[2023-08-27 13:57:48,519 INFO] Use GPU: 0 for training
[2023-08-27 13:57:48,882 INFO] unlabeled data number: 21588, labeled data number 50
[2023-08-27 13:57:55,195 INFO] Create train and test data loaders
[2023-08-27 13:57:55,196 INFO] [!] data loader keys: dict_keys(['train_lb', 'train_ulb', 'eval'])
[2023-08-27 13:57:55,998 INFO] Create optimizer and scheduler
[2023-08-27 13:57:56,001 INFO] Number of Trainable Params: 21402250
[2023-08-27 13:58:00,677 INFO] Arguments: Namespace(save_dir='./saved_models/usb_cv/', save_name='freematch_eurosat_40_0', resume=True, load_path='./saved_models/usb_cv//freematch_eurosat_40_0/latest_model.pth', overwrite=True, use_tensorboard=True, use_wandb=False, use_aim=False, epoch=200, num_train_iter=204800, num_warmup_iter=5120, num_eval_iter=2048, num_log_iter=256, num_labels=50, batch_size=1, uratio=1, eval_batch_size=16, ema_m=0.9999, ulb_loss_ratio=1.0, optim='AdamW', lr=5e-05, momentum=0.9, weight_decay=0.0005, layer_decay=1.0, net='vit_small_patch2_32', net_from_name=False, use_pretrain=True, pretrain_path='https://github.com/microsoft/Semi-supervised-learning/releases/download/v.0.0.0/vit_small_patch2_32_mlp_im_1k_32.pth', algorithm='freematch', use_cat=True, amp=False, clip_grad=0, imb_algorithm=None, data_dir='/usr/data/data', dataset='eurosat', 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=4.0, sample_rate=16000, world_size=8, rank=0, dist_url='tcp://127.0.0.1:29476', dist_backend='nccl', seed=2, gpu=0, multiprocessing_distributed=True, c='/usr/data/jwy/otherbaseline-main/config/usb_cv/freematch/freematch_eurosat_40_0.yaml', hard_label=True, T=0.5, ema_p=0.999, ent_loss_ratio=0.001, use_quantile=False, clip_thresh=False, clip=0.0, distributed=True, ulb_dest_len=21588, lb_dest_len=50)
[2023-08-27 13:58:00,677 INFO] Resume load path ./saved_models/usb_cv//freematch_eurosat_40_0/latest_model.pth does not exist
[2023-08-27 13:58:00,678 INFO] Model training
[2023-08-27 13:59:31,612 INFO] 256 iteration USE_EMA: True, train/sup_loss: 2.7781, train/unsup_loss: 0.7490, train/total_loss: 3.5009, train/util_ratio: 1.0000, train/run_time: 0.1609, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 14:00:21,485 INFO] 512 iteration USE_EMA: True, train/sup_loss: 1.2371, train/unsup_loss: 1.5949, train/total_loss: 2.8112, train/util_ratio: 1.0000, train/run_time: 0.1722, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 14:01:11,213 INFO] 768 iteration USE_EMA: True, train/sup_loss: 0.7999, train/unsup_loss: 1.7974, train/total_loss: 2.5831, train/util_ratio: 1.0000, train/run_time: 0.1659, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 14:02:00,840 INFO] 1024 iteration USE_EMA: True, train/sup_loss: 0.1875, train/unsup_loss: 1.0009, train/total_loss: 1.1761, train/util_ratio: 1.0000, train/run_time: 0.1664, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 14:03:33,799 INFO] 1280 iteration USE_EMA: True, train/sup_loss: 0.1078, train/unsup_loss: 1.2927, train/total_loss: 1.3893, train/util_ratio: 1.0000, train/run_time: 0.1688, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 14:04:23,351 INFO] 1536 iteration USE_EMA: True, train/sup_loss: 0.2224, train/unsup_loss: 0.7822, train/total_loss: 0.9900, train/util_ratio: 1.0000, train/run_time: 0.1583, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 14:05:13,243 INFO] 1792 iteration USE_EMA: True, train/sup_loss: 0.0445, train/unsup_loss: 0.2544, train/total_loss: 0.2893, train/util_ratio: 1.0000, train/run_time: 0.1759, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 14:06:03,461 INFO] validating...
[2023-08-27 14:06:28,107 INFO] confusion matrix:
[[0.185      0.         0.16       0.         0.         0.
  0.01333333 0.00166667 0.13666667 0.50333333]
 [0.         0.         0.065      0.         0.         0.
  0.00166667 0.         0.00833333 0.925     ]
 [0.         0.         0.46833333 0.         0.         0.
  0.00333333 0.         0.03166667 0.49666667]
 [0.012      0.         0.128      0.         0.         0.
  0.008      0.         0.182      0.67      ]
 [0.05       0.         0.026      0.         0.         0.
  0.         0.         0.004      0.92      ]
 [0.0075     0.         0.235      0.         0.         0.
  0.0025     0.         0.2025     0.5525    ]
 [0.05       0.         0.468      0.         0.         0.
  0.056      0.002      0.062      0.362     ]
 [0.005      0.         0.09       0.         0.         0.
  0.00333333 0.00333333 0.02333333 0.875     ]
 [0.01402806 0.         0.06412826 0.         0.         0.
  0.00200401 0.         0.24248497 0.67735471]
 [0.         0.         0.00333333 0.         0.         0.
  0.         0.         0.01       0.98666667]]
[2023-08-27 14:06:28,744 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 14:06:29,487 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/model_best.pth
[2023-08-27 14:06:29,488 INFO] 2048 iteration, USE_EMA: True, train/sup_loss: 0.0291, train/unsup_loss: 0.2677, train/total_loss: 0.2840, train/util_ratio: 0.7500, train/run_time: 0.1659, eval/loss: 2.9102, eval/top-1-acc: 0.2102, eval/balanced_acc: 0.1942, eval/precision: 0.2445, eval/recall: 0.1942, eval/F1: 0.1289, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.2102, at 2048 iters
[2023-08-27 14:08:01,365 INFO] 2304 iteration USE_EMA: True, train/sup_loss: 0.0141, train/unsup_loss: 0.1567, train/total_loss: 0.1562, train/util_ratio: 0.8750, train/run_time: 0.1569, lr: 0.0000, train/prefecth_time: 0.0051 
[2023-08-27 14:08:51,166 INFO] 2560 iteration USE_EMA: True, train/sup_loss: 0.0097, train/unsup_loss: 0.3512, train/total_loss: 0.3464, train/util_ratio: 0.8750, train/run_time: 0.1638, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 14:09:40,574 INFO] 2816 iteration USE_EMA: True, train/sup_loss: 0.0248, train/unsup_loss: 0.1623, train/total_loss: 0.1696, train/util_ratio: 0.8750, train/run_time: 0.1736, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 14:10:30,642 INFO] 3072 iteration USE_EMA: True, train/sup_loss: 0.0060, train/unsup_loss: 0.1175, train/total_loss: 0.1064, train/util_ratio: 0.7500, train/run_time: 0.1627, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 14:12:03,370 INFO] 3328 iteration USE_EMA: True, train/sup_loss: 0.0045, train/unsup_loss: 0.0544, train/total_loss: 0.0469, train/util_ratio: 1.0000, train/run_time: 0.1847, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 14:12:52,831 INFO] 3584 iteration USE_EMA: True, train/sup_loss: 0.0059, train/unsup_loss: 0.2431, train/total_loss: 0.2393, train/util_ratio: 1.0000, train/run_time: 0.1598, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 14:13:42,577 INFO] 3840 iteration USE_EMA: True, train/sup_loss: 0.0062, train/unsup_loss: 0.7796, train/total_loss: 0.7737, train/util_ratio: 1.0000, train/run_time: 0.1715, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 14:14:32,402 INFO] validating...
[2023-08-27 14:14:56,741 INFO] confusion matrix:
[[0.765      0.         0.09333333 0.         0.         0.
  0.03166667 0.         0.08666667 0.02333333]
 [0.00166667 0.         0.31833333 0.         0.         0.
  0.005      0.08       0.05333333 0.54166667]
 [0.         0.         0.92       0.         0.         0.
  0.00333333 0.00833333 0.01333333 0.055     ]
 [0.05       0.         0.18       0.026      0.         0.
  0.044      0.012      0.622      0.066     ]
 [0.162      0.         0.076      0.022      0.03       0.
  0.02       0.012      0.058      0.62      ]
 [0.095      0.         0.43       0.         0.         0.
  0.0425     0.005      0.365      0.0625    ]
 [0.096      0.         0.34       0.         0.         0.
  0.532      0.002      0.016      0.014     ]
 [0.01166667 0.         0.10833333 0.         0.         0.
  0.01       0.77166667 0.01       0.08833333]
 [0.03006012 0.         0.06012024 0.         0.         0.
  0.00200401 0.00400802 0.82965932 0.0741483 ]
 [0.         0.         0.015      0.         0.         0.
  0.00166667 0.         0.02833333 0.955     ]]
[2023-08-27 14:14:57,514 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 14:14:58,691 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/model_best.pth
[2023-08-27 14:14:58,692 INFO] 4096 iteration, USE_EMA: True, train/sup_loss: 0.0028, train/unsup_loss: 0.2305, train/total_loss: 0.2187, train/util_ratio: 1.0000, train/run_time: 0.1586, eval/loss: 1.7645, eval/top-1-acc: 0.5103, eval/balanced_acc: 0.4829, eval/precision: 0.5071, eval/recall: 0.4829, eval/F1: 0.3948, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.5103, at 4096 iters
[2023-08-27 14:16:30,485 INFO] 4352 iteration USE_EMA: True, train/sup_loss: 0.0092, train/unsup_loss: 0.0563, train/total_loss: 0.0532, train/util_ratio: 1.0000, train/run_time: 0.1564, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 14:17:20,027 INFO] 4608 iteration USE_EMA: True, train/sup_loss: 0.0144, train/unsup_loss: 0.4586, train/total_loss: 0.4609, train/util_ratio: 1.0000, train/run_time: 0.1669, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 14:18:09,495 INFO] 4864 iteration USE_EMA: True, train/sup_loss: 0.0007, train/unsup_loss: 0.0158, train/total_loss: 0.0045, train/util_ratio: 1.0000, train/run_time: 0.1680, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 14:18:59,278 INFO] 5120 iteration USE_EMA: True, train/sup_loss: 0.0008, train/unsup_loss: 0.0112, train/total_loss: 0.0025, train/util_ratio: 1.0000, train/run_time: 0.1574, lr: 0.0001, train/prefecth_time: 0.0028 
[2023-08-27 14:20:32,549 INFO] 5376 iteration USE_EMA: True, train/sup_loss: 0.0009, train/unsup_loss: 0.1100, train/total_loss: 0.0987, train/util_ratio: 0.8750, train/run_time: 0.1705, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 14:21:22,048 INFO] 5632 iteration USE_EMA: True, train/sup_loss: 0.0159, train/unsup_loss: 0.2913, train/total_loss: 0.2926, train/util_ratio: 1.0000, train/run_time: 0.1632, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 14:22:11,183 INFO] 5888 iteration USE_EMA: True, train/sup_loss: 0.0120, train/unsup_loss: 0.2013, train/total_loss: 0.1988, train/util_ratio: 0.8750, train/run_time: 0.1657, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 14:23:00,461 INFO] validating...
[2023-08-27 14:23:24,382 INFO] confusion matrix:
[[0.91333333 0.         0.02166667 0.         0.         0.00166667
  0.03166667 0.         0.03       0.00166667]
 [0.         0.595      0.16833333 0.00166667 0.         0.01833333
  0.00333333 0.08333333 0.03833333 0.09166667]
 [0.         0.         0.965      0.         0.         0.
  0.00666667 0.02       0.00666667 0.00166667]
 [0.044      0.         0.076      0.456      0.         0.
  0.014      0.018      0.392      0.        ]
 [0.026      0.         0.018      0.038      0.812      0.
  0.016      0.038      0.024      0.028     ]
 [0.0975     0.         0.17       0.0025     0.         0.495
  0.0725     0.0025     0.155      0.005     ]
 [0.044      0.         0.182      0.004      0.         0.002
  0.764      0.002      0.002      0.        ]
 [0.00166667 0.         0.01166667 0.005      0.00166667 0.
  0.00333333 0.97       0.00333333 0.00333333]
 [0.01803607 0.         0.02004008 0.00200401 0.         0.
  0.00200401 0.         0.95591182 0.00200401]
 [0.00166667 0.         0.02833333 0.         0.         0.
  0.         0.         0.03333333 0.93666667]]
[2023-08-27 14:23:25,344 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 14:23:26,300 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/model_best.pth
[2023-08-27 14:23:26,302 INFO] 6144 iteration, USE_EMA: True, train/sup_loss: 0.0009, train/unsup_loss: 0.0106, train/total_loss: -0.0007, train/util_ratio: 1.0000, train/run_time: 0.1659, eval/loss: 0.7926, eval/top-1-acc: 0.8000, eval/balanced_acc: 0.7863, eval/precision: 0.8458, eval/recall: 0.7863, eval/F1: 0.7871, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.8000, at 6144 iters
[2023-08-27 14:24:57,405 INFO] 6400 iteration USE_EMA: True, train/sup_loss: 0.0009, train/unsup_loss: 0.0271, train/total_loss: 0.0132, train/util_ratio: 1.0000, train/run_time: 0.1658, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-27 14:25:46,925 INFO] 6656 iteration USE_EMA: True, train/sup_loss: 0.0021, train/unsup_loss: 0.0621, train/total_loss: 0.0496, train/util_ratio: 1.0000, train/run_time: 0.1656, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 14:26:36,466 INFO] 6912 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.3959, train/total_loss: 0.3840, train/util_ratio: 1.0000, train/run_time: 0.1649, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 14:27:26,016 INFO] 7168 iteration USE_EMA: True, train/sup_loss: 0.0011, train/unsup_loss: 0.6495, train/total_loss: 0.6335, train/util_ratio: 1.0000, train/run_time: 0.1664, lr: 0.0000, train/prefecth_time: 0.0023 
[2023-08-27 14:28:58,736 INFO] 7424 iteration USE_EMA: True, train/sup_loss: 0.0006, train/unsup_loss: 0.0508, train/total_loss: 0.0367, train/util_ratio: 1.0000, train/run_time: 0.1674, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 14:29:48,359 INFO] 7680 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.0053, train/total_loss: -0.0065, train/util_ratio: 0.8750, train/run_time: 0.1614, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 14:30:37,678 INFO] 7936 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.2439, train/total_loss: 0.2322, train/util_ratio: 1.0000, train/run_time: 0.1684, lr: 0.0000, train/prefecth_time: 0.0041 
[2023-08-27 14:31:27,312 INFO] validating...
[2023-08-27 14:31:51,795 INFO] confusion matrix:
[[0.94       0.         0.01166667 0.         0.         0.00833333
  0.02666667 0.         0.01166667 0.00166667]
 [0.         0.9        0.02666667 0.00333333 0.         0.04833333
  0.         0.02166667 0.         0.        ]
 [0.         0.00166667 0.955      0.         0.         0.02333333
  0.00333333 0.015      0.00166667 0.        ]
 [0.024      0.         0.028      0.818      0.         0.
  0.006      0.008      0.116      0.        ]
 [0.004      0.         0.         0.01       0.958      0.
  0.008      0.02       0.         0.        ]
 [0.04       0.005      0.0275     0.005      0.         0.8525
  0.06       0.         0.01       0.        ]
 [0.028      0.         0.128      0.002      0.         0.002
  0.836      0.002      0.002      0.        ]
 [0.         0.         0.         0.00333333 0.005      0.
  0.         0.99166667 0.         0.        ]
 [0.01402806 0.         0.01202405 0.         0.         0.
  0.         0.         0.96993988 0.00400802]
 [0.00333333 0.005      0.025      0.         0.         0.00166667
  0.         0.         0.03166667 0.93333333]]
[2023-08-27 14:31:52,762 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 14:31:53,805 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/model_best.pth
[2023-08-27 14:31:53,806 INFO] 8192 iteration, USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.4001, train/total_loss: 0.3884, train/util_ratio: 0.8750, train/run_time: 0.1685, eval/loss: 0.3318, eval/top-1-acc: 0.9192, eval/balanced_acc: 0.9154, eval/precision: 0.9227, eval/recall: 0.9154, eval/F1: 0.9168, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9192, at 8192 iters
[2023-08-27 14:33:24,765 INFO] 8448 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.4291, train/total_loss: 0.4174, train/util_ratio: 0.8750, train/run_time: 0.1715, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 14:34:14,184 INFO] 8704 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.0224, train/total_loss: 0.0107, train/util_ratio: 1.0000, train/run_time: 0.1724, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-27 14:35:03,162 INFO] 8960 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.0062, train/total_loss: -0.0081, train/util_ratio: 1.0000, train/run_time: 0.1752, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 14:35:52,420 INFO] 9216 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.0098, train/total_loss: 0.0007, train/util_ratio: 1.0000, train/run_time: 0.1579, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 14:37:25,527 INFO] 9472 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.4010, train/total_loss: 0.3915, train/util_ratio: 1.0000, train/run_time: 0.1640, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 14:38:14,759 INFO] 9728 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.2744, train/total_loss: 0.2651, train/util_ratio: 1.0000, train/run_time: 0.1618, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 14:39:04,216 INFO] 9984 iteration USE_EMA: True, train/sup_loss: 0.0007, train/unsup_loss: 0.8225, train/total_loss: 0.8086, train/util_ratio: 1.0000, train/run_time: 0.1744, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 14:39:53,504 INFO] validating...
[2023-08-27 14:40:17,768 INFO] confusion matrix:
[[0.95166667 0.00166667 0.00666667 0.         0.         0.01
  0.02333333 0.         0.005      0.00166667]
 [0.         0.94333333 0.005      0.         0.         0.04166667
  0.         0.01       0.         0.        ]
 [0.         0.00333333 0.95166667 0.         0.         0.02666667
  0.005      0.01166667 0.00166667 0.        ]
 [0.008      0.         0.01       0.916      0.002      0.
  0.002      0.004      0.058      0.        ]
 [0.         0.         0.         0.004      0.976      0.
  0.01       0.01       0.         0.        ]
 [0.025      0.005      0.0125     0.0075     0.         0.8975
  0.045      0.         0.0075     0.        ]
 [0.026      0.         0.092      0.         0.         0.002
  0.876      0.002      0.002      0.        ]
 [0.         0.         0.         0.00333333 0.005      0.
  0.         0.99166667 0.         0.        ]
 [0.01402806 0.         0.00601202 0.00200401 0.         0.
  0.         0.         0.9739479  0.00400802]
 [0.005      0.01166667 0.01666667 0.         0.         0.01166667
  0.         0.         0.02       0.935     ]]
[2023-08-27 14:40:18,571 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 14:40:19,318 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/model_best.pth
[2023-08-27 14:40:19,319 INFO] 10240 iteration, USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.2754, train/total_loss: 0.2611, train/util_ratio: 1.0000, train/run_time: 0.1582, eval/loss: 0.1887, eval/top-1-acc: 0.9433, eval/balanced_acc: 0.9413, eval/precision: 0.9426, eval/recall: 0.9413, eval/F1: 0.9414, lr: 0.0000, train/prefecth_time: 0.0039 BEST_EVAL_ACC: 0.9433, at 10240 iters
[2023-08-27 14:41:51,587 INFO] 10496 iteration USE_EMA: True, train/sup_loss: 0.0005, train/unsup_loss: 0.1398, train/total_loss: 0.1233, train/util_ratio: 1.0000, train/run_time: 0.1617, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 14:42:41,075 INFO] 10752 iteration USE_EMA: True, train/sup_loss: 0.0006, train/unsup_loss: 0.0043, train/total_loss: -0.0072, train/util_ratio: 1.0000, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 14:43:30,547 INFO] 11008 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0571, train/total_loss: 0.0452, train/util_ratio: 1.0000, train/run_time: 0.1607, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 14:44:20,149 INFO] 11264 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0289, train/total_loss: 0.0146, train/util_ratio: 0.8750, train/run_time: 0.1679, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 14:45:52,977 INFO] 11520 iteration USE_EMA: True, train/sup_loss: 0.0010, train/unsup_loss: 0.0071, train/total_loss: -0.0090, train/util_ratio: 0.7500, train/run_time: 0.1675, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 14:46:42,342 INFO] 11776 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0680, train/total_loss: 0.0587, train/util_ratio: 1.0000, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 14:47:31,828 INFO] 12032 iteration USE_EMA: True, train/sup_loss: 0.0006, train/unsup_loss: 0.6233, train/total_loss: 0.6093, train/util_ratio: 1.0000, train/run_time: 0.1595, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 14:48:21,107 INFO] validating...
[2023-08-27 14:48:45,092 INFO] confusion matrix:
[[0.94666667 0.00166667 0.00666667 0.         0.         0.01166667
  0.02666667 0.         0.005      0.00166667]
 [0.         0.96333333 0.005      0.         0.         0.02666667
  0.         0.005      0.         0.        ]
 [0.         0.00333333 0.94       0.         0.         0.035
  0.01       0.01166667 0.         0.        ]
 [0.004      0.         0.006      0.958      0.002      0.
  0.002      0.002      0.026      0.        ]
 [0.         0.         0.         0.002      0.984      0.
  0.008      0.006      0.         0.        ]
 [0.0175     0.005      0.005      0.0075     0.         0.925
  0.0375     0.         0.0025     0.        ]
 [0.02       0.         0.062      0.         0.         0.002
  0.914      0.002      0.         0.        ]
 [0.         0.         0.         0.00333333 0.00833333 0.
  0.         0.98833333 0.         0.        ]
 [0.01002004 0.         0.00200401 0.00601202 0.         0.
  0.         0.         0.97995992 0.00200401]
 [0.005      0.00833333 0.015      0.         0.         0.01
  0.         0.         0.015      0.94666667]]
[2023-08-27 14:48:45,862 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 14:48:46,901 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/model_best.pth
[2023-08-27 14:48:46,902 INFO] 12288 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.1770, train/total_loss: 0.1650, train/util_ratio: 1.0000, train/run_time: 0.1602, eval/loss: 0.1438, eval/top-1-acc: 0.9554, eval/balanced_acc: 0.9546, eval/precision: 0.9537, eval/recall: 0.9546, eval/F1: 0.9540, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9554, at 12288 iters
[2023-08-27 14:50:18,263 INFO] 12544 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.2329, train/total_loss: 0.2210, train/util_ratio: 1.0000, train/run_time: 0.1747, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 14:51:07,778 INFO] 12800 iteration USE_EMA: True, train/sup_loss: 0.0036, train/unsup_loss: 0.3694, train/total_loss: 0.3584, train/util_ratio: 1.0000, train/run_time: 0.1706, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 14:51:57,599 INFO] 13056 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.1440, train/total_loss: 0.1270, train/util_ratio: 1.0000, train/run_time: 0.1658, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 14:52:47,420 INFO] 13312 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0045, train/total_loss: -0.0098, train/util_ratio: 0.8750, train/run_time: 0.1588, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 14:54:20,329 INFO] 13568 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0043, train/total_loss: -0.0100, train/util_ratio: 0.6250, train/run_time: 0.1618, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 14:55:09,817 INFO] 13824 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.4645, train/total_loss: 0.4526, train/util_ratio: 1.0000, train/run_time: 0.1591, lr: 0.0000, train/prefecth_time: 0.0048 
[2023-08-27 14:55:59,449 INFO] 14080 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.1257, train/total_loss: 0.1137, train/util_ratio: 1.0000, train/run_time: 0.1651, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 14:56:49,168 INFO] validating...
[2023-08-27 14:57:13,360 INFO] confusion matrix:
[[0.945      0.00166667 0.00666667 0.00166667 0.         0.01166667
  0.03       0.         0.00166667 0.00166667]
 [0.         0.975      0.005      0.         0.         0.01666667
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.91333333 0.00166667 0.         0.06166667
  0.00833333 0.01       0.00166667 0.        ]
 [0.004      0.         0.002      0.974      0.002      0.
  0.002      0.002      0.014      0.        ]
 [0.         0.         0.         0.002      0.988      0.
  0.006      0.004      0.         0.        ]
 [0.015      0.005      0.005      0.0075     0.         0.945
  0.02       0.         0.0025     0.        ]
 [0.014      0.         0.046      0.002      0.         0.004
  0.932      0.002      0.         0.        ]
 [0.         0.         0.         0.00333333 0.00666667 0.
  0.         0.99       0.         0.        ]
 [0.01002004 0.         0.         0.00601202 0.         0.
  0.         0.         0.98196393 0.00200401]
 [0.005      0.01       0.01333333 0.         0.         0.01
  0.         0.         0.01166667 0.95      ]]
[2023-08-27 14:57:14,199 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 14:57:15,052 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/model_best.pth
[2023-08-27 14:57:15,053 INFO] 14336 iteration, USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0768, train/total_loss: 0.0649, train/util_ratio: 1.0000, train/run_time: 0.1683, eval/loss: 0.1320, eval/top-1-acc: 0.9593, eval/balanced_acc: 0.9594, eval/precision: 0.9571, eval/recall: 0.9594, eval/F1: 0.9580, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9593, at 14336 iters
[2023-08-27 14:58:46,634 INFO] 14592 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0022, train/total_loss: -0.0123, train/util_ratio: 1.0000, train/run_time: 0.1618, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 14:59:36,253 INFO] 14848 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0025, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1713, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 15:00:25,851 INFO] 15104 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.1256, train/total_loss: 0.1187, train/util_ratio: 1.0000, train/run_time: 0.1606, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 15:01:15,437 INFO] 15360 iteration USE_EMA: True, train/sup_loss: 0.0034, train/unsup_loss: 0.2282, train/total_loss: 0.2170, train/util_ratio: 0.8750, train/run_time: 0.1693, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 15:02:49,135 INFO] 15616 iteration USE_EMA: True, train/sup_loss: 0.0006, train/unsup_loss: 0.0078, train/total_loss: -0.0036, train/util_ratio: 1.0000, train/run_time: 0.1601, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 15:03:38,734 INFO] 15872 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0471, train/total_loss: 0.0327, train/util_ratio: 0.6250, train/run_time: 0.1684, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 15:04:28,477 INFO] 16128 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0683, train/total_loss: 0.0540, train/util_ratio: 1.0000, train/run_time: 0.1613, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 15:05:18,356 INFO] validating...
[2023-08-27 15:05:42,743 INFO] confusion matrix:
[[0.94833333 0.00166667 0.00666667 0.00166667 0.         0.01166667
  0.02833333 0.         0.00166667 0.        ]
 [0.         0.97666667 0.00333333 0.         0.         0.01666667
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.89833333 0.00166667 0.         0.07333333
  0.01166667 0.01       0.00166667 0.        ]
 [0.004      0.         0.002      0.976      0.002      0.
  0.         0.002      0.014      0.        ]
 [0.         0.         0.         0.002      0.99       0.
  0.006      0.002      0.         0.        ]
 [0.0125     0.005      0.005      0.0075     0.         0.955
  0.0125     0.         0.0025     0.        ]
 [0.014      0.         0.042      0.002      0.         0.004
  0.936      0.002      0.         0.        ]
 [0.         0.         0.         0.00333333 0.00833333 0.
  0.         0.98833333 0.         0.        ]
 [0.00801603 0.         0.         0.00601202 0.         0.
  0.         0.         0.98396794 0.00200401]
 [0.005      0.00833333 0.01333333 0.         0.         0.01
  0.         0.         0.01       0.95333333]]
[2023-08-27 15:05:43,592 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 15:05:44,921 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/model_best.pth
[2023-08-27 15:05:44,922 INFO] 16384 iteration, USE_EMA: True, train/sup_loss: 0.0005, train/unsup_loss: 0.0905, train/total_loss: 0.0738, train/util_ratio: 1.0000, train/run_time: 0.1594, eval/loss: 0.1322, eval/top-1-acc: 0.9600, eval/balanced_acc: 0.9606, eval/precision: 0.9577, eval/recall: 0.9606, eval/F1: 0.9587, lr: 0.0000, train/prefecth_time: 0.0035 BEST_EVAL_ACC: 0.9600, at 16384 iters
[2023-08-27 15:07:16,148 INFO] 16640 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0858, train/total_loss: 0.0738, train/util_ratio: 1.0000, train/run_time: 0.1609, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 15:08:05,865 INFO] 16896 iteration USE_EMA: True, train/sup_loss: 0.0007, train/unsup_loss: 0.4470, train/total_loss: 0.4331, train/util_ratio: 1.0000, train/run_time: 0.1664, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 15:08:55,533 INFO] 17152 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.1298, train/total_loss: 0.1153, train/util_ratio: 1.0000, train/run_time: 0.1737, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 15:09:45,364 INFO] 17408 iteration USE_EMA: True, train/sup_loss: 0.0024, train/unsup_loss: 0.1997, train/total_loss: 0.1899, train/util_ratio: 1.0000, train/run_time: 0.1678, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 15:11:19,044 INFO] 17664 iteration USE_EMA: True, train/sup_loss: 0.0012, train/unsup_loss: 0.0013, train/total_loss: -0.0121, train/util_ratio: 0.8750, train/run_time: 0.1676, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 15:12:08,402 INFO] 17920 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0728, train/total_loss: 0.0608, train/util_ratio: 0.8750, train/run_time: 0.1639, lr: 0.0000, train/prefecth_time: 0.0051 
[2023-08-27 15:12:57,854 INFO] 18176 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.1457, train/total_loss: 0.1338, train/util_ratio: 0.8750, train/run_time: 0.1644, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 15:13:47,365 INFO] validating...
[2023-08-27 15:14:11,934 INFO] confusion matrix:
[[0.94333333 0.00333333 0.00666667 0.00166667 0.         0.01333333
  0.03       0.         0.00166667 0.        ]
 [0.         0.98333333 0.00333333 0.         0.         0.01
  0.         0.00333333 0.         0.        ]
 [0.         0.005      0.87833333 0.00166667 0.         0.08833333
  0.01333333 0.01166667 0.00166667 0.        ]
 [0.004      0.         0.         0.984      0.         0.
  0.         0.002      0.01       0.        ]
 [0.         0.         0.         0.002      0.99       0.
  0.006      0.002      0.         0.        ]
 [0.01       0.0025     0.005      0.0075     0.         0.965
  0.0075     0.         0.0025     0.        ]
 [0.01       0.         0.038      0.004      0.         0.004
  0.942      0.002      0.         0.        ]
 [0.         0.         0.         0.00333333 0.01166667 0.
  0.         0.985      0.         0.        ]
 [0.00801603 0.00200401 0.         0.00400802 0.         0.
  0.         0.         0.98396794 0.00200401]
 [0.005      0.00333333 0.01333333 0.00166667 0.         0.00833333
  0.         0.         0.00833333 0.96      ]]
[2023-08-27 15:14:12,740 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 15:14:13,707 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/model_best.pth
[2023-08-27 15:14:13,708 INFO] 18432 iteration, USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.6584, train/total_loss: 0.6439, train/util_ratio: 1.0000, train/run_time: 0.1599, eval/loss: 0.1391, eval/top-1-acc: 0.9604, eval/balanced_acc: 0.9615, eval/precision: 0.9580, eval/recall: 0.9615, eval/F1: 0.9592, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9604, at 18432 iters
[2023-08-27 15:15:45,195 INFO] 18688 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.1381, train/total_loss: 0.1236, train/util_ratio: 0.7500, train/run_time: 0.1658, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 15:16:34,939 INFO] 18944 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.3531, train/total_loss: 0.3388, train/util_ratio: 0.8750, train/run_time: 0.1589, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-27 15:17:24,491 INFO] 19200 iteration USE_EMA: True, train/sup_loss: 0.0006, train/unsup_loss: 0.0241, train/total_loss: 0.0126, train/util_ratio: 1.0000, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 15:18:14,159 INFO] 19456 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0042, train/total_loss: -0.0053, train/util_ratio: 0.8750, train/run_time: 0.1721, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 15:19:47,567 INFO] 19712 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.3869, train/total_loss: 0.3752, train/util_ratio: 1.0000, train/run_time: 0.1655, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 15:20:37,647 INFO] 19968 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0320, train/total_loss: 0.0176, train/util_ratio: 0.7500, train/run_time: 0.1771, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 15:21:27,328 INFO] 20224 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0027, train/total_loss: -0.0068, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 15:22:17,203 INFO] validating...
[2023-08-27 15:22:41,693 INFO] confusion matrix:
[[0.94666667 0.00166667 0.00666667 0.         0.         0.01166667
  0.03166667 0.         0.00166667 0.        ]
 [0.         0.98333333 0.00333333 0.         0.         0.01
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.87166667 0.00166667 0.         0.09666667
  0.015      0.01       0.00166667 0.        ]
 [0.004      0.         0.         0.988      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.0025     0.005      0.0075     0.         0.97
  0.0075     0.         0.0025     0.        ]
 [0.01       0.         0.032      0.004      0.         0.004
  0.95       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01166667 0.
  0.         0.985      0.         0.        ]
 [0.00801603 0.00200401 0.         0.00400802 0.         0.
  0.         0.         0.98396794 0.00200401]
 [0.005      0.005      0.01333333 0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.965     ]]
[2023-08-27 15:22:42,498 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 15:22:43,517 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/model_best.pth
[2023-08-27 15:22:43,519 INFO] 20480 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.4016, train/total_loss: 0.3896, train/util_ratio: 1.0000, train/run_time: 0.1671, eval/loss: 0.1462, eval/top-1-acc: 0.9622, eval/balanced_acc: 0.9636, eval/precision: 0.9599, eval/recall: 0.9636, eval/F1: 0.9610, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 15:24:14,480 INFO] 20736 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.1763, train/total_loss: 0.1621, train/util_ratio: 1.0000, train/run_time: 0.1644, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 15:25:04,176 INFO] 20992 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.1536, train/total_loss: 0.1417, train/util_ratio: 1.0000, train/run_time: 0.1766, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 15:25:53,683 INFO] 21248 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0898, train/total_loss: 0.0728, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 15:26:43,497 INFO] 21504 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0073, train/total_loss: -0.0048, train/util_ratio: 1.0000, train/run_time: 0.1865, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-27 15:28:16,092 INFO] 21760 iteration USE_EMA: True, train/sup_loss: 0.0007, train/unsup_loss: 0.0049, train/total_loss: -0.0041, train/util_ratio: 0.8750, train/run_time: 0.1583, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 15:29:05,361 INFO] 22016 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0214, train/total_loss: 0.0043, train/util_ratio: 0.8750, train/run_time: 0.1661, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-27 15:29:54,712 INFO] 22272 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1933, train/total_loss: 0.1812, train/util_ratio: 0.8750, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 15:30:44,375 INFO] validating...
[2023-08-27 15:31:08,996 INFO] confusion matrix:
[[0.94166667 0.00166667 0.00666667 0.         0.         0.01333333
  0.035      0.         0.00166667 0.        ]
 [0.         0.98333333 0.00333333 0.         0.         0.01
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.86333333 0.00166667 0.         0.10666667
  0.015      0.00833333 0.00166667 0.        ]
 [0.002      0.         0.         0.99       0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.0025     0.005      0.0075     0.         0.9725
  0.005      0.         0.0025     0.        ]
 [0.006      0.         0.03       0.004      0.         0.004
  0.956      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.01002004 0.00200401 0.         0.         0.         0.
  0.         0.         0.98597194 0.00200401]
 [0.00666667 0.005      0.01333333 0.00166667 0.         0.00666667
  0.         0.00166667 0.00333333 0.96166667]]
[2023-08-27 15:31:09,784 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 15:31:09,785 INFO] 22528 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0779, train/total_loss: 0.0658, train/util_ratio: 1.0000, train/run_time: 0.1601, eval/loss: 0.1504, eval/top-1-acc: 0.9613, eval/balanced_acc: 0.9630, eval/precision: 0.9590, eval/recall: 0.9630, eval/F1: 0.9601, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 15:32:42,192 INFO] 22784 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0001, train/total_loss: -0.0143, train/util_ratio: 1.0000, train/run_time: 0.1651, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 15:33:31,648 INFO] 23040 iteration USE_EMA: True, train/sup_loss: 0.0006, train/unsup_loss: 0.0897, train/total_loss: 0.0781, train/util_ratio: 1.0000, train/run_time: 0.1604, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 15:34:21,074 INFO] 23296 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4415, train/total_loss: 0.4319, train/util_ratio: 1.0000, train/run_time: 0.1677, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 15:35:11,000 INFO] 23552 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0160, train/total_loss: 0.0065, train/util_ratio: 1.0000, train/run_time: 0.1667, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-27 15:36:44,758 INFO] 23808 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0210, train/total_loss: 0.0089, train/util_ratio: 1.0000, train/run_time: 0.1677, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 15:37:34,421 INFO] 24064 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0125, train/total_loss: -0.0021, train/util_ratio: 1.0000, train/run_time: 0.1699, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 15:38:24,113 INFO] 24320 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.1038, train/total_loss: 0.0919, train/util_ratio: 1.0000, train/run_time: 0.1693, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 15:39:13,518 INFO] validating...
[2023-08-27 15:39:38,148 INFO] confusion matrix:
[[0.93333333 0.00333333 0.005      0.         0.         0.015
  0.04166667 0.         0.00166667 0.        ]
 [0.         0.985      0.00333333 0.         0.         0.00833333
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.86       0.00166667 0.         0.11
  0.015      0.00666667 0.00333333 0.        ]
 [0.002      0.         0.         0.99       0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.0025     0.005      0.0075     0.         0.9725
  0.005      0.         0.0025     0.        ]
 [0.004      0.         0.03       0.004      0.         0.004
  0.958      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00601202 0.00200401 0.         0.         0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.005      0.005      0.015      0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.96333333]]
[2023-08-27 15:39:39,487 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 15:39:39,489 INFO] 24576 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0006, train/total_loss: -0.0164, train/util_ratio: 0.7500, train/run_time: 0.1629, eval/loss: 0.1539, eval/top-1-acc: 0.9609, eval/balanced_acc: 0.9627, eval/precision: 0.9586, eval/recall: 0.9627, eval/F1: 0.9597, lr: 0.0000, train/prefecth_time: 0.0023 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 15:41:11,006 INFO] 24832 iteration USE_EMA: True, train/sup_loss: 0.0076, train/unsup_loss: 0.0007, train/total_loss: -0.0089, train/util_ratio: 0.8750, train/run_time: 0.1707, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 15:42:00,523 INFO] 25088 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.1985, train/total_loss: 0.1914, train/util_ratio: 1.0000, train/run_time: 0.1678, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 15:42:50,112 INFO] 25344 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0042, train/total_loss: -0.0104, train/util_ratio: 1.0000, train/run_time: 0.1604, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 15:43:39,703 INFO] 25600 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0084, train/total_loss: -0.0060, train/util_ratio: 0.8750, train/run_time: 0.1568, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 15:45:12,087 INFO] 25856 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0901, train/total_loss: 0.0781, train/util_ratio: 1.0000, train/run_time: 0.1770, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-27 15:46:01,639 INFO] 26112 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0225, train/total_loss: 0.0079, train/util_ratio: 0.7500, train/run_time: 0.1626, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 15:46:51,616 INFO] 26368 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1810, train/total_loss: 0.1639, train/util_ratio: 1.0000, train/run_time: 0.1618, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 15:47:41,196 INFO] validating...
[2023-08-27 15:48:05,707 INFO] confusion matrix:
[[0.94       0.00333333 0.005      0.         0.         0.01166667
  0.04       0.         0.         0.        ]
 [0.         0.985      0.00333333 0.         0.         0.00833333
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.85666667 0.00166667 0.         0.11666667
  0.015      0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.004      0.99       0.
  0.004      0.002      0.         0.        ]
 [0.005      0.0025     0.005      0.0075     0.         0.9725
  0.005      0.         0.0025     0.        ]
 [0.004      0.         0.026      0.004      0.         0.004
  0.962      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00601202 0.00200401 0.         0.         0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00666667 0.005      0.01333333 0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.96333333]]
[2023-08-27 15:48:06,534 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 15:48:06,535 INFO] 26624 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0718, train/total_loss: 0.0573, train/util_ratio: 1.0000, train/run_time: 0.1601, eval/loss: 0.1605, eval/top-1-acc: 0.9615, eval/balanced_acc: 0.9633, eval/precision: 0.9591, eval/recall: 0.9633, eval/F1: 0.9601, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 15:49:38,421 INFO] 26880 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0178, train/total_loss: 0.0082, train/util_ratio: 1.0000, train/run_time: 0.1610, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 15:50:28,044 INFO] 27136 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0048, train/total_loss: -0.0121, train/util_ratio: 0.7500, train/run_time: 0.1657, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 15:51:17,361 INFO] 27392 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1517, train/total_loss: 0.1396, train/util_ratio: 1.0000, train/run_time: 0.1723, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 15:52:06,887 INFO] 27648 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.2758, train/total_loss: 0.2589, train/util_ratio: 1.0000, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-27 15:53:40,105 INFO] 27904 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0703, train/total_loss: 0.0558, train/util_ratio: 1.0000, train/run_time: 0.1657, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 15:54:29,744 INFO] 28160 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0622, train/total_loss: 0.0451, train/util_ratio: 1.0000, train/run_time: 0.1658, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 15:55:19,307 INFO] 28416 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.1186, train/total_loss: 0.1041, train/util_ratio: 0.8750, train/run_time: 0.1595, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 15:56:08,914 INFO] validating...
[2023-08-27 15:56:33,348 INFO] confusion matrix:
[[0.94166667 0.00333333 0.005      0.         0.         0.01
  0.04       0.         0.         0.        ]
 [0.         0.985      0.00333333 0.         0.         0.00833333
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.84666667 0.00166667 0.         0.125
  0.01666667 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.988      0.         0.
  0.         0.         0.012      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.0025     0.005      0.0075     0.         0.975
  0.0025     0.         0.0025     0.        ]
 [0.004      0.         0.026      0.004      0.         0.004
  0.962      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00601202 0.         0.         0.         0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00666667 0.005      0.01333333 0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.96333333]]
[2023-08-27 15:56:34,171 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 15:56:34,172 INFO] 28672 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0016, train/total_loss: -0.0104, train/util_ratio: 1.0000, train/run_time: 0.1657, eval/loss: 0.1672, eval/top-1-acc: 0.9609, eval/balanced_acc: 0.9629, eval/precision: 0.9585, eval/recall: 0.9629, eval/F1: 0.9596, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 15:58:06,060 INFO] 28928 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0225, train/total_loss: 0.0105, train/util_ratio: 0.8750, train/run_time: 0.1661, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 15:58:55,566 INFO] 29184 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0239, train/total_loss: 0.0119, train/util_ratio: 0.8750, train/run_time: 0.1617, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 15:59:45,149 INFO] 29440 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1071, train/total_loss: 0.0951, train/util_ratio: 1.0000, train/run_time: 0.1665, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 16:00:34,838 INFO] 29696 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0002, train/total_loss: -0.0143, train/util_ratio: 1.0000, train/run_time: 0.1691, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 16:02:08,355 INFO] 29952 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0429, train/total_loss: 0.0333, train/util_ratio: 1.0000, train/run_time: 0.1752, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 16:02:58,076 INFO] 30208 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0032, train/total_loss: -0.0089, train/util_ratio: 1.0000, train/run_time: 0.1601, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 16:03:47,885 INFO] 30464 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0260, train/total_loss: 0.0140, train/util_ratio: 0.8750, train/run_time: 0.1634, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 16:04:37,829 INFO] validating...
[2023-08-27 16:05:02,041 INFO] confusion matrix:
[[0.93333333 0.00333333 0.005      0.         0.         0.01166667
  0.04666667 0.         0.         0.        ]
 [0.         0.98666667 0.00333333 0.         0.         0.00666667
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.84666667 0.00166667 0.         0.12833333
  0.01333333 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.986      0.         0.
  0.         0.         0.014      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.0025     0.005      0.0075     0.         0.975
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.004
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00601202 0.         0.         0.         0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00666667 0.005      0.01166667 0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.965     ]]
[2023-08-27 16:05:02,841 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 16:05:02,842 INFO] 30720 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.1296, train/total_loss: 0.1176, train/util_ratio: 1.0000, train/run_time: 0.1742, eval/loss: 0.1741, eval/top-1-acc: 0.9607, eval/balanced_acc: 0.9628, eval/precision: 0.9584, eval/recall: 0.9628, eval/F1: 0.9593, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 16:06:35,994 INFO] 30976 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.1256, train/total_loss: 0.1135, train/util_ratio: 1.0000, train/run_time: 0.1638, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 16:07:25,828 INFO] 31232 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0009, train/total_loss: -0.0160, train/util_ratio: 0.7500, train/run_time: 0.1614, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 16:08:15,599 INFO] 31488 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0150, train/total_loss: 0.0029, train/util_ratio: 1.0000, train/run_time: 0.1677, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 16:09:05,339 INFO] 31744 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.1101, train/total_loss: 0.0956, train/util_ratio: 1.0000, train/run_time: 0.1809, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 16:10:38,151 INFO] 32000 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.4691, train/total_loss: 0.4546, train/util_ratio: 1.0000, train/run_time: 0.1663, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 16:11:27,879 INFO] 32256 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1175, train/total_loss: 0.1079, train/util_ratio: 0.8750, train/run_time: 0.1779, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 16:12:17,722 INFO] 32512 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0384, train/total_loss: 0.0263, train/util_ratio: 1.0000, train/run_time: 0.1795, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 16:13:07,403 INFO] validating...
[2023-08-27 16:13:31,734 INFO] confusion matrix:
[[0.93       0.00333333 0.005      0.         0.         0.01
  0.05       0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.845      0.00166667 0.         0.12833333
  0.015      0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.986      0.         0.
  0.         0.         0.014      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.0025     0.005      0.0075     0.         0.975
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.004
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00601202 0.         0.         0.         0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00666667 0.005      0.01333333 0.00166667 0.         0.00666667
  0.         0.         0.005      0.96166667]]
[2023-08-27 16:13:32,490 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 16:13:32,491 INFO] 32768 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4324, train/total_loss: 0.4178, train/util_ratio: 1.0000, train/run_time: 0.1659, eval/loss: 0.1802, eval/top-1-acc: 0.9598, eval/balanced_acc: 0.9620, eval/precision: 0.9574, eval/recall: 0.9620, eval/F1: 0.9584, lr: 0.0000, train/prefecth_time: 0.0036 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 16:15:04,942 INFO] 33024 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0036, train/total_loss: -0.0082, train/util_ratio: 1.0000, train/run_time: 0.1742, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 16:15:54,657 INFO] 33280 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.4567, train/total_loss: 0.4447, train/util_ratio: 1.0000, train/run_time: 0.1726, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 16:16:44,429 INFO] 33536 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.1077, train/total_loss: 0.0981, train/util_ratio: 1.0000, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 16:17:33,962 INFO] 33792 iteration USE_EMA: True, train/sup_loss: 0.0013, train/unsup_loss: 0.1256, train/total_loss: 0.1148, train/util_ratio: 1.0000, train/run_time: 0.1661, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 16:19:07,149 INFO] 34048 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0042, train/total_loss: -0.0104, train/util_ratio: 1.0000, train/run_time: 0.1575, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 16:19:56,851 INFO] 34304 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0012, train/total_loss: -0.0159, train/util_ratio: 1.0000, train/run_time: 0.1586, lr: 0.0000, train/prefecth_time: 0.0045 
[2023-08-27 16:20:46,365 INFO] 34560 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0057, train/total_loss: -0.0063, train/util_ratio: 1.0000, train/run_time: 0.1662, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 16:21:36,018 INFO] validating...
[2023-08-27 16:22:00,528 INFO] confusion matrix:
[[0.92833333 0.00333333 0.005      0.         0.         0.00833333
  0.05333333 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.84666667 0.00166667 0.         0.125
  0.01666667 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.986      0.         0.
  0.         0.         0.014      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.0075     0.         0.98
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.002
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00601202 0.         0.         0.00200401 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00666667 0.00333333 0.01166667 0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.96666667]]
[2023-08-27 16:22:01,489 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 16:22:01,491 INFO] 34816 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0645, train/total_loss: 0.0524, train/util_ratio: 0.8750, train/run_time: 0.1609, eval/loss: 0.1849, eval/top-1-acc: 0.9607, eval/balanced_acc: 0.9630, eval/precision: 0.9584, eval/recall: 0.9630, eval/F1: 0.9594, lr: 0.0000, train/prefecth_time: 0.0031 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 16:23:33,829 INFO] 35072 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0005, train/total_loss: -0.0116, train/util_ratio: 1.0000, train/run_time: 0.1587, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 16:24:23,572 INFO] 35328 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1873, train/total_loss: 0.1777, train/util_ratio: 1.0000, train/run_time: 0.1706, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 16:25:13,171 INFO] 35584 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.2212, train/total_loss: 0.2041, train/util_ratio: 1.0000, train/run_time: 0.1774, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 16:26:02,727 INFO] 35840 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0020, train/total_loss: -0.0126, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 16:27:35,976 INFO] 36096 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0044, train/total_loss: -0.0077, train/util_ratio: 1.0000, train/run_time: 0.1615, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 16:28:25,508 INFO] 36352 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0004, train/total_loss: -0.0092, train/util_ratio: 1.0000, train/run_time: 0.1603, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 16:29:15,073 INFO] 36608 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.3074, train/total_loss: 0.2929, train/util_ratio: 1.0000, train/run_time: 0.1746, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 16:30:04,789 INFO] validating...
[2023-08-27 16:30:28,931 INFO] confusion matrix:
[[0.92666667 0.00166667 0.005      0.         0.         0.00833333
  0.055      0.         0.00333333 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.84       0.00166667 0.         0.13333333
  0.01666667 0.00333333 0.00166667 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.0075     0.         0.98
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.002
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.005      0.01333333 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00666667 0.00166667 0.01166667 0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.96833333]]
[2023-08-27 16:30:29,774 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 16:30:29,775 INFO] 36864 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0272, train/total_loss: 0.0151, train/util_ratio: 0.8750, train/run_time: 0.1602, eval/loss: 0.1914, eval/top-1-acc: 0.9604, eval/balanced_acc: 0.9627, eval/precision: 0.9580, eval/recall: 0.9627, eval/F1: 0.9590, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 16:32:02,210 INFO] 37120 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0127, train/total_loss: -0.0044, train/util_ratio: 0.8750, train/run_time: 0.1596, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 16:32:51,501 INFO] 37376 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1954, train/total_loss: 0.1808, train/util_ratio: 0.8750, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 16:33:41,233 INFO] 37632 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0557, train/total_loss: 0.0411, train/util_ratio: 1.0000, train/run_time: 0.1653, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-27 16:34:30,816 INFO] 37888 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0029, train/total_loss: -0.0141, train/util_ratio: 1.0000, train/run_time: 0.1671, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-27 16:36:03,223 INFO] 38144 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0022, train/total_loss: -0.0099, train/util_ratio: 1.0000, train/run_time: 0.1580, lr: 0.0000, train/prefecth_time: 0.0046 
[2023-08-27 16:36:52,888 INFO] 38400 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0004, train/total_loss: -0.0091, train/util_ratio: 1.0000, train/run_time: 0.1654, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 16:37:42,557 INFO] 38656 iteration USE_EMA: True, train/sup_loss: 0.0008, train/unsup_loss: 0.0532, train/total_loss: 0.0443, train/util_ratio: 1.0000, train/run_time: 0.1677, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 16:38:32,155 INFO] validating...
[2023-08-27 16:38:56,333 INFO] confusion matrix:
[[0.93166667 0.00166667 0.005      0.         0.         0.00833333
  0.05       0.         0.00333333 0.        ]
 [0.         0.98833333 0.005      0.         0.         0.005
  0.         0.00166667 0.         0.        ]
 [0.         0.00333333 0.83666667 0.00166667 0.         0.13333333
  0.01833333 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.0075     0.         0.98
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.002
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.005      0.015      0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00666667 0.00166667 0.01333333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96833333]]
[2023-08-27 16:38:57,129 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 16:38:57,130 INFO] 38912 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0165, train/total_loss: -0.0006, train/util_ratio: 0.8750, train/run_time: 0.1605, eval/loss: 0.1956, eval/top-1-acc: 0.9605, eval/balanced_acc: 0.9629, eval/precision: 0.9581, eval/recall: 0.9629, eval/F1: 0.9592, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 16:40:29,124 INFO] 39168 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0146, train/total_loss: 0.0000, train/util_ratio: 1.0000, train/run_time: 0.1694, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 16:41:18,799 INFO] 39424 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0603, train/total_loss: 0.0458, train/util_ratio: 0.8750, train/run_time: 0.1619, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 16:42:08,633 INFO] 39680 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0008, train/total_loss: -0.0112, train/util_ratio: 0.8750, train/run_time: 0.1826, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 16:42:58,335 INFO] 39936 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3618, train/total_loss: 0.3522, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 16:44:31,123 INFO] 40192 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0011, train/total_loss: -0.0135, train/util_ratio: 1.0000, train/run_time: 0.1663, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 16:45:20,321 INFO] 40448 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0019, train/total_loss: -0.0127, train/util_ratio: 1.0000, train/run_time: 0.1582, lr: 0.0000, train/prefecth_time: 0.0044 
[2023-08-27 16:46:09,806 INFO] 40704 iteration USE_EMA: True, train/sup_loss: 0.0010, train/unsup_loss: 0.0021, train/total_loss: -0.0115, train/util_ratio: 1.0000, train/run_time: 0.1665, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 16:46:59,220 INFO] validating...
[2023-08-27 16:47:23,538 INFO] confusion matrix:
[[0.92833333 0.00166667 0.005      0.         0.         0.00833333
  0.05333333 0.         0.00333333 0.        ]
 [0.         0.98833333 0.00666667 0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00333333 0.84       0.00166667 0.         0.13166667
  0.01833333 0.00333333 0.00166667 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.0075     0.         0.98
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.002
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.005      0.015      0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00666667 0.00166667 0.01333333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96833333]]
[2023-08-27 16:47:24,381 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 16:47:24,382 INFO] 40960 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0161, train/total_loss: 0.0040, train/util_ratio: 1.0000, train/run_time: 0.1604, eval/loss: 0.1986, eval/top-1-acc: 0.9607, eval/balanced_acc: 0.9631, eval/precision: 0.9583, eval/recall: 0.9631, eval/F1: 0.9594, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 16:48:56,613 INFO] 41216 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.8137, train/total_loss: 0.7991, train/util_ratio: 1.0000, train/run_time: 0.1575, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-27 16:49:46,402 INFO] 41472 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0004, train/total_loss: -0.0092, train/util_ratio: 1.0000, train/run_time: 0.1583, lr: 0.0000, train/prefecth_time: 0.0044 
[2023-08-27 16:50:36,272 INFO] 41728 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1027, train/total_loss: 0.0881, train/util_ratio: 1.0000, train/run_time: 0.1614, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 16:51:25,974 INFO] 41984 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0063, train/total_loss: -0.0031, train/util_ratio: 1.0000, train/run_time: 0.1657, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 16:52:59,187 INFO] 42240 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0120, train/total_loss: -0.0001, train/util_ratio: 1.0000, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 16:53:48,706 INFO] 42496 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0554, train/total_loss: 0.0434, train/util_ratio: 1.0000, train/run_time: 0.1697, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 16:54:38,327 INFO] 42752 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0577, train/total_loss: 0.0481, train/util_ratio: 1.0000, train/run_time: 0.1589, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 16:55:27,818 INFO] validating...
[2023-08-27 16:55:52,357 INFO] confusion matrix:
[[0.93166667 0.00166667 0.005      0.         0.         0.00833333
  0.05       0.         0.00333333 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.84       0.00166667 0.         0.13166667
  0.01833333 0.00333333 0.00166667 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.0075     0.         0.98
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.024      0.004      0.         0.002
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.005      0.015      0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99398798 0.        ]
 [0.00833333 0.00166667 0.01333333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96666667]]
[2023-08-27 16:55:53,135 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 16:55:53,136 INFO] 43008 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0328, train/total_loss: 0.0206, train/util_ratio: 1.0000, train/run_time: 0.1589, eval/loss: 0.2010, eval/top-1-acc: 0.9607, eval/balanced_acc: 0.9631, eval/precision: 0.9583, eval/recall: 0.9631, eval/F1: 0.9594, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 16:57:25,572 INFO] 43264 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0494, train/total_loss: 0.0398, train/util_ratio: 0.8750, train/run_time: 0.1645, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 16:58:15,269 INFO] 43520 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0036, train/total_loss: -0.0136, train/util_ratio: 0.8750, train/run_time: 0.1710, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 16:59:04,430 INFO] 43776 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0004, train/total_loss: -0.0116, train/util_ratio: 0.8750, train/run_time: 0.1604, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 16:59:53,874 INFO] 44032 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0068, train/total_loss: -0.0053, train/util_ratio: 1.0000, train/run_time: 0.1760, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 17:01:27,189 INFO] 44288 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0378, train/total_loss: 0.0232, train/util_ratio: 0.8750, train/run_time: 0.1667, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 17:02:16,582 INFO] 44544 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0025, train/total_loss: -0.0121, train/util_ratio: 1.0000, train/run_time: 0.1619, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 17:03:06,302 INFO] 44800 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.6148, train/total_loss: 0.6002, train/util_ratio: 0.8750, train/run_time: 0.1683, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 17:03:55,717 INFO] validating...
[2023-08-27 17:04:19,995 INFO] confusion matrix:
[[0.92833333 0.00166667 0.005      0.         0.         0.00833333
  0.05333333 0.         0.00333333 0.        ]
 [0.         0.98833333 0.005      0.         0.         0.005
  0.         0.00166667 0.         0.        ]
 [0.         0.00333333 0.84166667 0.00166667 0.         0.12833333
  0.01833333 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0075     0.         0.9775
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.024      0.004      0.         0.002
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.015      0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99398798 0.        ]
 [0.00833333 0.00166667 0.01333333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96666667]]
[2023-08-27 17:04:20,778 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 17:04:20,779 INFO] 45056 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1007, train/total_loss: 0.0861, train/util_ratio: 1.0000, train/run_time: 0.1614, eval/loss: 0.2021, eval/top-1-acc: 0.9607, eval/balanced_acc: 0.9630, eval/precision: 0.9583, eval/recall: 0.9630, eval/F1: 0.9594, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 17:05:53,290 INFO] 45312 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0113, train/total_loss: -0.0032, train/util_ratio: 1.0000, train/run_time: 0.1606, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-27 17:06:43,339 INFO] 45568 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0067, train/total_loss: -0.0054, train/util_ratio: 0.8750, train/run_time: 0.1661, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 17:07:33,479 INFO] 45824 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0056, train/total_loss: -0.0064, train/util_ratio: 0.8750, train/run_time: 0.1678, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 17:08:23,039 INFO] 46080 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0033, train/total_loss: -0.0087, train/util_ratio: 1.0000, train/run_time: 0.1680, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 17:09:55,807 INFO] 46336 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0437, train/total_loss: 0.0291, train/util_ratio: 1.0000, train/run_time: 0.1717, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 17:10:44,774 INFO] 46592 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0177, train/total_loss: 0.0083, train/util_ratio: 1.0000, train/run_time: 0.1681, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 17:11:34,255 INFO] 46848 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0058, train/total_loss: -0.0087, train/util_ratio: 1.0000, train/run_time: 0.1673, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 17:12:23,675 INFO] validating...
[2023-08-27 17:12:48,216 INFO] confusion matrix:
[[0.92666667 0.00166667 0.005      0.         0.         0.00833333
  0.055      0.         0.00333333 0.        ]
 [0.         0.98833333 0.005      0.         0.         0.005
  0.         0.00166667 0.         0.        ]
 [0.         0.00333333 0.84       0.00166667 0.         0.12833333
  0.02       0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.98
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.002
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.015      0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99398798 0.        ]
 [0.01       0.         0.01333333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96666667]]
[2023-08-27 17:12:49,073 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 17:12:49,075 INFO] 47104 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0001, train/total_loss: -0.0095, train/util_ratio: 0.8750, train/run_time: 0.1578, eval/loss: 0.2046, eval/top-1-acc: 0.9607, eval/balanced_acc: 0.9631, eval/precision: 0.9584, eval/recall: 0.9631, eval/F1: 0.9594, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 17:14:21,395 INFO] 47360 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4925, train/total_loss: 0.4804, train/util_ratio: 1.0000, train/run_time: 0.1598, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 17:15:10,858 INFO] 47616 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0914, train/total_loss: 0.0792, train/util_ratio: 1.0000, train/run_time: 0.1671, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 17:16:00,278 INFO] 47872 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0039, train/total_loss: -0.0107, train/util_ratio: 1.0000, train/run_time: 0.1673, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 17:16:49,946 INFO] 48128 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0452, train/total_loss: 0.0307, train/util_ratio: 1.0000, train/run_time: 0.1652, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 17:18:22,919 INFO] 48384 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4534, train/total_loss: 0.4388, train/util_ratio: 1.0000, train/run_time: 0.1692, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 17:19:12,625 INFO] 48640 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0898, train/total_loss: 0.0727, train/util_ratio: 0.8750, train/run_time: 0.1700, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 17:20:02,441 INFO] 48896 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1116, train/total_loss: 0.0970, train/util_ratio: 1.0000, train/run_time: 0.1710, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 17:20:52,034 INFO] validating...
[2023-08-27 17:21:16,697 INFO] confusion matrix:
[[0.92833333 0.00166667 0.005      0.         0.         0.00833333
  0.05333333 0.         0.00333333 0.        ]
 [0.         0.985      0.005      0.         0.         0.00833333
  0.         0.00166667 0.         0.        ]
 [0.         0.00333333 0.835      0.00166667 0.         0.13166667
  0.02166667 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.98
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01666667 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99398798 0.        ]
 [0.01       0.         0.01333333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96666667]]
[2023-08-27 17:21:17,663 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 17:21:17,664 INFO] 49152 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0091, train/total_loss: -0.0080, train/util_ratio: 1.0000, train/run_time: 0.1627, eval/loss: 0.2112, eval/top-1-acc: 0.9604, eval/balanced_acc: 0.9629, eval/precision: 0.9580, eval/recall: 0.9629, eval/F1: 0.9591, lr: 0.0000, train/prefecth_time: 0.0033 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 17:22:49,046 INFO] 49408 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0176, train/total_loss: 0.0005, train/util_ratio: 1.0000, train/run_time: 0.1615, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 17:23:38,644 INFO] 49664 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2339, train/total_loss: 0.2218, train/util_ratio: 1.0000, train/run_time: 0.1608, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 17:24:28,356 INFO] 49920 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.6609, train/total_loss: 0.6514, train/util_ratio: 1.0000, train/run_time: 0.1742, lr: 0.0000, train/prefecth_time: 0.0044 
[2023-08-27 17:25:17,904 INFO] 50176 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0587, train/total_loss: 0.0466, train/util_ratio: 1.0000, train/run_time: 0.1657, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 17:26:51,215 INFO] 50432 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1276, train/total_loss: 0.1155, train/util_ratio: 1.0000, train/run_time: 0.1607, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 17:27:41,000 INFO] 50688 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.5634, train/total_loss: 0.5513, train/util_ratio: 1.0000, train/run_time: 0.1667, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 17:28:30,461 INFO] 50944 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1066, train/total_loss: 0.0920, train/util_ratio: 1.0000, train/run_time: 0.1674, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 17:29:19,899 INFO] validating...
[2023-08-27 17:29:44,486 INFO] confusion matrix:
[[0.92833333 0.00166667 0.00333333 0.         0.         0.00833333
  0.055      0.         0.00333333 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00666667
  0.         0.00166667 0.         0.        ]
 [0.         0.00333333 0.82       0.00166667 0.         0.14166667
  0.02666667 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.98
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01666667 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99398798 0.        ]
 [0.01       0.         0.01333333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96666667]]
[2023-08-27 17:29:45,258 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 17:29:45,259 INFO] 51200 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0671, train/total_loss: 0.0525, train/util_ratio: 0.8750, train/run_time: 0.1569, eval/loss: 0.2202, eval/top-1-acc: 0.9589, eval/balanced_acc: 0.9616, eval/precision: 0.9566, eval/recall: 0.9616, eval/F1: 0.9575, lr: 0.0000, train/prefecth_time: 0.0032 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 17:31:17,140 INFO] 51456 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0013, train/total_loss: -0.0108, train/util_ratio: 0.8750, train/run_time: 0.1680, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 17:32:06,570 INFO] 51712 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0297, train/total_loss: 0.0176, train/util_ratio: 1.0000, train/run_time: 0.1568, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 17:32:56,338 INFO] 51968 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0129, train/total_loss: -0.0017, train/util_ratio: 1.0000, train/run_time: 0.1592, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-27 17:33:45,915 INFO] 52224 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0057, train/total_loss: -0.0065, train/util_ratio: 0.8750, train/run_time: 0.1590, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 17:35:19,035 INFO] 52480 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0218, train/total_loss: 0.0097, train/util_ratio: 1.0000, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 17:36:08,672 INFO] 52736 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0071, train/total_loss: -0.0025, train/util_ratio: 1.0000, train/run_time: 0.1624, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-27 17:36:58,410 INFO] 52992 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0248, train/total_loss: 0.0102, train/util_ratio: 1.0000, train/run_time: 0.1572, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 17:37:47,625 INFO] validating...
[2023-08-27 17:38:12,148 INFO] confusion matrix:
[[0.92333333 0.00166667 0.00333333 0.         0.         0.00833333
  0.06       0.         0.00333333 0.        ]
 [0.         0.985      0.005      0.         0.         0.00666667
  0.         0.00333333 0.         0.        ]
 [0.         0.00333333 0.81       0.00166667 0.         0.15
  0.02833333 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.98
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.002
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01666667 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.         0.         0.
  0.         0.         0.99599198 0.        ]
 [0.00833333 0.         0.015      0.00166667 0.         0.005
  0.         0.         0.00333333 0.96666667]]
[2023-08-27 17:38:12,941 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 17:38:12,942 INFO] 53248 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0176, train/total_loss: 0.0055, train/util_ratio: 1.0000, train/run_time: 0.1582, eval/loss: 0.2280, eval/top-1-acc: 0.9570, eval/balanced_acc: 0.9599, eval/precision: 0.9549, eval/recall: 0.9599, eval/F1: 0.9556, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 17:39:45,012 INFO] 53504 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0273, train/total_loss: 0.0127, train/util_ratio: 0.8750, train/run_time: 0.1595, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 17:40:34,873 INFO] 53760 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0015, train/total_loss: -0.0181, train/util_ratio: 0.8750, train/run_time: 0.1780, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 17:41:24,426 INFO] 54016 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0598, train/total_loss: 0.0477, train/util_ratio: 0.8750, train/run_time: 0.1591, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 17:42:14,050 INFO] 54272 iteration USE_EMA: True, train/sup_loss: 0.0007, train/unsup_loss: 0.0251, train/total_loss: 0.0137, train/util_ratio: 1.0000, train/run_time: 0.1662, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 17:43:47,232 INFO] 54528 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1442, train/total_loss: 0.1320, train/util_ratio: 1.0000, train/run_time: 0.1743, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 17:44:36,752 INFO] 54784 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0040, train/total_loss: -0.0130, train/util_ratio: 0.8750, train/run_time: 0.1706, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 17:45:26,324 INFO] 55040 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.9283, train/total_loss: 0.9162, train/util_ratio: 1.0000, train/run_time: 0.1675, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-27 17:46:15,795 INFO] validating...
[2023-08-27 17:46:40,232 INFO] confusion matrix:
[[0.925      0.00333333 0.00333333 0.         0.         0.00833333
  0.05833333 0.         0.00166667 0.        ]
 [0.         0.98833333 0.00833333 0.         0.         0.00333333
  0.         0.         0.         0.        ]
 [0.         0.00333333 0.81166667 0.00166667 0.         0.15
  0.02666667 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.98
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01666667 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.         0.         0.
  0.         0.         0.99599198 0.        ]
 [0.00833333 0.         0.015      0.00166667 0.         0.005
  0.         0.         0.00333333 0.96666667]]
[2023-08-27 17:46:41,178 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 17:46:41,180 INFO] 55296 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.5225, train/total_loss: 0.5129, train/util_ratio: 1.0000, train/run_time: 0.1667, eval/loss: 0.2332, eval/top-1-acc: 0.9580, eval/balanced_acc: 0.9608, eval/precision: 0.9557, eval/recall: 0.9608, eval/F1: 0.9565, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 17:48:13,186 INFO] 55552 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0433, train/total_loss: 0.0312, train/util_ratio: 1.0000, train/run_time: 0.1641, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 17:49:03,039 INFO] 55808 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0020, train/total_loss: -0.0125, train/util_ratio: 1.0000, train/run_time: 0.1614, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 17:49:52,573 INFO] 56064 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0052, train/total_loss: -0.0044, train/util_ratio: 0.8750, train/run_time: 0.1678, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-27 17:50:42,341 INFO] 56320 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1513, train/total_loss: 0.1367, train/util_ratio: 1.0000, train/run_time: 0.1707, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 17:52:14,958 INFO] 56576 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0497, train/total_loss: 0.0351, train/util_ratio: 1.0000, train/run_time: 0.1653, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 17:53:04,336 INFO] 56832 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.6596, train/total_loss: 0.6450, train/util_ratio: 1.0000, train/run_time: 0.1665, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 17:53:53,849 INFO] 57088 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0274, train/total_loss: 0.0153, train/util_ratio: 1.0000, train/run_time: 0.1575, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 17:54:43,435 INFO] validating...
[2023-08-27 17:55:07,724 INFO] confusion matrix:
[[0.92       0.00333333 0.00333333 0.         0.         0.00833333
  0.06333333 0.         0.00166667 0.        ]
 [0.         0.98666667 0.00833333 0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00333333 0.81166667 0.00166667 0.         0.14833333
  0.02833333 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.9825
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.022      0.004      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01666667 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.         0.         0.
  0.         0.         0.99599198 0.        ]
 [0.00833333 0.         0.015      0.00166667 0.         0.005
  0.         0.         0.00333333 0.96666667]]
[2023-08-27 17:55:08,509 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 17:55:08,510 INFO] 57344 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0549, train/total_loss: 0.0454, train/util_ratio: 1.0000, train/run_time: 0.1608, eval/loss: 0.2364, eval/top-1-acc: 0.9576, eval/balanced_acc: 0.9605, eval/precision: 0.9555, eval/recall: 0.9605, eval/F1: 0.9562, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 17:56:40,866 INFO] 57600 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0928, train/total_loss: 0.0784, train/util_ratio: 1.0000, train/run_time: 0.1580, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 17:57:30,096 INFO] 57856 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0019, train/total_loss: -0.0152, train/util_ratio: 1.0000, train/run_time: 0.1696, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 17:58:19,552 INFO] 58112 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0451, train/total_loss: 0.0305, train/util_ratio: 1.0000, train/run_time: 0.1632, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 17:59:09,289 INFO] 58368 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0615, train/total_loss: 0.0520, train/util_ratio: 1.0000, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-27 18:00:42,780 INFO] 58624 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0002, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1602, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 18:01:32,580 INFO] 58880 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0043, train/total_loss: -0.0053, train/util_ratio: 1.0000, train/run_time: 0.1657, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 18:02:22,274 INFO] 59136 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.8114, train/total_loss: 0.7992, train/util_ratio: 1.0000, train/run_time: 0.1610, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 18:03:12,372 INFO] validating...
[2023-08-27 18:03:37,030 INFO] confusion matrix:
[[0.91333333 0.00333333 0.00333333 0.         0.         0.00833333
  0.07       0.         0.00166667 0.        ]
 [0.         0.98666667 0.00833333 0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00333333 0.815      0.00166667 0.         0.14666667
  0.02666667 0.00333333 0.00333333 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.9825
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.02       0.004      0.         0.
  0.974      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01666667 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.         0.         0.
  0.         0.         0.99398798 0.00200401]
 [0.00833333 0.         0.01333333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96833333]]
[2023-08-27 18:03:37,889 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 18:03:37,891 INFO] 59392 iteration, USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0339, train/total_loss: 0.0195, train/util_ratio: 1.0000, train/run_time: 0.1573, eval/loss: 0.2397, eval/top-1-acc: 0.9574, eval/balanced_acc: 0.9604, eval/precision: 0.9554, eval/recall: 0.9604, eval/F1: 0.9561, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 18:05:10,181 INFO] 59648 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0007, train/total_loss: -0.0138, train/util_ratio: 0.8750, train/run_time: 0.1671, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 18:06:00,259 INFO] 59904 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0473, train/total_loss: 0.0401, train/util_ratio: 1.0000, train/run_time: 0.1608, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 18:06:50,181 INFO] 60160 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0019, train/total_loss: -0.0152, train/util_ratio: 1.0000, train/run_time: 0.1625, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 18:07:39,862 INFO] 60416 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0279, train/total_loss: 0.0159, train/util_ratio: 1.0000, train/run_time: 0.1592, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 18:09:12,529 INFO] 60672 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0618, train/total_loss: 0.0472, train/util_ratio: 1.0000, train/run_time: 0.1682, lr: 0.0000, train/prefecth_time: 0.0041 
[2023-08-27 18:10:02,018 INFO] 60928 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0075, train/total_loss: -0.0021, train/util_ratio: 1.0000, train/run_time: 0.1606, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 18:10:51,553 INFO] 61184 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0014, train/total_loss: -0.0107, train/util_ratio: 1.0000, train/run_time: 0.1748, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-27 18:11:41,130 INFO] validating...
[2023-08-27 18:12:05,787 INFO] confusion matrix:
[[0.91166667 0.00333333 0.00333333 0.         0.         0.00833333
  0.07166667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.00833333 0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.81666667 0.00166667 0.         0.14666667
  0.02666667 0.005      0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.9825
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.02       0.004      0.         0.
  0.974      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01666667 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.         0.         0.
  0.         0.         0.99398798 0.00200401]
 [0.00833333 0.         0.01333333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96833333]]
[2023-08-27 18:12:06,606 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 18:12:06,608 INFO] 61440 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3558, train/total_loss: 0.3461, train/util_ratio: 1.0000, train/run_time: 0.1661, eval/loss: 0.2421, eval/top-1-acc: 0.9572, eval/balanced_acc: 0.9602, eval/precision: 0.9552, eval/recall: 0.9602, eval/F1: 0.9559, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 18:13:38,936 INFO] 61696 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.2785, train/total_loss: 0.2614, train/util_ratio: 1.0000, train/run_time: 0.1635, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 18:14:28,574 INFO] 61952 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0182, train/total_loss: 0.0011, train/util_ratio: 1.0000, train/run_time: 0.1748, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 18:15:17,986 INFO] 62208 iteration USE_EMA: True, train/sup_loss: 0.0025, train/unsup_loss: 0.0165, train/total_loss: 0.0044, train/util_ratio: 1.0000, train/run_time: 0.1601, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 18:16:07,825 INFO] 62464 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1047, train/total_loss: 0.0950, train/util_ratio: 1.0000, train/run_time: 0.1653, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 18:17:40,677 INFO] 62720 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1174, train/total_loss: 0.1052, train/util_ratio: 1.0000, train/run_time: 0.1647, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 18:18:30,212 INFO] 62976 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1459, train/total_loss: 0.1338, train/util_ratio: 1.0000, train/run_time: 0.1642, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-27 18:19:20,217 INFO] 63232 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0145, train/total_loss: -0.0001, train/util_ratio: 1.0000, train/run_time: 0.1648, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 18:20:09,890 INFO] validating...
[2023-08-27 18:20:34,194 INFO] confusion matrix:
[[0.91       0.00333333 0.00333333 0.         0.         0.00833333
  0.07333333 0.         0.00166667 0.        ]
 [0.         0.98666667 0.00833333 0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.81833333 0.00166667 0.         0.14666667
  0.02666667 0.00333333 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.02       0.002      0.         0.
  0.976      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01666667 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.         0.         0.
  0.         0.         0.99398798 0.00200401]
 [0.00833333 0.         0.015      0.00166667 0.         0.005
  0.         0.         0.00333333 0.96666667]]
[2023-08-27 18:20:35,108 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 18:20:35,109 INFO] 63488 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0046, train/total_loss: -0.0100, train/util_ratio: 1.0000, train/run_time: 0.1743, eval/loss: 0.2423, eval/top-1-acc: 0.9576, eval/balanced_acc: 0.9607, eval/precision: 0.9557, eval/recall: 0.9607, eval/F1: 0.9563, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 18:22:07,160 INFO] 63744 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0044, train/total_loss: -0.0077, train/util_ratio: 1.0000, train/run_time: 0.1691, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 18:22:56,883 INFO] 64000 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0015, train/total_loss: -0.0131, train/util_ratio: 1.0000, train/run_time: 0.1705, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 18:23:46,424 INFO] 64256 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0035, train/total_loss: -0.0086, train/util_ratio: 1.0000, train/run_time: 0.1663, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-27 18:24:35,923 INFO] 64512 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0148, train/total_loss: -0.0020, train/util_ratio: 1.0000, train/run_time: 0.1658, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 18:26:08,956 INFO] 64768 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0002, train/total_loss: -0.0144, train/util_ratio: 0.8750, train/run_time: 0.1686, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 18:26:58,516 INFO] 65024 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.3064, train/total_loss: 0.2943, train/util_ratio: 1.0000, train/run_time: 0.1798, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 18:27:48,289 INFO] 65280 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0001, train/total_loss: -0.0169, train/util_ratio: 0.8750, train/run_time: 0.1806, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 18:28:37,838 INFO] validating...
[2023-08-27 18:29:02,009 INFO] confusion matrix:
[[0.905      0.00333333 0.00333333 0.         0.         0.00833333
  0.07833333 0.         0.00166667 0.        ]
 [0.         0.98666667 0.00666667 0.         0.         0.005
  0.         0.00166667 0.         0.        ]
 [0.         0.00166667 0.82333333 0.00166667 0.         0.14333333
  0.025      0.00333333 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.9825
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.02       0.002      0.         0.
  0.976      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01666667 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.         0.         0.
  0.         0.         0.99398798 0.00200401]
 [0.00833333 0.00166667 0.015      0.00166667 0.         0.005
  0.         0.         0.00333333 0.965     ]]
[2023-08-27 18:29:02,819 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 18:29:02,820 INFO] 65536 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0521, train/total_loss: 0.0401, train/util_ratio: 0.8750, train/run_time: 0.1654, eval/loss: 0.2457, eval/top-1-acc: 0.9574, eval/balanced_acc: 0.9604, eval/precision: 0.9555, eval/recall: 0.9604, eval/F1: 0.9562, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 18:30:35,696 INFO] 65792 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1074, train/total_loss: 0.0953, train/util_ratio: 1.0000, train/run_time: 0.1720, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 18:31:25,490 INFO] 66048 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0002, train/total_loss: -0.0143, train/util_ratio: 0.8750, train/run_time: 0.1571, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 18:32:14,992 INFO] 66304 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0237, train/total_loss: 0.0092, train/util_ratio: 1.0000, train/run_time: 0.1668, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 18:33:04,586 INFO] 66560 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3067, train/total_loss: 0.2970, train/util_ratio: 1.0000, train/run_time: 0.1675, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 18:34:37,744 INFO] 66816 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1731, train/total_loss: 0.1560, train/util_ratio: 0.8750, train/run_time: 0.1637, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 18:35:27,242 INFO] 67072 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3316, train/total_loss: 0.3170, train/util_ratio: 1.0000, train/run_time: 0.1616, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-27 18:36:16,728 INFO] 67328 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.2561, train/total_loss: 0.2416, train/util_ratio: 1.0000, train/run_time: 0.1612, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 18:37:06,632 INFO] validating...
[2023-08-27 18:37:31,066 INFO] confusion matrix:
[[0.90666667 0.00333333 0.00333333 0.         0.         0.00833333
  0.07666667 0.         0.00166667 0.        ]
 [0.         0.985      0.00666667 0.         0.         0.00666667
  0.         0.00166667 0.         0.        ]
 [0.         0.00166667 0.83       0.00166667 0.         0.14
  0.02333333 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.9825
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.02       0.002      0.         0.
  0.976      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01666667 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.         0.         0.
  0.         0.         0.99398798 0.00200401]
 [0.00833333 0.00166667 0.015      0.00166667 0.         0.005
  0.         0.         0.00333333 0.965     ]]
[2023-08-27 18:37:31,959 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 18:37:31,961 INFO] 67584 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0006, train/total_loss: -0.0114, train/util_ratio: 1.0000, train/run_time: 0.1570, eval/loss: 0.2477, eval/top-1-acc: 0.9581, eval/balanced_acc: 0.9611, eval/precision: 0.9562, eval/recall: 0.9611, eval/F1: 0.9569, lr: 0.0000, train/prefecth_time: 0.0032 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 18:39:04,175 INFO] 67840 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0267, train/total_loss: 0.0121, train/util_ratio: 1.0000, train/run_time: 0.1650, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 18:39:53,730 INFO] 68096 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.2465, train/total_loss: 0.2319, train/util_ratio: 1.0000, train/run_time: 0.1688, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 18:40:43,517 INFO] 68352 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1011, train/total_loss: 0.0890, train/util_ratio: 1.0000, train/run_time: 0.1602, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 18:41:32,921 INFO] 68608 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2655, train/total_loss: 0.2484, train/util_ratio: 1.0000, train/run_time: 0.1598, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 18:43:06,343 INFO] 68864 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0949, train/total_loss: 0.0853, train/util_ratio: 1.0000, train/run_time: 0.1704, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 18:43:55,782 INFO] 69120 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0956, train/total_loss: 0.0810, train/util_ratio: 1.0000, train/run_time: 0.1607, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 18:44:45,434 INFO] 69376 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0048, train/total_loss: -0.0049, train/util_ratio: 1.0000, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 18:45:34,697 INFO] validating...
[2023-08-27 18:45:58,929 INFO] confusion matrix:
[[0.90166667 0.00333333 0.00333333 0.         0.         0.00833333
  0.08166667 0.         0.00166667 0.        ]
 [0.         0.985      0.00666667 0.         0.         0.00666667
  0.         0.00166667 0.         0.        ]
 [0.         0.00166667 0.835      0.00166667 0.         0.13666667
  0.02166667 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.9825
  0.0025     0.         0.0025     0.        ]
 [0.002      0.         0.02       0.002      0.         0.
  0.976      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01666667 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.         0.         0.
  0.         0.         0.99398798 0.00200401]
 [0.00833333 0.00166667 0.01666667 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96333333]]
[2023-08-27 18:45:59,742 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 18:45:59,743 INFO] 69632 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1906, train/total_loss: 0.1760, train/util_ratio: 1.0000, train/run_time: 0.1593, eval/loss: 0.2467, eval/top-1-acc: 0.9580, eval/balanced_acc: 0.9609, eval/precision: 0.9561, eval/recall: 0.9609, eval/F1: 0.9568, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 18:47:31,999 INFO] 69888 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0969, train/total_loss: 0.0823, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 18:48:21,792 INFO] 70144 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0004, train/total_loss: -0.0141, train/util_ratio: 1.0000, train/run_time: 0.1673, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-27 18:49:11,417 INFO] 70400 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0194, train/total_loss: 0.0100, train/util_ratio: 1.0000, train/run_time: 0.1655, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 18:50:01,207 INFO] 70656 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.9999, train/total_loss: 0.9878, train/util_ratio: 1.0000, train/run_time: 0.1685, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 18:51:34,631 INFO] 70912 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0009, train/total_loss: -0.0112, train/util_ratio: 1.0000, train/run_time: 0.1610, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 18:52:24,324 INFO] 71168 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1439, train/total_loss: 0.1293, train/util_ratio: 1.0000, train/run_time: 0.1695, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 18:53:14,114 INFO] 71424 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0411, train/total_loss: 0.0265, train/util_ratio: 1.0000, train/run_time: 0.1735, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 18:54:03,696 INFO] validating...
[2023-08-27 18:54:28,077 INFO] confusion matrix:
[[0.89666667 0.00333333 0.00333333 0.         0.         0.00833333
  0.08666667 0.         0.00166667 0.        ]
 [0.         0.985      0.00666667 0.         0.         0.00666667
  0.         0.00166667 0.         0.        ]
 [0.         0.00166667 0.84333333 0.00166667 0.         0.13
  0.01833333 0.00333333 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.02       0.002      0.         0.
  0.976      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01666667 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.01833333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96166667]]
[2023-08-27 18:54:29,027 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 18:54:29,028 INFO] 71680 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1087, train/total_loss: 0.0941, train/util_ratio: 1.0000, train/run_time: 0.1648, eval/loss: 0.2475, eval/top-1-acc: 0.9581, eval/balanced_acc: 0.9611, eval/precision: 0.9563, eval/recall: 0.9611, eval/F1: 0.9571, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 18:56:01,455 INFO] 71936 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0008, train/total_loss: -0.0113, train/util_ratio: 1.0000, train/run_time: 0.1717, lr: 0.0000, train/prefecth_time: 0.0041 
[2023-08-27 18:56:51,372 INFO] 72192 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0393, train/total_loss: 0.0272, train/util_ratio: 0.8750, train/run_time: 0.1805, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 18:57:40,883 INFO] 72448 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0069, train/total_loss: -0.0028, train/util_ratio: 1.0000, train/run_time: 0.1771, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 18:58:30,740 INFO] 72704 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0040, train/total_loss: -0.0106, train/util_ratio: 0.8750, train/run_time: 0.1604, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 19:00:03,612 INFO] 72960 iteration USE_EMA: True, train/sup_loss: 0.0026, train/unsup_loss: 0.0003, train/total_loss: -0.0117, train/util_ratio: 1.0000, train/run_time: 0.1609, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 19:00:53,240 INFO] 73216 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: -0.0091, train/util_ratio: 1.0000, train/run_time: 0.1589, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-27 19:01:42,962 INFO] 73472 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0496, train/total_loss: 0.0400, train/util_ratio: 1.0000, train/run_time: 0.1629, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 19:02:32,369 INFO] validating...
[2023-08-27 19:02:56,531 INFO] confusion matrix:
[[0.89833333 0.00333333 0.00333333 0.         0.         0.00833333
  0.085      0.         0.00166667 0.        ]
 [0.         0.98666667 0.00666667 0.         0.         0.00666667
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.84166667 0.00166667 0.         0.13333333
  0.01833333 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.02       0.002      0.         0.
  0.976      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01666667 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.01833333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96166667]]
[2023-08-27 19:02:57,426 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 19:02:57,427 INFO] 73728 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: -0.0116, train/util_ratio: 1.0000, train/run_time: 0.1600, eval/loss: 0.2507, eval/top-1-acc: 0.9583, eval/balanced_acc: 0.9613, eval/precision: 0.9565, eval/recall: 0.9613, eval/F1: 0.9572, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 19:04:29,812 INFO] 73984 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0298, train/total_loss: 0.0127, train/util_ratio: 0.8750, train/run_time: 0.1575, lr: 0.0000, train/prefecth_time: 0.0048 
[2023-08-27 19:05:19,668 INFO] 74240 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0516, train/total_loss: 0.0369, train/util_ratio: 1.0000, train/run_time: 0.1663, lr: 0.0000, train/prefecth_time: 0.0053 
[2023-08-27 19:06:09,489 INFO] 74496 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2272, train/total_loss: 0.2175, train/util_ratio: 1.0000, train/run_time: 0.1702, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 19:06:59,272 INFO] 74752 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0088, train/total_loss: -0.0083, train/util_ratio: 1.0000, train/run_time: 0.1664, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-27 19:08:32,526 INFO] 75008 iteration USE_EMA: True, train/sup_loss: 0.0018, train/unsup_loss: 0.0348, train/total_loss: 0.0245, train/util_ratio: 1.0000, train/run_time: 0.1681, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 19:09:22,562 INFO] 75264 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0158, train/total_loss: 0.0012, train/util_ratio: 1.0000, train/run_time: 0.1677, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 19:10:12,154 INFO] 75520 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0194, train/total_loss: 0.0022, train/util_ratio: 1.0000, train/run_time: 0.1706, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 19:11:01,757 INFO] validating...
[2023-08-27 19:11:26,205 INFO] confusion matrix:
[[0.9        0.00333333 0.00333333 0.         0.         0.00833333
  0.08333333 0.         0.00166667 0.        ]
 [0.         0.98833333 0.005      0.         0.         0.00666667
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.84       0.00166667 0.         0.135
  0.01833333 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.022      0.002      0.         0.
  0.974      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01666667 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.01833333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96166667]]
[2023-08-27 19:11:26,974 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 19:11:26,975 INFO] 75776 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0213, train/total_loss: 0.0042, train/util_ratio: 0.8750, train/run_time: 0.1684, eval/loss: 0.2552, eval/top-1-acc: 0.9585, eval/balanced_acc: 0.9614, eval/precision: 0.9566, eval/recall: 0.9614, eval/F1: 0.9574, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 19:12:59,307 INFO] 76032 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0076, train/total_loss: -0.0070, train/util_ratio: 1.0000, train/run_time: 0.1656, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 19:13:48,972 INFO] 76288 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2000, train/total_loss: 0.1879, train/util_ratio: 1.0000, train/run_time: 0.1598, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 19:14:38,741 INFO] 76544 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1588, train/total_loss: 0.1442, train/util_ratio: 1.0000, train/run_time: 0.1808, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-27 19:15:28,519 INFO] 76800 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0019, train/total_loss: -0.0127, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 19:17:01,848 INFO] 77056 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0112, train/total_loss: -0.0034, train/util_ratio: 1.0000, train/run_time: 0.1595, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 19:17:51,470 INFO] 77312 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0064, train/total_loss: -0.0081, train/util_ratio: 1.0000, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 19:18:41,227 INFO] 77568 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0419, train/total_loss: 0.0273, train/util_ratio: 1.0000, train/run_time: 0.1665, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 19:19:31,055 INFO] validating...
[2023-08-27 19:19:55,797 INFO] confusion matrix:
[[0.9        0.00333333 0.00333333 0.         0.         0.00833333
  0.08333333 0.         0.00166667 0.        ]
 [0.         0.98833333 0.005      0.         0.         0.00666667
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.83666667 0.00166667 0.         0.13833333
  0.01833333 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.022      0.002      0.         0.
  0.974      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.01833333 0.00166667 0.         0.00333333
  0.         0.         0.00333333 0.96333333]]
[2023-08-27 19:19:56,808 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 19:19:56,809 INFO] 77824 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.3200, train/total_loss: 0.3054, train/util_ratio: 1.0000, train/run_time: 0.1579, eval/loss: 0.2599, eval/top-1-acc: 0.9576, eval/balanced_acc: 0.9605, eval/precision: 0.9557, eval/recall: 0.9605, eval/F1: 0.9564, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 19:21:28,701 INFO] 78080 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0002, train/total_loss: -0.0119, train/util_ratio: 1.0000, train/run_time: 0.1724, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 19:22:18,192 INFO] 78336 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0135, train/total_loss: -0.0036, train/util_ratio: 0.8750, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 19:23:08,086 INFO] 78592 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0049, train/total_loss: -0.0072, train/util_ratio: 1.0000, train/run_time: 0.1738, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 19:23:57,934 INFO] 78848 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0004, train/total_loss: -0.0167, train/util_ratio: 1.0000, train/run_time: 0.1661, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 19:25:30,618 INFO] 79104 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0015, train/total_loss: -0.0081, train/util_ratio: 1.0000, train/run_time: 0.1705, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 19:26:20,296 INFO] 79360 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1284, train/total_loss: 0.1163, train/util_ratio: 1.0000, train/run_time: 0.1628, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 19:27:10,122 INFO] 79616 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3623, train/total_loss: 0.3477, train/util_ratio: 0.8750, train/run_time: 0.1716, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 19:27:59,753 INFO] validating...
[2023-08-27 19:28:24,196 INFO] confusion matrix:
[[0.9        0.00333333 0.00333333 0.         0.         0.00833333
  0.08333333 0.         0.00166667 0.        ]
 [0.         0.99       0.005      0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.84       0.00166667 0.         0.135
  0.01833333 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.01833333 0.00166667 0.         0.00333333
  0.         0.         0.00333333 0.96333333]]
[2023-08-27 19:28:24,955 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 19:28:24,956 INFO] 79872 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0143, train/util_ratio: 1.0000, train/run_time: 0.1655, eval/loss: 0.2605, eval/top-1-acc: 0.9580, eval/balanced_acc: 0.9608, eval/precision: 0.9560, eval/recall: 0.9608, eval/F1: 0.9568, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 19:29:56,937 INFO] 80128 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0056, train/total_loss: -0.0090, train/util_ratio: 1.0000, train/run_time: 0.1699, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 19:30:46,537 INFO] 80384 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0832, train/total_loss: 0.0711, train/util_ratio: 1.0000, train/run_time: 0.1730, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 19:31:36,193 INFO] 80640 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0136, train/total_loss: -0.0035, train/util_ratio: 1.0000, train/run_time: 0.1654, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 19:32:26,003 INFO] 80896 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1344, train/total_loss: 0.1248, train/util_ratio: 1.0000, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 19:33:59,264 INFO] 81152 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0250, train/total_loss: 0.0079, train/util_ratio: 1.0000, train/run_time: 0.1563, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 19:34:48,943 INFO] 81408 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1652, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 19:35:38,815 INFO] 81664 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0847, train/total_loss: 0.0677, train/util_ratio: 1.0000, train/run_time: 0.1651, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-27 19:36:28,369 INFO] validating...
[2023-08-27 19:36:52,613 INFO] confusion matrix:
[[0.90166667 0.00333333 0.00333333 0.         0.         0.00833333
  0.08166667 0.         0.00166667 0.        ]
 [0.         0.99       0.005      0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.83833333 0.00166667 0.         0.13833333
  0.01666667 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02166667 0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.01833333 0.00166667 0.         0.005
  0.         0.         0.00333333 0.96166667]]
[2023-08-27 19:36:53,599 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 19:36:53,600 INFO] 81920 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0017, train/total_loss: -0.0154, train/util_ratio: 1.0000, train/run_time: 0.1572, eval/loss: 0.2676, eval/top-1-acc: 0.9574, eval/balanced_acc: 0.9603, eval/precision: 0.9554, eval/recall: 0.9603, eval/F1: 0.9562, lr: 0.0000, train/prefecth_time: 0.0037 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 19:38:26,021 INFO] 82176 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2409, train/total_loss: 0.2288, train/util_ratio: 1.0000, train/run_time: 0.1669, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 19:39:15,584 INFO] 82432 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0199, train/total_loss: 0.0103, train/util_ratio: 1.0000, train/run_time: 0.1748, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 19:40:05,252 INFO] 82688 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1787, train/total_loss: 0.1714, train/util_ratio: 1.0000, train/run_time: 0.1717, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 19:40:54,576 INFO] 82944 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0031, train/total_loss: -0.0115, train/util_ratio: 0.8750, train/run_time: 0.1678, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 19:42:27,603 INFO] 83200 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0796, train/total_loss: 0.0650, train/util_ratio: 1.0000, train/run_time: 0.1592, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-27 19:43:17,370 INFO] 83456 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0065, train/total_loss: -0.0056, train/util_ratio: 1.0000, train/run_time: 0.1754, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 19:44:06,917 INFO] 83712 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1014, train/total_loss: 0.0942, train/util_ratio: 1.0000, train/run_time: 0.1675, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 19:44:56,475 INFO] validating...
[2023-08-27 19:45:20,049 INFO] confusion matrix:
[[0.90333333 0.00333333 0.00333333 0.         0.         0.00833333
  0.08       0.         0.00166667 0.        ]
 [0.         0.99       0.005      0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.84       0.00166667 0.         0.13666667
  0.01666667 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.0025     0.0025     0.005      0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02166667 0.
  0.         0.97666667 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.02       0.00166667 0.         0.005
  0.         0.         0.00333333 0.96      ]]
[2023-08-27 19:45:20,779 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 19:45:20,780 INFO] 83968 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0609, train/total_loss: 0.0463, train/util_ratio: 1.0000, train/run_time: 0.1575, eval/loss: 0.2733, eval/top-1-acc: 0.9576, eval/balanced_acc: 0.9605, eval/precision: 0.9556, eval/recall: 0.9605, eval/F1: 0.9565, lr: 0.0000, train/prefecth_time: 0.0032 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 19:46:53,464 INFO] 84224 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3940, train/total_loss: 0.3794, train/util_ratio: 1.0000, train/run_time: 0.1647, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 19:47:43,331 INFO] 84480 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0872, train/total_loss: 0.0751, train/util_ratio: 1.0000, train/run_time: 0.1598, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 19:48:33,032 INFO] 84736 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0041, train/total_loss: -0.0031, train/util_ratio: 1.0000, train/run_time: 0.1594, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 19:49:22,478 INFO] 84992 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1118, train/total_loss: 0.0972, train/util_ratio: 1.0000, train/run_time: 0.1621, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 19:50:55,012 INFO] 85248 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0283, train/total_loss: 0.0112, train/util_ratio: 1.0000, train/run_time: 0.1601, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 19:51:44,622 INFO] 85504 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1778, train/total_loss: 0.1632, train/util_ratio: 1.0000, train/run_time: 0.1690, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 19:52:34,224 INFO] 85760 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0008, train/total_loss: -0.0163, train/util_ratio: 0.8750, train/run_time: 0.1761, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 19:53:23,680 INFO] validating...
[2023-08-27 19:53:48,195 INFO] confusion matrix:
[[0.905      0.00333333 0.00333333 0.         0.         0.00833333
  0.07833333 0.         0.00166667 0.        ]
 [0.         0.99       0.005      0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.84       0.00166667 0.         0.13833333
  0.015      0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.02166667 0.00166667 0.         0.005
  0.         0.         0.00333333 0.95666667]]
[2023-08-27 19:53:48,930 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 19:53:48,931 INFO] 86016 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1213, train/total_loss: 0.1067, train/util_ratio: 1.0000, train/run_time: 0.1669, eval/loss: 0.2793, eval/top-1-acc: 0.9576, eval/balanced_acc: 0.9604, eval/precision: 0.9556, eval/recall: 0.9604, eval/F1: 0.9565, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 19:55:21,482 INFO] 86272 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: -0.0140, train/util_ratio: 1.0000, train/run_time: 0.1734, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 19:56:10,978 INFO] 86528 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0197, train/total_loss: 0.0077, train/util_ratio: 1.0000, train/run_time: 0.1567, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 19:57:00,595 INFO] 86784 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1892, train/total_loss: 0.1721, train/util_ratio: 1.0000, train/run_time: 0.1653, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 19:57:50,417 INFO] 87040 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0014, train/total_loss: -0.0107, train/util_ratio: 1.0000, train/run_time: 0.1706, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 19:59:23,372 INFO] 87296 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0137, train/total_loss: 0.0016, train/util_ratio: 0.7500, train/run_time: 0.1742, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 20:00:13,309 INFO] 87552 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0282, train/total_loss: 0.0136, train/util_ratio: 1.0000, train/run_time: 0.1674, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 20:01:03,394 INFO] 87808 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0055, train/total_loss: -0.0091, train/util_ratio: 0.8750, train/run_time: 0.1573, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 20:01:52,940 INFO] validating...
[2023-08-27 20:02:17,646 INFO] confusion matrix:
[[0.905      0.00333333 0.00333333 0.         0.         0.01
  0.07666667 0.         0.00166667 0.        ]
 [0.         0.99       0.005      0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.84166667 0.00166667 0.         0.13833333
  0.015      0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.02166667 0.00166667 0.         0.005
  0.         0.         0.005      0.955     ]]
[2023-08-27 20:02:18,378 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 20:02:18,380 INFO] 88064 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0016, train/total_loss: -0.0105, train/util_ratio: 1.0000, train/run_time: 0.1673, eval/loss: 0.2842, eval/top-1-acc: 0.9576, eval/balanced_acc: 0.9604, eval/precision: 0.9556, eval/recall: 0.9604, eval/F1: 0.9565, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 20:03:50,854 INFO] 88320 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0327, train/total_loss: 0.0181, train/util_ratio: 1.0000, train/run_time: 0.1761, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 20:04:40,454 INFO] 88576 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0158, train/total_loss: 0.0037, train/util_ratio: 1.0000, train/run_time: 0.1778, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 20:05:30,244 INFO] 88832 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0066, train/total_loss: -0.0080, train/util_ratio: 0.8750, train/run_time: 0.1607, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 20:06:20,036 INFO] 89088 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0692, train/total_loss: 0.0546, train/util_ratio: 1.0000, train/run_time: 0.1664, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 20:07:53,502 INFO] 89344 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1642, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-27 20:08:42,851 INFO] 89600 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0048, train/total_loss: -0.0098, train/util_ratio: 0.8750, train/run_time: 0.1611, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 20:09:32,575 INFO] 89856 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0140, train/total_loss: -0.0006, train/util_ratio: 1.0000, train/run_time: 0.1692, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 20:10:22,278 INFO] validating...
[2023-08-27 20:10:46,854 INFO] confusion matrix:
[[0.905      0.00333333 0.00333333 0.         0.         0.01
  0.07666667 0.         0.00166667 0.        ]
 [0.         0.99       0.005      0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.00166667 0.84166667 0.00166667 0.         0.14
  0.01333333 0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.02166667 0.00166667 0.         0.005
  0.         0.         0.005      0.955     ]]
[2023-08-27 20:10:47,902 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 20:10:47,904 INFO] 90112 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0308, train/total_loss: 0.0236, train/util_ratio: 1.0000, train/run_time: 0.1682, eval/loss: 0.2879, eval/top-1-acc: 0.9578, eval/balanced_acc: 0.9607, eval/precision: 0.9558, eval/recall: 0.9607, eval/F1: 0.9567, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 20:12:19,521 INFO] 90368 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0296, train/total_loss: 0.0199, train/util_ratio: 1.0000, train/run_time: 0.1684, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 20:13:09,269 INFO] 90624 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0052, train/total_loss: -0.0044, train/util_ratio: 1.0000, train/run_time: 0.1714, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 20:13:58,713 INFO] 90880 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0400, train/total_loss: 0.0304, train/util_ratio: 1.0000, train/run_time: 0.1654, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 20:14:48,227 INFO] 91136 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0036, train/total_loss: -0.0086, train/util_ratio: 1.0000, train/run_time: 0.1668, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-27 20:16:21,271 INFO] 91392 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1444, train/total_loss: 0.1298, train/util_ratio: 1.0000, train/run_time: 0.1645, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-27 20:17:10,758 INFO] 91648 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0036, train/total_loss: -0.0111, train/util_ratio: 1.0000, train/run_time: 0.1585, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 20:18:00,486 INFO] 91904 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1138, train/total_loss: 0.0967, train/util_ratio: 1.0000, train/run_time: 0.1582, lr: 0.0000, train/prefecth_time: 0.0048 
[2023-08-27 20:18:50,475 INFO] validating...
[2023-08-27 20:19:14,738 INFO] confusion matrix:
[[0.905      0.00333333 0.00166667 0.         0.         0.01
  0.07833333 0.         0.00166667 0.        ]
 [0.         0.99166667 0.005      0.         0.         0.00333333
  0.         0.         0.         0.        ]
 [0.         0.         0.84166667 0.00166667 0.         0.14333333
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.02166667 0.00166667 0.         0.005
  0.         0.         0.005      0.955     ]]
[2023-08-27 20:19:15,538 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 20:19:15,539 INFO] 92160 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0035, train/total_loss: -0.0086, train/util_ratio: 1.0000, train/run_time: 0.1601, eval/loss: 0.2907, eval/top-1-acc: 0.9580, eval/balanced_acc: 0.9609, eval/precision: 0.9560, eval/recall: 0.9609, eval/F1: 0.9568, lr: 0.0000, train/prefecth_time: 0.0034 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 20:20:47,624 INFO] 92416 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0247, train/total_loss: 0.0150, train/util_ratio: 1.0000, train/run_time: 0.1739, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 20:21:37,001 INFO] 92672 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0020, train/total_loss: -0.0152, train/util_ratio: 1.0000, train/run_time: 0.1604, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 20:22:26,777 INFO] 92928 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2866, train/total_loss: 0.2745, train/util_ratio: 1.0000, train/run_time: 0.1676, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 20:23:16,580 INFO] 93184 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0580, train/total_loss: 0.0459, train/util_ratio: 0.8750, train/run_time: 0.1816, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 20:24:49,321 INFO] 93440 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1662, train/total_loss: 0.1515, train/util_ratio: 0.8750, train/run_time: 0.1705, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 20:25:39,137 INFO] 93696 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0013, train/total_loss: -0.0108, train/util_ratio: 1.0000, train/run_time: 0.1619, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 20:26:28,974 INFO] 93952 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0275, train/total_loss: 0.0129, train/util_ratio: 1.0000, train/run_time: 0.1669, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 20:27:18,850 INFO] validating...
[2023-08-27 20:27:43,525 INFO] confusion matrix:
[[0.90333333 0.00333333 0.00166667 0.         0.         0.01
  0.08       0.         0.00166667 0.        ]
 [0.         0.99166667 0.005      0.         0.         0.00333333
  0.         0.         0.         0.        ]
 [0.         0.         0.84166667 0.00166667 0.         0.14333333
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.02166667 0.00166667 0.         0.00666667
  0.         0.         0.005      0.955     ]]
[2023-08-27 20:27:44,289 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 20:27:44,290 INFO] 94208 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.5014, train/total_loss: 0.4868, train/util_ratio: 1.0000, train/run_time: 0.1658, eval/loss: 0.2930, eval/top-1-acc: 0.9576, eval/balanced_acc: 0.9604, eval/precision: 0.9556, eval/recall: 0.9604, eval/F1: 0.9564, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 20:29:16,114 INFO] 94464 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0296, train/total_loss: 0.0151, train/util_ratio: 1.0000, train/run_time: 0.1665, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 20:30:05,860 INFO] 94720 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.6652, train/total_loss: 0.6531, train/util_ratio: 1.0000, train/run_time: 0.1664, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 20:30:55,482 INFO] 94976 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0285, train/total_loss: 0.0165, train/util_ratio: 1.0000, train/run_time: 0.1686, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 20:31:44,881 INFO] 95232 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0095, train/total_loss: -0.0051, train/util_ratio: 1.0000, train/run_time: 0.1688, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-27 20:33:17,717 INFO] 95488 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0017, train/total_loss: -0.0104, train/util_ratio: 1.0000, train/run_time: 0.1721, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 20:34:07,602 INFO] 95744 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0032, train/total_loss: -0.0065, train/util_ratio: 1.0000, train/run_time: 0.1669, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 20:34:57,020 INFO] 96000 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0131, train/total_loss: 0.0034, train/util_ratio: 1.0000, train/run_time: 0.1671, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 20:35:46,573 INFO] validating...
[2023-08-27 20:36:10,765 INFO] confusion matrix:
[[0.90166667 0.00333333 0.00166667 0.         0.         0.01
  0.08166667 0.         0.00166667 0.        ]
 [0.         0.99166667 0.005      0.         0.         0.00333333
  0.         0.         0.         0.        ]
 [0.         0.         0.84166667 0.00166667 0.         0.14166667
  0.01333333 0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.022      0.002      0.         0.
  0.974      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.02333333 0.00166667 0.         0.00666667
  0.         0.         0.005      0.95333333]]
[2023-08-27 20:36:11,767 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 20:36:11,769 INFO] 96256 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0768, train/total_loss: 0.0647, train/util_ratio: 1.0000, train/run_time: 0.1656, eval/loss: 0.2974, eval/top-1-acc: 0.9574, eval/balanced_acc: 0.9603, eval/precision: 0.9554, eval/recall: 0.9603, eval/F1: 0.9562, lr: 0.0000, train/prefecth_time: 0.0034 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 20:37:44,549 INFO] 96512 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0052, train/total_loss: -0.0095, train/util_ratio: 1.0000, train/run_time: 0.1769, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 20:38:34,423 INFO] 96768 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3058, train/total_loss: 0.2912, train/util_ratio: 1.0000, train/run_time: 0.1748, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 20:39:24,336 INFO] 97024 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0018, train/total_loss: -0.0128, train/util_ratio: 1.0000, train/run_time: 0.1673, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-27 20:40:14,168 INFO] 97280 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0059, train/total_loss: -0.0037, train/util_ratio: 1.0000, train/run_time: 0.1655, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 20:41:47,447 INFO] 97536 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0145, train/util_ratio: 1.0000, train/run_time: 0.1773, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 20:42:37,357 INFO] 97792 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0002, train/total_loss: -0.0143, train/util_ratio: 1.0000, train/run_time: 0.1613, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 20:43:26,972 INFO] 98048 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0036, train/total_loss: -0.0086, train/util_ratio: 1.0000, train/run_time: 0.1664, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 20:44:16,673 INFO] validating...
[2023-08-27 20:44:40,789 INFO] confusion matrix:
[[0.90166667 0.00333333 0.00166667 0.         0.         0.01
  0.08166667 0.         0.00166667 0.        ]
 [0.         0.99       0.005      0.         0.         0.005
  0.         0.         0.         0.        ]
 [0.         0.         0.84166667 0.00166667 0.         0.14166667
  0.01333333 0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.994      0.
  0.004      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.02333333 0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.955     ]]
[2023-08-27 20:44:41,647 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 20:44:41,648 INFO] 98304 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0038, train/total_loss: -0.0083, train/util_ratio: 1.0000, train/run_time: 0.1667, eval/loss: 0.2992, eval/top-1-acc: 0.9570, eval/balanced_acc: 0.9599, eval/precision: 0.9551, eval/recall: 0.9599, eval/F1: 0.9559, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 20:46:14,426 INFO] 98560 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0249, train/total_loss: 0.0128, train/util_ratio: 1.0000, train/run_time: 0.1655, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 20:47:04,057 INFO] 98816 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.0031, train/total_loss: -0.0111, train/util_ratio: 1.0000, train/run_time: 0.1607, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 20:47:53,844 INFO] 99072 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0118, train/total_loss: -0.0003, train/util_ratio: 1.0000, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 20:48:43,323 INFO] 99328 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0257, train/total_loss: 0.0160, train/util_ratio: 1.0000, train/run_time: 0.1587, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 20:50:16,461 INFO] 99584 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0413, train/total_loss: 0.0267, train/util_ratio: 1.0000, train/run_time: 0.1667, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 20:51:06,388 INFO] 99840 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0043, train/total_loss: -0.0078, train/util_ratio: 0.8750, train/run_time: 0.1683, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 20:51:56,429 INFO] 100096 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0192, train/total_loss: 0.0071, train/util_ratio: 1.0000, train/run_time: 0.1655, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 20:52:46,523 INFO] validating...
[2023-08-27 20:53:11,070 INFO] confusion matrix:
[[0.89833333 0.00333333 0.00166667 0.         0.         0.01
  0.085      0.         0.00166667 0.        ]
 [0.         0.99166667 0.005      0.         0.         0.00333333
  0.         0.         0.         0.        ]
 [0.         0.         0.84166667 0.00166667 0.         0.14166667
  0.01333333 0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.025      0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.95333333]]
[2023-08-27 20:53:11,821 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 20:53:11,822 INFO] 100352 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.8210, train/total_loss: 0.8113, train/util_ratio: 1.0000, train/run_time: 0.1670, eval/loss: 0.3052, eval/top-1-acc: 0.9568, eval/balanced_acc: 0.9598, eval/precision: 0.9549, eval/recall: 0.9598, eval/F1: 0.9557, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 20:54:43,837 INFO] 100608 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0418, train/total_loss: 0.0246, train/util_ratio: 1.0000, train/run_time: 0.1754, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 20:55:33,668 INFO] 100864 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0714, train/total_loss: 0.0593, train/util_ratio: 1.0000, train/run_time: 0.1714, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 20:56:23,597 INFO] 101120 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0080, train/total_loss: -0.0066, train/util_ratio: 1.0000, train/run_time: 0.1781, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 20:57:13,439 INFO] 101376 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0315, train/total_loss: 0.0143, train/util_ratio: 1.0000, train/run_time: 0.1671, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 20:58:46,502 INFO] 101632 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0234, train/total_loss: 0.0112, train/util_ratio: 1.0000, train/run_time: 0.1764, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 20:59:37,219 INFO] 101888 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0898, train/total_loss: 0.0802, train/util_ratio: 1.0000, train/run_time: 0.1720, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 21:00:27,631 INFO] 102144 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3657, train/total_loss: 0.3536, train/util_ratio: 1.0000, train/run_time: 0.1604, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-27 21:01:17,391 INFO] validating...
[2023-08-27 21:01:41,892 INFO] confusion matrix:
[[0.9        0.00333333 0.00166667 0.         0.         0.01
  0.08333333 0.         0.00166667 0.        ]
 [0.         0.98833333 0.005      0.         0.         0.005
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.84166667 0.00166667 0.         0.14333333
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.02666667 0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.95166667]]
[2023-08-27 21:01:43,132 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 21:01:43,135 INFO] 102400 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0202, train/total_loss: 0.0081, train/util_ratio: 1.0000, train/run_time: 0.1677, eval/loss: 0.3053, eval/top-1-acc: 0.9565, eval/balanced_acc: 0.9595, eval/precision: 0.9546, eval/recall: 0.9595, eval/F1: 0.9554, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 21:03:15,002 INFO] 102656 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0187, train/total_loss: 0.0041, train/util_ratio: 0.8750, train/run_time: 0.1668, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 21:04:04,785 INFO] 102912 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0094, train/util_ratio: 1.0000, train/run_time: 0.1659, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 21:04:54,520 INFO] 103168 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0119, train/util_ratio: 0.8750, train/run_time: 0.1693, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 21:05:44,124 INFO] 103424 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3223, train/total_loss: 0.3126, train/util_ratio: 1.0000, train/run_time: 0.1668, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 21:07:16,961 INFO] 103680 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1590, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 21:08:06,379 INFO] 103936 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0386, train/total_loss: 0.0264, train/util_ratio: 1.0000, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 21:08:56,201 INFO] 104192 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0170, train/util_ratio: 1.0000, train/run_time: 0.1616, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 21:09:46,010 INFO] validating...
[2023-08-27 21:10:10,771 INFO] confusion matrix:
[[0.90333333 0.00333333 0.00166667 0.         0.         0.01
  0.08       0.         0.00166667 0.        ]
 [0.         0.98833333 0.005      0.         0.         0.005
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.84166667 0.00166667 0.         0.14333333
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.03       0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.94833333]]
[2023-08-27 21:10:11,630 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 21:10:11,631 INFO] 104448 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.6241, train/total_loss: 0.6095, train/util_ratio: 1.0000, train/run_time: 0.1651, eval/loss: 0.3053, eval/top-1-acc: 0.9567, eval/balanced_acc: 0.9597, eval/precision: 0.9548, eval/recall: 0.9597, eval/F1: 0.9556, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 21:11:43,989 INFO] 104704 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2039, train/total_loss: 0.1918, train/util_ratio: 1.0000, train/run_time: 0.1654, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 21:12:33,721 INFO] 104960 iteration USE_EMA: True, train/sup_loss: 0.0027, train/unsup_loss: 0.0012, train/total_loss: -0.0083, train/util_ratio: 0.8750, train/run_time: 0.1785, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 21:13:23,621 INFO] 105216 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0238, train/total_loss: 0.0117, train/util_ratio: 1.0000, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 21:14:13,485 INFO] 105472 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0028, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1610, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 21:15:46,513 INFO] 105728 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3681, train/total_loss: 0.3510, train/util_ratio: 0.8750, train/run_time: 0.1693, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 21:16:36,013 INFO] 105984 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0227, train/total_loss: 0.0106, train/util_ratio: 0.8750, train/run_time: 0.1621, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 21:17:25,818 INFO] 106240 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0011, train/total_loss: -0.0110, train/util_ratio: 1.0000, train/run_time: 0.1564, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 21:18:15,283 INFO] validating...
[2023-08-27 21:18:39,665 INFO] confusion matrix:
[[0.90166667 0.00333333 0.00166667 0.         0.         0.01
  0.08166667 0.         0.00166667 0.        ]
 [0.         0.98833333 0.005      0.         0.         0.005
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.84166667 0.00166667 0.         0.145
  0.01       0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.026      0.002      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.02       0.
  0.         0.97666667 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.03166667 0.00166667 0.         0.00666667
  0.         0.         0.00333333 0.94666667]]
[2023-08-27 21:18:40,416 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 21:18:40,417 INFO] 106496 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0142, train/total_loss: -0.0004, train/util_ratio: 1.0000, train/run_time: 0.1658, eval/loss: 0.3093, eval/top-1-acc: 0.9557, eval/balanced_acc: 0.9587, eval/precision: 0.9538, eval/recall: 0.9587, eval/F1: 0.9547, lr: 0.0000, train/prefecth_time: 0.0037 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 21:20:12,870 INFO] 106752 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0034, train/total_loss: -0.0087, train/util_ratio: 1.0000, train/run_time: 0.1685, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 21:21:02,817 INFO] 107008 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0464, train/total_loss: 0.0318, train/util_ratio: 1.0000, train/run_time: 0.1582, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-27 21:21:52,479 INFO] 107264 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0004, train/total_loss: -0.0117, train/util_ratio: 1.0000, train/run_time: 0.1679, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 21:22:42,327 INFO] 107520 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0403, train/total_loss: 0.0232, train/util_ratio: 0.8750, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-27 21:24:15,163 INFO] 107776 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0218, train/total_loss: 0.0096, train/util_ratio: 1.0000, train/run_time: 0.1593, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 21:25:04,978 INFO] 108032 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0157, train/total_loss: 0.0060, train/util_ratio: 1.0000, train/run_time: 0.1664, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 21:25:55,010 INFO] 108288 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0133, train/total_loss: -0.0013, train/util_ratio: 0.8750, train/run_time: 0.1683, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 21:26:44,866 INFO] validating...
[2023-08-27 21:27:09,230 INFO] confusion matrix:
[[0.90333333 0.00333333 0.00166667 0.         0.         0.01
  0.08       0.         0.00166667 0.        ]
 [0.         0.98833333 0.005      0.         0.         0.005
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.84       0.00166667 0.         0.14666667
  0.01       0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.026      0.004      0.         0.
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.03166667 0.00166667 0.         0.005
  0.         0.         0.00333333 0.94833333]]
[2023-08-27 21:27:10,046 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 21:27:10,048 INFO] 108544 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0745, train/total_loss: 0.0599, train/util_ratio: 0.7500, train/run_time: 0.1644, eval/loss: 0.3109, eval/top-1-acc: 0.9559, eval/balanced_acc: 0.9589, eval/precision: 0.9540, eval/recall: 0.9589, eval/F1: 0.9548, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 21:28:42,455 INFO] 108800 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0054, train/total_loss: -0.0067, train/util_ratio: 1.0000, train/run_time: 0.1703, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 21:29:32,220 INFO] 109056 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0056, train/total_loss: -0.0115, train/util_ratio: 1.0000, train/run_time: 0.1607, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 21:30:21,867 INFO] 109312 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.5278, train/total_loss: 0.5157, train/util_ratio: 1.0000, train/run_time: 0.1685, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 21:31:11,440 INFO] 109568 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0263, train/total_loss: 0.0142, train/util_ratio: 1.0000, train/run_time: 0.1623, lr: 0.0000, train/prefecth_time: 0.0041 
[2023-08-27 21:32:44,413 INFO] 109824 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: -0.0116, train/util_ratio: 1.0000, train/run_time: 0.1614, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-27 21:33:34,194 INFO] 110080 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0045, train/total_loss: -0.0076, train/util_ratio: 1.0000, train/run_time: 0.1652, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 21:34:23,908 INFO] 110336 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0183, train/total_loss: 0.0061, train/util_ratio: 1.0000, train/run_time: 0.1692, lr: 0.0000, train/prefecth_time: 0.0044 
[2023-08-27 21:35:13,738 INFO] validating...
[2023-08-27 21:35:38,421 INFO] confusion matrix:
[[0.90333333 0.00333333 0.00166667 0.         0.         0.00833333
  0.08166667 0.         0.00166667 0.        ]
 [0.         0.98833333 0.005      0.         0.         0.005
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.84166667 0.00166667 0.         0.14333333
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.004      0.         0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.026      0.004      0.         0.
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03166667 0.         0.         0.005
  0.         0.         0.00333333 0.94833333]]
[2023-08-27 21:35:39,256 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 21:35:39,257 INFO] 110592 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0032, train/total_loss: -0.0089, train/util_ratio: 0.8750, train/run_time: 0.1701, eval/loss: 0.3096, eval/top-1-acc: 0.9561, eval/balanced_acc: 0.9590, eval/precision: 0.9542, eval/recall: 0.9590, eval/F1: 0.9551, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 21:37:11,252 INFO] 110848 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0029, train/total_loss: -0.0092, train/util_ratio: 1.0000, train/run_time: 0.1694, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 21:38:00,950 INFO] 111104 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0102, train/total_loss: -0.0044, train/util_ratio: 0.8750, train/run_time: 0.1670, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 21:38:50,773 INFO] 111360 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1610, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 21:39:40,867 INFO] 111616 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0008, train/total_loss: -0.0138, train/util_ratio: 1.0000, train/run_time: 0.1741, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 21:41:14,862 INFO] 111872 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0194, train/total_loss: 0.0048, train/util_ratio: 1.0000, train/run_time: 0.1743, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 21:42:05,103 INFO] 112128 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0032, train/total_loss: -0.0139, train/util_ratio: 0.8750, train/run_time: 0.1612, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 21:42:55,422 INFO] 112384 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0051, train/total_loss: -0.0070, train/util_ratio: 1.0000, train/run_time: 0.1717, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 21:43:45,121 INFO] validating...
[2023-08-27 21:44:09,326 INFO] confusion matrix:
[[0.90666667 0.00333333 0.00166667 0.         0.         0.00666667
  0.08       0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00666667
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.83833333 0.00166667 0.         0.14666667
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.004      0.         0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03166667 0.         0.         0.00333333
  0.         0.         0.00333333 0.95      ]]
[2023-08-27 21:44:10,190 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 21:44:10,191 INFO] 112640 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0053, train/total_loss: -0.0067, train/util_ratio: 1.0000, train/run_time: 0.1696, eval/loss: 0.3100, eval/top-1-acc: 0.9563, eval/balanced_acc: 0.9592, eval/precision: 0.9543, eval/recall: 0.9592, eval/F1: 0.9552, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 21:45:43,439 INFO] 112896 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1615, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 21:46:32,994 INFO] 113152 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0019, train/total_loss: -0.0077, train/util_ratio: 1.0000, train/run_time: 0.1665, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 21:47:22,543 INFO] 113408 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0031, train/total_loss: -0.0090, train/util_ratio: 1.0000, train/run_time: 0.1665, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 21:48:12,549 INFO] 113664 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0241, train/total_loss: 0.0120, train/util_ratio: 1.0000, train/run_time: 0.1598, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 21:49:45,416 INFO] 113920 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0050, train/total_loss: -0.0097, train/util_ratio: 1.0000, train/run_time: 0.1724, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-27 21:50:35,217 INFO] 114176 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0071, train/total_loss: -0.0075, train/util_ratio: 1.0000, train/run_time: 0.1673, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 21:51:24,816 INFO] 114432 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2890, train/total_loss: 0.2793, train/util_ratio: 1.0000, train/run_time: 0.1762, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 21:52:14,209 INFO] validating...
[2023-08-27 21:52:38,456 INFO] confusion matrix:
[[0.90833333 0.00333333 0.00166667 0.         0.         0.00666667
  0.07833333 0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.00833333
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.83666667 0.00166667 0.         0.14833333
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.998      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.968      0.         0.002      0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00601202 0.         0.         0.00400802 0.         0.
  0.         0.         0.98797595 0.00200401]
 [0.00833333 0.00166667 0.03166667 0.00166667 0.         0.00333333
  0.         0.         0.00333333 0.95      ]]
[2023-08-27 21:52:39,336 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 21:52:39,337 INFO] 114688 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3307, train/total_loss: 0.3161, train/util_ratio: 1.0000, train/run_time: 0.1595, eval/loss: 0.3114, eval/top-1-acc: 0.9559, eval/balanced_acc: 0.9589, eval/precision: 0.9539, eval/recall: 0.9589, eval/F1: 0.9548, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 21:54:11,878 INFO] 114944 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4866, train/total_loss: 0.4744, train/util_ratio: 1.0000, train/run_time: 0.1606, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 21:55:01,277 INFO] 115200 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0038, train/total_loss: -0.0059, train/util_ratio: 1.0000, train/run_time: 0.1676, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 21:55:50,772 INFO] 115456 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0943, train/total_loss: 0.0797, train/util_ratio: 1.0000, train/run_time: 0.1607, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 21:56:40,203 INFO] 115712 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: -0.0141, train/util_ratio: 1.0000, train/run_time: 0.1601, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 21:58:13,042 INFO] 115968 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4079, train/total_loss: 0.3933, train/util_ratio: 1.0000, train/run_time: 0.1598, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 21:59:02,472 INFO] 116224 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0252, train/total_loss: 0.0106, train/util_ratio: 0.8750, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 21:59:51,958 INFO] 116480 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0023, train/total_loss: -0.0074, train/util_ratio: 1.0000, train/run_time: 0.1699, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 22:00:41,625 INFO] validating...
[2023-08-27 22:01:06,834 INFO] confusion matrix:
[[0.90833333 0.00333333 0.00166667 0.         0.         0.00666667
  0.07833333 0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.00833333
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.84       0.00166667 0.         0.145
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.998      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.026      0.004      0.         0.
  0.966      0.         0.002      0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00601202 0.         0.         0.00400802 0.         0.
  0.         0.         0.98797595 0.00200401]
 [0.00833333 0.00166667 0.03166667 0.00166667 0.         0.00333333
  0.         0.         0.005      0.94833333]]
[2023-08-27 22:01:07,759 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 22:01:07,761 INFO] 116736 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2978, train/total_loss: 0.2881, train/util_ratio: 1.0000, train/run_time: 0.1677, eval/loss: 0.3117, eval/top-1-acc: 0.9559, eval/balanced_acc: 0.9588, eval/precision: 0.9539, eval/recall: 0.9588, eval/F1: 0.9548, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 22:02:39,855 INFO] 116992 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0774, train/total_loss: 0.0678, train/util_ratio: 1.0000, train/run_time: 0.1616, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 22:03:29,610 INFO] 117248 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1361, train/total_loss: 0.1215, train/util_ratio: 0.8750, train/run_time: 0.1724, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 22:04:19,630 INFO] 117504 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0020, train/total_loss: -0.0101, train/util_ratio: 0.8750, train/run_time: 0.1649, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 22:05:08,959 INFO] 117760 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0038, train/total_loss: -0.0083, train/util_ratio: 1.0000, train/run_time: 0.1677, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 22:06:41,534 INFO] 118016 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2992, train/total_loss: 0.2846, train/util_ratio: 1.0000, train/run_time: 0.1651, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 22:07:30,784 INFO] 118272 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0565, train/total_loss: 0.0469, train/util_ratio: 1.0000, train/run_time: 0.1694, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 22:08:20,599 INFO] 118528 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0228, train/total_loss: 0.0131, train/util_ratio: 1.0000, train/run_time: 0.1732, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 22:09:09,961 INFO] validating...
[2023-08-27 22:09:34,472 INFO] confusion matrix:
[[0.90666667 0.00333333 0.00166667 0.         0.         0.00666667
  0.08       0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00666667
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.84       0.00166667 0.         0.145
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.998      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.026      0.002      0.         0.
  0.968      0.         0.002      0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00601202 0.         0.         0.00400802 0.         0.
  0.         0.         0.98797595 0.00200401]
 [0.00833333 0.00166667 0.03166667 0.00166667 0.         0.00333333
  0.         0.         0.005      0.94833333]]
[2023-08-27 22:09:35,333 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 22:09:35,334 INFO] 118784 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1245, train/total_loss: 0.1098, train/util_ratio: 1.0000, train/run_time: 0.1640, eval/loss: 0.3099, eval/top-1-acc: 0.9563, eval/balanced_acc: 0.9592, eval/precision: 0.9543, eval/recall: 0.9592, eval/F1: 0.9552, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 22:11:07,839 INFO] 119040 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0008, train/total_loss: -0.0089, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 22:11:57,764 INFO] 119296 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1063, train/total_loss: 0.0942, train/util_ratio: 1.0000, train/run_time: 0.1684, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 22:12:47,337 INFO] 119552 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0017, train/total_loss: -0.0080, train/util_ratio: 1.0000, train/run_time: 0.1603, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 22:13:36,628 INFO] 119808 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0056, train/total_loss: -0.0090, train/util_ratio: 1.0000, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 22:15:09,570 INFO] 120064 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0121, train/util_ratio: 1.0000, train/run_time: 0.1606, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 22:15:59,122 INFO] 120320 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1705, train/total_loss: 0.1559, train/util_ratio: 1.0000, train/run_time: 0.1652, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 22:16:48,810 INFO] 120576 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1618, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 22:17:38,493 INFO] validating...
[2023-08-27 22:18:03,140 INFO] confusion matrix:
[[0.90833333 0.00333333 0.00166667 0.         0.         0.00666667
  0.07833333 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00666667
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.84       0.00166667 0.         0.145
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.998      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.026      0.002      0.         0.
  0.968      0.         0.002      0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03166667 0.00166667 0.         0.00333333
  0.         0.         0.005      0.94666667]]
[2023-08-27 22:18:04,177 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 22:18:04,179 INFO] 120832 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0160, train/total_loss: 0.0014, train/util_ratio: 1.0000, train/run_time: 0.1640, eval/loss: 0.3105, eval/top-1-acc: 0.9565, eval/balanced_acc: 0.9594, eval/precision: 0.9545, eval/recall: 0.9594, eval/F1: 0.9554, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 22:19:36,331 INFO] 121088 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3048, train/total_loss: 0.2927, train/util_ratio: 1.0000, train/run_time: 0.1606, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 22:20:25,594 INFO] 121344 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1936, train/total_loss: 0.1814, train/util_ratio: 1.0000, train/run_time: 0.1698, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 22:21:14,973 INFO] 121600 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2474, train/total_loss: 0.2377, train/util_ratio: 1.0000, train/run_time: 0.1788, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 22:22:04,408 INFO] 121856 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0048, train/total_loss: -0.0073, train/util_ratio: 1.0000, train/run_time: 0.1588, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 22:23:37,748 INFO] 122112 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0067, train/total_loss: -0.0054, train/util_ratio: 1.0000, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 22:24:27,559 INFO] 122368 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0121, train/util_ratio: 1.0000, train/run_time: 0.1652, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 22:25:17,053 INFO] 122624 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2624, train/total_loss: 0.2502, train/util_ratio: 1.0000, train/run_time: 0.1594, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-27 22:26:06,610 INFO] validating...
[2023-08-27 22:26:31,006 INFO] confusion matrix:
[[0.91       0.00333333 0.00166667 0.         0.         0.00666667
  0.07666667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00666667
  0.         0.         0.00166667 0.        ]
 [0.         0.         0.83833333 0.00166667 0.         0.14666667
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.026      0.002      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01166667 0.00166667 0.03166667 0.         0.         0.005
  0.         0.         0.005      0.945     ]]
[2023-08-27 22:26:31,983 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 22:26:31,984 INFO] 122880 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0768, train/total_loss: 0.0647, train/util_ratio: 1.0000, train/run_time: 0.1575, eval/loss: 0.3101, eval/top-1-acc: 0.9563, eval/balanced_acc: 0.9592, eval/precision: 0.9543, eval/recall: 0.9592, eval/F1: 0.9552, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 22:28:04,257 INFO] 123136 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0011, train/total_loss: -0.0135, train/util_ratio: 1.0000, train/run_time: 0.1802, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 22:28:54,124 INFO] 123392 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0104, train/total_loss: -0.0018, train/util_ratio: 1.0000, train/run_time: 0.1614, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 22:29:43,842 INFO] 123648 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0078, train/total_loss: -0.0043, train/util_ratio: 1.0000, train/run_time: 0.1616, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-27 22:30:33,280 INFO] 123904 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0111, train/total_loss: -0.0010, train/util_ratio: 1.0000, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 22:32:06,300 INFO] 124160 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0146, train/util_ratio: 1.0000, train/run_time: 0.1609, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 22:32:56,171 INFO] 124416 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0080, train/total_loss: -0.0067, train/util_ratio: 0.8750, train/run_time: 0.1917, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 22:33:46,054 INFO] 124672 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0883, train/total_loss: 0.0737, train/util_ratio: 1.0000, train/run_time: 0.1602, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 22:34:35,598 INFO] validating...
[2023-08-27 22:34:59,755 INFO] confusion matrix:
[[0.91166667 0.00333333 0.00166667 0.         0.         0.00666667
  0.075      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.83833333 0.00166667 0.         0.14833333
  0.01       0.         0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.026      0.004      0.         0.
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01166667 0.00166667 0.03166667 0.         0.         0.005
  0.         0.         0.005      0.945     ]]
[2023-08-27 22:35:00,610 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 22:35:00,612 INFO] 124928 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0008, train/total_loss: -0.0113, train/util_ratio: 1.0000, train/run_time: 0.1683, eval/loss: 0.3121, eval/top-1-acc: 0.9563, eval/balanced_acc: 0.9592, eval/precision: 0.9543, eval/recall: 0.9592, eval/F1: 0.9552, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 22:36:33,114 INFO] 125184 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0071, train/total_loss: -0.0075, train/util_ratio: 1.0000, train/run_time: 0.1624, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 22:37:22,830 INFO] 125440 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0045, train/total_loss: -0.0073, train/util_ratio: 1.0000, train/run_time: 0.1675, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 22:38:12,579 INFO] 125696 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: -0.0067, train/util_ratio: 1.0000, train/run_time: 0.1681, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 22:39:02,132 INFO] 125952 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0079, train/total_loss: -0.0018, train/util_ratio: 1.0000, train/run_time: 0.1676, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 22:40:35,234 INFO] 126208 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0028, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1724, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 22:41:24,795 INFO] 126464 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0145, train/util_ratio: 1.0000, train/run_time: 0.1656, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 22:42:14,352 INFO] 126720 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0338, train/total_loss: 0.0216, train/util_ratio: 1.0000, train/run_time: 0.1658, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 22:43:04,031 INFO] validating...
[2023-08-27 22:43:28,470 INFO] confusion matrix:
[[0.91166667 0.00333333 0.00166667 0.         0.         0.00666667
  0.075      0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.00666667
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.83833333 0.00166667 0.         0.14666667
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.026      0.004      0.         0.
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01166667 0.00166667 0.03166667 0.         0.         0.00333333
  0.         0.         0.005      0.94666667]]
[2023-08-27 22:43:29,486 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 22:43:29,488 INFO] 126976 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0101, train/total_loss: 0.0005, train/util_ratio: 1.0000, train/run_time: 0.1596, eval/loss: 0.3126, eval/top-1-acc: 0.9563, eval/balanced_acc: 0.9592, eval/precision: 0.9543, eval/recall: 0.9592, eval/F1: 0.9552, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 22:45:01,743 INFO] 127232 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0145, train/util_ratio: 1.0000, train/run_time: 0.1690, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 22:45:51,061 INFO] 127488 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0046, train/total_loss: -0.0075, train/util_ratio: 1.0000, train/run_time: 0.1871, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 22:46:40,889 INFO] 127744 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0146, train/util_ratio: 1.0000, train/run_time: 0.1721, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 22:47:30,769 INFO] 128000 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0870, train/total_loss: 0.0774, train/util_ratio: 1.0000, train/run_time: 0.1628, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 22:49:04,313 INFO] 128256 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1367, train/total_loss: 0.1270, train/util_ratio: 1.0000, train/run_time: 0.1580, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 22:49:54,221 INFO] 128512 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0370, train/total_loss: 0.0273, train/util_ratio: 1.0000, train/run_time: 0.1714, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 22:50:44,041 INFO] 128768 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0012, train/total_loss: -0.0109, train/util_ratio: 1.0000, train/run_time: 0.1622, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 22:51:33,422 INFO] validating...
[2023-08-27 22:51:58,009 INFO] confusion matrix:
[[0.91166667 0.00333333 0.00166667 0.         0.         0.00666667
  0.075      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.83666667 0.00166667 0.         0.14833333
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.026      0.004      0.         0.
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01166667 0.00166667 0.03166667 0.         0.         0.00333333
  0.         0.         0.005      0.94666667]]
[2023-08-27 22:51:59,020 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 22:51:59,022 INFO] 129024 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0024, train/total_loss: -0.0073, train/util_ratio: 1.0000, train/run_time: 0.1600, eval/loss: 0.3149, eval/top-1-acc: 0.9565, eval/balanced_acc: 0.9594, eval/precision: 0.9545, eval/recall: 0.9594, eval/F1: 0.9554, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 22:53:31,179 INFO] 129280 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0271, train/total_loss: 0.0125, train/util_ratio: 1.0000, train/run_time: 0.1651, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-27 22:54:20,531 INFO] 129536 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0026, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1590, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 22:55:10,028 INFO] 129792 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0144, train/util_ratio: 1.0000, train/run_time: 0.1570, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 22:55:59,876 INFO] 130048 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.9266, train/total_loss: 0.9120, train/util_ratio: 1.0000, train/run_time: 0.1589, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 22:57:33,066 INFO] 130304 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 22:58:23,163 INFO] 130560 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: -0.0116, train/util_ratio: 1.0000, train/run_time: 0.1674, lr: 0.0000, train/prefecth_time: 0.0046 
[2023-08-27 22:59:13,251 INFO] 130816 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0070, train/total_loss: -0.0077, train/util_ratio: 1.0000, train/run_time: 0.1638, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 23:00:02,973 INFO] validating...
[2023-08-27 23:00:26,911 INFO] confusion matrix:
[[0.91166667 0.00333333 0.00166667 0.         0.         0.00666667
  0.075      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.83666667 0.00166667 0.         0.14833333
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03166667 0.         0.         0.00333333
  0.         0.         0.005      0.94833333]]
[2023-08-27 23:00:27,695 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 23:00:27,696 INFO] 131072 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0255, train/total_loss: 0.0133, train/util_ratio: 1.0000, train/run_time: 0.1608, eval/loss: 0.3154, eval/top-1-acc: 0.9568, eval/balanced_acc: 0.9598, eval/precision: 0.9548, eval/recall: 0.9598, eval/F1: 0.9558, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 23:02:00,424 INFO] 131328 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0011, train/total_loss: -0.0085, train/util_ratio: 1.0000, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 23:02:50,366 INFO] 131584 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0016, train/total_loss: -0.0080, train/util_ratio: 1.0000, train/run_time: 0.1770, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 23:03:40,332 INFO] 131840 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0024, train/total_loss: -0.0098, train/util_ratio: 1.0000, train/run_time: 0.1694, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 23:04:29,838 INFO] 132096 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.9068, train/total_loss: 0.8922, train/util_ratio: 1.0000, train/run_time: 0.1805, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 23:06:03,342 INFO] 132352 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0044, train/total_loss: -0.0102, train/util_ratio: 1.0000, train/run_time: 0.1733, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 23:06:52,929 INFO] 132608 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0144, train/util_ratio: 0.8750, train/run_time: 0.1855, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 23:07:42,894 INFO] 132864 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0179, train/total_loss: 0.0008, train/util_ratio: 1.0000, train/run_time: 0.1634, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 23:08:32,744 INFO] validating...
[2023-08-27 23:08:57,373 INFO] confusion matrix:
[[0.91166667 0.00333333 0.00166667 0.         0.         0.00666667
  0.075      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.835      0.00166667 0.         0.15
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.005      0.         0.9825
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03166667 0.         0.         0.005
  0.         0.         0.005      0.94666667]]
[2023-08-27 23:08:58,392 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 23:08:58,396 INFO] 133120 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: -0.0140, train/util_ratio: 1.0000, train/run_time: 0.1654, eval/loss: 0.3175, eval/top-1-acc: 0.9565, eval/balanced_acc: 0.9594, eval/precision: 0.9545, eval/recall: 0.9594, eval/F1: 0.9554, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 23:10:30,056 INFO] 133376 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0014, train/total_loss: -0.0157, train/util_ratio: 1.0000, train/run_time: 0.1712, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 23:11:19,651 INFO] 133632 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0009, train/total_loss: -0.0112, train/util_ratio: 1.0000, train/run_time: 0.1600, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-27 23:12:09,298 INFO] 133888 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0017, train/total_loss: -0.0154, train/util_ratio: 1.0000, train/run_time: 0.1624, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 23:12:58,976 INFO] 134144 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0388, train/total_loss: 0.0267, train/util_ratio: 1.0000, train/run_time: 0.1654, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-27 23:14:32,127 INFO] 134400 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0056, train/total_loss: -0.0065, train/util_ratio: 1.0000, train/run_time: 0.1630, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-27 23:15:21,522 INFO] 134656 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0146, train/util_ratio: 0.8750, train/run_time: 0.1656, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-27 23:16:10,856 INFO] 134912 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0761, train/total_loss: 0.0640, train/util_ratio: 1.0000, train/run_time: 0.1602, lr: 0.0000, train/prefecth_time: 0.0044 
[2023-08-27 23:17:00,202 INFO] validating...
[2023-08-27 23:17:25,049 INFO] confusion matrix:
[[0.91166667 0.00333333 0.00166667 0.         0.         0.00666667
  0.075      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.835      0.00166667 0.         0.15
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03166667 0.         0.         0.005
  0.         0.         0.005      0.94666667]]
[2023-08-27 23:17:26,090 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 23:17:26,092 INFO] 135168 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2695, train/total_loss: 0.2573, train/util_ratio: 1.0000, train/run_time: 0.1635, eval/loss: 0.3194, eval/top-1-acc: 0.9567, eval/balanced_acc: 0.9597, eval/precision: 0.9547, eval/recall: 0.9597, eval/F1: 0.9556, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 23:18:58,385 INFO] 135424 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0504, train/total_loss: 0.0358, train/util_ratio: 1.0000, train/run_time: 0.1765, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 23:19:47,876 INFO] 135680 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0283, train/total_loss: 0.0187, train/util_ratio: 1.0000, train/run_time: 0.1774, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 23:20:37,347 INFO] 135936 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0668, train/total_loss: 0.0572, train/util_ratio: 1.0000, train/run_time: 0.1793, lr: 0.0000, train/prefecth_time: 0.0041 
[2023-08-27 23:21:27,205 INFO] 136192 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0009, train/total_loss: -0.0137, train/util_ratio: 0.8750, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-27 23:22:59,655 INFO] 136448 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0319, train/total_loss: 0.0197, train/util_ratio: 1.0000, train/run_time: 0.1603, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 23:23:49,119 INFO] 136704 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0012, train/total_loss: -0.0085, train/util_ratio: 0.8750, train/run_time: 0.1629, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 23:24:38,925 INFO] 136960 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2943, train/total_loss: 0.2822, train/util_ratio: 1.0000, train/run_time: 0.1684, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 23:25:28,699 INFO] validating...
[2023-08-27 23:25:53,105 INFO] confusion matrix:
[[0.91166667 0.00333333 0.00166667 0.         0.         0.00666667
  0.075      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.83666667 0.00166667 0.         0.14833333
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03166667 0.         0.         0.005
  0.         0.         0.005      0.94666667]]
[2023-08-27 23:25:54,091 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 23:25:54,093 INFO] 137216 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0131, train/total_loss: -0.0040, train/util_ratio: 1.0000, train/run_time: 0.1576, eval/loss: 0.3218, eval/top-1-acc: 0.9568, eval/balanced_acc: 0.9599, eval/precision: 0.9549, eval/recall: 0.9599, eval/F1: 0.9558, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 23:27:26,619 INFO] 137472 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0905, train/total_loss: 0.0783, train/util_ratio: 1.0000, train/run_time: 0.1600, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 23:28:16,257 INFO] 137728 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0463, train/total_loss: 0.0342, train/util_ratio: 1.0000, train/run_time: 0.1709, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 23:29:06,309 INFO] 137984 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1682, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-27 23:29:55,920 INFO] 138240 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0014, train/total_loss: -0.0082, train/util_ratio: 1.0000, train/run_time: 0.1680, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-27 23:31:28,930 INFO] 138496 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1063, train/total_loss: 0.0942, train/util_ratio: 1.0000, train/run_time: 0.1606, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-27 23:32:18,569 INFO] 138752 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.6703, train/total_loss: 0.6606, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 23:33:08,464 INFO] 139008 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0208, train/total_loss: 0.0111, train/util_ratio: 1.0000, train/run_time: 0.1618, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 23:33:57,903 INFO] validating...
[2023-08-27 23:34:22,534 INFO] confusion matrix:
[[0.91166667 0.00333333 0.00166667 0.         0.         0.00666667
  0.075      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.83666667 0.00166667 0.         0.14833333
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.022      0.004      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.03       0.         0.         0.00666667
  0.         0.         0.005      0.94833333]]
[2023-08-27 23:34:23,463 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 23:34:23,464 INFO] 139264 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0016, train/total_loss: -0.0130, train/util_ratio: 1.0000, train/run_time: 0.1602, eval/loss: 0.3235, eval/top-1-acc: 0.9572, eval/balanced_acc: 0.9602, eval/precision: 0.9553, eval/recall: 0.9602, eval/F1: 0.9561, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 23:35:55,134 INFO] 139520 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1818, train/total_loss: 0.1696, train/util_ratio: 1.0000, train/run_time: 0.1650, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 23:36:44,527 INFO] 139776 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: -0.0165, train/util_ratio: 1.0000, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 23:37:33,985 INFO] 140032 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0217, train/total_loss: 0.0046, train/util_ratio: 1.0000, train/run_time: 0.1604, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 23:38:23,534 INFO] 140288 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0014, train/total_loss: -0.0107, train/util_ratio: 1.0000, train/run_time: 0.1608, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 23:39:56,591 INFO] 140544 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0135, train/total_loss: -0.0011, train/util_ratio: 1.0000, train/run_time: 0.1727, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-27 23:40:46,071 INFO] 140800 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-27 23:41:35,546 INFO] 141056 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1622, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 23:42:24,871 INFO] validating...
[2023-08-27 23:42:49,274 INFO] confusion matrix:
[[0.91333333 0.00333333 0.00166667 0.         0.         0.00666667
  0.07333333 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.835      0.00166667 0.         0.15
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.022      0.004      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.02666667 0.         0.         0.00666667
  0.         0.         0.005      0.95166667]]
[2023-08-27 23:42:50,022 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 23:42:50,023 INFO] 141312 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0004, train/total_loss: -0.0117, train/util_ratio: 1.0000, train/run_time: 0.1560, eval/loss: 0.3258, eval/top-1-acc: 0.9574, eval/balanced_acc: 0.9604, eval/precision: 0.9554, eval/recall: 0.9604, eval/F1: 0.9563, lr: 0.0000, train/prefecth_time: 0.0039 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 23:44:22,505 INFO] 141568 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1391, train/total_loss: 0.1270, train/util_ratio: 0.8750, train/run_time: 0.1603, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-27 23:45:12,155 INFO] 141824 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0055, train/total_loss: -0.0041, train/util_ratio: 1.0000, train/run_time: 0.1622, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-27 23:46:02,088 INFO] 142080 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0479, train/total_loss: 0.0333, train/util_ratio: 1.0000, train/run_time: 0.2020, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 23:46:51,708 INFO] 142336 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0075, train/total_loss: -0.0046, train/util_ratio: 1.0000, train/run_time: 0.1601, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 23:48:25,179 INFO] 142592 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1595, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 23:49:15,061 INFO] 142848 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0075, train/total_loss: -0.0046, train/util_ratio: 1.0000, train/run_time: 0.1718, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 23:50:04,859 INFO] 143104 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0709, train/total_loss: 0.0587, train/util_ratio: 1.0000, train/run_time: 0.1611, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 23:50:55,002 INFO] validating...
[2023-08-27 23:51:19,609 INFO] confusion matrix:
[[0.91166667 0.00333333 0.00166667 0.         0.         0.00833333
  0.07333333 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.835      0.00166667 0.         0.15
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.02666667 0.         0.         0.00666667
  0.         0.         0.005      0.95166667]]
[2023-08-27 23:51:20,434 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 23:51:20,435 INFO] 143360 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0022, train/total_loss: -0.0124, train/util_ratio: 1.0000, train/run_time: 0.1687, eval/loss: 0.3287, eval/top-1-acc: 0.9568, eval/balanced_acc: 0.9598, eval/precision: 0.9549, eval/recall: 0.9598, eval/F1: 0.9557, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-27 23:52:53,056 INFO] 143616 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0014, train/total_loss: -0.0082, train/util_ratio: 1.0000, train/run_time: 0.1733, lr: 0.0000, train/prefecth_time: 0.0049 
[2023-08-27 23:53:42,912 INFO] 143872 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2214, train/total_loss: 0.2068, train/util_ratio: 1.0000, train/run_time: 0.1611, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-27 23:54:32,603 INFO] 144128 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0290, train/total_loss: 0.0144, train/util_ratio: 1.0000, train/run_time: 0.1681, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-27 23:55:22,256 INFO] 144384 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0079, train/total_loss: -0.0042, train/util_ratio: 1.0000, train/run_time: 0.1601, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-27 23:56:55,722 INFO] 144640 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0258, train/total_loss: 0.0136, train/util_ratio: 1.0000, train/run_time: 0.1624, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-27 23:57:45,440 INFO] 144896 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0460, train/total_loss: 0.0339, train/util_ratio: 1.0000, train/run_time: 0.1676, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-27 23:58:35,248 INFO] 145152 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1702, train/total_loss: 0.1556, train/util_ratio: 1.0000, train/run_time: 0.1657, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-27 23:59:24,849 INFO] validating...
[2023-08-27 23:59:49,312 INFO] confusion matrix:
[[0.91333333 0.00333333 0.00166667 0.         0.         0.00666667
  0.07333333 0.         0.00166667 0.        ]
 [0.         0.985      0.00666667 0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.835      0.00166667 0.         0.15
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.005
  0.         0.         0.005      0.94833333]]
[2023-08-27 23:59:50,264 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-27 23:59:50,266 INFO] 145408 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0058, train/total_loss: -0.0088, train/util_ratio: 1.0000, train/run_time: 0.1600, eval/loss: 0.3312, eval/top-1-acc: 0.9567, eval/balanced_acc: 0.9597, eval/precision: 0.9547, eval/recall: 0.9597, eval/F1: 0.9556, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 00:01:22,427 INFO] 145664 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4496, train/total_loss: 0.4375, train/util_ratio: 1.0000, train/run_time: 0.1620, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 00:02:12,343 INFO] 145920 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0130, train/total_loss: 0.0008, train/util_ratio: 1.0000, train/run_time: 0.1567, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-28 00:03:02,025 INFO] 146176 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0007, train/total_loss: -0.0139, train/util_ratio: 1.0000, train/run_time: 0.1619, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 00:03:51,782 INFO] 146432 iteration USE_EMA: True, train/sup_loss: 0.0004, train/unsup_loss: 0.0116, train/total_loss: -0.0001, train/util_ratio: 1.0000, train/run_time: 0.1663, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-28 00:05:25,438 INFO] 146688 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0191, train/total_loss: 0.0070, train/util_ratio: 1.0000, train/run_time: 0.1662, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 00:06:15,152 INFO] 146944 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0094, train/util_ratio: 1.0000, train/run_time: 0.1708, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 00:07:04,296 INFO] 147200 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0175, train/total_loss: 0.0003, train/util_ratio: 1.0000, train/run_time: 0.1692, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 00:07:54,149 INFO] validating...
[2023-08-28 00:08:18,139 INFO] confusion matrix:
[[0.91333333 0.00333333 0.00166667 0.         0.         0.00666667
  0.07333333 0.         0.00166667 0.        ]
 [0.         0.985      0.00666667 0.         0.         0.005
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.83333333 0.00166667 0.         0.15166667
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 00:08:18,949 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 00:08:18,950 INFO] 147456 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0070, train/total_loss: -0.0076, train/util_ratio: 1.0000, train/run_time: 0.1657, eval/loss: 0.3327, eval/top-1-acc: 0.9565, eval/balanced_acc: 0.9595, eval/precision: 0.9545, eval/recall: 0.9595, eval/F1: 0.9554, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 00:09:51,724 INFO] 147712 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0096, train/util_ratio: 1.0000, train/run_time: 0.1661, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-28 00:10:41,510 INFO] 147968 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1021, train/total_loss: 0.0925, train/util_ratio: 1.0000, train/run_time: 0.1782, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 00:11:31,415 INFO] 148224 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0022, train/total_loss: -0.0124, train/util_ratio: 1.0000, train/run_time: 0.1674, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-28 00:12:21,028 INFO] 148480 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0149, train/total_loss: 0.0028, train/util_ratio: 1.0000, train/run_time: 0.1684, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 00:13:54,146 INFO] 148736 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0230, train/total_loss: 0.0109, train/util_ratio: 1.0000, train/run_time: 0.1763, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 00:14:43,751 INFO] 148992 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: -0.0140, train/util_ratio: 1.0000, train/run_time: 0.1636, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-28 00:15:33,784 INFO] 149248 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0012, train/total_loss: -0.0109, train/util_ratio: 1.0000, train/run_time: 0.1609, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 00:16:23,298 INFO] validating...
[2023-08-28 00:16:47,954 INFO] confusion matrix:
[[0.915      0.00333333 0.00166667 0.         0.         0.00666667
  0.07166667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.00666667 0.         0.         0.00333333
  0.         0.         0.00333333 0.        ]
 [0.         0.         0.83666667 0.00166667 0.         0.14833333
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 00:16:48,909 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 00:16:48,911 INFO] 149504 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1494, train/total_loss: 0.1348, train/util_ratio: 1.0000, train/run_time: 0.1611, eval/loss: 0.3329, eval/top-1-acc: 0.9576, eval/balanced_acc: 0.9605, eval/precision: 0.9556, eval/recall: 0.9605, eval/F1: 0.9565, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 00:18:20,981 INFO] 149760 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0132, train/total_loss: -0.0014, train/util_ratio: 1.0000, train/run_time: 0.1590, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-28 00:19:10,839 INFO] 150016 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2832, train/total_loss: 0.2710, train/util_ratio: 1.0000, train/run_time: 0.1669, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 00:20:00,856 INFO] 150272 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0030, train/total_loss: -0.0141, train/util_ratio: 1.0000, train/run_time: 0.1614, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 00:20:50,860 INFO] 150528 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0024, train/total_loss: -0.0097, train/util_ratio: 1.0000, train/run_time: 0.1652, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 00:22:24,076 INFO] 150784 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2155, train/total_loss: 0.2008, train/util_ratio: 1.0000, train/run_time: 0.1710, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 00:23:13,807 INFO] 151040 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0119, train/util_ratio: 1.0000, train/run_time: 0.1764, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 00:24:03,707 INFO] 151296 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0029, train/total_loss: -0.0093, train/util_ratio: 0.8750, train/run_time: 0.1732, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 00:24:53,077 INFO] validating...
[2023-08-28 00:25:17,817 INFO] confusion matrix:
[[0.915      0.00333333 0.00166667 0.         0.         0.00666667
  0.07166667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.         0.83833333 0.00166667 0.         0.14666667
  0.01       0.00166667 0.00166667 0.        ]
 [0.002      0.         0.         0.992      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 00:25:18,729 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 00:25:18,730 INFO] 151552 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0522, train/total_loss: 0.0376, train/util_ratio: 1.0000, train/run_time: 0.1616, eval/loss: 0.3339, eval/top-1-acc: 0.9576, eval/balanced_acc: 0.9605, eval/precision: 0.9556, eval/recall: 0.9605, eval/F1: 0.9565, lr: 0.0000, train/prefecth_time: 0.0031 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 00:26:50,730 INFO] 151808 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0017, train/total_loss: -0.0129, train/util_ratio: 1.0000, train/run_time: 0.1621, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-28 00:27:40,392 INFO] 152064 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0121, train/util_ratio: 1.0000, train/run_time: 0.1721, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-28 00:28:30,232 INFO] 152320 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0019, train/total_loss: -0.0077, train/util_ratio: 1.0000, train/run_time: 0.1701, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 00:29:19,506 INFO] 152576 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0110, train/total_loss: -0.0036, train/util_ratio: 1.0000, train/run_time: 0.1601, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 00:30:52,553 INFO] 152832 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0119, train/util_ratio: 1.0000, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 00:31:41,956 INFO] 153088 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: -0.0140, train/util_ratio: 1.0000, train/run_time: 0.1711, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 00:32:31,693 INFO] 153344 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0645, train/total_loss: 0.0499, train/util_ratio: 1.0000, train/run_time: 0.1879, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 00:33:21,733 INFO] validating...
[2023-08-28 00:33:46,394 INFO] confusion matrix:
[[0.915      0.00333333 0.00166667 0.         0.         0.00666667
  0.07166667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.         0.84       0.00166667 0.         0.145
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.02       0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 00:33:47,396 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 00:33:47,397 INFO] 153600 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0094, train/total_loss: -0.0027, train/util_ratio: 1.0000, train/run_time: 0.1604, eval/loss: 0.3351, eval/top-1-acc: 0.9580, eval/balanced_acc: 0.9609, eval/precision: 0.9559, eval/recall: 0.9609, eval/F1: 0.9569, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 00:35:19,153 INFO] 153856 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0242, train/total_loss: 0.0123, train/util_ratio: 1.0000, train/run_time: 0.1661, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 00:36:08,666 INFO] 154112 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0019, train/total_loss: -0.0102, train/util_ratio: 1.0000, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 00:36:58,534 INFO] 154368 iteration USE_EMA: True, train/sup_loss: 0.0010, train/unsup_loss: 0.0241, train/total_loss: 0.0129, train/util_ratio: 0.8750, train/run_time: 0.1750, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-28 00:37:48,069 INFO] 154624 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0002, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1718, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 00:39:20,946 INFO] 154880 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0008, train/total_loss: -0.0113, train/util_ratio: 1.0000, train/run_time: 0.1604, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 00:40:10,559 INFO] 155136 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0283, train/total_loss: 0.0186, train/util_ratio: 1.0000, train/run_time: 0.1618, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 00:41:00,378 INFO] 155392 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1832, train/total_loss: 0.1686, train/util_ratio: 1.0000, train/run_time: 0.1616, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 00:41:49,733 INFO] validating...
[2023-08-28 00:42:14,577 INFO] confusion matrix:
[[0.915      0.00333333 0.00166667 0.         0.         0.00666667
  0.07166667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.         0.84       0.00166667 0.         0.145
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01833333 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 00:42:15,503 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 00:42:15,504 INFO] 155648 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2109, train/total_loss: 0.2013, train/util_ratio: 1.0000, train/run_time: 0.1668, eval/loss: 0.3364, eval/top-1-acc: 0.9583, eval/balanced_acc: 0.9612, eval/precision: 0.9563, eval/recall: 0.9612, eval/F1: 0.9573, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 00:43:47,740 INFO] 155904 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0074, train/total_loss: -0.0072, train/util_ratio: 1.0000, train/run_time: 0.1715, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 00:44:37,209 INFO] 156160 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0015, train/total_loss: -0.0131, train/util_ratio: 1.0000, train/run_time: 0.1637, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-28 00:45:26,791 INFO] 156416 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0835, train/total_loss: 0.0689, train/util_ratio: 1.0000, train/run_time: 0.1746, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 00:46:16,350 INFO] 156672 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0096, train/util_ratio: 1.0000, train/run_time: 0.1607, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 00:47:49,566 INFO] 156928 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1027, train/total_loss: 0.0906, train/util_ratio: 1.0000, train/run_time: 0.1572, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-28 00:48:39,138 INFO] 157184 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0143, train/util_ratio: 1.0000, train/run_time: 0.1682, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 00:49:28,966 INFO] 157440 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0173, train/total_loss: 0.0052, train/util_ratio: 1.0000, train/run_time: 0.1645, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 00:50:18,675 INFO] validating...
[2023-08-28 00:50:43,413 INFO] confusion matrix:
[[0.915      0.00333333 0.00166667 0.         0.         0.00666667
  0.07166667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.         0.83666667 0.00166667 0.         0.14833333
  0.01       0.00166667 0.00166667 0.        ]
 [0.002      0.         0.         0.992      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.         0.01666667 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 00:50:44,441 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 00:50:44,443 INFO] 157696 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0143, train/util_ratio: 1.0000, train/run_time: 0.1601, eval/loss: 0.3383, eval/top-1-acc: 0.9578, eval/balanced_acc: 0.9606, eval/precision: 0.9558, eval/recall: 0.9606, eval/F1: 0.9567, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 00:52:16,841 INFO] 157952 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: -0.0115, train/util_ratio: 1.0000, train/run_time: 0.1606, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-28 00:53:06,644 INFO] 158208 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0902, train/total_loss: 0.0780, train/util_ratio: 1.0000, train/run_time: 0.1653, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-28 00:53:57,940 INFO] 158464 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0067, train/total_loss: -0.0054, train/util_ratio: 1.0000, train/run_time: 0.1843, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 00:54:48,990 INFO] 158720 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0001, train/total_loss: -0.0095, train/util_ratio: 1.0000, train/run_time: 0.1831, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 00:56:24,110 INFO] 158976 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0206, train/total_loss: 0.0085, train/util_ratio: 1.0000, train/run_time: 0.1617, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-28 00:57:13,887 INFO] 159232 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0098, train/total_loss: -0.0024, train/util_ratio: 1.0000, train/run_time: 0.1655, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-28 00:58:04,412 INFO] 159488 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0335, train/total_loss: 0.0214, train/util_ratio: 1.0000, train/run_time: 0.1712, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-28 00:58:55,065 INFO] validating...
[2023-08-28 00:59:19,394 INFO] confusion matrix:
[[0.915      0.00333333 0.00166667 0.         0.         0.00666667
  0.07166667 0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.005
  0.         0.         0.005      0.        ]
 [0.         0.         0.83666667 0.00166667 0.         0.14833333
  0.01       0.00166667 0.00166667 0.        ]
 [0.004      0.         0.         0.99       0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.         0.01666667 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 00:59:20,297 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 00:59:20,298 INFO] 159744 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0439, train/total_loss: 0.0293, train/util_ratio: 1.0000, train/run_time: 0.1652, eval/loss: 0.3409, eval/top-1-acc: 0.9572, eval/balanced_acc: 0.9601, eval/precision: 0.9552, eval/recall: 0.9601, eval/F1: 0.9561, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 01:00:53,586 INFO] 160000 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0223, train/total_loss: 0.0102, train/util_ratio: 1.0000, train/run_time: 0.1607, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-28 01:01:43,366 INFO] 160256 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0145, train/util_ratio: 1.0000, train/run_time: 0.1667, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:02:33,055 INFO] 160512 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1180, train/total_loss: 0.1084, train/util_ratio: 1.0000, train/run_time: 0.1572, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 01:03:22,631 INFO] 160768 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0102, train/total_loss: -0.0044, train/util_ratio: 1.0000, train/run_time: 0.1568, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 01:04:56,087 INFO] 161024 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0076, train/total_loss: -0.0045, train/util_ratio: 1.0000, train/run_time: 0.1772, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-28 01:05:46,166 INFO] 161280 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0121, train/util_ratio: 1.0000, train/run_time: 0.1592, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-28 01:06:35,751 INFO] 161536 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0054, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1704, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 01:07:25,527 INFO] validating...
[2023-08-28 01:07:50,267 INFO] confusion matrix:
[[0.91833333 0.00333333 0.00166667 0.         0.         0.00666667
  0.06833333 0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.005
  0.         0.         0.005      0.        ]
 [0.         0.         0.83666667 0.00166667 0.         0.14833333
  0.01       0.00166667 0.00166667 0.        ]
 [0.004      0.         0.         0.988      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.004      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.         0.01666667 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 01:07:51,043 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 01:07:51,044 INFO] 161792 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0036, train/total_loss: -0.0085, train/util_ratio: 1.0000, train/run_time: 0.1622, eval/loss: 0.3426, eval/top-1-acc: 0.9578, eval/balanced_acc: 0.9606, eval/precision: 0.9558, eval/recall: 0.9606, eval/F1: 0.9567, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 01:09:22,886 INFO] 162048 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0009, train/total_loss: -0.0112, train/util_ratio: 0.8750, train/run_time: 0.1585, lr: 0.0000, train/prefecth_time: 0.0044 
[2023-08-28 01:10:12,602 INFO] 162304 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.5565, train/total_loss: 0.5394, train/util_ratio: 0.8750, train/run_time: 0.1687, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:11:02,496 INFO] 162560 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0121, train/util_ratio: 1.0000, train/run_time: 0.1796, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 01:11:52,222 INFO] 162816 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0074, train/total_loss: -0.0073, train/util_ratio: 1.0000, train/run_time: 0.1700, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 01:13:25,423 INFO] 163072 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0083, train/total_loss: -0.0013, train/util_ratio: 1.0000, train/run_time: 0.1571, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-28 01:14:15,125 INFO] 163328 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0072, train/total_loss: -0.0049, train/util_ratio: 1.0000, train/run_time: 0.1653, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 01:15:05,109 INFO] 163584 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0115, train/total_loss: -0.0031, train/util_ratio: 1.0000, train/run_time: 0.1677, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 01:15:54,647 INFO] validating...
[2023-08-28 01:16:19,031 INFO] confusion matrix:
[[0.91833333 0.00333333 0.00166667 0.         0.         0.00666667
  0.06833333 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83666667 0.00166667 0.         0.14666667
  0.01       0.00166667 0.00166667 0.        ]
 [0.004      0.         0.         0.988      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01666667 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 01:16:19,768 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 01:16:19,769 INFO] 163840 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1224, train/total_loss: 0.1102, train/util_ratio: 1.0000, train/run_time: 0.1672, eval/loss: 0.3457, eval/top-1-acc: 0.9581, eval/balanced_acc: 0.9610, eval/precision: 0.9562, eval/recall: 0.9610, eval/F1: 0.9571, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 01:17:52,366 INFO] 164096 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0278, train/total_loss: 0.0156, train/util_ratio: 1.0000, train/run_time: 0.1722, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 01:18:42,156 INFO] 164352 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0543, train/total_loss: 0.0423, train/util_ratio: 1.0000, train/run_time: 0.1789, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-28 01:19:31,692 INFO] 164608 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0046, train/total_loss: -0.0051, train/util_ratio: 1.0000, train/run_time: 0.1750, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 01:20:21,385 INFO] 164864 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2167, train/total_loss: 0.2045, train/util_ratio: 1.0000, train/run_time: 0.1673, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 01:21:54,552 INFO] 165120 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0906, train/total_loss: 0.0784, train/util_ratio: 1.0000, train/run_time: 0.1585, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 01:22:44,008 INFO] 165376 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3948, train/total_loss: 0.3827, train/util_ratio: 1.0000, train/run_time: 0.1635, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 01:23:33,541 INFO] 165632 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0188, train/total_loss: 0.0042, train/util_ratio: 1.0000, train/run_time: 0.1644, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 01:24:22,981 INFO] validating...
[2023-08-28 01:24:47,578 INFO] confusion matrix:
[[0.915      0.00333333 0.00166667 0.         0.         0.00666667
  0.07166667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83666667 0.00166667 0.         0.14666667
  0.01       0.00166667 0.00166667 0.        ]
 [0.004      0.         0.         0.988      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01666667 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 01:24:48,337 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 01:24:48,337 INFO] 165888 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0145, train/util_ratio: 1.0000, train/run_time: 0.1641, eval/loss: 0.3486, eval/top-1-acc: 0.9574, eval/balanced_acc: 0.9603, eval/precision: 0.9554, eval/recall: 0.9603, eval/F1: 0.9563, lr: 0.0000, train/prefecth_time: 0.0031 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 01:26:20,736 INFO] 166144 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0289, train/total_loss: 0.0143, train/util_ratio: 1.0000, train/run_time: 0.1629, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:27:10,705 INFO] 166400 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0169, train/util_ratio: 1.0000, train/run_time: 0.1751, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:28:00,352 INFO] 166656 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: -0.0165, train/util_ratio: 1.0000, train/run_time: 0.1686, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 01:28:50,376 INFO] 166912 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0118, train/util_ratio: 1.0000, train/run_time: 0.1654, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:30:23,569 INFO] 167168 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0009, train/total_loss: -0.0162, train/util_ratio: 1.0000, train/run_time: 0.1756, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 01:31:13,192 INFO] 167424 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: -0.0115, train/util_ratio: 1.0000, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 01:32:02,793 INFO] 167680 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0144, train/util_ratio: 1.0000, train/run_time: 0.1569, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:32:52,614 INFO] validating...
[2023-08-28 01:33:17,070 INFO] confusion matrix:
[[0.915      0.00333333 0.00166667 0.         0.         0.00666667
  0.07166667 0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.005
  0.         0.         0.005      0.        ]
 [0.         0.         0.83666667 0.00166667 0.         0.14666667
  0.01       0.00166667 0.00333333 0.        ]
 [0.004      0.         0.         0.988      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01833333 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 01:33:18,001 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 01:33:18,002 INFO] 167936 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1059, train/total_loss: 0.0913, train/util_ratio: 1.0000, train/run_time: 0.1655, eval/loss: 0.3521, eval/top-1-acc: 0.9570, eval/balanced_acc: 0.9599, eval/precision: 0.9550, eval/recall: 0.9599, eval/F1: 0.9560, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 01:34:50,825 INFO] 168192 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2019, train/total_loss: 0.1872, train/util_ratio: 1.0000, train/run_time: 0.1624, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 01:35:40,020 INFO] 168448 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0168, train/util_ratio: 1.0000, train/run_time: 0.1655, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:36:29,105 INFO] 168704 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4491, train/total_loss: 0.4394, train/util_ratio: 1.0000, train/run_time: 0.1737, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 01:37:18,584 INFO] 168960 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2061, train/total_loss: 0.1915, train/util_ratio: 1.0000, train/run_time: 0.1668, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-28 01:38:51,561 INFO] 169216 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1147, train/total_loss: 0.1026, train/util_ratio: 1.0000, train/run_time: 0.1602, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:39:41,295 INFO] 169472 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0363, train/total_loss: 0.0242, train/util_ratio: 1.0000, train/run_time: 0.1917, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:40:30,853 INFO] 169728 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0039, train/total_loss: -0.0107, train/util_ratio: 1.0000, train/run_time: 0.1690, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:41:20,542 INFO] validating...
[2023-08-28 01:41:45,211 INFO] confusion matrix:
[[0.91833333 0.00333333 0.00166667 0.         0.         0.00666667
  0.06833333 0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.005
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83666667 0.00166667 0.         0.14666667
  0.01       0.         0.00333333 0.        ]
 [0.004      0.         0.         0.988      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01833333 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 01:41:46,016 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 01:41:46,017 INFO] 169984 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0023, train/total_loss: -0.0098, train/util_ratio: 1.0000, train/run_time: 0.1567, eval/loss: 0.3546, eval/top-1-acc: 0.9576, eval/balanced_acc: 0.9604, eval/precision: 0.9556, eval/recall: 0.9604, eval/F1: 0.9565, lr: 0.0000, train/prefecth_time: 0.0033 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 01:43:18,254 INFO] 170240 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0143, train/util_ratio: 1.0000, train/run_time: 0.1672, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:44:07,699 INFO] 170496 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0145, train/util_ratio: 1.0000, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 01:44:57,505 INFO] 170752 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4174, train/total_loss: 0.4053, train/util_ratio: 1.0000, train/run_time: 0.1735, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 01:45:47,503 INFO] 171008 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 01:47:20,747 INFO] 171264 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1915, train/total_loss: 0.1819, train/util_ratio: 1.0000, train/run_time: 0.1658, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 01:48:10,458 INFO] 171520 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0016, train/total_loss: -0.0105, train/util_ratio: 1.0000, train/run_time: 0.1684, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 01:49:00,038 INFO] 171776 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0153, train/total_loss: 0.0057, train/util_ratio: 1.0000, train/run_time: 0.1672, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 01:49:49,576 INFO] validating...
[2023-08-28 01:50:14,190 INFO] confusion matrix:
[[0.91833333 0.00333333 0.00166667 0.         0.         0.00666667
  0.06833333 0.         0.00166667 0.        ]
 [0.         0.98333333 0.00666667 0.         0.         0.005
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83833333 0.00166667 0.         0.145
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01833333 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 01:50:15,109 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 01:50:15,111 INFO] 172032 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0078, train/total_loss: -0.0068, train/util_ratio: 1.0000, train/run_time: 0.1610, eval/loss: 0.3570, eval/top-1-acc: 0.9580, eval/balanced_acc: 0.9608, eval/precision: 0.9559, eval/recall: 0.9608, eval/F1: 0.9569, lr: 0.0000, train/prefecth_time: 0.0038 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 01:51:46,577 INFO] 172288 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0144, train/util_ratio: 1.0000, train/run_time: 0.1665, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 01:52:36,046 INFO] 172544 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0380, train/total_loss: 0.0234, train/util_ratio: 1.0000, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:53:25,222 INFO] 172800 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0029, train/total_loss: -0.0092, train/util_ratio: 1.0000, train/run_time: 0.1615, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 01:54:15,059 INFO] 173056 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0870, train/total_loss: 0.0724, train/util_ratio: 1.0000, train/run_time: 0.1606, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 01:55:48,310 INFO] 173312 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0148, train/total_loss: 0.0002, train/util_ratio: 1.0000, train/run_time: 0.1674, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 01:56:37,748 INFO] 173568 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1611, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 01:57:27,083 INFO] 173824 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0061, train/total_loss: -0.0036, train/util_ratio: 1.0000, train/run_time: 0.1651, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-28 01:58:16,379 INFO] validating...
[2023-08-28 01:58:41,101 INFO] confusion matrix:
[[0.92       0.00333333 0.00166667 0.         0.         0.005
  0.06833333 0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.005
  0.         0.         0.005      0.        ]
 [0.         0.         0.84       0.00166667 0.         0.145
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01833333 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 01:58:41,882 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 01:58:41,884 INFO] 174080 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2775, train/total_loss: 0.2679, train/util_ratio: 1.0000, train/run_time: 0.1582, eval/loss: 0.3573, eval/top-1-acc: 0.9585, eval/balanced_acc: 0.9614, eval/precision: 0.9565, eval/recall: 0.9614, eval/F1: 0.9575, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 02:00:14,732 INFO] 174336 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1506, train/total_loss: 0.1409, train/util_ratio: 1.0000, train/run_time: 0.1713, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-28 02:01:04,438 INFO] 174592 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0146, train/util_ratio: 1.0000, train/run_time: 0.1725, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-28 02:01:53,976 INFO] 174848 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0262, train/total_loss: 0.0116, train/util_ratio: 1.0000, train/run_time: 0.1821, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 02:02:43,523 INFO] 175104 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0024, train/total_loss: -0.0097, train/util_ratio: 1.0000, train/run_time: 0.1909, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 02:04:17,254 INFO] 175360 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0446, train/total_loss: 0.0325, train/util_ratio: 1.0000, train/run_time: 0.1699, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 02:05:07,120 INFO] 175616 iteration USE_EMA: True, train/sup_loss: 0.0003, train/unsup_loss: 0.0733, train/total_loss: 0.0615, train/util_ratio: 1.0000, train/run_time: 0.1695, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-28 02:05:56,760 INFO] 175872 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1570, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-28 02:06:46,529 INFO] validating...
[2023-08-28 02:07:10,823 INFO] confusion matrix:
[[0.91833333 0.00333333 0.00166667 0.         0.         0.005
  0.07       0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.005
  0.         0.         0.005      0.        ]
 [0.         0.         0.83833333 0.00166667 0.         0.14666667
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01833333 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 02:07:11,658 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 02:07:11,659 INFO] 176128 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0015, train/total_loss: -0.0131, train/util_ratio: 1.0000, train/run_time: 0.1611, eval/loss: 0.3594, eval/top-1-acc: 0.9583, eval/balanced_acc: 0.9613, eval/precision: 0.9563, eval/recall: 0.9613, eval/F1: 0.9573, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 02:08:43,967 INFO] 176384 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0062, train/total_loss: -0.0110, train/util_ratio: 1.0000, train/run_time: 0.1639, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 02:09:33,743 INFO] 176640 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0146, train/util_ratio: 1.0000, train/run_time: 0.1735, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 02:10:23,400 INFO] 176896 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0071, train/util_ratio: 1.0000, train/run_time: 0.1661, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 02:11:13,142 INFO] 177152 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1063, train/total_loss: 0.0942, train/util_ratio: 1.0000, train/run_time: 0.1776, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-28 02:12:46,156 INFO] 177408 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3492, train/total_loss: 0.3370, train/util_ratio: 1.0000, train/run_time: 0.1685, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 02:13:35,790 INFO] 177664 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0315, train/total_loss: 0.0169, train/util_ratio: 0.8750, train/run_time: 0.1744, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-28 02:14:25,602 INFO] 177920 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3661, train/total_loss: 0.3540, train/util_ratio: 1.0000, train/run_time: 0.1661, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 02:15:15,281 INFO] validating...
[2023-08-28 02:15:39,263 INFO] confusion matrix:
[[0.91833333 0.00333333 0.00166667 0.         0.         0.005
  0.07       0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.005
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.835      0.00166667 0.         0.14666667
  0.01333333 0.         0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01666667 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.00666667
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 02:15:40,065 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 02:15:40,066 INFO] 178176 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0976, train/total_loss: 0.0830, train/util_ratio: 0.8750, train/run_time: 0.1680, eval/loss: 0.3605, eval/top-1-acc: 0.9581, eval/balanced_acc: 0.9611, eval/precision: 0.9562, eval/recall: 0.9611, eval/F1: 0.9571, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 02:17:12,659 INFO] 178432 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0171, train/util_ratio: 1.0000, train/run_time: 0.1699, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 02:18:02,064 INFO] 178688 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0007, train/total_loss: -0.0114, train/util_ratio: 1.0000, train/run_time: 0.1611, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 02:18:51,916 INFO] 178944 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0040, train/total_loss: -0.0057, train/util_ratio: 1.0000, train/run_time: 0.1574, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 02:19:41,339 INFO] 179200 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: -0.0142, train/util_ratio: 1.0000, train/run_time: 0.1657, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 02:21:14,557 INFO] 179456 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: -0.0091, train/util_ratio: 1.0000, train/run_time: 0.1601, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 02:22:04,065 INFO] 179712 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0121, train/util_ratio: 1.0000, train/run_time: 0.1728, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 02:22:53,580 INFO] 179968 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0042, train/total_loss: -0.0079, train/util_ratio: 1.0000, train/run_time: 0.1701, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-28 02:23:43,227 INFO] validating...
[2023-08-28 02:24:07,970 INFO] confusion matrix:
[[0.92       0.00333333 0.00166667 0.         0.         0.005
  0.06833333 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83333333 0.00166667 0.         0.15
  0.01166667 0.         0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.015      0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.01       0.00166667 0.03       0.         0.         0.00666667
  0.         0.         0.00333333 0.94833333]]
[2023-08-28 02:24:08,817 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 02:24:08,818 INFO] 180224 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0143, train/total_loss: 0.0022, train/util_ratio: 1.0000, train/run_time: 0.1620, eval/loss: 0.3603, eval/top-1-acc: 0.9581, eval/balanced_acc: 0.9611, eval/precision: 0.9562, eval/recall: 0.9611, eval/F1: 0.9571, lr: 0.0000, train/prefecth_time: 0.0038 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 02:25:41,035 INFO] 180480 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0078, train/total_loss: -0.0043, train/util_ratio: 1.0000, train/run_time: 0.1594, lr: 0.0000, train/prefecth_time: 0.0046 
[2023-08-28 02:26:30,885 INFO] 180736 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0032, train/total_loss: -0.0089, train/util_ratio: 1.0000, train/run_time: 0.1674, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-28 02:27:20,273 INFO] 180992 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0221, train/total_loss: 0.0100, train/util_ratio: 1.0000, train/run_time: 0.1572, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-28 02:28:09,569 INFO] 181248 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0457, train/total_loss: 0.0335, train/util_ratio: 1.0000, train/run_time: 0.1603, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 02:29:42,765 INFO] 181504 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0918, train/total_loss: 0.0797, train/util_ratio: 1.0000, train/run_time: 0.1777, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 02:30:32,432 INFO] 181760 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: -0.0116, train/util_ratio: 1.0000, train/run_time: 0.1637, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-28 02:31:22,151 INFO] 182016 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0094, train/util_ratio: 1.0000, train/run_time: 0.1614, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 02:32:12,038 INFO] validating...
[2023-08-28 02:32:36,438 INFO] confusion matrix:
[[0.92166667 0.00166667 0.00166667 0.         0.         0.00666667
  0.06666667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.835      0.00166667 0.         0.15
  0.01       0.         0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.015      0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.00666667
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 02:32:37,237 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 02:32:37,238 INFO] 182272 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2297, train/total_loss: 0.2175, train/util_ratio: 1.0000, train/run_time: 0.1715, eval/loss: 0.3619, eval/top-1-acc: 0.9587, eval/balanced_acc: 0.9616, eval/precision: 0.9567, eval/recall: 0.9616, eval/F1: 0.9576, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 02:34:09,328 INFO] 182528 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0019, train/total_loss: -0.0103, train/util_ratio: 1.0000, train/run_time: 0.1582, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-28 02:34:58,574 INFO] 182784 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0094, train/util_ratio: 1.0000, train/run_time: 0.1561, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 02:35:48,269 INFO] 183040 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0021, train/total_loss: -0.0125, train/util_ratio: 1.0000, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 02:36:37,522 INFO] 183296 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0007, train/total_loss: -0.0139, train/util_ratio: 1.0000, train/run_time: 0.1599, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 02:38:10,332 INFO] 183552 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0007, train/total_loss: -0.0114, train/util_ratio: 1.0000, train/run_time: 0.1719, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-28 02:38:59,823 INFO] 183808 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0111, train/total_loss: -0.0036, train/util_ratio: 1.0000, train/run_time: 0.1597, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 02:39:49,501 INFO] 184064 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.5123, train/total_loss: 0.5002, train/util_ratio: 1.0000, train/run_time: 0.1684, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 02:40:38,888 INFO] validating...
[2023-08-28 02:41:02,766 INFO] confusion matrix:
[[0.92166667 0.00166667 0.00166667 0.         0.         0.00666667
  0.06666667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.835      0.00166667 0.         0.15
  0.01       0.         0.00166667 0.        ]
 [0.002      0.         0.         0.99       0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.015      0.
  0.         0.985      0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.00666667
  0.         0.         0.00333333 0.95      ]]
[2023-08-28 02:41:03,514 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 02:41:03,515 INFO] 184320 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0119, train/util_ratio: 1.0000, train/run_time: 0.1653, eval/loss: 0.3618, eval/top-1-acc: 0.9587, eval/balanced_acc: 0.9616, eval/precision: 0.9567, eval/recall: 0.9616, eval/F1: 0.9576, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 02:42:36,417 INFO] 184576 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0025, train/total_loss: -0.0121, train/util_ratio: 1.0000, train/run_time: 0.1659, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 02:43:26,250 INFO] 184832 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0278, train/total_loss: 0.0157, train/util_ratio: 1.0000, train/run_time: 0.1642, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 02:44:16,276 INFO] 185088 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0735, train/total_loss: 0.0614, train/util_ratio: 1.0000, train/run_time: 0.1675, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-28 02:45:06,146 INFO] 185344 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3221, train/total_loss: 0.3050, train/util_ratio: 0.8750, train/run_time: 0.1655, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-28 02:46:39,248 INFO] 185600 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0019, train/total_loss: -0.0103, train/util_ratio: 1.0000, train/run_time: 0.1698, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 02:47:29,257 INFO] 185856 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0009, train/total_loss: -0.0162, train/util_ratio: 1.0000, train/run_time: 0.1625, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 02:48:19,140 INFO] 186112 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0806, train/total_loss: 0.0659, train/util_ratio: 1.0000, train/run_time: 0.1683, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 02:49:08,443 INFO] validating...
[2023-08-28 02:49:32,638 INFO] confusion matrix:
[[0.92166667 0.00166667 0.00166667 0.         0.         0.00666667
  0.06666667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83       0.00166667 0.         0.15166667
  0.01166667 0.00166667 0.00166667 0.        ]
 [0.002      0.         0.         0.99       0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01666667 0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 02:49:33,545 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 02:49:33,546 INFO] 186368 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0097, train/total_loss: -0.0049, train/util_ratio: 1.0000, train/run_time: 0.1677, eval/loss: 0.3616, eval/top-1-acc: 0.9580, eval/balanced_acc: 0.9609, eval/precision: 0.9560, eval/recall: 0.9609, eval/F1: 0.9569, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 02:51:05,564 INFO] 186624 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0032, train/total_loss: -0.0089, train/util_ratio: 1.0000, train/run_time: 0.1693, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 02:51:55,528 INFO] 186880 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0910, train/total_loss: 0.0788, train/util_ratio: 1.0000, train/run_time: 0.1636, lr: 0.0000, train/prefecth_time: 0.0051 
[2023-08-28 02:52:45,104 INFO] 187136 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1220, train/total_loss: 0.1124, train/util_ratio: 1.0000, train/run_time: 0.1664, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 02:53:34,960 INFO] 187392 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1192, train/total_loss: 0.1070, train/util_ratio: 1.0000, train/run_time: 0.1665, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 02:55:07,819 INFO] 187648 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0010, train/total_loss: -0.0111, train/util_ratio: 1.0000, train/run_time: 0.1610, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-28 02:55:57,111 INFO] 187904 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0004, train/total_loss: -0.0117, train/util_ratio: 1.0000, train/run_time: 0.1721, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 02:56:46,861 INFO] 188160 iteration USE_EMA: True, train/sup_loss: 0.0002, train/unsup_loss: 0.0021, train/total_loss: -0.0099, train/util_ratio: 1.0000, train/run_time: 0.1624, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 02:57:36,373 INFO] validating...
[2023-08-28 02:58:00,753 INFO] confusion matrix:
[[0.92166667 0.00166667 0.00166667 0.         0.         0.00666667
  0.06666667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83166667 0.00166667 0.         0.15
  0.01166667 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.015      0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 02:58:01,495 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 02:58:01,496 INFO] 188416 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0121, train/util_ratio: 1.0000, train/run_time: 0.1656, eval/loss: 0.3638, eval/top-1-acc: 0.9585, eval/balanced_acc: 0.9614, eval/precision: 0.9565, eval/recall: 0.9614, eval/F1: 0.9574, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 02:59:33,591 INFO] 188672 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0110, train/total_loss: -0.0061, train/util_ratio: 1.0000, train/run_time: 0.1617, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 03:00:23,139 INFO] 188928 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0170, train/util_ratio: 1.0000, train/run_time: 0.1605, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 03:01:13,100 INFO] 189184 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0030, train/total_loss: -0.0141, train/util_ratio: 1.0000, train/run_time: 0.1653, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-28 03:02:02,811 INFO] 189440 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0035, train/total_loss: -0.0086, train/util_ratio: 1.0000, train/run_time: 0.1563, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 03:03:35,951 INFO] 189696 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0003, train/total_loss: -0.0093, train/util_ratio: 1.0000, train/run_time: 0.1622, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:04:26,029 INFO] 189952 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0095, train/total_loss: -0.0052, train/util_ratio: 1.0000, train/run_time: 0.1660, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:05:15,873 INFO] 190208 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: -0.0116, train/util_ratio: 1.0000, train/run_time: 0.1678, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-28 03:06:05,829 INFO] validating...
[2023-08-28 03:06:30,300 INFO] confusion matrix:
[[0.92166667 0.00166667 0.00166667 0.         0.         0.00666667
  0.06666667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83333333 0.00166667 0.         0.15166667
  0.01       0.         0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01833333 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 03:06:31,135 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 03:06:31,136 INFO] 190464 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0009, train/total_loss: -0.0113, train/util_ratio: 1.0000, train/run_time: 0.1579, eval/loss: 0.3663, eval/top-1-acc: 0.9583, eval/balanced_acc: 0.9613, eval/precision: 0.9563, eval/recall: 0.9613, eval/F1: 0.9572, lr: 0.0000, train/prefecth_time: 0.0040 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 03:08:03,439 INFO] 190720 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: -0.0095, train/util_ratio: 1.0000, train/run_time: 0.1686, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-28 03:08:52,813 INFO] 190976 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0468, train/total_loss: 0.0322, train/util_ratio: 1.0000, train/run_time: 0.1669, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 03:09:42,160 INFO] 191232 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1715, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 03:10:31,745 INFO] 191488 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0115, train/total_loss: -0.0007, train/util_ratio: 1.0000, train/run_time: 0.1683, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 03:12:04,333 INFO] 191744 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1497, train/total_loss: 0.1351, train/util_ratio: 1.0000, train/run_time: 0.1596, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-28 03:12:53,859 INFO] 192000 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: -0.0116, train/util_ratio: 1.0000, train/run_time: 0.1610, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 03:13:43,767 INFO] 192256 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0874, train/total_loss: 0.0777, train/util_ratio: 0.8750, train/run_time: 0.1651, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-28 03:14:33,583 INFO] validating...
[2023-08-28 03:14:57,475 INFO] confusion matrix:
[[0.925      0.00166667 0.00166667 0.         0.         0.005
  0.065      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83166667 0.00166667 0.         0.15166667
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.9875
  0.         0.         0.         0.        ]
 [0.002      0.         0.024      0.002      0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01833333 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.00333333
  0.         0.         0.00333333 0.95333333]]
[2023-08-28 03:14:58,258 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 03:14:58,259 INFO] 192512 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1598, eval/loss: 0.3698, eval/top-1-acc: 0.9585, eval/balanced_acc: 0.9614, eval/precision: 0.9564, eval/recall: 0.9614, eval/F1: 0.9574, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 03:16:30,662 INFO] 192768 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0021, train/total_loss: -0.0100, train/util_ratio: 1.0000, train/run_time: 0.1887, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 03:17:20,116 INFO] 193024 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4206, train/total_loss: 0.4084, train/util_ratio: 1.0000, train/run_time: 0.1601, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-28 03:18:09,592 INFO] 193280 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2000, train/total_loss: 0.1854, train/util_ratio: 0.8750, train/run_time: 0.1678, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:18:59,605 INFO] 193536 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0146, train/util_ratio: 1.0000, train/run_time: 0.1606, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 03:20:32,309 INFO] 193792 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0106, train/total_loss: -0.0041, train/util_ratio: 1.0000, train/run_time: 0.1561, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-28 03:21:21,556 INFO] 194048 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0157, train/total_loss: -0.0014, train/util_ratio: 1.0000, train/run_time: 0.1608, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 03:22:11,040 INFO] 194304 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0580, train/total_loss: 0.0408, train/util_ratio: 1.0000, train/run_time: 0.1706, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:23:00,630 INFO] validating...
[2023-08-28 03:23:25,041 INFO] confusion matrix:
[[0.925      0.00166667 0.00166667 0.         0.         0.005
  0.065      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83166667 0.00166667 0.         0.15166667
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.004      0.         0.024      0.002      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01833333 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 03:23:25,801 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 03:23:25,802 INFO] 194560 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0267, train/total_loss: 0.0121, train/util_ratio: 1.0000, train/run_time: 0.1664, eval/loss: 0.3718, eval/top-1-acc: 0.9580, eval/balanced_acc: 0.9608, eval/precision: 0.9559, eval/recall: 0.9608, eval/F1: 0.9568, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 03:24:58,108 INFO] 194816 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0832, train/total_loss: 0.0661, train/util_ratio: 1.0000, train/run_time: 0.1636, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 03:25:47,646 INFO] 195072 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1655, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:26:37,525 INFO] 195328 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1704, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 03:27:27,157 INFO] 195584 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0617, train/total_loss: 0.0520, train/util_ratio: 1.0000, train/run_time: 0.1592, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-28 03:29:00,411 INFO] 195840 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.3038, train/total_loss: 0.2942, train/util_ratio: 1.0000, train/run_time: 0.1718, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 03:29:50,046 INFO] 196096 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0022, train/total_loss: -0.0124, train/util_ratio: 1.0000, train/run_time: 0.1629, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 03:30:39,795 INFO] 196352 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0014, train/total_loss: -0.0132, train/util_ratio: 1.0000, train/run_time: 0.1765, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 03:31:29,036 INFO] validating...
[2023-08-28 03:31:53,817 INFO] confusion matrix:
[[0.925      0.00166667 0.00166667 0.         0.         0.005
  0.065      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.82666667 0.00166667 0.         0.155
  0.01166667 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.004      0.         0.026      0.002      0.         0.
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01833333 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.03       0.         0.         0.005
  0.         0.         0.00333333 0.95166667]]
[2023-08-28 03:31:54,535 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 03:31:54,536 INFO] 196608 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1327, train/total_loss: 0.1205, train/util_ratio: 1.0000, train/run_time: 0.1663, eval/loss: 0.3716, eval/top-1-acc: 0.9572, eval/balanced_acc: 0.9601, eval/precision: 0.9552, eval/recall: 0.9601, eval/F1: 0.9561, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 03:33:27,215 INFO] 196864 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1458, train/total_loss: 0.1362, train/util_ratio: 1.0000, train/run_time: 0.1669, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:34:16,938 INFO] 197120 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2741, train/total_loss: 0.2620, train/util_ratio: 1.0000, train/run_time: 0.1676, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:35:06,783 INFO] 197376 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0008, train/total_loss: -0.0113, train/util_ratio: 1.0000, train/run_time: 0.1709, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-28 03:35:56,439 INFO] 197632 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0067, train/total_loss: -0.0054, train/util_ratio: 1.0000, train/run_time: 0.1624, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 03:37:29,340 INFO] 197888 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0026, train/total_loss: -0.0145, train/util_ratio: 1.0000, train/run_time: 0.1781, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 03:38:18,654 INFO] 198144 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0766, train/total_loss: 0.0619, train/util_ratio: 1.0000, train/run_time: 0.1567, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-28 03:39:08,172 INFO] 198400 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0077, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1692, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:39:57,748 INFO] validating...
[2023-08-28 03:40:22,521 INFO] confusion matrix:
[[0.92333333 0.00166667 0.00166667 0.         0.         0.005
  0.06666667 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.82833333 0.00166667 0.         0.15333333
  0.01166667 0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.004      0.         0.026      0.002      0.         0.
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01833333 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.02666667 0.         0.         0.005
  0.         0.         0.00333333 0.955     ]]
[2023-08-28 03:40:23,340 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 03:40:23,341 INFO] 198656 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1648, train/total_loss: 0.1476, train/util_ratio: 1.0000, train/run_time: 0.1655, eval/loss: 0.3717, eval/top-1-acc: 0.9574, eval/balanced_acc: 0.9602, eval/precision: 0.9553, eval/recall: 0.9602, eval/F1: 0.9562, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 03:41:55,355 INFO] 198912 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0096, train/util_ratio: 1.0000, train/run_time: 0.1665, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 03:42:45,151 INFO] 199168 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0011, train/total_loss: -0.0086, train/util_ratio: 1.0000, train/run_time: 0.1779, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:43:34,896 INFO] 199424 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0121, train/util_ratio: 1.0000, train/run_time: 0.1770, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 03:44:24,980 INFO] 199680 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: -0.0120, train/util_ratio: 1.0000, train/run_time: 0.1654, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 03:45:57,730 INFO] 199936 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0794, train/total_loss: 0.0622, train/util_ratio: 0.8750, train/run_time: 0.1698, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 03:46:47,389 INFO] 200192 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0040, train/total_loss: -0.0106, train/util_ratio: 1.0000, train/run_time: 0.1714, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 03:47:36,907 INFO] 200448 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0146, train/util_ratio: 1.0000, train/run_time: 0.1602, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-28 03:48:26,441 INFO] validating...
[2023-08-28 03:48:50,769 INFO] confusion matrix:
[[0.92333333 0.00166667 0.00166667 0.         0.         0.005
  0.06666667 0.         0.00166667 0.        ]
 [0.         0.985      0.005      0.         0.         0.00333333
  0.         0.00166667 0.005      0.        ]
 [0.         0.00166667 0.83       0.00166667 0.         0.15333333
  0.01       0.00166667 0.00166667 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.004      0.         0.026      0.002      0.         0.
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01833333 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.02833333 0.         0.         0.005
  0.         0.         0.00333333 0.95333333]]
[2023-08-28 03:48:51,667 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 03:48:51,668 INFO] 200704 iteration, USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0432, train/total_loss: 0.0336, train/util_ratio: 1.0000, train/run_time: 0.1594, eval/loss: 0.3721, eval/top-1-acc: 0.9572, eval/balanced_acc: 0.9601, eval/precision: 0.9551, eval/recall: 0.9601, eval/F1: 0.9561, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 03:50:23,961 INFO] 200960 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0071, train/total_loss: -0.0075, train/util_ratio: 1.0000, train/run_time: 0.1589, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:51:13,508 INFO] 201216 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.4903, train/total_loss: 0.4757, train/util_ratio: 1.0000, train/run_time: 0.1609, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-28 03:52:03,213 INFO] 201472 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0189, train/total_loss: 0.0018, train/util_ratio: 1.0000, train/run_time: 0.1563, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-28 03:52:52,883 INFO] 201728 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.2970, train/total_loss: 0.2823, train/util_ratio: 0.8750, train/run_time: 0.1589, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-28 03:54:25,953 INFO] 201984 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0438, train/total_loss: 0.0341, train/util_ratio: 1.0000, train/run_time: 0.1782, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 03:55:15,502 INFO] 202240 iteration USE_EMA: True, train/sup_loss: 0.0001, train/unsup_loss: 0.0043, train/total_loss: -0.0077, train/util_ratio: 1.0000, train/run_time: 0.1603, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 03:56:05,320 INFO] 202496 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0100, train/total_loss: -0.0022, train/util_ratio: 1.0000, train/run_time: 0.1733, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-28 03:56:54,954 INFO] validating...
[2023-08-28 03:57:19,718 INFO] confusion matrix:
[[0.925      0.00166667 0.00166667 0.         0.         0.005
  0.065      0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83       0.00166667 0.         0.15333333
  0.01       0.00166667 0.00166667 0.        ]
 [0.002      0.         0.         0.988      0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.004      0.         0.026      0.002      0.         0.
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01833333 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.02833333 0.         0.         0.005
  0.         0.         0.00333333 0.95333333]]
[2023-08-28 03:57:20,651 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 03:57:20,652 INFO] 202752 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0117, train/total_loss: -0.0030, train/util_ratio: 1.0000, train/run_time: 0.1649, eval/loss: 0.3722, eval/top-1-acc: 0.9574, eval/balanced_acc: 0.9602, eval/precision: 0.9553, eval/recall: 0.9602, eval/F1: 0.9562, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 03:58:52,232 INFO] 203008 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0008, train/total_loss: -0.0113, train/util_ratio: 1.0000, train/run_time: 0.1616, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-28 03:59:41,516 INFO] 203264 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0000, train/total_loss: -0.0096, train/util_ratio: 1.0000, train/run_time: 0.1592, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-28 04:00:31,033 INFO] 203520 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0031, train/total_loss: -0.0066, train/util_ratio: 1.0000, train/run_time: 0.1658, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-28 04:01:20,324 INFO] 203776 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.1362, train/total_loss: 0.1216, train/util_ratio: 1.0000, train/run_time: 0.1666, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-28 04:02:53,369 INFO] 204032 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0010, train/total_loss: -0.0161, train/util_ratio: 1.0000, train/run_time: 0.1726, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-28 04:03:42,625 INFO] 204288 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0074, train/total_loss: -0.0047, train/util_ratio: 1.0000, train/run_time: 0.1654, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 04:04:32,065 INFO] 204544 iteration USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: -0.0115, train/util_ratio: 1.0000, train/run_time: 0.1595, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-28 04:05:21,176 INFO] validating...
[2023-08-28 04:05:45,123 INFO] confusion matrix:
[[0.92666667 0.00166667 0.00166667 0.         0.         0.005
  0.06333333 0.         0.00166667 0.        ]
 [0.         0.98666667 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.        ]
 [0.         0.00166667 0.83166667 0.00166667 0.         0.15166667
  0.01       0.00166667 0.00166667 0.        ]
 [0.002      0.         0.         0.988      0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.005      0.0025     0.0025     0.         0.985
  0.0025     0.         0.         0.        ]
 [0.004      0.         0.026      0.002      0.         0.
  0.968      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01833333 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.00833333 0.00166667 0.02833333 0.         0.         0.005
  0.         0.         0.00333333 0.95333333]]
[2023-08-28 04:05:45,939 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 04:05:45,940 INFO] 204800 iteration, USE_EMA: True, train/sup_loss: 0.0000, train/unsup_loss: 0.0114, train/total_loss: -0.0008, train/util_ratio: 1.0000, train/run_time: 0.1655, eval/loss: 0.3732, eval/top-1-acc: 0.9578, eval/balanced_acc: 0.9605, eval/precision: 0.9557, eval/recall: 0.9605, eval/F1: 0.9566, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9622, at 20480 iters
[2023-08-28 04:05:49,069 INFO] model saved: ./saved_models/usb_cv/freematch_eurosat_40_0/latest_model.pth
[2023-08-28 04:05:49,071 INFO] Model result - eval/best_acc : 0.9622152250416743
[2023-08-28 04:05:49,071 INFO] Model result - eval/best_it : 20479
