667 0.07333333 0.02       0.03333333]
 [0.05333333 0.02666667 0.00666667 0.01333333 0.02       0.81333333
  0.         0.06       0.         0.00666667]
 [0.00666667 0.         0.01333333 0.07333333 0.01333333 0.
  0.82       0.02       0.         0.05333333]
 [0.03333333 0.00666667 0.04       0.02       0.16       0.00666667
  0.00666667 0.65333333 0.         0.07333333]
 [0.03333333 0.         0.01333333 0.08       0.08666667 0.02
  0.00666667 0.11333333 0.61333333 0.03333333]
 [0.03333333 0.         0.11333333 0.24       0.00666667 0.00666667
  0.1        0.13333333 0.02       0.34666667]]
[2023-08-15 23:02:51,636 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 23:02:51,638 INFO] 45056 iteration, USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.1567, train/total_loss: 0.1579, train/util_ratio: 0.8750, train/run_time: 0.6887, eval/loss: 2.3798, eval/top-1-acc: 0.6413, eval/balanced_acc: 0.6413, eval/precision: 0.6623, eval/recall: 0.6413, eval/F1: 0.6433, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.6560, at 38912 iters
[2023-08-15 23:06:16,443 INFO] 45312 iteration USE_EMA: False, train/sup_loss: 0.0019, train/unsup_loss: 0.3223, train/total_loss: 0.3242, train/util_ratio: 0.8754, train/run_time: 0.7687, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 23:09:41,362 INFO] 45568 iteration USE_EMA: False, train/sup_loss: 0.0016, train/unsup_loss: 0.1742, train/total_loss: 0.1758, train/util_ratio: 0.8774, train/run_time: 0.7799, lr: 0.0000, train/prefecth_time: 0.0075 
[2023-08-15 23:13:09,628 INFO] 45824 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.2343, train/total_loss: 0.2352, train/util_ratio: 0.6380, train/run_time: 0.7707, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-15 23:16:34,549 INFO] 46080 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.4426, train/total_loss: 0.4438, train/util_ratio: 0.9296, train/run_time: 0.6844, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 23:20:03,169 INFO] 46336 iteration USE_EMA: False, train/sup_loss: 0.0025, train/unsup_loss: 0.4562, train/total_loss: 0.4587, train/util_ratio: 0.8842, train/run_time: 0.7671, lr: 0.0000, train/prefecth_time: 0.0061 
[2023-08-15 23:23:28,176 INFO] 46592 iteration USE_EMA: False, train/sup_loss: 0.0017, train/unsup_loss: 0.1085, train/total_loss: 0.1102, train/util_ratio: 0.8708, train/run_time: 0.8336, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 23:26:50,977 INFO] 46848 iteration USE_EMA: False, train/sup_loss: 0.0014, train/unsup_loss: 0.0920, train/total_loss: 0.0933, train/util_ratio: 0.7650, train/run_time: 0.7310, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-15 23:30:14,075 INFO] validating...
[2023-08-15 23:30:28,716 INFO] confusion matrix:
[[0.38       0.02666667 0.09333333 0.14       0.         0.03333333
  0.09333333 0.02       0.14666667 0.06666667]
 [0.         0.91333333 0.         0.00666667 0.         0.05333333
  0.02       0.00666667 0.         0.        ]
 [0.09333333 0.00666667 0.61333333 0.08666667 0.         0.03333333
  0.02666667 0.         0.06       0.08      ]
 [0.00666667 0.         0.04       0.74       0.08666667 0.00666667
  0.03333333 0.04       0.04666667 0.        ]
 [0.00666667 0.         0.         0.06       0.83333333 0.
  0.00666667 0.03333333 0.05333333 0.00666667]
 [0.02       0.05333333 0.00666667 0.         0.02       0.84666667
  0.01333333 0.02       0.00666667 0.01333333]
 [0.01333333 0.         0.01333333 0.00666667 0.00666667 0.
  0.93333333 0.         0.00666667 0.02      ]
 [0.02666667 0.00666667 0.08       0.05333333 0.32       0.00666667
  0.01333333 0.41333333 0.03333333 0.04666667]
 [0.01333333 0.         0.03333333 0.06       0.13333333 0.02
  0.01333333 0.03333333 0.67333333 0.02      ]
 [0.04       0.01333333 0.12666667 0.22       0.02666667 0.04
  0.21333333 0.03333333 0.06       0.22666667]]
[2023-08-15 23:30:30,680 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 23:30:32,760 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-15 23:30:32,762 INFO] 47104 iteration, USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.3889, train/total_loss: 0.3896, train/util_ratio: 0.9628, train/run_time: 0.7415, eval/loss: 2.0872, eval/top-1-acc: 0.6573, eval/balanced_acc: 0.6573, eval/precision: 0.6539, eval/recall: 0.6573, eval/F1: 0.6388, lr: 0.0000, train/prefecth_time: 0.0070 BEST_EVAL_ACC: 0.6573, at 47104 iters
[2023-08-15 23:34:00,938 INFO] 47360 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.1489, train/total_loss: 0.1498, train/util_ratio: 0.8721, train/run_time: 0.7991, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 23:37:27,388 INFO] 47616 iteration USE_EMA: False, train/sup_loss: 0.0029, train/unsup_loss: 0.4930, train/total_loss: 0.4958, train/util_ratio: 0.6968, train/run_time: 0.7442, lr: 0.0000, train/prefecth_time: 0.0059 
[2023-08-15 23:40:51,463 INFO] 47872 iteration USE_EMA: False, train/sup_loss: 0.0027, train/unsup_loss: 0.0427, train/total_loss: 0.0454, train/util_ratio: 1.0000, train/run_time: 0.7644, lr: 0.0000, train/prefecth_time: 0.0061 
[2023-08-15 23:44:15,918 INFO] 48128 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.1042, train/total_loss: 0.1050, train/util_ratio: 0.6232, train/run_time: 0.7611, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-15 23:47:42,044 INFO] 48384 iteration USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.4783, train/total_loss: 0.4794, train/util_ratio: 0.6250, train/run_time: 0.7990, lr: 0.0000, train/prefecth_time: 0.0081 
[2023-08-15 23:51:07,385 INFO] 48640 iteration USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.2579, train/total_loss: 0.2590, train/util_ratio: 0.6550, train/run_time: 0.7460, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-15 23:54:33,000 INFO] 48896 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.3365, train/total_loss: 0.3371, train/util_ratio: 0.8750, train/run_time: 0.5508, lr: 0.0000, train/prefecth_time: 0.0047 
[2023-08-15 23:57:57,622 INFO] validating...
[2023-08-15 23:58:12,277 INFO] confusion matrix:
[[0.56666667 0.00666667 0.02666667 0.24666667 0.         0.02
  0.03333333 0.01333333 0.08666667 0.        ]
 [0.00666667 0.84666667 0.         0.00666667 0.         0.11333333
  0.02       0.00666667 0.         0.        ]
 [0.20666667 0.00666667 0.51333333 0.21333333 0.         0.04
  0.         0.00666667 0.01333333 0.        ]
 [0.01333333 0.         0.00666667 0.78666667 0.05333333 0.
  0.00666667 0.07333333 0.06       0.        ]
 [0.02666667 0.         0.00666667 0.08666667 0.78666667 0.
  0.         0.06       0.03333333 0.        ]
 [0.07333333 0.01333333 0.         0.         0.01333333 0.84
  0.00666667 0.05333333 0.         0.        ]
 [0.         0.         0.02666667 0.26666667 0.00666667 0.
  0.7        0.         0.         0.        ]
 [0.05333333 0.00666667 0.04666667 0.10666667 0.14666667 0.
  0.         0.62       0.02       0.        ]
 [0.06666667 0.         0.         0.06       0.10666667 0.01333333
  0.         0.06666667 0.68666667 0.        ]
 [0.08666667 0.01333333 0.15333333 0.52666667 0.01333333 0.01333333
  0.1        0.04666667 0.03333333 0.01333333]]
[2023-08-15 23:58:14,304 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-15 23:58:14,306 INFO] 49152 iteration, USE_EMA: False, train/sup_loss: 0.0016, train/unsup_loss: 0.1139, train/total_loss: 0.1155, train/util_ratio: 0.8750, train/run_time: 0.7911, eval/loss: 2.8513, eval/top-1-acc: 0.6360, eval/balanced_acc: 0.6360, eval/precision: 0.7167, eval/recall: 0.6360, eval/F1: 0.6175, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.6573, at 47104 iters
[2023-08-16 00:01:40,578 INFO] 49408 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.8170, train/total_loss: 0.8176, train/util_ratio: 0.8054, train/run_time: 0.7005, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-16 00:05:06,363 INFO] 49664 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.4147, train/total_loss: 0.4151, train/util_ratio: 1.0000, train/run_time: 0.6773, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 00:08:31,166 INFO] 49920 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.1260, train/total_loss: 0.1268, train/util_ratio: 0.8593, train/run_time: 0.7763, lr: 0.0000, train/prefecth_time: 0.0064 
[2023-08-16 00:11:55,239 INFO] 50176 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.0867, train/total_loss: 0.0873, train/util_ratio: 0.7000, train/run_time: 0.7734, lr: 0.0000, train/prefecth_time: 0.0076 
[2023-08-16 00:15:22,910 INFO] 50432 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.5821, train/total_loss: 0.5830, train/util_ratio: 0.7511, train/run_time: 0.7868, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-16 00:18:50,687 INFO] 50688 iteration USE_EMA: False, train/sup_loss: 0.0014, train/unsup_loss: 0.0553, train/total_loss: 0.0567, train/util_ratio: 0.6464, train/run_time: 0.7568, lr: 0.0000, train/prefecth_time: 0.0055 
[2023-08-16 00:22:17,874 INFO] 50944 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.3387, train/total_loss: 0.3394, train/util_ratio: 0.9998, train/run_time: 0.7225, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 00:25:43,517 INFO] validating...
[2023-08-16 00:25:58,256 INFO] confusion matrix:
[[0.49333333 0.01333333 0.12       0.14666667 0.         0.02666667
  0.         0.04666667 0.12       0.03333333]
 [0.         0.88       0.         0.         0.         0.08
  0.02       0.00666667 0.         0.01333333]
 [0.11333333 0.00666667 0.61333333 0.06       0.         0.01333333
  0.00666667 0.09333333 0.01333333 0.08      ]
 [0.01333333 0.         0.01333333 0.58       0.05333333 0.
  0.00666667 0.24666667 0.08       0.00666667]
 [0.02666667 0.         0.         0.05333333 0.78       0.
  0.         0.06666667 0.06666667 0.00666667]
 [0.03333333 0.02       0.02       0.         0.01333333 0.84666667
  0.01333333 0.04       0.         0.01333333]
 [0.01333333 0.         0.02       0.08666667 0.01333333 0.
  0.76       0.04       0.00666667 0.06      ]
 [0.02666667 0.00666667 0.04666667 0.00666667 0.14       0.
  0.         0.71333333 0.02       0.04      ]
 [0.04       0.         0.02       0.02666667 0.07333333 0.02
  0.         0.08666667 0.73333333 0.        ]
 [0.04       0.00666667 0.18       0.14       0.00666667 0.00666667
  0.11333333 0.21333333 0.05333333 0.24      ]]
[2023-08-16 00:26:00,399 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 00:26:02,443 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-16 00:26:02,445 INFO] 51200 iteration, USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.2448, train/total_loss: 0.2451, train/util_ratio: 0.8341, train/run_time: 0.7732, eval/loss: 2.1850, eval/top-1-acc: 0.6640, eval/balanced_acc: 0.6640, eval/precision: 0.6697, eval/recall: 0.6640, eval/F1: 0.6586, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.6640, at 51200 iters
[2023-08-16 00:29:27,689 INFO] 51456 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.3344, train/total_loss: 0.3352, train/util_ratio: 0.8361, train/run_time: 0.6787, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-16 00:32:55,030 INFO] 51712 iteration USE_EMA: False, train/sup_loss: 0.0069, train/unsup_loss: 0.8873, train/total_loss: 0.8942, train/util_ratio: 1.0000, train/run_time: 0.7325, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 00:36:18,872 INFO] 51968 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.2201, train/total_loss: 0.2208, train/util_ratio: 0.9382, train/run_time: 0.6916, lr: 0.0000, train/prefecth_time: 0.0096 
[2023-08-16 00:39:42,419 INFO] 52224 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0350, train/total_loss: 0.0353, train/util_ratio: 0.8772, train/run_time: 0.7482, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 00:43:08,242 INFO] 52480 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.0831, train/total_loss: 0.0840, train/util_ratio: 0.8698, train/run_time: 0.7978, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-16 00:46:32,092 INFO] 52736 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.3488, train/total_loss: 0.3500, train/util_ratio: 0.7918, train/run_time: 0.6745, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 00:49:55,724 INFO] 52992 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 1.2374, train/total_loss: 1.2377, train/util_ratio: 1.0000, train/run_time: 0.7798, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 00:53:22,201 INFO] validating...
[2023-08-16 00:53:36,995 INFO] confusion matrix:
[[0.52666667 0.00666667 0.08       0.14666667 0.         0.04
  0.         0.01333333 0.11333333 0.07333333]
 [0.         0.89333333 0.         0.         0.         0.09333333
  0.00666667 0.         0.         0.00666667]
 [0.12       0.00666667 0.70666667 0.05333333 0.         0.02
  0.00666667 0.00666667 0.02666667 0.05333333]
 [0.01333333 0.         0.04       0.64       0.06666667 0.
  0.01333333 0.12       0.10666667 0.        ]
 [0.02       0.         0.         0.04666667 0.73333333 0.
  0.00666667 0.10666667 0.08       0.00666667]
 [0.02666667 0.02666667 0.01333333 0.         0.         0.86
  0.04666667 0.01333333 0.         0.01333333]
 [0.         0.         0.04       0.03333333 0.00666667 0.
  0.83333333 0.         0.01333333 0.07333333]
 [0.04       0.00666667 0.09333333 0.04666667 0.06666667 0.
  0.01333333 0.64666667 0.04       0.04666667]
 [0.04       0.         0.04       0.01333333 0.06666667 0.02
  0.00666667 0.09333333 0.72       0.        ]
 [0.05333333 0.01333333 0.18666667 0.16666667 0.02       0.01333333
  0.09333333 0.1        0.06       0.29333333]]
[2023-08-16 00:53:39,184 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 00:53:41,988 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-16 00:53:41,990 INFO] 53248 iteration, USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.1659, train/total_loss: 0.1667, train/util_ratio: 0.8655, train/run_time: 0.7930, eval/loss: 2.3695, eval/top-1-acc: 0.6853, eval/balanced_acc: 0.6853, eval/precision: 0.6835, eval/recall: 0.6853, eval/F1: 0.6794, lr: 0.0000, train/prefecth_time: 0.0057 BEST_EVAL_ACC: 0.6853, at 53248 iters
[2023-08-16 00:57:07,805 INFO] 53504 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.1678, train/total_loss: 0.1683, train/util_ratio: 0.8750, train/run_time: 0.7607, lr: 0.0000, train/prefecth_time: 0.0055 
[2023-08-16 01:00:32,598 INFO] 53760 iteration USE_EMA: False, train/sup_loss: 0.0108, train/unsup_loss: 0.3962, train/total_loss: 0.4069, train/util_ratio: 0.6692, train/run_time: 0.7238, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 01:03:56,136 INFO] 54016 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.3697, train/total_loss: 0.3701, train/util_ratio: 0.8750, train/run_time: 0.7336, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 01:07:21,459 INFO] 54272 iteration USE_EMA: False, train/sup_loss: 0.0039, train/unsup_loss: 0.2597, train/total_loss: 0.2636, train/util_ratio: 0.5366, train/run_time: 0.6424, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 01:10:49,265 INFO] 54528 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0500, train/total_loss: 0.0503, train/util_ratio: 0.6252, train/run_time: 0.8133, lr: 0.0000, train/prefecth_time: 0.0048 
[2023-08-16 01:14:13,242 INFO] 54784 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.1471, train/total_loss: 0.1478, train/util_ratio: 0.4881, train/run_time: 0.7200, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 01:17:39,320 INFO] 55040 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.5830, train/total_loss: 0.5834, train/util_ratio: 1.0000, train/run_time: 0.7965, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 01:21:05,294 INFO] validating...
[2023-08-16 01:21:19,871 INFO] confusion matrix:
[[0.58       0.         0.03333333 0.07333333 0.02666667 0.05333333
  0.03333333 0.06666667 0.06666667 0.06666667]
 [0.02666667 0.82       0.         0.         0.         0.10666667
  0.00666667 0.02       0.         0.02      ]
 [0.19333333 0.00666667 0.54666667 0.03333333 0.         0.02
  0.         0.00666667 0.00666667 0.18666667]
 [0.01333333 0.         0.03333333 0.49333333 0.12666667 0.00666667
  0.06       0.18666667 0.08       0.        ]
 [0.02666667 0.         0.         0.02666667 0.85333333 0.
  0.00666667 0.06       0.02       0.00666667]
 [0.06666667 0.01333333 0.00666667 0.         0.00666667 0.85333333
  0.04       0.00666667 0.         0.00666667]
 [0.         0.         0.00666667 0.         0.02       0.
  0.87333333 0.02       0.         0.08      ]
 [0.05333333 0.00666667 0.06666667 0.         0.25333333 0.00666667
  0.00666667 0.57333333 0.00666667 0.02666667]
 [0.06666667 0.         0.00666667 0.02       0.24666667 0.02
  0.00666667 0.06       0.57333333 0.        ]
 [0.08666667 0.00666667 0.12666667 0.09333333 0.06       0.02666667
  0.13333333 0.09333333 0.02       0.35333333]]
[2023-08-16 01:21:21,748 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 01:21:21,749 INFO] 55296 iteration, USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.4766, train/total_loss: 0.4771, train/util_ratio: 0.7500, train/run_time: 0.7131, eval/loss: 2.1858, eval/top-1-acc: 0.6520, eval/balanced_acc: 0.6520, eval/precision: 0.6613, eval/recall: 0.6520, eval/F1: 0.6478, lr: 0.0000, train/prefecth_time: 0.0071 BEST_EVAL_ACC: 0.6853, at 53248 iters
[2023-08-16 01:24:49,636 INFO] 55552 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0995, train/total_loss: 0.0996, train/util_ratio: 0.9531, train/run_time: 0.7730, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 01:28:13,239 INFO] 55808 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.6370, train/total_loss: 0.6378, train/util_ratio: 1.0000, train/run_time: 0.7858, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 01:31:37,282 INFO] 56064 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2682, train/total_loss: 0.2685, train/util_ratio: 0.8822, train/run_time: 0.7963, lr: 0.0000, train/prefecth_time: 0.0051 
[2023-08-16 01:35:03,396 INFO] 56320 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 1.3357, train/total_loss: 1.3360, train/util_ratio: 1.0000, train/run_time: 0.8176, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 01:38:29,878 INFO] 56576 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0313, train/total_loss: 0.0317, train/util_ratio: 0.3526, train/run_time: 0.7760, lr: 0.0000, train/prefecth_time: 0.0054 
[2023-08-16 01:41:54,411 INFO] 56832 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.6575, train/total_loss: 0.6577, train/util_ratio: 1.0000, train/run_time: 0.7642, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 01:45:20,304 INFO] 57088 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.8632, train/total_loss: 0.8635, train/util_ratio: 0.9411, train/run_time: 0.7646, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 01:48:44,115 INFO] validating...
[2023-08-16 01:48:58,824 INFO] confusion matrix:
[[0.38666667 0.02       0.33333333 0.14       0.         0.03333333
  0.02       0.         0.04666667 0.02      ]
 [0.         0.91333333 0.         0.         0.         0.08
  0.00666667 0.         0.         0.        ]
 [0.02       0.01333333 0.88666667 0.02       0.         0.04
  0.         0.01333333 0.         0.00666667]
 [0.         0.         0.12       0.68       0.02       0.00666667
  0.01333333 0.04       0.12       0.        ]
 [0.00666667 0.         0.02666667 0.06       0.68666667 0.00666667
  0.00666667 0.13333333 0.07333333 0.        ]
 [0.03333333 0.04       0.02666667 0.         0.         0.9
  0.         0.         0.         0.        ]
 [0.01333333 0.         0.05333333 0.05333333 0.00666667 0.
  0.79333333 0.         0.00666667 0.07333333]
 [0.02       0.00666667 0.22666667 0.05333333 0.03333333 0.00666667
  0.01333333 0.61333333 0.02       0.00666667]
 [0.01333333 0.         0.12       0.01333333 0.05333333 0.02
  0.         0.07333333 0.70666667 0.        ]
 [0.03333333 0.02       0.50666667 0.12       0.01333333 0.02666667
  0.07333333 0.02666667 0.04666667 0.13333333]]
[2023-08-16 01:49:00,715 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 01:49:00,717 INFO] 57344 iteration, USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.4313, train/total_loss: 0.4317, train/util_ratio: 0.9870, train/run_time: 0.7611, eval/loss: 2.7924, eval/top-1-acc: 0.6700, eval/balanced_acc: 0.6700, eval/precision: 0.7051, eval/recall: 0.6700, eval/F1: 0.6577, lr: 0.0000, train/prefecth_time: 0.0071 BEST_EVAL_ACC: 0.6853, at 53248 iters
[2023-08-16 01:52:24,138 INFO] 57600 iteration USE_EMA: False, train/sup_loss: 0.0021, train/unsup_loss: 1.4356, train/total_loss: 1.4377, train/util_ratio: 0.9999, train/run_time: 0.6931, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 01:55:46,983 INFO] 57856 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1451, train/total_loss: 0.1453, train/util_ratio: 0.7509, train/run_time: 0.7188, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 01:59:12,242 INFO] 58112 iteration USE_EMA: False, train/sup_loss: 0.0021, train/unsup_loss: 0.1860, train/total_loss: 0.1881, train/util_ratio: 0.8854, train/run_time: 0.7553, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 02:02:36,279 INFO] 58368 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0031, train/total_loss: 0.0034, train/util_ratio: 0.8750, train/run_time: 0.7601, lr: 0.0000, train/prefecth_time: 0.0065 
[2023-08-16 02:06:02,520 INFO] 58624 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.2658, train/total_loss: 0.2665, train/util_ratio: 1.0000, train/run_time: 0.7655, lr: 0.0000, train/prefecth_time: 0.0066 
[2023-08-16 02:09:29,083 INFO] 58880 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.9316, train/total_loss: 0.9320, train/util_ratio: 0.8117, train/run_time: 0.7928, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-16 02:12:52,180 INFO] 59136 iteration USE_EMA: False, train/sup_loss: 0.0343, train/unsup_loss: 0.0051, train/total_loss: 0.0394, train/util_ratio: 0.7531, train/run_time: 0.7886, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 02:16:17,099 INFO] validating...
[2023-08-16 02:16:31,871 INFO] confusion matrix:
[[0.63333333 0.02       0.07333333 0.10666667 0.00666667 0.01333333
  0.         0.00666667 0.05333333 0.08666667]
 [0.         0.91333333 0.         0.         0.         0.06
  0.00666667 0.         0.         0.02      ]
 [0.13333333 0.01333333 0.69333333 0.02666667 0.         0.02666667
  0.         0.01333333 0.00666667 0.08666667]
 [0.01333333 0.         0.02       0.7        0.05333333 0.
  0.00666667 0.09333333 0.06666667 0.04666667]
 [0.04       0.         0.00666667 0.06       0.79333333 0.01333333
  0.         0.04       0.02666667 0.02      ]
 [0.07333333 0.04666667 0.00666667 0.         0.         0.86666667
  0.         0.00666667 0.         0.        ]
 [0.02666667 0.         0.02       0.05333333 0.02       0.
  0.49333333 0.01333333 0.00666667 0.36666667]
 [0.04666667 0.01333333 0.06666667 0.02666667 0.1        0.
  0.         0.68666667 0.01333333 0.04666667]
 [0.08666667 0.         0.06       0.03333333 0.08       0.01333333
  0.         0.08       0.64666667 0.        ]
 [0.14       0.02666667 0.16       0.1        0.01333333 0.01333333
  0.01333333 0.06666667 0.03333333 0.43333333]]
[2023-08-16 02:16:33,854 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 02:16:35,762 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-16 02:16:35,763 INFO] 59392 iteration, USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.4112, train/total_loss: 0.4121, train/util_ratio: 0.7412, train/run_time: 0.7707, eval/loss: 2.3039, eval/top-1-acc: 0.6860, eval/balanced_acc: 0.6860, eval/precision: 0.7059, eval/recall: 0.6860, eval/F1: 0.6873, lr: 0.0000, train/prefecth_time: 0.0055 BEST_EVAL_ACC: 0.6860, at 59392 iters
[2023-08-16 02:20:03,342 INFO] 59648 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1653, train/total_loss: 0.1656, train/util_ratio: 0.8311, train/run_time: 0.7479, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 02:23:28,075 INFO] 59904 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.5405, train/total_loss: 0.5411, train/util_ratio: 0.8750, train/run_time: 0.8169, lr: 0.0000, train/prefecth_time: 0.0054 
[2023-08-16 02:26:49,513 INFO] 60160 iteration USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.1246, train/total_loss: 0.1261, train/util_ratio: 0.7717, train/run_time: 0.7485, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 02:30:13,924 INFO] 60416 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.4861, train/total_loss: 0.4866, train/util_ratio: 0.7591, train/run_time: 0.8260, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 02:33:37,349 INFO] 60672 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0145, train/total_loss: 0.0147, train/util_ratio: 0.7883, train/run_time: 0.8002, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 02:37:03,597 INFO] 60928 iteration USE_EMA: False, train/sup_loss: 0.0016, train/unsup_loss: 0.4313, train/total_loss: 0.4328, train/util_ratio: 0.7787, train/run_time: 0.8294, lr: 0.0000, train/prefecth_time: 0.0055 
[2023-08-16 02:40:25,697 INFO] 61184 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1376, train/total_loss: 0.1378, train/util_ratio: 0.8750, train/run_time: 0.7353, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-16 02:43:50,128 INFO] validating...
[2023-08-16 02:44:04,731 INFO] confusion matrix:
[[0.54666667 0.00666667 0.06666667 0.18       0.         0.05333333
  0.         0.05333333 0.06       0.03333333]
 [0.         0.85333333 0.         0.         0.         0.12
  0.00666667 0.         0.         0.02      ]
 [0.1        0.01333333 0.66666667 0.06       0.         0.04666667
  0.         0.04       0.01333333 0.06      ]
 [0.01333333 0.         0.00666667 0.63333333 0.04666667 0.01333333
  0.         0.19333333 0.09333333 0.        ]
 [0.03333333 0.         0.         0.08       0.77333333 0.00666667
  0.         0.05333333 0.04666667 0.00666667]
 [0.03333333 0.02666667 0.02       0.         0.01333333 0.9
  0.         0.00666667 0.         0.        ]
 [0.02       0.         0.02       0.12666667 0.         0.01333333
  0.59333333 0.05333333 0.02       0.15333333]
 [0.05333333 0.00666667 0.04666667 0.01333333 0.11333333 0.02666667
  0.         0.67333333 0.03333333 0.03333333]
 [0.06666667 0.         0.04       0.02666667 0.08666667 0.03333333
  0.         0.08       0.66       0.00666667]
 [0.1        0.02       0.15333333 0.16666667 0.         0.05333333
  0.02666667 0.10666667 0.06666667 0.30666667]]
[2023-08-16 02:44:06,615 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 02:44:06,616 INFO] 61440 iteration, USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.4327, train/total_loss: 0.4331, train/util_ratio: 1.0000, train/run_time: 0.6827, eval/loss: 2.4515, eval/top-1-acc: 0.6607, eval/balanced_acc: 0.6607, eval/precision: 0.6731, eval/recall: 0.6607, eval/F1: 0.6577, lr: 0.0000, train/prefecth_time: 0.0069 BEST_EVAL_ACC: 0.6860, at 59392 iters
[2023-08-16 02:47:30,472 INFO] 61696 iteration USE_EMA: False, train/sup_loss: 0.2404, train/unsup_loss: 0.0073, train/total_loss: 0.2476, train/util_ratio: 1.0000, train/run_time: 0.8015, lr: 0.0000, train/prefecth_time: 0.0055 
[2023-08-16 02:50:52,329 INFO] 61952 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0419, train/total_loss: 0.0422, train/util_ratio: 0.7983, train/run_time: 0.7425, lr: 0.0000, train/prefecth_time: 0.0069 
[2023-08-16 02:54:15,530 INFO] 62208 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0844, train/total_loss: 0.0846, train/util_ratio: 1.0000, train/run_time: 0.7924, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 02:57:38,645 INFO] 62464 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.2227, train/total_loss: 0.2230, train/util_ratio: 0.7500, train/run_time: 0.8215, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 03:01:06,240 INFO] 62720 iteration USE_EMA: False, train/sup_loss: 0.0040, train/unsup_loss: 0.4576, train/total_loss: 0.4616, train/util_ratio: 0.9931, train/run_time: 0.7019, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 03:04:29,608 INFO] 62976 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1351, train/total_loss: 0.1353, train/util_ratio: 0.8760, train/run_time: 0.7355, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-16 03:07:55,624 INFO] 63232 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.7143, train/total_loss: 0.7151, train/util_ratio: 0.7671, train/run_time: 0.7980, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 03:11:20,742 INFO] validating...
[2023-08-16 03:11:35,704 INFO] confusion matrix:
[[0.42666667 0.02       0.10666667 0.14       0.02       0.02
  0.01333333 0.05333333 0.15333333 0.04666667]
 [0.         0.90666667 0.         0.         0.         0.08666667
  0.00666667 0.         0.         0.        ]
 [0.1        0.02666667 0.73333333 0.02       0.         0.01333333
  0.         0.00666667 0.03333333 0.06666667]
 [0.00666667 0.         0.03333333 0.56       0.14       0.
  0.00666667 0.08666667 0.14       0.02666667]
 [0.02       0.         0.         0.03333333 0.85333333 0.
  0.00666667 0.02666667 0.05333333 0.00666667]
 [0.04666667 0.04666667 0.01333333 0.         0.02666667 0.86
  0.         0.         0.00666667 0.        ]
 [0.         0.         0.03333333 0.02       0.01333333 0.
  0.88       0.00666667 0.02       0.02666667]
 [0.02666667 0.00666667 0.06666667 0.02666667 0.25333333 0.00666667
  0.01333333 0.48666667 0.06666667 0.04666667]
 [0.02666667 0.         0.02666667 0.00666667 0.11333333 0.02
  0.         0.05333333 0.74666667 0.00666667]
 [0.05333333 0.04       0.19333333 0.12       0.01333333 0.01333333
  0.12666667 0.04       0.10666667 0.29333333]]
[2023-08-16 03:11:37,650 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 03:11:37,651 INFO] 63488 iteration, USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.3654, train/total_loss: 0.3657, train/util_ratio: 1.0000, train/run_time: 0.7403, eval/loss: 2.4338, eval/top-1-acc: 0.6747, eval/balanced_acc: 0.6747, eval/precision: 0.6723, eval/recall: 0.6747, eval/F1: 0.6623, lr: 0.0000, train/prefecth_time: 0.0071 BEST_EVAL_ACC: 0.6860, at 59392 iters
[2023-08-16 03:15:00,961 INFO] 63744 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0090, train/total_loss: 0.0093, train/util_ratio: 0.7971, train/run_time: 0.7928, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-16 03:18:23,951 INFO] 64000 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.4691, train/total_loss: 0.4694, train/util_ratio: 0.6100, train/run_time: 0.7823, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 03:21:46,566 INFO] 64256 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1000, train/total_loss: 0.1001, train/util_ratio: 0.7824, train/run_time: 0.7763, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 03:25:09,255 INFO] 64512 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3613, train/total_loss: 0.3615, train/util_ratio: 0.8750, train/run_time: 0.7998, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-16 03:28:36,264 INFO] 64768 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.9612, train/total_loss: 0.9619, train/util_ratio: 0.8750, train/run_time: 0.7579, lr: 0.0000, train/prefecth_time: 0.0061 
[2023-08-16 03:31:59,807 INFO] 65024 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.5724, train/total_loss: 0.5726, train/util_ratio: 0.8345, train/run_time: 0.7527, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 03:35:23,825 INFO] 65280 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 1.2405, train/total_loss: 1.2407, train/util_ratio: 0.9857, train/run_time: 0.7972, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 03:38:48,336 INFO] validating...
[2023-08-16 03:39:02,754 INFO] confusion matrix:
[[0.51333333 0.02       0.15333333 0.06666667 0.02       0.02
  0.         0.04666667 0.07333333 0.08666667]
 [0.         0.89333333 0.         0.         0.         0.08666667
  0.00666667 0.         0.         0.01333333]
 [0.10666667 0.01333333 0.8        0.02       0.         0.02
  0.         0.00666667 0.         0.03333333]
 [0.00666667 0.         0.05333333 0.68       0.04       0.
  0.         0.07333333 0.1        0.04666667]
 [0.02666667 0.         0.         0.04       0.79333333 0.
  0.00666667 0.04666667 0.06666667 0.02      ]
 [0.05333333 0.03333333 0.01333333 0.         0.         0.87333333
  0.         0.01333333 0.         0.01333333]
 [0.02       0.         0.06666667 0.04       0.01333333 0.00666667
  0.77333333 0.         0.01333333 0.06666667]
 [0.04       0.00666667 0.10666667 0.03333333 0.16666667 0.00666667
  0.         0.57333333 0.04       0.02666667]
 [0.06       0.         0.06666667 0.03333333 0.09333333 0.01333333
  0.         0.03333333 0.7        0.        ]
 [0.07333333 0.01333333 0.28       0.1        0.02666667 0.00666667
  0.08666667 0.04666667 0.05333333 0.31333333]]
[2023-08-16 03:39:04,649 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 03:39:06,471 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-16 03:39:06,472 INFO] 65536 iteration, USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.0251, train/total_loss: 0.0255, train/util_ratio: 1.0000, train/run_time: 0.7584, eval/loss: 2.4293, eval/top-1-acc: 0.6913, eval/balanced_acc: 0.6913, eval/precision: 0.6948, eval/recall: 0.6913, eval/F1: 0.6864, lr: 0.0000, train/prefecth_time: 0.0070 BEST_EVAL_ACC: 0.6913, at 65536 iters
[2023-08-16 03:42:30,205 INFO] 65792 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2226, train/total_loss: 0.2228, train/util_ratio: 0.8790, train/run_time: 0.7379, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-16 03:45:52,954 INFO] 66048 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.0520, train/total_loss: 0.0525, train/util_ratio: 1.0000, train/run_time: 0.7464, lr: 0.0000, train/prefecth_time: 0.0058 
[2023-08-16 03:49:14,381 INFO] 66304 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2109, train/total_loss: 0.2111, train/util_ratio: 0.9995, train/run_time: 0.7551, lr: 0.0000, train/prefecth_time: 0.0055 
[2023-08-16 03:52:36,381 INFO] 66560 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1770, train/total_loss: 0.1772, train/util_ratio: 0.9098, train/run_time: 0.7306, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 03:56:01,116 INFO] 66816 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.2172, train/total_loss: 0.2177, train/util_ratio: 0.7502, train/run_time: 0.7835, lr: 0.0000, train/prefecth_time: 0.0054 
[2023-08-16 03:59:23,274 INFO] 67072 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0144, train/total_loss: 0.0146, train/util_ratio: 1.0000, train/run_time: 0.7894, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 04:02:46,969 INFO] 67328 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0829, train/total_loss: 0.0830, train/util_ratio: 1.0000, train/run_time: 0.7802, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-16 04:06:10,295 INFO] validating...
[2023-08-16 04:06:24,967 INFO] confusion matrix:
[[0.6        0.         0.04       0.09333333 0.02       0.04666667
  0.02       0.05333333 0.06666667 0.06      ]
 [0.00666667 0.78       0.         0.         0.         0.18666667
  0.00666667 0.         0.         0.02      ]
 [0.28666667 0.01333333 0.53333333 0.04666667 0.         0.05333333
  0.         0.00666667 0.02       0.04      ]
 [0.00666667 0.         0.02       0.65333333 0.04666667 0.01333333
  0.         0.08       0.14       0.04      ]
 [0.02666667 0.         0.         0.06666667 0.78       0.
  0.00666667 0.03333333 0.07333333 0.01333333]
 [0.05333333 0.02666667 0.         0.         0.         0.90666667
  0.         0.         0.         0.01333333]
 [0.02       0.         0.02666667 0.02666667 0.01333333 0.
  0.82       0.03333333 0.01333333 0.04666667]
 [0.06       0.00666667 0.05333333 0.04666667 0.14       0.00666667
  0.00666667 0.59333333 0.04666667 0.04      ]
 [0.08       0.         0.02       0.03333333 0.08       0.02
  0.         0.05333333 0.71333333 0.        ]
 [0.10666667 0.01333333 0.13333333 0.12       0.01333333 0.05333333
  0.10666667 0.08666667 0.04666667 0.32      ]]
[2023-08-16 04:06:26,916 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 04:06:26,917 INFO] 67584 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1950, train/total_loss: 0.1951, train/util_ratio: 0.9874, train/run_time: 0.7174, eval/loss: 2.5027, eval/top-1-acc: 0.6700, eval/balanced_acc: 0.6700, eval/precision: 0.6730, eval/recall: 0.6700, eval/F1: 0.6651, lr: 0.0000, train/prefecth_time: 0.0050 BEST_EVAL_ACC: 0.6913, at 65536 iters
[2023-08-16 04:09:50,656 INFO] 67840 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.3090, train/total_loss: 0.3093, train/util_ratio: 1.0000, train/run_time: 0.7275, lr: 0.0000, train/prefecth_time: 0.0056 
[2023-08-16 04:13:13,998 INFO] 68096 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0892, train/total_loss: 0.0895, train/util_ratio: 0.8750, train/run_time: 0.7123, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 04:16:34,322 INFO] 68352 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1138, train/total_loss: 0.1140, train/util_ratio: 0.7178, train/run_time: 0.7467, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 04:19:56,720 INFO] 68608 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.0524, train/total_loss: 0.0531, train/util_ratio: 0.8750, train/run_time: 0.7634, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-16 04:23:24,877 INFO] 68864 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.1777, train/total_loss: 0.1782, train/util_ratio: 0.5724, train/run_time: 0.7639, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-16 04:26:48,006 INFO] 69120 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0500, train/total_loss: 0.0502, train/util_ratio: 0.8750, train/run_time: 0.7761, lr: 0.0000, train/prefecth_time: 0.0051 
[2023-08-16 04:30:10,856 INFO] 69376 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.1052, train/total_loss: 0.1063, train/util_ratio: 0.9575, train/run_time: 0.7082, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-16 04:33:33,399 INFO] validating...
[2023-08-16 04:33:48,020 INFO] confusion matrix:
[[0.58       0.01333333 0.04666667 0.14       0.02       0.02
  0.00666667 0.03333333 0.10666667 0.03333333]
 [0.00666667 0.87333333 0.         0.         0.         0.09333333
  0.00666667 0.         0.         0.02      ]
 [0.17333333 0.00666667 0.61333333 0.05333333 0.         0.02
  0.00666667 0.         0.02       0.10666667]
 [0.         0.         0.02       0.72       0.09333333 0.00666667
  0.         0.03333333 0.11333333 0.01333333]
 [0.02666667 0.         0.         0.04666667 0.82666667 0.
  0.00666667 0.03333333 0.05333333 0.00666667]
 [0.05333333 0.03333333 0.00666667 0.         0.00666667 0.88
  0.01333333 0.00666667 0.         0.        ]
 [0.04       0.         0.00666667 0.02666667 0.01333333 0.
  0.86       0.         0.01333333 0.04      ]
 [0.03333333 0.00666667 0.1        0.02       0.25333333 0.
  0.01333333 0.47333333 0.04666667 0.05333333]
 [0.05333333 0.         0.01333333 0.02666667 0.08666667 0.02
  0.         0.04       0.76       0.        ]
 [0.1        0.02       0.14       0.16666667 0.03333333 0.02
  0.18       0.04666667 0.07333333 0.22      ]]
[2023-08-16 04:33:49,945 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 04:33:49,946 INFO] 69632 iteration, USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1348, train/total_loss: 0.1350, train/util_ratio: 0.9790, train/run_time: 0.7295, eval/loss: 2.4780, eval/top-1-acc: 0.6807, eval/balanced_acc: 0.6807, eval/precision: 0.6741, eval/recall: 0.6807, eval/F1: 0.6683, lr: 0.0000, train/prefecth_time: 0.0042 BEST_EVAL_ACC: 0.6913, at 65536 iters
[2023-08-16 04:37:14,598 INFO] 69888 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.2198, train/total_loss: 0.2201, train/util_ratio: 0.8090, train/run_time: 0.7602, lr: 0.0000, train/prefecth_time: 0.0045 
[2023-08-16 04:40:38,457 INFO] 70144 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0744, train/total_loss: 0.0745, train/util_ratio: 0.9662, train/run_time: 0.7823, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 04:44:01,397 INFO] 70400 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3576, train/total_loss: 0.3579, train/util_ratio: 1.0000, train/run_time: 0.7182, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 04:47:25,012 INFO] 70656 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.1592, train/total_loss: 0.1596, train/util_ratio: 0.8201, train/run_time: 0.6896, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 04:50:49,149 INFO] 70912 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.4775, train/total_loss: 0.4777, train/util_ratio: 0.8665, train/run_time: 0.7503, lr: 0.0000, train/prefecth_time: 0.0048 
[2023-08-16 04:54:11,740 INFO] 71168 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.6825, train/total_loss: 0.6829, train/util_ratio: 0.8111, train/run_time: 0.7266, lr: 0.0000, train/prefecth_time: 0.0055 
[2023-08-16 04:57:34,691 INFO] 71424 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.3834, train/total_loss: 0.3837, train/util_ratio: 1.0000, train/run_time: 0.7315, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 05:00:57,246 INFO] validating...
[2023-08-16 05:01:11,786 INFO] confusion matrix:
[[0.51333333 0.00666667 0.08       0.11333333 0.02666667 0.03333333
  0.01333333 0.06       0.12       0.03333333]
 [0.02666667 0.78666667 0.         0.         0.         0.14666667
  0.00666667 0.00666667 0.         0.02666667]
 [0.1        0.01333333 0.72666667 0.04       0.         0.02
  0.00666667 0.01333333 0.01333333 0.06666667]
 [0.         0.         0.04       0.61333333 0.04       0.00666667
  0.01333333 0.16       0.11333333 0.01333333]
 [0.02666667 0.         0.         0.05333333 0.81333333 0.
  0.00666667 0.04666667 0.04666667 0.00666667]
 [0.03333333 0.01333333 0.03333333 0.         0.00666667 0.84
  0.04       0.02666667 0.         0.00666667]
 [0.01333333 0.         0.02       0.00666667 0.00666667 0.
  0.88666667 0.03333333 0.00666667 0.02666667]
 [0.04       0.00666667 0.08666667 0.         0.14       0.
  0.02666667 0.62666667 0.04       0.03333333]
 [0.03333333 0.         0.03333333 0.01333333 0.08       0.02
  0.00666667 0.07333333 0.74       0.        ]
 [0.07333333 0.00666667 0.17333333 0.12666667 0.01333333 0.01333333
  0.16       0.15333333 0.06       0.22      ]]
[2023-08-16 05:01:13,636 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 05:01:13,637 INFO] 71680 iteration, USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.2887, train/total_loss: 0.2891, train/util_ratio: 0.7933, train/run_time: 0.8006, eval/loss: 2.2756, eval/top-1-acc: 0.6767, eval/balanced_acc: 0.6767, eval/precision: 0.6723, eval/recall: 0.6767, eval/F1: 0.6656, lr: 0.0000, train/prefecth_time: 0.0041 BEST_EVAL_ACC: 0.6913, at 65536 iters
[2023-08-16 05:04:37,588 INFO] 71936 iteration USE_EMA: False, train/sup_loss: 0.0058, train/unsup_loss: 0.0392, train/total_loss: 0.0451, train/util_ratio: 0.7173, train/run_time: 0.5526, lr: 0.0000, train/prefecth_time: 0.0103 
[2023-08-16 05:07:59,445 INFO] 72192 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.2106, train/total_loss: 0.2110, train/util_ratio: 0.8573, train/run_time: 0.7411, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 05:11:23,002 INFO] 72448 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.3950, train/total_loss: 0.3954, train/util_ratio: 0.8757, train/run_time: 0.7801, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-16 05:14:44,951 INFO] 72704 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2481, train/total_loss: 0.2482, train/util_ratio: 0.8406, train/run_time: 0.7098, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-16 05:18:08,488 INFO] 72960 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.3136, train/total_loss: 0.3141, train/util_ratio: 0.6408, train/run_time: 0.7534, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 05:21:32,040 INFO] 73216 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1196, train/total_loss: 0.1198, train/util_ratio: 0.8750, train/run_time: 0.7733, lr: 0.0000, train/prefecth_time: 0.0059 
[2023-08-16 05:24:55,945 INFO] 73472 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1048, train/total_loss: 0.1051, train/util_ratio: 0.6229, train/run_time: 0.7705, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 05:28:18,522 INFO] validating...
[2023-08-16 05:28:33,343 INFO] confusion matrix:
[[0.52666667 0.00666667 0.02666667 0.12666667 0.02       0.03333333
  0.04       0.02666667 0.10666667 0.08666667]
 [0.01333333 0.73333333 0.         0.         0.         0.22666667
  0.00666667 0.         0.         0.02      ]
 [0.13333333 0.00666667 0.58666667 0.06       0.         0.02666667
  0.00666667 0.00666667 0.02666667 0.14666667]
 [0.00666667 0.         0.02       0.72       0.09333333 0.00666667
  0.02666667 0.04       0.04666667 0.04      ]
 [0.02666667 0.         0.         0.06       0.85333333 0.
  0.00666667 0.03333333 0.00666667 0.01333333]
 [0.04666667 0.00666667 0.01333333 0.         0.02       0.85333333
  0.04       0.01333333 0.         0.00666667]
 [0.01333333 0.         0.         0.00666667 0.01333333 0.
  0.88666667 0.         0.00666667 0.07333333]
 [0.05333333 0.00666667 0.04666667 0.04666667 0.18666667 0.01333333
  0.01333333 0.55333333 0.02       0.06      ]
 [0.04       0.         0.02       0.07333333 0.18       0.02
  0.00666667 0.05333333 0.6        0.00666667]
 [0.05333333 0.         0.12666667 0.16       0.04666667 0.00666667
  0.14       0.06       0.02666667 0.38      ]]
[2023-08-16 05:28:35,355 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 05:28:35,357 INFO] 73728 iteration, USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.1869, train/total_loss: 0.1874, train/util_ratio: 1.0000, train/run_time: 0.7131, eval/loss: 2.3187, eval/top-1-acc: 0.6693, eval/balanced_acc: 0.6693, eval/precision: 0.6767, eval/recall: 0.6693, eval/F1: 0.6650, lr: 0.0000, train/prefecth_time: 0.0053 BEST_EVAL_ACC: 0.6913, at 65536 iters
[2023-08-16 05:32:00,430 INFO] 73984 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.5406, train/total_loss: 0.5412, train/util_ratio: 0.7500, train/run_time: 0.6906, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 05:35:23,854 INFO] 74240 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.4608, train/total_loss: 0.4610, train/util_ratio: 0.8738, train/run_time: 0.5912, lr: 0.0000, train/prefecth_time: 0.0093 
[2023-08-16 05:38:48,192 INFO] 74496 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4456, train/total_loss: 0.4457, train/util_ratio: 0.8637, train/run_time: 0.7925, lr: 0.0000, train/prefecth_time: 0.0052 
[2023-08-16 05:42:10,897 INFO] 74752 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.8969, train/total_loss: 0.8976, train/util_ratio: 0.8750, train/run_time: 0.8197, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-16 05:45:35,725 INFO] 75008 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.2679, train/total_loss: 0.2684, train/util_ratio: 0.7500, train/run_time: 0.7813, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 05:48:59,634 INFO] 75264 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.4600, train/total_loss: 0.4610, train/util_ratio: 0.9915, train/run_time: 0.7366, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-16 05:52:22,662 INFO] 75520 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1866, train/total_loss: 0.1868, train/util_ratio: 0.8750, train/run_time: 0.7668, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 05:55:47,241 INFO] validating...
[2023-08-16 05:56:01,856 INFO] confusion matrix:
[[0.58666667 0.01333333 0.08666667 0.19333333 0.         0.02666667
  0.         0.03333333 0.05333333 0.00666667]
 [0.00666667 0.88666667 0.         0.         0.         0.08
  0.00666667 0.         0.         0.02      ]
 [0.11333333 0.01333333 0.76       0.05333333 0.         0.02666667
  0.00666667 0.         0.         0.02666667]
 [0.         0.         0.03333333 0.74666667 0.04       0.00666667
  0.         0.08666667 0.06666667 0.02      ]
 [0.02666667 0.         0.00666667 0.08       0.76666667 0.
  0.00666667 0.08       0.03333333 0.        ]
 [0.06       0.01333333 0.01333333 0.         0.01333333 0.86666667
  0.01333333 0.01333333 0.         0.00666667]
 [0.04666667 0.         0.02666667 0.05333333 0.         0.
  0.77333333 0.         0.00666667 0.09333333]
 [0.03333333 0.00666667 0.13333333 0.03333333 0.08666667 0.
  0.01333333 0.65333333 0.02       0.02      ]
 [0.06666667 0.         0.05333333 0.08       0.08       0.02
  0.         0.08       0.62       0.        ]
 [0.10666667 0.00666667 0.24       0.22       0.00666667 0.02666667
  0.06666667 0.06       0.02       0.24666667]]
[2023-08-16 05:56:03,865 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 05:56:03,866 INFO] 75776 iteration, USE_EMA: False, train/sup_loss: 0.0043, train/unsup_loss: 0.0020, train/total_loss: 0.0063, train/util_ratio: 0.8750, train/run_time: 0.7172, eval/loss: 2.3834, eval/top-1-acc: 0.6907, eval/balanced_acc: 0.6907, eval/precision: 0.7009, eval/recall: 0.6907, eval/F1: 0.6849, lr: 0.0000, train/prefecth_time: 0.0041 BEST_EVAL_ACC: 0.6913, at 65536 iters
[2023-08-16 05:59:28,165 INFO] 76032 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0820, train/total_loss: 0.0822, train/util_ratio: 0.8750, train/run_time: 0.7282, lr: 0.0000, train/prefecth_time: 0.0058 
[2023-08-16 06:02:52,024 INFO] 76288 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3141, train/total_loss: 0.3143, train/util_ratio: 0.7539, train/run_time: 0.7677, lr: 0.0000, train/prefecth_time: 0.0054 
[2023-08-16 06:06:15,546 INFO] 76544 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0059, train/total_loss: 0.0061, train/util_ratio: 0.5022, train/run_time: 0.7847, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 06:09:37,681 INFO] 76800 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2054, train/total_loss: 0.2056, train/util_ratio: 1.0000, train/run_time: 0.7400, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 06:13:01,982 INFO] 77056 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0373, train/total_loss: 0.0375, train/util_ratio: 0.8750, train/run_time: 0.7926, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-16 06:16:25,260 INFO] 77312 iteration USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.2693, train/total_loss: 0.2704, train/util_ratio: 0.8981, train/run_time: 0.7527, lr: 0.0000, train/prefecth_time: 0.0052 
[2023-08-16 06:19:48,247 INFO] 77568 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2195, train/total_loss: 0.2197, train/util_ratio: 0.9527, train/run_time: 0.7623, lr: 0.0000, train/prefecth_time: 0.0054 
[2023-08-16 06:23:10,499 INFO] validating...
[2023-08-16 06:23:24,974 INFO] confusion matrix:
[[0.54       0.01333333 0.06       0.14666667 0.02       0.03333333
  0.         0.02666667 0.1        0.06      ]
 [0.         0.85333333 0.         0.         0.         0.12
  0.00666667 0.         0.         0.02      ]
 [0.1        0.00666667 0.66       0.08666667 0.         0.04
  0.00666667 0.         0.00666667 0.09333333]
 [0.         0.         0.00666667 0.76       0.06666667 0.00666667
  0.00666667 0.04       0.07333333 0.04      ]
 [0.02666667 0.         0.         0.06666667 0.82666667 0.
  0.00666667 0.02666667 0.03333333 0.01333333]
 [0.04       0.02666667 0.01333333 0.         0.01333333 0.87333333
  0.01333333 0.00666667 0.         0.01333333]
 [0.04       0.         0.00666667 0.01333333 0.00666667 0.
  0.82666667 0.         0.00666667 0.1       ]
 [0.02       0.00666667 0.06666667 0.08666667 0.2        0.02
  0.01333333 0.5        0.03333333 0.05333333]
 [0.04666667 0.         0.01333333 0.07333333 0.1        0.02
  0.         0.04666667 0.7        0.        ]
 [0.06       0.00666667 0.11333333 0.2        0.04       0.03333333
  0.07333333 0.06       0.03333333 0.38      ]]
[2023-08-16 06:23:26,828 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 06:23:28,678 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-16 06:23:28,679 INFO] 77824 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2982, train/total_loss: 0.2983, train/util_ratio: 0.8730, train/run_time: 0.7471, eval/loss: 2.3481, eval/top-1-acc: 0.6920, eval/balanced_acc: 0.6920, eval/precision: 0.6971, eval/recall: 0.6920, eval/F1: 0.6880, lr: 0.0000, train/prefecth_time: 0.0050 BEST_EVAL_ACC: 0.6920, at 77824 iters
[2023-08-16 06:26:53,406 INFO] 78080 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1190, train/total_loss: 0.1192, train/util_ratio: 0.8752, train/run_time: 0.7906, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 06:30:16,558 INFO] 78336 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3262, train/total_loss: 0.3264, train/util_ratio: 1.0000, train/run_time: 0.6434, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 06:33:40,382 INFO] 78592 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1607, train/total_loss: 0.1609, train/util_ratio: 0.9810, train/run_time: 0.7967, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 06:37:02,211 INFO] 78848 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.3973, train/total_loss: 0.3976, train/util_ratio: 1.0000, train/run_time: 0.6925, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-16 06:40:28,679 INFO] 79104 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.8512, train/total_loss: 0.8515, train/util_ratio: 0.8750, train/run_time: 0.8336, lr: 0.0000, train/prefecth_time: 0.0075 
[2023-08-16 06:43:50,112 INFO] 79360 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.1051, train/total_loss: 0.1056, train/util_ratio: 0.8750, train/run_time: 0.8142, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-16 06:47:12,174 INFO] 79616 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0010, train/total_loss: 0.0012, train/util_ratio: 0.7500, train/run_time: 0.7737, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-16 06:50:34,812 INFO] validating...
[2023-08-16 06:50:49,456 INFO] confusion matrix:
[[0.54       0.02       0.03333333 0.18666667 0.         0.01333333
  0.         0.03333333 0.11333333 0.06      ]
 [0.00666667 0.91333333 0.         0.         0.         0.07333333
  0.00666667 0.         0.         0.        ]
 [0.11333333 0.00666667 0.66666667 0.08       0.         0.03333333
  0.         0.00666667 0.         0.09333333]
 [0.         0.         0.02       0.75333333 0.02666667 0.00666667
  0.         0.08666667 0.08       0.02666667]
 [0.02666667 0.         0.         0.08666667 0.76666667 0.
  0.00666667 0.04666667 0.06       0.00666667]
 [0.05333333 0.02666667 0.02       0.         0.00666667 0.86666667
  0.00666667 0.01333333 0.         0.00666667]
 [0.04       0.         0.02666667 0.06666667 0.         0.00666667
  0.76       0.         0.00666667 0.09333333]
 [0.03333333 0.00666667 0.08       0.04       0.07333333 0.
  0.         0.67333333 0.04666667 0.04666667]
 [0.02666667 0.         0.02       0.04666667 0.06666667 0.02
  0.         0.06       0.74666667 0.01333333]
 [0.08       0.02666667 0.16       0.20666667 0.00666667 0.02
  0.06       0.06666667 0.03333333 0.34      ]]
[2023-08-16 06:50:51,478 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 06:50:53,331 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/model_best.pth
[2023-08-16 06:50:53,332 INFO] 79872 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.5272, train/total_loss: 0.5273, train/util_ratio: 1.0000, train/run_time: 0.8147, eval/loss: 2.4261, eval/top-1-acc: 0.7027, eval/balanced_acc: 0.7027, eval/precision: 0.7076, eval/recall: 0.7027, eval/F1: 0.7005, lr: 0.0000, train/prefecth_time: 0.0062 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 06:54:16,608 INFO] 80128 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0055, train/total_loss: 0.0056, train/util_ratio: 0.9029, train/run_time: 0.8249, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-16 06:57:40,467 INFO] 80384 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0138, train/total_loss: 0.0140, train/util_ratio: 0.8750, train/run_time: 0.7792, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 07:01:03,359 INFO] 80640 iteration USE_EMA: False, train/sup_loss: 0.0080, train/unsup_loss: 0.3603, train/total_loss: 0.3683, train/util_ratio: 1.0000, train/run_time: 0.7490, lr: 0.0000, train/prefecth_time: 0.0048 
[2023-08-16 07:04:25,670 INFO] 80896 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.1127, train/total_loss: 0.1132, train/util_ratio: 0.9913, train/run_time: 0.6907, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 07:07:50,214 INFO] 81152 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1115, train/total_loss: 0.1116, train/util_ratio: 0.8751, train/run_time: 0.7492, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 07:11:14,321 INFO] 81408 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.1089, train/total_loss: 0.1094, train/util_ratio: 0.7503, train/run_time: 0.8029, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-16 07:14:39,801 INFO] 81664 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1520, train/total_loss: 0.1523, train/util_ratio: 0.9762, train/run_time: 0.7579, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 07:18:02,718 INFO] validating...
[2023-08-16 07:18:17,334 INFO] confusion matrix:
[[0.48       0.01333333 0.11333333 0.18666667 0.00666667 0.02666667
  0.         0.03333333 0.1        0.04      ]
 [0.         0.88666667 0.         0.         0.         0.1
  0.00666667 0.         0.         0.00666667]
 [0.08       0.01333333 0.77333333 0.05333333 0.         0.04
  0.         0.00666667 0.         0.03333333]
 [0.         0.         0.02666667 0.71333333 0.05333333 0.00666667
  0.         0.1        0.06666667 0.03333333]
 [0.02666667 0.         0.         0.06666667 0.80666667 0.
  0.         0.05333333 0.04       0.00666667]
 [0.04       0.02666667 0.02       0.         0.01333333 0.88666667
  0.         0.01333333 0.         0.        ]
 [0.04       0.         0.02666667 0.1        0.01333333 0.
  0.58       0.00666667 0.01333333 0.22      ]
 [0.03333333 0.00666667 0.12       0.01333333 0.1        0.00666667
  0.         0.63333333 0.04666667 0.04      ]
 [0.02666667 0.         0.06       0.02666667 0.08       0.02
  0.         0.07333333 0.71333333 0.        ]
 [0.09333333 0.02       0.24666667 0.18666667 0.00666667 0.02666667
  0.02       0.03333333 0.05333333 0.31333333]]
[2023-08-16 07:18:19,177 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 07:18:19,178 INFO] 81920 iteration, USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1733, train/total_loss: 0.1736, train/util_ratio: 1.0000, train/run_time: 0.7616, eval/loss: 2.6139, eval/top-1-acc: 0.6787, eval/balanced_acc: 0.6787, eval/precision: 0.6896, eval/recall: 0.6787, eval/F1: 0.6742, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 07:21:43,572 INFO] 82176 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1316, train/total_loss: 0.1318, train/util_ratio: 0.6595, train/run_time: 0.8153, lr: 0.0000, train/prefecth_time: 0.0063 
[2023-08-16 07:25:05,844 INFO] 82432 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0469, train/total_loss: 0.0470, train/util_ratio: 0.8750, train/run_time: 0.7655, lr: 0.0000, train/prefecth_time: 0.0041 
[2023-08-16 07:28:28,668 INFO] 82688 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.3176, train/total_loss: 0.3181, train/util_ratio: 0.9060, train/run_time: 0.7422, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 07:31:51,231 INFO] 82944 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1556, train/total_loss: 0.1557, train/util_ratio: 1.0000, train/run_time: 0.7205, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 07:35:16,140 INFO] 83200 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4024, train/total_loss: 0.4025, train/util_ratio: 1.0000, train/run_time: 0.8350, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-16 07:38:40,899 INFO] 83456 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0885, train/total_loss: 0.0886, train/util_ratio: 0.8750, train/run_time: 0.7724, lr: 0.0000, train/prefecth_time: 0.0060 
[2023-08-16 07:42:02,495 INFO] 83712 iteration USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.0022, train/total_loss: 0.0037, train/util_ratio: 0.7500, train/run_time: 0.7471, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 07:45:25,662 INFO] validating...
[2023-08-16 07:45:40,271 INFO] confusion matrix:
[[0.43333333 0.01333333 0.06       0.12       0.05333333 0.02666667
  0.         0.03333333 0.17333333 0.08666667]
 [0.00666667 0.88       0.         0.         0.         0.08666667
  0.00666667 0.         0.         0.02      ]
 [0.06666667 0.00666667 0.71333333 0.03333333 0.00666667 0.04
  0.         0.         0.02666667 0.10666667]
 [0.         0.         0.02       0.61333333 0.10666667 0.00666667
  0.01333333 0.10666667 0.07333333 0.06      ]
 [0.01333333 0.         0.         0.02       0.86       0.
  0.00666667 0.04       0.04666667 0.01333333]
 [0.03333333 0.03333333 0.02       0.         0.02666667 0.86
  0.01333333 0.00666667 0.         0.00666667]
 [0.02       0.         0.02       0.00666667 0.02666667 0.
  0.81333333 0.00666667 0.00666667 0.1       ]
 [0.02666667 0.00666667 0.09333333 0.02       0.17333333 0.00666667
  0.00666667 0.56666667 0.04       0.06      ]
 [0.02666667 0.         0.03333333 0.01333333 0.11333333 0.02
  0.         0.07333333 0.71333333 0.00666667]
 [0.08       0.01333333 0.18       0.12666667 0.04       0.02
  0.08       0.04666667 0.04       0.37333333]]
[2023-08-16 07:45:42,122 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 07:45:42,123 INFO] 83968 iteration, USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1848, train/total_loss: 0.1851, train/util_ratio: 0.9906, train/run_time: 0.7212, eval/loss: 2.4408, eval/top-1-acc: 0.6827, eval/balanced_acc: 0.6827, eval/precision: 0.6817, eval/recall: 0.6827, eval/F1: 0.6772, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 07:49:06,020 INFO] 84224 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.1190, train/total_loss: 0.1198, train/util_ratio: 0.8750, train/run_time: 0.7530, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 07:52:29,915 INFO] 84480 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.4190, train/total_loss: 0.4192, train/util_ratio: 0.7545, train/run_time: 0.6620, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 07:55:51,182 INFO] 84736 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0609, train/total_loss: 0.0610, train/util_ratio: 1.0000, train/run_time: 0.7446, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 07:59:12,961 INFO] 84992 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2238, train/total_loss: 0.2239, train/util_ratio: 0.9412, train/run_time: 0.7291, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 08:02:38,078 INFO] 85248 iteration USE_EMA: False, train/sup_loss: 0.0037, train/unsup_loss: 0.6266, train/total_loss: 0.6303, train/util_ratio: 0.9983, train/run_time: 0.7353, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 08:05:59,298 INFO] 85504 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0891, train/total_loss: 0.0892, train/util_ratio: 1.0000, train/run_time: 0.6298, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 08:09:22,332 INFO] 85760 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3294, train/total_loss: 0.3295, train/util_ratio: 0.8158, train/run_time: 0.7881, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-16 08:12:45,540 INFO] validating...
[2023-08-16 08:13:00,105 INFO] confusion matrix:
[[0.6        0.00666667 0.00666667 0.16666667 0.00666667 0.02666667
  0.         0.02666667 0.08       0.08      ]
 [0.01333333 0.88666667 0.         0.         0.         0.07333333
  0.00666667 0.         0.         0.02      ]
 [0.13333333 0.00666667 0.54666667 0.06       0.         0.02
  0.00666667 0.00666667 0.01333333 0.20666667]
 [0.         0.         0.00666667 0.74666667 0.04666667 0.00666667
  0.         0.07333333 0.05333333 0.06666667]
 [0.02666667 0.         0.         0.06666667 0.8        0.
  0.00666667 0.06       0.02       0.02      ]
 [0.05333333 0.03333333 0.         0.         0.01333333 0.86666667
  0.01333333 0.00666667 0.         0.01333333]
 [0.06       0.         0.         0.00666667 0.00666667 0.
  0.82       0.         0.00666667 0.1       ]
 [0.04       0.01333333 0.04666667 0.03333333 0.09333333 0.00666667
  0.00666667 0.65333333 0.02       0.08666667]
 [0.06666667 0.         0.         0.05333333 0.10666667 0.02
  0.         0.09333333 0.64666667 0.01333333]
 [0.14       0.00666667 0.08       0.12666667 0.04       0.02
  0.07333333 0.04666667 0.02666667 0.44      ]]
[2023-08-16 08:13:01,943 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 08:13:01,944 INFO] 86016 iteration, USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3825, train/total_loss: 0.3827, train/util_ratio: 1.0000, train/run_time: 0.7969, eval/loss: 2.5485, eval/top-1-acc: 0.7007, eval/balanced_acc: 0.7007, eval/precision: 0.7121, eval/recall: 0.7007, eval/F1: 0.7022, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 08:16:27,572 INFO] 86272 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0194, train/total_loss: 0.0197, train/util_ratio: 1.0000, train/run_time: 0.7219, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-16 08:19:48,569 INFO] 86528 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2764, train/total_loss: 0.2766, train/util_ratio: 0.9866, train/run_time: 0.7317, lr: 0.0000, train/prefecth_time: 0.0072 
[2023-08-16 08:23:11,312 INFO] 86784 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.7444, train/total_loss: 0.7448, train/util_ratio: 0.8079, train/run_time: 0.8045, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 08:26:34,391 INFO] 87040 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0324, train/total_loss: 0.0326, train/util_ratio: 1.0000, train/run_time: 0.7589, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 08:29:59,909 INFO] 87296 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3568, train/total_loss: 0.3570, train/util_ratio: 0.9128, train/run_time: 0.7696, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-16 08:33:21,346 INFO] 87552 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0311, train/total_loss: 0.0312, train/util_ratio: 1.0000, train/run_time: 0.8034, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 08:36:46,057 INFO] 87808 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.4441, train/total_loss: 0.4445, train/util_ratio: 0.9473, train/run_time: 0.7807, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 08:40:08,713 INFO] validating...
[2023-08-16 08:40:23,480 INFO] confusion matrix:
[[0.57333333 0.00666667 0.04       0.15333333 0.         0.03333333
  0.         0.03333333 0.1        0.06      ]
 [0.         0.84666667 0.         0.         0.         0.12666667
  0.00666667 0.         0.         0.02      ]
 [0.12666667 0.00666667 0.71333333 0.04666667 0.         0.02
  0.         0.         0.         0.08666667]
 [0.         0.         0.02       0.72666667 0.04       0.01333333
  0.         0.07333333 0.09333333 0.03333333]
 [0.08       0.         0.         0.05333333 0.76666667 0.
  0.00666667 0.04       0.04       0.01333333]
 [0.04666667 0.02       0.02       0.         0.00666667 0.89333333
  0.         0.00666667 0.         0.00666667]
 [0.06       0.         0.02666667 0.06       0.         0.00666667
  0.70666667 0.00666667 0.01333333 0.12      ]
 [0.03333333 0.00666667 0.06666667 0.04       0.12666667 0.01333333
  0.         0.62666667 0.03333333 0.05333333]
 [0.04666667 0.         0.02       0.04666667 0.06666667 0.02
  0.         0.06666667 0.72666667 0.00666667]
 [0.09333333 0.00666667 0.17333333 0.15333333 0.         0.02
  0.03333333 0.08       0.04666667 0.39333333]]
[2023-08-16 08:40:25,315 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 08:40:25,316 INFO] 88064 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3318, train/total_loss: 0.3319, train/util_ratio: 0.7500, train/run_time: 0.7318, eval/loss: 2.5617, eval/top-1-acc: 0.6973, eval/balanced_acc: 0.6973, eval/precision: 0.7053, eval/recall: 0.6973, eval/F1: 0.6972, lr: 0.0000, train/prefecth_time: 0.0070 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 08:43:50,723 INFO] 88320 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 1.0165, train/total_loss: 1.0167, train/util_ratio: 0.9364, train/run_time: 0.6911, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 08:47:14,615 INFO] 88576 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0820, train/total_loss: 0.0821, train/util_ratio: 0.8750, train/run_time: 0.8291, lr: 0.0000, train/prefecth_time: 0.0054 
[2023-08-16 08:50:36,087 INFO] 88832 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1307, train/total_loss: 0.1309, train/util_ratio: 1.0000, train/run_time: 0.6921, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-16 08:53:58,361 INFO] 89088 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0709, train/total_loss: 0.0710, train/util_ratio: 0.8750, train/run_time: 0.7973, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 08:57:22,719 INFO] 89344 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0132, train/total_loss: 0.0135, train/util_ratio: 0.6574, train/run_time: 0.7246, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 09:00:46,372 INFO] 89600 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0179, train/total_loss: 0.0181, train/util_ratio: 1.0000, train/run_time: 0.8430, lr: 0.0000, train/prefecth_time: 0.0054 
[2023-08-16 09:04:08,658 INFO] 89856 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.1796, train/total_loss: 0.1800, train/util_ratio: 0.9785, train/run_time: 0.7422, lr: 0.0000, train/prefecth_time: 0.0047 
[2023-08-16 09:07:31,210 INFO] validating...
[2023-08-16 09:07:45,720 INFO] confusion matrix:
[[0.54666667 0.00666667 0.08666667 0.11333333 0.00666667 0.02666667
  0.         0.04       0.11333333 0.06      ]
 [0.00666667 0.88       0.         0.         0.         0.09333333
  0.00666667 0.         0.         0.01333333]
 [0.10666667 0.00666667 0.76666667 0.01333333 0.         0.02
  0.         0.         0.02       0.06666667]
 [0.         0.         0.05333333 0.58666667 0.1        0.00666667
  0.         0.1        0.09333333 0.06      ]
 [0.02666667 0.         0.         0.02       0.85333333 0.
  0.00666667 0.04       0.03333333 0.02      ]
 [0.04666667 0.02       0.02       0.         0.02       0.84666667
  0.02       0.01333333 0.         0.01333333]
 [0.04       0.         0.03333333 0.02666667 0.02       0.
  0.74666667 0.00666667 0.01333333 0.11333333]
 [0.04       0.00666667 0.10666667 0.01333333 0.17333333 0.
  0.00666667 0.57333333 0.03333333 0.04666667]
 [0.04       0.         0.05333333 0.         0.09333333 0.02
  0.         0.06       0.72666667 0.00666667]
 [0.07333333 0.00666667 0.23333333 0.1        0.02666667 0.01333333
  0.04       0.07333333 0.05333333 0.38      ]]
[2023-08-16 09:07:47,598 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 09:07:47,598 INFO] 90112 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0383, train/total_loss: 0.0384, train/util_ratio: 0.8947, train/run_time: 0.7924, eval/loss: 2.6003, eval/top-1-acc: 0.6907, eval/balanced_acc: 0.6907, eval/precision: 0.6954, eval/recall: 0.6907, eval/F1: 0.6881, lr: 0.0000, train/prefecth_time: 0.0055 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 09:11:12,649 INFO] 90368 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2324, train/total_loss: 0.2325, train/util_ratio: 0.7500, train/run_time: 0.8002, lr: 0.0000, train/prefecth_time: 0.0021 
[2023-08-16 09:14:35,345 INFO] 90624 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2198, train/total_loss: 0.2199, train/util_ratio: 0.9032, train/run_time: 0.8190, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-16 09:18:02,343 INFO] 90880 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2272, train/total_loss: 0.2274, train/util_ratio: 0.8938, train/run_time: 0.7035, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 09:21:25,434 INFO] 91136 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2101, train/total_loss: 0.2102, train/util_ratio: 0.9023, train/run_time: 0.7671, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 09:24:50,475 INFO] 91392 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2894, train/total_loss: 0.2895, train/util_ratio: 0.8680, train/run_time: 0.6991, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 09:28:13,539 INFO] 91648 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2288, train/total_loss: 0.2289, train/util_ratio: 0.7425, train/run_time: 0.5584, lr: 0.0000, train/prefecth_time: 0.0074 
[2023-08-16 09:31:36,658 INFO] 91904 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.0098, train/total_loss: 0.0104, train/util_ratio: 0.7241, train/run_time: 0.7437, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-16 09:35:03,213 INFO] validating...
[2023-08-16 09:35:17,742 INFO] confusion matrix:
[[0.60666667 0.         0.03333333 0.07333333 0.02       0.03333333
  0.04666667 0.04       0.10666667 0.04      ]
 [0.         0.86666667 0.         0.         0.         0.10666667
  0.00666667 0.         0.         0.02      ]
 [0.12       0.00666667 0.74       0.01333333 0.00666667 0.02
  0.00666667 0.         0.02       0.06666667]
 [0.         0.         0.04       0.48       0.11333333 0.01333333
  0.09333333 0.12666667 0.11333333 0.02      ]
 [0.02666667 0.         0.         0.02       0.86       0.
  0.00666667 0.04       0.03333333 0.01333333]
 [0.06       0.02       0.01333333 0.         0.00666667 0.86666667
  0.02666667 0.00666667 0.         0.        ]
 [0.06       0.         0.02666667 0.         0.00666667 0.
  0.86       0.00666667 0.         0.04      ]
 [0.03333333 0.00666667 0.08666667 0.00666667 0.18       0.00666667
  0.04       0.57333333 0.02       0.04666667]
 [0.07333333 0.         0.02666667 0.01333333 0.10666667 0.02
  0.         0.06666667 0.69333333 0.        ]
 [0.13333333 0.00666667 0.15333333 0.09333333 0.04       0.02
  0.18666667 0.06       0.06       0.24666667]]
[2023-08-16 09:35:19,753 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 09:35:19,754 INFO] 92160 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0392, train/total_loss: 0.0393, train/util_ratio: 0.8750, train/run_time: 0.7656, eval/loss: 2.5841, eval/top-1-acc: 0.6793, eval/balanced_acc: 0.6793, eval/precision: 0.6748, eval/recall: 0.6793, eval/F1: 0.6673, lr: 0.0000, train/prefecth_time: 0.0050 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 09:38:46,296 INFO] 92416 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3458, train/total_loss: 0.3460, train/util_ratio: 0.8058, train/run_time: 0.7830, lr: 0.0000, train/prefecth_time: 0.0047 
[2023-08-16 09:42:10,008 INFO] 92672 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0752, train/total_loss: 0.0753, train/util_ratio: 1.0000, train/run_time: 0.7389, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 09:45:34,748 INFO] 92928 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3799, train/total_loss: 0.3800, train/util_ratio: 0.9131, train/run_time: 0.7242, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-16 09:48:57,336 INFO] 93184 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4954, train/total_loss: 0.4955, train/util_ratio: 0.7466, train/run_time: 0.7721, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 09:52:22,001 INFO] 93440 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0763, train/total_loss: 0.0765, train/util_ratio: 1.0000, train/run_time: 0.7565, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 09:55:44,417 INFO] 93696 iteration USE_EMA: False, train/sup_loss: 0.0048, train/unsup_loss: 0.4622, train/total_loss: 0.4670, train/util_ratio: 0.9795, train/run_time: 0.7833, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-16 09:59:06,745 INFO] 93952 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1861, train/total_loss: 0.1862, train/util_ratio: 0.8730, train/run_time: 0.7816, lr: 0.0000, train/prefecth_time: 0.0078 
[2023-08-16 10:02:30,646 INFO] validating...
[2023-08-16 10:02:45,425 INFO] confusion matrix:
[[0.54666667 0.01333333 0.04       0.10666667 0.00666667 0.02666667
  0.01333333 0.04       0.11333333 0.09333333]
 [0.         0.88666667 0.         0.         0.         0.08666667
  0.00666667 0.         0.         0.02      ]
 [0.12666667 0.01333333 0.70666667 0.02666667 0.         0.02666667
  0.         0.01333333 0.02666667 0.06      ]
 [0.         0.         0.04       0.58       0.02666667 0.01333333
  0.02       0.16       0.12666667 0.03333333]
 [0.04       0.         0.         0.02       0.78       0.
  0.00666667 0.07333333 0.06       0.02      ]
 [0.04666667 0.03333333 0.00666667 0.         0.00666667 0.88
  0.00666667 0.00666667 0.         0.01333333]
 [0.03333333 0.         0.02666667 0.01333333 0.         0.00666667
  0.82666667 0.00666667 0.01333333 0.07333333]
 [0.05333333 0.00666667 0.07333333 0.00666667 0.10666667 0.00666667
  0.00666667 0.66666667 0.03333333 0.04      ]
 [0.05333333 0.         0.01333333 0.00666667 0.06666667 0.02
  0.         0.07333333 0.76       0.00666667]
 [0.08666667 0.00666667 0.14666667 0.1        0.         0.01333333
  0.08       0.09333333 0.08666667 0.38666667]]
[2023-08-16 10:02:47,301 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 10:02:47,302 INFO] 94208 iteration, USE_EMA: False, train/sup_loss: 0.0031, train/unsup_loss: 0.3215, train/total_loss: 0.3247, train/util_ratio: 1.0000, train/run_time: 0.7484, eval/loss: 2.5036, eval/top-1-acc: 0.7020, eval/balanced_acc: 0.7020, eval/precision: 0.7007, eval/recall: 0.7020, eval/F1: 0.6989, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 10:06:12,745 INFO] 94464 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1798, train/total_loss: 0.1801, train/util_ratio: 0.8765, train/run_time: 0.7727, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 10:09:36,903 INFO] 94720 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2148, train/total_loss: 0.2149, train/util_ratio: 0.7845, train/run_time: 0.7753, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 10:12:59,848 INFO] 94976 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0107, train/total_loss: 0.0108, train/util_ratio: 1.0000, train/run_time: 0.7418, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 10:16:23,080 INFO] 95232 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0498, train/total_loss: 0.0499, train/util_ratio: 0.7502, train/run_time: 0.7736, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 10:19:48,120 INFO] 95488 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0016, train/total_loss: 0.0018, train/util_ratio: 1.0000, train/run_time: 0.7807, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 10:23:11,348 INFO] 95744 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2093, train/total_loss: 0.2094, train/util_ratio: 0.9323, train/run_time: 0.7410, lr: 0.0000, train/prefecth_time: 0.0072 
[2023-08-16 10:26:41,044 INFO] 96000 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1331, train/total_loss: 0.1332, train/util_ratio: 0.7500, train/run_time: 1.2039, lr: 0.0000, train/prefecth_time: 0.0346 
[2023-08-16 10:30:09,555 INFO] validating...
[2023-08-16 10:30:24,152 INFO] confusion matrix:
[[0.57333333 0.01333333 0.04       0.13333333 0.00666667 0.02
  0.         0.04       0.10666667 0.06666667]
 [0.01333333 0.88666667 0.         0.         0.         0.07333333
  0.00666667 0.         0.         0.02      ]
 [0.1        0.01333333 0.70666667 0.04       0.         0.02666667
  0.         0.         0.02       0.09333333]
 [0.         0.         0.02666667 0.71333333 0.02666667 0.00666667
  0.         0.1        0.1        0.02666667]
 [0.02666667 0.         0.         0.08       0.79333333 0.
  0.         0.05333333 0.04       0.00666667]
 [0.05333333 0.02666667 0.00666667 0.         0.00666667 0.88666667
  0.         0.00666667 0.         0.01333333]
 [0.03333333 0.         0.02       0.08666667 0.02       0.
  0.69333333 0.00666667 0.01333333 0.12666667]
 [0.03333333 0.00666667 0.08       0.02666667 0.11333333 0.00666667
  0.         0.64       0.03333333 0.06      ]
 [0.04       0.         0.03333333 0.04       0.07333333 0.02
  0.         0.06       0.72666667 0.00666667]
 [0.08       0.00666667 0.17333333 0.18       0.00666667 0.02
  0.04       0.05333333 0.06       0.38      ]]
[2023-08-16 10:30:26,041 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 10:30:26,041 INFO] 96256 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.6906, train/total_loss: 0.6908, train/util_ratio: 1.0000, train/run_time: 0.7265, eval/loss: 2.6656, eval/top-1-acc: 0.7000, eval/balanced_acc: 0.7000, eval/precision: 0.7064, eval/recall: 0.7000, eval/F1: 0.6993, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 10:33:51,177 INFO] 96512 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0805, train/total_loss: 0.0805, train/util_ratio: 0.6890, train/run_time: 0.7481, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 10:37:31,493 INFO] 96768 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1377, train/total_loss: 0.1378, train/util_ratio: 0.9357, train/run_time: 0.7671, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 10:40:55,958 INFO] 97024 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2874, train/total_loss: 0.2875, train/util_ratio: 0.9389, train/run_time: 0.7122, lr: 0.0000, train/prefecth_time: 0.0050 
[2023-08-16 10:44:48,402 INFO] 97280 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1618, train/total_loss: 0.1618, train/util_ratio: 0.8846, train/run_time: 0.7692, lr: 0.0000, train/prefecth_time: 0.0079 
[2023-08-16 10:48:16,546 INFO] 97536 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1506, train/total_loss: 0.1507, train/util_ratio: 0.8750, train/run_time: 0.7912, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 10:51:42,291 INFO] 97792 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0344, train/total_loss: 0.0345, train/util_ratio: 1.0000, train/run_time: 0.7593, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 10:55:05,293 INFO] 98048 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0738, train/total_loss: 0.0738, train/util_ratio: 1.0000, train/run_time: 0.7714, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 10:58:38,248 INFO] validating...
[2023-08-16 10:58:51,868 INFO] confusion matrix:
[[0.56       0.         0.03333333 0.12       0.01333333 0.04
  0.         0.03333333 0.10666667 0.09333333]
 [0.         0.86       0.         0.         0.         0.11333333
  0.00666667 0.         0.         0.02      ]
 [0.09333333 0.01333333 0.64       0.05333333 0.         0.03333333
  0.         0.         0.02       0.14666667]
 [0.         0.         0.01333333 0.66666667 0.06666667 0.01333333
  0.         0.10666667 0.08       0.05333333]
 [0.02666667 0.         0.         0.04666667 0.84       0.
  0.         0.04       0.03333333 0.01333333]
 [0.05333333 0.02666667 0.         0.         0.00666667 0.89333333
  0.         0.00666667 0.         0.01333333]
 [0.03333333 0.         0.02666667 0.02666667 0.01333333 0.00666667
  0.73333333 0.00666667 0.01333333 0.14      ]
 [0.03333333 0.00666667 0.05333333 0.04666667 0.14       0.01333333
  0.00666667 0.6        0.03333333 0.06666667]
 [0.04       0.         0.02666667 0.03333333 0.08666667 0.02
  0.         0.06666667 0.70666667 0.02      ]
 [0.08       0.02       0.13333333 0.12       0.02       0.02
  0.04666667 0.07333333 0.04666667 0.44      ]]
[2023-08-16 10:58:53,926 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 10:58:53,927 INFO] 98304 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0218, train/total_loss: 0.0219, train/util_ratio: 1.0000, train/run_time: 0.7594, eval/loss: 2.5889, eval/top-1-acc: 0.6940, eval/balanced_acc: 0.6940, eval/precision: 0.6992, eval/recall: 0.6940, eval/F1: 0.6939, lr: 0.0000, train/prefecth_time: 0.0049 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 11:02:21,924 INFO] 98560 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0067, train/total_loss: 0.0069, train/util_ratio: 0.8750, train/run_time: 0.7587, lr: 0.0000, train/prefecth_time: 0.0072 
[2023-08-16 11:05:47,473 INFO] 98816 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0053, train/total_loss: 0.0054, train/util_ratio: 0.6253, train/run_time: 0.7896, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 11:09:11,465 INFO] 99072 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.6227, train/total_loss: 0.6228, train/util_ratio: 0.8748, train/run_time: 0.7391, lr: 0.0000, train/prefecth_time: 0.0051 
[2023-08-16 11:12:38,563 INFO] 99328 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2703, train/total_loss: 0.2705, train/util_ratio: 0.8677, train/run_time: 0.7574, lr: 0.0000, train/prefecth_time: 0.0057 
[2023-08-16 11:16:06,077 INFO] 99584 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2269, train/total_loss: 0.2270, train/util_ratio: 0.8485, train/run_time: 0.7464, lr: 0.0000, train/prefecth_time: 0.0070 
[2023-08-16 11:19:31,148 INFO] 99840 iteration USE_EMA: False, train/sup_loss: 0.0035, train/unsup_loss: 0.2661, train/total_loss: 0.2696, train/util_ratio: 1.0000, train/run_time: 0.7289, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-16 11:22:57,610 INFO] 100096 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.5944, train/total_loss: 0.5945, train/util_ratio: 0.8724, train/run_time: 0.8030, lr: 0.0000, train/prefecth_time: 0.0139 
[2023-08-16 11:26:23,523 INFO] validating...
[2023-08-16 11:26:38,130 INFO] confusion matrix:
[[0.55333333 0.00666667 0.05333333 0.12       0.00666667 0.03333333
  0.         0.03333333 0.07333333 0.12      ]
 [0.         0.90666667 0.         0.         0.         0.08
  0.00666667 0.         0.         0.00666667]
 [0.1        0.00666667 0.70666667 0.02666667 0.         0.02666667
  0.         0.         0.01333333 0.12      ]
 [0.         0.         0.04       0.69333333 0.02666667 0.00666667
  0.         0.08       0.1        0.05333333]
 [0.02666667 0.         0.         0.07333333 0.79333333 0.
  0.         0.05333333 0.03333333 0.02      ]
 [0.05333333 0.02666667 0.00666667 0.         0.00666667 0.88666667
  0.         0.00666667 0.         0.01333333]
 [0.03333333 0.         0.02666667 0.04666667 0.         0.00666667
  0.55333333 0.         0.01333333 0.32      ]
 [0.04       0.00666667 0.08       0.03333333 0.11333333 0.00666667
  0.         0.62       0.03333333 0.06666667]
 [0.06       0.         0.04666667 0.02666667 0.08       0.02
  0.         0.05333333 0.69333333 0.02      ]
 [0.07333333 0.02       0.21333333 0.12666667 0.00666667 0.01333333
  0.02       0.04666667 0.03333333 0.44666667]]
[2023-08-16 11:26:40,071 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 11:26:40,072 INFO] 100352 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0134, train/total_loss: 0.0135, train/util_ratio: 0.8750, train/run_time: 0.7724, eval/loss: 2.6714, eval/top-1-acc: 0.6853, eval/balanced_acc: 0.6853, eval/precision: 0.7038, eval/recall: 0.6853, eval/F1: 0.6878, lr: 0.0000, train/prefecth_time: 0.0047 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 11:30:08,068 INFO] 100608 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4679, train/total_loss: 0.4680, train/util_ratio: 1.0000, train/run_time: 0.7900, lr: 0.0000, train/prefecth_time: 0.0069 
[2023-08-16 11:33:33,019 INFO] 100864 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0073, train/total_loss: 0.0074, train/util_ratio: 0.6255, train/run_time: 0.7248, lr: 0.0000, train/prefecth_time: 0.0071 
[2023-08-16 11:36:55,820 INFO] 101120 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0093, train/total_loss: 0.0093, train/util_ratio: 0.8770, train/run_time: 0.8074, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 11:40:21,895 INFO] 101376 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0019, train/total_loss: 0.0020, train/util_ratio: 1.0000, train/run_time: 0.7777, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-16 11:43:48,264 INFO] 101632 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3846, train/total_loss: 0.3847, train/util_ratio: 0.8750, train/run_time: 0.7979, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 11:47:01,269 INFO] 101888 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1054, train/total_loss: 0.1055, train/util_ratio: 1.0000, train/run_time: 0.5049, lr: 0.0000, train/prefecth_time: 0.0048 
[2023-08-16 11:49:37,101 INFO] 102144 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1103, train/total_loss: 0.1104, train/util_ratio: 0.8756, train/run_time: 0.6154, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-16 11:52:11,427 INFO] validating...
[2023-08-16 11:52:23,507 INFO] confusion matrix:
[[0.56666667 0.02       0.03333333 0.08       0.         0.01333333
  0.         0.05333333 0.11333333 0.12      ]
 [0.         0.91333333 0.         0.         0.         0.07333333
  0.00666667 0.         0.         0.00666667]
 [0.10666667 0.01333333 0.70666667 0.01333333 0.         0.02666667
  0.         0.00666667 0.01333333 0.11333333]
 [0.00666667 0.         0.02       0.6        0.01333333 0.00666667
  0.         0.14       0.14666667 0.06666667]
 [0.02666667 0.         0.         0.06       0.76       0.
  0.         0.08       0.05333333 0.02      ]
 [0.05333333 0.04666667 0.00666667 0.         0.00666667 0.87333333
  0.         0.00666667 0.         0.00666667]
 [0.04       0.         0.02666667 0.03333333 0.         0.00666667
  0.72666667 0.00666667 0.01333333 0.14666667]
 [0.04       0.00666667 0.07333333 0.00666667 0.11333333 0.00666667
  0.         0.68       0.02666667 0.04666667]
 [0.06       0.         0.03333333 0.01333333 0.07333333 0.02
  0.         0.08666667 0.7        0.01333333]
 [0.08       0.02       0.16       0.09333333 0.         0.02666667
  0.04       0.13333333 0.05333333 0.39333333]]
[2023-08-16 11:52:25,563 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 11:52:25,564 INFO] 102400 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0372, train/total_loss: 0.0373, train/util_ratio: 1.0000, train/run_time: 0.5722, eval/loss: 2.6113, eval/top-1-acc: 0.6920, eval/balanced_acc: 0.6920, eval/precision: 0.6978, eval/recall: 0.6920, eval/F1: 0.6925, lr: 0.0000, train/prefecth_time: 0.0042 BEST_EVAL_ACC: 0.7027, at 79872 iters
[2023-08-16 11:52:28,232 INFO] model saved: /liuzicheng/jwy/saved_models/usb_audio/softmatch_gtzan_100_0/latest_model.pth
[2023-08-16 11:52:39,151 INFO] Model loaded
[2023-08-16 11:52:39,167 INFO] additional parameter loaded
[2023-08-16 11:52:51,058 INFO] confusion matrix:
[[0.60666667 0.02       0.02666667 0.08       0.         0.02666667
  0.00666667 0.02       0.08       0.13333333]
 [0.02       0.85333333 0.00666667 0.         0.         0.10666667
  0.00666667 0.00666667 0.         0.        ]
 [0.05333333 0.         0.76       0.04       0.         0.
  0.         0.01333333 0.00666667 0.12666667]
 [0.         0.02       0.00666667 0.56666667 0.02       0.
  0.         0.14       0.2        0.04666667]
 [0.02666667 0.         0.         0.02       0.73333333 0.00666667
  0.         0.16       0.04666667 0.00666667]
 [0.04       0.03333333 0.         0.         0.01333333 0.89333333
  0.         0.02       0.         0.        ]
 [0.01333333 0.         0.00666667 0.07333333 0.00666667 0.
  0.75333333 0.01333333 0.01333333 0.12      ]
 [0.02666667 0.01333333 0.04666667 0.02666667 0.12666667 0.00666667
  0.02       0.68666667 0.01333333 0.03333333]
 [0.04       0.         0.02666667 0.00666667 0.08666667 0.00666667
  0.         0.06       0.73333333 0.04      ]
 [0.08       0.01333333 0.18666667 0.07333333 0.         0.
  0.05333333 0.06666667 0.03333333 0.49333333]]
[2023-08-16 11:52:51,064 INFO] Model result - eval/best_acc : 0.7026666666666667
[2023-08-16 11:52:51,064 INFO] Model result - eval/best_it : 79871
