[2023-08-23 06:00:02,999 INFO] Use GPU: 0 for training
[2023-08-23 06:00:53,899 INFO] Use GPU: 0 for training
[2023-08-23 06:00:54,494 INFO] unlabeled data number: 21588, labeled data number 20
[2023-08-23 06:01:07,057 INFO] Create train and test data loaders
[2023-08-23 06:01:07,059 INFO] [!] data loader keys: dict_keys(['train_lb', 'train_ulb', 'eval'])
[2023-08-23 06:01:14,351 INFO] Create optimizer and scheduler
[2023-08-23 06:01:14,378 INFO] Number of Trainable Params: 21402250
[2023-08-23 06:01:14,542 INFO] Arguments: Namespace(save_dir='./saved_models/usb_cv/', save_name='flexmatch_eurosat_20_0', resume=True, load_path='./saved_models/usb_cv//flexmatch_eurosat_20_0/latest_model.pth', overwrite=True, use_tensorboard=True, use_wandb=False, use_aim=False, epoch=200, num_train_iter=204800, num_warmup_iter=0, num_eval_iter=2048, num_log_iter=256, num_labels=20, batch_size=1, uratio=1, eval_batch_size=16, ema_m=0.0, 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='flexmatch', 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://127.0.0.1:18059', dist_backend='nccl', seed=0, gpu=0, multiprocessing_distributed=True, c='/usr/data/jwy/otherbaseline-main/config/usb_cv/flexmatch/flexmatch_eurosat_20_0.yaml', hard_label=True, T=0.5, p_cutoff=0.95, thresh_warmup=True, clip=0.0, distributed=True, ulb_dest_len=21588, lb_dest_len=20)
[2023-08-23 06:01:14,542 INFO] Resume load path ./saved_models/usb_cv//flexmatch_eurosat_20_0/latest_model.pth does not exist
[2023-08-23 06:03:59,111 INFO] Model training
[2023-08-23 06:06:06,310 INFO] 256 iteration USE_EMA: False, train/sup_loss: 0.1574, train/unsup_loss: 1.1996, train/total_loss: 1.3569, train/util_ratio: 1.0000, train/run_time: 0.3181, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 06:07:32,900 INFO] 512 iteration USE_EMA: False, train/sup_loss: 0.1327, train/unsup_loss: 0.6658, train/total_loss: 0.7986, train/util_ratio: 1.0000, train/run_time: 0.3200, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 06:08:59,741 INFO] 768 iteration USE_EMA: False, train/sup_loss: 0.0417, train/unsup_loss: 0.7354, train/total_loss: 0.7770, train/util_ratio: 1.0000, train/run_time: 0.3144, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 06:10:26,499 INFO] 1024 iteration USE_EMA: False, train/sup_loss: 0.0082, train/unsup_loss: 1.0986, train/total_loss: 1.1067, train/util_ratio: 1.0000, train/run_time: 0.3130, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 06:12:36,038 INFO] 1280 iteration USE_EMA: False, train/sup_loss: 0.0111, train/unsup_loss: 0.6697, train/total_loss: 0.6807, train/util_ratio: 1.0000, train/run_time: 0.3149, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 06:14:02,898 INFO] 1536 iteration USE_EMA: False, train/sup_loss: 0.0450, train/unsup_loss: 1.3607, train/total_loss: 1.4057, train/util_ratio: 1.0000, train/run_time: 0.3082, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 06:15:29,328 INFO] 1792 iteration USE_EMA: False, train/sup_loss: 0.0078, train/unsup_loss: 0.9407, train/total_loss: 0.9485, train/util_ratio: 1.0000, train/run_time: 0.3154, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 06:16:55,967 INFO] validating...
[2023-08-23 06:17:20,578 INFO] confusion matrix:
[[0.91666667 0.00666667 0.005      0.00166667 0.         0.00666667
  0.025      0.         0.03833333 0.        ]
 [0.         0.96       0.00666667 0.         0.         0.02833333
  0.         0.         0.005      0.        ]
 [0.         0.00333333 0.87       0.01       0.00166667 0.015
  0.02166667 0.03333333 0.045      0.        ]
 [0.014      0.         0.004      0.25       0.016      0.
  0.01       0.012      0.694      0.        ]
 [0.002      0.         0.         0.014      0.962      0.
  0.018      0.004      0.         0.        ]
 [0.0125     0.0125     0.0125     0.005      0.         0.895
  0.035      0.         0.0275     0.        ]
 [0.022      0.         0.156      0.064      0.01       0.002
  0.738      0.         0.008      0.        ]
 [0.         0.         0.         0.         0.025      0.
  0.00166667 0.97166667 0.00166667 0.        ]
 [0.03206413 0.01002004 0.00200401 0.00801603 0.00801603 0.01002004
  0.00601202 0.         0.9238477  0.        ]
 [0.00833333 0.285      0.005      0.         0.         0.
  0.         0.         0.06666667 0.635     ]]
[2023-08-23 06:17:21,216 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 06:17:22,096 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 06:17:22,097 INFO] 2048 iteration, USE_EMA: False, train/sup_loss: 0.0057, train/unsup_loss: 0.7819, train/total_loss: 0.7876, train/util_ratio: 1.0000, train/run_time: 0.3056, eval/loss: 0.7450, eval/top-1-acc: 0.8161, eval/balanced_acc: 0.8122, eval/precision: 0.8392, eval/recall: 0.8122, eval/F1: 0.8028, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.8161, at 2048 iters
[2023-08-23 06:19:29,740 INFO] 2304 iteration USE_EMA: False, train/sup_loss: 0.0032, train/unsup_loss: 0.4598, train/total_loss: 0.4630, train/util_ratio: 1.0000, train/run_time: 0.3084, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 06:20:56,405 INFO] 2560 iteration USE_EMA: False, train/sup_loss: 0.0069, train/unsup_loss: 1.2447, train/total_loss: 1.2516, train/util_ratio: 1.0000, train/run_time: 0.3138, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 06:22:22,785 INFO] 2816 iteration USE_EMA: False, train/sup_loss: 0.0111, train/unsup_loss: 0.2170, train/total_loss: 0.2281, train/util_ratio: 1.0000, train/run_time: 0.3071, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-23 06:23:48,940 INFO] 3072 iteration USE_EMA: False, train/sup_loss: 0.0058, train/unsup_loss: 0.2739, train/total_loss: 0.2797, train/util_ratio: 1.0000, train/run_time: 0.2984, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 06:25:58,646 INFO] 3328 iteration USE_EMA: False, train/sup_loss: 0.0035, train/unsup_loss: 0.1112, train/total_loss: 0.1147, train/util_ratio: 1.0000, train/run_time: 0.3068, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 06:27:25,513 INFO] 3584 iteration USE_EMA: False, train/sup_loss: 0.0040, train/unsup_loss: 0.4551, train/total_loss: 0.4591, train/util_ratio: 1.0000, train/run_time: 0.3083, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 06:28:51,748 INFO] 3840 iteration USE_EMA: False, train/sup_loss: 0.0033, train/unsup_loss: 0.2651, train/total_loss: 0.2684, train/util_ratio: 1.0000, train/run_time: 0.3085, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 06:30:18,112 INFO] validating...
[2023-08-23 06:30:42,060 INFO] confusion matrix:
[[0.91333333 0.00833333 0.01       0.         0.         0.01166667
  0.035      0.         0.02166667 0.        ]
 [0.         0.93166667 0.02       0.         0.         0.04
  0.         0.00166667 0.00166667 0.005     ]
 [0.         0.00333333 0.93333333 0.         0.         0.01166667
  0.005      0.01166667 0.035      0.        ]
 [0.         0.         0.         0.14       0.002      0.
  0.         0.002      0.856      0.        ]
 [0.         0.         0.002      0.002      0.954      0.
  0.006      0.032      0.004      0.        ]
 [0.005      0.015      0.015      0.         0.         0.9025
  0.04       0.         0.0225     0.        ]
 [0.012      0.         0.176      0.01       0.004      0.002
  0.782      0.         0.014      0.        ]
 [0.         0.         0.         0.         0.00333333 0.
  0.         0.99166667 0.005      0.        ]
 [0.01002004 0.00400802 0.         0.00400802 0.00200401 0.
  0.         0.         0.97995992 0.        ]
 [0.00666667 0.34666667 0.01       0.         0.         0.00333333
  0.         0.         0.015      0.61833333]]
[2023-08-23 06:30:43,001 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 06:30:44,133 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 06:30:44,134 INFO] 4096 iteration, USE_EMA: False, train/sup_loss: 0.0063, train/unsup_loss: 0.4169, train/total_loss: 0.4233, train/util_ratio: 1.0000, train/run_time: 0.3071, eval/loss: 0.8683, eval/top-1-acc: 0.8189, eval/balanced_acc: 0.8147, eval/precision: 0.8643, eval/recall: 0.8147, eval/F1: 0.7973, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.8189, at 4096 iters
[2023-08-23 06:32:51,449 INFO] 4352 iteration USE_EMA: False, train/sup_loss: 0.0039, train/unsup_loss: 0.0466, train/total_loss: 0.0505, train/util_ratio: 1.0000, train/run_time: 0.3079, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 06:34:18,432 INFO] 4608 iteration USE_EMA: False, train/sup_loss: 0.0063, train/unsup_loss: 1.1903, train/total_loss: 1.1965, train/util_ratio: 1.0000, train/run_time: 0.3125, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 06:35:45,003 INFO] 4864 iteration USE_EMA: False, train/sup_loss: 0.0017, train/unsup_loss: 0.6638, train/total_loss: 0.6654, train/util_ratio: 1.0000, train/run_time: 0.3193, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 06:37:11,522 INFO] 5120 iteration USE_EMA: False, train/sup_loss: 0.0103, train/unsup_loss: 0.1445, train/total_loss: 0.1549, train/util_ratio: 1.0000, train/run_time: 0.3064, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 06:39:21,194 INFO] 5376 iteration USE_EMA: False, train/sup_loss: 0.0019, train/unsup_loss: 0.0748, train/total_loss: 0.0767, train/util_ratio: 1.0000, train/run_time: 0.3082, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-23 06:40:48,062 INFO] 5632 iteration USE_EMA: False, train/sup_loss: 0.0022, train/unsup_loss: 0.5880, train/total_loss: 0.5902, train/util_ratio: 1.0000, train/run_time: 0.3031, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 06:42:15,196 INFO] 5888 iteration USE_EMA: False, train/sup_loss: 0.0045, train/unsup_loss: 0.6538, train/total_loss: 0.6583, train/util_ratio: 1.0000, train/run_time: 0.3177, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-23 06:43:42,535 INFO] validating...
[2023-08-23 06:44:06,985 INFO] confusion matrix:
[[0.92       0.005      0.00333333 0.         0.         0.005
  0.03833333 0.         0.02833333 0.        ]
 [0.         0.965      0.00666667 0.         0.         0.01833333
  0.         0.00166667 0.00166667 0.00666667]
 [0.         0.005      0.87666667 0.00166667 0.00333333 0.005
  0.03333333 0.02833333 0.04666667 0.        ]
 [0.004      0.         0.         0.126      0.006      0.
  0.         0.002      0.862      0.        ]
 [0.         0.         0.         0.002      0.984      0.
  0.004      0.01       0.         0.        ]
 [0.015      0.015      0.01       0.         0.         0.8425
  0.0925     0.         0.025      0.        ]
 [0.016      0.002      0.142      0.01       0.01       0.
  0.796      0.002      0.022      0.        ]
 [0.         0.         0.         0.         0.01       0.
  0.         0.98333333 0.00666667 0.        ]
 [0.02204409 0.00601202 0.         0.         0.01002004 0.
  0.         0.         0.96192385 0.        ]
 [0.00333333 0.35666667 0.         0.         0.         0.
  0.         0.         0.03166667 0.60833333]]
[2023-08-23 06:44:07,792 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 06:44:07,793 INFO] 6144 iteration, USE_EMA: False, train/sup_loss: 0.0036, train/unsup_loss: 0.4056, train/total_loss: 0.4092, train/util_ratio: 1.0000, train/run_time: 0.3057, eval/loss: 1.0168, eval/top-1-acc: 0.8116, eval/balanced_acc: 0.8064, eval/precision: 0.8601, eval/recall: 0.8064, eval/F1: 0.7891, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.8189, at 4096 iters
[2023-08-23 06:46:16,992 INFO] 6400 iteration USE_EMA: False, train/sup_loss: 0.0057, train/unsup_loss: 0.6933, train/total_loss: 0.6990, train/util_ratio: 1.0000, train/run_time: 0.3126, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 06:47:44,219 INFO] 6656 iteration USE_EMA: False, train/sup_loss: 0.0020, train/unsup_loss: 0.3629, train/total_loss: 0.3648, train/util_ratio: 1.0000, train/run_time: 0.3103, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 06:49:11,403 INFO] 6912 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.0941, train/total_loss: 0.0950, train/util_ratio: 1.0000, train/run_time: 0.3112, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 06:50:38,466 INFO] 7168 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.3415, train/total_loss: 0.3424, train/util_ratio: 1.0000, train/run_time: 0.3087, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 06:52:48,649 INFO] 7424 iteration USE_EMA: False, train/sup_loss: 0.0043, train/unsup_loss: 0.4053, train/total_loss: 0.4096, train/util_ratio: 1.0000, train/run_time: 0.3086, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 06:54:15,643 INFO] 7680 iteration USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.7390, train/total_loss: 0.7401, train/util_ratio: 1.0000, train/run_time: 0.3344, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 06:55:42,847 INFO] 7936 iteration USE_EMA: False, train/sup_loss: 0.0022, train/unsup_loss: 0.1676, train/total_loss: 0.1698, train/util_ratio: 1.0000, train/run_time: 0.3184, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 06:57:09,851 INFO] validating...
[2023-08-23 06:57:34,086 INFO] confusion matrix:
[[0.85833333 0.005      0.00666667 0.         0.         0.01
  0.06333333 0.         0.05666667 0.        ]
 [0.         0.91166667 0.005      0.         0.         0.04166667
  0.         0.00833333 0.00333333 0.03      ]
 [0.         0.00333333 0.92       0.         0.00166667 0.01166667
  0.00166667 0.04166667 0.01833333 0.00166667]
 [0.002      0.         0.002      0.094      0.004      0.
  0.         0.002      0.896      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.002      0.004      0.         0.        ]
 [0.005      0.0075     0.0025     0.         0.         0.9175
  0.0425     0.         0.025      0.        ]
 [0.006      0.         0.21       0.004      0.008      0.002
  0.75       0.002      0.018      0.        ]
 [0.         0.         0.         0.         0.01166667 0.
  0.         0.98333333 0.005      0.        ]
 [0.00400802 0.00400802 0.         0.         0.         0.
  0.         0.         0.99198397 0.        ]
 [0.00333333 0.23666667 0.00666667 0.         0.         0.00166667
  0.         0.         0.025      0.72666667]]
[2023-08-23 06:57:34,913 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 06:57:34,914 INFO] 8192 iteration, USE_EMA: False, train/sup_loss: 0.0026, train/unsup_loss: 0.4902, train/total_loss: 0.4929, train/util_ratio: 1.0000, train/run_time: 0.3119, eval/loss: 1.0086, eval/top-1-acc: 0.8187, eval/balanced_acc: 0.8145, eval/precision: 0.8655, eval/recall: 0.8145, eval/F1: 0.7934, lr: 0.0000, train/prefecth_time: 0.0023 BEST_EVAL_ACC: 0.8189, at 4096 iters
[2023-08-23 06:59:43,756 INFO] 8448 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.2045, train/total_loss: 0.2057, train/util_ratio: 1.0000, train/run_time: 0.3137, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 07:01:10,662 INFO] 8704 iteration USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.7753, train/total_loss: 0.7768, train/util_ratio: 1.0000, train/run_time: 0.3144, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 07:02:37,418 INFO] 8960 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.0246, train/total_loss: 0.0254, train/util_ratio: 1.0000, train/run_time: 0.3140, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-23 07:04:03,695 INFO] 9216 iteration USE_EMA: False, train/sup_loss: 0.0031, train/unsup_loss: 0.1162, train/total_loss: 0.1193, train/util_ratio: 1.0000, train/run_time: 0.3063, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 07:06:13,812 INFO] 9472 iteration USE_EMA: False, train/sup_loss: 0.0117, train/unsup_loss: 0.1735, train/total_loss: 0.1851, train/util_ratio: 1.0000, train/run_time: 0.3214, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 07:07:41,148 INFO] 9728 iteration USE_EMA: False, train/sup_loss: 0.0035, train/unsup_loss: 0.1155, train/total_loss: 0.1191, train/util_ratio: 0.8750, train/run_time: 0.3179, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 07:09:07,925 INFO] 9984 iteration USE_EMA: False, train/sup_loss: 0.0049, train/unsup_loss: 0.0790, train/total_loss: 0.0839, train/util_ratio: 1.0000, train/run_time: 0.3077, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 07:10:34,313 INFO] validating...
[2023-08-23 07:10:58,962 INFO] confusion matrix:
[[0.94       0.00333333 0.00666667 0.         0.         0.015
  0.02666667 0.         0.00833333 0.        ]
 [0.         0.95       0.01833333 0.         0.         0.01833333
  0.         0.00666667 0.         0.00666667]
 [0.         0.00333333 0.96333333 0.         0.         0.00833333
  0.         0.02166667 0.00333333 0.        ]
 [0.002      0.         0.002      0.214      0.01       0.
  0.         0.012      0.76       0.        ]
 [0.         0.         0.002      0.002      0.99       0.
  0.002      0.004      0.         0.        ]
 [0.005      0.0125     0.025      0.0025     0.         0.91
  0.0275     0.         0.0175     0.        ]
 [0.028      0.         0.28       0.026      0.006      0.002
  0.65       0.008      0.         0.        ]
 [0.         0.         0.         0.         0.01       0.
  0.         0.98833333 0.00166667 0.        ]
 [0.04008016 0.00400802 0.00400802 0.01202405 0.00200401 0.
  0.00200401 0.         0.93587174 0.        ]
 [0.01333333 0.32       0.01833333 0.         0.         0.
  0.         0.         0.01166667 0.63666667]]
[2023-08-23 07:10:59,822 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 07:11:01,132 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 07:11:01,133 INFO] 10240 iteration, USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.4376, train/total_loss: 0.4383, train/util_ratio: 0.8750, train/run_time: 0.3054, eval/loss: 0.8908, eval/top-1-acc: 0.8233, eval/balanced_acc: 0.8178, eval/precision: 0.8564, eval/recall: 0.8178, eval/F1: 0.8046, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.8233, at 10240 iters
[2023-08-23 07:13:08,658 INFO] 10496 iteration USE_EMA: False, train/sup_loss: 0.0020, train/unsup_loss: 0.5508, train/total_loss: 0.5529, train/util_ratio: 1.0000, train/run_time: 0.3096, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 07:14:35,557 INFO] 10752 iteration USE_EMA: False, train/sup_loss: 0.0021, train/unsup_loss: 0.5866, train/total_loss: 0.5887, train/util_ratio: 1.0000, train/run_time: 0.3104, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 07:16:02,649 INFO] 11008 iteration USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.2010, train/total_loss: 0.2023, train/util_ratio: 1.0000, train/run_time: 0.3152, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 07:17:29,352 INFO] 11264 iteration USE_EMA: False, train/sup_loss: 0.0025, train/unsup_loss: 0.0465, train/total_loss: 0.0490, train/util_ratio: 1.0000, train/run_time: 0.3085, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 07:19:38,980 INFO] 11520 iteration USE_EMA: False, train/sup_loss: 0.0014, train/unsup_loss: 0.2473, train/total_loss: 0.2486, train/util_ratio: 1.0000, train/run_time: 0.3071, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 07:21:05,636 INFO] 11776 iteration USE_EMA: False, train/sup_loss: 0.0031, train/unsup_loss: 0.0399, train/total_loss: 0.0430, train/util_ratio: 1.0000, train/run_time: 0.3215, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 07:22:34,672 INFO] 12032 iteration USE_EMA: False, train/sup_loss: 0.0016, train/unsup_loss: 0.1855, train/total_loss: 0.1870, train/util_ratio: 0.8750, train/run_time: 0.3639, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 07:24:14,653 INFO] validating...
[2023-08-23 07:24:38,628 INFO] confusion matrix:
[[0.90166667 0.00333333 0.00833333 0.01833333 0.         0.03666667
  0.03       0.         0.         0.00166667]
 [0.         0.95833333 0.005      0.         0.         0.02333333
  0.         0.01166667 0.         0.00166667]
 [0.         0.00666667 0.955      0.00166667 0.005      0.01333333
  0.00166667 0.01666667 0.         0.        ]
 [0.         0.         0.002      0.922      0.042      0.
  0.         0.018      0.016      0.        ]
 [0.         0.         0.002      0.002      0.99       0.
  0.002      0.004      0.         0.        ]
 [0.005      0.015      0.0075     0.015      0.         0.915
  0.04       0.0025     0.         0.        ]
 [0.018      0.         0.216      0.014      0.008      0.004
  0.738      0.002      0.         0.        ]
 [0.         0.         0.00166667 0.00166667 0.00833333 0.
  0.         0.98833333 0.         0.        ]
 [0.0260521  0.01002004 0.01002004 0.58517034 0.09819639 0.03006012
  0.         0.01002004 0.22845691 0.00200401]
 [0.00666667 0.3        0.01333333 0.         0.         0.035
  0.         0.00166667 0.         0.64333333]]
[2023-08-23 07:24:39,446 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 07:24:40,867 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 07:24:40,869 INFO] 12288 iteration, USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.7641, train/total_loss: 0.7654, train/util_ratio: 1.0000, train/run_time: 0.3429, eval/loss: 0.7638, eval/top-1-acc: 0.8285, eval/balanced_acc: 0.8240, eval/precision: 0.8551, eval/recall: 0.8240, eval/F1: 0.8071, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.8285, at 12288 iters
[2023-08-23 07:27:01,897 INFO] 12544 iteration USE_EMA: False, train/sup_loss: 0.0021, train/unsup_loss: 0.2303, train/total_loss: 0.2323, train/util_ratio: 0.7500, train/run_time: 0.3535, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 07:28:41,433 INFO] 12800 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.2914, train/total_loss: 0.2920, train/util_ratio: 1.0000, train/run_time: 0.3536, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 07:30:21,254 INFO] 13056 iteration USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.3903, train/total_loss: 0.3916, train/util_ratio: 1.0000, train/run_time: 0.3748, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 07:32:00,537 INFO] 13312 iteration USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.4317, train/total_loss: 0.4330, train/util_ratio: 0.8750, train/run_time: 0.3600, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 07:34:24,053 INFO] 13568 iteration USE_EMA: False, train/sup_loss: 0.0017, train/unsup_loss: 0.4283, train/total_loss: 0.4300, train/util_ratio: 1.0000, train/run_time: 0.3597, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-23 07:36:03,509 INFO] 13824 iteration USE_EMA: False, train/sup_loss: 0.0165, train/unsup_loss: 0.1528, train/total_loss: 0.1693, train/util_ratio: 0.8750, train/run_time: 0.3849, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 07:37:43,573 INFO] 14080 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.0333, train/total_loss: 0.0340, train/util_ratio: 1.0000, train/run_time: 0.3642, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 07:39:23,144 INFO] validating...
[2023-08-23 07:39:47,608 INFO] confusion matrix:
[[0.90666667 0.         0.00333333 0.01       0.         0.01166667
  0.06333333 0.         0.         0.005     ]
 [0.         0.76166667 0.005      0.00166667 0.         0.17166667
  0.         0.02       0.         0.04      ]
 [0.         0.         0.85666667 0.02833333 0.00166667 0.03333333
  0.02166667 0.05333333 0.005      0.        ]
 [0.004      0.         0.         0.976      0.008      0.
  0.         0.01       0.002      0.        ]
 [0.         0.         0.         0.004      0.982      0.
  0.004      0.01       0.         0.        ]
 [0.01       0.         0.005      0.0175     0.         0.875
  0.0925     0.         0.         0.        ]
 [0.004      0.         0.148      0.014      0.         0.002
  0.812      0.02       0.         0.        ]
 [0.         0.         0.         0.00166667 0.00333333 0.
  0.         0.995      0.         0.        ]
 [0.0240481  0.         0.         0.7755511  0.02805611 0.00801603
  0.00200401 0.00200401 0.15230461 0.00801603]
 [0.02       0.00166667 0.01166667 0.005      0.         0.015
  0.         0.00833333 0.         0.93833333]]
[2023-08-23 07:39:48,554 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 07:39:49,597 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 07:39:49,598 INFO] 14336 iteration, USE_EMA: False, train/sup_loss: 0.0022, train/unsup_loss: 0.0781, train/total_loss: 0.0803, train/util_ratio: 1.0000, train/run_time: 0.3438, eval/loss: 0.7085, eval/top-1-acc: 0.8309, eval/balanced_acc: 0.8256, eval/precision: 0.8604, eval/recall: 0.8256, eval/F1: 0.8048, lr: 0.0000, train/prefecth_time: 0.0023 BEST_EVAL_ACC: 0.8309, at 14336 iters
[2023-08-23 07:42:10,895 INFO] 14592 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.5392, train/total_loss: 0.5402, train/util_ratio: 0.8750, train/run_time: 0.3590, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 07:43:50,872 INFO] 14848 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.2167, train/total_loss: 0.2180, train/util_ratio: 1.0000, train/run_time: 0.3703, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 07:45:31,334 INFO] 15104 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.5947, train/total_loss: 0.5949, train/util_ratio: 1.0000, train/run_time: 0.3721, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 07:47:10,990 INFO] 15360 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.5498, train/total_loss: 0.5504, train/util_ratio: 1.0000, train/run_time: 0.3477, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-23 07:49:33,167 INFO] 15616 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.9319, train/total_loss: 0.9328, train/util_ratio: 1.0000, train/run_time: 0.3530, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 07:51:12,874 INFO] 15872 iteration USE_EMA: False, train/sup_loss: 0.0037, train/unsup_loss: 0.1554, train/total_loss: 0.1592, train/util_ratio: 0.8750, train/run_time: 0.3856, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 07:52:52,802 INFO] 16128 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.3793, train/total_loss: 0.3796, train/util_ratio: 1.0000, train/run_time: 0.3465, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 07:54:32,961 INFO] validating...
[2023-08-23 07:54:56,998 INFO] confusion matrix:
[[0.85666667 0.00166667 0.00166667 0.         0.         0.035
  0.08833333 0.         0.01666667 0.        ]
 [0.         0.85833333 0.00166667 0.         0.         0.12666667
  0.         0.01166667 0.00166667 0.        ]
 [0.         0.         0.84333333 0.01       0.         0.09833333
  0.00666667 0.03666667 0.005      0.        ]
 [0.002      0.         0.         0.988      0.002      0.
  0.         0.002      0.006      0.        ]
 [0.         0.         0.         0.01       0.978      0.
  0.002      0.01       0.         0.        ]
 [0.005      0.         0.0025     0.015      0.         0.905
  0.07       0.         0.0025     0.        ]
 [0.002      0.         0.178      0.022      0.         0.01
  0.784      0.004      0.         0.        ]
 [0.         0.         0.         0.005      0.00333333 0.
  0.         0.99166667 0.         0.        ]
 [0.00801603 0.         0.00200401 0.04408818 0.00200401 0.
  0.00400802 0.         0.93787575 0.00200401]
 [0.00833333 0.07666667 0.00166667 0.         0.         0.02833333
  0.         0.00166667 0.01833333 0.865     ]]
[2023-08-23 07:54:57,786 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 07:54:58,984 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 07:54:58,986 INFO] 16384 iteration, USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.0488, train/total_loss: 0.0499, train/util_ratio: 1.0000, train/run_time: 0.3445, eval/loss: 0.3716, eval/top-1-acc: 0.8991, eval/balanced_acc: 0.9008, eval/precision: 0.8997, eval/recall: 0.9008, eval/F1: 0.8972, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.8991, at 16384 iters
[2023-08-23 07:57:20,182 INFO] 16640 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.8219, train/total_loss: 0.8224, train/util_ratio: 1.0000, train/run_time: 0.3461, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 07:59:00,180 INFO] 16896 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.2710, train/total_loss: 0.2715, train/util_ratio: 0.8750, train/run_time: 0.3471, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 08:00:39,696 INFO] 17152 iteration USE_EMA: False, train/sup_loss: 0.0104, train/unsup_loss: 0.0847, train/total_loss: 0.0951, train/util_ratio: 1.0000, train/run_time: 0.3579, lr: 0.0000, train/prefecth_time: 0.0046 
[2023-08-23 08:02:19,388 INFO] 17408 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.0849, train/total_loss: 0.0857, train/util_ratio: 0.8750, train/run_time: 0.3524, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 08:04:42,212 INFO] 17664 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1398, train/total_loss: 0.1402, train/util_ratio: 1.0000, train/run_time: 0.3727, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 08:06:21,394 INFO] 17920 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.1623, train/total_loss: 0.1628, train/util_ratio: 1.0000, train/run_time: 0.3517, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 08:08:01,330 INFO] 18176 iteration USE_EMA: False, train/sup_loss: 0.0059, train/unsup_loss: 0.1246, train/total_loss: 0.1304, train/util_ratio: 1.0000, train/run_time: 0.3598, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 08:09:41,062 INFO] validating...
[2023-08-23 08:10:05,223 INFO] confusion matrix:
[[0.90666667 0.00166667 0.00166667 0.         0.         0.00666667
  0.04333333 0.         0.04       0.        ]
 [0.         0.765      0.         0.         0.         0.20166667
  0.         0.01333333 0.02       0.        ]
 [0.         0.         0.74166667 0.00666667 0.005      0.08333333
  0.025      0.06833333 0.07       0.        ]
 [0.         0.         0.         0.96       0.01       0.
  0.         0.016      0.014      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.         0.006      0.         0.        ]
 [0.005      0.         0.0025     0.0225     0.         0.76
  0.065      0.         0.145      0.        ]
 [0.004      0.         0.138      0.012      0.004      0.002
  0.81       0.022      0.008      0.        ]
 [0.         0.         0.         0.00166667 0.005      0.
  0.         0.99333333 0.         0.        ]
 [0.00400802 0.         0.         0.01202405 0.         0.
  0.         0.         0.98396794 0.        ]
 [0.00166667 0.14666667 0.00166667 0.00166667 0.         0.01666667
  0.         0.00166667 0.03166667 0.79833333]]
[2023-08-23 08:10:05,998 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 08:10:05,999 INFO] 18432 iteration, USE_EMA: False, train/sup_loss: 0.0081, train/unsup_loss: 0.3616, train/total_loss: 0.3698, train/util_ratio: 1.0000, train/run_time: 0.3627, eval/loss: 0.5275, eval/top-1-acc: 0.8703, eval/balanced_acc: 0.8711, eval/precision: 0.8723, eval/recall: 0.8711, eval/F1: 0.8671, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.8991, at 16384 iters
[2023-08-23 08:12:27,995 INFO] 18688 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.2723, train/total_loss: 0.2728, train/util_ratio: 1.0000, train/run_time: 0.3468, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 08:14:07,198 INFO] 18944 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3553, train/total_loss: 0.3555, train/util_ratio: 0.8750, train/run_time: 0.3431, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-23 08:15:46,632 INFO] 19200 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0625, train/total_loss: 0.0627, train/util_ratio: 1.0000, train/run_time: 0.3578, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 08:17:25,761 INFO] 19456 iteration USE_EMA: False, train/sup_loss: 0.0170, train/unsup_loss: 0.7243, train/total_loss: 0.7413, train/util_ratio: 1.0000, train/run_time: 0.3529, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-23 08:19:48,921 INFO] 19712 iteration USE_EMA: False, train/sup_loss: 0.0030, train/unsup_loss: 0.0613, train/total_loss: 0.0644, train/util_ratio: 0.8750, train/run_time: 0.3707, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 08:21:28,535 INFO] 19968 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.0389, train/total_loss: 0.0394, train/util_ratio: 1.0000, train/run_time: 0.3760, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-23 08:23:44,022 INFO] 20224 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0760, train/total_loss: 0.0762, train/util_ratio: 1.0000, train/run_time: 0.5341, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 08:26:05,396 INFO] validating...
[2023-08-23 08:26:29,563 INFO] confusion matrix:
[[0.51833333 0.         0.00166667 0.00333333 0.         0.02666667
  0.42333333 0.         0.02666667 0.        ]
 [0.         0.855      0.005      0.         0.         0.13333333
  0.         0.005      0.00166667 0.        ]
 [0.         0.         0.79333333 0.01833333 0.00333333 0.09
  0.03166667 0.02666667 0.03666667 0.        ]
 [0.         0.         0.         0.982      0.004      0.
  0.         0.006      0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.002      0.004      0.         0.        ]
 [0.         0.         0.0025     0.0175     0.         0.8875
  0.0875     0.         0.005      0.        ]
 [0.         0.         0.136      0.02       0.002      0.002
  0.824      0.016      0.         0.        ]
 [0.         0.         0.         0.00333333 0.00666667 0.
  0.         0.98833333 0.00166667 0.        ]
 [0.00400802 0.00200401 0.         0.02204409 0.00200401 0.
  0.00400802 0.         0.96392786 0.00200401]
 [0.00333333 0.01       0.00833333 0.005      0.         0.01166667
  0.         0.00333333 0.01333333 0.945     ]]
[2023-08-23 08:26:30,524 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 08:26:30,525 INFO] 20480 iteration, USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.5209, train/total_loss: 0.5213, train/util_ratio: 1.0000, train/run_time: 0.5388, eval/loss: 0.5412, eval/top-1-acc: 0.8696, eval/balanced_acc: 0.8749, eval/precision: 0.8831, eval/recall: 0.8749, eval/F1: 0.8672, lr: 0.0000, train/prefecth_time: 0.0023 BEST_EVAL_ACC: 0.8991, at 16384 iters
[2023-08-23 08:29:32,983 INFO] 20736 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0383, train/total_loss: 0.0385, train/util_ratio: 1.0000, train/run_time: 0.5378, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 08:31:54,503 INFO] 20992 iteration USE_EMA: False, train/sup_loss: 0.0894, train/unsup_loss: 0.1220, train/total_loss: 0.2114, train/util_ratio: 1.0000, train/run_time: 0.5322, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 08:34:15,334 INFO] 21248 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.0196, train/total_loss: 0.0204, train/util_ratio: 1.0000, train/run_time: 0.5279, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 08:36:34,929 INFO] 21504 iteration USE_EMA: False, train/sup_loss: 0.0023, train/unsup_loss: 0.0087, train/total_loss: 0.0110, train/util_ratio: 1.0000, train/run_time: 0.5244, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 08:39:37,609 INFO] 21760 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.0512, train/total_loss: 0.0519, train/util_ratio: 0.8750, train/run_time: 0.5324, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 08:41:58,364 INFO] 22016 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.3207, train/total_loss: 0.3213, train/util_ratio: 0.8750, train/run_time: 0.5438, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 08:44:20,713 INFO] 22272 iteration USE_EMA: False, train/sup_loss: 0.0024, train/unsup_loss: 0.2009, train/total_loss: 0.2033, train/util_ratio: 1.0000, train/run_time: 0.4787, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 08:46:44,555 INFO] validating...
[2023-08-23 08:47:08,599 INFO] confusion matrix:
[[0.85666667 0.00166667 0.00833333 0.00166667 0.         0.01166667
  0.10666667 0.         0.01166667 0.00166667]
 [0.         0.91666667 0.005      0.         0.         0.07333333
  0.         0.005      0.         0.        ]
 [0.         0.005      0.81666667 0.01       0.00166667 0.06166667
  0.01333333 0.035      0.05666667 0.        ]
 [0.         0.         0.004      0.982      0.002      0.
  0.         0.002      0.01       0.        ]
 [0.         0.         0.002      0.004      0.988      0.
  0.         0.006      0.         0.        ]
 [0.005      0.0025     0.005      0.02       0.         0.855
  0.0975     0.         0.015      0.        ]
 [0.004      0.         0.208      0.012      0.         0.002
  0.752      0.022      0.         0.        ]
 [0.         0.         0.         0.00333333 0.01       0.
  0.         0.985      0.00166667 0.        ]
 [0.00200401 0.         0.         0.01202405 0.         0.
  0.00200401 0.         0.98196393 0.00200401]
 [0.00666667 0.02       0.00666667 0.00166667 0.         0.
  0.         0.00166667 0.01       0.95333333]]
[2023-08-23 08:47:09,400 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 08:47:10,524 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 08:47:10,526 INFO] 22528 iteration, USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.2602, train/total_loss: 0.2610, train/util_ratio: 0.8750, train/run_time: 0.5395, eval/loss: 0.4074, eval/top-1-acc: 0.9094, eval/balanced_acc: 0.9087, eval/precision: 0.9067, eval/recall: 0.9087, eval/F1: 0.9067, lr: 0.0000, train/prefecth_time: 0.0023 BEST_EVAL_ACC: 0.9094, at 22528 iters
[2023-08-23 08:50:13,118 INFO] 22784 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1520, train/total_loss: 0.1522, train/util_ratio: 1.0000, train/run_time: 0.5077, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 08:52:34,592 INFO] 23040 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.6495, train/total_loss: 0.6499, train/util_ratio: 1.0000, train/run_time: 0.5290, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 08:54:55,310 INFO] 23296 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1787, train/total_loss: 0.1789, train/util_ratio: 1.0000, train/run_time: 0.5575, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 08:57:18,602 INFO] 23552 iteration USE_EMA: False, train/sup_loss: 0.0019, train/unsup_loss: 0.1316, train/total_loss: 0.1334, train/util_ratio: 0.8750, train/run_time: 0.5339, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-23 09:00:21,926 INFO] 23808 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.3047, train/total_loss: 0.3051, train/util_ratio: 1.0000, train/run_time: 0.4775, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 09:02:37,798 INFO] 24064 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.9912, train/total_loss: 0.9921, train/util_ratio: 1.0000, train/run_time: 0.4808, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 09:04:55,346 INFO] 24320 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2914, train/total_loss: 0.2915, train/util_ratio: 0.8750, train/run_time: 0.5420, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 09:07:14,345 INFO] validating...
[2023-08-23 09:07:38,635 INFO] confusion matrix:
[[0.85166667 0.         0.00333333 0.00166667 0.         0.00333333
  0.105      0.         0.035      0.        ]
 [0.         0.87666667 0.00166667 0.         0.         0.085
  0.         0.00833333 0.02833333 0.        ]
 [0.         0.005      0.83333333 0.005      0.00166667 0.02666667
  0.01666667 0.03333333 0.07833333 0.        ]
 [0.         0.         0.         0.948      0.002      0.
  0.         0.         0.05       0.        ]
 [0.         0.         0.         0.004      0.99       0.
  0.         0.006      0.         0.        ]
 [0.0075     0.         0.005      0.0225     0.         0.445
  0.31       0.         0.21       0.        ]
 [0.004      0.         0.176      0.006      0.004      0.
  0.788      0.01       0.012      0.        ]
 [0.         0.         0.         0.00333333 0.00833333 0.
  0.         0.985      0.00333333 0.        ]
 [0.00200401 0.         0.         0.00200401 0.         0.
  0.         0.         0.99599198 0.        ]
 [0.00333333 0.01       0.         0.00166667 0.         0.00333333
  0.         0.         0.02333333 0.95833333]]
[2023-08-23 09:07:39,563 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 09:07:39,564 INFO] 24576 iteration, USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.2029, train/total_loss: 0.2039, train/util_ratio: 0.8750, train/run_time: 0.4792, eval/loss: 0.5757, eval/top-1-acc: 0.8781, eval/balanced_acc: 0.8672, eval/precision: 0.8774, eval/recall: 0.8672, eval/F1: 0.8652, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9094, at 22528 iters
[2023-08-23 09:10:43,700 INFO] 24832 iteration USE_EMA: False, train/sup_loss: 0.0052, train/unsup_loss: 0.1680, train/total_loss: 0.1731, train/util_ratio: 1.0000, train/run_time: 0.5333, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-23 09:13:04,631 INFO] 25088 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0416, train/total_loss: 0.0419, train/util_ratio: 1.0000, train/run_time: 0.5124, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 09:15:25,691 INFO] 25344 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0181, train/total_loss: 0.0184, train/util_ratio: 0.8750, train/run_time: 0.4827, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 09:17:47,496 INFO] 25600 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.0298, train/total_loss: 0.0303, train/util_ratio: 0.7500, train/run_time: 0.5301, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-23 09:20:51,465 INFO] 25856 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.0633, train/total_loss: 0.0643, train/util_ratio: 1.0000, train/run_time: 0.4926, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 09:23:10,572 INFO] 26112 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0846, train/total_loss: 0.0849, train/util_ratio: 1.0000, train/run_time: 0.5308, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 09:25:31,883 INFO] 26368 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0409, train/total_loss: 0.0412, train/util_ratio: 1.0000, train/run_time: 0.4791, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 09:27:54,040 INFO] validating...
[2023-08-23 09:28:18,025 INFO] confusion matrix:
[[0.95333333 0.         0.         0.         0.         0.01333333
  0.03       0.         0.00166667 0.00166667]
 [0.         0.78666667 0.00333333 0.         0.         0.18333333
  0.00333333 0.01       0.01333333 0.        ]
 [0.         0.         0.68666667 0.01       0.         0.125
  0.02       0.02166667 0.135      0.00166667]
 [0.         0.         0.002      0.99       0.002      0.
  0.         0.002      0.004      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.         0.004      0.         0.        ]
 [0.01       0.         0.         0.0125     0.         0.77
  0.2025     0.         0.005      0.        ]
 [0.006      0.         0.176      0.008      0.         0.014
  0.788      0.006      0.002      0.        ]
 [0.         0.         0.         0.005      0.01       0.
  0.         0.98333333 0.00166667 0.        ]
 [0.01002004 0.         0.         0.01803607 0.         0.
  0.         0.         0.96593186 0.00601202]
 [0.005      0.00166667 0.00166667 0.00166667 0.         0.00333333
  0.         0.         0.00333333 0.98333333]]
[2023-08-23 09:28:18,828 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 09:28:18,829 INFO] 26624 iteration, USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.4489, train/total_loss: 0.4492, train/util_ratio: 0.7500, train/run_time: 0.5382, eval/loss: 0.5227, eval/top-1-acc: 0.8913, eval/balanced_acc: 0.8901, eval/precision: 0.8884, eval/recall: 0.8901, eval/F1: 0.8858, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9094, at 22528 iters
[2023-08-23 09:31:25,253 INFO] 26880 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.3769, train/total_loss: 0.3775, train/util_ratio: 1.0000, train/run_time: 0.5360, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 09:33:44,914 INFO] 27136 iteration USE_EMA: False, train/sup_loss: 0.0034, train/unsup_loss: 0.2808, train/total_loss: 0.2842, train/util_ratio: 0.8750, train/run_time: 0.5281, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 09:36:07,173 INFO] 27392 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.7130, train/total_loss: 0.7134, train/util_ratio: 1.0000, train/run_time: 0.5386, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 09:38:27,083 INFO] 27648 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.0131, train/total_loss: 0.0142, train/util_ratio: 1.0000, train/run_time: 0.4759, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 09:41:30,304 INFO] 27904 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0445, train/total_loss: 0.0446, train/util_ratio: 0.8750, train/run_time: 0.4779, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 09:43:51,407 INFO] 28160 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1762, train/total_loss: 0.1765, train/util_ratio: 1.0000, train/run_time: 0.5325, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 09:46:12,050 INFO] 28416 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.2877, train/total_loss: 0.2879, train/util_ratio: 1.0000, train/run_time: 0.5326, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 09:48:34,149 INFO] validating...
[2023-08-23 09:48:58,580 INFO] confusion matrix:
[[0.94       0.00166667 0.         0.00166667 0.         0.005
  0.04       0.         0.01       0.00166667]
 [0.         0.875      0.005      0.         0.         0.11166667
  0.         0.00666667 0.00166667 0.        ]
 [0.         0.         0.665      0.01166667 0.00166667 0.11166667
  0.03833333 0.03166667 0.14       0.        ]
 [0.         0.         0.         0.976      0.008      0.
  0.         0.002      0.014      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.005      0.         0.         0.015      0.         0.7125
  0.26       0.         0.0075     0.        ]
 [0.006      0.         0.13       0.01       0.         0.002
  0.846      0.006      0.         0.        ]
 [0.         0.         0.         0.00333333 0.01       0.
  0.         0.985      0.00166667 0.        ]
 [0.00200401 0.00400802 0.         0.00601202 0.00200401 0.
  0.         0.         0.97995992 0.00601202]
 [0.005      0.01       0.00333333 0.00166667 0.         0.00333333
  0.         0.         0.00666667 0.97      ]]
[2023-08-23 09:48:59,601 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 09:48:59,603 INFO] 28672 iteration, USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2401, train/total_loss: 0.2403, train/util_ratio: 1.0000, train/run_time: 0.4756, eval/loss: 0.5029, eval/top-1-acc: 0.8970, eval/balanced_acc: 0.8943, eval/precision: 0.8920, eval/recall: 0.8943, eval/F1: 0.8905, lr: 0.0000, train/prefecth_time: 0.0033 BEST_EVAL_ACC: 0.9094, at 22528 iters
[2023-08-23 09:52:02,407 INFO] 28928 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.2183, train/total_loss: 0.2185, train/util_ratio: 1.0000, train/run_time: 0.4850, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 09:54:23,217 INFO] 29184 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.6480, train/total_loss: 0.6484, train/util_ratio: 0.8750, train/run_time: 0.5447, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 09:56:46,666 INFO] 29440 iteration USE_EMA: False, train/sup_loss: 0.0020, train/unsup_loss: 0.1624, train/total_loss: 0.1644, train/util_ratio: 1.0000, train/run_time: 0.5315, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 09:59:06,360 INFO] 29696 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.5616, train/total_loss: 0.5620, train/util_ratio: 1.0000, train/run_time: 0.4788, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 10:02:11,958 INFO] 29952 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4757, train/total_loss: 0.4758, train/util_ratio: 1.0000, train/run_time: 0.5422, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 10:04:34,049 INFO] 30208 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.2499, train/total_loss: 0.2503, train/util_ratio: 1.0000, train/run_time: 0.4758, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 10:06:56,382 INFO] 30464 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2623, train/total_loss: 0.2626, train/util_ratio: 1.0000, train/run_time: 0.4777, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 10:09:16,278 INFO] validating...
[2023-08-23 10:09:40,306 INFO] confusion matrix:
[[0.94333333 0.00166667 0.         0.00333333 0.         0.00666667
  0.035      0.         0.00666667 0.00333333]
 [0.00166667 0.91666667 0.005      0.         0.         0.065
  0.         0.005      0.00333333 0.00333333]
 [0.         0.005      0.70666667 0.005      0.         0.05
  0.04       0.02833333 0.165      0.        ]
 [0.         0.         0.         0.99       0.002      0.
  0.         0.002      0.006      0.        ]
 [0.         0.         0.         0.006      0.992      0.
  0.         0.002      0.         0.        ]
 [0.005      0.005      0.005      0.0175     0.         0.7175
  0.2475     0.         0.0025     0.        ]
 [0.006      0.         0.114      0.012      0.         0.
  0.858      0.01       0.         0.        ]
 [0.         0.         0.         0.005      0.01       0.
  0.         0.98333333 0.00166667 0.        ]
 [0.00400802 0.         0.         0.00801603 0.         0.
  0.         0.         0.98597194 0.00200401]
 [0.005      0.00333333 0.00333333 0.00166667 0.         0.
  0.         0.         0.00333333 0.98333333]]
[2023-08-23 10:09:41,113 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 10:09:41,879 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 10:09:41,880 INFO] 30720 iteration, USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0179, train/total_loss: 0.0182, train/util_ratio: 1.0000, train/run_time: 0.5382, eval/loss: 0.3969, eval/top-1-acc: 0.9111, eval/balanced_acc: 0.9077, eval/precision: 0.9075, eval/recall: 0.9077, eval/F1: 0.9051, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9111, at 30720 iters
[2023-08-23 10:12:48,246 INFO] 30976 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.1462, train/total_loss: 0.1467, train/util_ratio: 1.0000, train/run_time: 0.5425, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 10:15:12,079 INFO] 31232 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3984, train/total_loss: 0.3987, train/util_ratio: 1.0000, train/run_time: 0.5384, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 10:17:33,880 INFO] 31488 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.0157, train/total_loss: 0.0163, train/util_ratio: 1.0000, train/run_time: 0.5390, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 10:19:56,196 INFO] 31744 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2842, train/total_loss: 0.2843, train/util_ratio: 0.8750, train/run_time: 0.4786, lr: 0.0000, train/prefecth_time: 0.0023 
[2023-08-23 10:22:59,619 INFO] 32000 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.2083, train/total_loss: 0.2087, train/util_ratio: 0.8750, train/run_time: 0.5271, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 10:25:22,146 INFO] 32256 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.3495, train/total_loss: 0.3499, train/util_ratio: 1.0000, train/run_time: 0.5274, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 10:27:37,966 INFO] 32512 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.4658, train/total_loss: 0.4660, train/util_ratio: 1.0000, train/run_time: 0.4771, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 10:29:59,511 INFO] validating...
[2023-08-23 10:30:23,342 INFO] confusion matrix:
[[0.96666667 0.         0.         0.         0.         0.00166667
  0.02333333 0.         0.00666667 0.00166667]
 [0.00166667 0.88166667 0.00166667 0.         0.         0.07333333
  0.         0.01166667 0.00333333 0.02666667]
 [0.00166667 0.01166667 0.72333333 0.00833333 0.00166667 0.055
  0.01166667 0.02333333 0.16       0.00333333]
 [0.         0.         0.         0.982      0.002      0.
  0.         0.002      0.014      0.        ]
 [0.         0.         0.         0.         0.998      0.
  0.         0.         0.002      0.        ]
 [0.0375     0.0025     0.005      0.02       0.         0.725
  0.1925     0.         0.0175     0.        ]
 [0.014      0.         0.178      0.018      0.         0.004
  0.776      0.         0.01       0.        ]
 [0.         0.         0.00166667 0.00333333 0.02166667 0.
  0.         0.97166667 0.00166667 0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.01       0.         0.         0.00166667 0.         0.00166667
  0.         0.         0.00833333 0.97833333]]
[2023-08-23 10:30:24,140 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 10:30:24,140 INFO] 32768 iteration, USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0476, train/total_loss: 0.0477, train/util_ratio: 1.0000, train/run_time: 0.5368, eval/loss: 0.4592, eval/top-1-acc: 0.9029, eval/balanced_acc: 0.8993, eval/precision: 0.8980, eval/recall: 0.8993, eval/F1: 0.8968, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9111, at 30720 iters
[2023-08-23 10:33:24,614 INFO] 33024 iteration USE_EMA: False, train/sup_loss: 0.0029, train/unsup_loss: 0.0310, train/total_loss: 0.0339, train/util_ratio: 0.7500, train/run_time: 0.4801, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 10:35:41,599 INFO] 33280 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.1047, train/total_loss: 0.1052, train/util_ratio: 1.0000, train/run_time: 0.5302, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 10:38:02,683 INFO] 33536 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0780, train/total_loss: 0.0781, train/util_ratio: 0.8750, train/run_time: 0.5377, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 10:40:23,644 INFO] 33792 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.3266, train/total_loss: 0.3271, train/util_ratio: 1.0000, train/run_time: 0.4764, lr: 0.0000, train/prefecth_time: 0.0023 
[2023-08-23 10:43:26,515 INFO] 34048 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.4146, train/total_loss: 0.4151, train/util_ratio: 0.8750, train/run_time: 0.4963, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-23 10:45:46,831 INFO] 34304 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0735, train/total_loss: 0.0736, train/util_ratio: 0.8750, train/run_time: 0.5637, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 10:48:09,389 INFO] 34560 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.7046, train/total_loss: 0.7048, train/util_ratio: 0.8750, train/run_time: 0.5397, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 10:50:30,548 INFO] validating...
[2023-08-23 10:50:55,013 INFO] confusion matrix:
[[0.93166667 0.00166667 0.         0.00333333 0.         0.015
  0.035      0.         0.01333333 0.        ]
 [0.         0.91       0.00166667 0.00166667 0.         0.07166667
  0.         0.01166667 0.00333333 0.        ]
 [0.         0.00166667 0.74       0.00833333 0.00166667 0.05166667
  0.00833333 0.04166667 0.14666667 0.        ]
 [0.         0.         0.         0.988      0.         0.
  0.         0.002      0.01       0.        ]
 [0.         0.         0.         0.004      0.992      0.
  0.         0.004      0.         0.        ]
 [0.0075     0.0025     0.005      0.02       0.         0.7375
  0.2175     0.         0.01       0.        ]
 [0.008      0.         0.182      0.012      0.002      0.002
  0.786      0.006      0.002      0.        ]
 [0.         0.         0.         0.005      0.00666667 0.
  0.         0.98666667 0.00166667 0.        ]
 [0.00200401 0.         0.         0.01002004 0.         0.
  0.         0.         0.98597194 0.00200401]
 [0.01333333 0.08333333 0.01333333 0.00333333 0.         0.02333333
  0.         0.00333333 0.015      0.845     ]]
[2023-08-23 10:50:55,831 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 10:50:55,832 INFO] 34816 iteration, USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0327, train/total_loss: 0.0329, train/util_ratio: 0.7500, train/run_time: 0.5304, eval/loss: 0.4862, eval/top-1-acc: 0.8924, eval/balanced_acc: 0.8903, eval/precision: 0.8889, eval/recall: 0.8903, eval/F1: 0.8877, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9111, at 30720 iters
[2023-08-23 10:53:58,721 INFO] 35072 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.1349, train/total_loss: 0.1352, train/util_ratio: 0.8750, train/run_time: 0.5344, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 10:56:18,648 INFO] 35328 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0032, train/total_loss: 0.0032, train/util_ratio: 1.0000, train/run_time: 0.6218, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 10:58:40,322 INFO] 35584 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2004, train/total_loss: 0.2005, train/util_ratio: 1.0000, train/run_time: 0.5292, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 11:01:03,113 INFO] 35840 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0543, train/total_loss: 0.0544, train/util_ratio: 0.8750, train/run_time: 0.5373, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 11:04:09,807 INFO] 36096 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0043, train/total_loss: 0.0045, train/util_ratio: 0.8750, train/run_time: 0.5129, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 11:06:30,370 INFO] 36352 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0054, train/total_loss: 0.0055, train/util_ratio: 1.0000, train/run_time: 0.5533, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 11:08:50,144 INFO] 36608 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0503, train/total_loss: 0.0505, train/util_ratio: 1.0000, train/run_time: 0.5298, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 11:11:11,214 INFO] validating...
[2023-08-23 11:11:35,556 INFO] confusion matrix:
[[0.94166667 0.00166667 0.         0.         0.         0.01
  0.03666667 0.         0.00833333 0.00166667]
 [0.         0.875      0.00166667 0.00166667 0.         0.105
  0.         0.00833333 0.         0.00833333]
 [0.         0.00333333 0.78333333 0.00666667 0.00166667 0.065
  0.00666667 0.04       0.09166667 0.00166667]
 [0.         0.         0.         0.988      0.         0.
  0.         0.002      0.01       0.        ]
 [0.         0.         0.         0.008      0.984      0.
  0.         0.008      0.         0.        ]
 [0.0075     0.         0.005      0.02       0.         0.725
  0.2275     0.         0.015      0.        ]
 [0.008      0.         0.204      0.016      0.         0.002
  0.768      0.002      0.         0.        ]
 [0.         0.         0.         0.00833333 0.00166667 0.
  0.         0.98833333 0.00166667 0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.00200401
  0.         0.         0.98997996 0.        ]
 [0.005      0.02666667 0.00333333 0.00166667 0.         0.19166667
  0.         0.         0.01       0.76166667]]
[2023-08-23 11:11:36,366 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 11:11:36,367 INFO] 36864 iteration, USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.5498, train/total_loss: 0.5499, train/util_ratio: 1.0000, train/run_time: 0.4762, eval/loss: 0.6329, eval/top-1-acc: 0.8824, eval/balanced_acc: 0.8805, eval/precision: 0.8815, eval/recall: 0.8805, eval/F1: 0.8777, lr: 0.0000, train/prefecth_time: 0.0031 BEST_EVAL_ACC: 0.9111, at 30720 iters
[2023-08-23 11:14:38,189 INFO] 37120 iteration USE_EMA: False, train/sup_loss: 0.0014, train/unsup_loss: 0.4432, train/total_loss: 0.4445, train/util_ratio: 1.0000, train/run_time: 0.5324, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 11:17:00,874 INFO] 37376 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1583, train/total_loss: 0.1584, train/util_ratio: 1.0000, train/run_time: 0.5437, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 11:19:17,430 INFO] 37632 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1075, train/total_loss: 0.1078, train/util_ratio: 1.0000, train/run_time: 0.5422, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 11:21:37,997 INFO] 37888 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.0055, train/total_loss: 0.0062, train/util_ratio: 1.0000, train/run_time: 0.5407, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 11:24:41,540 INFO] 38144 iteration USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.2541, train/total_loss: 0.2552, train/util_ratio: 1.0000, train/run_time: 0.5273, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 11:27:02,253 INFO] 38400 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0355, train/total_loss: 0.0357, train/util_ratio: 0.8750, train/run_time: 0.4851, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 11:29:23,303 INFO] 38656 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0133, train/total_loss: 0.0134, train/util_ratio: 1.0000, train/run_time: 0.5407, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 11:31:39,231 INFO] validating...
[2023-08-23 11:32:03,301 INFO] confusion matrix:
[[0.94333333 0.00166667 0.         0.00166667 0.         0.01666667
  0.03166667 0.         0.00333333 0.00166667]
 [0.         0.85333333 0.00333333 0.         0.         0.14333333
  0.         0.         0.         0.        ]
 [0.         0.005      0.65666667 0.00333333 0.         0.20333333
  0.01       0.00166667 0.12       0.        ]
 [0.         0.         0.         0.996      0.002      0.
  0.         0.         0.002      0.        ]
 [0.         0.         0.002      0.002      0.988      0.
  0.004      0.004      0.         0.        ]
 [0.005      0.         0.         0.01       0.         0.775
  0.21       0.         0.         0.        ]
 [0.01       0.         0.166      0.008      0.002      0.022
  0.792      0.         0.         0.        ]
 [0.         0.         0.         0.005      0.01666667 0.
  0.         0.97666667 0.00166667 0.        ]
 [0.00601202 0.         0.         0.01803607 0.         0.00200401
  0.         0.         0.9739479  0.        ]
 [0.00666667 0.02       0.00833333 0.00166667 0.         0.19666667
  0.         0.         0.00166667 0.765     ]]
[2023-08-23 11:32:04,232 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 11:32:04,233 INFO] 38912 iteration, USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3595, train/total_loss: 0.3597, train/util_ratio: 1.0000, train/run_time: 0.5302, eval/loss: 0.6599, eval/top-1-acc: 0.8707, eval/balanced_acc: 0.8720, eval/precision: 0.8795, eval/recall: 0.8720, eval/F1: 0.8689, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9111, at 30720 iters
[2023-08-23 11:47:11,448 INFO] 39168 iteration USE_EMA: False, train/sup_loss: 0.0016, train/unsup_loss: 0.0271, train/total_loss: 0.0286, train/util_ratio: 1.0000, train/run_time: 0.5374, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 11:49:34,086 INFO] 39424 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.0025, train/total_loss: 0.0033, train/util_ratio: 1.0000, train/run_time: 0.5356, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 11:51:56,157 INFO] 39680 iteration USE_EMA: False, train/sup_loss: 0.0019, train/unsup_loss: 0.4155, train/total_loss: 0.4174, train/util_ratio: 0.8750, train/run_time: 0.5419, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-23 11:54:18,467 INFO] 39936 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.4266, train/total_loss: 0.4270, train/util_ratio: 1.0000, train/run_time: 0.4780, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-23 11:57:23,509 INFO] 40192 iteration USE_EMA: False, train/sup_loss: 0.0103, train/unsup_loss: 0.0399, train/total_loss: 0.0502, train/util_ratio: 1.0000, train/run_time: 0.5619, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 11:59:44,947 INFO] 40448 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.1588, train/total_loss: 0.1596, train/util_ratio: 1.0000, train/run_time: 0.5458, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 12:02:07,753 INFO] 40704 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.0528, train/total_loss: 0.0538, train/util_ratio: 0.8750, train/run_time: 0.5640, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-23 12:04:30,351 INFO] validating...
[2023-08-23 12:04:54,941 INFO] confusion matrix:
[[0.95666667 0.00166667 0.00333333 0.         0.         0.00333333
  0.025      0.         0.01       0.        ]
 [0.         0.93833333 0.00333333 0.         0.         0.05666667
  0.         0.00166667 0.         0.        ]
 [0.00166667 0.01       0.77166667 0.01166667 0.         0.085
  0.         0.02833333 0.09166667 0.        ]
 [0.002      0.         0.         0.986      0.         0.
  0.         0.002      0.01       0.        ]
 [0.         0.         0.         0.01       0.974      0.
  0.         0.016      0.         0.        ]
 [0.0225     0.015      0.005      0.015      0.         0.91
  0.0225     0.         0.01       0.        ]
 [0.006      0.         0.17       0.012      0.         0.004
  0.802      0.006      0.         0.        ]
 [0.         0.         0.         0.005      0.         0.
  0.         0.99333333 0.00166667 0.        ]
 [0.00400802 0.         0.         0.01002004 0.         0.
  0.         0.         0.98597194 0.        ]
 [0.005      0.02       0.00166667 0.00166667 0.         0.
  0.         0.         0.01333333 0.95833333]]
[2023-08-23 12:04:55,687 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 12:04:56,726 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 12:04:56,727 INFO] 40960 iteration, USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.0530, train/total_loss: 0.0541, train/util_ratio: 1.0000, train/run_time: 0.5370, eval/loss: 0.3143, eval/top-1-acc: 0.9276, eval/balanced_acc: 0.9276, eval/precision: 0.9258, eval/recall: 0.9276, eval/F1: 0.9251, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9276, at 40960 iters
[2023-08-23 12:07:59,974 INFO] 41216 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.0373, train/total_loss: 0.0382, train/util_ratio: 1.0000, train/run_time: 0.5420, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 12:10:21,883 INFO] 41472 iteration USE_EMA: False, train/sup_loss: 0.0021, train/unsup_loss: 0.0915, train/total_loss: 0.0936, train/util_ratio: 1.0000, train/run_time: 0.4990, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 12:12:43,768 INFO] 41728 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0181, train/total_loss: 0.0183, train/util_ratio: 1.0000, train/run_time: 0.5317, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 12:15:05,849 INFO] 41984 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.2453, train/total_loss: 0.2456, train/util_ratio: 0.8750, train/run_time: 0.5441, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-23 12:18:06,736 INFO] 42240 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.0252, train/total_loss: 0.0255, train/util_ratio: 1.0000, train/run_time: 0.5362, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 12:20:26,431 INFO] 42496 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.0259, train/total_loss: 0.0268, train/util_ratio: 0.8750, train/run_time: 0.5351, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 12:22:46,025 INFO] 42752 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0190, train/total_loss: 0.0192, train/util_ratio: 1.0000, train/run_time: 0.4912, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-23 12:25:05,608 INFO] validating...
[2023-08-23 12:25:30,020 INFO] confusion matrix:
[[0.92166667 0.         0.00166667 0.         0.         0.005
  0.06666667 0.         0.005      0.        ]
 [0.         0.875      0.00333333 0.         0.         0.11666667
  0.         0.005      0.         0.        ]
 [0.         0.00333333 0.70166667 0.00166667 0.         0.11833333
  0.01       0.015      0.15       0.        ]
 [0.         0.         0.002      0.982      0.         0.
  0.         0.002      0.014      0.        ]
 [0.         0.         0.         0.         0.988      0.
  0.006      0.006      0.         0.        ]
 [0.0075     0.         0.0025     0.015      0.         0.94
  0.035      0.         0.         0.        ]
 [0.004      0.         0.082      0.002      0.         0.004
  0.908      0.         0.         0.        ]
 [0.         0.         0.         0.00666667 0.         0.
  0.         0.99166667 0.00166667 0.        ]
 [0.00200401 0.         0.         0.00400802 0.         0.
  0.         0.         0.99398798 0.        ]
 [0.02       0.015      0.01166667 0.00166667 0.         0.00666667
  0.         0.         0.00833333 0.93666667]]
[2023-08-23 12:25:30,859 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 12:25:30,860 INFO] 43008 iteration, USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.1604, train/total_loss: 0.1619, train/util_ratio: 1.0000, train/run_time: 0.4949, eval/loss: 0.3645, eval/top-1-acc: 0.9200, eval/balanced_acc: 0.9239, eval/precision: 0.9197, eval/recall: 0.9239, eval/F1: 0.9179, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9276, at 40960 iters
[2023-08-23 12:28:34,250 INFO] 43264 iteration USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.1843, train/total_loss: 0.1856, train/util_ratio: 1.0000, train/run_time: 0.4947, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-23 12:30:54,841 INFO] 43520 iteration USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.2795, train/total_loss: 0.2810, train/util_ratio: 1.0000, train/run_time: 0.5127, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 12:33:15,485 INFO] 43776 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.7312, train/total_loss: 0.7316, train/util_ratio: 1.0000, train/run_time: 0.5415, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 12:35:35,978 INFO] 44032 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.1878, train/total_loss: 0.1883, train/util_ratio: 1.0000, train/run_time: 0.4795, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 12:38:38,931 INFO] 44288 iteration USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.0050, train/total_loss: 0.0063, train/util_ratio: 1.0000, train/run_time: 0.5404, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 12:41:00,334 INFO] 44544 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.2090, train/total_loss: 0.2093, train/util_ratio: 1.0000, train/run_time: 0.5607, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 12:43:20,800 INFO] 44800 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.6971, train/total_loss: 0.6976, train/util_ratio: 0.8750, train/run_time: 0.5352, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 12:45:40,674 INFO] validating...
[2023-08-23 12:46:05,182 INFO] confusion matrix:
[[0.95333333 0.         0.         0.         0.         0.00333333
  0.04166667 0.         0.00166667 0.        ]
 [0.         0.88833333 0.00166667 0.         0.         0.1
  0.         0.01       0.         0.        ]
 [0.         0.00833333 0.78       0.00666667 0.         0.08666667
  0.00666667 0.04666667 0.065      0.        ]
 [0.         0.         0.         0.98       0.002      0.
  0.         0.002      0.016      0.        ]
 [0.         0.         0.002      0.002      0.974      0.
  0.004      0.018      0.         0.        ]
 [0.01       0.         0.005      0.015      0.         0.9375
  0.03       0.         0.0025     0.        ]
 [0.01       0.         0.156      0.004      0.         0.002
  0.828      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.         0.
  0.         0.99833333 0.         0.        ]
 [0.00601202 0.00200401 0.00200401 0.00200401 0.         0.
  0.00200401 0.         0.98396794 0.00200401]
 [0.00666667 0.04666667 0.00666667 0.00166667 0.         0.00333333
  0.         0.00166667 0.00333333 0.93      ]]
[2023-08-23 12:46:06,054 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 12:46:06,055 INFO] 45056 iteration, USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.0616, train/total_loss: 0.0625, train/util_ratio: 1.0000, train/run_time: 0.5391, eval/loss: 0.3497, eval/top-1-acc: 0.9237, eval/balanced_acc: 0.9253, eval/precision: 0.9223, eval/recall: 0.9253, eval/F1: 0.9221, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9276, at 40960 iters
[2023-08-23 12:49:08,686 INFO] 45312 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.3208, train/total_loss: 0.3212, train/util_ratio: 0.8750, train/run_time: 0.5050, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 12:51:28,414 INFO] 45568 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.0671, train/total_loss: 0.0677, train/util_ratio: 0.8750, train/run_time: 0.5413, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 12:53:49,498 INFO] 45824 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.0056, train/total_loss: 0.0065, train/util_ratio: 0.8750, train/run_time: 0.5386, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 12:56:10,547 INFO] 46080 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.0213, train/total_loss: 0.0221, train/util_ratio: 1.0000, train/run_time: 0.5398, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 12:59:15,005 INFO] 46336 iteration USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.1821, train/total_loss: 0.1836, train/util_ratio: 1.0000, train/run_time: 0.5415, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 13:01:35,776 INFO] 46592 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.4584, train/total_loss: 0.4591, train/util_ratio: 0.8750, train/run_time: 0.4796, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 13:03:55,746 INFO] 46848 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.8044, train/total_loss: 0.8050, train/util_ratio: 1.0000, train/run_time: 0.5348, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-23 13:06:17,523 INFO] validating...
[2023-08-23 13:06:41,868 INFO] confusion matrix:
[[0.86166667 0.00166667 0.00333333 0.00166667 0.         0.00166667
  0.12166667 0.         0.00666667 0.00166667]
 [0.         0.90666667 0.00333333 0.00166667 0.         0.08333333
  0.         0.005      0.         0.        ]
 [0.         0.01333333 0.81666667 0.00333333 0.         0.04833333
  0.00666667 0.02333333 0.08833333 0.        ]
 [0.         0.         0.002      0.992      0.002      0.
  0.         0.002      0.002      0.        ]
 [0.         0.         0.002      0.004      0.98       0.
  0.004      0.01       0.         0.        ]
 [0.0125     0.0075     0.005      0.0175     0.         0.9
  0.0525     0.         0.005      0.        ]
 [0.002      0.         0.208      0.004      0.         0.
  0.786      0.         0.         0.        ]
 [0.         0.         0.         0.01       0.         0.
  0.         0.98833333 0.00166667 0.        ]
 [0.00400802 0.         0.00200401 0.01202405 0.         0.
  0.00200401 0.         0.97995992 0.        ]
 [0.01333333 0.01166667 0.01666667 0.00166667 0.         0.00666667
  0.         0.         0.00166667 0.94833333]]
[2023-08-23 13:06:42,664 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 13:06:42,666 INFO] 47104 iteration, USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.2558, train/total_loss: 0.2566, train/util_ratio: 0.8750, train/run_time: 0.5331, eval/loss: 0.4392, eval/top-1-acc: 0.9152, eval/balanced_acc: 0.9160, eval/precision: 0.9135, eval/recall: 0.9160, eval/F1: 0.9137, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9276, at 40960 iters
[2023-08-23 13:09:46,503 INFO] 47360 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1041, train/total_loss: 0.1042, train/util_ratio: 1.0000, train/run_time: 0.4873, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 13:12:07,120 INFO] 47616 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.0104, train/total_loss: 0.0112, train/util_ratio: 1.0000, train/run_time: 0.5531, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 13:14:26,733 INFO] 47872 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.1903, train/total_loss: 0.1908, train/util_ratio: 0.8750, train/run_time: 0.4952, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 13:16:46,981 INFO] 48128 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0531, train/total_loss: 0.0532, train/util_ratio: 0.7500, train/run_time: 0.5322, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 13:19:50,291 INFO] 48384 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.3049, train/total_loss: 0.3053, train/util_ratio: 1.0000, train/run_time: 0.5336, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 13:22:10,929 INFO] 48640 iteration USE_EMA: False, train/sup_loss: 0.0014, train/unsup_loss: 0.3271, train/total_loss: 0.3285, train/util_ratio: 1.0000, train/run_time: 0.5981, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 13:24:29,788 INFO] 48896 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0031, train/total_loss: 0.0033, train/util_ratio: 1.0000, train/run_time: 0.5825, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 13:26:49,575 INFO] validating...
[2023-08-23 13:27:13,907 INFO] confusion matrix:
[[0.90166667 0.00666667 0.00333333 0.         0.         0.00666667
  0.06666667 0.         0.015      0.        ]
 [0.         0.91833333 0.00166667 0.         0.         0.06833333
  0.         0.01166667 0.         0.        ]
 [0.         0.015      0.74166667 0.00333333 0.         0.03833333
  0.00666667 0.04       0.155      0.        ]
 [0.         0.         0.         0.976      0.         0.
  0.         0.002      0.022      0.        ]
 [0.         0.         0.         0.006      0.994      0.
  0.         0.         0.         0.        ]
 [0.005      0.0175     0.005      0.0075     0.         0.925
  0.0375     0.         0.0025     0.        ]
 [0.004      0.002      0.16       0.002      0.         0.
  0.83       0.         0.002      0.        ]
 [0.         0.         0.         0.00333333 0.01       0.
  0.         0.985      0.00166667 0.        ]
 [0.00400802 0.         0.         0.         0.         0.
  0.         0.         0.99398798 0.00200401]
 [0.00666667 0.12166667 0.01       0.00166667 0.         0.00833333
  0.         0.00333333 0.005      0.84333333]]
[2023-08-23 13:27:14,646 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 13:27:14,647 INFO] 49152 iteration, USE_EMA: False, train/sup_loss: 0.0035, train/unsup_loss: 0.0755, train/total_loss: 0.0789, train/util_ratio: 1.0000, train/run_time: 0.5361, eval/loss: 0.4151, eval/top-1-acc: 0.9076, eval/balanced_acc: 0.9109, eval/precision: 0.9091, eval/recall: 0.9109, eval/F1: 0.9075, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9276, at 40960 iters
[2023-08-23 13:30:17,272 INFO] 49408 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2710, train/total_loss: 0.2712, train/util_ratio: 1.0000, train/run_time: 0.4794, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 13:32:38,764 INFO] 49664 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1154, train/total_loss: 0.1155, train/util_ratio: 0.8750, train/run_time: 0.5442, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 13:35:00,841 INFO] 49920 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.0203, train/total_loss: 0.0212, train/util_ratio: 0.8750, train/run_time: 0.4868, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 13:37:22,335 INFO] 50176 iteration USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.1737, train/total_loss: 0.1752, train/util_ratio: 1.0000, train/run_time: 0.5372, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 13:40:28,284 INFO] 50432 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1294, train/total_loss: 0.1296, train/util_ratio: 1.0000, train/run_time: 0.4802, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 13:42:48,138 INFO] 50688 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.0043, train/total_loss: 0.0049, train/util_ratio: 1.0000, train/run_time: 0.5425, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 13:45:10,556 INFO] 50944 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.0138, train/total_loss: 0.0148, train/util_ratio: 1.0000, train/run_time: 0.5116, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 13:47:32,533 INFO] validating...
[2023-08-23 13:47:56,857 INFO] confusion matrix:
[[0.91333333 0.00166667 0.         0.         0.         0.01833333
  0.055      0.         0.01       0.00166667]
 [0.         0.82666667 0.00333333 0.         0.         0.16666667
  0.         0.00166667 0.00166667 0.        ]
 [0.         0.00833333 0.67       0.00333333 0.         0.10833333
  0.02666667 0.025      0.15833333 0.        ]
 [0.         0.         0.         0.982      0.002      0.
  0.         0.002      0.014      0.        ]
 [0.         0.         0.         0.006      0.99       0.
  0.004      0.         0.         0.        ]
 [0.005      0.         0.0025     0.0075     0.         0.9675
  0.0125     0.         0.005      0.        ]
 [0.01       0.         0.036      0.004      0.         0.002
  0.948      0.         0.         0.        ]
 [0.         0.         0.         0.005      0.00666667 0.
  0.         0.98666667 0.00166667 0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.00200401]
 [0.005      0.00333333 0.01       0.00166667 0.         0.005
  0.         0.         0.         0.975     ]]
[2023-08-23 13:47:57,785 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 13:47:57,786 INFO] 51200 iteration, USE_EMA: False, train/sup_loss: 0.0024, train/unsup_loss: 0.1965, train/total_loss: 0.1989, train/util_ratio: 1.0000, train/run_time: 0.5431, eval/loss: 0.4217, eval/top-1-acc: 0.9194, eval/balanced_acc: 0.9249, eval/precision: 0.9219, eval/recall: 0.9249, eval/F1: 0.9170, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9276, at 40960 iters
[2023-08-23 13:51:02,282 INFO] 51456 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.0075, train/total_loss: 0.0083, train/util_ratio: 1.0000, train/run_time: 0.4868, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 13:53:23,702 INFO] 51712 iteration USE_EMA: False, train/sup_loss: 0.0027, train/unsup_loss: 0.0039, train/total_loss: 0.0066, train/util_ratio: 1.0000, train/run_time: 0.5428, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 13:55:45,621 INFO] 51968 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.0355, train/total_loss: 0.0358, train/util_ratio: 1.0000, train/run_time: 0.4930, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 13:58:08,377 INFO] 52224 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0057, train/total_loss: 0.0058, train/util_ratio: 0.8750, train/run_time: 0.5359, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 14:01:13,506 INFO] 52480 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1094, train/total_loss: 0.1095, train/util_ratio: 1.0000, train/run_time: 0.4973, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 14:03:35,975 INFO] 52736 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4393, train/total_loss: 0.4395, train/util_ratio: 1.0000, train/run_time: 0.4795, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 14:05:58,184 INFO] 52992 iteration USE_EMA: False, train/sup_loss: 0.0048, train/unsup_loss: 0.0093, train/total_loss: 0.0141, train/util_ratio: 1.0000, train/run_time: 0.5418, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 14:08:19,651 INFO] validating...
[2023-08-23 14:08:43,909 INFO] confusion matrix:
[[0.92166667 0.00166667 0.         0.         0.         0.005
  0.05666667 0.         0.01333333 0.00166667]
 [0.         0.90166667 0.00166667 0.         0.         0.08833333
  0.         0.00166667 0.005      0.00166667]
 [0.         0.00666667 0.64666667 0.00166667 0.         0.05
  0.00833333 0.00833333 0.27833333 0.        ]
 [0.002      0.         0.         0.964      0.006      0.
  0.         0.002      0.026      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0025     0.0025     0.005      0.005      0.         0.97
  0.01       0.         0.005      0.        ]
 [0.014      0.         0.088      0.006      0.         0.002
  0.888      0.         0.002      0.        ]
 [0.         0.         0.         0.00166667 0.01       0.
  0.         0.985      0.00333333 0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.         0.         0.99198397 0.00200401]
 [0.005      0.00333333 0.005      0.00166667 0.         0.00166667
  0.         0.         0.00333333 0.98      ]]
[2023-08-23 14:08:44,621 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 14:08:44,622 INFO] 53248 iteration, USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.5964, train/total_loss: 0.5971, train/util_ratio: 1.0000, train/run_time: 0.4787, eval/loss: 0.4666, eval/top-1-acc: 0.9202, eval/balanced_acc: 0.9245, eval/precision: 0.9231, eval/recall: 0.9245, eval/F1: 0.9187, lr: 0.0000, train/prefecth_time: 0.0023 BEST_EVAL_ACC: 0.9276, at 40960 iters
[2023-08-23 14:11:48,360 INFO] 53504 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0111, train/total_loss: 0.0112, train/util_ratio: 1.0000, train/run_time: 0.5361, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 14:14:10,326 INFO] 53760 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1309, train/total_loss: 0.1311, train/util_ratio: 0.8750, train/run_time: 0.4895, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 14:16:32,337 INFO] 54016 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.1731, train/total_loss: 0.1737, train/util_ratio: 1.0000, train/run_time: 0.5419, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 14:18:53,503 INFO] 54272 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.2510, train/total_loss: 0.2515, train/util_ratio: 1.0000, train/run_time: 0.5293, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 14:21:57,499 INFO] 54528 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.0141, train/total_loss: 0.0146, train/util_ratio: 0.8750, train/run_time: 0.5623, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 14:24:19,763 INFO] 54784 iteration USE_EMA: False, train/sup_loss: 0.0084, train/unsup_loss: 0.0659, train/total_loss: 0.0743, train/util_ratio: 0.8750, train/run_time: 0.5396, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 14:26:44,127 INFO] 55040 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.0127, train/total_loss: 0.0132, train/util_ratio: 0.8750, train/run_time: 0.5359, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 14:29:06,065 INFO] validating...
[2023-08-23 14:29:30,362 INFO] confusion matrix:
[[0.93333333 0.00166667 0.00166667 0.         0.         0.005
  0.04833333 0.         0.00833333 0.00166667]
 [0.         0.88833333 0.00333333 0.         0.         0.10666667
  0.         0.00166667 0.         0.        ]
 [0.         0.00166667 0.78666667 0.00166667 0.         0.05333333
  0.02       0.005      0.13166667 0.        ]
 [0.         0.         0.         0.986      0.         0.
  0.         0.         0.014      0.        ]
 [0.         0.         0.         0.01       0.988      0.
  0.         0.         0.002      0.        ]
 [0.01       0.         0.0025     0.0075     0.         0.9425
  0.035      0.         0.0025     0.        ]
 [0.008      0.         0.038      0.004      0.         0.
  0.948      0.         0.002      0.        ]
 [0.         0.         0.         0.00666667 0.00833333 0.
  0.         0.98333333 0.00166667 0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.00200401 0.         0.98997996 0.00200401]
 [0.005      0.005      0.00166667 0.         0.         0.00166667
  0.         0.         0.005      0.98166667]]
[2023-08-23 14:29:31,194 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 14:29:32,249 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 14:29:32,250 INFO] 55296 iteration, USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 1.2787, train/total_loss: 1.2792, train/util_ratio: 1.0000, train/run_time: 0.5432, eval/loss: 0.3097, eval/top-1-acc: 0.9402, eval/balanced_acc: 0.9428, eval/precision: 0.9387, eval/recall: 0.9428, eval/F1: 0.9382, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9402, at 55296 iters
[2023-08-23 14:32:33,680 INFO] 55552 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.1589, train/total_loss: 0.1597, train/util_ratio: 1.0000, train/run_time: 0.5305, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-23 14:34:54,930 INFO] 55808 iteration USE_EMA: False, train/sup_loss: 0.0035, train/unsup_loss: 0.2451, train/total_loss: 0.2486, train/util_ratio: 1.0000, train/run_time: 0.4930, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 14:37:16,637 INFO] 56064 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4260, train/total_loss: 0.4262, train/util_ratio: 1.0000, train/run_time: 0.5342, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 14:39:38,152 INFO] 56320 iteration USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.0026, train/total_loss: 0.0037, train/util_ratio: 0.7500, train/run_time: 0.5407, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 14:42:42,814 INFO] 56576 iteration USE_EMA: False, train/sup_loss: 0.0014, train/unsup_loss: 0.0004, train/total_loss: 0.0018, train/util_ratio: 0.8750, train/run_time: 0.5391, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 14:45:04,985 INFO] 56832 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.5165, train/total_loss: 0.5168, train/util_ratio: 1.0000, train/run_time: 0.4799, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 14:47:26,568 INFO] 57088 iteration USE_EMA: False, train/sup_loss: 0.0023, train/unsup_loss: 0.0456, train/total_loss: 0.0479, train/util_ratio: 1.0000, train/run_time: 0.5421, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 14:49:48,002 INFO] validating...
[2023-08-23 14:50:12,324 INFO] confusion matrix:
[[0.89333333 0.00166667 0.00166667 0.         0.         0.00166667
  0.08833333 0.         0.01       0.00333333]
 [0.         0.90833333 0.00333333 0.         0.         0.085
  0.         0.00333333 0.         0.        ]
 [0.00166667 0.00833333 0.82666667 0.00166667 0.         0.025
  0.015      0.01       0.11166667 0.        ]
 [0.         0.         0.         0.986      0.002      0.
  0.         0.002      0.01       0.        ]
 [0.         0.         0.         0.002      0.99       0.
  0.006      0.002      0.         0.        ]
 [0.02       0.0075     0.005      0.0175     0.         0.8875
  0.055      0.         0.0075     0.        ]
 [0.002      0.         0.038      0.006      0.         0.
  0.954      0.         0.         0.        ]
 [0.         0.         0.         0.005      0.01       0.
  0.         0.985      0.         0.        ]
 [0.00400802 0.         0.00200401 0.00400802 0.         0.
  0.00200401 0.         0.98597194 0.00200401]
 [0.01       0.01333333 0.01       0.         0.         0.00166667
  0.         0.         0.00666667 0.95833333]]
[2023-08-23 14:50:13,069 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 14:50:13,070 INFO] 57344 iteration, USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1345, train/total_loss: 0.1348, train/util_ratio: 1.0000, train/run_time: 0.5395, eval/loss: 0.2744, eval/top-1-acc: 0.9363, eval/balanced_acc: 0.9375, eval/precision: 0.9346, eval/recall: 0.9375, eval/F1: 0.9345, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.9402, at 55296 iters
[2023-08-23 14:53:15,900 INFO] 57600 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1432, train/total_loss: 0.1433, train/util_ratio: 1.0000, train/run_time: 0.5382, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 14:55:36,964 INFO] 57856 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.0064, train/total_loss: 0.0068, train/util_ratio: 0.8750, train/run_time: 0.5420, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 14:57:58,588 INFO] 58112 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.8373, train/total_loss: 0.8379, train/util_ratio: 1.0000, train/run_time: 0.5315, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 15:00:20,957 INFO] 58368 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.0405, train/total_loss: 0.0411, train/util_ratio: 0.7500, train/run_time: 0.4768, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 15:03:26,198 INFO] 58624 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0066, train/total_loss: 0.0068, train/util_ratio: 1.0000, train/run_time: 0.5667, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 15:05:47,090 INFO] 58880 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0083, train/total_loss: 0.0085, train/util_ratio: 0.8750, train/run_time: 0.4983, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-23 15:08:05,435 INFO] 59136 iteration USE_EMA: False, train/sup_loss: 0.0026, train/unsup_loss: 0.0009, train/total_loss: 0.0035, train/util_ratio: 1.0000, train/run_time: 0.5430, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 15:10:25,126 INFO] validating...
[2023-08-23 15:10:49,823 INFO] confusion matrix:
[[0.94666667 0.00166667 0.00333333 0.         0.         0.00833333
  0.03166667 0.         0.00833333 0.        ]
 [0.         0.875      0.00333333 0.         0.         0.12
  0.         0.00166667 0.         0.        ]
 [0.         0.015      0.79166667 0.00666667 0.         0.07833333
  0.005      0.005      0.09833333 0.        ]
 [0.002      0.         0.         0.996      0.         0.
  0.         0.         0.002      0.        ]
 [0.         0.         0.         0.01       0.988      0.
  0.002      0.         0.         0.        ]
 [0.0075     0.         0.005      0.0125     0.         0.9625
  0.0125     0.         0.         0.        ]
 [0.014      0.         0.066      0.008      0.         0.002
  0.908      0.         0.002      0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00601202 0.         0.         0.01803607 0.         0.
  0.         0.         0.9739479  0.00200401]
 [0.00833333 0.01333333 0.015      0.         0.         0.01
  0.         0.         0.00666667 0.94666667]]
[2023-08-23 15:10:50,919 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 15:10:50,924 INFO] 59392 iteration, USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1144, train/total_loss: 0.1147, train/util_ratio: 1.0000, train/run_time: 0.5351, eval/loss: 0.3429, eval/top-1-acc: 0.9341, eval/balanced_acc: 0.9372, eval/precision: 0.9325, eval/recall: 0.9372, eval/F1: 0.9324, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9402, at 55296 iters
[2023-08-23 15:13:53,213 INFO] 59648 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.1242, train/total_loss: 0.1246, train/util_ratio: 1.0000, train/run_time: 0.5560, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 15:16:14,613 INFO] 59904 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0537, train/total_loss: 0.0539, train/util_ratio: 1.0000, train/run_time: 0.5373, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 15:18:34,927 INFO] 60160 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1453, train/total_loss: 0.1455, train/util_ratio: 1.0000, train/run_time: 0.5391, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 15:20:58,071 INFO] 60416 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0565, train/total_loss: 0.0567, train/util_ratio: 1.0000, train/run_time: 0.5343, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 15:24:01,609 INFO] 60672 iteration USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.0187, train/total_loss: 0.0200, train/util_ratio: 1.0000, train/run_time: 0.5449, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-23 15:26:22,790 INFO] 60928 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0312, train/total_loss: 0.0312, train/util_ratio: 1.0000, train/run_time: 0.5434, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 15:28:43,234 INFO] 61184 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1036, train/total_loss: 0.1036, train/util_ratio: 1.0000, train/run_time: 0.5990, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 15:31:01,991 INFO] validating...
[2023-08-23 15:31:26,368 INFO] confusion matrix:
[[0.955      0.00166667 0.00333333 0.         0.         0.005
  0.03       0.         0.005      0.        ]
 [0.         0.895      0.00333333 0.         0.         0.09833333
  0.         0.00333333 0.         0.        ]
 [0.         0.005      0.82666667 0.00333333 0.         0.04666667
  0.00833333 0.00833333 0.10166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.004      0.004      0.        ]
 [0.         0.         0.         0.002      0.982      0.
  0.004      0.012      0.         0.        ]
 [0.0125     0.0025     0.005      0.015      0.         0.935
  0.0275     0.         0.0025     0.        ]
 [0.008      0.         0.074      0.002      0.         0.
  0.912      0.004      0.         0.        ]
 [0.         0.         0.         0.00166667 0.00333333 0.
  0.         0.995      0.         0.        ]
 [0.00400802 0.         0.00200401 0.0240481  0.         0.
  0.00200401 0.         0.96793587 0.        ]
 [0.015      0.025      0.00833333 0.00166667 0.         0.00166667
  0.         0.         0.01333333 0.935     ]]
[2023-08-23 15:31:27,290 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 15:31:27,292 INFO] 61440 iteration, USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0289, train/total_loss: 0.0290, train/util_ratio: 1.0000, train/run_time: 0.4786, eval/loss: 0.2879, eval/top-1-acc: 0.9380, eval/balanced_acc: 0.9396, eval/precision: 0.9357, eval/recall: 0.9396, eval/F1: 0.9364, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9402, at 55296 iters
[2023-08-23 15:34:30,610 INFO] 61696 iteration USE_EMA: False, train/sup_loss: 0.0013, train/unsup_loss: 0.1731, train/total_loss: 0.1744, train/util_ratio: 1.0000, train/run_time: 0.5457, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 15:36:54,112 INFO] 61952 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4219, train/total_loss: 0.4221, train/util_ratio: 0.8750, train/run_time: 0.5339, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 15:39:14,375 INFO] 62208 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1700, train/total_loss: 0.1701, train/util_ratio: 1.0000, train/run_time: 0.5430, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 15:41:36,118 INFO] 62464 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3249, train/total_loss: 0.3250, train/util_ratio: 1.0000, train/run_time: 0.5411, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 15:44:39,373 INFO] 62720 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.1275, train/total_loss: 0.1281, train/util_ratio: 1.0000, train/run_time: 0.5357, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 15:47:02,634 INFO] 62976 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.1615, train/total_loss: 0.1627, train/util_ratio: 1.0000, train/run_time: 0.5466, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 15:49:25,925 INFO] 63232 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3036, train/total_loss: 0.3036, train/util_ratio: 1.0000, train/run_time: 0.5421, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 15:51:48,163 INFO] validating...
[2023-08-23 15:52:12,421 INFO] confusion matrix:
[[0.85333333 0.00166667 0.00333333 0.         0.         0.005
  0.13333333 0.         0.00333333 0.        ]
 [0.         0.885      0.005      0.00166667 0.         0.10333333
  0.         0.005      0.         0.        ]
 [0.         0.00166667 0.82833333 0.005      0.         0.04
  0.05333333 0.01166667 0.06       0.        ]
 [0.002      0.         0.         0.984      0.002      0.
  0.002      0.002      0.008      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0175     0.         0.         0.01       0.         0.92
  0.05       0.         0.0025     0.        ]
 [0.         0.         0.026      0.         0.002      0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97666667 0.00166667 0.        ]
 [0.00400802 0.         0.         0.01002004 0.         0.
  0.00200401 0.         0.98196393 0.00200401]
 [0.01333333 0.01       0.01       0.         0.         0.00166667
  0.         0.00166667 0.00333333 0.96      ]]
[2023-08-23 15:52:13,139 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 15:52:13,140 INFO] 63488 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.5589, train/total_loss: 0.5590, train/util_ratio: 1.0000, train/run_time: 0.5412, eval/loss: 0.3248, eval/top-1-acc: 0.9328, eval/balanced_acc: 0.9357, eval/precision: 0.9327, eval/recall: 0.9357, eval/F1: 0.9315, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9402, at 55296 iters
[2023-08-23 15:55:15,530 INFO] 63744 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0968, train/total_loss: 0.0970, train/util_ratio: 0.8750, train/run_time: 0.5453, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 15:57:37,761 INFO] 64000 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1738, train/total_loss: 0.1740, train/util_ratio: 0.8750, train/run_time: 0.5564, lr: 0.0000, train/prefecth_time: 0.0045 
[2023-08-23 15:59:58,468 INFO] 64256 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2600, train/total_loss: 0.2601, train/util_ratio: 1.0000, train/run_time: 0.5392, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-23 16:02:21,076 INFO] 64512 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.3284, train/total_loss: 0.3287, train/util_ratio: 1.0000, train/run_time: 0.5367, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 16:05:25,183 INFO] 64768 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1053, train/total_loss: 0.1055, train/util_ratio: 1.0000, train/run_time: 0.5073, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 16:07:46,238 INFO] 65024 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0067, train/total_loss: 0.0070, train/util_ratio: 0.8750, train/run_time: 0.5371, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 16:10:05,838 INFO] 65280 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 1.4097, train/total_loss: 1.4100, train/util_ratio: 1.0000, train/run_time: 0.4814, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 16:12:26,590 INFO] validating...
[2023-08-23 16:12:51,077 INFO] confusion matrix:
[[0.92333333 0.00166667 0.00333333 0.         0.         0.00333333
  0.06666667 0.         0.00166667 0.        ]
 [0.         0.855      0.00666667 0.         0.         0.13666667
  0.         0.00166667 0.         0.        ]
 [0.         0.01833333 0.845      0.00833333 0.         0.09166667
  0.00666667 0.005      0.025      0.        ]
 [0.         0.         0.         0.988      0.002      0.
  0.         0.004      0.006      0.        ]
 [0.         0.         0.         0.002      0.99       0.
  0.006      0.002      0.         0.        ]
 [0.01       0.         0.005      0.0125     0.         0.9325
  0.0375     0.         0.0025     0.        ]
 [0.004      0.         0.068      0.004      0.002      0.
  0.922      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.005      0.
  0.         0.99166667 0.         0.        ]
 [0.00400802 0.         0.         0.01402806 0.         0.
  0.00200401 0.         0.97795591 0.00200401]
 [0.00833333 0.005      0.00833333 0.         0.         0.00333333
  0.         0.         0.         0.975     ]]
[2023-08-23 16:12:52,120 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 16:12:52,121 INFO] 65536 iteration, USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0313, train/total_loss: 0.0315, train/util_ratio: 1.0000, train/run_time: 0.4791, eval/loss: 0.3132, eval/top-1-acc: 0.9381, eval/balanced_acc: 0.9400, eval/precision: 0.9364, eval/recall: 0.9400, eval/F1: 0.9362, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9402, at 55296 iters
[2023-08-23 16:15:57,110 INFO] 65792 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2897, train/total_loss: 0.2899, train/util_ratio: 0.8750, train/run_time: 0.5007, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 16:18:18,417 INFO] 66048 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.0559, train/total_loss: 0.0565, train/util_ratio: 0.8750, train/run_time: 0.4974, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 16:20:41,009 INFO] 66304 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2628, train/total_loss: 0.2630, train/util_ratio: 0.8750, train/run_time: 0.5376, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 16:23:03,451 INFO] 66560 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1508, train/total_loss: 0.1509, train/util_ratio: 1.0000, train/run_time: 0.4765, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 16:26:08,920 INFO] 66816 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0594, train/total_loss: 0.0594, train/util_ratio: 0.7500, train/run_time: 0.5386, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 16:28:31,742 INFO] 67072 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0251, train/total_loss: 0.0252, train/util_ratio: 1.0000, train/run_time: 0.5379, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 16:30:54,566 INFO] 67328 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2196, train/total_loss: 0.2197, train/util_ratio: 1.0000, train/run_time: 0.5675, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 16:33:17,256 INFO] validating...
[2023-08-23 16:33:41,500 INFO] confusion matrix:
[[0.95       0.00166667 0.00333333 0.         0.         0.00333333
  0.035      0.         0.00666667 0.        ]
 [0.         0.92       0.00833333 0.         0.         0.07166667
  0.         0.         0.         0.        ]
 [0.         0.02166667 0.82833333 0.00833333 0.         0.07666667
  0.01166667 0.00333333 0.05       0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.004      0.992      0.
  0.004      0.         0.         0.        ]
 [0.0125     0.0175     0.005      0.0125     0.         0.9225
  0.0275     0.         0.0025     0.        ]
 [0.006      0.         0.046      0.006      0.         0.
  0.942      0.         0.         0.        ]
 [0.         0.         0.         0.00833333 0.01166667 0.
  0.         0.97833333 0.00166667 0.        ]
 [0.00400802 0.         0.         0.00601202 0.         0.
  0.00200401 0.         0.98597194 0.00200401]
 [0.00833333 0.02833333 0.00333333 0.00166667 0.         0.
  0.         0.         0.005      0.95333333]]
[2023-08-23 16:33:42,423 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 16:33:43,558 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 16:33:43,561 INFO] 67584 iteration, USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0182, train/total_loss: 0.0184, train/util_ratio: 1.0000, train/run_time: 0.6078, eval/loss: 0.2248, eval/top-1-acc: 0.9450, eval/balanced_acc: 0.9464, eval/precision: 0.9421, eval/recall: 0.9464, eval/F1: 0.9433, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9450, at 67584 iters
[2023-08-23 16:36:46,283 INFO] 67840 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.3754, train/total_loss: 0.3756, train/util_ratio: 1.0000, train/run_time: 0.6090, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 16:39:07,462 INFO] 68096 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.3188, train/total_loss: 0.3197, train/util_ratio: 1.0000, train/run_time: 0.5345, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 16:41:30,357 INFO] 68352 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0316, train/total_loss: 0.0317, train/util_ratio: 1.0000, train/run_time: 0.5008, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-23 16:43:52,744 INFO] 68608 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0772, train/total_loss: 0.0773, train/util_ratio: 0.8750, train/run_time: 0.5394, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-23 16:46:57,143 INFO] 68864 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0132, train/total_loss: 0.0132, train/util_ratio: 1.0000, train/run_time: 0.5331, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-23 16:49:19,561 INFO] 69120 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0890, train/total_loss: 0.0891, train/util_ratio: 1.0000, train/run_time: 0.5406, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 16:51:42,521 INFO] 69376 iteration USE_EMA: False, train/sup_loss: 0.0011, train/unsup_loss: 0.7568, train/total_loss: 0.7579, train/util_ratio: 1.0000, train/run_time: 0.5397, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 16:54:03,643 INFO] validating...
[2023-08-23 16:54:28,167 INFO] confusion matrix:
[[0.87666667 0.00166667 0.005      0.00166667 0.         0.00333333
  0.10666667 0.         0.005      0.        ]
 [0.         0.90333333 0.00666667 0.         0.         0.08666667
  0.         0.00333333 0.         0.        ]
 [0.         0.01       0.93       0.005      0.         0.02666667
  0.00833333 0.00666667 0.01333333 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.008      0.986      0.
  0.006      0.         0.         0.        ]
 [0.0075     0.005      0.005      0.015      0.         0.92
  0.045      0.         0.0025     0.        ]
 [0.002      0.         0.05       0.004      0.         0.
  0.944      0.         0.         0.        ]
 [0.         0.00166667 0.         0.015      0.01666667 0.
  0.00166667 0.965      0.         0.        ]
 [0.00400802 0.         0.00400802 0.02805611 0.         0.
  0.00400802 0.         0.95791583 0.00200401]
 [0.00666667 0.01666667 0.00833333 0.00166667 0.         0.00166667
  0.         0.         0.         0.965     ]]
[2023-08-23 16:54:28,943 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 16:54:28,944 INFO] 69632 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3013, train/total_loss: 0.3014, train/util_ratio: 1.0000, train/run_time: 0.5111, eval/loss: 0.2855, eval/top-1-acc: 0.9433, eval/balanced_acc: 0.9444, eval/precision: 0.9416, eval/recall: 0.9444, eval/F1: 0.9419, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.9450, at 67584 iters
[2023-08-23 16:57:31,009 INFO] 69888 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.1145, train/total_loss: 0.1150, train/util_ratio: 0.8750, train/run_time: 0.5521, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 16:59:54,413 INFO] 70144 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0611, train/total_loss: 0.0613, train/util_ratio: 0.8750, train/run_time: 0.5374, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 17:02:16,070 INFO] 70400 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0102, train/total_loss: 0.0103, train/util_ratio: 1.0000, train/run_time: 0.5419, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 17:04:38,772 INFO] 70656 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.0144, train/total_loss: 0.0149, train/util_ratio: 0.8750, train/run_time: 0.5305, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 17:07:44,116 INFO] 70912 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0153, train/total_loss: 0.0155, train/util_ratio: 1.0000, train/run_time: 0.5284, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 17:10:07,220 INFO] 71168 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2792, train/total_loss: 0.2792, train/util_ratio: 1.0000, train/run_time: 0.5412, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 17:12:30,525 INFO] 71424 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1184, train/total_loss: 0.1185, train/util_ratio: 1.0000, train/run_time: 0.5414, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 17:14:53,789 INFO] validating...
[2023-08-23 17:15:18,143 INFO] confusion matrix:
[[0.925      0.00166667 0.00166667 0.         0.         0.00166667
  0.06833333 0.         0.00166667 0.        ]
 [0.         0.88833333 0.005      0.         0.         0.105
  0.         0.00166667 0.         0.        ]
 [0.         0.01       0.825      0.00166667 0.         0.07833333
  0.07166667 0.00666667 0.00666667 0.        ]
 [0.002      0.         0.         0.984      0.004      0.
  0.002      0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.99       0.
  0.006      0.002      0.         0.        ]
 [0.0275     0.         0.         0.005      0.         0.9325
  0.0325     0.         0.0025     0.        ]
 [0.008      0.         0.022      0.         0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.00666667 0.01333333 0.
  0.00166667 0.97833333 0.         0.        ]
 [0.00400802 0.00200401 0.00200401 0.00801603 0.         0.
  0.00200401 0.         0.97995992 0.00200401]
 [0.00833333 0.02166667 0.015      0.         0.         0.00333333
  0.         0.         0.00166667 0.95      ]]
[2023-08-23 17:15:19,083 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 17:15:19,084 INFO] 71680 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0219, train/total_loss: 0.0220, train/util_ratio: 1.0000, train/run_time: 0.5351, eval/loss: 0.2891, eval/top-1-acc: 0.9398, eval/balanced_acc: 0.9423, eval/precision: 0.9389, eval/recall: 0.9423, eval/F1: 0.9385, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9450, at 67584 iters
[2023-08-23 17:18:21,883 INFO] 71936 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.0032, train/total_loss: 0.0037, train/util_ratio: 1.0000, train/run_time: 0.5245, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 17:20:43,202 INFO] 72192 iteration USE_EMA: False, train/sup_loss: 0.0017, train/unsup_loss: 0.4876, train/total_loss: 0.4893, train/util_ratio: 1.0000, train/run_time: 0.4766, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 17:23:03,338 INFO] 72448 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0783, train/total_loss: 0.0786, train/util_ratio: 1.0000, train/run_time: 0.5386, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 17:25:25,193 INFO] 72704 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0922, train/total_loss: 0.0923, train/util_ratio: 0.8750, train/run_time: 0.5390, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 17:28:29,812 INFO] 72960 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0007, train/total_loss: 0.0008, train/util_ratio: 0.8750, train/run_time: 0.5259, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 17:30:52,260 INFO] 73216 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.5218, train/total_loss: 0.5219, train/util_ratio: 1.0000, train/run_time: 0.5490, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 17:33:14,888 INFO] 73472 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1814, train/total_loss: 0.1815, train/util_ratio: 1.0000, train/run_time: 0.5851, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 17:35:36,185 INFO] validating...
[2023-08-23 17:36:00,543 INFO] confusion matrix:
[[0.95333333 0.00166667 0.00333333 0.         0.         0.00166667
  0.035      0.         0.005      0.        ]
 [0.         0.9        0.00833333 0.         0.         0.08833333
  0.         0.00333333 0.         0.        ]
 [0.         0.00666667 0.94       0.00333333 0.         0.02833333
  0.00833333 0.005      0.00833333 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.004      0.986      0.
  0.008      0.002      0.         0.        ]
 [0.02       0.005      0.01       0.02       0.         0.915
  0.0275     0.         0.0025     0.        ]
 [0.012      0.         0.06       0.         0.002      0.
  0.926      0.         0.         0.        ]
 [0.         0.         0.         0.00666667 0.00666667 0.
  0.         0.98666667 0.         0.        ]
 [0.00601202 0.         0.         0.02004008 0.         0.
  0.         0.         0.9739479  0.        ]
 [0.01666667 0.05666667 0.015      0.00166667 0.         0.00333333
  0.         0.         0.00666667 0.9       ]]
[2023-08-23 17:36:01,611 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 17:36:02,758 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 17:36:02,759 INFO] 73728 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.5293, train/total_loss: 0.5293, train/util_ratio: 1.0000, train/run_time: 0.4793, eval/loss: 0.2353, eval/top-1-acc: 0.9470, eval/balanced_acc: 0.9475, eval/precision: 0.9452, eval/recall: 0.9475, eval/F1: 0.9458, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9470, at 73728 iters
[2023-08-23 17:39:06,125 INFO] 73984 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3438, train/total_loss: 0.3438, train/util_ratio: 1.0000, train/run_time: 0.5401, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 17:41:31,318 INFO] 74240 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.0037, train/total_loss: 0.0040, train/util_ratio: 0.8750, train/run_time: 0.5402, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-23 17:43:52,885 INFO] 74496 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1618, train/total_loss: 0.1621, train/util_ratio: 1.0000, train/run_time: 0.5261, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 17:46:15,800 INFO] 74752 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.6675, train/total_loss: 0.6676, train/util_ratio: 1.0000, train/run_time: 0.4779, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-23 17:49:20,942 INFO] 75008 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1323, train/total_loss: 0.1323, train/util_ratio: 1.0000, train/run_time: 0.5487, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 17:51:43,464 INFO] 75264 iteration USE_EMA: False, train/sup_loss: 0.0015, train/unsup_loss: 0.5421, train/total_loss: 0.5436, train/util_ratio: 1.0000, train/run_time: 0.4764, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 17:54:06,235 INFO] 75520 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0005, train/total_loss: 0.0005, train/util_ratio: 1.0000, train/run_time: 0.5424, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 17:56:27,279 INFO] validating...
[2023-08-23 17:56:51,747 INFO] confusion matrix:
[[0.94666667 0.00166667 0.00333333 0.         0.         0.00833333
  0.03666667 0.         0.00333333 0.        ]
 [0.         0.86833333 0.00666667 0.         0.         0.12333333
  0.         0.00166667 0.         0.        ]
 [0.         0.00166667 0.86166667 0.00166667 0.         0.07333333
  0.04333333 0.00333333 0.015      0.        ]
 [0.002      0.         0.         0.984      0.004      0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.0075     0.         0.005      0.0125     0.         0.9575
  0.015      0.         0.0025     0.        ]
 [0.016      0.         0.02       0.004      0.         0.004
  0.956      0.         0.         0.        ]
 [0.         0.         0.         0.00833333 0.01166667 0.
  0.00166667 0.97833333 0.         0.        ]
 [0.00400802 0.00200401 0.         0.01402806 0.         0.
  0.00200401 0.         0.97795591 0.        ]
 [0.015      0.01       0.01833333 0.         0.         0.00333333
  0.         0.         0.00666667 0.94666667]]
[2023-08-23 17:56:52,819 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 17:56:52,820 INFO] 75776 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0050, train/total_loss: 0.0051, train/util_ratio: 1.0000, train/run_time: 0.5415, eval/loss: 0.2744, eval/top-1-acc: 0.9446, eval/balanced_acc: 0.9473, eval/precision: 0.9430, eval/recall: 0.9473, eval/F1: 0.9432, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9470, at 73728 iters
[2023-08-23 17:59:56,921 INFO] 76032 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3119, train/total_loss: 0.3120, train/util_ratio: 0.8750, train/run_time: 0.5341, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 18:02:18,644 INFO] 76288 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.1818, train/total_loss: 0.1826, train/util_ratio: 1.0000, train/run_time: 0.5266, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 18:04:41,251 INFO] 76544 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3498, train/total_loss: 0.3499, train/util_ratio: 0.7500, train/run_time: 0.5494, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 18:07:03,632 INFO] 76800 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0180, train/total_loss: 0.0181, train/util_ratio: 0.8750, train/run_time: 0.5356, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 18:10:09,684 INFO] 77056 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1496, train/total_loss: 0.1497, train/util_ratio: 0.8750, train/run_time: 0.5419, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 18:12:31,792 INFO] 77312 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0031, train/total_loss: 0.0033, train/util_ratio: 1.0000, train/run_time: 0.5318, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 18:14:54,893 INFO] 77568 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.1174, train/total_loss: 0.1180, train/util_ratio: 1.0000, train/run_time: 0.5466, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 18:17:16,145 INFO] validating...
[2023-08-23 18:17:40,706 INFO] confusion matrix:
[[0.94       0.00166667 0.00333333 0.         0.         0.005
  0.04833333 0.         0.00166667 0.        ]
 [0.         0.88166667 0.005      0.         0.         0.10833333
  0.         0.005      0.         0.        ]
 [0.         0.         0.90333333 0.00166667 0.         0.045
  0.03       0.00833333 0.01166667 0.        ]
 [0.         0.         0.         0.99       0.002      0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.998      0.
  0.         0.         0.         0.        ]
 [0.0175     0.         0.0025     0.01       0.         0.93
  0.0375     0.         0.0025     0.        ]
 [0.01       0.         0.028      0.         0.004      0.
  0.958      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01666667 0.
  0.00166667 0.98       0.         0.        ]
 [0.00400802 0.         0.         0.00601202 0.         0.
  0.00200401 0.         0.98797595 0.        ]
 [0.015      0.01       0.02       0.00166667 0.         0.00333333
  0.         0.         0.         0.95      ]]
[2023-08-23 18:17:41,730 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 18:17:42,831 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-23 18:17:42,832 INFO] 77824 iteration, USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.3804, train/total_loss: 0.3814, train/util_ratio: 0.8750, train/run_time: 0.5254, eval/loss: 0.2474, eval/top-1-acc: 0.9504, eval/balanced_acc: 0.9519, eval/precision: 0.9481, eval/recall: 0.9519, eval/F1: 0.9489, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 18:20:46,083 INFO] 78080 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1648, train/total_loss: 0.1649, train/util_ratio: 1.0000, train/run_time: 0.5248, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 18:23:07,004 INFO] 78336 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0588, train/total_loss: 0.0589, train/util_ratio: 1.0000, train/run_time: 0.5431, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 18:25:29,223 INFO] 78592 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0488, train/total_loss: 0.0488, train/util_ratio: 0.8750, train/run_time: 0.5430, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 18:27:51,949 INFO] 78848 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.4224, train/total_loss: 0.4228, train/util_ratio: 0.8750, train/run_time: 0.5412, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 18:30:56,508 INFO] 79104 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0906, train/total_loss: 0.0907, train/util_ratio: 1.0000, train/run_time: 0.4876, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 18:33:17,551 INFO] 79360 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0621, train/total_loss: 0.0622, train/util_ratio: 1.0000, train/run_time: 0.5438, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 18:35:39,481 INFO] 79616 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.5713, train/total_loss: 0.5715, train/util_ratio: 1.0000, train/run_time: 0.5399, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 18:38:01,178 INFO] validating...
[2023-08-23 18:38:25,677 INFO] confusion matrix:
[[0.95       0.00166667 0.00333333 0.         0.         0.00833333
  0.03166667 0.         0.005      0.        ]
 [0.         0.89       0.00333333 0.         0.         0.10333333
  0.         0.00333333 0.         0.        ]
 [0.         0.025      0.80166667 0.00333333 0.00166667 0.13333333
  0.00333333 0.01333333 0.01666667 0.00166667]
 [0.         0.         0.         0.992      0.002      0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.005      0.         0.0025     0.015      0.         0.965
  0.01       0.         0.0025     0.        ]
 [0.01       0.002      0.04       0.006      0.002      0.006
  0.934      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01       0.
  0.         0.98833333 0.         0.        ]
 [0.00601202 0.00200401 0.         0.00801603 0.         0.
  0.00200401 0.         0.98196393 0.        ]
 [0.005      0.005      0.005      0.00166667 0.         0.00333333
  0.         0.         0.         0.98      ]]
[2023-08-23 18:38:26,530 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 18:38:26,531 INFO] 79872 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1910, train/total_loss: 0.1911, train/util_ratio: 1.0000, train/run_time: 0.5254, eval/loss: 0.2863, eval/top-1-acc: 0.9450, eval/balanced_acc: 0.9477, eval/precision: 0.9441, eval/recall: 0.9477, eval/F1: 0.9433, lr: 0.0000, train/prefecth_time: 0.0023 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 18:41:30,406 INFO] 80128 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.0118, train/total_loss: 0.0122, train/util_ratio: 1.0000, train/run_time: 0.5585, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 18:43:52,492 INFO] 80384 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0153, train/total_loss: 0.0153, train/util_ratio: 1.0000, train/run_time: 0.5397, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 18:46:15,337 INFO] 80640 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0487, train/total_loss: 0.0487, train/util_ratio: 1.0000, train/run_time: 0.5351, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 18:48:37,067 INFO] 80896 iteration USE_EMA: False, train/sup_loss: 0.0008, train/unsup_loss: 0.4281, train/total_loss: 0.4289, train/util_ratio: 1.0000, train/run_time: 0.5365, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-23 18:51:41,928 INFO] 81152 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0323, train/total_loss: 0.0324, train/util_ratio: 1.0000, train/run_time: 0.5406, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-23 18:54:04,658 INFO] 81408 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1713, train/total_loss: 0.1716, train/util_ratio: 1.0000, train/run_time: 0.5337, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 18:56:27,985 INFO] 81664 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3767, train/total_loss: 0.3768, train/util_ratio: 1.0000, train/run_time: 0.4974, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 18:58:49,955 INFO] validating...
[2023-08-23 18:59:14,482 INFO] confusion matrix:
[[0.94666667 0.00166667 0.00333333 0.         0.         0.00833333
  0.03333333 0.         0.00666667 0.        ]
 [0.         0.89333333 0.005      0.         0.         0.095
  0.         0.005      0.00166667 0.        ]
 [0.         0.035      0.845      0.00833333 0.         0.06166667
  0.00833333 0.01833333 0.02333333 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.004      0.992      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.         0.005      0.015      0.         0.9525
  0.0225     0.         0.0025     0.        ]
 [0.006      0.         0.044      0.006      0.         0.
  0.944      0.         0.         0.        ]
 [0.         0.         0.         0.01       0.00666667 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.02004008 0.         0.
  0.00200401 0.         0.9739479  0.        ]
 [0.01166667 0.04       0.01       0.00166667 0.         0.00333333
  0.         0.         0.01       0.92333333]]
[2023-08-23 18:59:15,384 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 18:59:15,385 INFO] 81920 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4402, train/total_loss: 0.4403, train/util_ratio: 1.0000, train/run_time: 0.5352, eval/loss: 0.2840, eval/top-1-acc: 0.9422, eval/balanced_acc: 0.9448, eval/precision: 0.9402, eval/recall: 0.9448, eval/F1: 0.9412, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 19:02:20,191 INFO] 82176 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.0194, train/total_loss: 0.0203, train/util_ratio: 1.0000, train/run_time: 0.5477, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 19:04:43,062 INFO] 82432 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0871, train/total_loss: 0.0871, train/util_ratio: 1.0000, train/run_time: 0.5497, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 19:07:05,706 INFO] 82688 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1708, train/total_loss: 0.1711, train/util_ratio: 1.0000, train/run_time: 0.5380, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 19:09:29,141 INFO] 82944 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1980, train/total_loss: 0.1981, train/util_ratio: 0.8750, train/run_time: 0.5409, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 19:12:33,864 INFO] 83200 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.3218, train/total_loss: 0.3221, train/util_ratio: 0.8750, train/run_time: 0.5418, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 19:14:56,190 INFO] 83456 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3277, train/total_loss: 0.3278, train/util_ratio: 1.0000, train/run_time: 0.5256, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-23 19:17:17,581 INFO] 83712 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0601, train/total_loss: 0.0603, train/util_ratio: 1.0000, train/run_time: 0.5448, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 19:19:39,856 INFO] validating...
[2023-08-23 19:20:04,319 INFO] confusion matrix:
[[0.95833333 0.00166667 0.00333333 0.         0.         0.00666667
  0.02666667 0.         0.00333333 0.        ]
 [0.         0.89833333 0.00333333 0.         0.         0.09166667
  0.         0.00666667 0.         0.        ]
 [0.         0.03666667 0.69833333 0.01       0.         0.17
  0.06       0.01666667 0.00833333 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.01       0.         0.         0.0075     0.         0.9475
  0.0325     0.         0.0025     0.        ]
 [0.008      0.         0.014      0.008      0.         0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.00833333 0.005      0.
  0.         0.98666667 0.         0.        ]
 [0.00601202 0.         0.         0.02004008 0.         0.
  0.00200401 0.         0.97194389 0.        ]
 [0.01333333 0.01666667 0.00666667 0.         0.         0.00333333
  0.         0.         0.00166667 0.95833333]]
[2023-08-23 19:20:05,116 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 19:20:05,117 INFO] 83968 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0019, train/total_loss: 0.0020, train/util_ratio: 1.0000, train/run_time: 0.5429, eval/loss: 0.3342, eval/top-1-acc: 0.9337, eval/balanced_acc: 0.9373, eval/precision: 0.9340, eval/recall: 0.9373, eval/F1: 0.9313, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 19:23:07,876 INFO] 84224 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0256, train/total_loss: 0.0257, train/util_ratio: 1.0000, train/run_time: 0.5277, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 19:25:29,232 INFO] 84480 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4929, train/total_loss: 0.4930, train/util_ratio: 0.7500, train/run_time: 0.5415, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 19:27:50,952 INFO] 84736 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1529, train/total_loss: 0.1530, train/util_ratio: 1.0000, train/run_time: 0.5606, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 19:30:11,528 INFO] 84992 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0011, train/total_loss: 0.0012, train/util_ratio: 0.8750, train/run_time: 0.5377, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 19:33:17,808 INFO] 85248 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0897, train/total_loss: 0.0898, train/util_ratio: 0.8750, train/run_time: 0.5431, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 19:35:40,054 INFO] 85504 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0867, train/total_loss: 0.0868, train/util_ratio: 1.0000, train/run_time: 0.4818, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 19:38:00,914 INFO] 85760 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0209, train/total_loss: 0.0210, train/util_ratio: 1.0000, train/run_time: 0.5414, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 19:40:23,076 INFO] validating...
[2023-08-23 19:40:47,527 INFO] confusion matrix:
[[0.93       0.00166667 0.00666667 0.         0.         0.00833333
  0.04666667 0.         0.00666667 0.        ]
 [0.         0.89833333 0.00166667 0.         0.         0.09
  0.         0.01       0.         0.        ]
 [0.         0.03166667 0.84333333 0.00666667 0.         0.04
  0.00833333 0.04833333 0.02166667 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.002      0.004      0.        ]
 [0.         0.         0.         0.002      0.998      0.
  0.         0.         0.         0.        ]
 [0.0025     0.005      0.005      0.0125     0.         0.945
  0.0275     0.         0.0025     0.        ]
 [0.004      0.         0.042      0.01       0.004      0.
  0.932      0.006      0.002      0.        ]
 [0.         0.         0.         0.005      0.01       0.
  0.         0.985      0.         0.        ]
 [0.00400802 0.         0.         0.02004008 0.         0.
  0.00200401 0.         0.9739479  0.        ]
 [0.015      0.03       0.00666667 0.00166667 0.         0.00333333
  0.         0.00166667 0.00333333 0.93833333]]
[2023-08-23 19:40:48,322 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 19:40:48,323 INFO] 86016 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.6312, train/total_loss: 0.6313, train/util_ratio: 0.8750, train/run_time: 0.4858, eval/loss: 0.2949, eval/top-1-acc: 0.9415, eval/balanced_acc: 0.9438, eval/precision: 0.9396, eval/recall: 0.9438, eval/F1: 0.9406, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 19:43:52,206 INFO] 86272 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.0085, train/total_loss: 0.0088, train/util_ratio: 1.0000, train/run_time: 0.5338, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 19:46:16,807 INFO] 86528 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0871, train/total_loss: 0.0871, train/util_ratio: 1.0000, train/run_time: 0.5338, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 19:48:41,134 INFO] 86784 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2055, train/total_loss: 0.2056, train/util_ratio: 0.8750, train/run_time: 0.5260, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 19:51:04,146 INFO] 87040 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3916, train/total_loss: 0.3917, train/util_ratio: 0.8750, train/run_time: 0.4793, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 19:54:09,807 INFO] 87296 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2801, train/total_loss: 0.2802, train/util_ratio: 0.8750, train/run_time: 0.4908, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 19:56:33,214 INFO] 87552 iteration USE_EMA: False, train/sup_loss: 0.0019, train/unsup_loss: 0.0530, train/total_loss: 0.0550, train/util_ratio: 1.0000, train/run_time: 0.5417, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 19:58:56,142 INFO] 87808 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 1.0293, train/total_loss: 1.0293, train/util_ratio: 0.8750, train/run_time: 0.5310, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 20:01:18,710 INFO] validating...
[2023-08-23 20:01:42,555 INFO] confusion matrix:
[[0.95166667 0.00166667 0.00333333 0.         0.         0.01
  0.03166667 0.         0.00166667 0.        ]
 [0.         0.88666667 0.005      0.         0.         0.10166667
  0.         0.00666667 0.         0.        ]
 [0.         0.02833333 0.80166667 0.00333333 0.         0.07833333
  0.02166667 0.02666667 0.04       0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.002      0.004      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0025     0.         0.005      0.01       0.         0.955
  0.025      0.         0.0025     0.        ]
 [0.006      0.         0.036      0.006      0.         0.
  0.952      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.00333333 0.
  0.         0.99333333 0.         0.        ]
 [0.00400802 0.         0.         0.01202405 0.         0.
  0.00200401 0.         0.98196393 0.        ]
 [0.015      0.015      0.00833333 0.         0.         0.00333333
  0.         0.00166667 0.         0.95666667]]
[2023-08-23 20:01:43,375 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 20:01:43,376 INFO] 88064 iteration, USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.1132, train/total_loss: 0.1136, train/util_ratio: 1.0000, train/run_time: 0.4803, eval/loss: 0.2766, eval/top-1-acc: 0.9439, eval/balanced_acc: 0.9467, eval/precision: 0.9420, eval/recall: 0.9467, eval/F1: 0.9425, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 20:04:46,903 INFO] 88320 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0020, train/total_loss: 0.0021, train/util_ratio: 1.0000, train/run_time: 0.5309, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 20:07:08,267 INFO] 88576 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0180, train/total_loss: 0.0181, train/util_ratio: 0.8750, train/run_time: 0.5396, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 20:09:29,714 INFO] 88832 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0148, train/total_loss: 0.0149, train/util_ratio: 0.8750, train/run_time: 0.4787, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 20:11:51,432 INFO] 89088 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0018, train/total_loss: 0.0018, train/util_ratio: 1.0000, train/run_time: 0.4767, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 20:14:56,161 INFO] 89344 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2323, train/total_loss: 0.2323, train/util_ratio: 1.0000, train/run_time: 0.5352, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-23 20:17:17,192 INFO] 89600 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1157, train/total_loss: 0.1159, train/util_ratio: 1.0000, train/run_time: 0.5247, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 20:19:38,922 INFO] 89856 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0071, train/total_loss: 0.0071, train/util_ratio: 0.7500, train/run_time: 0.5353, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 20:22:01,890 INFO] validating...
[2023-08-23 20:22:25,793 INFO] confusion matrix:
[[0.97666667 0.00166667 0.00333333 0.         0.         0.00166667
  0.01333333 0.         0.00333333 0.        ]
 [0.         0.86833333 0.00833333 0.         0.         0.11333333
  0.         0.00166667 0.00833333 0.        ]
 [0.         0.005      0.82833333 0.00666667 0.         0.05666667
  0.01333333 0.01166667 0.07833333 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.         0.002      0.         0.        ]
 [0.0225     0.         0.005      0.0125     0.         0.8875
  0.0375     0.         0.035      0.        ]
 [0.014      0.         0.032      0.004      0.         0.
  0.95       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.00666667 0.
  0.         0.98833333 0.00166667 0.        ]
 [0.00400802 0.         0.         0.01202405 0.         0.
  0.         0.         0.98396794 0.        ]
 [0.02333333 0.01333333 0.01666667 0.         0.         0.015
  0.         0.         0.00166667 0.93      ]]
[2023-08-23 20:22:26,709 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 20:22:26,710 INFO] 90112 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.6442, train/total_loss: 0.6442, train/util_ratio: 0.8750, train/run_time: 0.5225, eval/loss: 0.2909, eval/top-1-acc: 0.9392, eval/balanced_acc: 0.9403, eval/precision: 0.9368, eval/recall: 0.9403, eval/F1: 0.9369, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 20:25:31,474 INFO] 90368 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2168, train/total_loss: 0.2169, train/util_ratio: 0.8750, train/run_time: 0.5691, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 20:27:54,419 INFO] 90624 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0886, train/total_loss: 0.0887, train/util_ratio: 1.0000, train/run_time: 0.5589, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 20:30:18,359 INFO] 90880 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0069, train/total_loss: 0.0070, train/util_ratio: 0.8750, train/run_time: 0.5430, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 20:32:41,337 INFO] 91136 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2556, train/total_loss: 0.2557, train/util_ratio: 1.0000, train/run_time: 0.5397, lr: 0.0000, train/prefecth_time: 0.0024 
[2023-08-23 20:35:45,629 INFO] 91392 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2000, train/total_loss: 0.2002, train/util_ratio: 1.0000, train/run_time: 0.5216, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-23 20:38:08,179 INFO] 91648 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.5729, train/total_loss: 0.5731, train/util_ratio: 1.0000, train/run_time: 0.5479, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 20:40:30,842 INFO] 91904 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0070, train/total_loss: 0.0070, train/util_ratio: 0.7500, train/run_time: 0.5384, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 20:42:53,147 INFO] validating...
[2023-08-23 20:43:17,754 INFO] confusion matrix:
[[0.96666667 0.00166667 0.005      0.         0.         0.01166667
  0.01333333 0.         0.00166667 0.        ]
 [0.         0.83       0.005      0.         0.         0.16
  0.         0.005      0.         0.        ]
 [0.         0.00666667 0.775      0.00666667 0.         0.06666667
  0.005      0.02       0.12       0.        ]
 [0.         0.         0.         0.976      0.002      0.
  0.         0.006      0.016      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.         0.004      0.         0.        ]
 [0.005      0.         0.005      0.01       0.         0.96
  0.02       0.         0.         0.        ]
 [0.02       0.         0.042      0.006      0.         0.004
  0.922      0.006      0.         0.        ]
 [0.         0.         0.         0.00333333 0.00333333 0.
  0.         0.99333333 0.         0.        ]
 [0.00601202 0.         0.         0.01002004 0.         0.
  0.         0.         0.98396794 0.        ]
 [0.01833333 0.01       0.01166667 0.         0.         0.005
  0.         0.         0.         0.955     ]]
[2023-08-23 20:43:18,666 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 20:43:18,668 INFO] 92160 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2009, train/total_loss: 0.2010, train/util_ratio: 1.0000, train/run_time: 0.5416, eval/loss: 0.3673, eval/top-1-acc: 0.9322, eval/balanced_acc: 0.9356, eval/precision: 0.9324, eval/recall: 0.9356, eval/F1: 0.9304, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 20:46:23,123 INFO] 92416 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.5348, train/total_loss: 0.5349, train/util_ratio: 1.0000, train/run_time: 0.5416, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 20:48:46,872 INFO] 92672 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.5411, train/total_loss: 0.5412, train/util_ratio: 0.8750, train/run_time: 0.5305, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 20:51:10,853 INFO] 92928 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0653, train/total_loss: 0.0655, train/util_ratio: 0.8750, train/run_time: 0.5252, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 20:53:34,454 INFO] 93184 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.1052, train/total_loss: 0.1060, train/util_ratio: 0.8750, train/run_time: 0.5375, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 20:56:38,739 INFO] 93440 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0936, train/total_loss: 0.0939, train/util_ratio: 1.0000, train/run_time: 0.5642, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 20:59:00,489 INFO] 93696 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0037, train/total_loss: 0.0038, train/util_ratio: 0.8750, train/run_time: 0.5319, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-23 21:01:22,961 INFO] 93952 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.3305, train/total_loss: 0.3309, train/util_ratio: 0.8750, train/run_time: 0.5277, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-23 21:03:43,870 INFO] validating...
[2023-08-23 21:04:08,450 INFO] confusion matrix:
[[0.975      0.00166667 0.00166667 0.         0.         0.00333333
  0.01333333 0.         0.005      0.        ]
 [0.         0.88333333 0.00166667 0.         0.         0.10833333
  0.         0.005      0.00166667 0.        ]
 [0.         0.015      0.66333333 0.00166667 0.00166667 0.055
  0.025      0.03666667 0.20166667 0.        ]
 [0.002      0.         0.         0.964      0.002      0.
  0.         0.002      0.03       0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.         0.002      0.         0.        ]
 [0.0125     0.         0.0025     0.01       0.         0.955
  0.015      0.         0.0025     0.0025    ]
 [0.01       0.004      0.03       0.004      0.002      0.
  0.944      0.004      0.002      0.        ]
 [0.         0.         0.         0.005      0.005      0.
  0.         0.99       0.         0.        ]
 [0.00601202 0.00200401 0.         0.01202405 0.         0.
  0.         0.         0.97995992 0.        ]
 [0.015      0.02       0.01166667 0.         0.         0.00333333
  0.         0.         0.00166667 0.94833333]]
[2023-08-23 21:04:09,526 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 21:04:09,527 INFO] 94208 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0526, train/total_loss: 0.0527, train/util_ratio: 1.0000, train/run_time: 0.4758, eval/loss: 0.4029, eval/top-1-acc: 0.9259, eval/balanced_acc: 0.9299, eval/precision: 0.9269, eval/recall: 0.9299, eval/F1: 0.9237, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 21:07:12,925 INFO] 94464 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3251, train/total_loss: 0.3252, train/util_ratio: 0.7500, train/run_time: 0.4995, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 21:09:34,223 INFO] 94720 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.6265, train/total_loss: 0.6266, train/util_ratio: 1.0000, train/run_time: 0.4904, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-23 21:11:56,411 INFO] 94976 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0457, train/total_loss: 0.0459, train/util_ratio: 1.0000, train/run_time: 0.5390, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 21:14:18,715 INFO] 95232 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0305, train/total_loss: 0.0306, train/util_ratio: 1.0000, train/run_time: 0.4822, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 21:17:23,361 INFO] 95488 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0175, train/total_loss: 0.0175, train/util_ratio: 1.0000, train/run_time: 0.5480, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 21:19:46,321 INFO] 95744 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0053, train/total_loss: 0.0057, train/util_ratio: 0.8750, train/run_time: 0.5097, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 21:22:08,445 INFO] 96000 iteration USE_EMA: False, train/sup_loss: 0.0030, train/unsup_loss: 0.1925, train/total_loss: 0.1955, train/util_ratio: 1.0000, train/run_time: 0.4863, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 21:24:29,531 INFO] validating...
[2023-08-23 21:24:53,377 INFO] confusion matrix:
[[0.895      0.00166667 0.00666667 0.         0.         0.00333333
  0.09       0.         0.00333333 0.        ]
 [0.         0.87       0.005      0.         0.         0.12166667
  0.         0.00333333 0.         0.        ]
 [0.         0.015      0.83833333 0.00166667 0.         0.04
  0.02666667 0.025      0.05333333 0.        ]
 [0.         0.         0.002      0.986      0.         0.
  0.         0.002      0.01       0.        ]
 [0.         0.         0.         0.004      0.976      0.
  0.002      0.018      0.         0.        ]
 [0.0075     0.         0.0025     0.0075     0.         0.8875
  0.085      0.         0.0075     0.0025    ]
 [0.002      0.         0.042      0.         0.         0.
  0.948      0.008      0.         0.        ]
 [0.         0.         0.         0.         0.         0.
  0.         1.         0.         0.        ]
 [0.00400802 0.         0.         0.01202405 0.         0.
  0.00200401 0.         0.98196393 0.        ]
 [0.015      0.01166667 0.01833333 0.         0.         0.00333333
  0.         0.         0.         0.95166667]]
[2023-08-23 21:24:54,271 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 21:24:54,272 INFO] 96256 iteration, USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.6327, train/total_loss: 0.6331, train/util_ratio: 1.0000, train/run_time: 0.4772, eval/loss: 0.3278, eval/top-1-acc: 0.9322, eval/balanced_acc: 0.9334, eval/precision: 0.9308, eval/recall: 0.9334, eval/F1: 0.9304, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 21:27:58,713 INFO] 96512 iteration USE_EMA: False, train/sup_loss: 0.0303, train/unsup_loss: 0.1877, train/total_loss: 0.2180, train/util_ratio: 1.0000, train/run_time: 0.5357, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 21:30:21,631 INFO] 96768 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0749, train/total_loss: 0.0751, train/util_ratio: 1.0000, train/run_time: 0.5429, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 21:32:45,347 INFO] 97024 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0239, train/total_loss: 0.0239, train/util_ratio: 1.0000, train/run_time: 0.5343, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 21:35:08,387 INFO] 97280 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1216, train/total_loss: 0.1217, train/util_ratio: 1.0000, train/run_time: 0.5255, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 21:38:13,628 INFO] 97536 iteration USE_EMA: False, train/sup_loss: 0.0038, train/unsup_loss: 0.0425, train/total_loss: 0.0462, train/util_ratio: 1.0000, train/run_time: 0.5429, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 21:40:36,251 INFO] 97792 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0198, train/total_loss: 0.0200, train/util_ratio: 0.8750, train/run_time: 0.5485, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 21:42:58,910 INFO] 98048 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1712, train/total_loss: 0.1713, train/util_ratio: 1.0000, train/run_time: 0.4790, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 21:45:21,524 INFO] validating...
[2023-08-23 21:45:46,001 INFO] confusion matrix:
[[0.945      0.00166667 0.00166667 0.         0.         0.00166667
  0.04333333 0.         0.00666667 0.        ]
 [0.         0.90166667 0.00333333 0.         0.         0.085
  0.         0.00333333 0.00666667 0.        ]
 [0.00166667 0.01166667 0.705      0.00166667 0.00166667 0.04
  0.04       0.02666667 0.17166667 0.        ]
 [0.         0.         0.002      0.97       0.004      0.
  0.002      0.         0.022      0.        ]
 [0.         0.         0.         0.002      0.988      0.
  0.006      0.004      0.         0.        ]
 [0.015      0.0025     0.0025     0.005      0.         0.94
  0.025      0.         0.01       0.        ]
 [0.004      0.         0.02       0.         0.         0.
  0.976      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.00333333 0.
  0.         0.99166667 0.00333333 0.        ]
 [0.00400802 0.         0.         0.00801603 0.         0.
  0.         0.         0.98797595 0.        ]
 [0.00833333 0.01833333 0.005      0.         0.         0.00333333
  0.         0.         0.005      0.96      ]]
[2023-08-23 21:45:46,964 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 21:45:46,965 INFO] 98304 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0360, train/total_loss: 0.0361, train/util_ratio: 0.8750, train/run_time: 0.5350, eval/loss: 0.3255, eval/top-1-acc: 0.9331, eval/balanced_acc: 0.9365, eval/precision: 0.9338, eval/recall: 0.9365, eval/F1: 0.9313, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 21:48:49,806 INFO] 98560 iteration USE_EMA: False, train/sup_loss: 0.0016, train/unsup_loss: 0.5150, train/total_loss: 0.5165, train/util_ratio: 1.0000, train/run_time: 0.5422, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 21:51:11,277 INFO] 98816 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1880, train/total_loss: 0.1883, train/util_ratio: 1.0000, train/run_time: 0.4968, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 21:53:31,791 INFO] 99072 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2070, train/total_loss: 0.2071, train/util_ratio: 1.0000, train/run_time: 0.5427, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 21:55:53,960 INFO] 99328 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1164, train/total_loss: 0.1165, train/util_ratio: 1.0000, train/run_time: 0.4784, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 21:58:59,647 INFO] 99584 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1035, train/total_loss: 0.1036, train/util_ratio: 0.8750, train/run_time: 0.5354, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 22:01:21,179 INFO] 99840 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.0836, train/total_loss: 0.0839, train/util_ratio: 1.0000, train/run_time: 0.5711, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 22:03:42,878 INFO] 100096 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.0015, train/total_loss: 0.0019, train/util_ratio: 1.0000, train/run_time: 0.5299, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 22:06:06,089 INFO] validating...
[2023-08-23 22:06:30,100 INFO] confusion matrix:
[[0.93666667 0.00166667 0.005      0.         0.         0.00333333
  0.05166667 0.         0.00166667 0.        ]
 [0.         0.895      0.005      0.         0.         0.08666667
  0.         0.01       0.00333333 0.        ]
 [0.00166667 0.00333333 0.90666667 0.00333333 0.         0.01666667
  0.00666667 0.015      0.04666667 0.        ]
 [0.         0.         0.002      0.982      0.         0.
  0.         0.002      0.014      0.        ]
 [0.         0.         0.         0.002      0.988      0.
  0.004      0.006      0.         0.        ]
 [0.02       0.005      0.005      0.01       0.         0.8775
  0.0625     0.         0.0175     0.0025    ]
 [0.004      0.         0.046      0.         0.         0.
  0.948      0.002      0.         0.        ]
 [0.         0.         0.         0.00166667 0.00333333 0.
  0.         0.995      0.         0.        ]
 [0.00400802 0.         0.         0.00601202 0.         0.
  0.00200401 0.         0.98797595 0.        ]
 [0.01333333 0.01       0.015      0.         0.         0.00166667
  0.         0.         0.00166667 0.95833333]]
[2023-08-23 22:06:31,016 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 22:06:31,017 INFO] 100352 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2219, train/total_loss: 0.2219, train/util_ratio: 0.8750, train/run_time: 0.5356, eval/loss: 0.2432, eval/top-1-acc: 0.9480, eval/balanced_acc: 0.9475, eval/precision: 0.9455, eval/recall: 0.9475, eval/F1: 0.9459, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 22:09:38,478 INFO] 100608 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.0270, train/total_loss: 0.0279, train/util_ratio: 0.8750, train/run_time: 0.5433, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 22:12:02,900 INFO] 100864 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2539, train/total_loss: 0.2540, train/util_ratio: 1.0000, train/run_time: 0.5255, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 22:14:26,014 INFO] 101120 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.5375, train/total_loss: 0.5376, train/util_ratio: 0.8750, train/run_time: 0.5565, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 22:16:48,194 INFO] 101376 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 1.2961, train/total_loss: 1.2963, train/util_ratio: 1.0000, train/run_time: 0.4774, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 22:19:52,290 INFO] 101632 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.6587, train/total_loss: 0.6587, train/util_ratio: 1.0000, train/run_time: 0.5489, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-23 22:22:14,084 INFO] 101888 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0163, train/total_loss: 0.0164, train/util_ratio: 0.8750, train/run_time: 0.5295, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 22:24:35,383 INFO] 102144 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0052, train/total_loss: 0.0052, train/util_ratio: 1.0000, train/run_time: 0.5361, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 22:26:57,599 INFO] validating...
[2023-08-23 22:27:21,531 INFO] confusion matrix:
[[0.93       0.00166667 0.005      0.         0.         0.00333333
  0.055      0.         0.00333333 0.00166667]
 [0.         0.915      0.00333333 0.         0.         0.075
  0.         0.00166667 0.005      0.        ]
 [0.         0.01166667 0.84833333 0.00166667 0.         0.03
  0.01166667 0.00333333 0.09333333 0.        ]
 [0.         0.         0.002      0.978      0.         0.
  0.         0.002      0.018      0.        ]
 [0.         0.         0.         0.002      0.988      0.
  0.006      0.004      0.         0.        ]
 [0.0075     0.0125     0.0075     0.01       0.         0.93
  0.0225     0.         0.0075     0.0025    ]
 [0.002      0.002      0.034      0.         0.         0.
  0.962      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.00333333 0.
  0.         0.99333333 0.         0.        ]
 [0.00601202 0.00200401 0.         0.00400802 0.         0.
  0.         0.         0.98797595 0.        ]
 [0.005      0.01333333 0.01333333 0.         0.         0.00166667
  0.         0.         0.00166667 0.965     ]]
[2023-08-23 22:27:22,509 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 22:27:22,510 INFO] 102400 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0304, train/total_loss: 0.0304, train/util_ratio: 1.0000, train/run_time: 0.5621, eval/loss: 0.2219, eval/top-1-acc: 0.9483, eval/balanced_acc: 0.9498, eval/precision: 0.9463, eval/recall: 0.9498, eval/F1: 0.9470, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 22:30:26,748 INFO] 102656 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.1221, train/total_loss: 0.1224, train/util_ratio: 1.0000, train/run_time: 0.5411, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 22:32:48,003 INFO] 102912 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0075, train/total_loss: 0.0077, train/util_ratio: 1.0000, train/run_time: 0.5481, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 22:35:11,653 INFO] 103168 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.0617, train/total_loss: 0.0621, train/util_ratio: 1.0000, train/run_time: 0.5406, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 22:37:32,944 INFO] 103424 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.0069, train/total_loss: 0.0080, train/util_ratio: 0.8750, train/run_time: 0.5318, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-23 22:40:37,288 INFO] 103680 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0621, train/total_loss: 0.0622, train/util_ratio: 1.0000, train/run_time: 0.5716, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 22:42:58,880 INFO] 103936 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2403, train/total_loss: 0.2403, train/util_ratio: 1.0000, train/run_time: 0.5325, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 22:45:19,361 INFO] 104192 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.6361, train/total_loss: 0.6370, train/util_ratio: 1.0000, train/run_time: 0.5295, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 22:47:40,501 INFO] validating...
[2023-08-23 22:48:04,452 INFO] confusion matrix:
[[0.92333333 0.00166667 0.005      0.         0.         0.00666667
  0.05666667 0.         0.00333333 0.00333333]
 [0.         0.89       0.005      0.         0.         0.09
  0.         0.00666667 0.00333333 0.005     ]
 [0.         0.00166667 0.85833333 0.00333333 0.         0.055
  0.025      0.00666667 0.05       0.        ]
 [0.         0.         0.002      0.99       0.         0.
  0.002      0.         0.006      0.        ]
 [0.         0.         0.         0.         0.994      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.005      0.         0.01       0.         0.9475
  0.03       0.         0.         0.0025    ]
 [0.         0.         0.036      0.         0.         0.
  0.964      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.00333333 0.
  0.         0.99166667 0.00166667 0.        ]
 [0.00601202 0.         0.         0.01202405 0.         0.
  0.         0.         0.98196393 0.        ]
 [0.00333333 0.005      0.015      0.00166667 0.         0.00166667
  0.         0.         0.00333333 0.97      ]]
[2023-08-23 22:48:05,190 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 22:48:05,191 INFO] 104448 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0185, train/total_loss: 0.0185, train/util_ratio: 1.0000, train/run_time: 0.4800, eval/loss: 0.2612, eval/top-1-acc: 0.9489, eval/balanced_acc: 0.9511, eval/precision: 0.9466, eval/recall: 0.9511, eval/F1: 0.9474, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 22:51:09,984 INFO] 104704 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.3035, train/total_loss: 0.3035, train/util_ratio: 1.0000, train/run_time: 0.5464, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 22:53:31,056 INFO] 104960 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0032, train/total_loss: 0.0033, train/util_ratio: 1.0000, train/run_time: 0.5026, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 22:55:51,759 INFO] 105216 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.5461, train/total_loss: 0.5463, train/util_ratio: 1.0000, train/run_time: 0.5377, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 22:58:13,651 INFO] 105472 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0129, train/total_loss: 0.0132, train/util_ratio: 1.0000, train/run_time: 0.5743, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 23:01:19,522 INFO] 105728 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0165, train/total_loss: 0.0166, train/util_ratio: 1.0000, train/run_time: 0.5476, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 23:03:41,794 INFO] 105984 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0257, train/total_loss: 0.0259, train/util_ratio: 1.0000, train/run_time: 0.5376, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 23:06:04,584 INFO] 106240 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.9573, train/total_loss: 0.9574, train/util_ratio: 1.0000, train/run_time: 0.5351, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-23 23:08:26,779 INFO] validating...
[2023-08-23 23:08:51,096 INFO] confusion matrix:
[[0.89166667 0.00166667 0.00166667 0.         0.         0.00666667
  0.09       0.         0.00666667 0.00166667]
 [0.         0.85333333 0.00333333 0.         0.         0.135
  0.         0.005      0.00333333 0.        ]
 [0.         0.         0.75666667 0.005      0.         0.09333333
  0.05       0.00833333 0.08666667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.         0.002      0.         0.        ]
 [0.0025     0.         0.         0.0125     0.         0.9575
  0.0275     0.         0.         0.        ]
 [0.002      0.         0.016      0.006      0.002      0.
  0.974      0.         0.         0.        ]
 [0.         0.         0.         0.005      0.01       0.
  0.         0.98333333 0.00166667 0.        ]
 [0.00400802 0.         0.         0.00601202 0.         0.
  0.         0.         0.98997996 0.        ]
 [0.015      0.01166667 0.01166667 0.         0.         0.005
  0.         0.00333333 0.005      0.94833333]]
[2023-08-23 23:08:52,144 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 23:08:52,145 INFO] 106496 iteration, USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.5443, train/total_loss: 0.5448, train/util_ratio: 1.0000, train/run_time: 0.5345, eval/loss: 0.3602, eval/top-1-acc: 0.9294, eval/balanced_acc: 0.9343, eval/precision: 0.9299, eval/recall: 0.9343, eval/F1: 0.9277, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 23:11:56,118 INFO] 106752 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1888, train/total_loss: 0.1889, train/util_ratio: 1.0000, train/run_time: 0.5336, lr: 0.0000, train/prefecth_time: 0.0060 
[2023-08-23 23:14:19,284 INFO] 107008 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3527, train/total_loss: 0.3528, train/util_ratio: 1.0000, train/run_time: 0.4968, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 23:16:41,069 INFO] 107264 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0054, train/total_loss: 0.0055, train/util_ratio: 1.0000, train/run_time: 0.5262, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 23:19:03,236 INFO] 107520 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.6433, train/total_loss: 0.6433, train/util_ratio: 1.0000, train/run_time: 0.4793, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 23:22:09,581 INFO] 107776 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2463, train/total_loss: 0.2464, train/util_ratio: 0.8750, train/run_time: 0.5627, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 23:24:30,658 INFO] 108032 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0056, train/total_loss: 0.0057, train/util_ratio: 1.0000, train/run_time: 0.4890, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-23 23:26:53,374 INFO] 108288 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.0133, train/total_loss: 0.0136, train/util_ratio: 1.0000, train/run_time: 0.5472, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 23:29:15,413 INFO] validating...
[2023-08-23 23:29:39,300 INFO] confusion matrix:
[[0.92833333 0.00166667 0.00333333 0.         0.         0.00666667
  0.05833333 0.         0.00166667 0.        ]
 [0.         0.89666667 0.00666667 0.         0.         0.09666667
  0.         0.         0.         0.        ]
 [0.         0.00666667 0.815      0.005      0.         0.065
  0.05166667 0.00666667 0.05       0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.         0.002      0.         0.        ]
 [0.005      0.         0.         0.01       0.         0.955
  0.03       0.         0.         0.        ]
 [0.002      0.         0.018      0.002      0.         0.
  0.978      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.015      0.
  0.         0.98       0.00166667 0.        ]
 [0.00601202 0.         0.         0.00801603 0.         0.
  0.         0.         0.98597194 0.        ]
 [0.005      0.005      0.00666667 0.         0.         0.00166667
  0.         0.         0.00166667 0.98      ]]
[2023-08-23 23:29:40,217 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 23:29:40,218 INFO] 108544 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0427, train/total_loss: 0.0427, train/util_ratio: 0.8750, train/run_time: 0.5358, eval/loss: 0.2764, eval/top-1-acc: 0.9480, eval/balanced_acc: 0.9509, eval/precision: 0.9460, eval/recall: 0.9509, eval/F1: 0.9463, lr: 0.0000, train/prefecth_time: 0.0031 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 23:32:44,309 INFO] 108800 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0050, train/total_loss: 0.0052, train/util_ratio: 1.0000, train/run_time: 0.5543, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 23:35:08,491 INFO] 109056 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0090, train/total_loss: 0.0090, train/util_ratio: 1.0000, train/run_time: 0.5571, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-23 23:37:32,548 INFO] 109312 iteration USE_EMA: False, train/sup_loss: 0.0024, train/unsup_loss: 0.0126, train/total_loss: 0.0150, train/util_ratio: 1.0000, train/run_time: 0.5424, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-23 23:39:54,026 INFO] 109568 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0071, train/total_loss: 0.0071, train/util_ratio: 1.0000, train/run_time: 0.5343, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-23 23:43:00,700 INFO] 109824 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0038, train/total_loss: 0.0038, train/util_ratio: 1.0000, train/run_time: 0.5256, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-23 23:45:23,738 INFO] 110080 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0098, train/total_loss: 0.0098, train/util_ratio: 1.0000, train/run_time: 0.5432, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-23 23:47:45,408 INFO] 110336 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0244, train/total_loss: 0.0245, train/util_ratio: 1.0000, train/run_time: 0.5534, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-23 23:50:07,442 INFO] validating...
[2023-08-23 23:50:31,974 INFO] confusion matrix:
[[0.93833333 0.00166667 0.00166667 0.         0.         0.005
  0.05       0.         0.00333333 0.        ]
 [0.         0.89833333 0.00833333 0.         0.         0.09333333
  0.         0.         0.         0.        ]
 [0.         0.01166667 0.78666667 0.00166667 0.         0.065
  0.06166667 0.00666667 0.06666667 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.002      0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.998      0.
  0.         0.         0.         0.        ]
 [0.005      0.0025     0.         0.005      0.         0.9425
  0.0425     0.         0.0025     0.        ]
 [0.002      0.         0.016      0.         0.004      0.
  0.976      0.         0.002      0.        ]
 [0.         0.         0.         0.00333333 0.045      0.
  0.00166667 0.94833333 0.00166667 0.        ]
 [0.00801603 0.         0.         0.00200401 0.         0.
  0.         0.         0.98997996 0.        ]
 [0.01666667 0.00666667 0.01333333 0.         0.         0.00333333
  0.         0.         0.00166667 0.95833333]]
[2023-08-23 23:50:32,885 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-23 23:50:32,886 INFO] 110592 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1491, train/total_loss: 0.1491, train/util_ratio: 1.0000, train/run_time: 0.5577, eval/loss: 0.3181, eval/top-1-acc: 0.9392, eval/balanced_acc: 0.9426, eval/precision: 0.9375, eval/recall: 0.9426, eval/F1: 0.9376, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-23 23:53:36,033 INFO] 110848 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0029, train/total_loss: 0.0030, train/util_ratio: 1.0000, train/run_time: 0.5436, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-23 23:55:58,120 INFO] 111104 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1850, train/total_loss: 0.1851, train/util_ratio: 1.0000, train/run_time: 0.5459, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-23 23:58:20,208 INFO] 111360 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0815, train/total_loss: 0.0816, train/util_ratio: 1.0000, train/run_time: 0.5410, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 00:00:42,525 INFO] 111616 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0173, train/total_loss: 0.0173, train/util_ratio: 1.0000, train/run_time: 0.5254, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 00:03:47,872 INFO] 111872 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.0042, train/total_loss: 0.0052, train/util_ratio: 1.0000, train/run_time: 0.5201, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 00:06:09,505 INFO] 112128 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2137, train/total_loss: 0.2138, train/util_ratio: 0.8750, train/run_time: 0.4913, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 00:08:30,998 INFO] 112384 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1489, train/total_loss: 0.1491, train/util_ratio: 1.0000, train/run_time: 0.4863, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 00:10:54,730 INFO] validating...
[2023-08-24 00:11:19,122 INFO] confusion matrix:
[[0.94       0.00166667 0.         0.         0.         0.005
  0.04833333 0.         0.005      0.        ]
 [0.         0.88666667 0.00333333 0.         0.         0.105
  0.         0.005      0.         0.        ]
 [0.         0.00666667 0.685      0.00166667 0.         0.165
  0.025      0.01       0.10666667 0.        ]
 [0.         0.         0.         0.98       0.008      0.
  0.002      0.         0.01       0.        ]
 [0.         0.         0.         0.         1.         0.
  0.         0.         0.         0.        ]
 [0.0075     0.         0.         0.0025     0.         0.95
  0.04       0.         0.         0.        ]
 [0.004      0.         0.024      0.         0.006      0.
  0.964      0.         0.002      0.        ]
 [0.         0.         0.         0.00333333 0.04       0.
  0.         0.955      0.00166667 0.        ]
 [0.00400802 0.         0.         0.00200401 0.         0.
  0.00200401 0.         0.98997996 0.00200401]
 [0.00666667 0.00166667 0.005      0.         0.         0.00333333
  0.         0.         0.00166667 0.98166667]]
[2023-08-24 00:11:19,933 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 00:11:19,934 INFO] 112640 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0554, train/total_loss: 0.0554, train/util_ratio: 0.8750, train/run_time: 0.5344, eval/loss: 0.3798, eval/top-1-acc: 0.9289, eval/balanced_acc: 0.9332, eval/precision: 0.9293, eval/recall: 0.9332, eval/F1: 0.9260, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 00:14:23,935 INFO] 112896 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0566, train/total_loss: 0.0567, train/util_ratio: 1.0000, train/run_time: 0.4798, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 00:16:45,954 INFO] 113152 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0353, train/total_loss: 0.0354, train/util_ratio: 1.0000, train/run_time: 0.4835, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 00:19:07,748 INFO] 113408 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2311, train/total_loss: 0.2311, train/util_ratio: 0.8750, train/run_time: 0.5184, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 00:21:29,248 INFO] 113664 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1001, train/total_loss: 0.1002, train/util_ratio: 1.0000, train/run_time: 0.4780, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 00:24:33,989 INFO] 113920 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.6848, train/total_loss: 0.6853, train/util_ratio: 1.0000, train/run_time: 0.5434, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 00:26:57,545 INFO] 114176 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1384, train/total_loss: 0.1385, train/util_ratio: 1.0000, train/run_time: 0.5344, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 00:29:19,670 INFO] 114432 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0336, train/total_loss: 0.0337, train/util_ratio: 1.0000, train/run_time: 0.5425, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 00:31:41,643 INFO] validating...
[2023-08-24 00:32:06,138 INFO] confusion matrix:
[[0.92166667 0.00166667 0.005      0.00166667 0.         0.005
  0.06       0.         0.005      0.        ]
 [0.         0.90166667 0.00833333 0.         0.         0.08833333
  0.         0.00166667 0.         0.        ]
 [0.         0.00666667 0.87333333 0.00166667 0.         0.05166667
  0.005      0.00166667 0.06       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.        ]
 [0.01       0.005      0.005      0.0125     0.         0.905
  0.0575     0.         0.005      0.        ]
 [0.004      0.002      0.036      0.012      0.         0.
  0.944      0.         0.002      0.        ]
 [0.         0.         0.         0.01333333 0.06666667 0.
  0.         0.91833333 0.00166667 0.        ]
 [0.00400802 0.         0.         0.00601202 0.         0.
  0.         0.         0.98997996 0.        ]
 [0.00833333 0.00833333 0.00833333 0.00166667 0.         0.00166667
  0.         0.         0.00166667 0.97      ]]
[2023-08-24 00:32:07,172 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 00:32:07,173 INFO] 114688 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0207, train/total_loss: 0.0207, train/util_ratio: 1.0000, train/run_time: 0.5371, eval/loss: 0.3080, eval/top-1-acc: 0.9398, eval/balanced_acc: 0.9414, eval/precision: 0.9366, eval/recall: 0.9414, eval/F1: 0.9378, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 00:35:12,629 INFO] 114944 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2885, train/total_loss: 0.2885, train/util_ratio: 1.0000, train/run_time: 0.5247, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 00:37:35,915 INFO] 115200 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0207, train/total_loss: 0.0208, train/util_ratio: 1.0000, train/run_time: 0.5483, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 00:39:59,151 INFO] 115456 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0465, train/total_loss: 0.0466, train/util_ratio: 1.0000, train/run_time: 0.4889, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 00:42:21,536 INFO] 115712 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.3121, train/total_loss: 0.3128, train/util_ratio: 1.0000, train/run_time: 0.5258, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 00:45:26,764 INFO] 115968 iteration USE_EMA: False, train/sup_loss: 0.0018, train/unsup_loss: 0.0223, train/total_loss: 0.0241, train/util_ratio: 1.0000, train/run_time: 0.5259, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 00:47:49,529 INFO] 116224 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0027, train/total_loss: 0.0027, train/util_ratio: 1.0000, train/run_time: 0.5428, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 00:50:12,201 INFO] 116480 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0377, train/total_loss: 0.0377, train/util_ratio: 1.0000, train/run_time: 0.5438, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 00:52:35,267 INFO] validating...
[2023-08-24 00:52:59,492 INFO] confusion matrix:
[[0.92       0.00166667 0.00666667 0.         0.         0.01
  0.05833333 0.         0.00166667 0.00166667]
 [0.         0.895      0.00333333 0.         0.         0.09666667
  0.         0.00333333 0.         0.00166667]
 [0.         0.01333333 0.82333333 0.005      0.         0.08
  0.015      0.00333333 0.05833333 0.00166667]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.004      0.         0.         0.        ]
 [0.0025     0.0025     0.0025     0.01       0.         0.9475
  0.035      0.         0.         0.        ]
 [0.002      0.002      0.028      0.006      0.         0.
  0.962      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01       0.
  0.         0.985      0.00166667 0.        ]
 [0.00400802 0.         0.         0.00601202 0.         0.
  0.         0.         0.98797595 0.00200401]
 [0.005      0.00166667 0.01       0.         0.         0.00166667
  0.         0.         0.         0.98166667]]
[2023-08-24 00:53:00,489 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 00:53:00,490 INFO] 116736 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0507, train/total_loss: 0.0508, train/util_ratio: 0.8750, train/run_time: 0.4779, eval/loss: 0.3055, eval/top-1-acc: 0.9461, eval/balanced_acc: 0.9486, eval/precision: 0.9438, eval/recall: 0.9486, eval/F1: 0.9443, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 00:56:05,467 INFO] 116992 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0195, train/total_loss: 0.0196, train/util_ratio: 1.0000, train/run_time: 0.5170, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 00:58:27,217 INFO] 117248 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1983, train/total_loss: 0.1983, train/util_ratio: 1.0000, train/run_time: 0.4837, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 01:00:49,089 INFO] 117504 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0916, train/total_loss: 0.0916, train/util_ratio: 1.0000, train/run_time: 0.5351, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 01:03:12,468 INFO] 117760 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0252, train/total_loss: 0.0252, train/util_ratio: 1.0000, train/run_time: 0.5431, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 01:06:16,449 INFO] 118016 iteration USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.0224, train/total_loss: 0.0233, train/util_ratio: 1.0000, train/run_time: 0.5231, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 01:08:39,268 INFO] 118272 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0798, train/total_loss: 0.0799, train/util_ratio: 1.0000, train/run_time: 0.5307, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 01:11:02,647 INFO] 118528 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1921, train/total_loss: 0.1921, train/util_ratio: 0.8750, train/run_time: 0.4951, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 01:13:24,842 INFO] validating...
[2023-08-24 01:13:49,325 INFO] confusion matrix:
[[0.935      0.00166667 0.00333333 0.         0.         0.01
  0.04833333 0.         0.00166667 0.        ]
 [0.         0.90666667 0.00333333 0.         0.         0.08666667
  0.         0.00333333 0.         0.        ]
 [0.         0.04166667 0.84       0.005      0.         0.06166667
  0.02833333 0.01166667 0.01166667 0.        ]
 [0.         0.         0.         0.998      0.         0.
  0.         0.         0.002      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.005      0.005      0.0025     0.01       0.         0.9225
  0.055      0.         0.         0.        ]
 [0.004      0.         0.026      0.006      0.004      0.
  0.96       0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01166667 0.
  0.         0.98666667 0.         0.        ]
 [0.00400802 0.         0.         0.00601202 0.         0.
  0.00200401 0.         0.98797595 0.        ]
 [0.01166667 0.01833333 0.00833333 0.         0.         0.00666667
  0.         0.         0.00166667 0.95333333]]
[2023-08-24 01:13:50,160 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 01:13:50,161 INFO] 118784 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0011, train/total_loss: 0.0011, train/util_ratio: 1.0000, train/run_time: 0.4839, eval/loss: 0.2948, eval/top-1-acc: 0.9467, eval/balanced_acc: 0.9484, eval/precision: 0.9445, eval/recall: 0.9484, eval/F1: 0.9452, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 01:16:55,536 INFO] 119040 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0027, train/total_loss: 0.0027, train/util_ratio: 1.0000, train/run_time: 0.5418, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-24 01:19:19,873 INFO] 119296 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2368, train/total_loss: 0.2368, train/util_ratio: 1.0000, train/run_time: 0.5465, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 01:21:44,728 INFO] 119552 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2977, train/total_loss: 0.2978, train/util_ratio: 1.0000, train/run_time: 0.5396, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 01:24:07,725 INFO] 119808 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0043, train/total_loss: 0.0043, train/util_ratio: 1.0000, train/run_time: 0.5386, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 01:27:11,998 INFO] 120064 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2487, train/total_loss: 0.2487, train/util_ratio: 1.0000, train/run_time: 0.4801, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 01:29:35,486 INFO] 120320 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3131, train/total_loss: 0.3131, train/util_ratio: 0.8750, train/run_time: 0.5369, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 01:31:58,094 INFO] 120576 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0113, train/total_loss: 0.0114, train/util_ratio: 1.0000, train/run_time: 0.5461, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 01:34:20,366 INFO] validating...
[2023-08-24 01:34:44,841 INFO] confusion matrix:
[[0.95833333 0.00166667 0.005      0.         0.         0.00333333
  0.03       0.         0.00166667 0.        ]
 [0.         0.895      0.00333333 0.00166667 0.         0.09166667
  0.         0.005      0.         0.00333333]
 [0.00166667 0.01333333 0.865      0.00666667 0.         0.025
  0.01666667 0.00333333 0.06666667 0.00166667]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.         0.002      0.         0.        ]
 [0.015      0.0075     0.0025     0.015      0.         0.89
  0.065      0.         0.005      0.        ]
 [0.01       0.         0.034      0.006      0.004      0.
  0.944      0.         0.002      0.        ]
 [0.         0.         0.         0.005      0.00666667 0.
  0.         0.98666667 0.00166667 0.        ]
 [0.00601202 0.         0.         0.00400802 0.         0.
  0.         0.         0.98997996 0.        ]
 [0.00833333 0.005      0.00333333 0.         0.         0.00333333
  0.         0.         0.00166667 0.97833333]]
[2023-08-24 01:34:45,863 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 01:34:45,864 INFO] 120832 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2942, train/total_loss: 0.2943, train/util_ratio: 1.0000, train/run_time: 0.4778, eval/loss: 0.2794, eval/top-1-acc: 0.9496, eval/balanced_acc: 0.9497, eval/precision: 0.9463, eval/recall: 0.9497, eval/F1: 0.9472, lr: 0.0000, train/prefecth_time: 0.0023 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 01:37:50,250 INFO] 121088 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.8127, train/total_loss: 0.8129, train/util_ratio: 0.8750, train/run_time: 0.4781, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 01:40:12,955 INFO] 121344 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1664, train/total_loss: 0.1665, train/util_ratio: 1.0000, train/run_time: 0.4846, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 01:42:36,295 INFO] 121600 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0499, train/total_loss: 0.0500, train/util_ratio: 1.0000, train/run_time: 0.4986, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 01:44:58,945 INFO] 121856 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1601, train/total_loss: 0.1601, train/util_ratio: 1.0000, train/run_time: 0.5102, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 01:48:03,967 INFO] 122112 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0019, train/total_loss: 0.0019, train/util_ratio: 1.0000, train/run_time: 0.5387, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-24 01:50:25,301 INFO] 122368 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0117, train/total_loss: 0.0118, train/util_ratio: 1.0000, train/run_time: 0.5333, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 01:52:47,158 INFO] 122624 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1722, train/total_loss: 0.1723, train/util_ratio: 0.8750, train/run_time: 0.5196, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 01:55:08,936 INFO] validating...
[2023-08-24 01:55:33,197 INFO] confusion matrix:
[[0.92166667 0.00166667 0.005      0.         0.         0.00666667
  0.06333333 0.         0.00166667 0.        ]
 [0.         0.90166667 0.00333333 0.         0.         0.08833333
  0.         0.005      0.         0.00166667]
 [0.         0.03166667 0.84666667 0.00666667 0.         0.085
  0.01166667 0.00666667 0.01166667 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.         0.002      0.         0.        ]
 [0.005      0.005      0.0025     0.01       0.         0.93
  0.045      0.         0.0025     0.        ]
 [0.002      0.         0.034      0.002      0.006      0.002
  0.95       0.004      0.         0.        ]
 [0.         0.         0.         0.00333333 0.01       0.
  0.         0.98666667 0.         0.        ]
 [0.00400802 0.         0.         0.01803607 0.         0.
  0.         0.         0.97795591 0.        ]
 [0.00833333 0.01       0.00333333 0.00166667 0.         0.00333333
  0.         0.00166667 0.         0.97166667]]
[2023-08-24 01:55:34,104 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 01:55:34,105 INFO] 122880 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0064, train/total_loss: 0.0065, train/util_ratio: 1.0000, train/run_time: 0.5388, eval/loss: 0.2921, eval/top-1-acc: 0.9461, eval/balanced_acc: 0.9478, eval/precision: 0.9437, eval/recall: 0.9478, eval/F1: 0.9444, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 01:58:36,999 INFO] 123136 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.4665, train/total_loss: 0.4665, train/util_ratio: 1.0000, train/run_time: 0.5432, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 02:00:58,251 INFO] 123392 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1465, train/total_loss: 0.1466, train/util_ratio: 0.8750, train/run_time: 0.5400, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 02:03:19,422 INFO] 123648 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1004, train/total_loss: 0.1004, train/util_ratio: 1.0000, train/run_time: 0.5109, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 02:05:40,809 INFO] 123904 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0222, train/total_loss: 0.0222, train/util_ratio: 0.8750, train/run_time: 0.4852, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 02:08:44,945 INFO] 124160 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1287, train/total_loss: 0.1287, train/util_ratio: 1.0000, train/run_time: 0.5413, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 02:11:07,192 INFO] 124416 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0383, train/total_loss: 0.0383, train/util_ratio: 1.0000, train/run_time: 0.5254, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 02:13:28,826 INFO] 124672 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0167, train/total_loss: 0.0169, train/util_ratio: 1.0000, train/run_time: 0.5408, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 02:15:49,453 INFO] validating...
[2023-08-24 02:16:14,252 INFO] confusion matrix:
[[0.93666667 0.00166667 0.005      0.         0.         0.00833333
  0.04666667 0.         0.00166667 0.        ]
 [0.         0.90166667 0.00333333 0.         0.         0.09166667
  0.         0.00333333 0.         0.        ]
 [0.         0.04666667 0.82166667 0.00333333 0.         0.07833333
  0.01166667 0.01       0.02833333 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.         0.004      0.         0.        ]
 [0.         0.         0.0025     0.005      0.         0.9525
  0.0375     0.         0.0025     0.        ]
 [0.002      0.         0.034      0.         0.         0.
  0.964      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.005      0.
  0.         0.99333333 0.         0.        ]
 [0.00400802 0.         0.         0.01002004 0.         0.
  0.00200401 0.         0.98396794 0.        ]
 [0.00833333 0.035      0.01       0.         0.         0.005
  0.         0.00166667 0.         0.94      ]]
[2023-08-24 02:16:15,148 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 02:16:15,149 INFO] 124928 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1477, train/total_loss: 0.1477, train/util_ratio: 1.0000, train/run_time: 0.4787, eval/loss: 0.3196, eval/top-1-acc: 0.9455, eval/balanced_acc: 0.9484, eval/precision: 0.9439, eval/recall: 0.9484, eval/F1: 0.9445, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 02:19:18,862 INFO] 125184 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0119, train/total_loss: 0.0119, train/util_ratio: 1.0000, train/run_time: 0.5537, lr: 0.0000, train/prefecth_time: 0.0045 
[2023-08-24 02:21:41,443 INFO] 125440 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0025, train/total_loss: 0.0028, train/util_ratio: 0.8750, train/run_time: 0.4798, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 02:24:04,815 INFO] 125696 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2427, train/total_loss: 0.2428, train/util_ratio: 1.0000, train/run_time: 0.5687, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 02:26:27,065 INFO] 125952 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2167, train/total_loss: 0.2167, train/util_ratio: 1.0000, train/run_time: 0.4768, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 02:29:30,670 INFO] 126208 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.6134, train/total_loss: 0.6135, train/util_ratio: 1.0000, train/run_time: 0.5453, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 02:31:53,514 INFO] 126464 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0044, train/total_loss: 0.0044, train/util_ratio: 1.0000, train/run_time: 0.5422, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 02:34:17,292 INFO] 126720 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2995, train/total_loss: 0.2995, train/util_ratio: 1.0000, train/run_time: 0.5420, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 02:36:40,326 INFO] validating...
[2023-08-24 02:37:04,414 INFO] confusion matrix:
[[0.94       0.00166667 0.00333333 0.         0.         0.00333333
  0.04833333 0.         0.00333333 0.        ]
 [0.         0.9        0.00333333 0.         0.         0.09333333
  0.         0.00333333 0.         0.        ]
 [0.         0.035      0.81833333 0.00333333 0.         0.07666667
  0.00666667 0.01       0.05       0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.         0.002      0.         0.        ]
 [0.005      0.         0.0075     0.0075     0.         0.9525
  0.0225     0.         0.005      0.        ]
 [0.002      0.         0.048      0.         0.002      0.
  0.946      0.         0.002      0.        ]
 [0.         0.         0.         0.00166667 0.01       0.
  0.         0.98833333 0.         0.        ]
 [0.00400802 0.         0.         0.00400802 0.         0.
  0.00200401 0.         0.98997996 0.        ]
 [0.00833333 0.01166667 0.00166667 0.         0.         0.005
  0.         0.         0.00333333 0.97      ]]
[2023-08-24 02:37:05,243 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 02:37:05,244 INFO] 126976 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0827, train/total_loss: 0.0828, train/util_ratio: 0.8750, train/run_time: 0.4849, eval/loss: 0.2947, eval/top-1-acc: 0.9468, eval/balanced_acc: 0.9493, eval/precision: 0.9445, eval/recall: 0.9493, eval/F1: 0.9453, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 02:40:09,942 INFO] 127232 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1916, train/total_loss: 0.1917, train/util_ratio: 1.0000, train/run_time: 0.5460, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 02:42:31,481 INFO] 127488 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0282, train/total_loss: 0.0282, train/util_ratio: 1.0000, train/run_time: 0.5288, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 02:44:54,935 INFO] 127744 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0347, train/total_loss: 0.0348, train/util_ratio: 1.0000, train/run_time: 0.5429, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 02:47:16,527 INFO] 128000 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0085, train/total_loss: 0.0085, train/util_ratio: 1.0000, train/run_time: 0.5322, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 02:50:21,393 INFO] 128256 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2712, train/total_loss: 0.2712, train/util_ratio: 1.0000, train/run_time: 0.4763, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-24 02:52:41,612 INFO] 128512 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0006, train/total_loss: 0.0007, train/util_ratio: 1.0000, train/run_time: 0.5416, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 02:55:03,071 INFO] 128768 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1069, train/total_loss: 0.1069, train/util_ratio: 1.0000, train/run_time: 0.5410, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 02:57:24,638 INFO] validating...
[2023-08-24 02:57:49,333 INFO] confusion matrix:
[[0.935      0.00166667 0.00333333 0.00166667 0.         0.005
  0.05       0.         0.00166667 0.00166667]
 [0.         0.89666667 0.005      0.         0.         0.095
  0.         0.00333333 0.         0.        ]
 [0.         0.01833333 0.86       0.00166667 0.         0.04166667
  0.03333333 0.00833333 0.03666667 0.        ]
 [0.         0.         0.         0.996      0.002      0.
  0.         0.         0.002      0.        ]
 [0.         0.         0.         0.002      0.998      0.
  0.         0.         0.         0.        ]
 [0.005      0.0025     0.         0.0075     0.         0.92
  0.065      0.         0.         0.        ]
 [0.006      0.         0.036      0.         0.         0.
  0.958      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.02       0.
  0.         0.97833333 0.         0.        ]
 [0.00601202 0.         0.         0.00601202 0.         0.
  0.         0.         0.98797595 0.        ]
 [0.00666667 0.00666667 0.00666667 0.         0.         0.00333333
  0.         0.         0.         0.97666667]]
[2023-08-24 02:57:50,210 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 02:57:50,212 INFO] 129024 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2464, train/total_loss: 0.2464, train/util_ratio: 1.0000, train/run_time: 0.4855, eval/loss: 0.2692, eval/top-1-acc: 0.9492, eval/balanced_acc: 0.9507, eval/precision: 0.9466, eval/recall: 0.9507, eval/F1: 0.9475, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 03:00:55,089 INFO] 129280 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0271, train/total_loss: 0.0271, train/util_ratio: 1.0000, train/run_time: 0.5258, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 03:03:17,199 INFO] 129536 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0047, train/total_loss: 0.0047, train/util_ratio: 0.7500, train/run_time: 0.5391, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 03:05:40,811 INFO] 129792 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2260, train/total_loss: 0.2261, train/util_ratio: 1.0000, train/run_time: 0.5264, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 03:08:03,762 INFO] 130048 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0378, train/total_loss: 0.0378, train/util_ratio: 1.0000, train/run_time: 0.5269, lr: 0.0000, train/prefecth_time: 0.0023 
[2023-08-24 03:11:08,529 INFO] 130304 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0499, train/total_loss: 0.0499, train/util_ratio: 1.0000, train/run_time: 0.5059, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 03:13:29,646 INFO] 130560 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0459, train/total_loss: 0.0459, train/util_ratio: 0.8750, train/run_time: 0.5349, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 03:15:51,061 INFO] 130816 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1634, train/total_loss: 0.1634, train/util_ratio: 1.0000, train/run_time: 0.5284, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 03:18:12,619 INFO] validating...
[2023-08-24 03:18:37,179 INFO] confusion matrix:
[[0.95666667 0.00166667 0.00166667 0.         0.         0.005
  0.03333333 0.         0.00166667 0.        ]
 [0.         0.89333333 0.00333333 0.         0.         0.1
  0.         0.00333333 0.         0.        ]
 [0.         0.01666667 0.79       0.00666667 0.         0.07666667
  0.025      0.00666667 0.07833333 0.        ]
 [0.         0.         0.         0.998      0.         0.
  0.         0.         0.002      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0125     0.0025     0.         0.0075     0.         0.945
  0.0275     0.         0.005      0.        ]
 [0.01       0.         0.034      0.         0.         0.002
  0.952      0.         0.002      0.        ]
 [0.         0.         0.         0.005      0.01       0.
  0.         0.98333333 0.00166667 0.        ]
 [0.00601202 0.         0.         0.00801603 0.         0.
  0.         0.         0.98597194 0.        ]
 [0.01       0.01       0.005      0.         0.         0.005
  0.         0.         0.         0.97      ]]
[2023-08-24 03:18:38,100 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 03:18:38,101 INFO] 131072 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0177, train/total_loss: 0.0177, train/util_ratio: 1.0000, train/run_time: 0.4777, eval/loss: 0.2977, eval/top-1-acc: 0.9442, eval/balanced_acc: 0.9468, eval/precision: 0.9419, eval/recall: 0.9468, eval/F1: 0.9423, lr: 0.0000, train/prefecth_time: 0.0023 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 03:21:42,187 INFO] 131328 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2202, train/total_loss: 0.2202, train/util_ratio: 1.0000, train/run_time: 0.4827, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 03:24:04,216 INFO] 131584 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.7581, train/total_loss: 0.7581, train/util_ratio: 1.0000, train/run_time: 0.5309, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 03:26:26,457 INFO] 131840 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3248, train/total_loss: 0.3248, train/util_ratio: 1.0000, train/run_time: 0.5338, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 03:28:48,727 INFO] 132096 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1331, train/total_loss: 0.1331, train/util_ratio: 0.8750, train/run_time: 0.5381, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 03:31:52,735 INFO] 132352 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 1.0041, train/total_loss: 1.0041, train/util_ratio: 1.0000, train/run_time: 0.5601, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 03:34:15,593 INFO] 132608 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.7548, train/total_loss: 0.7548, train/util_ratio: 1.0000, train/run_time: 0.5594, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 03:36:39,116 INFO] 132864 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0024, train/total_loss: 0.0025, train/util_ratio: 1.0000, train/run_time: 0.5428, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 03:38:59,652 INFO] validating...
[2023-08-24 03:39:24,220 INFO] confusion matrix:
[[0.95166667 0.00166667 0.         0.         0.         0.005
  0.03833333 0.         0.00333333 0.        ]
 [0.         0.88833333 0.00166667 0.         0.         0.10333333
  0.         0.00666667 0.         0.        ]
 [0.         0.01       0.77       0.005      0.         0.08333333
  0.04666667 0.01333333 0.07166667 0.        ]
 [0.         0.         0.         0.998      0.         0.
  0.         0.         0.002      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.01       0.         0.         0.0075     0.         0.94
  0.035      0.         0.0075     0.        ]
 [0.006      0.         0.028      0.         0.         0.002
  0.964      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.00666667 0.
  0.         0.99       0.         0.        ]
 [0.00400802 0.         0.         0.00601202 0.         0.
  0.00200401 0.         0.98797595 0.        ]
 [0.01666667 0.01166667 0.00833333 0.00166667 0.         0.005
  0.         0.00166667 0.00833333 0.94666667]]
[2023-08-24 03:39:25,199 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 03:39:25,200 INFO] 133120 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0051, train/total_loss: 0.0051, train/util_ratio: 1.0000, train/run_time: 0.5376, eval/loss: 0.3406, eval/top-1-acc: 0.9398, eval/balanced_acc: 0.9429, eval/precision: 0.9382, eval/recall: 0.9429, eval/F1: 0.9378, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 03:42:29,541 INFO] 133376 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1317, train/total_loss: 0.1317, train/util_ratio: 0.7500, train/run_time: 0.5563, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 03:44:51,928 INFO] 133632 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0789, train/total_loss: 0.0789, train/util_ratio: 1.0000, train/run_time: 0.5408, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 03:47:13,977 INFO] 133888 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1189, train/total_loss: 0.1189, train/util_ratio: 1.0000, train/run_time: 0.5401, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 03:49:35,109 INFO] 134144 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1339, train/total_loss: 0.1340, train/util_ratio: 1.0000, train/run_time: 0.5340, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 03:52:40,199 INFO] 134400 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0288, train/total_loss: 0.0288, train/util_ratio: 1.0000, train/run_time: 0.5485, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 03:55:02,979 INFO] 134656 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1682, train/total_loss: 0.1683, train/util_ratio: 0.8750, train/run_time: 0.5533, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 03:57:24,570 INFO] 134912 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.2010, train/total_loss: 0.2011, train/util_ratio: 1.0000, train/run_time: 0.5113, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 03:59:47,658 INFO] validating...
[2023-08-24 04:00:11,958 INFO] confusion matrix:
[[0.92833333 0.00166667 0.00333333 0.         0.         0.005
  0.05666667 0.         0.005      0.        ]
 [0.         0.89333333 0.00333333 0.         0.         0.09833333
  0.         0.005      0.         0.        ]
 [0.         0.01666667 0.78833333 0.00833333 0.         0.05333333
  0.05       0.00666667 0.07666667 0.        ]
 [0.         0.         0.         0.998      0.         0.
  0.         0.         0.002      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0125     0.         0.         0.005      0.         0.9175
  0.0575     0.         0.0075     0.        ]
 [0.006      0.         0.02       0.         0.004      0.
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.00666667 0.
  0.         0.99       0.         0.        ]
 [0.00400802 0.         0.         0.01603206 0.         0.
  0.         0.         0.97995992 0.        ]
 [0.00666667 0.01333333 0.00333333 0.00166667 0.         0.00166667
  0.         0.         0.00333333 0.97      ]]
[2023-08-24 04:00:13,015 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 04:00:13,016 INFO] 135168 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2622, train/total_loss: 0.2622, train/util_ratio: 1.0000, train/run_time: 0.5374, eval/loss: 0.3241, eval/top-1-acc: 0.9407, eval/balanced_acc: 0.9429, eval/precision: 0.9386, eval/recall: 0.9429, eval/F1: 0.9386, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 04:03:16,268 INFO] 135424 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0511, train/total_loss: 0.0512, train/util_ratio: 1.0000, train/run_time: 0.5473, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 04:05:38,947 INFO] 135680 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0077, train/total_loss: 0.0077, train/util_ratio: 1.0000, train/run_time: 0.5193, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 04:08:00,604 INFO] 135936 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3036, train/total_loss: 0.3036, train/util_ratio: 1.0000, train/run_time: 0.5318, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 04:10:22,683 INFO] 136192 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1347, train/total_loss: 0.1347, train/util_ratio: 1.0000, train/run_time: 0.5398, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 04:13:27,821 INFO] 136448 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0056, train/total_loss: 0.0056, train/util_ratio: 1.0000, train/run_time: 0.5791, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-24 04:15:49,828 INFO] 136704 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0049, train/total_loss: 0.0050, train/util_ratio: 1.0000, train/run_time: 0.5908, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 04:18:13,359 INFO] 136960 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2986, train/total_loss: 0.2986, train/util_ratio: 0.8750, train/run_time: 0.5460, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 04:20:36,050 INFO] validating...
[2023-08-24 04:21:00,094 INFO] confusion matrix:
[[0.93666667 0.00166667 0.00333333 0.         0.         0.00833333
  0.04666667 0.         0.00333333 0.        ]
 [0.         0.86166667 0.00333333 0.         0.         0.13
  0.         0.005      0.         0.        ]
 [0.         0.02       0.83666667 0.005      0.         0.08166667
  0.03       0.01       0.01666667 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.002      0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.         0.         0.01       0.         0.9575
  0.0225     0.         0.005      0.        ]
 [0.004      0.         0.028      0.         0.         0.002
  0.966      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.00833333 0.
  0.         0.98833333 0.         0.        ]
 [0.00400802 0.         0.         0.01402806 0.         0.
  0.00200401 0.         0.97995992 0.        ]
 [0.00833333 0.00833333 0.         0.         0.         0.00333333
  0.         0.         0.005      0.975     ]]
[2023-08-24 04:21:00,866 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 04:21:00,867 INFO] 137216 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0233, train/total_loss: 0.0233, train/util_ratio: 1.0000, train/run_time: 0.5376, eval/loss: 0.3104, eval/top-1-acc: 0.9455, eval/balanced_acc: 0.9484, eval/precision: 0.9442, eval/recall: 0.9484, eval/F1: 0.9439, lr: 0.0000, train/prefecth_time: 0.0046 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 04:24:04,890 INFO] 137472 iteration USE_EMA: False, train/sup_loss: 0.0004, train/unsup_loss: 0.7754, train/total_loss: 0.7757, train/util_ratio: 1.0000, train/run_time: 0.5390, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 04:26:26,273 INFO] 137728 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0044, train/total_loss: 0.0046, train/util_ratio: 1.0000, train/run_time: 0.4827, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 04:28:48,449 INFO] 137984 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2129, train/total_loss: 0.2129, train/util_ratio: 1.0000, train/run_time: 0.5110, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 04:31:11,360 INFO] 138240 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1602, train/total_loss: 0.1602, train/util_ratio: 0.8750, train/run_time: 0.5375, lr: 0.0000, train/prefecth_time: 0.0023 
[2023-08-24 04:34:17,141 INFO] 138496 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0057, train/total_loss: 0.0057, train/util_ratio: 1.0000, train/run_time: 0.5037, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 04:36:41,029 INFO] 138752 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: 0.0006, train/util_ratio: 1.0000, train/run_time: 0.5305, lr: 0.0000, train/prefecth_time: 0.0042 
[2023-08-24 04:39:04,060 INFO] 139008 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0076, train/total_loss: 0.0076, train/util_ratio: 1.0000, train/run_time: 0.5423, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 04:41:27,610 INFO] validating...
[2023-08-24 04:41:52,077 INFO] confusion matrix:
[[0.945      0.00166667 0.00166667 0.         0.         0.005
  0.04333333 0.         0.00333333 0.        ]
 [0.         0.9        0.00333333 0.         0.         0.09166667
  0.         0.005      0.         0.        ]
 [0.         0.01833333 0.82666667 0.00666667 0.00166667 0.045
  0.04666667 0.01333333 0.04166667 0.        ]
 [0.         0.         0.         0.998      0.         0.
  0.         0.         0.002      0.        ]
 [0.         0.         0.         0.002      0.998      0.
  0.         0.         0.         0.        ]
 [0.01       0.0025     0.         0.0175     0.         0.92
  0.0425     0.         0.0075     0.        ]
 [0.004      0.         0.026      0.002      0.004      0.
  0.964      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01666667 0.
  0.         0.98       0.         0.        ]
 [0.00400802 0.         0.         0.01402806 0.         0.
  0.00200401 0.         0.97995992 0.        ]
 [0.01       0.00666667 0.00333333 0.00166667 0.         0.00166667
  0.         0.00166667 0.00166667 0.97333333]]
[2023-08-24 04:41:53,217 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 04:41:53,219 INFO] 139264 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0678, train/total_loss: 0.0679, train/util_ratio: 1.0000, train/run_time: 0.5379, eval/loss: 0.2737, eval/top-1-acc: 0.9468, eval/balanced_acc: 0.9485, eval/precision: 0.9440, eval/recall: 0.9485, eval/F1: 0.9449, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 04:44:58,834 INFO] 139520 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0096, train/total_loss: 0.0097, train/util_ratio: 1.0000, train/run_time: 0.5377, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 04:47:21,389 INFO] 139776 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0007, train/total_loss: 0.0008, train/util_ratio: 0.8750, train/run_time: 0.4786, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 04:49:42,744 INFO] 140032 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1677, train/total_loss: 0.1678, train/util_ratio: 0.8750, train/run_time: 0.4928, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 04:52:05,609 INFO] 140288 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3668, train/total_loss: 0.3668, train/util_ratio: 1.0000, train/run_time: 0.4851, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 04:55:10,915 INFO] 140544 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0119, train/total_loss: 0.0120, train/util_ratio: 1.0000, train/run_time: 0.4776, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 04:57:33,487 INFO] 140800 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0271, train/total_loss: 0.0271, train/util_ratio: 1.0000, train/run_time: 0.5263, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-24 04:59:56,003 INFO] 141056 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0438, train/total_loss: 0.0438, train/util_ratio: 1.0000, train/run_time: 0.4781, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 05:02:18,512 INFO] validating...
[2023-08-24 05:02:43,014 INFO] confusion matrix:
[[0.94166667 0.         0.00333333 0.         0.         0.005
  0.04666667 0.00166667 0.00166667 0.        ]
 [0.         0.87833333 0.00166667 0.         0.         0.11
  0.         0.01       0.         0.        ]
 [0.         0.01666667 0.85166667 0.005      0.         0.07
  0.02       0.01333333 0.02333333 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.004      0.         0.         0.        ]
 [0.0075     0.         0.0025     0.0075     0.         0.96
  0.015      0.         0.0075     0.        ]
 [0.004      0.         0.034      0.002      0.         0.
  0.96       0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01166667 0.
  0.         0.98666667 0.         0.        ]
 [0.00400802 0.         0.         0.01202405 0.         0.00200401
  0.00200401 0.         0.97995992 0.        ]
 [0.00833333 0.005      0.00333333 0.         0.         0.005
  0.         0.00166667 0.00833333 0.96833333]]
[2023-08-24 05:02:43,830 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 05:02:43,831 INFO] 141312 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0076, train/total_loss: 0.0076, train/util_ratio: 0.8750, train/run_time: 0.4794, eval/loss: 0.3043, eval/top-1-acc: 0.9489, eval/balanced_acc: 0.9515, eval/precision: 0.9469, eval/recall: 0.9515, eval/F1: 0.9474, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9504, at 77824 iters
[2023-08-24 05:05:48,363 INFO] 141568 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: 0.0006, train/util_ratio: 1.0000, train/run_time: 0.5219, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 05:08:11,582 INFO] 141824 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1763, train/total_loss: 0.1764, train/util_ratio: 1.0000, train/run_time: 0.5381, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 05:10:33,405 INFO] 142080 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1292, train/total_loss: 0.1292, train/util_ratio: 1.0000, train/run_time: 0.5344, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 05:12:56,791 INFO] 142336 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0660, train/total_loss: 0.0660, train/util_ratio: 1.0000, train/run_time: 0.4779, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 05:16:03,286 INFO] 142592 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0120, train/total_loss: 0.0121, train/util_ratio: 1.0000, train/run_time: 0.5384, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 05:18:25,293 INFO] 142848 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0252, train/total_loss: 0.0252, train/util_ratio: 0.8750, train/run_time: 0.5440, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 05:20:48,109 INFO] 143104 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0377, train/total_loss: 0.0377, train/util_ratio: 1.0000, train/run_time: 0.5422, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 05:23:10,317 INFO] validating...
[2023-08-24 05:23:34,601 INFO] confusion matrix:
[[0.95166667 0.00166667 0.00333333 0.         0.         0.01166667
  0.03       0.         0.00166667 0.        ]
 [0.         0.88       0.00166667 0.         0.         0.11333333
  0.         0.005      0.         0.        ]
 [0.         0.01166667 0.86333333 0.00166667 0.         0.09666667
  0.00666667 0.00833333 0.01166667 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.0025     0.         0.005      0.005      0.         0.985
  0.0025     0.         0.         0.        ]
 [0.006      0.         0.048      0.002      0.002      0.002
  0.94       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01       0.
  0.         0.98666667 0.         0.        ]
 [0.00400802 0.         0.         0.01202405 0.         0.00200401
  0.00200401 0.         0.97795591 0.00200401]
 [0.00666667 0.00666667 0.         0.         0.         0.00166667
  0.         0.00166667 0.00166667 0.98166667]]
[2023-08-24 05:23:35,551 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 05:23:36,895 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-24 05:23:36,896 INFO] 143360 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0010, train/total_loss: 0.0010, train/util_ratio: 1.0000, train/run_time: 0.5385, eval/loss: 0.2968, eval/top-1-acc: 0.9528, eval/balanced_acc: 0.9554, eval/precision: 0.9519, eval/recall: 0.9554, eval/F1: 0.9515, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9528, at 143360 iters
[2023-08-24 05:26:39,989 INFO] 143616 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0013, train/total_loss: 0.0013, train/util_ratio: 0.8750, train/run_time: 0.5327, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 05:29:02,046 INFO] 143872 iteration USE_EMA: False, train/sup_loss: 0.0455, train/unsup_loss: 0.0279, train/total_loss: 0.0735, train/util_ratio: 1.0000, train/run_time: 0.5418, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 05:31:23,745 INFO] 144128 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3534, train/total_loss: 0.3534, train/util_ratio: 1.0000, train/run_time: 0.5110, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 05:33:44,698 INFO] 144384 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: 0.0002, train/util_ratio: 1.0000, train/run_time: 0.5300, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 05:36:49,036 INFO] 144640 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1043, train/total_loss: 0.1043, train/util_ratio: 1.0000, train/run_time: 0.4808, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 05:39:10,744 INFO] 144896 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0052, train/total_loss: 0.0052, train/util_ratio: 0.8750, train/run_time: 0.5440, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 05:41:32,526 INFO] 145152 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3237, train/total_loss: 0.3237, train/util_ratio: 1.0000, train/run_time: 0.5383, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 05:43:53,380 INFO] validating...
[2023-08-24 05:44:17,587 INFO] confusion matrix:
[[0.95666667 0.00166667 0.00333333 0.         0.         0.00666667
  0.02666667 0.         0.005      0.        ]
 [0.         0.88666667 0.         0.         0.         0.10166667
  0.         0.01166667 0.         0.        ]
 [0.         0.015      0.78833333 0.00333333 0.         0.09666667
  0.04       0.045      0.01166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.         0.         0.0075     0.         0.9675
  0.015      0.         0.005      0.        ]
 [0.008      0.         0.026      0.         0.         0.002
  0.96       0.004      0.         0.        ]
 [0.         0.         0.         0.00166667 0.005      0.
  0.         0.99333333 0.         0.        ]
 [0.00400802 0.         0.         0.01202405 0.         0.
  0.00200401 0.         0.98196393 0.        ]
 [0.01       0.00833333 0.00333333 0.         0.         0.00333333
  0.         0.00166667 0.00166667 0.97166667]]
[2023-08-24 05:44:18,478 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 05:44:18,479 INFO] 145408 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0245, train/total_loss: 0.0245, train/util_ratio: 0.8750, train/run_time: 0.4788, eval/loss: 0.3107, eval/top-1-acc: 0.9459, eval/balanced_acc: 0.9490, eval/precision: 0.9451, eval/recall: 0.9490, eval/F1: 0.9444, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9528, at 143360 iters
[2023-08-24 05:47:21,811 INFO] 145664 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0714, train/total_loss: 0.0715, train/util_ratio: 1.0000, train/run_time: 0.4809, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 05:49:43,520 INFO] 145920 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3494, train/total_loss: 0.3494, train/util_ratio: 1.0000, train/run_time: 0.5379, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 05:52:05,937 INFO] 146176 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1233, train/total_loss: 0.1233, train/util_ratio: 0.8750, train/run_time: 0.5454, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 05:54:26,489 INFO] 146432 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0846, train/total_loss: 0.0847, train/util_ratio: 1.0000, train/run_time: 0.4798, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 05:57:29,377 INFO] 146688 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0666, train/total_loss: 0.0667, train/util_ratio: 1.0000, train/run_time: 0.5452, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 05:59:50,121 INFO] 146944 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3894, train/total_loss: 0.3895, train/util_ratio: 1.0000, train/run_time: 0.5464, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 06:02:11,965 INFO] 147200 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0009, train/total_loss: 0.0009, train/util_ratio: 1.0000, train/run_time: 0.5427, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 06:04:33,570 INFO] validating...
[2023-08-24 06:04:57,879 INFO] confusion matrix:
[[0.93       0.00166667 0.00333333 0.         0.         0.00666667
  0.05666667 0.         0.00166667 0.        ]
 [0.         0.895      0.00166667 0.         0.         0.095
  0.         0.00833333 0.         0.        ]
 [0.         0.01166667 0.88833333 0.00333333 0.         0.05666667
  0.01833333 0.015      0.00666667 0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.002      0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.         0.0025     0.01       0.         0.955
  0.0225     0.         0.005      0.        ]
 [0.004      0.         0.032      0.004      0.         0.
  0.96       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.00666667 0.
  0.         0.99       0.         0.        ]
 [0.00400802 0.         0.         0.01803607 0.         0.
  0.00200401 0.         0.9759519  0.        ]
 [0.00833333 0.00833333 0.00833333 0.         0.         0.00333333
  0.         0.00166667 0.00333333 0.96666667]]
[2023-08-24 06:04:58,971 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 06:04:58,972 INFO] 147456 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0070, train/total_loss: 0.0070, train/util_ratio: 1.0000, train/run_time: 0.5416, eval/loss: 0.2750, eval/top-1-acc: 0.9524, eval/balanced_acc: 0.9543, eval/precision: 0.9503, eval/recall: 0.9543, eval/F1: 0.9510, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9528, at 143360 iters
[2023-08-24 06:08:03,471 INFO] 147712 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1582, train/total_loss: 0.1583, train/util_ratio: 1.0000, train/run_time: 0.5103, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 06:10:25,372 INFO] 147968 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1711, train/total_loss: 0.1711, train/util_ratio: 1.0000, train/run_time: 0.5428, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 06:12:45,878 INFO] 148224 iteration USE_EMA: False, train/sup_loss: 0.0007, train/unsup_loss: 0.0024, train/total_loss: 0.0032, train/util_ratio: 1.0000, train/run_time: 0.5323, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 06:15:08,064 INFO] 148480 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0011, train/total_loss: 0.0012, train/util_ratio: 1.0000, train/run_time: 0.4828, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 06:18:13,303 INFO] 148736 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0048, train/total_loss: 0.0049, train/util_ratio: 1.0000, train/run_time: 0.5266, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-24 06:20:35,444 INFO] 148992 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.5125, train/total_loss: 0.5126, train/util_ratio: 1.0000, train/run_time: 0.5348, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 06:22:57,763 INFO] 149248 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2829, train/total_loss: 0.2830, train/util_ratio: 1.0000, train/run_time: 0.5559, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 06:25:18,655 INFO] validating...
[2023-08-24 06:25:43,109 INFO] confusion matrix:
[[0.94666667 0.00166667 0.00333333 0.         0.         0.00833333
  0.03333333 0.         0.00666667 0.        ]
 [0.         0.9        0.         0.         0.         0.09
  0.         0.01       0.         0.        ]
 [0.         0.01666667 0.85666667 0.00333333 0.         0.065
  0.01       0.03166667 0.01666667 0.        ]
 [0.         0.         0.         0.988      0.         0.
  0.002      0.         0.01       0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.005      0.0025     0.01       0.         0.955
  0.015      0.         0.0075     0.        ]
 [0.006      0.         0.032      0.004      0.002      0.
  0.952      0.004      0.         0.        ]
 [0.         0.         0.         0.00666667 0.00833333 0.
  0.         0.985      0.         0.        ]
 [0.00400802 0.         0.         0.01202405 0.         0.
  0.00200401 0.         0.98196393 0.        ]
 [0.00666667 0.025      0.00666667 0.         0.         0.00166667
  0.         0.00166667 0.00666667 0.95166667]]
[2023-08-24 06:25:44,072 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 06:25:44,073 INFO] 149504 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2754, train/total_loss: 0.2755, train/util_ratio: 1.0000, train/run_time: 0.5103, eval/loss: 0.2792, eval/top-1-acc: 0.9487, eval/balanced_acc: 0.9509, eval/precision: 0.9467, eval/recall: 0.9509, eval/F1: 0.9475, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9528, at 143360 iters
[2023-08-24 06:28:48,962 INFO] 149760 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0398, train/total_loss: 0.0399, train/util_ratio: 0.8750, train/run_time: 0.5515, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 06:31:11,104 INFO] 150016 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0111, train/total_loss: 0.0111, train/util_ratio: 1.0000, train/run_time: 0.4806, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 06:33:34,031 INFO] 150272 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0341, train/total_loss: 0.0341, train/util_ratio: 1.0000, train/run_time: 0.5325, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 06:35:56,878 INFO] 150528 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0327, train/total_loss: 0.0327, train/util_ratio: 1.0000, train/run_time: 0.5650, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 06:39:02,472 INFO] 150784 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.5738, train/total_loss: 0.5738, train/util_ratio: 1.0000, train/run_time: 0.4805, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 06:41:25,345 INFO] 151040 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.5214, train/total_loss: 0.5217, train/util_ratio: 0.8750, train/run_time: 0.5334, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 06:43:48,154 INFO] 151296 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0014, train/total_loss: 0.0014, train/util_ratio: 1.0000, train/run_time: 0.4821, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 06:46:09,983 INFO] validating...
[2023-08-24 06:46:34,125 INFO] confusion matrix:
[[0.95833333 0.00166667 0.00333333 0.         0.         0.005
  0.02666667 0.         0.005      0.        ]
 [0.         0.89666667 0.00166667 0.         0.         0.09166667
  0.         0.00833333 0.00166667 0.        ]
 [0.         0.01833333 0.81666667 0.00833333 0.         0.06666667
  0.02166667 0.02333333 0.045      0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.0075     0.0025     0.0025     0.01       0.         0.96
  0.01       0.         0.0075     0.        ]
 [0.012      0.         0.03       0.002      0.         0.
  0.952      0.004      0.         0.        ]
 [0.         0.         0.         0.00666667 0.01       0.
  0.         0.98166667 0.00166667 0.        ]
 [0.00601202 0.         0.         0.01603206 0.         0.
  0.         0.         0.97795591 0.        ]
 [0.00666667 0.01166667 0.00666667 0.00166667 0.         0.00333333
  0.         0.00166667 0.00333333 0.965     ]]
[2023-08-24 06:46:34,896 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 06:46:34,896 INFO] 151552 iteration, USE_EMA: False, train/sup_loss: 0.0009, train/unsup_loss: 0.0509, train/total_loss: 0.0518, train/util_ratio: 1.0000, train/run_time: 0.4853, eval/loss: 0.2859, eval/top-1-acc: 0.9467, eval/balanced_acc: 0.9492, eval/precision: 0.9444, eval/recall: 0.9492, eval/F1: 0.9452, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9528, at 143360 iters
[2023-08-24 06:49:39,468 INFO] 151808 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0012, train/total_loss: 0.0013, train/util_ratio: 1.0000, train/run_time: 0.5355, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 06:52:01,418 INFO] 152064 iteration USE_EMA: False, train/sup_loss: 0.0005, train/unsup_loss: 0.0006, train/total_loss: 0.0012, train/util_ratio: 0.8750, train/run_time: 0.5458, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 06:54:24,304 INFO] 152320 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3070, train/total_loss: 0.3071, train/util_ratio: 1.0000, train/run_time: 0.5287, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 06:56:47,049 INFO] 152576 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0264, train/total_loss: 0.0264, train/util_ratio: 1.0000, train/run_time: 0.4757, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 06:59:52,343 INFO] 152832 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.4377, train/total_loss: 0.4377, train/util_ratio: 1.0000, train/run_time: 0.5112, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 07:02:16,072 INFO] 153088 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0323, train/total_loss: 0.0323, train/util_ratio: 1.0000, train/run_time: 0.5308, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 07:04:38,482 INFO] 153344 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1157, train/total_loss: 0.1158, train/util_ratio: 1.0000, train/run_time: 0.5251, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 07:07:00,719 INFO] validating...
[2023-08-24 07:07:25,224 INFO] confusion matrix:
[[0.95666667 0.00166667 0.00333333 0.         0.         0.00166667
  0.03166667 0.         0.005      0.        ]
 [0.         0.9        0.00166667 0.         0.         0.09166667
  0.         0.00666667 0.         0.        ]
 [0.         0.01333333 0.87333333 0.00333333 0.         0.06666667
  0.02       0.01166667 0.01166667 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.01       0.0025     0.0025     0.0075     0.         0.94
  0.0325     0.         0.005      0.        ]
 [0.006      0.         0.034      0.         0.002      0.
  0.958      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01166667 0.
  0.         0.98666667 0.         0.        ]
 [0.00400802 0.         0.         0.01402806 0.         0.
  0.00200401 0.         0.97995992 0.        ]
 [0.01666667 0.01833333 0.00333333 0.         0.         0.00333333
  0.         0.         0.005      0.95333333]]
[2023-08-24 07:07:26,048 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 07:07:26,049 INFO] 153600 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0209, train/total_loss: 0.0209, train/util_ratio: 1.0000, train/run_time: 0.5409, eval/loss: 0.2778, eval/top-1-acc: 0.9517, eval/balanced_acc: 0.9532, eval/precision: 0.9492, eval/recall: 0.9532, eval/F1: 0.9501, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9528, at 143360 iters
[2023-08-24 07:10:28,947 INFO] 153856 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2402, train/total_loss: 0.2402, train/util_ratio: 1.0000, train/run_time: 0.5356, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 07:12:49,544 INFO] 154112 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0404, train/total_loss: 0.0405, train/util_ratio: 0.8750, train/run_time: 0.5344, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 07:15:11,410 INFO] 154368 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0225, train/total_loss: 0.0225, train/util_ratio: 1.0000, train/run_time: 0.5217, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 07:17:34,299 INFO] 154624 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0048, train/total_loss: 0.0048, train/util_ratio: 1.0000, train/run_time: 0.5346, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 07:20:40,274 INFO] 154880 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2801, train/total_loss: 0.2802, train/util_ratio: 1.0000, train/run_time: 0.4812, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 07:23:03,497 INFO] 155136 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0065, train/total_loss: 0.0065, train/util_ratio: 0.8750, train/run_time: 0.5063, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 07:25:26,302 INFO] 155392 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1000, train/total_loss: 0.1000, train/util_ratio: 0.8750, train/run_time: 0.5341, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 07:27:48,800 INFO] validating...
[2023-08-24 07:28:12,790 INFO] confusion matrix:
[[0.96833333 0.         0.00166667 0.         0.         0.005
  0.01833333 0.         0.00666667 0.        ]
 [0.         0.88833333 0.00333333 0.         0.         0.105
  0.         0.00333333 0.         0.        ]
 [0.         0.025      0.80166667 0.00833333 0.         0.1
  0.03833333 0.01166667 0.015      0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.         0.         0.005      0.         0.9775
  0.01       0.         0.0025     0.        ]
 [0.014      0.         0.034      0.002      0.         0.002
  0.946      0.         0.002      0.        ]
 [0.         0.         0.         0.00666667 0.01       0.
  0.         0.98166667 0.00166667 0.        ]
 [0.00400802 0.         0.         0.01603206 0.         0.00200401
  0.         0.         0.97795591 0.        ]
 [0.01166667 0.00666667 0.005      0.         0.         0.00333333
  0.         0.         0.00166667 0.97166667]]
[2023-08-24 07:28:13,831 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 07:28:13,833 INFO] 155648 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0018, train/total_loss: 0.0019, train/util_ratio: 1.0000, train/run_time: 0.4795, eval/loss: 0.3189, eval/top-1-acc: 0.9468, eval/balanced_acc: 0.9499, eval/precision: 0.9454, eval/recall: 0.9499, eval/F1: 0.9453, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9528, at 143360 iters
[2023-08-24 07:31:19,406 INFO] 155904 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0518, train/total_loss: 0.0518, train/util_ratio: 1.0000, train/run_time: 0.5477, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 07:33:42,701 INFO] 156160 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0019, train/total_loss: 0.0019, train/util_ratio: 1.0000, train/run_time: 0.5430, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 07:36:03,344 INFO] 156416 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0457, train/total_loss: 0.0458, train/util_ratio: 1.0000, train/run_time: 0.5385, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-24 07:38:25,430 INFO] 156672 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0247, train/total_loss: 0.0248, train/util_ratio: 1.0000, train/run_time: 0.4838, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 07:41:31,085 INFO] 156928 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1581, train/total_loss: 0.1582, train/util_ratio: 1.0000, train/run_time: 0.5357, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 07:43:52,215 INFO] 157184 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0054, train/total_loss: 0.0055, train/util_ratio: 1.0000, train/run_time: 0.5342, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 07:46:13,539 INFO] 157440 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0017, train/total_loss: 0.0017, train/util_ratio: 1.0000, train/run_time: 0.5012, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 07:48:35,659 INFO] validating...
[2023-08-24 07:49:00,010 INFO] confusion matrix:
[[0.95666667 0.00166667 0.00333333 0.         0.         0.005
  0.02833333 0.         0.005      0.        ]
 [0.         0.89166667 0.00166667 0.         0.         0.1
  0.         0.005      0.00166667 0.        ]
 [0.         0.02833333 0.80666667 0.005      0.         0.10833333
  0.02833333 0.015      0.00833333 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.998      0.
  0.         0.         0.         0.        ]
 [0.01       0.         0.0025     0.005      0.         0.9625
  0.0125     0.         0.0075     0.        ]
 [0.01       0.         0.026      0.002      0.006      0.002
  0.954      0.         0.         0.        ]
 [0.         0.         0.         0.005      0.015      0.
  0.         0.98       0.         0.        ]
 [0.00601202 0.         0.         0.01603206 0.         0.
  0.         0.         0.9759519  0.00200401]
 [0.00666667 0.00833333 0.01       0.00166667 0.         0.00333333
  0.         0.00166667 0.00166667 0.96666667]]
[2023-08-24 07:49:00,993 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 07:49:00,995 INFO] 157696 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2203, train/total_loss: 0.2203, train/util_ratio: 1.0000, train/run_time: 0.5327, eval/loss: 0.3111, eval/top-1-acc: 0.9457, eval/balanced_acc: 0.9486, eval/precision: 0.9441, eval/recall: 0.9486, eval/F1: 0.9442, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9528, at 143360 iters
[2023-08-24 07:52:03,322 INFO] 157952 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0416, train/total_loss: 0.0417, train/util_ratio: 0.8750, train/run_time: 0.5417, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 07:54:26,057 INFO] 158208 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0563, train/total_loss: 0.0563, train/util_ratio: 1.0000, train/run_time: 0.5386, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 07:56:48,903 INFO] 158464 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2082, train/total_loss: 0.2082, train/util_ratio: 0.8750, train/run_time: 0.5385, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 07:59:10,703 INFO] 158720 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0065, train/total_loss: 0.0065, train/util_ratio: 1.0000, train/run_time: 0.5373, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 08:02:17,680 INFO] 158976 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1197, train/total_loss: 0.1197, train/util_ratio: 1.0000, train/run_time: 0.5337, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-24 08:04:39,512 INFO] 159232 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0043, train/total_loss: 0.0043, train/util_ratio: 1.0000, train/run_time: 0.4844, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 08:07:02,479 INFO] 159488 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0079, train/total_loss: 0.0079, train/util_ratio: 1.0000, train/run_time: 0.5296, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 08:09:24,650 INFO] validating...
[2023-08-24 08:09:49,337 INFO] confusion matrix:
[[0.96       0.00166667 0.00333333 0.         0.         0.00333333
  0.025      0.         0.00666667 0.        ]
 [0.         0.9        0.00333333 0.         0.         0.09333333
  0.         0.00333333 0.         0.        ]
 [0.         0.01333333 0.885      0.00166667 0.         0.06833333
  0.02       0.005      0.00666667 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.        ]
 [0.0075     0.         0.0025     0.005      0.         0.955
  0.0225     0.         0.0075     0.        ]
 [0.006      0.         0.03       0.         0.006      0.
  0.958      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.01166667 0.
  0.         0.98666667 0.         0.        ]
 [0.00400802 0.         0.         0.01603206 0.         0.
  0.00200401 0.         0.97795591 0.        ]
 [0.00666667 0.00666667 0.00666667 0.00166667 0.         0.00333333
  0.         0.         0.00333333 0.97166667]]
[2023-08-24 08:09:50,177 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 08:09:51,432 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/model_best.pth
[2023-08-24 08:09:51,433 INFO] 159744 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2967, train/total_loss: 0.2967, train/util_ratio: 1.0000, train/run_time: 0.5359, eval/loss: 0.2586, eval/top-1-acc: 0.9567, eval/balanced_acc: 0.9582, eval/precision: 0.9541, eval/recall: 0.9582, eval/F1: 0.9550, lr: 0.0000, train/prefecth_time: 0.0031 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 08:12:54,203 INFO] 160000 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0883, train/total_loss: 0.0883, train/util_ratio: 1.0000, train/run_time: 0.4828, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 08:15:15,109 INFO] 160256 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.0781, train/total_loss: 0.0783, train/util_ratio: 1.0000, train/run_time: 0.5397, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 08:17:37,262 INFO] 160512 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0144, train/total_loss: 0.0144, train/util_ratio: 1.0000, train/run_time: 0.4836, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 08:19:58,370 INFO] 160768 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0060, train/total_loss: 0.0060, train/util_ratio: 0.8750, train/run_time: 0.5421, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 08:23:01,515 INFO] 161024 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.4693, train/total_loss: 0.4693, train/util_ratio: 1.0000, train/run_time: 0.4842, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-24 08:25:24,287 INFO] 161280 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0116, train/total_loss: 0.0116, train/util_ratio: 1.0000, train/run_time: 0.5316, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-24 08:27:45,826 INFO] 161536 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0366, train/total_loss: 0.0366, train/util_ratio: 1.0000, train/run_time: 0.5295, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 08:30:07,521 INFO] validating...
[2023-08-24 08:30:31,584 INFO] confusion matrix:
[[0.965      0.         0.00333333 0.         0.         0.00333333
  0.02666667 0.         0.00166667 0.        ]
 [0.         0.90333333 0.00166667 0.         0.         0.09
  0.         0.005      0.         0.        ]
 [0.         0.01166667 0.88833333 0.00166667 0.         0.06166667
  0.01666667 0.01       0.01       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.        ]
 [0.015      0.005      0.0025     0.01       0.         0.9475
  0.015      0.         0.005      0.        ]
 [0.01       0.         0.034      0.006      0.         0.
  0.95       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00601202 0.         0.         0.01803607 0.         0.00200401
  0.00200401 0.         0.97194389 0.        ]
 [0.01333333 0.005      0.00666667 0.         0.         0.00166667
  0.         0.00166667 0.00333333 0.96833333]]
[2023-08-24 08:30:32,334 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 08:30:32,335 INFO] 161792 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0025, train/total_loss: 0.0026, train/util_ratio: 1.0000, train/run_time: 0.5257, eval/loss: 0.2507, eval/top-1-acc: 0.9555, eval/balanced_acc: 0.9568, eval/precision: 0.9530, eval/recall: 0.9568, eval/F1: 0.9540, lr: 0.0000, train/prefecth_time: 0.0023 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 08:33:36,945 INFO] 162048 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0327, train/total_loss: 0.0327, train/util_ratio: 0.8750, train/run_time: 0.5187, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 08:35:58,025 INFO] 162304 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0054, train/total_loss: 0.0055, train/util_ratio: 1.0000, train/run_time: 0.5467, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 08:38:20,278 INFO] 162560 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0521, train/total_loss: 0.0521, train/util_ratio: 1.0000, train/run_time: 0.5429, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 08:40:42,112 INFO] 162816 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2682, train/total_loss: 0.2682, train/util_ratio: 0.8750, train/run_time: 0.4795, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 08:43:44,838 INFO] 163072 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0088, train/total_loss: 0.0088, train/util_ratio: 1.0000, train/run_time: 0.5379, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 08:46:08,097 INFO] 163328 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0382, train/total_loss: 0.0382, train/util_ratio: 0.8750, train/run_time: 0.4906, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 08:48:30,037 INFO] 163584 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0395, train/total_loss: 0.0396, train/util_ratio: 1.0000, train/run_time: 0.5317, lr: 0.0000, train/prefecth_time: 0.0043 
[2023-08-24 08:50:51,784 INFO] validating...
[2023-08-24 08:51:16,331 INFO] confusion matrix:
[[0.955      0.00166667 0.00333333 0.         0.         0.00333333
  0.03       0.         0.00666667 0.        ]
 [0.         0.90166667 0.00166667 0.         0.         0.09
  0.         0.00666667 0.         0.        ]
 [0.         0.01       0.85833333 0.00166667 0.         0.07833333
  0.02833333 0.015      0.00833333 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.        ]
 [0.0075     0.005      0.0025     0.005      0.         0.9675
  0.01       0.         0.0025     0.        ]
 [0.006      0.         0.022      0.         0.         0.
  0.972      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01       0.
  0.         0.99       0.         0.        ]
 [0.00601202 0.         0.         0.01002004 0.         0.00200401
  0.         0.         0.98196393 0.        ]
 [0.00666667 0.00333333 0.00666667 0.00166667 0.         0.00333333
  0.         0.00166667 0.00666667 0.97      ]]
[2023-08-24 08:51:17,235 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 08:51:17,237 INFO] 163840 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0143, train/total_loss: 0.0143, train/util_ratio: 1.0000, train/run_time: 0.4804, eval/loss: 0.2514, eval/top-1-acc: 0.9563, eval/balanced_acc: 0.9586, eval/precision: 0.9543, eval/recall: 0.9586, eval/F1: 0.9549, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 08:54:20,415 INFO] 164096 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1338, train/total_loss: 0.1338, train/util_ratio: 0.7500, train/run_time: 0.5379, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 08:56:42,549 INFO] 164352 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0292, train/total_loss: 0.0292, train/util_ratio: 0.8750, train/run_time: 0.5415, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-24 08:59:03,596 INFO] 164608 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0038, train/total_loss: 0.0038, train/util_ratio: 0.8750, train/run_time: 0.5319, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 09:01:26,529 INFO] 164864 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0082, train/total_loss: 0.0083, train/util_ratio: 1.0000, train/run_time: 0.5386, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 09:04:32,491 INFO] 165120 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: 0.0005, train/util_ratio: 0.8750, train/run_time: 0.5453, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 09:06:54,261 INFO] 165376 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0015, train/total_loss: 0.0015, train/util_ratio: 1.0000, train/run_time: 0.5378, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 09:09:16,322 INFO] 165632 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0098, train/total_loss: 0.0099, train/util_ratio: 0.8750, train/run_time: 0.5389, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 09:11:37,420 INFO] validating...
[2023-08-24 09:12:01,597 INFO] confusion matrix:
[[0.96666667 0.00166667 0.00333333 0.         0.         0.00333333
  0.02       0.         0.005      0.        ]
 [0.         0.90166667 0.00333333 0.         0.         0.09166667
  0.         0.00333333 0.         0.        ]
 [0.         0.01833333 0.85833333 0.00166667 0.         0.08333333
  0.01166667 0.015      0.01166667 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.002      0.002      0.         0.        ]
 [0.0125     0.0025     0.005      0.005      0.         0.9725
  0.0025     0.         0.         0.        ]
 [0.016      0.         0.036      0.002      0.         0.002
  0.944      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.00666667 0.
  0.         0.99       0.         0.        ]
 [0.00601202 0.         0.         0.01202405 0.         0.00200401
  0.         0.         0.97995992 0.        ]
 [0.00666667 0.01       0.00333333 0.00166667 0.         0.00333333
  0.         0.         0.005      0.97      ]]
[2023-08-24 09:12:02,411 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 09:12:02,412 INFO] 165888 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.4252, train/total_loss: 0.4253, train/util_ratio: 1.0000, train/run_time: 0.5356, eval/loss: 0.2838, eval/top-1-acc: 0.9552, eval/balanced_acc: 0.9573, eval/precision: 0.9535, eval/recall: 0.9573, eval/F1: 0.9539, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 09:15:07,643 INFO] 166144 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.6519, train/total_loss: 0.6520, train/util_ratio: 1.0000, train/run_time: 0.5310, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 09:17:30,370 INFO] 166400 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0725, train/total_loss: 0.0726, train/util_ratio: 1.0000, train/run_time: 0.4917, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 09:19:52,840 INFO] 166656 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2307, train/total_loss: 0.2307, train/util_ratio: 1.0000, train/run_time: 0.5347, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 09:22:14,132 INFO] 166912 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0384, train/total_loss: 0.0384, train/util_ratio: 1.0000, train/run_time: 0.4782, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 09:25:19,645 INFO] 167168 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0047, train/total_loss: 0.0047, train/util_ratio: 1.0000, train/run_time: 0.5364, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 09:27:42,417 INFO] 167424 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0005, train/total_loss: 0.0005, train/util_ratio: 1.0000, train/run_time: 0.5257, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 09:30:04,711 INFO] 167680 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1260, train/total_loss: 0.1260, train/util_ratio: 1.0000, train/run_time: 0.4847, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 09:32:27,021 INFO] validating...
[2023-08-24 09:32:51,425 INFO] confusion matrix:
[[0.945      0.00166667 0.00333333 0.         0.         0.005
  0.04       0.         0.005      0.        ]
 [0.         0.905      0.00333333 0.         0.         0.08833333
  0.         0.00333333 0.         0.        ]
 [0.         0.01833333 0.855      0.00166667 0.         0.08
  0.01666667 0.015      0.01333333 0.        ]
 [0.         0.         0.         0.984      0.         0.
  0.002      0.002      0.012      0.        ]
 [0.         0.         0.         0.002      0.99       0.
  0.002      0.006      0.         0.        ]
 [0.01       0.0075     0.0025     0.005      0.         0.9625
  0.01       0.         0.0025     0.        ]
 [0.006      0.         0.032      0.         0.         0.002
  0.956      0.004      0.         0.        ]
 [0.         0.         0.         0.         0.00666667 0.
  0.         0.99333333 0.         0.        ]
 [0.00400802 0.         0.         0.00801603 0.         0.00200401
  0.00200401 0.         0.98396794 0.        ]
 [0.005      0.01       0.01       0.         0.         0.00333333
  0.         0.         0.         0.97166667]]
[2023-08-24 09:32:52,248 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 09:32:52,249 INFO] 167936 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0013, train/total_loss: 0.0013, train/util_ratio: 1.0000, train/run_time: 0.5381, eval/loss: 0.2728, eval/top-1-acc: 0.9526, eval/balanced_acc: 0.9546, eval/precision: 0.9507, eval/recall: 0.9546, eval/F1: 0.9513, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 09:35:55,122 INFO] 168192 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0023, train/total_loss: 0.0023, train/util_ratio: 1.0000, train/run_time: 0.5321, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 09:38:17,089 INFO] 168448 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0354, train/total_loss: 0.0354, train/util_ratio: 1.0000, train/run_time: 0.5155, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 09:40:38,891 INFO] 168704 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 1.1680, train/total_loss: 1.1680, train/util_ratio: 1.0000, train/run_time: 0.5355, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 09:42:59,945 INFO] 168960 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0088, train/total_loss: 0.0088, train/util_ratio: 1.0000, train/run_time: 0.5413, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 09:46:03,468 INFO] 169216 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1675, train/total_loss: 0.1675, train/util_ratio: 1.0000, train/run_time: 0.5255, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 09:48:24,149 INFO] 169472 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0852, train/total_loss: 0.0852, train/util_ratio: 1.0000, train/run_time: 0.5137, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 09:50:45,569 INFO] 169728 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1287, train/total_loss: 0.1287, train/util_ratio: 1.0000, train/run_time: 0.5327, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 09:53:05,281 INFO] validating...
[2023-08-24 09:53:29,345 INFO] confusion matrix:
[[0.95333333 0.00166667 0.00333333 0.         0.         0.00666667
  0.02833333 0.         0.00666667 0.        ]
 [0.         0.89666667 0.00166667 0.         0.         0.09666667
  0.         0.005      0.         0.        ]
 [0.         0.02       0.84       0.00166667 0.         0.07666667
  0.02       0.02166667 0.02       0.        ]
 [0.         0.         0.         0.98       0.006      0.
  0.002      0.002      0.01       0.        ]
 [0.         0.         0.         0.         0.996      0.
  0.002      0.002      0.         0.        ]
 [0.0075     0.         0.0025     0.005      0.         0.9725
  0.01       0.         0.0025     0.        ]
 [0.008      0.         0.034      0.         0.         0.002
  0.954      0.002      0.         0.        ]
 [0.         0.         0.         0.         0.00833333 0.
  0.         0.99166667 0.         0.        ]
 [0.00601202 0.         0.         0.01002004 0.         0.00200401
  0.         0.         0.98196393 0.        ]
 [0.00666667 0.01       0.00333333 0.00166667 0.         0.00333333
  0.         0.         0.00166667 0.97333333]]
[2023-08-24 09:53:30,158 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 09:53:30,159 INFO] 169984 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0239, train/total_loss: 0.0239, train/util_ratio: 1.0000, train/run_time: 0.5118, eval/loss: 0.2868, eval/top-1-acc: 0.9515, eval/balanced_acc: 0.9539, eval/precision: 0.9497, eval/recall: 0.9539, eval/F1: 0.9501, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 09:56:33,776 INFO] 170240 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0005, train/total_loss: 0.0006, train/util_ratio: 1.0000, train/run_time: 0.5041, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 09:58:56,470 INFO] 170496 iteration USE_EMA: False, train/sup_loss: 0.0010, train/unsup_loss: 0.0224, train/total_loss: 0.0234, train/util_ratio: 0.8750, train/run_time: 0.5096, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 10:01:18,232 INFO] 170752 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0070, train/total_loss: 0.0070, train/util_ratio: 0.8750, train/run_time: 0.5204, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 10:03:41,279 INFO] 171008 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.5116, train/total_loss: 0.5116, train/util_ratio: 1.0000, train/run_time: 0.5377, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 10:06:46,841 INFO] 171264 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0003, train/total_loss: 0.0004, train/util_ratio: 1.0000, train/run_time: 0.5300, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 10:09:08,781 INFO] 171520 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3043, train/total_loss: 0.3044, train/util_ratio: 0.8750, train/run_time: 0.5758, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 10:11:30,885 INFO] 171776 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.6338, train/total_loss: 0.6338, train/util_ratio: 1.0000, train/run_time: 0.5318, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 10:13:53,085 INFO] validating...
[2023-08-24 10:14:17,480 INFO] confusion matrix:
[[0.95333333 0.00166667 0.00333333 0.         0.         0.00666667
  0.03333333 0.         0.00166667 0.        ]
 [0.         0.83833333 0.00166667 0.         0.         0.15333333
  0.         0.00666667 0.         0.        ]
 [0.         0.01333333 0.84666667 0.00166667 0.         0.09666667
  0.015      0.01333333 0.01333333 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.         0.         0.008      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.0075     0.         0.         0.0075     0.         0.9725
  0.01       0.         0.0025     0.        ]
 [0.006      0.         0.038      0.         0.         0.002
  0.954      0.         0.         0.        ]
 [0.         0.         0.         0.00166667 0.00833333 0.
  0.         0.99       0.         0.        ]
 [0.00601202 0.         0.         0.01402806 0.         0.00200401
  0.         0.         0.97795591 0.        ]
 [0.01       0.00833333 0.005      0.00166667 0.         0.00333333
  0.         0.00166667 0.         0.97      ]]
[2023-08-24 10:14:18,377 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 10:14:18,378 INFO] 172032 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3244, train/total_loss: 0.3244, train/util_ratio: 0.8750, train/run_time: 0.5046, eval/loss: 0.3412, eval/top-1-acc: 0.9455, eval/balanced_acc: 0.9487, eval/precision: 0.9455, eval/recall: 0.9487, eval/F1: 0.9442, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 10:17:21,678 INFO] 172288 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2837, train/total_loss: 0.2837, train/util_ratio: 1.0000, train/run_time: 0.5480, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 10:19:43,335 INFO] 172544 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0015, train/total_loss: 0.0015, train/util_ratio: 1.0000, train/run_time: 0.5416, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 10:22:06,158 INFO] 172800 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0025, train/total_loss: 0.0026, train/util_ratio: 1.0000, train/run_time: 0.5492, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 10:24:29,913 INFO] 173056 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2810, train/total_loss: 0.2810, train/util_ratio: 1.0000, train/run_time: 0.5424, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 10:27:34,489 INFO] 173312 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0577, train/total_loss: 0.0577, train/util_ratio: 1.0000, train/run_time: 0.5431, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 10:29:56,230 INFO] 173568 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.4218, train/total_loss: 0.4218, train/util_ratio: 1.0000, train/run_time: 0.5382, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 10:32:18,891 INFO] 173824 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0245, train/total_loss: 0.0245, train/util_ratio: 1.0000, train/run_time: 0.4756, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 10:34:40,227 INFO] validating...
[2023-08-24 10:35:04,448 INFO] confusion matrix:
[[0.94333333 0.00166667 0.00333333 0.         0.         0.005
  0.04166667 0.         0.005      0.        ]
 [0.         0.875      0.00166667 0.         0.         0.11833333
  0.         0.005      0.         0.        ]
 [0.         0.01833333 0.88333333 0.00166667 0.         0.06333333
  0.01333333 0.00833333 0.01166667 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.0075     0.         0.0025     0.0075     0.         0.9675
  0.0125     0.         0.0025     0.        ]
 [0.006      0.         0.028      0.002      0.         0.002
  0.962      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01       0.
  0.         0.98666667 0.         0.        ]
 [0.00400802 0.         0.         0.01603206 0.         0.00200401
  0.         0.         0.97795591 0.        ]
 [0.00666667 0.005      0.00333333 0.00166667 0.         0.00333333
  0.         0.         0.         0.98      ]]
[2023-08-24 10:35:05,390 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 10:35:05,392 INFO] 174080 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1311, train/total_loss: 0.1311, train/util_ratio: 1.0000, train/run_time: 0.5078, eval/loss: 0.2842, eval/top-1-acc: 0.9541, eval/balanced_acc: 0.9564, eval/precision: 0.9522, eval/recall: 0.9564, eval/F1: 0.9526, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 10:38:10,656 INFO] 174336 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0171, train/total_loss: 0.0171, train/util_ratio: 1.0000, train/run_time: 0.5370, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 10:40:30,896 INFO] 174592 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0043, train/total_loss: 0.0043, train/util_ratio: 1.0000, train/run_time: 0.5455, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 10:42:54,682 INFO] 174848 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2336, train/total_loss: 0.2336, train/util_ratio: 1.0000, train/run_time: 0.5340, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 10:45:19,726 INFO] 175104 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0246, train/total_loss: 0.0246, train/util_ratio: 1.0000, train/run_time: 0.5358, lr: 0.0000, train/prefecth_time: 0.0023 
[2023-08-24 10:48:25,763 INFO] 175360 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.4501, train/total_loss: 0.4501, train/util_ratio: 0.8750, train/run_time: 0.5455, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 10:50:48,708 INFO] 175616 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0317, train/total_loss: 0.0320, train/util_ratio: 0.8750, train/run_time: 0.5157, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 10:53:10,668 INFO] 175872 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.7582, train/total_loss: 0.7582, train/util_ratio: 1.0000, train/run_time: 0.5479, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 10:55:33,497 INFO] validating...
[2023-08-24 10:55:57,988 INFO] confusion matrix:
[[0.92666667 0.00166667 0.00333333 0.         0.         0.00833333
  0.055      0.         0.005      0.        ]
 [0.         0.88666667 0.00333333 0.         0.         0.105
  0.         0.00333333 0.00166667 0.        ]
 [0.         0.01166667 0.90166667 0.00166667 0.         0.05333333
  0.01333333 0.00666667 0.01166667 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.         0.0025     0.0075     0.         0.9675
  0.0175     0.         0.0025     0.        ]
 [0.004      0.         0.032      0.         0.         0.
  0.964      0.         0.         0.        ]
 [0.         0.         0.         0.         0.01       0.
  0.         0.99       0.         0.        ]
 [0.00400802 0.         0.         0.00801603 0.         0.
  0.00200401 0.         0.98597194 0.        ]
 [0.00666667 0.00333333 0.00666667 0.00166667 0.         0.005
  0.         0.00166667 0.005      0.97      ]]
[2023-08-24 10:55:58,804 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 10:55:58,805 INFO] 176128 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0325, train/total_loss: 0.0325, train/util_ratio: 1.0000, train/run_time: 0.5343, eval/loss: 0.2838, eval/top-1-acc: 0.9552, eval/balanced_acc: 0.9574, eval/precision: 0.9531, eval/recall: 0.9574, eval/F1: 0.9539, lr: 0.0000, train/prefecth_time: 0.0028 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 10:59:02,644 INFO] 176384 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0428, train/total_loss: 0.0429, train/util_ratio: 1.0000, train/run_time: 0.5427, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 11:01:24,772 INFO] 176640 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2433, train/total_loss: 0.2434, train/util_ratio: 1.0000, train/run_time: 0.5393, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 11:03:47,784 INFO] 176896 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0036, train/total_loss: 0.0036, train/util_ratio: 1.0000, train/run_time: 0.5346, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 11:06:10,011 INFO] 177152 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1198, train/total_loss: 0.1198, train/util_ratio: 1.0000, train/run_time: 0.5425, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 11:09:15,928 INFO] 177408 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0062, train/total_loss: 0.0062, train/util_ratio: 1.0000, train/run_time: 0.5557, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 11:11:39,341 INFO] 177664 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0376, train/total_loss: 0.0376, train/util_ratio: 1.0000, train/run_time: 0.5344, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 11:14:01,999 INFO] 177920 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1825, train/total_loss: 0.1826, train/util_ratio: 0.8750, train/run_time: 0.5451, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 11:16:26,656 INFO] validating...
[2023-08-24 11:16:51,283 INFO] confusion matrix:
[[0.955      0.00166667 0.00166667 0.         0.         0.00833333
  0.03166667 0.         0.00166667 0.        ]
 [0.         0.90666667 0.00166667 0.         0.         0.08666667
  0.         0.005      0.         0.        ]
 [0.         0.02333333 0.805      0.00166667 0.         0.10166667
  0.02666667 0.02166667 0.02       0.        ]
 [0.         0.         0.         0.99       0.         0.
  0.         0.         0.01       0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.004      0.         0.         0.        ]
 [0.0025     0.0025     0.         0.0075     0.         0.975
  0.0125     0.         0.         0.        ]
 [0.008      0.         0.026      0.         0.         0.002
  0.964      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00601202 0.         0.         0.00601202 0.         0.00200401
  0.         0.         0.98597194 0.        ]
 [0.00666667 0.01       0.00333333 0.00166667 0.         0.00333333
  0.         0.         0.         0.975     ]]
[2023-08-24 11:16:52,220 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 11:16:52,222 INFO] 178176 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0147, train/total_loss: 0.0147, train/util_ratio: 0.8750, train/run_time: 0.4806, eval/loss: 0.3120, eval/top-1-acc: 0.9504, eval/balanced_acc: 0.9534, eval/precision: 0.9489, eval/recall: 0.9534, eval/F1: 0.9489, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 11:19:57,017 INFO] 178432 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0578, train/total_loss: 0.0578, train/util_ratio: 1.0000, train/run_time: 0.5285, lr: 0.0000, train/prefecth_time: 0.0038 
[2023-08-24 11:22:19,607 INFO] 178688 iteration USE_EMA: False, train/sup_loss: 0.0002, train/unsup_loss: 0.1953, train/total_loss: 0.1956, train/util_ratio: 1.0000, train/run_time: 0.4910, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 11:24:42,639 INFO] 178944 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0146, train/total_loss: 0.0146, train/util_ratio: 1.0000, train/run_time: 0.4907, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 11:27:06,390 INFO] 179200 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1408, train/total_loss: 0.1408, train/util_ratio: 1.0000, train/run_time: 0.5461, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 11:30:11,746 INFO] 179456 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0769, train/total_loss: 0.0769, train/util_ratio: 1.0000, train/run_time: 0.5314, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 11:32:32,441 INFO] 179712 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0183, train/total_loss: 0.0183, train/util_ratio: 1.0000, train/run_time: 0.5435, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 11:34:54,562 INFO] 179968 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1372, train/total_loss: 0.1372, train/util_ratio: 1.0000, train/run_time: 0.5062, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 11:37:15,658 INFO] validating...
[2023-08-24 11:37:40,203 INFO] confusion matrix:
[[0.96166667 0.00166667 0.00166667 0.         0.         0.00833333
  0.02666667 0.         0.         0.        ]
 [0.         0.905      0.00333333 0.         0.         0.08833333
  0.         0.00333333 0.         0.        ]
 [0.         0.025      0.855      0.00333333 0.         0.09166667
  0.01166667 0.00333333 0.01       0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.         0.0025     0.005      0.         0.98
  0.0075     0.         0.         0.        ]
 [0.012      0.         0.034      0.         0.         0.002
  0.952      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00601202 0.         0.         0.01603206 0.         0.00200401
  0.         0.         0.9759519  0.        ]
 [0.01166667 0.01       0.00666667 0.00166667 0.         0.00333333
  0.         0.         0.         0.96666667]]
[2023-08-24 11:37:41,080 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 11:37:41,081 INFO] 180224 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0004, train/total_loss: 0.0004, train/util_ratio: 1.0000, train/run_time: 0.5422, eval/loss: 0.2857, eval/top-1-acc: 0.9543, eval/balanced_acc: 0.9568, eval/precision: 0.9527, eval/recall: 0.9568, eval/F1: 0.9531, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 11:40:45,218 INFO] 180480 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0429, train/total_loss: 0.0429, train/util_ratio: 1.0000, train/run_time: 0.5250, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 11:43:06,139 INFO] 180736 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0762, train/total_loss: 0.0762, train/util_ratio: 0.8750, train/run_time: 0.5263, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 11:45:29,316 INFO] 180992 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0481, train/total_loss: 0.0481, train/util_ratio: 1.0000, train/run_time: 0.5290, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 11:47:50,000 INFO] 181248 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0153, train/total_loss: 0.0153, train/util_ratio: 0.7500, train/run_time: 0.5360, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 11:50:54,575 INFO] 181504 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0008, train/total_loss: 0.0008, train/util_ratio: 1.0000, train/run_time: 0.5256, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 11:53:18,335 INFO] 181760 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0468, train/total_loss: 0.0468, train/util_ratio: 1.0000, train/run_time: 0.5429, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 11:55:40,887 INFO] 182016 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1837, train/total_loss: 0.1837, train/util_ratio: 0.8750, train/run_time: 0.5419, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 11:58:03,683 INFO] validating...
[2023-08-24 11:58:28,258 INFO] confusion matrix:
[[0.96666667 0.00166667 0.00333333 0.         0.         0.00666667
  0.02       0.         0.00166667 0.        ]
 [0.         0.885      0.00333333 0.         0.         0.10833333
  0.         0.00333333 0.         0.        ]
 [0.         0.02       0.835      0.00833333 0.         0.095
  0.015      0.01166667 0.015      0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.004      0.99       0.
  0.004      0.002      0.         0.        ]
 [0.005      0.         0.         0.0075     0.         0.9825
  0.005      0.         0.         0.        ]
 [0.02       0.         0.034      0.01       0.         0.002
  0.934      0.         0.         0.        ]
 [0.         0.         0.         0.00666667 0.00833333 0.
  0.         0.985      0.         0.        ]
 [0.00601202 0.         0.         0.01202405 0.         0.00200401
  0.         0.         0.97995992 0.        ]
 [0.015      0.00833333 0.01166667 0.00166667 0.         0.005
  0.         0.         0.         0.95833333]]
[2023-08-24 11:58:29,114 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 11:58:29,115 INFO] 182272 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0265, train/total_loss: 0.0265, train/util_ratio: 0.8750, train/run_time: 0.4824, eval/loss: 0.3189, eval/top-1-acc: 0.9483, eval/balanced_acc: 0.9512, eval/precision: 0.9474, eval/recall: 0.9512, eval/F1: 0.9471, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 12:01:33,901 INFO] 182528 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.4331, train/total_loss: 0.4332, train/util_ratio: 1.0000, train/run_time: 0.5783, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 12:03:55,116 INFO] 182784 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0030, train/total_loss: 0.0030, train/util_ratio: 1.0000, train/run_time: 0.5258, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-24 12:06:17,657 INFO] 183040 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.1900, train/total_loss: 0.1901, train/util_ratio: 1.0000, train/run_time: 0.5479, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 12:08:38,887 INFO] 183296 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0079, train/total_loss: 0.0079, train/util_ratio: 1.0000, train/run_time: 0.5406, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 12:11:42,290 INFO] 183552 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0046, train/total_loss: 0.0046, train/util_ratio: 1.0000, train/run_time: 0.5372, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 12:14:05,034 INFO] 183808 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2728, train/total_loss: 0.2728, train/util_ratio: 1.0000, train/run_time: 0.5378, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 12:16:26,590 INFO] 184064 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0551, train/total_loss: 0.0551, train/util_ratio: 1.0000, train/run_time: 0.5414, lr: 0.0000, train/prefecth_time: 0.0045 
[2023-08-24 12:18:47,984 INFO] validating...
[2023-08-24 12:19:12,296 INFO] confusion matrix:
[[0.92       0.00166667 0.00166667 0.         0.         0.01166667
  0.06333333 0.         0.00166667 0.        ]
 [0.         0.85833333 0.00333333 0.         0.         0.135
  0.         0.00333333 0.         0.        ]
 [0.         0.02       0.81666667 0.00166667 0.         0.11
  0.02       0.01333333 0.01833333 0.        ]
 [0.         0.         0.         0.992      0.         0.
  0.002      0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.0025     0.         0.         0.005      0.         0.9825
  0.01       0.         0.         0.        ]
 [0.006      0.         0.022      0.         0.         0.002
  0.97       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01166667 0.
  0.         0.985      0.         0.        ]
 [0.00601202 0.         0.         0.01002004 0.         0.00200401
  0.         0.         0.98196393 0.        ]
 [0.00666667 0.00833333 0.00666667 0.00166667 0.         0.00666667
  0.         0.         0.00166667 0.96833333]]
[2023-08-24 12:19:13,207 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 12:19:13,208 INFO] 184320 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0414, train/total_loss: 0.0415, train/util_ratio: 1.0000, train/run_time: 0.5425, eval/loss: 0.3569, eval/top-1-acc: 0.9426, eval/balanced_acc: 0.9467, eval/precision: 0.9429, eval/recall: 0.9467, eval/F1: 0.9414, lr: 0.0000, train/prefecth_time: 0.0024 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 12:22:18,252 INFO] 184576 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0956, train/total_loss: 0.0956, train/util_ratio: 0.8750, train/run_time: 0.5395, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 12:24:39,123 INFO] 184832 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0131, train/total_loss: 0.0131, train/util_ratio: 1.0000, train/run_time: 0.5351, lr: 0.0000, train/prefecth_time: 0.0037 
[2023-08-24 12:27:01,408 INFO] 185088 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0011, train/total_loss: 0.0011, train/util_ratio: 1.0000, train/run_time: 0.5296, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 12:29:22,845 INFO] 185344 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0116, train/total_loss: 0.0117, train/util_ratio: 1.0000, train/run_time: 0.5372, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 12:32:27,068 INFO] 185600 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.6369, train/total_loss: 0.6370, train/util_ratio: 1.0000, train/run_time: 0.4785, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 12:34:49,744 INFO] 185856 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2115, train/total_loss: 0.2115, train/util_ratio: 1.0000, train/run_time: 0.5075, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 12:37:12,988 INFO] 186112 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3910, train/total_loss: 0.3910, train/util_ratio: 1.0000, train/run_time: 0.5433, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 12:39:34,926 INFO] validating...
[2023-08-24 12:39:59,428 INFO] confusion matrix:
[[0.94833333 0.00166667 0.00166667 0.         0.         0.00666667
  0.03666667 0.         0.005      0.        ]
 [0.         0.885      0.00166667 0.         0.         0.105
  0.         0.005      0.00333333 0.        ]
 [0.         0.02333333 0.82666667 0.00166667 0.         0.09
  0.01166667 0.01333333 0.03333333 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.004      0.99       0.
  0.004      0.002      0.         0.        ]
 [0.005      0.         0.         0.0075     0.         0.975
  0.0075     0.         0.005      0.        ]
 [0.008      0.         0.028      0.004      0.         0.002
  0.958      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01       0.
  0.         0.98666667 0.         0.        ]
 [0.00601202 0.         0.         0.01202405 0.         0.00200401
  0.         0.         0.97995992 0.        ]
 [0.01333333 0.01166667 0.00666667 0.00166667 0.         0.005
  0.         0.         0.         0.96166667]]
[2023-08-24 12:40:00,469 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 12:40:00,470 INFO] 186368 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0006, train/total_loss: 0.0006, train/util_ratio: 0.8750, train/run_time: 0.5346, eval/loss: 0.3177, eval/top-1-acc: 0.9474, eval/balanced_acc: 0.9505, eval/precision: 0.9459, eval/recall: 0.9505, eval/F1: 0.9461, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 12:43:05,158 INFO] 186624 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.2664, train/total_loss: 0.2665, train/util_ratio: 1.0000, train/run_time: 0.5377, lr: 0.0000, train/prefecth_time: 0.0035 
[2023-08-24 12:45:28,469 INFO] 186880 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0653, train/total_loss: 0.0653, train/util_ratio: 1.0000, train/run_time: 0.5291, lr: 0.0000, train/prefecth_time: 0.0034 
[2023-08-24 12:47:51,312 INFO] 187136 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0023, train/total_loss: 0.0024, train/util_ratio: 1.0000, train/run_time: 0.5518, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 12:50:15,012 INFO] 187392 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0152, train/total_loss: 0.0153, train/util_ratio: 1.0000, train/run_time: 0.5348, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-24 12:53:20,236 INFO] 187648 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1548, train/total_loss: 0.1549, train/util_ratio: 1.0000, train/run_time: 0.5365, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 12:55:43,481 INFO] 187904 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0482, train/total_loss: 0.0482, train/util_ratio: 1.0000, train/run_time: 0.5526, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 12:58:06,764 INFO] 188160 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0217, train/total_loss: 0.0218, train/util_ratio: 1.0000, train/run_time: 0.5343, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 13:00:30,275 INFO] validating...
[2023-08-24 13:00:54,796 INFO] confusion matrix:
[[0.94833333 0.00166667 0.00166667 0.         0.         0.00833333
  0.035      0.         0.005      0.        ]
 [0.         0.88666667 0.00333333 0.         0.         0.10666667
  0.         0.00333333 0.         0.        ]
 [0.         0.02166667 0.85       0.00333333 0.         0.065
  0.00833333 0.01166667 0.04       0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.002      0.996      0.
  0.002      0.         0.         0.        ]
 [0.005      0.         0.0025     0.01       0.         0.97
  0.01       0.         0.0025     0.        ]
 [0.008      0.         0.032      0.006      0.002      0.002
  0.95       0.         0.         0.        ]
 [0.         0.         0.         0.005      0.01166667 0.
  0.         0.98166667 0.00166667 0.        ]
 [0.00400802 0.         0.         0.01603206 0.         0.00200401
  0.         0.         0.97795591 0.        ]
 [0.01       0.01       0.00666667 0.00166667 0.         0.00333333
  0.         0.         0.         0.96833333]]
[2023-08-24 13:00:55,765 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 13:00:55,766 INFO] 188416 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0222, train/total_loss: 0.0222, train/util_ratio: 1.0000, train/run_time: 0.5314, eval/loss: 0.3034, eval/top-1-acc: 0.9498, eval/balanced_acc: 0.9525, eval/precision: 0.9477, eval/recall: 0.9525, eval/F1: 0.9484, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 13:04:01,688 INFO] 188672 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0839, train/total_loss: 0.0839, train/util_ratio: 1.0000, train/run_time: 0.5460, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 13:06:25,233 INFO] 188928 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0051, train/total_loss: 0.0052, train/util_ratio: 1.0000, train/run_time: 0.4819, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 13:08:47,685 INFO] 189184 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0729, train/total_loss: 0.0729, train/util_ratio: 1.0000, train/run_time: 0.5016, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 13:11:08,995 INFO] 189440 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.7155, train/total_loss: 0.7156, train/util_ratio: 1.0000, train/run_time: 0.5341, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 13:14:15,454 INFO] 189696 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0002, train/total_loss: 0.0002, train/util_ratio: 0.8750, train/run_time: 0.5475, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 13:16:38,347 INFO] 189952 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0196, train/total_loss: 0.0197, train/util_ratio: 1.0000, train/run_time: 0.5347, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 13:19:00,481 INFO] 190208 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0052, train/total_loss: 0.0052, train/util_ratio: 0.8750, train/run_time: 0.5165, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 13:21:23,172 INFO] validating...
[2023-08-24 13:21:47,614 INFO] confusion matrix:
[[0.945      0.00166667 0.00333333 0.         0.         0.00833333
  0.03666667 0.         0.005      0.        ]
 [0.         0.87833333 0.00166667 0.         0.         0.11333333
  0.         0.00666667 0.         0.        ]
 [0.         0.02       0.835      0.00333333 0.         0.07
  0.01833333 0.02       0.03333333 0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.004      0.         0.         0.        ]
 [0.0025     0.         0.         0.0075     0.         0.975
  0.0125     0.         0.0025     0.        ]
 [0.006      0.         0.028      0.         0.         0.002
  0.964      0.         0.         0.        ]
 [0.         0.         0.         0.005      0.01166667 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.01803607 0.         0.00200401
  0.         0.         0.9759519  0.        ]
 [0.01       0.015      0.00333333 0.00166667 0.         0.00833333
  0.         0.         0.00333333 0.95833333]]
[2023-08-24 13:21:48,409 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 13:21:48,409 INFO] 190464 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0773, train/total_loss: 0.0773, train/util_ratio: 1.0000, train/run_time: 0.5408, eval/loss: 0.3244, eval/top-1-acc: 0.9470, eval/balanced_acc: 0.9503, eval/precision: 0.9454, eval/recall: 0.9503, eval/F1: 0.9457, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 13:24:52,363 INFO] 190720 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0843, train/total_loss: 0.0843, train/util_ratio: 1.0000, train/run_time: 0.5390, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 13:27:14,332 INFO] 190976 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0712, train/total_loss: 0.0712, train/util_ratio: 0.8750, train/run_time: 0.5404, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 13:29:36,421 INFO] 191232 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0001, train/total_loss: 0.0001, train/util_ratio: 1.0000, train/run_time: 0.5265, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 13:31:56,916 INFO] 191488 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0014, train/total_loss: 0.0014, train/util_ratio: 1.0000, train/run_time: 0.5329, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 13:35:01,769 INFO] 191744 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.3338, train/total_loss: 0.3338, train/util_ratio: 1.0000, train/run_time: 0.5291, lr: 0.0000, train/prefecth_time: 0.0040 
[2023-08-24 13:37:24,564 INFO] 192000 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0033, train/total_loss: 0.0033, train/util_ratio: 1.0000, train/run_time: 0.5320, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 13:39:46,588 INFO] 192256 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0854, train/total_loss: 0.0854, train/util_ratio: 1.0000, train/run_time: 0.5453, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 13:42:08,577 INFO] validating...
[2023-08-24 13:42:33,267 INFO] confusion matrix:
[[0.935      0.00166667 0.00166667 0.         0.         0.00833333
  0.05166667 0.         0.00166667 0.        ]
 [0.         0.88833333 0.00166667 0.         0.         0.105
  0.         0.005      0.         0.        ]
 [0.         0.02       0.855      0.00166667 0.         0.07
  0.01666667 0.00833333 0.02833333 0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.004      0.         0.         0.        ]
 [0.005      0.         0.0025     0.0075     0.         0.975
  0.0075     0.         0.0025     0.        ]
 [0.006      0.         0.028      0.004      0.         0.002
  0.96       0.         0.         0.        ]
 [0.         0.         0.         0.00833333 0.015      0.
  0.00166667 0.975      0.         0.        ]
 [0.00601202 0.         0.         0.01603206 0.         0.00200401
  0.         0.         0.9759519  0.        ]
 [0.00666667 0.01166667 0.005      0.00166667 0.         0.00333333
  0.         0.         0.00333333 0.96833333]]
[2023-08-24 13:42:34,285 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 13:42:34,287 INFO] 192512 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0254, train/total_loss: 0.0255, train/util_ratio: 0.8750, train/run_time: 0.5444, eval/loss: 0.3093, eval/top-1-acc: 0.9492, eval/balanced_acc: 0.9523, eval/precision: 0.9473, eval/recall: 0.9523, eval/F1: 0.9480, lr: 0.0000, train/prefecth_time: 0.0026 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 13:45:38,401 INFO] 192768 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2007, train/total_loss: 0.2007, train/util_ratio: 1.0000, train/run_time: 0.5299, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 13:48:01,089 INFO] 193024 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1002, train/total_loss: 0.1003, train/util_ratio: 1.0000, train/run_time: 0.5403, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 13:50:24,519 INFO] 193280 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.4321, train/total_loss: 0.4321, train/util_ratio: 1.0000, train/run_time: 0.5005, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 13:52:47,559 INFO] 193536 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0033, train/total_loss: 0.0033, train/util_ratio: 1.0000, train/run_time: 0.5443, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 13:55:52,230 INFO] 193792 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0083, train/total_loss: 0.0083, train/util_ratio: 1.0000, train/run_time: 0.4675, lr: 0.0000, train/prefecth_time: 0.0041 
[2023-08-24 13:58:16,439 INFO] 194048 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.4155, train/total_loss: 0.4155, train/util_ratio: 1.0000, train/run_time: 0.5431, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 14:00:38,580 INFO] 194304 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0031, train/total_loss: 0.0031, train/util_ratio: 1.0000, train/run_time: 0.5355, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 14:03:00,053 INFO] validating...
[2023-08-24 14:03:24,517 INFO] confusion matrix:
[[0.94166667 0.00166667 0.00166667 0.         0.         0.00833333
  0.04333333 0.         0.00333333 0.        ]
 [0.         0.89       0.00166667 0.         0.         0.10166667
  0.         0.005      0.00166667 0.        ]
 [0.         0.015      0.835      0.00166667 0.         0.07666667
  0.02333333 0.01333333 0.035      0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.0025     0.         0.0025     0.0075     0.         0.9825
  0.0025     0.         0.0025     0.        ]
 [0.008      0.         0.024      0.004      0.         0.002
  0.962      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01       0.
  0.         0.98666667 0.         0.        ]
 [0.00601202 0.         0.         0.01603206 0.         0.00200401
  0.         0.         0.9759519  0.        ]
 [0.00666667 0.01166667 0.00333333 0.00166667 0.         0.00333333
  0.         0.         0.00333333 0.97      ]]
[2023-08-24 14:03:25,347 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 14:03:25,348 INFO] 194560 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0438, train/total_loss: 0.0438, train/util_ratio: 0.8750, train/run_time: 0.4748, eval/loss: 0.3030, eval/top-1-acc: 0.9498, eval/balanced_acc: 0.9530, eval/precision: 0.9481, eval/recall: 0.9530, eval/F1: 0.9484, lr: 0.0000, train/prefecth_time: 0.0031 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 14:06:30,963 INFO] 194816 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.5618, train/total_loss: 0.5618, train/util_ratio: 1.0000, train/run_time: 0.5284, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 14:08:54,242 INFO] 195072 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0059, train/total_loss: 0.0059, train/util_ratio: 1.0000, train/run_time: 0.5511, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 14:11:17,985 INFO] 195328 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0038, train/total_loss: 0.0038, train/util_ratio: 1.0000, train/run_time: 0.5926, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 14:13:39,563 INFO] 195584 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1734, train/total_loss: 0.1735, train/util_ratio: 1.0000, train/run_time: 0.5364, lr: 0.0000, train/prefecth_time: 0.0026 
[2023-08-24 14:16:44,615 INFO] 195840 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0226, train/total_loss: 0.0226, train/util_ratio: 1.0000, train/run_time: 0.4835, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 14:19:06,194 INFO] 196096 iteration USE_EMA: False, train/sup_loss: 0.0006, train/unsup_loss: 0.0838, train/total_loss: 0.0844, train/util_ratio: 1.0000, train/run_time: 0.5365, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 14:21:28,423 INFO] 196352 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0098, train/total_loss: 0.0099, train/util_ratio: 0.7500, train/run_time: 0.4792, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 14:23:51,860 INFO] validating...
[2023-08-24 14:24:16,171 INFO] confusion matrix:
[[0.95333333 0.00166667 0.00166667 0.         0.         0.00666667
  0.035      0.         0.00166667 0.        ]
 [0.         0.88666667 0.00333333 0.         0.         0.10666667
  0.         0.00333333 0.         0.        ]
 [0.         0.015      0.88       0.00166667 0.         0.05333333
  0.01333333 0.00666667 0.03       0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.002      0.992      0.
  0.004      0.002      0.         0.        ]
 [0.005      0.         0.0025     0.01       0.         0.97
  0.01       0.         0.0025     0.        ]
 [0.01       0.         0.026      0.004      0.         0.
  0.96       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01       0.
  0.         0.98666667 0.         0.        ]
 [0.00601202 0.         0.         0.01803607 0.         0.00200401
  0.         0.         0.9739479  0.        ]
 [0.00666667 0.00833333 0.00333333 0.00166667 0.         0.00166667
  0.         0.         0.00333333 0.975     ]]
[2023-08-24 14:24:17,165 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 14:24:17,166 INFO] 196608 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.4689, train/total_loss: 0.4689, train/util_ratio: 1.0000, train/run_time: 0.4771, eval/loss: 0.2736, eval/top-1-acc: 0.9552, eval/balanced_acc: 0.9574, eval/precision: 0.9529, eval/recall: 0.9574, eval/F1: 0.9537, lr: 0.0000, train/prefecth_time: 0.0025 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 14:27:20,842 INFO] 196864 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0030, train/total_loss: 0.0030, train/util_ratio: 1.0000, train/run_time: 0.5138, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 14:29:42,978 INFO] 197120 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0755, train/total_loss: 0.0756, train/util_ratio: 1.0000, train/run_time: 0.5257, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 14:32:05,100 INFO] 197376 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2426, train/total_loss: 0.2426, train/util_ratio: 0.8750, train/run_time: 0.5457, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 14:34:26,911 INFO] 197632 iteration USE_EMA: False, train/sup_loss: 0.0003, train/unsup_loss: 0.0182, train/total_loss: 0.0185, train/util_ratio: 1.0000, train/run_time: 0.4801, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 14:37:31,051 INFO] 197888 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0085, train/total_loss: 0.0085, train/util_ratio: 1.0000, train/run_time: 0.4773, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 14:39:51,765 INFO] 198144 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.4339, train/total_loss: 0.4339, train/util_ratio: 1.0000, train/run_time: 0.5391, lr: 0.0000, train/prefecth_time: 0.0025 
[2023-08-24 14:42:13,386 INFO] 198400 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1111, train/total_loss: 0.1111, train/util_ratio: 1.0000, train/run_time: 0.5488, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 14:44:34,032 INFO] validating...
[2023-08-24 14:44:58,361 INFO] confusion matrix:
[[0.95166667 0.00166667 0.00166667 0.         0.         0.01
  0.03333333 0.         0.00166667 0.        ]
 [0.         0.88666667 0.00166667 0.         0.         0.10666667
  0.         0.005      0.         0.        ]
 [0.         0.01333333 0.87333333 0.00166667 0.         0.06333333
  0.01833333 0.01       0.02       0.        ]
 [0.         0.         0.         0.996      0.         0.
  0.         0.         0.004      0.        ]
 [0.         0.         0.         0.002      0.994      0.
  0.004      0.         0.         0.        ]
 [0.0025     0.         0.0025     0.0075     0.         0.9825
  0.005      0.         0.         0.        ]
 [0.01       0.         0.028      0.004      0.         0.002
  0.956      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01166667 0.
  0.         0.985      0.         0.        ]
 [0.00601202 0.         0.         0.02004008 0.         0.00200401
  0.         0.         0.97194389 0.        ]
 [0.00666667 0.01       0.00166667 0.00166667 0.         0.00333333
  0.         0.         0.00333333 0.97333333]]
[2023-08-24 14:44:59,401 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 14:44:59,403 INFO] 198656 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0542, train/total_loss: 0.0542, train/util_ratio: 0.8750, train/run_time: 0.5440, eval/loss: 0.2925, eval/top-1-acc: 0.9544, eval/balanced_acc: 0.9570, eval/precision: 0.9526, eval/recall: 0.9570, eval/F1: 0.9531, lr: 0.0000, train/prefecth_time: 0.0027 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 14:48:03,609 INFO] 198912 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0054, train/total_loss: 0.0054, train/util_ratio: 1.0000, train/run_time: 0.5379, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 14:50:24,629 INFO] 199168 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2747, train/total_loss: 0.2747, train/util_ratio: 0.8750, train/run_time: 0.5137, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 14:52:45,113 INFO] 199424 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0841, train/total_loss: 0.0842, train/util_ratio: 1.0000, train/run_time: 0.4788, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 14:55:06,064 INFO] 199680 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0007, train/total_loss: 0.0007, train/util_ratio: 1.0000, train/run_time: 0.5343, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 14:58:11,158 INFO] 199936 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0551, train/total_loss: 0.0551, train/util_ratio: 1.0000, train/run_time: 0.5390, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 15:00:33,287 INFO] 200192 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2240, train/total_loss: 0.2240, train/util_ratio: 1.0000, train/run_time: 0.5368, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 15:02:54,294 INFO] 200448 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.5735, train/total_loss: 0.5735, train/util_ratio: 1.0000, train/run_time: 0.5420, lr: 0.0000, train/prefecth_time: 0.0032 
[2023-08-24 15:05:16,178 INFO] validating...
[2023-08-24 15:05:40,131 INFO] confusion matrix:
[[0.95       0.00166667 0.00166667 0.         0.         0.00833333
  0.035      0.         0.00333333 0.        ]
 [0.         0.89       0.00166667 0.         0.         0.10333333
  0.         0.005      0.         0.        ]
 [0.         0.015      0.845      0.00166667 0.         0.06833333
  0.03666667 0.01       0.02333333 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.        ]
 [0.005      0.         0.         0.0075     0.         0.975
  0.01       0.         0.0025     0.        ]
 [0.014      0.         0.02       0.         0.         0.002
  0.964      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.02       0.
  0.00166667 0.975      0.         0.        ]
 [0.00400802 0.         0.         0.01603206 0.         0.00200401
  0.         0.         0.97795591 0.        ]
 [0.00833333 0.01       0.00166667 0.         0.         0.00333333
  0.         0.         0.00333333 0.97333333]]
[2023-08-24 15:05:41,235 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 15:05:41,236 INFO] 200704 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1299, train/total_loss: 0.1299, train/util_ratio: 1.0000, train/run_time: 0.5350, eval/loss: 0.2945, eval/top-1-acc: 0.9511, eval/balanced_acc: 0.9540, eval/precision: 0.9492, eval/recall: 0.9540, eval/F1: 0.9497, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 15:08:46,424 INFO] 200960 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.6313, train/total_loss: 0.6313, train/util_ratio: 1.0000, train/run_time: 0.4799, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 15:11:08,372 INFO] 201216 iteration USE_EMA: False, train/sup_loss: 0.0012, train/unsup_loss: 0.0027, train/total_loss: 0.0039, train/util_ratio: 0.8750, train/run_time: 0.5468, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 15:13:30,168 INFO] 201472 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0291, train/total_loss: 0.0291, train/util_ratio: 1.0000, train/run_time: 0.5412, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-24 15:15:52,625 INFO] 201728 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.2804, train/total_loss: 0.2804, train/util_ratio: 1.0000, train/run_time: 0.5438, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 15:18:57,260 INFO] 201984 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0142, train/total_loss: 0.0142, train/util_ratio: 0.8750, train/run_time: 0.5493, lr: 0.0000, train/prefecth_time: 0.0028 
[2023-08-24 15:21:19,815 INFO] 202240 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0220, train/total_loss: 0.0220, train/util_ratio: 1.0000, train/run_time: 0.5256, lr: 0.0000, train/prefecth_time: 0.0033 
[2023-08-24 15:23:41,423 INFO] 202496 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0916, train/total_loss: 0.0916, train/util_ratio: 1.0000, train/run_time: 0.4793, lr: 0.0000, train/prefecth_time: 0.0027 
[2023-08-24 15:26:04,070 INFO] validating...
[2023-08-24 15:26:28,354 INFO] confusion matrix:
[[0.955      0.00166667 0.00333333 0.         0.         0.005
  0.03333333 0.         0.00166667 0.        ]
 [0.         0.875      0.00166667 0.         0.         0.11833333
  0.         0.005      0.         0.        ]
 [0.         0.01       0.89166667 0.00333333 0.         0.05833333
  0.01333333 0.005      0.01833333 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.        ]
 [0.0075     0.         0.0025     0.0075     0.         0.9725
  0.0075     0.         0.0025     0.        ]
 [0.014      0.         0.03       0.006      0.         0.
  0.95       0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.015      0.
  0.         0.98166667 0.         0.        ]
 [0.00400802 0.         0.         0.01803607 0.         0.00200401
  0.         0.         0.9759519  0.        ]
 [0.00833333 0.01       0.00166667 0.         0.         0.00166667
  0.         0.         0.00333333 0.975     ]]
[2023-08-24 15:26:29,187 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 15:26:29,188 INFO] 202752 iteration, USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0009, train/total_loss: 0.0010, train/util_ratio: 1.0000, train/run_time: 0.5395, eval/loss: 0.3031, eval/top-1-acc: 0.9544, eval/balanced_acc: 0.9567, eval/precision: 0.9524, eval/recall: 0.9567, eval/F1: 0.9530, lr: 0.0000, train/prefecth_time: 0.0030 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 15:29:32,544 INFO] 203008 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.5495, train/total_loss: 0.5495, train/util_ratio: 1.0000, train/run_time: 0.5413, lr: 0.0000, train/prefecth_time: 0.0030 
[2023-08-24 15:31:54,312 INFO] 203264 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0559, train/total_loss: 0.0559, train/util_ratio: 1.0000, train/run_time: 0.5534, lr: 0.0000, train/prefecth_time: 0.0036 
[2023-08-24 15:34:15,592 INFO] 203520 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.0030, train/total_loss: 0.0031, train/util_ratio: 1.0000, train/run_time: 0.4769, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 15:36:37,435 INFO] 203776 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.1093, train/total_loss: 0.1093, train/util_ratio: 1.0000, train/run_time: 0.4779, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 15:39:41,514 INFO] 204032 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0156, train/total_loss: 0.0156, train/util_ratio: 1.0000, train/run_time: 0.4973, lr: 0.0000, train/prefecth_time: 0.0031 
[2023-08-24 15:42:03,330 INFO] 204288 iteration USE_EMA: False, train/sup_loss: 0.0001, train/unsup_loss: 0.5053, train/total_loss: 0.5054, train/util_ratio: 1.0000, train/run_time: 0.5387, lr: 0.0000, train/prefecth_time: 0.0039 
[2023-08-24 15:44:26,501 INFO] 204544 iteration USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0055, train/total_loss: 0.0055, train/util_ratio: 1.0000, train/run_time: 0.5386, lr: 0.0000, train/prefecth_time: 0.0029 
[2023-08-24 15:46:47,641 INFO] validating...
[2023-08-24 15:47:11,902 INFO] confusion matrix:
[[0.96       0.00166667 0.00333333 0.         0.         0.00666667
  0.02666667 0.         0.00166667 0.        ]
 [0.         0.845      0.00166667 0.         0.         0.14833333
  0.         0.005      0.         0.        ]
 [0.         0.01166667 0.87333333 0.00166667 0.         0.07666667
  0.015      0.00666667 0.015      0.        ]
 [0.         0.         0.         0.994      0.         0.
  0.         0.         0.006      0.        ]
 [0.         0.         0.         0.004      0.992      0.
  0.004      0.         0.         0.        ]
 [0.005      0.         0.0025     0.0075     0.         0.98
  0.005      0.         0.         0.        ]
 [0.014      0.         0.028      0.002      0.         0.002
  0.954      0.         0.         0.        ]
 [0.         0.         0.         0.00333333 0.01333333 0.
  0.         0.98333333 0.         0.        ]
 [0.00400802 0.         0.         0.01803607 0.         0.00200401
  0.         0.         0.9759519  0.        ]
 [0.00833333 0.01       0.00166667 0.         0.         0.005
  0.         0.         0.00333333 0.97166667]]
[2023-08-24 15:47:12,925 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 15:47:12,926 INFO] 204800 iteration, USE_EMA: False, train/sup_loss: 0.0000, train/unsup_loss: 0.0049, train/total_loss: 0.0049, train/util_ratio: 1.0000, train/run_time: 0.5334, eval/loss: 0.3320, eval/top-1-acc: 0.9500, eval/balanced_acc: 0.9529, eval/precision: 0.9493, eval/recall: 0.9529, eval/F1: 0.9486, lr: 0.0000, train/prefecth_time: 0.0029 BEST_EVAL_ACC: 0.9567, at 159744 iters
[2023-08-24 15:47:15,652 INFO] model saved: ./saved_models/usb_cv/flexmatch_eurosat_20_0/latest_model.pth
[2023-08-24 15:47:15,653 INFO] Model result - eval/best_acc : 0.9566586404889794
[2023-08-24 15:47:15,653 INFO] Model result - eval/best_it : 159743
