well-trained model
Browse files- SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/args.yaml +143 -0
- SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/log.txt +631 -0
- SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/model_best.pth.tar +3 -0
- SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/summary.csv +51 -0
- Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/args.yaml +150 -0
- Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/log.txt +860 -0
- Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/model_best.pth.tar +3 -0
- Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/summary.csv +51 -0
SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/args.yaml
ADDED
|
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| 1 |
+
DVS_DA: false
|
| 2 |
+
TET_loss_first: false
|
| 3 |
+
TET_loss_second: false
|
| 4 |
+
aa: rand-m9-mstd0.5-inc1
|
| 5 |
+
act_fun: BackEIGateGrad
|
| 6 |
+
adam_epoch: 1000
|
| 7 |
+
adaptive_node: false
|
| 8 |
+
amp: false
|
| 9 |
+
apex_amp: false
|
| 10 |
+
aug_splits: 0
|
| 11 |
+
batch_size: 16
|
| 12 |
+
bn_eps: null
|
| 13 |
+
bn_momentum: null
|
| 14 |
+
bn_tf: false
|
| 15 |
+
camvis: false
|
| 16 |
+
channels_last: false
|
| 17 |
+
clip_grad: null
|
| 18 |
+
color_jitter: 0.4
|
| 19 |
+
conf_mat: false
|
| 20 |
+
cooldown_epochs: 10
|
| 21 |
+
critical_loss: false
|
| 22 |
+
crop_pct: null
|
| 23 |
+
cut_mix: false
|
| 24 |
+
cutmix: 1.0
|
| 25 |
+
cutmix_beta: 1.0
|
| 26 |
+
cutmix_minmax: null
|
| 27 |
+
cutmix_noise: 0.0
|
| 28 |
+
cutmix_num: 1
|
| 29 |
+
cutmix_prob: 0.5
|
| 30 |
+
dataset: nomni
|
| 31 |
+
decay_epochs: 40.0
|
| 32 |
+
decay_rate: 0.1
|
| 33 |
+
device: 6
|
| 34 |
+
dist_bn: ''
|
| 35 |
+
drop: 0.0
|
| 36 |
+
drop_block: null
|
| 37 |
+
drop_connect: null
|
| 38 |
+
drop_path: 0.1
|
| 39 |
+
encode: direct
|
| 40 |
+
epochs: 50
|
| 41 |
+
eval: false
|
| 42 |
+
eval_checkpoint: ''
|
| 43 |
+
eval_metric: top1
|
| 44 |
+
event_mix: false
|
| 45 |
+
event_size: 48
|
| 46 |
+
gaussian_n: 3
|
| 47 |
+
gp: null
|
| 48 |
+
hflip: 0.5
|
| 49 |
+
img_size: 224
|
| 50 |
+
initial_checkpoint: ''
|
| 51 |
+
interpolation: ''
|
| 52 |
+
jsd: false
|
| 53 |
+
kernel_method: cuda
|
| 54 |
+
layer_by_layer: false
|
| 55 |
+
local_rank: 0
|
| 56 |
+
log_interval: 500
|
| 57 |
+
loss_fn: ce
|
| 58 |
+
lr: 1.2
|
| 59 |
+
lr_cycle_limit: 1
|
| 60 |
+
lr_cycle_mul: 1.0
|
| 61 |
+
lr_noise: null
|
| 62 |
+
lr_noise_pct: 0.67
|
| 63 |
+
lr_noise_std: 1.0
|
| 64 |
+
mean: null
|
| 65 |
+
min_lr: 1.0e-05
|
| 66 |
+
mix_up: false
|
| 67 |
+
mixup: 0.8
|
| 68 |
+
mixup_mode: batch
|
| 69 |
+
mixup_off_epoch: 0
|
| 70 |
+
mixup_prob: 1.0
|
| 71 |
+
mixup_switch_prob: 0.5
|
| 72 |
+
model: SCNN
|
| 73 |
+
model_ema: false
|
| 74 |
+
model_ema_decay: 0.99996
|
| 75 |
+
model_ema_force_cpu: false
|
| 76 |
+
momentum: 0.9
|
| 77 |
+
n_groups: 1
|
| 78 |
+
native_amp: false
|
| 79 |
+
newton_maxiter: 20
|
| 80 |
+
no_aug: false
|
| 81 |
+
no_prefetcher: false
|
| 82 |
+
no_resume_opt: false
|
| 83 |
+
node_resume: ''
|
| 84 |
+
node_trainable: false
|
| 85 |
+
node_type: LIFNode
|
| 86 |
+
noisy_grad: 0.0
|
| 87 |
+
num_classes: 1623
|
| 88 |
+
num_gpu: 1
|
| 89 |
+
opt: adamw
|
| 90 |
+
opt_betas: null
|
| 91 |
+
opt_eps: 1.0e-08
|
| 92 |
+
output: /home/hexiang/DomainAdaptation_DVS/Results/
|
| 93 |
+
patience_epochs: 10
|
| 94 |
+
pin_mem: false
|
| 95 |
+
power: 1
|
| 96 |
+
pretrained: false
|
| 97 |
+
rand_aug: false
|
| 98 |
+
randaug_m: 15
|
| 99 |
+
randaug_n: 3
|
| 100 |
+
ratio:
|
| 101 |
+
- 0.75
|
| 102 |
+
- 1.3333333333333333
|
| 103 |
+
reconstructed: false
|
| 104 |
+
recount: 1
|
| 105 |
+
recovery_interval: 0
|
| 106 |
+
remode: pixel
|
| 107 |
+
reprob: 0.25
|
| 108 |
+
requires_thres_grad: false
|
| 109 |
+
reset_drop: false
|
| 110 |
+
resplit: false
|
| 111 |
+
resume: ''
|
| 112 |
+
save_images: false
|
| 113 |
+
scale:
|
| 114 |
+
- 0.08
|
| 115 |
+
- 1.0
|
| 116 |
+
sched: step
|
| 117 |
+
seed: 1024
|
| 118 |
+
sigmoid_thres: false
|
| 119 |
+
smoothing: 0.0
|
| 120 |
+
spike_output: false
|
| 121 |
+
spike_rate: false
|
| 122 |
+
split_bn: false
|
| 123 |
+
start_epoch: null
|
| 124 |
+
std: null
|
| 125 |
+
step: 12
|
| 126 |
+
suffix: ''
|
| 127 |
+
sync_bn: false
|
| 128 |
+
tau: 2.0
|
| 129 |
+
temporal_flatten: false
|
| 130 |
+
threshold: 0.5
|
| 131 |
+
train_interpolation: random
|
| 132 |
+
train_portion: 0.9
|
| 133 |
+
traindata_ratio: 1.0
|
| 134 |
+
tsne: false
|
| 135 |
+
tta: 0
|
| 136 |
+
use_multi_epochs_loader: false
|
| 137 |
+
validation_batch_size_multiplier: 1
|
| 138 |
+
vflip: 0.0
|
| 139 |
+
visualize: false
|
| 140 |
+
warmup_epochs: 5
|
| 141 |
+
warmup_lr: 1.0e-06
|
| 142 |
+
weight_decay: 0.01
|
| 143 |
+
workers: 8
|
SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/log.txt
ADDED
|
@@ -0,0 +1,631 @@
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| 1 |
+
2023-08-14 11:38:06,097 - train: [ INFO] - Training with a single process on 1 GPUs.
|
| 2 |
+
2023-08-14 11:38:06,111 - train: [ INFO] - learning rate is 0.018750
|
| 3 |
+
2023-08-14 11:38:06,111 - train: [ INFO] - Model SCNN created, param count: 696579
|
| 4 |
+
2023-08-14 11:38:10,070 - train: [ INFO] - AMP not enabled. Training in float32.
|
| 5 |
+
2023-08-14 11:38:10,071 - train: [ INFO] - Scheduled epochs: 50
|
| 6 |
+
2023-08-14 11:38:15,025 - train: [ INFO] - Train: 0 [ 0/1521 (100%)] Loss: 7.394501 (7.3945) Acc@1: 0.0000 ( 0.0000) Acc@5: 0.0000 ( 0.0000) Time: 3.905s, 4.10/s (3.905s, 4.10/s) LR: 1.000e-06
|
| 7 |
+
2023-08-14 11:38:32,545 - train: [ INFO] - Train: 0 [ 500/1521 (100%)] Loss: 7.400451 (7.3924) Acc@1: 0.0000 ( 0.0374) Acc@5: 0.0000 ( 0.3244) Time: 0.037s, 436.15/s (0.043s, 374.23/s) LR: 1.000e-06
|
| 8 |
+
2023-08-14 11:38:52,090 - train: [ INFO] - Train: 0 [1000/1521 (100%)] Loss: 7.395097 (7.3925) Acc@1: 0.0000 ( 0.0375) Acc@5: 0.0000 ( 0.3122) Time: 0.041s, 393.55/s (0.041s, 391.02/s) LR: 1.000e-06
|
| 9 |
+
2023-08-14 11:39:12,831 - train: [ INFO] - Train: 0 [1500/1521 (100%)] Loss: 7.392328 (7.3926) Acc@1: 0.0000 ( 0.0541) Acc@5: 0.0000 ( 0.3081) Time: 0.045s, 357.30/s (0.041s, 389.27/s) LR: 1.000e-06
|
| 10 |
+
2023-08-14 11:39:13,635 - train: [ INFO] - Train: 0 [1520/1521 (100%)] Loss: 7.399750 (7.3926) Acc@1: 0.0000 ( 0.0534) Acc@5: 0.0000 ( 0.3041) Time: 0.036s, 445.86/s (0.041s, 389.38/s) LR: 1.000e-06
|
| 11 |
+
2023-08-14 11:39:13,949 - train: [ INFO] - Test: [ 0/507] Time: 0.249 (0.249) Loss: 7.3901 (7.3901) Acc@1: 0.0000 ( 0.0000)Acc@5: 0.0000 ( 0.0000)
|
| 12 |
+
|
| 13 |
+
2023-08-14 11:39:22,473 - train: [ INFO] - Test: [ 500/507] Time: 0.019 (0.018) Loss: 7.3610 (7.3926) Acc@1: 0.0000 ( 0.0624)Acc@5: 0.0000 ( 0.3119)
|
| 14 |
+
|
| 15 |
+
2023-08-14 11:39:22,594 - train: [ INFO] - Test: [ 507/507] Time: 0.017 (0.018) Loss: 7.3385 (7.3926) Acc@1: 0.0000 ( 0.0616)Acc@5: 0.0000 ( 0.3081)
|
| 16 |
+
|
| 17 |
+
2023-08-14 11:39:22,688 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 18 |
+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-0.pth.tar', 0.061614294516327786)
|
| 19 |
+
|
| 20 |
+
2023-08-14 11:39:23,125 - train: [ INFO] - Train: 1 [ 0/1521 (100%)] Loss: 7.380402 (7.3804) Acc@1: 0.0000 ( 0.0000) Acc@5: 0.0000 ( 0.0000) Time: 0.437s, 36.61/s (0.437s, 36.61/s) LR: 3.751e-03
|
| 21 |
+
2023-08-14 11:39:44,229 - train: [ INFO] - Train: 1 [ 500/1521 (100%)] Loss: 7.223928 (7.3917) Acc@1: 0.0000 ( 0.0998) Acc@5: 0.0000 ( 0.3743) Time: 0.040s, 396.11/s (0.043s, 372.22/s) LR: 3.751e-03
|
| 22 |
+
2023-08-14 11:40:05,508 - train: [ INFO] - Train: 1 [1000/1521 (100%)] Loss: 6.831066 (7.2411) Acc@1: 0.0000 ( 0.3059) Acc@5: 0.0000 ( 1.3112) Time: 0.045s, 351.95/s (0.043s, 374.13/s) LR: 3.751e-03
|
| 23 |
+
2023-08-14 11:40:26,538 - train: [ INFO] - Train: 1 [1500/1521 (100%)] Loss: 6.107768 (7.0026) Acc@1: 0.0000 ( 0.7537) Acc@5: 12.5000 ( 2.9106) Time: 0.039s, 409.03/s (0.043s, 376.22/s) LR: 3.751e-03
|
| 24 |
+
2023-08-14 11:40:27,331 - train: [ INFO] - Train: 1 [1520/1521 (100%)] Loss: 6.123400 (6.9930) Acc@1: 0.0000 ( 0.7520) Acc@5: 6.2500 ( 2.9339) Time: 0.035s, 451.11/s (0.042s, 376.56/s) LR: 3.751e-03
|
| 25 |
+
2023-08-14 11:40:27,687 - train: [ INFO] - Test: [ 0/507] Time: 0.233 (0.233) Loss: 6.2043 (6.2043) Acc@1: 0.0000 ( 0.0000)Acc@5: 6.2500 ( 6.2500)
|
| 26 |
+
|
| 27 |
+
2023-08-14 11:40:36,028 - train: [ INFO] - Test: [ 500/507] Time: 0.017 (0.017) Loss: 5.9023 (6.0272) Acc@1: 12.5000 ( 3.7176)Acc@5: 12.5000 (11.6392)
|
| 28 |
+
|
| 29 |
+
2023-08-14 11:40:36,145 - train: [ INFO] - Test: [ 507/507] Time: 0.017 (0.017) Loss: 5.7701 (6.0192) Acc@1: 0.0000 ( 3.7708)Acc@5: 33.3333 (11.7930)
|
| 30 |
+
|
| 31 |
+
2023-08-14 11:40:36,276 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 32 |
+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-1.pth.tar', 3.770794824399261)
|
| 33 |
+
|
| 34 |
+
2023-08-14 11:40:36,717 - train: [ INFO] - Train: 2 [ 0/1521 (100%)] Loss: 5.829011 (5.8290) Acc@1: 0.0000 ( 0.0000) Acc@5: 6.2500 ( 6.2500) Time: 0.440s, 36.37/s (0.440s, 36.37/s) LR: 7.501e-03
|
| 35 |
+
2023-08-14 11:40:57,337 - train: [ INFO] - Train: 2 [ 500/1521 (100%)] Loss: 4.673635 (5.5224) Acc@1: 18.7500 ( 6.0254) Acc@5: 31.2500 (17.2655) Time: 0.037s, 427.64/s (0.042s, 380.73/s) LR: 7.501e-03
|
| 36 |
+
2023-08-14 11:41:17,790 - train: [ INFO] - Train: 2 [1000/1521 (100%)] Loss: 4.651268 (5.2131) Acc@1: 25.0000 ( 8.3042) Acc@5: 43.7500 (22.0842) Time: 0.042s, 377.15/s (0.041s, 385.90/s) LR: 7.501e-03
|
| 37 |
+
2023-08-14 11:41:38,747 - train: [ INFO] - Train: 2 [1500/1521 (100%)] Loss: 3.863883 (4.9920) Acc@1: 18.7500 ( 9.9933) Acc@5: 56.2500 (25.7870) Time: 0.032s, 500.97/s (0.042s, 384.53/s) LR: 7.501e-03
|
| 38 |
+
2023-08-14 11:41:39,477 - train: [ INFO] - Train: 2 [1520/1521 (100%)] Loss: 4.111261 (4.9838) Acc@1: 18.7500 (10.0674) Acc@5: 43.7500 (25.9369) Time: 0.033s, 482.75/s (0.042s, 385.16/s) LR: 7.501e-03
|
| 39 |
+
2023-08-14 11:41:39,819 - train: [ INFO] - Test: [ 0/507] Time: 0.223 (0.223) Loss: 3.9865 (3.9865) Acc@1: 18.7500 (18.7500)Acc@5: 50.0000 (50.0000)
|
| 40 |
+
|
| 41 |
+
2023-08-14 11:41:48,394 - train: [ INFO] - Test: [ 500/507] Time: 0.014 (0.018) Loss: 4.7875 (4.5625) Acc@1: 0.0000 (13.5604)Acc@5: 18.7500 (33.7325)
|
| 42 |
+
|
| 43 |
+
2023-08-14 11:41:48,507 - train: [ INFO] - Test: [ 507/507] Time: 0.014 (0.018) Loss: 5.7907 (4.5594) Acc@1: 0.0000 (13.5551)Acc@5: 0.0000 (33.7646)
|
| 44 |
+
|
| 45 |
+
2023-08-14 11:41:48,631 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 46 |
+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-2.pth.tar', 13.555144793592113)
|
| 47 |
+
|
| 48 |
+
2023-08-14 11:41:49,059 - train: [ INFO] - Train: 3 [ 0/1521 (100%)] Loss: 3.697828 (3.6978) Acc@1: 37.5000 (37.5000) Acc@5: 50.0000 (50.0000) Time: 0.427s, 37.50/s (0.427s, 37.50/s) LR: 1.125e-02
|
| 49 |
+
2023-08-14 11:42:10,083 - train: [ INFO] - Train: 3 [ 500/1521 (100%)] Loss: 3.617290 (3.9872) Acc@1: 25.0000 (18.8249) Acc@5: 62.5000 (42.8643) Time: 0.054s, 296.95/s (0.043s, 373.78/s) LR: 1.125e-02
|
| 50 |
+
2023-08-14 11:42:31,681 - train: [ INFO] - Train: 3 [1000/1521 (100%)] Loss: 3.526606 (3.8882) Acc@1: 37.5000 (20.5107) Acc@5: 68.7500 (45.2922) Time: 0.046s, 347.12/s (0.043s, 372.14/s) LR: 1.125e-02
|
| 51 |
+
2023-08-14 11:42:52,437 - train: [ INFO] - Train: 3 [1500/1521 (100%)] Loss: 2.630880 (3.7894) Acc@1: 37.5000 (21.7313) Acc@5: 68.7500 (47.1019) Time: 0.041s, 387.38/s (0.042s, 376.49/s) LR: 1.125e-02
|
| 52 |
+
2023-08-14 11:42:53,261 - train: [ INFO] - Train: 3 [1520/1521 (100%)] Loss: 3.217838 (3.7852) Acc@1: 18.7500 (21.7661) Acc@5: 43.7500 (47.1811) Time: 0.048s, 333.49/s (0.042s, 376.64/s) LR: 1.125e-02
|
| 53 |
+
2023-08-14 11:42:53,607 - train: [ INFO] - Test: [ 0/507] Time: 0.232 (0.232) Loss: 2.9919 (2.9919) Acc@1: 25.0000 (25.0000)Acc@5: 62.5000 (62.5000)
|
| 54 |
+
|
| 55 |
+
2023-08-14 11:43:02,075 - train: [ INFO] - Test: [ 500/507] Time: 0.015 (0.017) Loss: 3.7877 (3.7068) Acc@1: 0.0000 (24.4511)Acc@5: 37.5000 (50.5739)
|
| 56 |
+
|
| 57 |
+
2023-08-14 11:43:02,230 - train: [ INFO] - Test: [ 507/507] Time: 0.024 (0.017) Loss: 1.8805 (3.7027) Acc@1: 100.0000 (24.4116)Acc@5: 100.0000 (50.5977)
|
| 58 |
+
|
| 59 |
+
2023-08-14 11:43:02,329 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 60 |
+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-3.pth.tar', 24.411583487369068)
|
| 61 |
+
|
| 62 |
+
2023-08-14 11:43:02,798 - train: [ INFO] - Train: 4 [ 0/1521 (100%)] Loss: 3.153165 (3.1532) Acc@1: 18.7500 (18.7500) Acc@5: 56.2500 (56.2500) Time: 0.467s, 34.24/s (0.467s, 34.24/s) LR: 1.500e-02
|
| 63 |
+
2023-08-14 11:43:27,813 - train: [ INFO] - Train: 4 [ 500/1521 (100%)] Loss: 2.868305 (3.1961) Acc@1: 37.5000 (29.4910) Acc@5: 75.0000 (58.1337) Time: 0.046s, 349.17/s (0.051s, 314.64/s) LR: 1.500e-02
|
| 64 |
+
2023-08-14 11:43:53,932 - train: [ INFO] - Train: 4 [1000/1521 (100%)] Loss: 3.580038 (3.1704) Acc@1: 31.2500 (29.8327) Acc@5: 56.2500 (58.8474) Time: 0.042s, 379.78/s (0.052s, 310.46/s) LR: 1.500e-02
|
| 65 |
+
2023-08-14 11:44:20,567 - train: [ INFO] - Train: 4 [1500/1521 (100%)] Loss: 2.664454 (3.1516) Acc@1: 31.2500 (30.2007) Acc@5: 56.2500 (59.4104) Time: 0.055s, 292.45/s (0.052s, 307.04/s) LR: 1.500e-02
|
| 66 |
+
2023-08-14 11:44:21,669 - train: [ INFO] - Train: 4 [1520/1521 (100%)] Loss: 3.833821 (3.1523) Acc@1: 12.5000 (30.1775) Acc@5: 43.7500 (59.4099) Time: 0.046s, 345.24/s (0.052s, 306.81/s) LR: 1.500e-02
|
| 67 |
+
2023-08-14 11:44:22,001 - train: [ INFO] - Test: [ 0/507] Time: 0.234 (0.234) Loss: 2.3624 (2.3624) Acc@1: 43.7500 (43.7500)Acc@5: 62.5000 (62.5000)
|
| 68 |
+
|
| 69 |
+
2023-08-14 11:44:33,097 - train: [ INFO] - Test: [ 500/507] Time: 0.030 (0.023) Loss: 4.0831 (3.3958) Acc@1: 0.0000 (28.5429)Acc@5: 31.2500 (56.2625)
|
| 70 |
+
|
| 71 |
+
2023-08-14 11:44:33,239 - train: [ INFO] - Test: [ 507/507] Time: 0.018 (0.023) Loss: 2.8070 (3.3947) Acc@1: 33.3333 (28.4165)Acc@5: 100.0000 (56.2415)
|
| 72 |
+
|
| 73 |
+
2023-08-14 11:44:33,338 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 74 |
+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-4.pth.tar', 28.416512631870535)
|
| 75 |
+
|
| 76 |
+
2023-08-14 11:44:33,811 - train: [ INFO] - Train: 5 [ 0/1521 (100%)] Loss: 2.139302 (2.1393) Acc@1: 50.0000 (50.0000) Acc@5: 81.2500 (81.2500) Time: 0.471s, 33.94/s (0.471s, 33.94/s) LR: 1.875e-02
|
| 77 |
+
2023-08-14 11:44:59,518 - train: [ INFO] - Train: 5 [ 500/1521 (100%)] Loss: 2.732995 (2.7597) Acc@1: 37.5000 (36.0404) Acc@5: 62.5000 (67.1532) Time: 0.036s, 448.35/s (0.052s, 306.27/s) LR: 1.875e-02
|
| 78 |
+
2023-08-14 11:45:26,626 - train: [ INFO] - Train: 5 [1000/1521 (100%)] Loss: 2.920964 (2.8127) Acc@1: 37.5000 (35.0337) Acc@5: 43.7500 (65.9590) Time: 0.039s, 407.28/s (0.053s, 300.62/s) LR: 1.875e-02
|
| 79 |
+
2023-08-14 11:45:53,133 - train: [ INFO] - Train: 5 [1500/1521 (100%)] Loss: 2.498252 (2.8114) Acc@1: 25.0000 (35.2848) Acc@5: 75.0000 (65.9852) Time: 0.051s, 313.44/s (0.053s, 301.04/s) LR: 1.875e-02
|
| 80 |
+
2023-08-14 11:45:54,126 - train: [ INFO] - Train: 5 [1520/1521 (100%)] Loss: 3.421094 (2.8131) Acc@1: 18.7500 (35.2728) Acc@5: 50.0000 (65.9352) Time: 0.049s, 325.99/s (0.053s, 301.30/s) LR: 1.875e-02
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2023-08-14 11:45:54,447 - train: [ INFO] - Test: [ 0/507] Time: 0.237 (0.237) Loss: 2.2780 (2.2780) Acc@1: 31.2500 (31.2500)Acc@5: 93.7500 (93.7500)
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2023-08-14 11:46:05,269 - train: [ INFO] - Test: [ 500/507] Time: 0.025 (0.022) Loss: 5.2645 (3.1537) Acc@1: 0.0000 (31.6492)Acc@5: 12.5000 (61.2899)
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2023-08-14 11:46:05,412 - train: [ INFO] - Test: [ 507/507] Time: 0.022 (0.022) Loss: 2.4773 (3.1584) Acc@1: 33.3333 (31.4356)Acc@5: 100.0000 (61.1460)
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+
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+
2023-08-14 11:46:05,538 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-5.pth.tar', 31.435613063170596)
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2023-08-14 11:46:06,000 - train: [ INFO] - Train: 6 [ 0/1521 (100%)] Loss: 2.698309 (2.6983) Acc@1: 18.7500 (18.7500) Acc@5: 62.5000 (62.5000) Time: 0.460s, 34.81/s (0.460s, 34.81/s) LR: 1.875e-02
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2023-08-14 11:46:32,016 - train: [ INFO] - Train: 6 [ 500/1521 (100%)] Loss: 2.163499 (2.3855) Acc@1: 37.5000 (42.6023) Acc@5: 81.2500 (74.2515) Time: 0.066s, 241.19/s (0.053s, 302.82/s) LR: 1.875e-02
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2023-08-14 11:46:58,945 - train: [ INFO] - Train: 6 [1000/1521 (100%)] Loss: 2.770019 (2.4656) Acc@1: 37.5000 (41.5709) Acc@5: 75.0000 (72.5212) Time: 0.058s, 273.59/s (0.053s, 299.96/s) LR: 1.875e-02
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2023-08-14 11:47:24,584 - train: [ INFO] - Train: 6 [1500/1521 (100%)] Loss: 3.092036 (2.4958) Acc@1: 37.5000 (40.9394) Acc@5: 62.5000 (72.0395) Time: 0.049s, 328.41/s (0.053s, 303.89/s) LR: 1.875e-02
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2023-08-14 11:47:25,565 - train: [ INFO] - Train: 6 [1520/1521 (100%)] Loss: 2.737461 (2.4991) Acc@1: 50.0000 (40.9106) Acc@5: 62.5000 (71.9839) Time: 0.039s, 410.56/s (0.053s, 304.17/s) LR: 1.875e-02
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2023-08-14 11:47:25,870 - train: [ INFO] - Test: [ 0/507] Time: 0.231 (0.231) Loss: 1.9921 (1.9921) Acc@1: 37.5000 (37.5000)Acc@5: 75.0000 (75.0000)
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2023-08-14 11:47:37,241 - train: [ INFO] - Test: [ 500/507] Time: 0.019 (0.023) Loss: 4.5381 (2.9958) Acc@1: 6.2500 (34.9177)Acc@5: 25.0000 (63.9596)
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2023-08-14 11:47:37,405 - train: [ INFO] - Test: [ 507/507] Time: 0.023 (0.023) Loss: 2.2037 (2.9986) Acc@1: 33.3333 (34.7998)Acc@5: 100.0000 (63.9187)
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2023-08-14 11:47:37,494 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-6.pth.tar', 34.799753543762094)
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2023-08-14 11:47:37,961 - train: [ INFO] - Train: 7 [ 0/1521 (100%)] Loss: 3.002996 (3.0030) Acc@1: 31.2500 (31.2500) Acc@5: 56.2500 (56.2500) Time: 0.466s, 34.33/s (0.466s, 34.33/s) LR: 1.875e-02
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2023-08-14 11:48:04,268 - train: [ INFO] - Train: 7 [ 500/1521 (100%)] Loss: 2.223528 (2.1216) Acc@1: 31.2500 (48.2660) Acc@5: 87.5000 (78.3807) Time: 0.038s, 421.02/s (0.053s, 299.47/s) LR: 1.875e-02
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2023-08-14 11:48:31,453 - train: [ INFO] - Train: 7 [1000/1521 (100%)] Loss: 2.243523 (2.2072) Acc@1: 31.2500 (46.3412) Acc@5: 87.5000 (77.0792) Time: 0.059s, 269.07/s (0.054s, 296.88/s) LR: 1.875e-02
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2023-08-14 11:48:57,297 - train: [ INFO] - Train: 7 [1500/1521 (100%)] Loss: 2.361006 (2.2790) Acc@1: 37.5000 (45.1907) Acc@5: 81.2500 (76.0368) Time: 0.051s, 315.17/s (0.053s, 301.00/s) LR: 1.875e-02
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2023-08-14 11:48:58,316 - train: [ INFO] - Train: 7 [1520/1521 (100%)] Loss: 2.634477 (2.2803) Acc@1: 18.7500 (45.1307) Acc@5: 68.7500 (76.0396) Time: 0.072s, 221.14/s (0.053s, 301.17/s) LR: 1.875e-02
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2023-08-14 11:48:58,692 - train: [ INFO] - Test: [ 0/507] Time: 0.243 (0.243) Loss: 2.2758 (2.2758) Acc@1: 43.7500 (43.7500)Acc@5: 81.2500 (81.2500)
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2023-08-14 11:49:09,914 - train: [ INFO] - Test: [ 500/507] Time: 0.021 (0.023) Loss: 3.4154 (2.7981) Acc@1: 12.5000 (37.7495)Acc@5: 62.5000 (67.4027)
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2023-08-14 11:49:10,054 - train: [ INFO] - Test: [ 507/507] Time: 0.015 (0.023) Loss: 1.6784 (2.7948) Acc@1: 66.6667 (37.7079)Acc@5: 100.0000 (67.4430)
|
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+
2023-08-14 11:49:10,181 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-7.pth.tar', 37.70794824587293)
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2023-08-14 11:49:10,626 - train: [ INFO] - Train: 8 [ 0/1521 (100%)] Loss: 2.279775 (2.2798) Acc@1: 56.2500 (56.2500) Acc@5: 68.7500 (68.7500) Time: 0.444s, 36.00/s (0.444s, 36.00/s) LR: 1.875e-02
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2023-08-14 11:49:37,614 - train: [ INFO] - Train: 8 [ 500/1521 (100%)] Loss: 2.877592 (2.0253) Acc@1: 31.2500 (49.7006) Acc@5: 62.5000 (80.5514) Time: 0.065s, 245.10/s (0.055s, 292.28/s) LR: 1.875e-02
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2023-08-14 11:50:04,485 - train: [ INFO] - Train: 8 [1000/1521 (100%)] Loss: 1.693362 (2.0886) Acc@1: 43.7500 (48.1956) Acc@5: 93.7500 (79.2707) Time: 0.041s, 394.71/s (0.054s, 295.00/s) LR: 1.875e-02
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2023-08-14 11:50:30,355 - train: [ INFO] - Train: 8 [1500/1521 (100%)] Loss: 1.719934 (2.1272) Acc@1: 43.7500 (47.7682) Acc@5: 87.5000 (78.6309) Time: 0.053s, 299.20/s (0.053s, 299.61/s) LR: 1.875e-02
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2023-08-14 11:50:31,335 - train: [ INFO] - Train: 8 [1520/1521 (100%)] Loss: 1.447373 (2.1312) Acc@1: 62.5000 (47.6619) Acc@5: 87.5000 (78.5791) Time: 0.052s, 308.28/s (0.053s, 299.94/s) LR: 1.875e-02
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2023-08-14 11:50:31,665 - train: [ INFO] - Test: [ 0/507] Time: 0.236 (0.236) Loss: 1.9691 (1.9691) Acc@1: 43.7500 (43.7500)Acc@5: 81.2500 (81.2500)
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2023-08-14 11:50:42,836 - train: [ INFO] - Test: [ 500/507] Time: 0.051 (0.023) Loss: 3.4989 (2.7264) Acc@1: 6.2500 (38.0240)Acc@5: 62.5000 (67.9641)
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2023-08-14 11:50:42,987 - train: [ INFO] - Test: [ 507/507] Time: 0.020 (0.023) Loss: 0.6794 (2.7263) Acc@1: 100.0000 (37.9667)Acc@5: 100.0000 (67.9236)
|
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+
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+
2023-08-14 11:50:43,117 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
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+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-8.pth.tar', 37.966728280961185)
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+
2023-08-14 11:50:43,579 - train: [ INFO] - Train: 9 [ 0/1521 (100%)] Loss: 1.376547 (1.3765) Acc@1: 75.0000 (75.0000) Acc@5: 93.7500 (93.7500) Time: 0.461s, 34.73/s (0.461s, 34.73/s) LR: 1.875e-02
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2023-08-14 11:51:09,927 - train: [ INFO] - Train: 9 [ 500/1521 (100%)] Loss: 1.663361 (1.8706) Acc@1: 50.0000 (53.1188) Acc@5: 87.5000 (83.6452) Time: 0.058s, 276.88/s (0.054s, 299.06/s) LR: 1.875e-02
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2023-08-14 11:51:35,579 - train: [ INFO] - Train: 9 [1000/1521 (100%)] Loss: 2.607419 (1.9578) Acc@1: 50.0000 (50.9428) Acc@5: 75.0000 (81.9118) Time: 0.058s, 277.37/s (0.052s, 305.35/s) LR: 1.875e-02
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2023-08-14 11:52:01,353 - train: [ INFO] - Train: 9 [1500/1521 (100%)] Loss: 1.995502 (2.0313) Acc@1: 43.7500 (49.5045) Acc@5: 68.7500 (80.4255) Time: 0.076s, 210.25/s (0.052s, 307.03/s) LR: 1.875e-02
|
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+
2023-08-14 11:52:02,433 - train: [ INFO] - Train: 9 [1520/1521 (100%)] Loss: 2.362884 (2.0333) Acc@1: 37.5000 (49.4247) Acc@5: 75.0000 (80.3748) Time: 0.048s, 332.61/s (0.052s, 306.89/s) LR: 1.875e-02
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2023-08-14 11:52:02,777 - train: [ INFO] - Test: [ 0/507] Time: 0.227 (0.227) Loss: 2.0146 (2.0146) Acc@1: 37.5000 (37.5000)Acc@5: 87.5000 (87.5000)
|
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2023-08-14 11:52:13,786 - train: [ INFO] - Test: [ 500/507] Time: 0.019 (0.022) Loss: 4.4421 (2.7019) Acc@1: 0.0000 (38.7725)Acc@5: 18.7500 (69.0369)
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2023-08-14 11:52:13,917 - train: [ INFO] - Test: [ 507/507] Time: 0.026 (0.022) Loss: 2.2114 (2.7066) Acc@1: 33.3333 (38.6075)Acc@5: 100.0000 (68.9464)
|
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+
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+
2023-08-14 11:52:14,014 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-9.pth.tar', 38.60751694487115)
|
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+
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+
2023-08-14 11:52:14,484 - train: [ INFO] - Train: 10 [ 0/1521 (100%)] Loss: 1.937686 (1.9377) Acc@1: 50.0000 (50.0000) Acc@5: 87.5000 (87.5000) Time: 0.469s, 34.15/s (0.469s, 34.15/s) LR: 1.875e-02
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2023-08-14 11:52:39,663 - train: [ INFO] - Train: 10 [ 500/1521 (100%)] Loss: 2.356527 (1.7971) Acc@1: 37.5000 (53.9172) Acc@5: 75.0000 (84.3937) Time: 0.060s, 266.62/s (0.051s, 312.61/s) LR: 1.875e-02
|
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+
2023-08-14 11:53:06,223 - train: [ INFO] - Train: 10 [1000/1521 (100%)] Loss: 2.453499 (1.8732) Acc@1: 37.5000 (52.3726) Acc@5: 62.5000 (83.1294) Time: 0.053s, 300.49/s (0.052s, 306.83/s) LR: 1.875e-02
|
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+
2023-08-14 11:53:33,252 - train: [ INFO] - Train: 10 [1500/1521 (100%)] Loss: 2.814014 (1.9338) Acc@1: 31.2500 (51.0701) Acc@5: 81.2500 (82.0037) Time: 0.074s, 216.58/s (0.053s, 303.15/s) LR: 1.875e-02
|
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+
2023-08-14 11:53:34,316 - train: [ INFO] - Train: 10 [1520/1521 (100%)] Loss: 2.485626 (1.9384) Acc@1: 37.5000 (50.9862) Acc@5: 68.7500 (81.8951) Time: 0.037s, 437.43/s (0.053s, 303.12/s) LR: 1.875e-02
|
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+
2023-08-14 11:53:34,645 - train: [ INFO] - Test: [ 0/507] Time: 0.230 (0.230) Loss: 2.0131 (2.0131) Acc@1: 50.0000 (50.0000)Acc@5: 87.5000 (87.5000)
|
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+
2023-08-14 11:53:45,801 - train: [ INFO] - Test: [ 500/507] Time: 0.017 (0.023) Loss: 3.9203 (2.5758) Acc@1: 6.2500 (41.7041)Acc@5: 37.5000 (70.9456)
|
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+
2023-08-14 11:53:45,951 - train: [ INFO] - Test: [ 507/507] Time: 0.016 (0.023) Loss: 0.3683 (2.5781) Acc@1: 100.0000 (41.5896)Acc@5: 100.0000 (70.8318)
|
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+
|
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+
2023-08-14 11:53:46,037 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
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+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-10.pth.tar', 41.58964879852126)
|
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+
|
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+
2023-08-14 11:53:46,472 - train: [ INFO] - Train: 11 [ 0/1521 (100%)] Loss: 1.254927 (1.2549) Acc@1: 68.7500 (68.7500) Acc@5: 93.7500 (93.7500) Time: 0.434s, 36.89/s (0.434s, 36.89/s) LR: 1.875e-02
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+
2023-08-14 11:54:13,094 - train: [ INFO] - Train: 11 [ 500/1521 (100%)] Loss: 1.741829 (1.6917) Acc@1: 43.7500 (56.1377) Acc@5: 87.5000 (85.8533) Time: 0.052s, 307.08/s (0.054s, 296.34/s) LR: 1.875e-02
|
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+
2023-08-14 11:54:38,774 - train: [ INFO] - Train: 11 [1000/1521 (100%)] Loss: 2.101770 (1.8006) Acc@1: 43.7500 (53.9086) Acc@5: 68.7500 (83.9473) Time: 0.050s, 321.18/s (0.053s, 303.76/s) LR: 1.875e-02
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2023-08-14 11:55:04,831 - train: [ INFO] - Train: 11 [1500/1521 (100%)] Loss: 2.202180 (1.8735) Acc@1: 43.7500 (52.4609) Acc@5: 68.7500 (82.7365) Time: 0.039s, 406.34/s (0.052s, 304.86/s) LR: 1.875e-02
|
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+
2023-08-14 11:55:05,916 - train: [ INFO] - Train: 11 [1520/1521 (100%)] Loss: 1.112081 (1.8723) Acc@1: 68.7500 (52.4778) Acc@5: 100.0000 (82.7457) Time: 0.062s, 257.93/s (0.053s, 304.73/s) LR: 1.875e-02
|
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+
2023-08-14 11:55:06,259 - train: [ INFO] - Test: [ 0/507] Time: 0.236 (0.236) Loss: 1.4080 (1.4080) Acc@1: 62.5000 (62.5000)Acc@5: 100.0000 (100.0000)
|
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+
2023-08-14 11:55:17,191 - train: [ INFO] - Test: [ 500/507] Time: 0.016 (0.022) Loss: 3.1167 (2.5911) Acc@1: 6.2500 (40.5813)Acc@5: 50.0000 (71.0579)
|
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2023-08-14 11:55:17,362 - train: [ INFO] - Test: [ 507/507] Time: 0.016 (0.022) Loss: 0.1781 (2.5905) Acc@1: 100.0000 (40.5422)Acc@5: 100.0000 (70.9797)
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2023-08-14 11:55:17,969 - train: [ INFO] - Train: 12 [ 0/1521 (100%)] Loss: 1.760891 (1.7609) Acc@1: 56.2500 (56.2500) Acc@5: 81.2500 (81.2500) Time: 0.478s, 33.49/s (0.478s, 33.49/s) LR: 1.875e-02
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2023-08-14 11:55:44,384 - train: [ INFO] - Train: 12 [ 500/1521 (100%)] Loss: 1.384920 (1.6558) Acc@1: 68.7500 (56.6742) Acc@5: 87.5000 (86.7390) Time: 0.071s, 226.80/s (0.054s, 298.14/s) LR: 1.875e-02
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2023-08-14 11:56:10,811 - train: [ INFO] - Train: 12 [1000/1521 (100%)] Loss: 1.458494 (1.7436) Acc@1: 68.7500 (55.0824) Acc@5: 93.7500 (85.0150) Time: 0.074s, 216.45/s (0.053s, 300.44/s) LR: 1.875e-02
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+
2023-08-14 11:56:36,914 - train: [ INFO] - Train: 12 [1500/1521 (100%)] Loss: 2.561432 (1.8220) Acc@1: 25.0000 (53.5851) Acc@5: 68.7500 (83.7317) Time: 0.057s, 282.53/s (0.053s, 302.44/s) LR: 1.875e-02
|
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+
2023-08-14 11:56:37,925 - train: [ INFO] - Train: 12 [1520/1521 (100%)] Loss: 2.459704 (1.8269) Acc@1: 50.0000 (53.4804) Acc@5: 68.7500 (83.6374) Time: 0.033s, 484.40/s (0.053s, 302.62/s) LR: 1.875e-02
|
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+
2023-08-14 11:56:38,270 - train: [ INFO] - Test: [ 0/507] Time: 0.223 (0.223) Loss: 2.7340 (2.7340) Acc@1: 25.0000 (25.0000)Acc@5: 75.0000 (75.0000)
|
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2023-08-14 11:56:49,362 - train: [ INFO] - Test: [ 500/507] Time: 0.018 (0.023) Loss: 3.9520 (2.5247) Acc@1: 6.2500 (41.7041)Acc@5: 31.2500 (72.1058)
|
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2023-08-14 11:56:49,519 - train: [ INFO] - Test: [ 507/507] Time: 0.016 (0.023) Loss: 1.5015 (2.5250) Acc@1: 66.6667 (41.6389)Acc@5: 100.0000 (72.1134)
|
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+
|
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+
2023-08-14 11:56:49,622 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
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+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-12.pth.tar', 41.63894023601464)
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+
2023-08-14 11:56:50,127 - train: [ INFO] - Train: 13 [ 0/1521 (100%)] Loss: 2.038987 (2.0390) Acc@1: 56.2500 (56.2500) Acc@5: 81.2500 (81.2500) Time: 0.504s, 31.77/s (0.504s, 31.77/s) LR: 1.875e-02
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+
2023-08-14 11:57:15,565 - train: [ INFO] - Train: 13 [ 500/1521 (100%)] Loss: 1.490846 (1.5575) Acc@1: 68.7500 (59.0943) Acc@5: 87.5000 (88.0988) Time: 0.033s, 487.14/s (0.052s, 309.07/s) LR: 1.875e-02
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+
2023-08-14 11:57:42,410 - train: [ INFO] - Train: 13 [1000/1521 (100%)] Loss: 2.311688 (1.6926) Acc@1: 31.2500 (56.0440) Acc@5: 68.7500 (85.9703) Time: 0.075s, 212.35/s (0.053s, 303.47/s) LR: 1.875e-02
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2023-08-14 11:58:08,183 - train: [ INFO] - Train: 13 [1500/1521 (100%)] Loss: 2.018530 (1.7837) Acc@1: 50.0000 (53.7766) Acc@5: 87.5000 (84.4853) Time: 0.044s, 360.18/s (0.052s, 305.77/s) LR: 1.875e-02
|
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2023-08-14 11:58:09,151 - train: [ INFO] - Train: 13 [1520/1521 (100%)] Loss: 1.871002 (1.7861) Acc@1: 56.2500 (53.7640) Acc@5: 75.0000 (84.4510) Time: 0.041s, 388.28/s (0.052s, 306.07/s) LR: 1.875e-02
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2023-08-14 11:58:09,582 - train: [ INFO] - Test: [ 0/507] Time: 0.258 (0.258) Loss: 2.3511 (2.3511) Acc@1: 37.5000 (37.5000)Acc@5: 87.5000 (87.5000)
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2023-08-14 11:58:20,538 - train: [ INFO] - Test: [ 500/507] Time: 0.020 (0.022) Loss: 3.0322 (2.5402) Acc@1: 18.7500 (41.2300)Acc@5: 62.5000 (72.0933)
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2023-08-14 11:58:20,677 - train: [ INFO] - Test: [ 507/507] Time: 0.018 (0.022) Loss: 0.1411 (2.5416) Acc@1: 100.0000 (41.2076)Acc@5: 100.0000 (72.0148)
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2023-08-14 11:58:21,249 - train: [ INFO] - Train: 14 [ 0/1521 (100%)] Loss: 2.061987 (2.0620) Acc@1: 50.0000 (50.0000) Acc@5: 68.7500 (68.7500) Time: 0.446s, 35.84/s (0.446s, 35.84/s) LR: 1.875e-02
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2023-08-14 11:58:47,268 - train: [ INFO] - Train: 14 [ 500/1521 (100%)] Loss: 1.140654 (1.5730) Acc@1: 56.2500 (59.3688) Acc@5: 100.0000 (87.8368) Time: 0.041s, 389.29/s (0.053s, 302.95/s) LR: 1.875e-02
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2023-08-14 11:59:13,302 - train: [ INFO] - Train: 14 [1000/1521 (100%)] Loss: 1.798601 (1.6751) Acc@1: 56.2500 (57.1116) Acc@5: 87.5000 (86.0639) Time: 0.066s, 243.53/s (0.052s, 305.14/s) LR: 1.875e-02
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2023-08-14 11:59:39,939 - train: [ INFO] - Train: 14 [1500/1521 (100%)] Loss: 2.209549 (1.7492) Acc@1: 43.7500 (55.2132) Acc@5: 81.2500 (84.8434) Time: 0.056s, 287.66/s (0.053s, 303.54/s) LR: 1.875e-02
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2023-08-14 11:59:40,990 - train: [ INFO] - Train: 14 [1520/1521 (100%)] Loss: 2.799808 (1.7523) Acc@1: 43.7500 (55.1159) Acc@5: 56.2500 (84.8085) Time: 0.052s, 304.79/s (0.053s, 303.56/s) LR: 1.875e-02
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2023-08-14 11:59:41,338 - train: [ INFO] - Test: [ 0/507] Time: 0.246 (0.246) Loss: 1.6687 (1.6687) Acc@1: 68.7500 (68.7500)Acc@5: 87.5000 (87.5000)
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2023-08-14 11:59:52,609 - train: [ INFO] - Test: [ 500/507] Time: 0.021 (0.023) Loss: 4.4842 (2.4696) Acc@1: 0.0000 (42.9017)Acc@5: 25.0000 (72.7046)
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2023-08-14 11:59:52,740 - train: [ INFO] - Test: [ 507/507] Time: 0.028 (0.023) Loss: 0.5599 (2.4746) Acc@1: 100.0000 (42.7480)Acc@5: 100.0000 (72.5693)
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2023-08-14 11:59:52,867 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-14.pth.tar', 42.74799753542822)
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2023-08-14 11:59:53,324 - train: [ INFO] - Train: 15 [ 0/1521 (100%)] Loss: 1.117009 (1.1170) Acc@1: 81.2500 (81.2500) Acc@5: 93.7500 (93.7500) Time: 0.456s, 35.11/s (0.456s, 35.11/s) LR: 1.875e-02
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2023-08-14 12:00:19,248 - train: [ INFO] - Train: 15 [ 500/1521 (100%)] Loss: 1.822500 (1.5543) Acc@1: 62.5000 (59.4686) Acc@5: 81.2500 (88.4855) Time: 0.056s, 284.93/s (0.053s, 303.93/s) LR: 1.875e-02
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2023-08-14 12:00:45,734 - train: [ INFO] - Train: 15 [1000/1521 (100%)] Loss: 1.840811 (1.6622) Acc@1: 50.0000 (56.8244) Acc@5: 75.0000 (86.5447) Time: 0.043s, 374.66/s (0.053s, 303.01/s) LR: 1.875e-02
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2023-08-14 12:01:12,129 - train: [ INFO] - Train: 15 [1500/1521 (100%)] Loss: 2.110165 (1.7299) Acc@1: 50.0000 (55.3506) Acc@5: 75.0000 (85.2765) Time: 0.075s, 213.37/s (0.053s, 303.06/s) LR: 1.875e-02
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2023-08-14 12:01:13,183 - train: [ INFO] - Train: 15 [1520/1521 (100%)] Loss: 1.493434 (1.7318) Acc@1: 56.2500 (55.3296) Acc@5: 93.7500 (85.2153) Time: 0.034s, 464.40/s (0.053s, 303.07/s) LR: 1.875e-02
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2023-08-14 12:01:13,512 - train: [ INFO] - Test: [ 0/507] Time: 0.245 (0.245) Loss: 2.5646 (2.5646) Acc@1: 37.5000 (37.5000)Acc@5: 68.7500 (68.7500)
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2023-08-14 12:01:24,433 - train: [ INFO] - Test: [ 500/507] Time: 0.023 (0.022) Loss: 4.0050 (2.4442) Acc@1: 0.0000 (43.1637)Acc@5: 25.0000 (72.8293)
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2023-08-14 12:01:24,573 - train: [ INFO] - Test: [ 507/507] Time: 0.029 (0.022) Loss: 0.2527 (2.4462) Acc@1: 100.0000 (43.0437)Acc@5: 100.0000 (72.7788)
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2023-08-14 12:01:24,676 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-15.pth.tar', 43.043746149106596)
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2023-08-14 12:01:25,129 - train: [ INFO] - Train: 16 [ 0/1521 (100%)] Loss: 0.977529 (0.9775) Acc@1: 81.2500 (81.2500) Acc@5: 93.7500 (93.7500) Time: 0.452s, 35.40/s (0.452s, 35.40/s) LR: 1.875e-02
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2023-08-14 12:01:50,661 - train: [ INFO] - Train: 16 [ 500/1521 (100%)] Loss: 1.637217 (1.4964) Acc@1: 62.5000 (61.1901) Acc@5: 81.2500 (88.8847) Time: 0.044s, 361.94/s (0.052s, 308.57/s) LR: 1.875e-02
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2023-08-14 12:02:16,050 - train: [ INFO] - Train: 16 [1000/1521 (100%)] Loss: 1.103460 (1.6068) Acc@1: 56.2500 (57.9920) Acc@5: 93.7500 (87.1503) Time: 0.056s, 284.33/s (0.051s, 311.82/s) LR: 1.875e-02
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2023-08-14 12:02:41,986 - train: [ INFO] - Train: 16 [1500/1521 (100%)] Loss: 1.425647 (1.6921) Acc@1: 62.5000 (56.0585) Acc@5: 87.5000 (85.8344) Time: 0.039s, 410.06/s (0.051s, 310.71/s) LR: 1.875e-02
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2023-08-14 12:02:42,978 - train: [ INFO] - Train: 16 [1520/1521 (100%)] Loss: 2.287619 (1.6936) Acc@1: 56.2500 (56.0651) Acc@5: 68.7500 (85.7988) Time: 0.039s, 409.91/s (0.051s, 310.86/s) LR: 1.875e-02
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2023-08-14 12:02:43,347 - train: [ INFO] - Test: [ 0/507] Time: 0.241 (0.241) Loss: 2.2758 (2.2758) Acc@1: 43.7500 (43.7500)Acc@5: 81.2500 (81.2500)
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2023-08-14 12:02:53,998 - train: [ INFO] - Test: [ 500/507] Time: 0.022 (0.022) Loss: 3.2139 (2.4423) Acc@1: 25.0000 (44.2365)Acc@5: 50.0000 (73.2909)
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2023-08-14 12:02:54,141 - train: [ INFO] - Test: [ 507/507] Time: 0.019 (0.022) Loss: 0.1322 (2.4406) Acc@1: 100.0000 (44.1405)Acc@5: 100.0000 (73.3457)
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2023-08-14 12:02:54,266 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-16.pth.tar', 44.14048059149723)
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2023-08-14 12:02:54,729 - train: [ INFO] - Train: 17 [ 0/1521 (100%)] Loss: 1.068232 (1.0682) Acc@1: 68.7500 (68.7500) Acc@5: 100.0000 (100.0000) Time: 0.460s, 34.75/s (0.460s, 34.75/s) LR: 1.875e-02
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2023-08-14 12:03:21,230 - train: [ INFO] - Train: 17 [ 500/1521 (100%)] Loss: 1.842285 (1.5213) Acc@1: 56.2500 (59.5434) Acc@5: 81.2500 (89.1841) Time: 0.044s, 365.26/s (0.054s, 297.41/s) LR: 1.875e-02
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2023-08-14 12:03:47,969 - train: [ INFO] - Train: 17 [1000/1521 (100%)] Loss: 1.889953 (1.6070) Acc@1: 50.0000 (57.7485) Acc@5: 81.2500 (87.4251) Time: 0.050s, 321.44/s (0.054s, 298.33/s) LR: 1.875e-02
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2023-08-14 12:04:14,532 - train: [ INFO] - Train: 17 [1500/1521 (100%)] Loss: 2.001745 (1.6834) Acc@1: 43.7500 (55.9835) Acc@5: 81.2500 (86.1467) Time: 0.050s, 317.09/s (0.053s, 299.29/s) LR: 1.875e-02
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2023-08-14 12:04:15,569 - train: [ INFO] - Train: 17 [1520/1521 (100%)] Loss: 2.497907 (1.6861) Acc@1: 37.5000 (55.9131) Acc@5: 75.0000 (86.0906) Time: 0.046s, 348.98/s (0.053s, 299.41/s) LR: 1.875e-02
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2023-08-14 12:04:15,945 - train: [ INFO] - Test: [ 0/507] Time: 0.264 (0.264) Loss: 2.3424 (2.3424) Acc@1: 25.0000 (25.0000)Acc@5: 87.5000 (87.5000)
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2023-08-14 12:04:27,243 - train: [ INFO] - Test: [ 500/507] Time: 0.031 (0.023) Loss: 3.4993 (2.3647) Acc@1: 6.2500 (45.2470)Acc@5: 50.0000 (74.7754)
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2023-08-14 12:04:27,389 - train: [ INFO] - Test: [ 507/507] Time: 0.015 (0.023) Loss: 0.5564 (2.3663) Acc@1: 100.0000 (45.2002)Acc@5: 100.0000 (74.7258)
|
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+
2023-08-14 12:04:27,513 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-17.pth.tar', 45.20024645717807)
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+
2023-08-14 12:04:27,957 - train: [ INFO] - Train: 18 [ 0/1521 (100%)] Loss: 1.301518 (1.3015) Acc@1: 56.2500 (56.2500) Acc@5: 100.0000 (100.0000) Time: 0.443s, 36.08/s (0.443s, 36.08/s) LR: 1.875e-02
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2023-08-14 12:04:53,802 - train: [ INFO] - Train: 18 [ 500/1521 (100%)] Loss: 1.294796 (1.4561) Acc@1: 62.5000 (61.5893) Acc@5: 93.7500 (89.9825) Time: 0.059s, 270.29/s (0.052s, 304.99/s) LR: 1.875e-02
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2023-08-14 12:05:19,970 - train: [ INFO] - Train: 18 [1000/1521 (100%)] Loss: 1.345485 (1.5727) Acc@1: 68.7500 (58.7225) Acc@5: 87.5000 (87.9995) Time: 0.046s, 350.46/s (0.052s, 305.38/s) LR: 1.875e-02
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2023-08-14 12:05:45,316 - train: [ INFO] - Train: 18 [1500/1521 (100%)] Loss: 2.028320 (1.6510) Acc@1: 50.0000 (56.8371) Acc@5: 68.7500 (86.7089) Time: 0.048s, 334.46/s (0.052s, 308.74/s) LR: 1.875e-02
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2023-08-14 12:05:46,333 - train: [ INFO] - Train: 18 [1520/1521 (100%)] Loss: 1.871944 (1.6544) Acc@1: 62.5000 (56.7965) Acc@5: 81.2500 (86.6494) Time: 0.059s, 271.01/s (0.052s, 308.82/s) LR: 1.875e-02
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2023-08-14 12:05:46,674 - train: [ INFO] - Test: [ 0/507] Time: 0.240 (0.240) Loss: 1.1865 (1.1865) Acc@1: 56.2500 (56.2500)Acc@5: 93.7500 (93.7500)
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2023-08-14 12:05:57,701 - train: [ INFO] - Test: [ 500/507] Time: 0.028 (0.022) Loss: 3.0707 (2.3757) Acc@1: 6.2500 (44.4736)Acc@5: 62.5000 (74.1766)
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2023-08-14 12:05:57,838 - train: [ INFO] - Test: [ 507/507] Time: 0.019 (0.022) Loss: 0.3418 (2.3757) Acc@1: 100.0000 (44.4239)Acc@5: 100.0000 (74.1713)
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2023-08-14 12:05:58,431 - train: [ INFO] - Train: 19 [ 0/1521 (100%)] Loss: 1.282263 (1.2823) Acc@1: 62.5000 (62.5000) Acc@5: 93.7500 (93.7500) Time: 0.466s, 34.34/s (0.466s, 34.34/s) LR: 1.875e-02
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2023-08-14 12:06:24,093 - train: [ INFO] - Train: 19 [ 500/1521 (100%)] Loss: 2.462451 (1.4765) Acc@1: 31.2500 (60.7535) Acc@5: 68.7500 (89.3338) Time: 0.037s, 435.67/s (0.052s, 306.87/s) LR: 1.875e-02
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2023-08-14 12:06:50,159 - train: [ INFO] - Train: 19 [1000/1521 (100%)] Loss: 1.377733 (1.5776) Acc@1: 62.5000 (58.3979) Acc@5: 100.0000 (87.8184) Time: 0.078s, 205.63/s (0.052s, 306.92/s) LR: 1.875e-02
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2023-08-14 12:07:16,132 - train: [ INFO] - Train: 19 [1500/1521 (100%)] Loss: 1.888937 (1.6511) Acc@1: 56.2500 (56.8996) Acc@5: 81.2500 (86.5590) Time: 0.041s, 386.12/s (0.052s, 307.31/s) LR: 1.875e-02
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2023-08-14 12:07:17,180 - train: [ INFO] - Train: 19 [1520/1521 (100%)] Loss: 1.769682 (1.6546) Acc@1: 50.0000 (56.8458) Acc@5: 87.5000 (86.4604) Time: 0.049s, 323.82/s (0.052s, 307.28/s) LR: 1.875e-02
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2023-08-14 12:07:17,507 - train: [ INFO] - Test: [ 0/507] Time: 0.231 (0.231) Loss: 2.2603 (2.2603) Acc@1: 43.7500 (43.7500)Acc@5: 81.2500 (81.2500)
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2023-08-14 12:07:28,647 - train: [ INFO] - Test: [ 500/507] Time: 0.032 (0.023) Loss: 3.9391 (2.3477) Acc@1: 12.5000 (44.8104)Acc@5: 37.5000 (74.8628)
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2023-08-14 12:07:28,783 - train: [ INFO] - Test: [ 507/507] Time: 0.023 (0.023) Loss: 1.6987 (2.3441) Acc@1: 66.6667 (44.8182)Acc@5: 100.0000 (74.9969)
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2023-08-14 12:07:29,448 - train: [ INFO] - Train: 20 [ 0/1521 (100%)] Loss: 1.065499 (1.0655) Acc@1: 62.5000 (62.5000) Acc@5: 93.7500 (93.7500) Time: 0.532s, 30.06/s (0.532s, 30.06/s) LR: 1.875e-02
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2023-08-14 12:07:55,654 - train: [ INFO] - Train: 20 [ 500/1521 (100%)] Loss: 1.369614 (1.4579) Acc@1: 62.5000 (61.0529) Acc@5: 93.7500 (89.6208) Time: 0.037s, 437.91/s (0.053s, 299.85/s) LR: 1.875e-02
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2023-08-14 12:08:22,584 - train: [ INFO] - Train: 20 [1000/1521 (100%)] Loss: 2.159347 (1.5433) Acc@1: 31.2500 (59.2158) Acc@5: 81.2500 (88.2368) Time: 0.063s, 255.81/s (0.054s, 298.49/s) LR: 1.875e-02
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2023-08-14 12:08:48,411 - train: [ INFO] - Train: 20 [1500/1521 (100%)] Loss: 2.412362 (1.6272) Acc@1: 50.0000 (57.3243) Acc@5: 62.5000 (86.9254) Time: 0.058s, 278.10/s (0.053s, 302.16/s) LR: 1.875e-02
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+
2023-08-14 12:08:49,324 - train: [ INFO] - Train: 20 [1520/1521 (100%)] Loss: 2.725108 (1.6312) Acc@1: 25.0000 (57.2156) Acc@5: 68.7500 (86.8384) Time: 0.035s, 453.89/s (0.053s, 302.71/s) LR: 1.875e-02
|
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+
2023-08-14 12:08:49,762 - train: [ INFO] - Test: [ 0/507] Time: 0.313 (0.313) Loss: 1.5841 (1.5841) Acc@1: 37.5000 (37.5000)Acc@5: 93.7500 (93.7500)
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2023-08-14 12:09:00,625 - train: [ INFO] - Test: [ 500/507] Time: 0.031 (0.022) Loss: 2.3499 (2.3313) Acc@1: 37.5000 (45.2345)Acc@5: 81.2500 (75.2495)
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2023-08-14 12:09:00,753 - train: [ INFO] - Test: [ 507/507] Time: 0.016 (0.022) Loss: 1.2085 (2.3276) Acc@1: 66.6667 (45.2619)Acc@5: 66.6667 (75.2927)
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2023-08-14 12:09:00,838 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-20.pth.tar', 45.26186075357471)
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2023-08-14 12:09:01,279 - train: [ INFO] - Train: 21 [ 0/1521 (100%)] Loss: 0.988681 (0.9887) Acc@1: 68.7500 (68.7500) Acc@5: 100.0000 (100.0000) Time: 0.439s, 36.42/s (0.439s, 36.42/s) LR: 1.875e-02
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2023-08-14 12:09:27,619 - train: [ INFO] - Train: 21 [ 500/1521 (100%)] Loss: 1.525110 (1.4421) Acc@1: 56.2500 (61.6018) Acc@5: 93.7500 (89.9077) Time: 0.070s, 227.25/s (0.053s, 299.39/s) LR: 1.875e-02
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+
2023-08-14 12:09:54,269 - train: [ INFO] - Train: 21 [1000/1521 (100%)] Loss: 2.906740 (1.5477) Acc@1: 37.5000 (59.3157) Acc@5: 68.7500 (88.0994) Time: 0.045s, 352.14/s (0.053s, 299.82/s) LR: 1.875e-02
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+
2023-08-14 12:10:20,308 - train: [ INFO] - Train: 21 [1500/1521 (100%)] Loss: 2.039098 (1.6304) Acc@1: 37.5000 (57.3243) Acc@5: 81.2500 (86.9837) Time: 0.075s, 213.66/s (0.053s, 302.27/s) LR: 1.875e-02
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+
2023-08-14 12:10:21,340 - train: [ INFO] - Train: 21 [1520/1521 (100%)] Loss: 1.200162 (1.6332) Acc@1: 75.0000 (57.2937) Acc@5: 87.5000 (86.9165) Time: 0.077s, 208.51/s (0.053s, 302.36/s) LR: 1.875e-02
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2023-08-14 12:10:21,696 - train: [ INFO] - Test: [ 0/507] Time: 0.245 (0.245) Loss: 2.5806 (2.5806) Acc@1: 18.7500 (18.7500)Acc@5: 81.2500 (81.2500)
|
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2023-08-14 12:10:33,105 - train: [ INFO] - Test: [ 500/507] Time: 0.027 (0.023) Loss: 3.1667 (2.4439) Acc@1: 12.5000 (43.5629)Acc@5: 43.7500 (72.9915)
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2023-08-14 12:10:33,241 - train: [ INFO] - Test: [ 507/507] Time: 0.018 (0.023) Loss: 0.4568 (2.4472) Acc@1: 100.0000 (43.4504)Acc@5: 100.0000 (72.9144)
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2023-08-14 12:10:33,775 - train: [ INFO] - Train: 22 [ 0/1521 (100%)] Loss: 1.365138 (1.3651) Acc@1: 68.7500 (68.7500) Acc@5: 87.5000 (87.5000) Time: 0.443s, 36.11/s (0.443s, 36.11/s) LR: 1.875e-02
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2023-08-14 12:10:59,481 - train: [ INFO] - Train: 22 [ 500/1521 (100%)] Loss: 1.677920 (1.4119) Acc@1: 56.2500 (62.8992) Acc@5: 93.7500 (90.2196) Time: 0.042s, 383.67/s (0.052s, 306.60/s) LR: 1.875e-02
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2023-08-14 12:11:25,209 - train: [ INFO] - Train: 22 [1000/1521 (100%)] Loss: 1.433880 (1.5362) Acc@1: 56.2500 (59.5467) Acc@5: 100.0000 (88.5989) Time: 0.044s, 366.62/s (0.052s, 308.79/s) LR: 1.875e-02
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2023-08-14 12:11:50,477 - train: [ INFO] - Train: 22 [1500/1521 (100%)] Loss: 1.655449 (1.6104) Acc@1: 68.7500 (57.8323) Acc@5: 81.2500 (87.3043) Time: 0.066s, 243.01/s (0.051s, 311.37/s) LR: 1.875e-02
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2023-08-14 12:11:51,523 - train: [ INFO] - Train: 22 [1520/1521 (100%)] Loss: 1.302347 (1.6135) Acc@1: 75.0000 (57.7211) Acc@5: 93.7500 (87.2247) Time: 0.055s, 289.23/s (0.051s, 311.30/s) LR: 1.875e-02
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2023-08-14 12:11:51,876 - train: [ INFO] - Test: [ 0/507] Time: 0.226 (0.226) Loss: 2.8031 (2.8031) Acc@1: 25.0000 (25.0000)Acc@5: 75.0000 (75.0000)
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2023-08-14 12:12:03,236 - train: [ INFO] - Test: [ 500/507] Time: 0.017 (0.023) Loss: 2.4736 (2.4430) Acc@1: 31.2500 (43.9247)Acc@5: 75.0000 (73.1287)
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2023-08-14 12:12:03,378 - train: [ INFO] - Test: [ 507/507] Time: 0.019 (0.023) Loss: 0.1757 (2.4427) Acc@1: 100.0000 (43.8694)Acc@5: 100.0000 (73.0869)
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2023-08-14 12:12:03,917 - train: [ INFO] - Train: 23 [ 0/1521 (100%)] Loss: 1.202419 (1.2024) Acc@1: 62.5000 (62.5000) Acc@5: 93.7500 (93.7500) Time: 0.453s, 35.34/s (0.453s, 35.34/s) LR: 1.875e-02
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2023-08-14 12:12:30,546 - train: [ INFO] - Train: 23 [ 500/1521 (100%)] Loss: 1.192782 (1.4041) Acc@1: 68.7500 (62.9491) Acc@5: 93.7500 (90.5938) Time: 0.052s, 307.12/s (0.054s, 296.06/s) LR: 1.875e-02
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2023-08-14 12:12:57,932 - train: [ INFO] - Train: 23 [1000/1521 (100%)] Loss: 1.553079 (1.5158) Acc@1: 50.0000 (60.1773) Acc@5: 93.7500 (88.8112) Time: 0.071s, 223.93/s (0.054s, 294.11/s) LR: 1.875e-02
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2023-08-14 12:13:23,491 - train: [ INFO] - Train: 23 [1500/1521 (100%)] Loss: 2.133540 (1.5982) Acc@1: 43.7500 (58.1404) Acc@5: 68.7500 (87.5458) Time: 0.051s, 311.81/s (0.053s, 300.16/s) LR: 1.875e-02
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2023-08-14 12:13:24,553 - train: [ INFO] - Train: 23 [1520/1521 (100%)] Loss: 1.725955 (1.5993) Acc@1: 50.0000 (58.0539) Acc@5: 93.7500 (87.5411) Time: 0.049s, 325.71/s (0.053s, 300.18/s) LR: 1.875e-02
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2023-08-14 12:13:25,019 - train: [ INFO] - Test: [ 0/507] Time: 0.331 (0.331) Loss: 1.7335 (1.7335) Acc@1: 43.7500 (43.7500)Acc@5: 93.7500 (93.7500)
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2023-08-14 12:13:36,077 - train: [ INFO] - Test: [ 500/507] Time: 0.020 (0.023) Loss: 3.6229 (2.4218) Acc@1: 37.5000 (44.1492)Acc@5: 56.2500 (73.1911)
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2023-08-14 12:13:36,211 - train: [ INFO] - Test: [ 507/507] Time: 0.018 (0.023) Loss: 0.4109 (2.4268) Acc@1: 100.0000 (43.9803)Acc@5: 100.0000 (73.0376)
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2023-08-14 12:13:36,791 - train: [ INFO] - Train: 24 [ 0/1521 (100%)] Loss: 1.265242 (1.2652) Acc@1: 68.7500 (68.7500) Acc@5: 100.0000 (100.0000) Time: 0.481s, 33.27/s (0.481s, 33.27/s) LR: 1.875e-02
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2023-08-14 12:14:03,313 - train: [ INFO] - Train: 24 [ 500/1521 (100%)] Loss: 1.089177 (1.4051) Acc@1: 75.0000 (62.9990) Acc@5: 93.7500 (90.3194) Time: 0.052s, 308.93/s (0.054s, 296.93/s) LR: 1.875e-02
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2023-08-14 12:14:29,310 - train: [ INFO] - Train: 24 [1000/1521 (100%)] Loss: 2.025333 (1.5070) Acc@1: 37.5000 (60.6518) Acc@5: 87.5000 (88.7737) Time: 0.042s, 383.44/s (0.053s, 302.26/s) LR: 1.875e-02
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2023-08-14 12:14:55,923 - train: [ INFO] - Train: 24 [1500/1521 (100%)] Loss: 1.766774 (1.5885) Acc@1: 50.0000 (58.4485) Acc@5: 87.5000 (87.4625) Time: 0.066s, 241.22/s (0.053s, 301.73/s) LR: 1.875e-02
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2023-08-14 12:14:57,046 - train: [ INFO] - Train: 24 [1520/1521 (100%)] Loss: 1.984609 (1.5936) Acc@1: 37.5000 (58.3087) Acc@5: 81.2500 (87.4014) Time: 0.063s, 253.83/s (0.053s, 301.50/s) LR: 1.875e-02
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2023-08-14 12:14:57,416 - train: [ INFO] - Test: [ 0/507] Time: 0.260 (0.260) Loss: 3.3853 (3.3853) Acc@1: 31.2500 (31.2500)Acc@5: 50.0000 (50.0000)
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2023-08-14 12:15:09,231 - train: [ INFO] - Test: [ 500/507] Time: 0.019 (0.024) Loss: 3.3945 (2.3489) Acc@1: 25.0000 (45.1722)Acc@5: 50.0000 (74.8004)
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2023-08-14 12:15:09,391 - train: [ INFO] - Test: [ 507/507] Time: 0.026 (0.024) Loss: 0.5968 (2.3460) Acc@1: 100.0000 (45.1756)Acc@5: 100.0000 (74.8367)
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2023-08-14 12:15:09,996 - train: [ INFO] - Train: 25 [ 0/1521 (100%)] Loss: 0.892705 (0.8927) Acc@1: 81.2500 (81.2500) Acc@5: 100.0000 (100.0000) Time: 0.484s, 33.09/s (0.484s, 33.09/s) LR: 1.875e-02
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2023-08-14 12:15:36,904 - train: [ INFO] - Train: 25 [ 500/1521 (100%)] Loss: 1.522364 (1.4086) Acc@1: 62.5000 (62.6871) Acc@5: 87.5000 (90.4815) Time: 0.053s, 302.01/s (0.055s, 292.72/s) LR: 1.875e-02
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2023-08-14 12:16:03,430 - train: [ INFO] - Train: 25 [1000/1521 (100%)] Loss: 1.676708 (1.4926) Acc@1: 56.2500 (60.3521) Acc@5: 87.5000 (89.1359) Time: 0.043s, 369.44/s (0.054s, 297.11/s) LR: 1.875e-02
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2023-08-14 12:16:29,142 - train: [ INFO] - Train: 25 [1500/1521 (100%)] Loss: 2.002273 (1.5783) Acc@1: 43.7500 (58.5152) Acc@5: 87.5000 (87.7207) Time: 0.060s, 268.85/s (0.053s, 301.66/s) LR: 1.875e-02
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2023-08-14 12:16:30,150 - train: [ INFO] - Train: 25 [1520/1521 (100%)] Loss: 1.716693 (1.5812) Acc@1: 50.0000 (58.4525) Acc@5: 81.2500 (87.6726) Time: 0.055s, 292.33/s (0.053s, 301.86/s) LR: 1.875e-02
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2023-08-14 12:16:30,510 - train: [ INFO] - Test: [ 0/507] Time: 0.253 (0.253) Loss: 2.0511 (2.0511) Acc@1: 25.0000 (25.0000)Acc@5: 100.0000 (100.0000)
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2023-08-14 12:16:41,555 - train: [ INFO] - Test: [ 500/507] Time: 0.021 (0.023) Loss: 2.4667 (2.3306) Acc@1: 37.5000 (45.2470)Acc@5: 75.0000 (75.1747)
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2023-08-14 12:16:41,746 - train: [ INFO] - Test: [ 507/507] Time: 0.021 (0.023) Loss: 0.2886 (2.3340) Acc@1: 100.0000 (45.0893)Acc@5: 100.0000 (75.0585)
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2023-08-14 12:16:42,371 - train: [ INFO] - Train: 26 [ 0/1521 (100%)] Loss: 1.465641 (1.4656) Acc@1: 56.2500 (56.2500) Acc@5: 87.5000 (87.5000) Time: 0.446s, 35.89/s (0.446s, 35.89/s) LR: 1.875e-02
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2023-08-14 12:17:08,623 - train: [ INFO] - Train: 26 [ 500/1521 (100%)] Loss: 1.453181 (1.4327) Acc@1: 75.0000 (62.3503) Acc@5: 81.2500 (89.9077) Time: 0.041s, 387.53/s (0.053s, 300.31/s) LR: 1.875e-02
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2023-08-14 12:17:34,790 - train: [ INFO] - Train: 26 [1000/1521 (100%)] Loss: 1.738152 (1.5040) Acc@1: 56.2500 (60.5519) Acc@5: 87.5000 (88.7737) Time: 0.045s, 357.63/s (0.053s, 303.02/s) LR: 1.875e-02
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2023-08-14 12:18:01,205 - train: [ INFO] - Train: 26 [1500/1521 (100%)] Loss: 2.210666 (1.5663) Acc@1: 50.0000 (58.9024) Acc@5: 75.0000 (87.9955) Time: 0.038s, 425.87/s (0.053s, 302.98/s) LR: 1.875e-02
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2023-08-14 12:18:02,257 - train: [ INFO] - Train: 26 [1520/1521 (100%)] Loss: 1.596307 (1.5686) Acc@1: 56.2500 (58.8716) Acc@5: 93.7500 (87.9808) Time: 0.066s, 243.02/s (0.053s, 303.00/s) LR: 1.875e-02
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2023-08-14 12:18:02,631 - train: [ INFO] - Test: [ 0/507] Time: 0.244 (0.244) Loss: 2.3952 (2.3952) Acc@1: 50.0000 (50.0000)Acc@5: 87.5000 (87.5000)
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2023-08-14 12:18:13,950 - train: [ INFO] - Test: [ 500/507] Time: 0.037 (0.023) Loss: 3.9080 (2.3382) Acc@1: 12.5000 (45.0349)Acc@5: 25.0000 (75.0499)
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2023-08-14 12:18:14,102 - train: [ INFO] - Test: [ 507/507] Time: 0.033 (0.023) Loss: 0.0658 (2.3382) Acc@1: 100.0000 (44.9415)Acc@5: 100.0000 (75.0092)
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2023-08-14 12:18:14,741 - train: [ INFO] - Train: 27 [ 0/1521 (100%)] Loss: 1.615785 (1.6158) Acc@1: 56.2500 (56.2500) Acc@5: 93.7500 (93.7500) Time: 0.456s, 35.12/s (0.456s, 35.12/s) LR: 1.875e-02
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+
2023-08-14 12:18:40,788 - train: [ INFO] - Train: 27 [ 500/1521 (100%)] Loss: 1.856778 (1.3779) Acc@1: 50.0000 (63.5604) Acc@5: 75.0000 (90.9681) Time: 0.050s, 320.21/s (0.053s, 302.52/s) LR: 1.875e-02
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2023-08-14 12:19:07,275 - train: [ INFO] - Train: 27 [1000/1521 (100%)] Loss: 1.720932 (1.4992) Acc@1: 43.7500 (60.2460) Acc@5: 87.5000 (89.1171) Time: 0.049s, 323.66/s (0.053s, 302.31/s) LR: 1.875e-02
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2023-08-14 12:19:32,334 - train: [ INFO] - Train: 27 [1500/1521 (100%)] Loss: 1.359236 (1.5658) Acc@1: 62.5000 (58.7234) Acc@5: 93.7500 (88.0621) Time: 0.072s, 223.33/s (0.052s, 307.76/s) LR: 1.875e-02
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2023-08-14 12:19:33,414 - train: [ INFO] - Train: 27 [1520/1521 (100%)] Loss: 2.974950 (1.5693) Acc@1: 31.2500 (58.6662) Acc@5: 62.5000 (88.0013) Time: 0.070s, 229.61/s (0.052s, 307.61/s) LR: 1.875e-02
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2023-08-14 12:19:33,743 - train: [ INFO] - Test: [ 0/507] Time: 0.232 (0.232) Loss: 1.9983 (1.9983) Acc@1: 37.5000 (37.5000)Acc@5: 81.2500 (81.2500)
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2023-08-14 12:19:44,851 - train: [ INFO] - Test: [ 500/507] Time: 0.014 (0.023) Loss: 2.7508 (2.3137) Acc@1: 43.7500 (45.6587)Acc@5: 68.7500 (75.7610)
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2023-08-14 12:19:45,000 - train: [ INFO] - Test: [ 507/507] Time: 0.019 (0.023) Loss: 0.3346 (2.3165) Acc@1: 100.0000 (45.5699)Acc@5: 100.0000 (75.7486)
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|
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2023-08-14 12:19:45,096 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-27.pth.tar', 45.56993222427603)
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2023-08-14 12:19:45,542 - train: [ INFO] - Train: 28 [ 0/1521 (100%)] Loss: 1.081041 (1.0810) Acc@1: 75.0000 (75.0000) Acc@5: 100.0000 (100.0000) Time: 0.445s, 35.98/s (0.445s, 35.98/s) LR: 1.875e-02
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2023-08-14 12:20:11,162 - train: [ INFO] - Train: 28 [ 500/1521 (100%)] Loss: 1.444797 (1.3796) Acc@1: 56.2500 (63.0115) Acc@5: 87.5000 (90.9057) Time: 0.050s, 316.99/s (0.052s, 307.59/s) LR: 1.875e-02
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2023-08-14 12:20:37,741 - train: [ INFO] - Train: 28 [1000/1521 (100%)] Loss: 1.295257 (1.4739) Acc@1: 68.7500 (60.8641) Acc@5: 93.7500 (89.3044) Time: 0.044s, 364.33/s (0.053s, 304.29/s) LR: 1.875e-02
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2023-08-14 12:21:03,545 - train: [ INFO] - Train: 28 [1500/1521 (100%)] Loss: 1.805021 (1.5634) Acc@1: 50.0000 (58.6109) Acc@5: 81.2500 (87.8956) Time: 0.047s, 337.07/s (0.052s, 306.20/s) LR: 1.875e-02
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2023-08-14 12:21:04,622 - train: [ INFO] - Train: 28 [1520/1521 (100%)] Loss: 1.948010 (1.5684) Acc@1: 50.0000 (58.4977) Acc@5: 75.0000 (87.8246) Time: 0.046s, 348.37/s (0.052s, 306.08/s) LR: 1.875e-02
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2023-08-14 12:21:05,062 - train: [ INFO] - Test: [ 0/507] Time: 0.351 (0.351) Loss: 2.0012 (2.0012) Acc@1: 56.2500 (56.2500)Acc@5: 81.2500 (81.2500)
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2023-08-14 12:21:16,804 - train: [ INFO] - Test: [ 500/507] Time: 0.022 (0.024) Loss: 3.9077 (2.4083) Acc@1: 0.0000 (43.8997)Acc@5: 50.0000 (73.8772)
|
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2023-08-14 12:21:16,975 - train: [ INFO] - Test: [ 507/507] Time: 0.019 (0.024) Loss: 2.0490 (2.4130) Acc@1: 66.6667 (43.7338)Acc@5: 66.6667 (73.8139)
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2023-08-14 12:21:17,683 - train: [ INFO] - Train: 29 [ 0/1521 (100%)] Loss: 1.363245 (1.3632) Acc@1: 62.5000 (62.5000) Acc@5: 87.5000 (87.5000) Time: 0.611s, 26.18/s (0.611s, 26.18/s) LR: 1.875e-02
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2023-08-14 12:21:43,811 - train: [ INFO] - Train: 29 [ 500/1521 (100%)] Loss: 1.141377 (1.3757) Acc@1: 62.5000 (63.1487) Acc@5: 93.7500 (90.5813) Time: 0.042s, 382.85/s (0.053s, 299.85/s) LR: 1.875e-02
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2023-08-14 12:22:09,992 - train: [ INFO] - Train: 29 [1000/1521 (100%)] Loss: 1.725423 (1.4695) Acc@1: 56.2500 (61.2200) Acc@5: 75.0000 (89.1671) Time: 0.042s, 377.47/s (0.053s, 302.71/s) LR: 1.875e-02
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+
2023-08-14 12:22:35,760 - train: [ INFO] - Train: 29 [1500/1521 (100%)] Loss: 1.717333 (1.5534) Acc@1: 56.2500 (59.2022) Acc@5: 93.7500 (87.9122) Time: 0.047s, 337.18/s (0.052s, 305.27/s) LR: 1.875e-02
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2023-08-14 12:22:36,727 - train: [ INFO] - Train: 29 [1520/1521 (100%)] Loss: 1.601911 (1.5549) Acc@1: 62.5000 (59.1757) Acc@5: 93.7500 (87.8821) Time: 0.043s, 369.97/s (0.052s, 305.58/s) LR: 1.875e-02
|
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+
2023-08-14 12:22:37,124 - train: [ INFO] - Test: [ 0/507] Time: 0.254 (0.254) Loss: 3.0332 (3.0332) Acc@1: 31.2500 (31.2500)Acc@5: 62.5000 (62.5000)
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2023-08-14 12:22:48,448 - train: [ INFO] - Test: [ 500/507] Time: 0.026 (0.023) Loss: 2.8149 (2.2627) Acc@1: 12.5000 (46.9935)Acc@5: 75.0000 (76.6218)
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2023-08-14 12:22:48,589 - train: [ INFO] - Test: [ 507/507] Time: 0.034 (0.023) Loss: 1.2076 (2.2642) Acc@1: 66.6667 (46.9378)Acc@5: 100.0000 (76.6359)
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2023-08-14 12:22:48,719 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
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+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-29.pth.tar', 46.93776956441883)
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2023-08-14 12:22:49,182 - train: [ INFO] - Train: 30 [ 0/1521 (100%)] Loss: 1.474060 (1.4741) Acc@1: 56.2500 (56.2500) Acc@5: 87.5000 (87.5000) Time: 0.462s, 34.61/s (0.462s, 34.61/s) LR: 1.875e-02
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2023-08-14 12:23:15,686 - train: [ INFO] - Train: 30 [ 500/1521 (100%)] Loss: 0.909601 (1.3618) Acc@1: 87.5000 (63.5604) Acc@5: 93.7500 (90.9182) Time: 0.055s, 292.48/s (0.054s, 297.33/s) LR: 1.875e-02
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2023-08-14 12:23:41,911 - train: [ INFO] - Train: 30 [1000/1521 (100%)] Loss: 2.182602 (1.4590) Acc@1: 50.0000 (61.4198) Acc@5: 75.0000 (89.3544) Time: 0.053s, 300.26/s (0.053s, 301.17/s) LR: 1.875e-02
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2023-08-14 12:24:07,751 - train: [ INFO] - Train: 30 [1500/1521 (100%)] Loss: 1.841388 (1.5327) Acc@1: 43.7500 (59.6019) Acc@5: 87.5000 (88.3369) Time: 0.048s, 334.14/s (0.053s, 303.95/s) LR: 1.875e-02
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+
2023-08-14 12:24:08,857 - train: [ INFO] - Train: 30 [1520/1521 (100%)] Loss: 1.677195 (1.5349) Acc@1: 43.7500 (59.5455) Acc@5: 87.5000 (88.2807) Time: 0.056s, 284.93/s (0.053s, 303.75/s) LR: 1.875e-02
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+
2023-08-14 12:24:09,317 - train: [ INFO] - Test: [ 0/507] Time: 0.342 (0.342) Loss: 3.0018 (3.0018) Acc@1: 12.5000 (12.5000)Acc@5: 75.0000 (75.0000)
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2023-08-14 12:24:20,468 - train: [ INFO] - Test: [ 500/507] Time: 0.016 (0.023) Loss: 4.5268 (2.3388) Acc@1: 0.0000 (45.6337)Acc@5: 18.7500 (74.7754)
|
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+
|
| 402 |
+
2023-08-14 12:24:20,634 - train: [ INFO] - Test: [ 507/507] Time: 0.025 (0.023) Loss: 0.9960 (2.3382) Acc@1: 66.6667 (45.5576)Acc@5: 100.0000 (74.8244)
|
| 403 |
+
|
| 404 |
+
2023-08-14 12:24:21,461 - train: [ INFO] - Train: 31 [ 0/1521 (100%)] Loss: 1.378582 (1.3786) Acc@1: 56.2500 (56.2500) Acc@5: 100.0000 (100.0000) Time: 0.670s, 23.89/s (0.670s, 23.89/s) LR: 1.875e-02
|
| 405 |
+
2023-08-14 12:24:47,417 - train: [ INFO] - Train: 31 [ 500/1521 (100%)] Loss: 1.158314 (1.3774) Acc@1: 62.5000 (63.1487) Acc@5: 100.0000 (90.5689) Time: 0.054s, 294.05/s (0.053s, 301.14/s) LR: 1.875e-02
|
| 406 |
+
2023-08-14 12:25:13,634 - train: [ INFO] - Train: 31 [1000/1521 (100%)] Loss: 2.252589 (1.4685) Acc@1: 37.5000 (61.1264) Acc@5: 68.7500 (89.3419) Time: 0.050s, 319.35/s (0.053s, 303.16/s) LR: 1.875e-02
|
| 407 |
+
2023-08-14 12:25:39,509 - train: [ INFO] - Train: 31 [1500/1521 (100%)] Loss: 1.930699 (1.5349) Acc@1: 43.7500 (59.6228) Acc@5: 87.5000 (88.3494) Time: 0.060s, 265.85/s (0.052s, 305.16/s) LR: 1.875e-02
|
| 408 |
+
2023-08-14 12:25:40,695 - train: [ INFO] - Train: 31 [1520/1521 (100%)] Loss: 2.076920 (1.5374) Acc@1: 56.2500 (59.5250) Acc@5: 75.0000 (88.2972) Time: 0.060s, 266.14/s (0.053s, 304.63/s) LR: 1.875e-02
|
| 409 |
+
2023-08-14 12:25:41,096 - train: [ INFO] - Test: [ 0/507] Time: 0.253 (0.253) Loss: 1.8955 (1.8955) Acc@1: 43.7500 (43.7500)Acc@5: 81.2500 (81.2500)
|
| 410 |
+
|
| 411 |
+
2023-08-14 12:25:52,413 - train: [ INFO] - Test: [ 500/507] Time: 0.028 (0.023) Loss: 4.7536 (2.3642) Acc@1: 0.0000 (44.9351)Acc@5: 37.5000 (74.8877)
|
| 412 |
+
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+
2023-08-14 12:25:52,577 - train: [ INFO] - Test: [ 507/507] Time: 0.014 (0.023) Loss: 2.0625 (2.3660) Acc@1: 33.3333 (44.9168)Acc@5: 66.6667 (74.8367)
|
| 414 |
+
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2023-08-14 12:25:53,318 - train: [ INFO] - Train: 32 [ 0/1521 (100%)] Loss: 1.173356 (1.1734) Acc@1: 68.7500 (68.7500) Acc@5: 100.0000 (100.0000) Time: 0.582s, 27.47/s (0.582s, 27.47/s) LR: 1.875e-02
|
| 416 |
+
2023-08-14 12:26:20,093 - train: [ INFO] - Train: 32 [ 500/1521 (100%)] Loss: 2.084410 (1.3496) Acc@1: 37.5000 (63.9845) Acc@5: 81.2500 (91.0055) Time: 0.036s, 439.77/s (0.055s, 293.08/s) LR: 1.875e-02
|
| 417 |
+
2023-08-14 12:26:46,877 - train: [ INFO] - Train: 32 [1000/1521 (100%)] Loss: 1.340560 (1.4544) Acc@1: 68.7500 (61.5509) Acc@5: 87.5000 (89.3669) Time: 0.065s, 247.96/s (0.054s, 295.89/s) LR: 1.875e-02
|
| 418 |
+
2023-08-14 12:27:14,350 - train: [ INFO] - Train: 32 [1500/1521 (100%)] Loss: 1.494066 (1.5294) Acc@1: 62.5000 (59.5603) Acc@5: 87.5000 (88.0746) Time: 0.046s, 350.85/s (0.054s, 294.35/s) LR: 1.875e-02
|
| 419 |
+
2023-08-14 12:27:15,436 - train: [ INFO] - Train: 32 [1520/1521 (100%)] Loss: 1.664829 (1.5326) Acc@1: 62.5000 (59.4633) Acc@5: 81.2500 (88.0588) Time: 0.071s, 225.04/s (0.054s, 294.36/s) LR: 1.875e-02
|
| 420 |
+
2023-08-14 12:27:15,815 - train: [ INFO] - Test: [ 0/507] Time: 0.250 (0.250) Loss: 2.2376 (2.2376) Acc@1: 12.5000 (12.5000)Acc@5: 87.5000 (87.5000)
|
| 421 |
+
|
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+
2023-08-14 12:27:26,934 - train: [ INFO] - Test: [ 500/507] Time: 0.029 (0.023) Loss: 4.3107 (2.3425) Acc@1: 6.2500 (44.8229)Acc@5: 37.5000 (74.8503)
|
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+
|
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+
2023-08-14 12:27:27,053 - train: [ INFO] - Test: [ 507/507] Time: 0.019 (0.023) Loss: 2.6025 (2.3385) Acc@1: 0.0000 (44.7936)Acc@5: 66.6667 (74.9107)
|
| 425 |
+
|
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+
2023-08-14 12:27:27,650 - train: [ INFO] - Train: 33 [ 0/1521 (100%)] Loss: 1.554518 (1.5545) Acc@1: 62.5000 (62.5000) Acc@5: 87.5000 (87.5000) Time: 0.470s, 34.06/s (0.470s, 34.06/s) LR: 1.875e-02
|
| 427 |
+
2023-08-14 12:27:53,771 - train: [ INFO] - Train: 33 [ 500/1521 (100%)] Loss: 1.425539 (1.3285) Acc@1: 75.0000 (64.4212) Acc@5: 93.7500 (91.7166) Time: 0.037s, 431.45/s (0.053s, 301.52/s) LR: 1.875e-02
|
| 428 |
+
2023-08-14 12:28:19,891 - train: [ INFO] - Train: 33 [1000/1521 (100%)] Loss: 1.640623 (1.4399) Acc@1: 56.2500 (61.5947) Acc@5: 87.5000 (89.6479) Time: 0.052s, 309.47/s (0.053s, 303.91/s) LR: 1.875e-02
|
| 429 |
+
2023-08-14 12:28:46,238 - train: [ INFO] - Train: 33 [1500/1521 (100%)] Loss: 1.633294 (1.5203) Acc@1: 62.5000 (59.8934) Acc@5: 93.7500 (88.4702) Time: 0.045s, 356.11/s (0.053s, 303.84/s) LR: 1.875e-02
|
| 430 |
+
2023-08-14 12:28:47,302 - train: [ INFO] - Train: 33 [1520/1521 (100%)] Loss: 1.831057 (1.5209) Acc@1: 50.0000 (59.8619) Acc@5: 75.0000 (88.4451) Time: 0.049s, 325.11/s (0.053s, 303.80/s) LR: 1.875e-02
|
| 431 |
+
2023-08-14 12:28:47,645 - train: [ INFO] - Test: [ 0/507] Time: 0.249 (0.249) Loss: 2.6190 (2.6190) Acc@1: 25.0000 (25.0000)Acc@5: 75.0000 (75.0000)
|
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+
|
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+
2023-08-14 12:28:58,669 - train: [ INFO] - Test: [ 500/507] Time: 0.015 (0.022) Loss: 3.7322 (2.2815) Acc@1: 0.0000 (46.3822)Acc@5: 37.5000 (75.3618)
|
| 434 |
+
|
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+
2023-08-14 12:28:58,817 - train: [ INFO] - Test: [ 507/507] Time: 0.015 (0.022) Loss: 2.1465 (2.2811) Acc@1: 33.3333 (46.3093)Acc@5: 66.6667 (75.3296)
|
| 436 |
+
|
| 437 |
+
2023-08-14 12:28:59,439 - train: [ INFO] - Train: 34 [ 0/1521 (100%)] Loss: 0.905683 (0.9057) Acc@1: 75.0000 (75.0000) Acc@5: 93.7500 (93.7500) Time: 0.496s, 32.25/s (0.496s, 32.25/s) LR: 1.875e-02
|
| 438 |
+
2023-08-14 12:29:25,763 - train: [ INFO] - Train: 34 [ 500/1521 (100%)] Loss: 1.557649 (1.3381) Acc@1: 56.2500 (63.8348) Acc@5: 81.2500 (91.5045) Time: 0.064s, 248.98/s (0.054s, 298.94/s) LR: 1.875e-02
|
| 439 |
+
2023-08-14 12:29:52,332 - train: [ INFO] - Train: 34 [1000/1521 (100%)] Loss: 1.545284 (1.4317) Acc@1: 56.2500 (62.1628) Acc@5: 93.7500 (89.8914) Time: 0.053s, 304.01/s (0.053s, 300.05/s) LR: 1.875e-02
|
| 440 |
+
2023-08-14 12:30:17,165 - train: [ INFO] - Train: 34 [1500/1521 (100%)] Loss: 3.028207 (1.5161) Acc@1: 25.0000 (60.1474) Acc@5: 56.2500 (88.4452) Time: 0.043s, 371.73/s (0.052s, 307.09/s) LR: 1.875e-02
|
| 441 |
+
2023-08-14 12:30:18,132 - train: [ INFO] - Train: 34 [1520/1521 (100%)] Loss: 1.756548 (1.5189) Acc@1: 50.0000 (60.0345) Acc@5: 87.5000 (88.4040) Time: 0.043s, 373.00/s (0.052s, 307.39/s) LR: 1.875e-02
|
| 442 |
+
2023-08-14 12:30:18,456 - train: [ INFO] - Test: [ 0/507] Time: 0.229 (0.229) Loss: 2.5544 (2.5544) Acc@1: 12.5000 (12.5000)Acc@5: 75.0000 (75.0000)
|
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+
|
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+
2023-08-14 12:30:29,736 - train: [ INFO] - Test: [ 500/507] Time: 0.032 (0.023) Loss: 4.6613 (2.3300) Acc@1: 0.0000 (45.4840)Acc@5: 6.2500 (75.4990)
|
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+
|
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+
2023-08-14 12:30:29,872 - train: [ INFO] - Test: [ 507/507] Time: 0.034 (0.023) Loss: 2.0590 (2.3323) Acc@1: 33.3333 (45.4344)Acc@5: 66.6667 (75.3913)
|
| 447 |
+
|
| 448 |
+
2023-08-14 12:30:30,461 - train: [ INFO] - Train: 35 [ 0/1521 (100%)] Loss: 1.183076 (1.1831) Acc@1: 75.0000 (75.0000) Acc@5: 93.7500 (93.7500) Time: 0.456s, 35.13/s (0.456s, 35.13/s) LR: 1.875e-02
|
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+
2023-08-14 12:30:56,739 - train: [ INFO] - Train: 35 [ 500/1521 (100%)] Loss: 1.430153 (1.3310) Acc@1: 75.0000 (64.2340) Acc@5: 93.7500 (91.4671) Time: 0.050s, 320.48/s (0.053s, 299.91/s) LR: 1.875e-02
|
| 450 |
+
2023-08-14 12:31:23,207 - train: [ INFO] - Train: 35 [1000/1521 (100%)] Loss: 1.414262 (1.4279) Acc@1: 62.5000 (61.9943) Acc@5: 93.7500 (90.0225) Time: 0.051s, 313.20/s (0.053s, 301.10/s) LR: 1.875e-02
|
| 451 |
+
2023-08-14 12:31:49,286 - train: [ INFO] - Train: 35 [1500/1521 (100%)] Loss: 3.039250 (1.4985) Acc@1: 37.5000 (60.4264) Acc@5: 62.5000 (88.8991) Time: 0.063s, 254.93/s (0.053s, 302.98/s) LR: 1.875e-02
|
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+
2023-08-14 12:31:50,311 - train: [ INFO] - Train: 35 [1520/1521 (100%)] Loss: 2.353764 (1.5015) Acc@1: 37.5000 (60.3468) Acc@5: 75.0000 (88.8190) Time: 0.065s, 246.34/s (0.053s, 303.10/s) LR: 1.875e-02
|
| 453 |
+
2023-08-14 12:31:50,637 - train: [ INFO] - Test: [ 0/507] Time: 0.235 (0.235) Loss: 2.2398 (2.2398) Acc@1: 31.2500 (31.2500)Acc@5: 75.0000 (75.0000)
|
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+
|
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+
2023-08-14 12:32:01,958 - train: [ INFO] - Test: [ 500/507] Time: 0.018 (0.023) Loss: 4.8316 (2.3611) Acc@1: 6.2500 (45.1347)Acc@5: 18.7500 (74.7380)
|
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+
|
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+
2023-08-14 12:32:02,095 - train: [ INFO] - Test: [ 507/507] Time: 0.025 (0.023) Loss: 0.9750 (2.3658) Acc@1: 100.0000 (44.9291)Acc@5: 100.0000 (74.6026)
|
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+
|
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+
2023-08-14 12:32:02,674 - train: [ INFO] - Train: 36 [ 0/1521 (100%)] Loss: 1.750331 (1.7503) Acc@1: 50.0000 (50.0000) Acc@5: 81.2500 (81.2500) Time: 0.481s, 33.29/s (0.481s, 33.29/s) LR: 1.875e-02
|
| 460 |
+
2023-08-14 12:32:29,334 - train: [ INFO] - Train: 36 [ 500/1521 (100%)] Loss: 1.431839 (1.2984) Acc@1: 43.7500 (65.7435) Acc@5: 100.0000 (91.6791) Time: 0.044s, 364.79/s (0.054s, 295.41/s) LR: 1.875e-02
|
| 461 |
+
2023-08-14 12:32:55,136 - train: [ INFO] - Train: 36 [1000/1521 (100%)] Loss: 1.589325 (1.4041) Acc@1: 75.0000 (62.9433) Acc@5: 87.5000 (90.0475) Time: 0.052s, 306.01/s (0.053s, 302.57/s) LR: 1.875e-02
|
| 462 |
+
2023-08-14 12:33:20,901 - train: [ INFO] - Train: 36 [1500/1521 (100%)] Loss: 1.824610 (1.4894) Acc@1: 56.2500 (60.7761) Acc@5: 68.7500 (88.8116) Time: 0.048s, 334.20/s (0.052s, 305.19/s) LR: 1.875e-02
|
| 463 |
+
2023-08-14 12:33:22,104 - train: [ INFO] - Train: 36 [1520/1521 (100%)] Loss: 1.226967 (1.4917) Acc@1: 68.7500 (60.7084) Acc@5: 93.7500 (88.7738) Time: 0.050s, 319.21/s (0.053s, 304.60/s) LR: 1.875e-02
|
| 464 |
+
2023-08-14 12:33:22,510 - train: [ INFO] - Test: [ 0/507] Time: 0.236 (0.236) Loss: 1.9927 (1.9927) Acc@1: 43.7500 (43.7500)Acc@5: 87.5000 (87.5000)
|
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+
|
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+
2023-08-14 12:33:33,701 - train: [ INFO] - Test: [ 500/507] Time: 0.018 (0.023) Loss: 4.5858 (2.2872) Acc@1: 6.2500 (46.3947)Acc@5: 31.2500 (76.3473)
|
| 467 |
+
|
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+
2023-08-14 12:33:33,839 - train: [ INFO] - Test: [ 507/507] Time: 0.024 (0.023) Loss: 1.5178 (2.2901) Acc@1: 66.6667 (46.2600)Acc@5: 100.0000 (76.2662)
|
| 469 |
+
|
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+
2023-08-14 12:33:34,439 - train: [ INFO] - Train: 37 [ 0/1521 (100%)] Loss: 0.983059 (0.9831) Acc@1: 68.7500 (68.7500) Acc@5: 100.0000 (100.0000) Time: 0.467s, 34.29/s (0.467s, 34.29/s) LR: 1.875e-02
|
| 471 |
+
2023-08-14 12:33:59,814 - train: [ INFO] - Train: 37 [ 500/1521 (100%)] Loss: 1.664097 (1.2991) Acc@1: 56.2500 (64.8578) Acc@5: 81.2500 (91.4546) Time: 0.037s, 426.74/s (0.052s, 310.26/s) LR: 1.875e-02
|
| 472 |
+
2023-08-14 12:34:25,516 - train: [ INFO] - Train: 37 [1000/1521 (100%)] Loss: 1.584372 (1.4049) Acc@1: 62.5000 (62.4500) Acc@5: 87.5000 (90.1474) Time: 0.041s, 388.71/s (0.051s, 310.79/s) LR: 1.875e-02
|
| 473 |
+
2023-08-14 12:34:51,699 - train: [ INFO] - Train: 37 [1500/1521 (100%)] Loss: 1.657115 (1.4950) Acc@1: 56.2500 (60.0516) Acc@5: 100.0000 (88.8616) Time: 0.038s, 417.85/s (0.052s, 309.04/s) LR: 1.875e-02
|
| 474 |
+
2023-08-14 12:34:52,690 - train: [ INFO] - Train: 37 [1520/1521 (100%)] Loss: 1.102845 (1.4972) Acc@1: 75.0000 (59.9811) Acc@5: 93.7500 (88.8067) Time: 0.056s, 287.05/s (0.052s, 309.22/s) LR: 1.875e-02
|
| 475 |
+
2023-08-14 12:34:53,023 - train: [ INFO] - Test: [ 0/507] Time: 0.228 (0.228) Loss: 2.8175 (2.8175) Acc@1: 31.2500 (31.2500)Acc@5: 62.5000 (62.5000)
|
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+
|
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+
2023-08-14 12:35:04,322 - train: [ INFO] - Test: [ 500/507] Time: 0.018 (0.023) Loss: 2.7957 (2.3313) Acc@1: 25.0000 (44.9975)Acc@5: 62.5000 (75.0125)
|
| 478 |
+
|
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+
2023-08-14 12:35:04,457 - train: [ INFO] - Test: [ 507/507] Time: 0.029 (0.023) Loss: 0.1492 (2.3324) Acc@1: 100.0000 (45.0031)Acc@5: 100.0000 (74.9846)
|
| 480 |
+
|
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+
2023-08-14 12:35:05,033 - train: [ INFO] - Train: 38 [ 0/1521 (100%)] Loss: 1.350842 (1.3508) Acc@1: 68.7500 (68.7500) Acc@5: 93.7500 (93.7500) Time: 0.473s, 33.86/s (0.473s, 33.86/s) LR: 1.875e-02
|
| 482 |
+
2023-08-14 12:35:31,626 - train: [ INFO] - Train: 38 [ 500/1521 (100%)] Loss: 2.014229 (1.3092) Acc@1: 56.2500 (65.3318) Acc@5: 75.0000 (91.3922) Time: 0.037s, 426.91/s (0.054s, 296.22/s) LR: 1.875e-02
|
| 483 |
+
2023-08-14 12:35:57,766 - train: [ INFO] - Train: 38 [1000/1521 (100%)] Loss: 2.028869 (1.4083) Acc@1: 43.7500 (62.7248) Acc@5: 93.7500 (90.0350) Time: 0.050s, 317.41/s (0.053s, 301.08/s) LR: 1.875e-02
|
| 484 |
+
2023-08-14 12:36:24,059 - train: [ INFO] - Train: 38 [1500/1521 (100%)] Loss: 1.927850 (1.4863) Acc@1: 50.0000 (60.8678) Acc@5: 87.5000 (88.8075) Time: 0.053s, 304.65/s (0.053s, 302.15/s) LR: 1.875e-02
|
| 485 |
+
2023-08-14 12:36:24,997 - train: [ INFO] - Train: 38 [1520/1521 (100%)] Loss: 2.064504 (1.4901) Acc@1: 43.7500 (60.7865) Acc@5: 75.0000 (88.7697) Time: 0.050s, 321.41/s (0.053s, 302.60/s) LR: 1.875e-02
|
| 486 |
+
2023-08-14 12:36:25,353 - train: [ INFO] - Test: [ 0/507] Time: 0.239 (0.239) Loss: 2.4103 (2.4103) Acc@1: 50.0000 (50.0000)Acc@5: 75.0000 (75.0000)
|
| 487 |
+
|
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+
2023-08-14 12:36:36,761 - train: [ INFO] - Test: [ 500/507] Time: 0.041 (0.023) Loss: 2.7910 (2.2872) Acc@1: 37.5000 (45.9830)Acc@5: 68.7500 (76.4596)
|
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+
|
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+
2023-08-14 12:36:36,892 - train: [ INFO] - Test: [ 507/507] Time: 0.021 (0.023) Loss: 0.2349 (2.2869) Acc@1: 100.0000 (46.0259)Acc@5: 100.0000 (76.4264)
|
| 491 |
+
|
| 492 |
+
2023-08-14 12:36:37,454 - train: [ INFO] - Train: 39 [ 0/1521 (100%)] Loss: 1.260080 (1.2601) Acc@1: 75.0000 (75.0000) Acc@5: 93.7500 (93.7500) Time: 0.466s, 34.33/s (0.466s, 34.33/s) LR: 1.875e-02
|
| 493 |
+
2023-08-14 12:37:03,519 - train: [ INFO] - Train: 39 [ 500/1521 (100%)] Loss: 1.535175 (1.2788) Acc@1: 62.5000 (66.0679) Acc@5: 87.5000 (92.0783) Time: 0.044s, 367.65/s (0.053s, 302.20/s) LR: 1.875e-02
|
| 494 |
+
2023-08-14 12:37:29,843 - train: [ INFO] - Train: 39 [1000/1521 (100%)] Loss: 1.995998 (1.4106) Acc@1: 43.7500 (62.6249) Acc@5: 87.5000 (90.0912) Time: 0.040s, 395.77/s (0.053s, 303.07/s) LR: 1.875e-02
|
| 495 |
+
2023-08-14 12:37:55,397 - train: [ INFO] - Train: 39 [1500/1521 (100%)] Loss: 1.216711 (1.4921) Acc@1: 68.7500 (60.6387) Acc@5: 93.7500 (88.8907) Time: 0.045s, 358.84/s (0.052s, 306.35/s) LR: 1.875e-02
|
| 496 |
+
2023-08-14 12:37:56,333 - train: [ INFO] - Train: 39 [1520/1521 (100%)] Loss: 1.194057 (1.4920) Acc@1: 68.7500 (60.6427) Acc@5: 87.5000 (88.9300) Time: 0.046s, 344.57/s (0.052s, 306.77/s) LR: 1.875e-02
|
| 497 |
+
2023-08-14 12:37:56,661 - train: [ INFO] - Test: [ 0/507] Time: 0.232 (0.232) Loss: 1.6758 (1.6758) Acc@1: 50.0000 (50.0000)Acc@5: 87.5000 (87.5000)
|
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+
|
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+
2023-08-14 12:38:07,886 - train: [ INFO] - Test: [ 500/507] Time: 0.020 (0.023) Loss: 2.6524 (2.2527) Acc@1: 12.5000 (47.1058)Acc@5: 75.0000 (76.1477)
|
| 500 |
+
|
| 501 |
+
2023-08-14 12:38:08,056 - train: [ INFO] - Test: [ 507/507] Time: 0.019 (0.023) Loss: 2.1037 (2.2554) Acc@1: 33.3333 (46.9501)Acc@5: 66.6667 (76.0937)
|
| 502 |
+
|
| 503 |
+
2023-08-14 12:38:08,194 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 504 |
+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-39.pth.tar', 46.950092422381935)
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2023-08-14 12:38:08,668 - train: [ INFO] - Train: 40 [ 0/1521 (100%)] Loss: 1.454771 (1.4548) Acc@1: 68.7500 (68.7500) Acc@5: 87.5000 (87.5000) Time: 0.473s, 33.84/s (0.473s, 33.84/s) LR: 1.875e-03
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2023-08-14 12:38:34,621 - train: [ INFO] - Train: 40 [ 500/1521 (100%)] Loss: 0.633621 (0.8577) Acc@1: 81.2500 (79.6906) Acc@5: 100.0000 (96.6692) Time: 0.066s, 243.72/s (0.053s, 303.41/s) LR: 1.875e-03
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2023-08-14 12:39:01,403 - train: [ INFO] - Train: 40 [1000/1521 (100%)] Loss: 0.634718 (0.7499) Acc@1: 81.2500 (82.8859) Acc@5: 100.0000 (97.4838) Time: 0.048s, 334.21/s (0.053s, 301.07/s) LR: 1.875e-03
|
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2023-08-14 12:39:27,558 - train: [ INFO] - Train: 40 [1500/1521 (100%)] Loss: 0.760376 (0.6980) Acc@1: 75.0000 (84.3479) Acc@5: 93.7500 (97.7682) Time: 0.063s, 252.93/s (0.053s, 302.67/s) LR: 1.875e-03
|
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+
2023-08-14 12:39:28,633 - train: [ INFO] - Train: 40 [1520/1521 (100%)] Loss: 1.150501 (0.6974) Acc@1: 68.7500 (84.3647) Acc@5: 100.0000 (97.7605) Time: 0.059s, 271.75/s (0.053s, 302.60/s) LR: 1.875e-03
|
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+
2023-08-14 12:39:28,965 - train: [ INFO] - Test: [ 0/507] Time: 0.233 (0.233) Loss: 1.2607 (1.2607) Acc@1: 50.0000 (50.0000)Acc@5: 100.0000 (100.0000)
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2023-08-14 12:39:40,219 - train: [ INFO] - Test: [ 500/507] Time: 0.021 (0.023) Loss: 3.0293 (1.5658) Acc@1: 12.5000 (61.4895)Acc@5: 56.2500 (86.6018)
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2023-08-14 12:39:40,362 - train: [ INFO] - Test: [ 507/507] Time: 0.016 (0.023) Loss: 0.1929 (1.5658) Acc@1: 100.0000 (61.4664)Acc@5: 100.0000 (86.5927)
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+
|
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2023-08-14 12:39:40,461 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 518 |
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-40.pth.tar', 61.466420209488604)
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2023-08-14 12:39:40,901 - train: [ INFO] - Train: 41 [ 0/1521 (100%)] Loss: 0.369474 (0.3695) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.439s, 36.45/s (0.439s, 36.45/s) LR: 1.875e-03
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2023-08-14 12:40:06,065 - train: [ INFO] - Train: 41 [ 500/1521 (100%)] Loss: 0.881067 (0.5250) Acc@1: 62.5000 (89.3338) Acc@5: 100.0000 (98.7525) Time: 0.048s, 335.59/s (0.051s, 313.16/s) LR: 1.875e-03
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2023-08-14 12:40:32,221 - train: [ INFO] - Train: 41 [1000/1521 (100%)] Loss: 0.775536 (0.5366) Acc@1: 81.2500 (88.9048) Acc@5: 100.0000 (98.7512) Time: 0.038s, 425.92/s (0.052s, 309.49/s) LR: 1.875e-03
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2023-08-14 12:40:58,904 - train: [ INFO] - Train: 41 [1500/1521 (100%)] Loss: 0.630207 (0.5443) Acc@1: 81.2500 (88.6701) Acc@5: 100.0000 (98.7467) Time: 0.052s, 309.45/s (0.052s, 306.22/s) LR: 1.875e-03
|
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2023-08-14 12:40:59,969 - train: [ INFO] - Train: 41 [1520/1521 (100%)] Loss: 0.277199 (0.5452) Acc@1: 93.7500 (88.6300) Acc@5: 100.0000 (98.7426) Time: 0.043s, 375.87/s (0.052s, 306.15/s) LR: 1.875e-03
|
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2023-08-14 12:41:00,344 - train: [ INFO] - Test: [ 0/507] Time: 0.256 (0.256) Loss: 1.5214 (1.5214) Acc@1: 43.7500 (43.7500)Acc@5: 93.7500 (93.7500)
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2023-08-14 12:41:11,826 - train: [ INFO] - Test: [ 500/507] Time: 0.031 (0.023) Loss: 2.4261 (1.5413) Acc@1: 31.2500 (62.5125)Acc@5: 68.7500 (86.6267)
|
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2023-08-14 12:41:11,974 - train: [ INFO] - Test: [ 507/507] Time: 0.014 (0.023) Loss: 0.1816 (1.5422) Acc@1: 100.0000 (62.3537)Acc@5: 100.0000 (86.5927)
|
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+
|
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2023-08-14 12:41:12,102 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 532 |
+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-41.pth.tar', 62.35366605052372)
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2023-08-14 12:41:12,583 - train: [ INFO] - Train: 42 [ 0/1521 (100%)] Loss: 0.504136 (0.5041) Acc@1: 93.7500 (93.7500) Acc@5: 100.0000 (100.0000) Time: 0.480s, 33.37/s (0.480s, 33.37/s) LR: 1.875e-03
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2023-08-14 12:41:39,721 - train: [ INFO] - Train: 42 [ 500/1521 (100%)] Loss: 0.542121 (0.4810) Acc@1: 87.5000 (90.8807) Acc@5: 100.0000 (99.0644) Time: 0.047s, 342.74/s (0.055s, 290.30/s) LR: 1.875e-03
|
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+
2023-08-14 12:42:06,574 - train: [ INFO] - Train: 42 [1000/1521 (100%)] Loss: 0.714420 (0.4888) Acc@1: 81.2500 (90.5345) Acc@5: 100.0000 (99.1071) Time: 0.038s, 418.54/s (0.054s, 294.09/s) LR: 1.875e-03
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+
2023-08-14 12:42:31,986 - train: [ INFO] - Train: 42 [1500/1521 (100%)] Loss: 0.808584 (0.4997) Acc@1: 68.7500 (90.3190) Acc@5: 93.7500 (99.0007) Time: 0.043s, 374.52/s (0.053s, 300.70/s) LR: 1.875e-03
|
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+
2023-08-14 12:42:33,042 - train: [ INFO] - Train: 42 [1520/1521 (100%)] Loss: 0.732772 (0.4999) Acc@1: 87.5000 (90.3353) Acc@5: 93.7500 (99.0015) Time: 0.056s, 284.93/s (0.053s, 300.73/s) LR: 1.875e-03
|
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+
2023-08-14 12:42:33,358 - train: [ INFO] - Test: [ 0/507] Time: 0.226 (0.226) Loss: 1.4189 (1.4189) Acc@1: 37.5000 (37.5000)Acc@5: 93.7500 (93.7500)
|
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2023-08-14 12:42:44,727 - train: [ INFO] - Test: [ 500/507] Time: 0.021 (0.023) Loss: 2.5699 (1.5431) Acc@1: 31.2500 (62.5374)Acc@5: 68.7500 (86.4895)
|
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2023-08-14 12:42:44,888 - train: [ INFO] - Test: [ 507/507] Time: 0.020 (0.023) Loss: 0.5429 (1.5443) Acc@1: 100.0000 (62.4030)Acc@5: 100.0000 (86.4818)
|
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+
|
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+
2023-08-14 12:42:45,013 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 546 |
+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-42.pth.tar', 62.402957486136785)
|
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+
|
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+
2023-08-14 12:42:45,461 - train: [ INFO] - Train: 43 [ 0/1521 (100%)] Loss: 0.473931 (0.4739) Acc@1: 93.7500 (93.7500) Acc@5: 100.0000 (100.0000) Time: 0.446s, 35.84/s (0.446s, 35.84/s) LR: 1.875e-03
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+
2023-08-14 12:43:11,859 - train: [ INFO] - Train: 43 [ 500/1521 (100%)] Loss: 0.407450 (0.4389) Acc@1: 87.5000 (92.4651) Acc@5: 100.0000 (99.4261) Time: 0.071s, 224.43/s (0.054s, 298.67/s) LR: 1.875e-03
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+
2023-08-14 12:43:37,561 - train: [ INFO] - Train: 43 [1000/1521 (100%)] Loss: 0.348935 (0.4560) Acc@1: 100.0000 (91.8831) Acc@5: 100.0000 (99.3007) Time: 0.057s, 280.91/s (0.052s, 304.86/s) LR: 1.875e-03
|
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+
2023-08-14 12:44:03,322 - train: [ INFO] - Train: 43 [1500/1521 (100%)] Loss: 0.426312 (0.4654) Acc@1: 93.7500 (91.4640) Acc@5: 100.0000 (99.2380) Time: 0.037s, 437.41/s (0.052s, 306.75/s) LR: 1.875e-03
|
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+
2023-08-14 12:44:04,343 - train: [ INFO] - Train: 43 [1520/1521 (100%)] Loss: 0.258656 (0.4657) Acc@1: 100.0000 (91.4407) Acc@5: 100.0000 (99.2439) Time: 0.041s, 393.52/s (0.052s, 306.83/s) LR: 1.875e-03
|
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+
2023-08-14 12:44:04,681 - train: [ INFO] - Test: [ 0/507] Time: 0.234 (0.234) Loss: 1.3383 (1.3383) Acc@1: 56.2500 (56.2500)Acc@5: 100.0000 (100.0000)
|
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+
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2023-08-14 12:44:15,674 - train: [ INFO] - Test: [ 500/507] Time: 0.018 (0.022) Loss: 2.2457 (1.5492) Acc@1: 43.7500 (62.2380)Acc@5: 68.7500 (86.4646)
|
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+
2023-08-14 12:44:15,848 - train: [ INFO] - Test: [ 507/507] Time: 0.024 (0.022) Loss: 0.2030 (1.5496) Acc@1: 100.0000 (62.1319)Acc@5: 100.0000 (86.4818)
|
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+
2023-08-14 12:44:16,390 - train: [ INFO] - Train: 44 [ 0/1521 (100%)] Loss: 0.438327 (0.4383) Acc@1: 93.7500 (93.7500) Acc@5: 100.0000 (100.0000) Time: 0.442s, 36.20/s (0.442s, 36.20/s) LR: 1.875e-03
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+
2023-08-14 12:44:42,452 - train: [ INFO] - Train: 44 [ 500/1521 (100%)] Loss: 0.599844 (0.4230) Acc@1: 87.5000 (92.9017) Acc@5: 100.0000 (99.4386) Time: 0.036s, 439.28/s (0.053s, 302.50/s) LR: 1.875e-03
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+
2023-08-14 12:45:08,535 - train: [ INFO] - Train: 44 [1000/1521 (100%)] Loss: 0.422030 (0.4381) Acc@1: 100.0000 (92.5325) Acc@5: 100.0000 (99.3756) Time: 0.078s, 204.29/s (0.053s, 304.62/s) LR: 1.875e-03
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2023-08-14 12:45:34,425 - train: [ INFO] - Train: 44 [1500/1521 (100%)] Loss: 0.666004 (0.4449) Acc@1: 87.5000 (92.2926) Acc@5: 100.0000 (99.4171) Time: 0.074s, 215.18/s (0.052s, 306.08/s) LR: 1.875e-03
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2023-08-14 12:45:35,506 - train: [ INFO] - Train: 44 [1520/1521 (100%)] Loss: 0.566741 (0.4452) Acc@1: 81.2500 (92.2502) Acc@5: 100.0000 (99.4206) Time: 0.041s, 390.37/s (0.052s, 305.95/s) LR: 1.875e-03
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+
2023-08-14 12:45:35,848 - train: [ INFO] - Test: [ 0/507] Time: 0.230 (0.230) Loss: 1.4178 (1.4178) Acc@1: 50.0000 (50.0000)Acc@5: 100.0000 (100.0000)
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2023-08-14 12:45:47,342 - train: [ INFO] - Test: [ 500/507] Time: 0.019 (0.023) Loss: 2.7626 (1.5331) Acc@1: 25.0000 (62.2879)Acc@5: 62.5000 (86.9261)
|
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2023-08-14 12:45:47,500 - train: [ INFO] - Test: [ 507/507] Time: 0.016 (0.023) Loss: 0.2199 (1.5332) Acc@1: 100.0000 (62.1935)Acc@5: 100.0000 (86.9871)
|
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+
2023-08-14 12:45:48,049 - train: [ INFO] - Train: 45 [ 0/1521 (100%)] Loss: 0.225532 (0.2255) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.446s, 35.85/s (0.446s, 35.85/s) LR: 1.875e-03
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2023-08-14 12:46:14,317 - train: [ INFO] - Train: 45 [ 500/1521 (100%)] Loss: 0.239985 (0.3962) Acc@1: 100.0000 (93.9247) Acc@5: 100.0000 (99.6507) Time: 0.072s, 222.17/s (0.053s, 300.13/s) LR: 1.875e-03
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2023-08-14 12:46:40,370 - train: [ INFO] - Train: 45 [1000/1521 (100%)] Loss: 0.643040 (0.4087) Acc@1: 68.7500 (93.5564) Acc@5: 100.0000 (99.5817) Time: 0.062s, 256.65/s (0.053s, 303.59/s) LR: 1.875e-03
|
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+
2023-08-14 12:47:05,937 - train: [ INFO] - Train: 45 [1500/1521 (100%)] Loss: 0.298725 (0.4227) Acc@1: 93.7500 (93.2170) Acc@5: 100.0000 (99.5545) Time: 0.044s, 365.36/s (0.052s, 306.65/s) LR: 1.875e-03
|
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+
2023-08-14 12:47:06,992 - train: [ INFO] - Train: 45 [1520/1521 (100%)] Loss: 0.490945 (0.4230) Acc@1: 81.2500 (93.1870) Acc@5: 100.0000 (99.5480) Time: 0.061s, 261.93/s (0.052s, 306.61/s) LR: 1.875e-03
|
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+
2023-08-14 12:47:07,318 - train: [ INFO] - Test: [ 0/507] Time: 0.247 (0.247) Loss: 1.0452 (1.0452) Acc@1: 62.5000 (62.5000)Acc@5: 100.0000 (100.0000)
|
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2023-08-14 12:47:18,794 - train: [ INFO] - Test: [ 500/507] Time: 0.018 (0.023) Loss: 2.2513 (1.5352) Acc@1: 37.5000 (62.5624)Acc@5: 68.7500 (86.8762)
|
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2023-08-14 12:47:18,953 - train: [ INFO] - Test: [ 507/507] Time: 0.014 (0.023) Loss: 0.0853 (1.5361) Acc@1: 100.0000 (62.4276)Acc@5: 100.0000 (86.9131)
|
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+
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2023-08-14 12:47:19,040 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
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('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-45.pth.tar', 62.42760320394331)
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+
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+
2023-08-14 12:47:19,551 - train: [ INFO] - Train: 46 [ 0/1521 (100%)] Loss: 0.458361 (0.4584) Acc@1: 93.7500 (93.7500) Acc@5: 100.0000 (100.0000) Time: 0.509s, 31.44/s (0.509s, 31.44/s) LR: 1.875e-03
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+
2023-08-14 12:47:45,417 - train: [ INFO] - Train: 46 [ 500/1521 (100%)] Loss: 0.362676 (0.3845) Acc@1: 93.7500 (94.4112) Acc@5: 100.0000 (99.6881) Time: 0.074s, 216.71/s (0.053s, 303.99/s) LR: 1.875e-03
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| 586 |
+
2023-08-14 12:48:11,965 - train: [ INFO] - Train: 46 [1000/1521 (100%)] Loss: 0.340098 (0.3962) Acc@1: 93.7500 (94.0559) Acc@5: 100.0000 (99.7003) Time: 0.057s, 282.30/s (0.053s, 302.69/s) LR: 1.875e-03
|
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+
2023-08-14 12:48:38,547 - train: [ INFO] - Train: 46 [1500/1521 (100%)] Loss: 0.464957 (0.4073) Acc@1: 93.7500 (93.8832) Acc@5: 100.0000 (99.6502) Time: 0.059s, 271.03/s (0.053s, 302.13/s) LR: 1.875e-03
|
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+
2023-08-14 12:48:39,552 - train: [ INFO] - Train: 46 [1520/1521 (100%)] Loss: 0.357903 (0.4073) Acc@1: 93.7500 (93.8815) Acc@5: 100.0000 (99.6507) Time: 0.057s, 282.37/s (0.053s, 302.33/s) LR: 1.875e-03
|
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+
2023-08-14 12:48:39,918 - train: [ INFO] - Test: [ 0/507] Time: 0.244 (0.244) Loss: 1.0936 (1.0936) Acc@1: 56.2500 (56.2500)Acc@5: 100.0000 (100.0000)
|
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+
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2023-08-14 12:48:51,351 - train: [ INFO] - Test: [ 500/507] Time: 0.018 (0.023) Loss: 2.6915 (1.5307) Acc@1: 25.0000 (62.3129)Acc@5: 62.5000 (86.8887)
|
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2023-08-14 12:48:51,525 - train: [ INFO] - Test: [ 507/507] Time: 0.018 (0.023) Loss: 0.3156 (1.5314) Acc@1: 100.0000 (62.2304)Acc@5: 100.0000 (86.8885)
|
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+
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+
2023-08-14 12:48:52,199 - train: [ INFO] - Train: 47 [ 0/1521 (100%)] Loss: 0.382151 (0.3822) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.585s, 27.37/s (0.585s, 27.37/s) LR: 1.875e-03
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2023-08-14 12:49:18,258 - train: [ INFO] - Train: 47 [ 500/1521 (100%)] Loss: 0.300303 (0.3694) Acc@1: 93.7500 (95.1347) Acc@5: 100.0000 (99.8378) Time: 0.044s, 365.65/s (0.053s, 300.93/s) LR: 1.875e-03
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+
2023-08-14 12:49:44,270 - train: [ INFO] - Train: 47 [1000/1521 (100%)] Loss: 0.384799 (0.3839) Acc@1: 100.0000 (94.6491) Acc@5: 100.0000 (99.7440) Time: 0.041s, 388.63/s (0.053s, 304.24/s) LR: 1.875e-03
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2023-08-14 12:50:10,871 - train: [ INFO] - Train: 47 [1500/1521 (100%)] Loss: 0.556240 (0.3941) Acc@1: 93.7500 (94.2996) Acc@5: 93.7500 (99.6919) Time: 0.083s, 191.77/s (0.053s, 303.09/s) LR: 1.875e-03
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+
2023-08-14 12:50:11,930 - train: [ INFO] - Train: 47 [1520/1521 (100%)] Loss: 0.186846 (0.3944) Acc@1: 100.0000 (94.3212) Acc@5: 100.0000 (99.6877) Time: 0.048s, 331.50/s (0.053s, 303.07/s) LR: 1.875e-03
|
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+
2023-08-14 12:50:12,387 - train: [ INFO] - Test: [ 0/507] Time: 0.253 (0.253) Loss: 1.1714 (1.1714) Acc@1: 62.5000 (62.5000)Acc@5: 100.0000 (100.0000)
|
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+
2023-08-14 12:50:23,603 - train: [ INFO] - Test: [ 500/507] Time: 0.015 (0.023) Loss: 2.6622 (1.5262) Acc@1: 37.5000 (62.2754)Acc@5: 68.7500 (86.7515)
|
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+
2023-08-14 12:50:23,751 - train: [ INFO] - Test: [ 507/507] Time: 0.026 (0.023) Loss: 0.3010 (1.5254) Acc@1: 100.0000 (62.1935)Acc@5: 100.0000 (86.8392)
|
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+
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+
2023-08-14 12:50:24,323 - train: [ INFO] - Train: 48 [ 0/1521 (100%)] Loss: 0.191560 (0.1916) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.467s, 34.23/s (0.467s, 34.23/s) LR: 1.875e-03
|
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+
2023-08-14 12:50:50,600 - train: [ INFO] - Train: 48 [ 500/1521 (100%)] Loss: 0.563042 (0.3595) Acc@1: 81.2500 (95.4217) Acc@5: 100.0000 (99.7630) Time: 0.048s, 332.33/s (0.053s, 299.80/s) LR: 1.875e-03
|
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+
2023-08-14 12:51:17,746 - train: [ INFO] - Train: 48 [1000/1521 (100%)] Loss: 0.462264 (0.3737) Acc@1: 93.7500 (95.1424) Acc@5: 100.0000 (99.7940) Time: 0.047s, 339.68/s (0.054s, 297.26/s) LR: 1.875e-03
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| 609 |
+
2023-08-14 12:51:44,975 - train: [ INFO] - Train: 48 [1500/1521 (100%)] Loss: 0.425053 (0.3836) Acc@1: 100.0000 (94.7493) Acc@5: 100.0000 (99.7627) Time: 0.047s, 342.24/s (0.054s, 296.12/s) LR: 1.875e-03
|
| 610 |
+
2023-08-14 12:51:46,032 - train: [ INFO] - Train: 48 [1520/1521 (100%)] Loss: 0.400020 (0.3841) Acc@1: 93.7500 (94.7280) Acc@5: 100.0000 (99.7617) Time: 0.077s, 207.88/s (0.054s, 296.21/s) LR: 1.875e-03
|
| 611 |
+
2023-08-14 12:51:46,407 - train: [ INFO] - Test: [ 0/507] Time: 0.245 (0.245) Loss: 1.1248 (1.1248) Acc@1: 68.7500 (68.7500)Acc@5: 100.0000 (100.0000)
|
| 612 |
+
|
| 613 |
+
2023-08-14 12:51:57,781 - train: [ INFO] - Test: [ 500/507] Time: 0.029 (0.023) Loss: 2.3270 (1.5299) Acc@1: 43.7500 (62.7745)Acc@5: 75.0000 (86.6018)
|
| 614 |
+
|
| 615 |
+
2023-08-14 12:51:57,947 - train: [ INFO] - Test: [ 507/507] Time: 0.048 (0.023) Loss: 0.3498 (1.5303) Acc@1: 100.0000 (62.6987)Acc@5: 100.0000 (86.6297)
|
| 616 |
+
|
| 617 |
+
2023-08-14 12:51:58,069 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 618 |
+
('/home/hexiang/DomainAdaptation_DVS/Results/Baseline/SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/checkpoint-48.pth.tar', 62.698706099815155)
|
| 619 |
+
|
| 620 |
+
2023-08-14 12:51:58,516 - train: [ INFO] - Train: 49 [ 0/1521 (100%)] Loss: 0.329599 (0.3296) Acc@1: 93.7500 (93.7500) Acc@5: 100.0000 (100.0000) Time: 0.445s, 35.92/s (0.445s, 35.92/s) LR: 1.875e-03
|
| 621 |
+
2023-08-14 12:52:25,543 - train: [ INFO] - Train: 49 [ 500/1521 (100%)] Loss: 0.278178 (0.3544) Acc@1: 100.0000 (95.8084) Acc@5: 100.0000 (99.8129) Time: 0.059s, 269.96/s (0.055s, 291.85/s) LR: 1.875e-03
|
| 622 |
+
2023-08-14 12:52:52,415 - train: [ INFO] - Train: 49 [1000/1521 (100%)] Loss: 0.212988 (0.3625) Acc@1: 100.0000 (95.4046) Acc@5: 100.0000 (99.8439) Time: 0.039s, 412.44/s (0.054s, 294.77/s) LR: 1.875e-03
|
| 623 |
+
2023-08-14 12:53:16,817 - train: [ INFO] - Train: 49 [1500/1521 (100%)] Loss: 0.353693 (0.3729) Acc@1: 100.0000 (95.1699) Acc@5: 100.0000 (99.8001) Time: 0.058s, 278.24/s (0.052s, 305.04/s) LR: 1.875e-03
|
| 624 |
+
2023-08-14 12:53:17,811 - train: [ INFO] - Train: 49 [1520/1521 (100%)] Loss: 0.257376 (0.3733) Acc@1: 100.0000 (95.1718) Acc@5: 100.0000 (99.8028) Time: 0.045s, 351.94/s (0.052s, 305.26/s) LR: 1.875e-03
|
| 625 |
+
2023-08-14 12:53:18,128 - train: [ INFO] - Test: [ 0/507] Time: 0.230 (0.230) Loss: 1.2824 (1.2824) Acc@1: 56.2500 (56.2500)Acc@5: 100.0000 (100.0000)
|
| 626 |
+
|
| 627 |
+
2023-08-14 12:53:28,785 - train: [ INFO] - Test: [ 500/507] Time: 0.015 (0.022) Loss: 2.5998 (1.5298) Acc@1: 31.2500 (62.4626)Acc@5: 75.0000 (86.7390)
|
| 628 |
+
|
| 629 |
+
2023-08-14 12:53:28,942 - train: [ INFO] - Test: [ 507/507] Time: 0.029 (0.022) Loss: 0.3407 (1.5296) Acc@1: 100.0000 (62.3906)Acc@5: 100.0000 (86.7899)
|
| 630 |
+
|
| 631 |
+
2023-08-14 12:53:29,042 - train: [ INFO] - *** Best metric: 62.698706099815155 (epoch 48)
|
SCNN-nomni-12-seed_1024-bs_16-DA_False-ls_0.0-lr_1.2-traindataratio_1.0-TET_loss_False-refined_False/model_best.pth.tar
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size 8371403
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ADDED
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ADDED
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DVS_DA: false
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TET_loss: false
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| 3 |
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aa: rand-m9-mstd0.5-inc1
|
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act_fun: BackEIGateGrad
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channels_last: false
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clip_grad: null
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| 17 |
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color_jitter: 0.4
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conf_mat: false
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cooldown_epochs: 10
|
| 20 |
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critical_loss: false
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| 21 |
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crop_pct: null
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| 22 |
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| 23 |
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cutmix: 1.0
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cutmix_noise: 0.0
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| 27 |
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cutmix_num: 1
|
| 28 |
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cutmix_prob: 0.5
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| 29 |
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decay_epochs: 40.0
|
| 30 |
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decay_rate: 0.1
|
| 31 |
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device: 6
|
| 32 |
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dist_bn: ''
|
| 33 |
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domain_loss: true
|
| 34 |
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domain_loss_coefficient: 0.5
|
| 35 |
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drop: 0.0
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| 36 |
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drop_block: null
|
| 37 |
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drop_connect: null
|
| 38 |
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drop_path: 0.1
|
| 39 |
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encode: direct
|
| 40 |
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epochs: 50
|
| 41 |
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eval: false
|
| 42 |
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eval_checkpoint: ''
|
| 43 |
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eval_metric: top1
|
| 44 |
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|
| 45 |
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event_size: 48
|
| 46 |
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gaussian_n: 3
|
| 47 |
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gp: null
|
| 48 |
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hflip: 0.5
|
| 49 |
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img_size: 224
|
| 50 |
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initial_checkpoint: ''
|
| 51 |
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interpolation: ''
|
| 52 |
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jsd: false
|
| 53 |
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kernel_method: cuda
|
| 54 |
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layer_by_layer: false
|
| 55 |
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|
| 56 |
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log_interval: 500
|
| 57 |
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loss_fn: ce
|
| 58 |
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lr: 1.2
|
| 59 |
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lr_cycle_limit: 1
|
| 60 |
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lr_cycle_mul: 1.0
|
| 61 |
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lr_noise: null
|
| 62 |
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lr_noise_pct: 0.67
|
| 63 |
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lr_noise_std: 1.0
|
| 64 |
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mean: null
|
| 65 |
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min_lr: 1.0e-05
|
| 66 |
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mix_up: false
|
| 67 |
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mixup: 0.8
|
| 68 |
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mixup_mode: batch
|
| 69 |
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mixup_off_epoch: 0
|
| 70 |
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mixup_prob: 1.0
|
| 71 |
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mixup_switch_prob: 0.5
|
| 72 |
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model: Transfer_SCNN
|
| 73 |
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model_ema: false
|
| 74 |
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model_ema_decay: 0.99996
|
| 75 |
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model_ema_force_cpu: false
|
| 76 |
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momentum: 0.9
|
| 77 |
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n_groups: 1
|
| 78 |
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native_amp: false
|
| 79 |
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newton_maxiter: 20
|
| 80 |
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no_aug: false
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| 81 |
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no_prefetcher: false
|
| 82 |
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no_resume_opt: false
|
| 83 |
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| 84 |
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no_use_hsv: false
|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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opt: adamw
|
| 92 |
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|
| 93 |
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|
| 94 |
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output: /home/hexiang/DomainAdaptation_DVS/Results3/
|
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|
| 96 |
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|
| 97 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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+
resume: ''
|
| 114 |
+
rgbdata_ratio: 1.0
|
| 115 |
+
save_images: false
|
| 116 |
+
scale:
|
| 117 |
+
- 0.08
|
| 118 |
+
- 1.0
|
| 119 |
+
sched: step
|
| 120 |
+
seed: 1024
|
| 121 |
+
sigmoid_thres: false
|
| 122 |
+
smoothing: 0.0
|
| 123 |
+
snr: 0
|
| 124 |
+
source_dataset: omni
|
| 125 |
+
spike_output: false
|
| 126 |
+
spike_rate: false
|
| 127 |
+
split_bn: false
|
| 128 |
+
start_epoch: null
|
| 129 |
+
std: null
|
| 130 |
+
step: 12
|
| 131 |
+
suffix: ''
|
| 132 |
+
sync_bn: false
|
| 133 |
+
target_dataset: nomni
|
| 134 |
+
tau: 2.0
|
| 135 |
+
temporal_flatten: false
|
| 136 |
+
threshold: 0.5
|
| 137 |
+
train_interpolation: random
|
| 138 |
+
train_portion: 0.9
|
| 139 |
+
traindata_ratio: 1.0
|
| 140 |
+
tsne: false
|
| 141 |
+
tsregular: -1.0
|
| 142 |
+
tta: 0
|
| 143 |
+
use_multi_epochs_loader: false
|
| 144 |
+
validation_batch_size_multiplier: 1
|
| 145 |
+
vflip: 0.0
|
| 146 |
+
visualize: false
|
| 147 |
+
warmup_epochs: 5
|
| 148 |
+
warmup_lr: 1.0e-06
|
| 149 |
+
weight_decay: 0.01
|
| 150 |
+
workers: 8
|
Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/log.txt
ADDED
|
@@ -0,0 +1,860 @@
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2023-08-14 11:42:29,043 - train: [ INFO] - Training with a single process on 1 GPUs.
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2023-08-14 11:42:29,055 - train: [ INFO] - learning rate is 0.018750
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2023-08-14 11:42:29,055 - train: [ INFO] - Model Transfer_SCNN created, param count: 696591
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2023-08-14 11:42:34,482 - train: [ INFO] - AMP not enabled. Training in float32.
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2023-08-14 11:42:34,483 - train: [ INFO] - Scheduled epochs: 50
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2023-08-14 11:43:07,753 - train: [ INFO] - Train: 0 [ 0/1521 ( 0%)] Loss: 7.897732 (7.8977) Acc@1: 0.0000 ( 0.0000) Acc@5: 0.0000 ( 0.0000) Time: 6.853s, 2.33/s LR: 1.000e-06 P_Replacement: 0.0
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2023-08-14 11:44:49,381 - train: [ INFO] - Train: 0 [ 500/1521 ( 33%)] Loss: 7.891829 (7.8929) Acc@1: 0.0000 ( 0.0374) Acc@5: 0.0000 ( 0.2620) Time: 0.217s, 73.90/s LR: 1.000e-06 P_Replacement: 5.550631511300887e-07
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2023-08-14 11:46:30,031 - train: [ INFO] - Train: 0 [1000/1521 ( 66%)] Loss: 7.883446 (7.8929) Acc@1: 0.0000 ( 0.0562) Acc@5: 0.0000 ( 0.2997) Time: 0.209s, 76.59/s LR: 1.000e-06 P_Replacement: 4.44050520904071e-06
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2023-08-14 11:48:14,490 - train: [ INFO] - Train: 0 [1500/1521 ( 99%)] Loss: 7.905701 (7.8926) Acc@1: 0.0000 ( 0.0500) Acc@5: 0.0000 ( 0.3040) Time: 0.209s, 76.59/s LR: 1.000e-06 P_Replacement: 1.49867050805124e-05
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2023-08-14 11:48:18,413 - train: [ INFO] - Train: 0 [1520/1521 (100%)] Loss: 7.889486 (7.8926) Acc@1: 0.0000 ( 0.0534) Acc@5: 0.0000 ( 0.3041) Time: 0.209s, 76.65/s LR: 1.000e-06 P_Replacement: 1.559420171715084e-05
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2023-08-14 11:48:18,745 - train: [ INFO] - Test: [ 0/507] Time: 0.270 (0.270) Loss: 7.3901 (7.3901) cLoss: 0.0000 (0.0000) Acc@1: 0.0000 ( 0.0000)Acc@5: 0.0000 ( 0.0000)
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2023-08-14 11:48:35,665 - train: [ INFO] - Test: [ 500/507] Time: 0.033 (0.034) Loss: 7.3609 (7.3926) cLoss: 0.0000 (0.0000) Acc@1: 0.0000 ( 0.0624)Acc@5: 0.0000 ( 0.3119)
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2023-08-14 11:48:35,900 - train: [ INFO] - Test: [ 507/507] Time: 0.031 (0.034) Loss: 7.3386 (7.3926) cLoss: 0.0000 (0.0000) Acc@1: 0.0000 ( 0.0616)Acc@5: 0.0000 ( 0.3081)
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2023-08-14 11:48:36,025 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-0.pth.tar', 0.061614294516327786)
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2023-08-14 11:48:36,628 - train: [ INFO] - Train: 1 [ 0/1521 ( 0%)] Loss: 7.896760 (7.8968) Acc@1: 0.0000 ( 0.0000) Acc@5: 0.0000 ( 0.0000) Time: 0.603s, 26.52/s LR: 3.751e-03 P_Replacement: 1.5625000000000004e-05
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2023-08-14 11:50:16,818 - train: [ INFO] - Train: 1 [ 500/1521 ( 33%)] Loss: 7.663272 (7.7239) Acc@1: 0.0000 ( 0.0998) Acc@5: 0.0000 ( 0.4616) Time: 0.201s, 79.53/s LR: 3.751e-03 P_Replacement: 3.66548396853058e-05
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2023-08-14 11:51:57,221 - train: [ INFO] - Train: 1 [1000/1521 ( 66%)] Loss: 6.900778 (7.4381) Acc@1: 0.0000 ( 0.4558) Acc@5: 0.0000 ( 2.0042) Time: 0.201s, 79.61/s LR: 3.751e-03 P_Replacement: 7.11460709118185e-05
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2023-08-14 11:53:40,489 - train: [ INFO] - Train: 1 [1500/1521 ( 99%)] Loss: 6.229725 (7.0529) Acc@1: 0.0000 ( 1.5365) Acc@5: 12.5000 ( 5.0341) Time: 0.203s, 78.88/s LR: 3.751e-03 P_Replacement: 0.0001224290725863187
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2023-08-14 11:53:44,330 - train: [ INFO] - Train: 1 [1520/1521 (100%)] Loss: 4.593245 (7.0361) Acc@1: 25.0000 ( 1.6149) Acc@5: 43.7500 ( 5.1981) Time: 0.203s, 78.94/s LR: 3.751e-03 P_Replacement: 0.00012487676635787435
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2023-08-14 11:53:44,642 - train: [ INFO] - Test: [ 0/507] Time: 0.237 (0.237) Loss: 3.9548 (3.9548) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (31.2500)Acc@5: 56.2500 (56.2500)
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2023-08-14 11:54:01,738 - train: [ INFO] - Test: [ 500/507] Time: 0.034 (0.035) Loss: 4.8824 (5.1874) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 ( 9.5933)Acc@5: 18.7500 (23.6277)
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2023-08-14 11:54:02,003 - train: [ INFO] - Test: [ 507/507] Time: 0.038 (0.035) Loss: 3.3671 (5.1758) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 ( 9.6981)Acc@5: 66.6667 (23.8324)
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2023-08-14 11:54:02,088 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-1.pth.tar', 9.698089958750312)
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2023-08-14 11:54:02,777 - train: [ INFO] - Train: 2 [ 0/1521 ( 0%)] Loss: 4.335170 (4.3352) Acc@1: 12.5000 (12.5000) Acc@5: 56.2500 (56.2500) Time: 0.687s, 23.28/s LR: 7.501e-03 P_Replacement: 0.00012500000000000003
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2023-08-14 11:55:42,798 - train: [ INFO] - Train: 2 [ 500/1521 ( 33%)] Loss: 5.797427 (4.6164) Acc@1: 0.0000 (16.6916) Acc@5: 12.5000 (38.0739) Time: 0.201s, 79.60/s LR: 7.501e-03 P_Replacement: 0.00019732315665340656
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2023-08-14 11:57:23,148 - train: [ INFO] - Train: 2 [1000/1521 ( 66%)] Loss: 3.331219 (4.2170) Acc@1: 18.7500 (21.5972) Acc@5: 68.7500 (45.7105) Time: 0.201s, 79.66/s LR: 7.501e-03 P_Replacement: 0.0002932387174824464
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2023-08-14 11:59:07,331 - train: [ INFO] - Train: 2 [1500/1521 ( 99%)] Loss: 2.905689 (3.9653) Acc@1: 43.7500 (25.0541) Acc@5: 68.7500 (50.4497) Time: 0.203s, 78.68/s LR: 7.501e-03 P_Replacement: 0.00041607706139390016
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2023-08-14 11:59:11,432 - train: [ INFO] - Train: 2 [1520/1521 (100%)] Loss: 2.999332 (3.9587) Acc@1: 37.5000 (25.1520) Acc@5: 75.0000 (50.5794) Time: 0.203s, 78.67/s LR: 7.501e-03 P_Replacement: 0.0004215976939177299
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2023-08-14 11:59:11,816 - train: [ INFO] - Test: [ 0/507] Time: 0.255 (0.255) Loss: 2.6828 (2.6828) cLoss: 0.0000 (0.0000) Acc@1: 25.0000 (25.0000)Acc@5: 75.0000 (75.0000)
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2023-08-14 11:59:28,951 - train: [ INFO] - Test: [ 500/507] Time: 0.028 (0.035) Loss: 3.7336 (3.1463) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (31.9361)Acc@5: 37.5000 (60.4042)
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2023-08-14 11:59:29,196 - train: [ INFO] - Test: [ 507/507] Time: 0.027 (0.035) Loss: 3.2717 (3.1470) cLoss: 0.0000 (0.0000) Acc@1: 0.0000 (31.8299)Acc@5: 33.3333 (60.3327)
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2023-08-14 11:59:29,280 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 61 |
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-2.pth.tar', 31.829944547134936)
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2023-08-14 11:59:30,010 - train: [ INFO] - Train: 3 [ 0/1521 ( 0%)] Loss: 1.935986 (1.9360) Acc@1: 56.2500 (56.2500) Acc@5: 81.2500 (81.2500) Time: 0.729s, 21.95/s LR: 1.125e-02 P_Replacement: 0.00042187499999999994
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2023-08-14 12:01:11,550 - train: [ INFO] - Train: 3 [ 500/1521 ( 33%)] Loss: 1.746115 (2.7375) Acc@1: 56.2500 (40.9930) Acc@5: 87.5000 (72.1307) Time: 0.204s, 78.39/s LR: 1.125e-02 P_Replacement: 0.0005763100140554324
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2023-08-14 12:02:52,420 - train: [ INFO] - Train: 3 [1000/1521 ( 66%)] Loss: 3.002455 (2.6919) Acc@1: 31.2500 (41.7333) Acc@5: 75.0000 (72.9833) Time: 0.203s, 78.85/s LR: 1.125e-02 P_Replacement: 0.0007644684449209242
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2023-08-14 12:04:34,518 - train: [ INFO] - Train: 3 [1500/1521 ( 99%)] Loss: 2.484884 (2.6461) Acc@1: 50.0000 (42.7548) Acc@5: 68.7500 (73.5426) Time: 0.203s, 78.68/s LR: 1.125e-02 P_Replacement: 0.0009896806715032566
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2023-08-14 12:04:38,467 - train: [ INFO] - Train: 3 [1520/1521 (100%)] Loss: 2.144819 (2.6446) Acc@1: 50.0000 (42.7556) Acc@5: 81.2500 (73.5741) Time: 0.203s, 78.71/s LR: 1.125e-02 P_Replacement: 0.0009995069843967178
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2023-08-14 12:04:38,827 - train: [ INFO] - Test: [ 0/507] Time: 0.246 (0.246) Loss: 1.5950 (1.5950) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (50.0000)Acc@5: 93.7500 (93.7500)
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2023-08-14 12:04:55,827 - train: [ INFO] - Test: [ 500/507] Time: 0.036 (0.034) Loss: 3.2419 (2.7664) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (38.9845)Acc@5: 75.0000 (68.7625)
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2023-08-14 12:04:56,047 - train: [ INFO] - Test: [ 507/507] Time: 0.042 (0.034) Loss: 3.2683 (2.7693) cLoss: 0.0000 (0.0000) Acc@1: 33.3333 (38.8540)Acc@5: 33.3333 (68.6630)
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+
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2023-08-14 12:04:56,170 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 80 |
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-3.pth.tar', 38.853974122936464)
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2023-08-14 12:04:56,819 - train: [ INFO] - Train: 4 [ 0/1521 ( 0%)] Loss: 2.008343 (2.0083) Acc@1: 68.7500 (68.7500) Acc@5: 75.0000 (75.0000) Time: 0.648s, 24.70/s LR: 1.500e-02 P_Replacement: 0.0010000000000000002
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2023-08-14 12:06:39,338 - train: [ INFO] - Train: 4 [ 500/1521 ( 33%)] Loss: 2.464504 (2.0911) Acc@1: 37.5000 (53.3433) Acc@5: 81.2500 (82.1981) Time: 0.206s, 77.70/s LR: 1.500e-02 P_Replacement: 0.001267365411891383
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2023-08-14 12:08:19,426 - train: [ INFO] - Train: 4 [1000/1521 ( 66%)] Loss: 1.898379 (2.1240) Acc@1: 56.2500 (52.6661) Acc@5: 93.7500 (81.5934) Time: 0.203s, 78.80/s LR: 1.500e-02 P_Replacement: 0.0015785852532272525
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2023-08-14 12:10:02,064 - train: [ INFO] - Train: 4 [1500/1521 ( 99%)] Loss: 1.055679 (2.1477) Acc@1: 81.2500 (52.0112) Acc@5: 100.0000 (81.2167) Time: 0.204s, 78.52/s LR: 1.500e-02 P_Replacement: 0.0019369899029143887
|
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2023-08-14 12:10:06,455 - train: [ INFO] - Train: 4 [1520/1521 (100%)] Loss: 2.451564 (2.1501) Acc@1: 50.0000 (51.9806) Acc@5: 75.0000 (81.1678) Time: 0.204s, 78.44/s LR: 1.500e-02 P_Replacement: 0.0019523546377948377
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+
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2023-08-14 12:10:06,802 - train: [ INFO] - Test: [ 0/507] Time: 0.246 (0.246) Loss: 2.6549 (2.6549) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (18.7500)Acc@5: 68.7500 (68.7500)
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2023-08-14 12:10:23,985 - train: [ INFO] - Test: [ 500/507] Time: 0.030 (0.035) Loss: 4.2170 (2.5534) cLoss: 0.0000 (0.0000) Acc@1: 25.0000 (42.1657)Acc@5: 37.5000 (71.7814)
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2023-08-14 12:10:24,204 - train: [ INFO] - Test: [ 507/507] Time: 0.025 (0.035) Loss: 1.1665 (2.5527) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (42.0579)Acc@5: 100.0000 (71.7437)
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2023-08-14 12:10:24,326 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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| 99 |
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-4.pth.tar', 42.05791743872567)
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2023-08-14 12:10:24,987 - train: [ INFO] - Train: 5 [ 0/1521 ( 0%)] Loss: 0.961572 (0.9616) Acc@1: 81.2500 (81.2500) Acc@5: 93.7500 (93.7500) Time: 0.660s, 24.23/s LR: 1.875e-02 P_Replacement: 0.001953125
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2023-08-14 12:12:08,426 - train: [ INFO] - Train: 5 [ 500/1521 ( 33%)] Loss: 2.110868 (1.8289) Acc@1: 50.0000 (56.8363) Acc@5: 81.2500 (86.8139) Time: 0.208s, 77.01/s LR: 1.875e-02 P_Replacement: 0.0023642393501612595
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+
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2023-08-14 12:13:48,466 - train: [ INFO] - Train: 5 [1000/1521 ( 66%)] Loss: 1.570213 (1.8983) Acc@1: 62.5000 (55.7567) Acc@5: 100.0000 (85.4833) Time: 0.204s, 78.46/s LR: 1.875e-02 P_Replacement: 0.0028293391424014315
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2023-08-14 12:15:29,799 - train: [ INFO] - Train: 5 [1500/1521 ( 99%)] Loss: 2.172712 (1.9568) Acc@1: 56.2500 (54.7094) Acc@5: 75.0000 (84.5145) Time: 0.204s, 78.62/s LR: 1.875e-02 P_Replacement: 0.0033517547556272944
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+
2023-08-14 12:15:34,012 - train: [ INFO] - Train: 5 [1520/1521 (100%)] Loss: 1.869580 (1.9617) Acc@1: 43.7500 (54.6392) Acc@5: 87.5000 (84.4469) Time: 0.204s, 78.59/s LR: 1.875e-02 P_Replacement: 0.0033738906541120905
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2023-08-14 12:15:34,339 - train: [ INFO] - Test: [ 0/507] Time: 0.236 (0.236) Loss: 1.8877 (1.8877) cLoss: 0.0000 (0.0000) Acc@1: 37.5000 (37.5000)Acc@5: 100.0000 (100.0000)
|
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2023-08-14 12:15:52,028 - train: [ INFO] - Test: [ 500/507] Time: 0.034 (0.036) Loss: 3.4816 (2.4997) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (43.4132)Acc@5: 31.2500 (72.6921)
|
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2023-08-14 12:15:52,268 - train: [ INFO] - Test: [ 507/507] Time: 0.030 (0.036) Loss: 1.6326 (2.5011) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (43.3395)Acc@5: 100.0000 (72.6309)
|
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2023-08-14 12:15:52,391 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 118 |
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-5.pth.tar', 43.33949476466528)
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2023-08-14 12:15:52,983 - train: [ INFO] - Train: 6 [ 0/1521 ( 0%)] Loss: 1.575486 (1.5755) Acc@1: 62.5000 (62.5000) Acc@5: 93.7500 (93.7500) Time: 0.590s, 27.12/s LR: 1.875e-02 P_Replacement: 0.0033749999999999995
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2023-08-14 12:17:35,683 - train: [ INFO] - Train: 6 [ 500/1521 ( 33%)] Loss: 1.608957 (1.5245) Acc@1: 68.7500 (64.1342) Acc@5: 87.5000 (90.4566) Time: 0.206s, 77.61/s LR: 1.875e-02 P_Replacement: 0.00396068182886506
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2023-08-14 12:19:16,109 - train: [ INFO] - Train: 6 [1000/1521 ( 66%)] Loss: 2.083491 (1.6413) Acc@1: 62.5000 (61.2263) Acc@5: 81.2500 (88.9673) Time: 0.204s, 78.62/s LR: 1.875e-02 P_Replacement: 0.004610480112443459
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2023-08-14 12:20:59,094 - train: [ INFO] - Train: 6 [1500/1521 ( 99%)] Loss: 1.609643 (1.6989) Acc@1: 56.2500 (59.5020) Acc@5: 87.5000 (87.8914) Time: 0.204s, 78.31/s LR: 1.875e-02 P_Replacement: 0.005327725229641978
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2023-08-14 12:21:03,133 - train: [ INFO] - Train: 6 [1520/1521 (100%)] Loss: 1.699763 (1.7024) Acc@1: 56.2500 (59.4264) Acc@5: 81.2500 (87.8328) Time: 0.204s, 78.32/s LR: 1.875e-02 P_Replacement: 0.005357865033348474
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2023-08-14 12:21:03,576 - train: [ INFO] - Test: [ 0/507] Time: 0.257 (0.257) Loss: 2.6065 (2.6065) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (12.5000)Acc@5: 75.0000 (75.0000)
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2023-08-14 12:21:20,464 - train: [ INFO] - Test: [ 500/507] Time: 0.032 (0.034) Loss: 4.8439 (2.5298) cLoss: 0.0000 (0.0000) Acc@1: 6.2500 (43.2510)Acc@5: 25.0000 (73.0040)
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2023-08-14 12:21:20,674 - train: [ INFO] - Test: [ 507/507] Time: 0.031 (0.034) Loss: 0.1407 (2.5378) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (42.9945)Acc@5: 100.0000 (72.8651)
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2023-08-14 12:21:21,383 - train: [ INFO] - Train: 7 [ 0/1521 ( 0%)] Loss: 1.932802 (1.9328) Acc@1: 43.7500 (43.7500) Acc@5: 75.0000 (75.0000) Time: 0.599s, 26.73/s LR: 1.875e-02 P_Replacement: 0.005359374999999999
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2023-08-14 12:23:04,304 - train: [ INFO] - Train: 7 [ 500/1521 ( 33%)] Loss: 1.552966 (1.3300) Acc@1: 62.5000 (67.5274) Acc@5: 87.5000 (92.5773) Time: 0.207s, 77.44/s LR: 1.875e-02 P_Replacement: 0.006150442848002786
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2023-08-14 12:24:45,302 - train: [ INFO] - Train: 7 [1000/1521 ( 66%)] Loss: 1.452065 (1.4269) Acc@1: 75.0000 (65.0599) Acc@5: 93.7500 (91.3337) Time: 0.204s, 78.32/s LR: 1.875e-02 P_Replacement: 0.007015758163353337
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2023-08-14 12:26:27,556 - train: [ INFO] - Train: 7 [1500/1521 ( 99%)] Loss: 1.213774 (1.5129) Acc@1: 68.7500 (63.0538) Acc@5: 100.0000 (90.0441) Time: 0.204s, 78.29/s LR: 1.875e-02 P_Replacement: 0.007958651324958436
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2023-08-14 12:26:31,705 - train: [ INFO] - Train: 7 [1520/1521 (100%)] Loss: 1.267217 (1.5162) Acc@1: 62.5000 (62.9438) Acc@5: 100.0000 (90.0066) Time: 0.204s, 78.28/s LR: 1.875e-02 P_Replacement: 0.00799802777550399
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2023-08-14 12:26:32,072 - train: [ INFO] - Test: [ 0/507] Time: 0.254 (0.254) Loss: 2.3313 (2.3313) cLoss: 0.0000 (0.0000) Acc@1: 37.5000 (37.5000)Acc@5: 81.2500 (81.2500)
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2023-08-14 12:26:49,605 - train: [ INFO] - Test: [ 500/507] Time: 0.034 (0.036) Loss: 4.1400 (2.3951) cLoss: 0.0000 (0.0000) Acc@1: 6.2500 (46.1452)Acc@5: 43.7500 (75.0374)
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2023-08-14 12:26:49,834 - train: [ INFO] - Test: [ 507/507] Time: 0.040 (0.035) Loss: 0.3358 (2.3941) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (46.0505)Acc@5: 100.0000 (75.0832)
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2023-08-14 12:26:49,929 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-7.pth.tar', 46.05052372150339)
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2023-08-14 12:26:50,537 - train: [ INFO] - Train: 8 [ 0/1521 ( 0%)] Loss: 0.633810 (0.6338) Acc@1: 87.5000 (87.5000) Acc@5: 100.0000 (100.0000) Time: 0.607s, 26.36/s LR: 1.875e-02 P_Replacement: 0.008000000000000002
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2023-08-14 12:28:32,352 - train: [ INFO] - Train: 8 [ 500/1521 ( 33%)] Loss: 1.050238 (1.2156) Acc@1: 56.2500 (70.2720) Acc@5: 100.0000 (93.6751) Time: 0.204s, 78.27/s LR: 1.875e-02 P_Replacement: 0.009027272407574435
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2023-08-14 12:30:13,355 - train: [ INFO] - Train: 8 [1000/1521 ( 66%)] Loss: 1.366530 (1.3296) Acc@1: 68.7500 (67.2890) Acc@5: 93.7500 (92.2577) Time: 0.203s, 78.74/s LR: 1.875e-02 P_Replacement: 0.010138923295131065
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2023-08-14 12:31:54,971 - train: [ INFO] - Train: 8 [1500/1521 ( 99%)] Loss: 1.877859 (1.4282) Acc@1: 50.0000 (64.8484) Acc@5: 81.2500 (91.0185) Time: 0.203s, 78.73/s LR: 1.875e-02 P_Replacement: 0.011338283041576667
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2023-08-14 12:31:58,892 - train: [ INFO] - Train: 8 [1520/1521 (100%)] Loss: 1.220402 (1.4287) Acc@1: 75.0000 (64.8751) Acc@5: 93.7500 (90.9887) Time: 0.203s, 78.77/s LR: 1.875e-02 P_Replacement: 0.011388128880578637
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2023-08-14 12:31:59,235 - train: [ INFO] - Test: [ 0/507] Time: 0.246 (0.246) Loss: 2.3613 (2.3613) cLoss: 0.0000 (0.0000) Acc@1: 43.7500 (43.7500)Acc@5: 81.2500 (81.2500)
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2023-08-14 12:32:16,355 - train: [ INFO] - Test: [ 500/507] Time: 0.044 (0.035) Loss: 3.3589 (2.4161) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (45.8458)Acc@5: 68.7500 (75.1996)
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2023-08-14 12:32:16,579 - train: [ INFO] - Test: [ 507/507] Time: 0.033 (0.035) Loss: 1.3578 (2.4187) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (45.7548)Acc@5: 100.0000 (75.1325)
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2023-08-14 12:32:17,318 - train: [ INFO] - Train: 9 [ 0/1521 ( 0%)] Loss: 1.189154 (1.1892) Acc@1: 87.5000 (87.5000) Acc@5: 87.5000 (87.5000) Time: 0.616s, 25.96/s LR: 1.875e-02 P_Replacement: 0.011390625000000001
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2023-08-14 12:34:00,141 - train: [ INFO] - Train: 9 [ 500/1521 ( 33%)] Loss: 1.610432 (1.1620) Acc@1: 62.5000 (71.8812) Acc@5: 81.2500 (94.2740) Time: 0.206s, 77.50/s LR: 1.875e-02 P_Replacement: 0.012684920507580015
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2023-08-14 12:35:40,188 - train: [ INFO] - Train: 9 [1000/1521 ( 66%)] Loss: 1.290100 (1.2613) Acc@1: 68.7500 (69.4181) Acc@5: 87.5000 (93.0507) Time: 0.203s, 78.71/s LR: 1.875e-02 P_Replacement: 0.014073725507776642
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2023-08-14 12:37:22,449 - train: [ INFO] - Train: 9 [1500/1521 ( 99%)] Loss: 1.956856 (1.3590) Acc@1: 50.0000 (66.6472) Acc@5: 68.7500 (91.7722) Time: 0.204s, 78.55/s LR: 1.875e-02 P_Replacement: 0.015560370379496672
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2023-08-14 12:37:26,522 - train: [ INFO] - Train: 9 [1520/1521 (100%)] Loss: 1.696777 (1.3633) Acc@1: 50.0000 (66.5352) Acc@5: 87.5000 (91.7160) Time: 0.204s, 78.55/s LR: 1.875e-02 P_Replacement: 0.015621918348572423
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2023-08-14 12:37:26,881 - train: [ INFO] - Test: [ 0/507] Time: 0.241 (0.241) Loss: 1.9267 (1.9267) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (50.0000)Acc@5: 81.2500 (81.2500)
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2023-08-14 12:37:44,197 - train: [ INFO] - Test: [ 500/507] Time: 0.035 (0.035) Loss: 3.2079 (2.3586) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (46.9561)Acc@5: 43.7500 (75.4616)
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2023-08-14 12:37:44,427 - train: [ INFO] - Test: [ 507/507] Time: 0.035 (0.035) Loss: 0.6506 (2.3565) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (46.8515)Acc@5: 100.0000 (75.5268)
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2023-08-14 12:37:44,553 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-9.pth.tar', 46.85150955021565)
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2023-08-14 12:37:45,153 - train: [ INFO] - Train: 10 [ 0/1521 ( 0%)] Loss: 0.963205 (0.9632) Acc@1: 87.5000 (87.5000) Acc@5: 100.0000 (100.0000) Time: 0.599s, 26.71/s LR: 1.875e-02 P_Replacement: 0.015625
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2023-08-14 12:39:28,750 - train: [ INFO] - Train: 10 [ 500/1521 ( 33%)] Loss: 1.172784 (1.0835) Acc@1: 75.0000 (73.5903) Acc@5: 93.7500 (94.7730) Time: 0.208s, 76.94/s LR: 1.875e-02 P_Replacement: 0.017217137148019514
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2023-08-14 12:41:09,101 - train: [ INFO] - Train: 10 [1000/1521 ( 66%)] Loss: 1.734934 (1.2127) Acc@1: 62.5000 (70.1236) Acc@5: 87.5000 (93.6251) Time: 0.204s, 78.30/s LR: 1.875e-02 P_Replacement: 0.018913914801290076
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2023-08-14 12:42:50,722 - train: [ INFO] - Train: 10 [1500/1521 ( 99%)] Loss: 2.104200 (1.3038) Acc@1: 50.0000 (67.7590) Acc@5: 75.0000 (92.5924) Time: 0.204s, 78.45/s LR: 1.875e-02 P_Replacement: 0.02071866333871846
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2023-08-14 12:42:54,534 - train: [ INFO] - Train: 10 [1520/1521 (100%)] Loss: 0.924179 (1.3066) Acc@1: 68.7500 (67.6775) Acc@5: 100.0000 (92.5666) Time: 0.204s, 78.51/s LR: 1.875e-02 P_Replacement: 0.020793146179485328
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2023-08-14 12:42:54,858 - train: [ INFO] - Test: [ 0/507] Time: 0.231 (0.231) Loss: 3.0118 (3.0118) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (18.7500)Acc@5: 62.5000 (62.5000)
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2023-08-14 12:43:12,306 - train: [ INFO] - Test: [ 500/507] Time: 0.039 (0.035) Loss: 3.5053 (2.2704) cLoss: 0.0000 (0.0000) Acc@1: 25.0000 (48.5903)Acc@5: 37.5000 (76.6841)
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2023-08-14 12:43:12,542 - train: [ INFO] - Test: [ 507/507] Time: 0.038 (0.035) Loss: 0.2452 (2.2711) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (48.4288)Acc@5: 100.0000 (76.5989)
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2023-08-14 12:43:12,652 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-10.pth.tar', 48.42883548983364)
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2023-08-14 12:43:13,284 - train: [ INFO] - Train: 11 [ 0/1521 ( 0%)] Loss: 1.098006 (1.0980) Acc@1: 62.5000 (62.5000) Acc@5: 100.0000 (100.0000) Time: 0.631s, 25.37/s LR: 1.875e-02 P_Replacement: 0.020796875000000006
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2023-08-14 12:44:57,615 - train: [ INFO] - Train: 11 [ 500/1521 ( 33%)] Loss: 0.996933 (1.0087) Acc@1: 81.2500 (75.8483) Acc@5: 93.7500 (96.0953) Time: 0.209s, 76.38/s LR: 1.875e-02 P_Replacement: 0.02271767232889295
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2023-08-14 12:46:38,069 - train: [ INFO] - Train: 11 [1000/1521 ( 66%)] Loss: 1.898590 (1.1415) Acc@1: 43.7500 (71.8781) Acc@5: 81.2500 (94.5242) Time: 0.205s, 77.97/s LR: 1.875e-02 P_Replacement: 0.024753241175671348
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2023-08-14 12:48:21,277 - train: [ INFO] - Train: 11 [1500/1521 ( 99%)] Loss: 1.259910 (1.2562) Acc@1: 75.0000 (68.5918) Acc@5: 87.5000 (93.1046) Time: 0.206s, 77.82/s LR: 1.875e-02 P_Replacement: 0.02690691191924201
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2023-08-14 12:48:25,140 - train: [ INFO] - Train: 11 [1520/1521 (100%)] Loss: 1.396467 (1.2585) Acc@1: 62.5000 (68.5528) Acc@5: 87.5000 (93.0638) Time: 0.205s, 77.88/s LR: 1.875e-02 P_Replacement: 0.026995562373317378
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2023-08-14 12:48:25,502 - train: [ INFO] - Test: [ 0/507] Time: 0.242 (0.242) Loss: 1.2533 (1.2533) cLoss: 0.0000 (0.0000) Acc@1: 56.2500 (56.2500)Acc@5: 93.7500 (93.7500)
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2023-08-14 12:48:43,021 - train: [ INFO] - Test: [ 500/507] Time: 0.029 (0.035) Loss: 3.2772 (2.2984) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (48.2036)Acc@5: 62.5000 (76.7091)
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2023-08-14 12:48:43,248 - train: [ INFO] - Test: [ 507/507] Time: 0.027 (0.035) Loss: 2.5770 (2.3001) cLoss: 0.0000 (0.0000) Acc@1: 33.3333 (48.0715)Acc@5: 66.6667 (76.6728)
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2023-08-14 12:48:43,958 - train: [ INFO] - Train: 12 [ 0/1521 ( 0%)] Loss: 1.067542 (1.0675) Acc@1: 75.0000 (75.0000) Acc@5: 87.5000 (87.5000) Time: 0.625s, 25.58/s LR: 1.875e-02 P_Replacement: 0.026999999999999996
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2023-08-14 12:50:27,514 - train: [ INFO] - Train: 12 [ 500/1521 ( 33%)] Loss: 0.817842 (0.9942) Acc@1: 81.2500 (75.6737) Acc@5: 100.0000 (95.7086) Time: 0.208s, 76.95/s LR: 1.875e-02 P_Replacement: 0.02928027605020029
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2023-08-14 12:52:06,683 - train: [ INFO] - Train: 12 [1000/1521 ( 66%)] Loss: 1.770104 (1.1185) Acc@1: 56.2500 (72.2340) Acc@5: 81.2500 (94.5929) Time: 0.203s, 78.77/s LR: 1.875e-02 P_Replacement: 0.03168545463092048
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2023-08-14 12:53:39,550 - train: [ INFO] - Train: 12 [1500/1521 ( 99%)] Loss: 1.113648 (1.2345) Acc@1: 68.7500 (69.0998) Acc@5: 93.7500 (93.2712) Time: 0.197s, 81.08/s LR: 1.875e-02 P_Replacement: 0.03421886612106735
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2023-08-14 12:53:42,412 - train: [ INFO] - Train: 12 [1520/1521 (100%)] Loss: 1.165117 (1.2410) Acc@1: 68.7500 (68.9431) Acc@5: 93.7500 (93.2035) Time: 0.197s, 81.37/s LR: 1.875e-02 P_Replacement: 0.03432291693006856
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2023-08-14 12:53:42,838 - train: [ INFO] - Test: [ 0/507] Time: 0.243 (0.243) Loss: 1.9666 (1.9666) cLoss: 0.0000 (0.0000) Acc@1: 43.7500 (43.7500)Acc@5: 93.7500 (93.7500)
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2023-08-14 12:53:58,386 - train: [ INFO] - Test: [ 500/507] Time: 0.027 (0.032) Loss: 3.9695 (2.3799) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (46.9810)Acc@5: 56.2500 (75.0250)
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2023-08-14 12:53:58,601 - train: [ INFO] - Test: [ 507/507] Time: 0.036 (0.032) Loss: 1.7663 (2.3774) cLoss: 0.0000 (0.0000) Acc@1: 33.3333 (46.8638)Acc@5: 100.0000 (75.0955)
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2023-08-14 12:53:59,246 - train: [ INFO] - Train: 13 [ 0/1521 ( 0%)] Loss: 1.401296 (1.4013) Acc@1: 56.2500 (56.2500) Acc@5: 100.0000 (100.0000) Time: 0.527s, 30.39/s LR: 1.875e-02 P_Replacement: 0.034328125
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2023-08-14 12:55:05,735 - train: [ INFO] - Train: 13 [ 500/1521 ( 33%)] Loss: 1.031133 (0.9654) Acc@1: 68.7500 (76.0354) Acc@5: 93.7500 (96.5319) Time: 0.134s, 119.62/s LR: 1.875e-02 P_Replacement: 0.03699869831194157
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2023-08-14 12:56:11,743 - train: [ INFO] - Train: 13 [1000/1521 ( 66%)] Loss: 1.425692 (1.0942) Acc@1: 62.5000 (72.8022) Acc@5: 93.7500 (95.2298) Time: 0.133s, 120.41/s LR: 1.875e-02 P_Replacement: 0.039804305167037465
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2023-08-14 12:57:17,398 - train: [ INFO] - Train: 13 [1500/1521 ( 99%)] Loss: 1.899512 (1.1984) Acc@1: 50.0000 (70.0824) Acc@5: 81.2500 (93.9124) Time: 0.132s, 120.89/s LR: 1.875e-02 P_Replacement: 0.04274827594419447
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2023-08-14 12:57:20,170 - train: [ INFO] - Train: 13 [1520/1521 (100%)] Loss: 1.295938 (1.2034) Acc@1: 81.2500 (69.9704) Acc@5: 93.7500 (93.8486) Time: 0.132s, 120.81/s LR: 1.875e-02 P_Replacement: 0.04286895984973886
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2023-08-14 12:57:20,526 - train: [ INFO] - Test: [ 0/507] Time: 0.242 (0.242) Loss: 1.9451 (1.9451) cLoss: 0.0000 (0.0000) Acc@1: 43.7500 (43.7500)Acc@5: 93.7500 (93.7500)
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2023-08-14 12:57:35,333 - train: [ INFO] - Test: [ 500/507] Time: 0.027 (0.030) Loss: 4.3586 (2.3630) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (47.4925)Acc@5: 56.2500 (76.0230)
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2023-08-14 12:57:35,560 - train: [ INFO] - Test: [ 507/507] Time: 0.027 (0.030) Loss: 1.5225 (2.3585) cLoss: 0.0000 (0.0000) Acc@1: 33.3333 (47.4430)Acc@5: 100.0000 (76.0567)
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2023-08-14 12:57:36,179 - train: [ INFO] - Train: 14 [ 0/1521 ( 0%)] Loss: 0.871121 (0.8711) Acc@1: 68.7500 (68.7500) Acc@5: 100.0000 (100.0000) Time: 0.521s, 30.69/s LR: 1.875e-02 P_Replacement: 0.04287499999999999
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2023-08-14 12:58:41,675 - train: [ INFO] - Train: 14 [ 500/1521 ( 33%)] Loss: 1.082036 (0.9845) Acc@1: 75.0000 (75.6487) Acc@5: 100.0000 (96.2700) Time: 0.132s, 121.43/s LR: 1.875e-02 P_Replacement: 0.04596668911411676
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2023-08-14 12:59:47,662 - train: [ INFO] - Train: 14 [1000/1521 ( 66%)] Loss: 0.907562 (1.0966) Acc@1: 68.7500 (72.6898) Acc@5: 100.0000 (95.1673) Time: 0.132s, 121.34/s LR: 1.875e-02 P_Replacement: 0.04920354278402229
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2023-08-14 13:00:52,825 - train: [ INFO] - Train: 14 [1500/1521 ( 99%)] Loss: 1.811885 (1.1844) Acc@1: 56.2500 (70.3115) Acc@5: 68.7500 (94.0581) Time: 0.131s, 121.81/s LR: 1.875e-02 P_Replacement: 0.052588891388623334
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2023-08-14 13:00:55,459 - train: [ INFO] - Train: 14 [1520/1521 (100%)] Loss: 1.066935 (1.1877) Acc@1: 68.7500 (70.2252) Acc@5: 100.0000 (93.9883) Time: 0.131s, 121.81/s LR: 1.875e-02 P_Replacement: 0.05272744113232831
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2023-08-14 13:00:55,819 - train: [ INFO] - Test: [ 0/507] Time: 0.247 (0.247) Loss: 1.9286 (1.9286) cLoss: 0.0000 (0.0000) Acc@1: 62.5000 (62.5000)Acc@5: 87.5000 (87.5000)
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2023-08-14 13:01:11,926 - train: [ INFO] - Test: [ 500/507] Time: 0.028 (0.033) Loss: 2.4179 (2.3131) cLoss: 0.0000 (0.0000) Acc@1: 43.7500 (47.9291)Acc@5: 81.2500 (76.6342)
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2023-08-14 13:01:12,145 - train: [ INFO] - Test: [ 507/507] Time: 0.026 (0.033) Loss: 0.7476 (2.3149) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (47.8250)Acc@5: 100.0000 (76.5866)
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2023-08-14 13:01:12,750 - train: [ INFO] - Train: 15 [ 0/1521 ( 0%)] Loss: 0.900675 (0.9007) Acc@1: 75.0000 (75.0000) Acc@5: 93.7500 (93.7500) Time: 0.515s, 31.06/s LR: 1.875e-02 P_Replacement: 0.052734375
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2023-08-14 13:02:18,818 - train: [ INFO] - Train: 15 [ 500/1521 ( 33%)] Loss: 1.141933 (0.9439) Acc@1: 62.5000 (77.1332) Acc@5: 100.0000 (96.6068) Time: 0.133s, 120.40/s LR: 1.875e-02 P_Replacement: 0.056277998456725896
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2023-08-14 13:03:24,574 - train: [ INFO] - Train: 15 [1000/1521 ( 66%)] Loss: 1.318015 (1.0651) Acc@1: 68.7500 (73.8262) Acc@5: 87.5000 (95.4296) Time: 0.132s, 121.03/s LR: 1.875e-02 P_Replacement: 0.059976917481874975
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2023-08-14 13:04:30,877 - train: [ INFO] - Train: 15 [1500/1521 ( 99%)] Loss: 1.275249 (1.1708) Acc@1: 68.7500 (70.8944) Acc@5: 93.7500 (94.1539) Time: 0.132s, 120.91/s LR: 1.875e-02 P_Replacement: 0.06383446245435401
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2023-08-14 13:04:33,563 - train: [ INFO] - Train: 15 [1520/1521 (100%)] Loss: 1.269547 (1.1743) Acc@1: 62.5000 (70.8169) Acc@5: 87.5000 (94.1198) Time: 0.132s, 120.89/s LR: 1.875e-02 P_Replacement: 0.06399211077783687
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2023-08-14 13:04:33,910 - train: [ INFO] - Test: [ 0/507] Time: 0.232 (0.232) Loss: 3.3362 (3.3362) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (31.2500)Acc@5: 56.2500 (56.2500)
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2023-08-14 13:04:49,151 - train: [ INFO] - Test: [ 500/507] Time: 0.027 (0.031) Loss: 4.4141 (2.3066) cLoss: 0.0000 (0.0000) Acc@1: 25.0000 (48.3159)Acc@5: 50.0000 (76.5719)
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2023-08-14 13:04:49,353 - train: [ INFO] - Test: [ 507/507] Time: 0.025 (0.031) Loss: 2.0253 (2.3063) cLoss: 0.0000 (0.0000) Acc@1: 33.3333 (48.2070)Acc@5: 66.6667 (76.5866)
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2023-08-14 13:04:50,050 - train: [ INFO] - Train: 16 [ 0/1521 ( 0%)] Loss: 0.894915 (0.8949) Acc@1: 75.0000 (75.0000) Acc@5: 93.7500 (93.7500) Time: 0.597s, 26.80/s LR: 1.875e-02 P_Replacement: 0.06400000000000002
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2023-08-14 13:05:55,994 - train: [ INFO] - Train: 16 [ 500/1521 ( 33%)] Loss: 1.199241 (0.9173) Acc@1: 56.2500 (77.4451) Acc@5: 93.7500 (96.6567) Time: 0.133s, 120.48/s LR: 1.875e-02 P_Replacement: 0.06802637633976896
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2023-08-14 13:07:01,550 - train: [ INFO] - Train: 16 [1000/1521 ( 66%)] Loss: 0.623075 (1.0422) Acc@1: 87.5000 (74.3631) Acc@5: 100.0000 (95.3984) Time: 0.132s, 121.25/s LR: 1.875e-02 P_Replacement: 0.07221817926059548
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2023-08-14 13:08:06,200 - train: [ INFO] - Train: 16 [1500/1521 ( 99%)] Loss: 1.177364 (1.1455) Acc@1: 75.0000 (71.6564) Acc@5: 93.7500 (94.3454) Time: 0.131s, 122.07/s LR: 1.875e-02 P_Replacement: 0.07657873914138642
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2023-08-14 13:08:08,714 - train: [ INFO] - Train: 16 [1520/1521 (100%)] Loss: 2.203560 (1.1518) Acc@1: 43.7500 (71.5031) Acc@5: 81.2500 (94.2801) Time: 0.131s, 122.14/s LR: 1.875e-02 P_Replacement: 0.07675671878626458
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2023-08-14 13:08:09,035 - train: [ INFO] - Test: [ 0/507] Time: 0.237 (0.237) Loss: 2.1793 (2.1793) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (50.0000)Acc@5: 93.7500 (93.7500)
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2023-08-14 13:08:24,531 - train: [ INFO] - Test: [ 500/507] Time: 0.030 (0.031) Loss: 3.5416 (2.3610) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (47.6422)Acc@5: 43.7500 (76.0230)
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2023-08-14 13:08:24,750 - train: [ INFO] - Test: [ 507/507] Time: 0.028 (0.031) Loss: 1.1227 (2.3558) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (47.6648)Acc@5: 100.0000 (76.0690)
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2023-08-14 13:08:25,360 - train: [ INFO] - Train: 17 [ 0/1521 ( 0%)] Loss: 0.432928 (0.4329) Acc@1: 93.7500 (93.7500) Acc@5: 100.0000 (100.0000) Time: 0.516s, 31.01/s LR: 1.875e-02 P_Replacement: 0.07676562499999999
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2023-08-14 13:09:31,120 - train: [ INFO] - Train: 17 [ 500/1521 ( 33%)] Loss: 1.207861 (0.9118) Acc@1: 75.0000 (77.3952) Acc@5: 81.2500 (96.8438) Time: 0.132s, 120.96/s LR: 1.875e-02 P_Replacement: 0.08130557276324592
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2023-08-14 13:10:36,966 - train: [ INFO] - Train: 17 [1000/1521 ( 66%)] Loss: 1.401141 (1.0437) Acc@1: 62.5000 (73.8949) Acc@5: 93.7500 (95.4358) Time: 0.132s, 121.23/s LR: 1.875e-02 P_Replacement: 0.08602107812018388
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2023-08-14 13:11:42,820 - train: [ INFO] - Train: 17 [1500/1521 ( 99%)] Loss: 1.542307 (1.1413) Acc@1: 56.2500 (71.2150) Acc@5: 81.2500 (94.4953) Time: 0.132s, 121.32/s LR: 1.875e-02 P_Replacement: 0.09091547144972065
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2023-08-14 13:11:45,696 - train: [ INFO] - Train: 17 [1520/1521 (100%)] Loss: 1.283226 (1.1438) Acc@1: 75.0000 (71.1662) Acc@5: 93.7500 (94.4773) Time: 0.132s, 121.17/s LR: 1.875e-02 P_Replacement: 0.09111501515761143
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2023-08-14 13:11:46,050 - train: [ INFO] - Test: [ 0/507] Time: 0.239 (0.239) Loss: 1.4668 (1.4668) cLoss: 0.0000 (0.0000) Acc@1: 62.5000 (62.5000)Acc@5: 93.7500 (93.7500)
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2023-08-14 13:12:00,790 - train: [ INFO] - Test: [ 500/507] Time: 0.029 (0.030) Loss: 3.2700 (2.3639) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (48.1662)Acc@5: 50.0000 (75.3743)
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2023-08-14 13:12:00,984 - train: [ INFO] - Test: [ 507/507] Time: 0.025 (0.030) Loss: 1.1666 (2.3605) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (48.0591)Acc@5: 100.0000 (75.5022)
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2023-08-14 13:12:01,679 - train: [ INFO] - Train: 18 [ 0/1521 ( 0%)] Loss: 0.677392 (0.6774) Acc@1: 81.2500 (81.2500) Acc@5: 100.0000 (100.0000) Time: 0.603s, 26.52/s LR: 1.875e-02 P_Replacement: 0.09112500000000001
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2023-08-14 13:13:07,560 - train: [ INFO] - Train: 18 [ 500/1521 ( 33%)] Loss: 0.646759 (0.9051) Acc@1: 81.2500 (78.2186) Acc@5: 100.0000 (96.8812) Time: 0.133s, 120.58/s LR: 1.875e-02 P_Replacement: 0.09620933772715684
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2023-08-14 13:14:13,074 - train: [ INFO] - Train: 18 [1000/1521 ( 66%)] Loss: 1.574759 (1.0362) Acc@1: 50.0000 (74.5255) Acc@5: 93.7500 (95.4171) Time: 0.132s, 121.34/s LR: 1.875e-02 P_Replacement: 0.10147936406064012
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2023-08-14 13:15:20,007 - train: [ INFO] - Train: 18 [1500/1521 ( 99%)] Loss: 1.216304 (1.1345) Acc@1: 62.5000 (71.8937) Acc@5: 87.5000 (94.3246) Time: 0.133s, 120.73/s LR: 1.875e-02 P_Replacement: 0.10693840937935664
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2023-08-14 13:15:22,581 - train: [ INFO] - Train: 18 [1520/1521 (100%)] Loss: 1.173579 (1.1395) Acc@1: 75.0000 (71.7949) Acc@5: 93.7500 (94.2595) Time: 0.132s, 120.78/s LR: 1.875e-02 P_Replacement: 0.10716074989187739
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2023-08-14 13:15:22,913 - train: [ INFO] - Test: [ 0/507] Time: 0.231 (0.231) Loss: 1.4901 (1.4901) cLoss: 0.0000 (0.0000) Acc@1: 56.2500 (56.2500)Acc@5: 100.0000 (100.0000)
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2023-08-14 13:15:38,078 - train: [ INFO] - Test: [ 500/507] Time: 0.045 (0.031) Loss: 3.9914 (2.2802) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (48.4281)Acc@5: 43.7500 (76.9087)
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2023-08-14 13:15:38,300 - train: [ INFO] - Test: [ 507/507] Time: 0.026 (0.031) Loss: 1.6723 (2.2826) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (48.3056)Acc@5: 100.0000 (76.9316)
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2023-08-14 13:15:38,996 - train: [ INFO] - Train: 19 [ 0/1521 ( 0%)] Loss: 0.562769 (0.5628) Acc@1: 81.2500 (81.2500) Acc@5: 100.0000 (100.0000) Time: 0.507s, 31.59/s LR: 1.875e-02 P_Replacement: 0.10717187499999999
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2023-08-14 13:16:45,865 - train: [ INFO] - Train: 19 [ 500/1521 ( 33%)] Loss: 0.865186 (0.8789) Acc@1: 87.5000 (78.3807) Acc@5: 87.5000 (97.1432) Time: 0.134s, 118.98/s LR: 1.875e-02 P_Replacement: 0.11283142123150164
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2023-08-14 13:17:51,121 - train: [ INFO] - Train: 19 [1000/1521 ( 66%)] Loss: 1.543616 (1.0334) Acc@1: 56.2500 (74.3257) Acc@5: 93.7500 (95.5420) Time: 0.132s, 120.77/s LR: 1.875e-02 P_Replacement: 0.11868678708196417
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2023-08-14 13:18:57,275 - train: [ INFO] - Train: 19 [1500/1521 ( 99%)] Loss: 1.405305 (1.1317) Acc@1: 62.5000 (71.6356) Acc@5: 93.7500 (94.4579) Time: 0.132s, 120.82/s LR: 1.875e-02 P_Replacement: 0.12474130293029438
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2023-08-14 13:18:59,967 - train: [ INFO] - Train: 19 [1520/1521 (100%)] Loss: 1.630443 (1.1355) Acc@1: 62.5000 (71.5935) Acc@5: 75.0000 (94.4034) Time: 0.132s, 120.80/s LR: 1.875e-02 P_Replacement: 0.1249876729890625
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2023-08-14 13:19:00,325 - train: [ INFO] - Test: [ 0/507] Time: 0.239 (0.239) Loss: 1.9089 (1.9089) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (31.2500)Acc@5: 87.5000 (87.5000)
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2023-08-14 13:19:15,001 - train: [ INFO] - Test: [ 500/507] Time: 0.026 (0.030) Loss: 3.7638 (2.3827) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (47.8792)Acc@5: 62.5000 (75.2121)
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2023-08-14 13:19:15,181 - train: [ INFO] - Test: [ 507/507] Time: 0.024 (0.030) Loss: 1.3254 (2.3841) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (47.8004)Acc@5: 100.0000 (75.2557)
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2023-08-14 13:19:15,776 - train: [ INFO] - Train: 20 [ 0/1521 ( 0%)] Loss: 0.880063 (0.8801) Acc@1: 81.2500 (81.2500) Acc@5: 93.7500 (93.7500) Time: 0.511s, 31.33/s LR: 1.875e-02 P_Replacement: 0.125
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2023-08-14 13:20:21,631 - train: [ INFO] - Train: 20 [ 500/1521 ( 33%)] Loss: 1.478921 (0.9023) Acc@1: 68.7500 (78.0314) Acc@5: 93.7500 (96.9810) Time: 0.132s, 120.79/s LR: 1.875e-02 P_Replacement: 0.1312655732762804
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2023-08-14 13:21:28,174 - train: [ INFO] - Train: 20 [1000/1521 ( 66%)] Loss: 1.545245 (1.0205) Acc@1: 56.2500 (74.6191) Acc@5: 81.2500 (95.8979) Time: 0.133s, 120.51/s LR: 1.875e-02 P_Replacement: 0.1377370971841561
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2023-08-14 13:22:34,099 - train: [ INFO] - Train: 20 [1500/1521 ( 99%)] Loss: 1.212358 (1.1315) Acc@1: 75.0000 (71.7397) Acc@5: 93.7500 (94.6661) Time: 0.132s, 120.79/s LR: 1.875e-02 P_Replacement: 0.14441790210253394
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2023-08-14 13:22:36,973 - train: [ INFO] - Train: 20 [1520/1521 (100%)] Loss: 1.535182 (1.1362) Acc@1: 62.5000 (71.6428) Acc@5: 93.7500 (94.6129) Time: 0.133s, 120.66/s LR: 1.875e-02 P_Replacement: 0.1446895344491667
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2023-08-14 13:22:37,319 - train: [ INFO] - Test: [ 0/507] Time: 0.233 (0.233) Loss: 1.7975 (1.7975) cLoss: 0.0000 (0.0000) Acc@1: 62.5000 (62.5000)Acc@5: 87.5000 (87.5000)
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2023-08-14 13:22:52,713 - train: [ INFO] - Test: [ 500/507] Time: 0.028 (0.031) Loss: 2.4855 (2.3746) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (47.3678)Acc@5: 68.7500 (75.7610)
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2023-08-14 13:22:52,916 - train: [ INFO] - Test: [ 507/507] Time: 0.025 (0.031) Loss: 0.0815 (2.3805) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (47.2335)Acc@5: 100.0000 (75.6377)
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2023-08-14 13:22:53,515 - train: [ INFO] - Train: 21 [ 0/1521 ( 0%)] Loss: 1.652106 (1.6521) Acc@1: 62.5000 (62.5000) Acc@5: 87.5000 (87.5000) Time: 0.514s, 31.13/s LR: 1.875e-02 P_Replacement: 0.14470312500000002
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2023-08-14 13:23:59,121 - train: [ INFO] - Train: 21 [ 500/1521 ( 33%)] Loss: 1.789188 (0.8924) Acc@1: 50.0000 (78.2435) Acc@5: 87.5000 (97.1307) Time: 0.132s, 121.24/s LR: 1.875e-02 P_Replacement: 0.1516055438614931
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2023-08-14 13:25:04,445 - train: [ INFO] - Train: 21 [1000/1521 ( 66%)] Loss: 0.984178 (1.0129) Acc@1: 81.2500 (74.7378) Acc@5: 100.0000 (96.0290) Time: 0.131s, 121.86/s LR: 1.875e-02 P_Replacement: 0.15872404436721593
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2023-08-14 13:26:09,729 - train: [ INFO] - Train: 21 [1500/1521 ( 99%)] Loss: 0.887379 (1.1206) Acc@1: 62.5000 (71.8521) Acc@5: 100.0000 (94.6494) Time: 0.131s, 122.09/s LR: 1.875e-02 P_Replacement: 0.16606195689607525
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2023-08-14 13:26:12,468 - train: [ INFO] - Train: 21 [1520/1521 (100%)] Loss: 1.808853 (1.1259) Acc@1: 56.2500 (71.7291) Acc@5: 75.0000 (94.5595) Time: 0.131s, 122.01/s LR: 1.875e-02 P_Replacement: 0.1663600842721901
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2023-08-14 13:26:12,815 - train: [ INFO] - Test: [ 0/507] Time: 0.233 (0.233) Loss: 1.4585 (1.4585) cLoss: 0.0000 (0.0000) Acc@1: 62.5000 (62.5000)Acc@5: 93.7500 (93.7500)
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2023-08-14 13:26:27,663 - train: [ INFO] - Test: [ 500/507] Time: 0.028 (0.030) Loss: 4.1813 (2.3273) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (48.7275)Acc@5: 43.7500 (76.3348)
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2023-08-14 13:26:27,891 - train: [ INFO] - Test: [ 507/507] Time: 0.023 (0.030) Loss: 1.0355 (2.3232) cLoss: 0.0000 (0.0000) Acc@1: 33.3333 (48.7616)Acc@5: 100.0000 (76.3894)
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2023-08-14 13:26:28,019 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-21.pth.tar', 48.76155268116197)
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2023-08-14 13:26:28,547 - train: [ INFO] - Train: 22 [ 0/1521 ( 0%)] Loss: 1.338962 (1.3390) Acc@1: 68.7500 (68.7500) Acc@5: 93.7500 (93.7500) Time: 0.527s, 30.35/s LR: 1.875e-02 P_Replacement: 0.16637500000000005
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2023-08-14 13:27:33,938 - train: [ INFO] - Train: 22 [ 500/1521 ( 33%)] Loss: 1.475561 (0.8518) Acc@1: 62.5000 (79.6657) Acc@5: 93.7500 (97.0808) Time: 0.132s, 121.61/s LR: 1.875e-02 P_Replacement: 0.17394508298713973
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2023-08-14 13:28:39,765 - train: [ INFO] - Train: 22 [1000/1521 ( 66%)] Loss: 1.130992 (1.0070) Acc@1: 56.2500 (75.2373) Acc@5: 100.0000 (95.7293) Time: 0.132s, 121.58/s LR: 1.875e-02 P_Replacement: 0.1817413786311436
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2023-08-14 13:29:44,645 - train: [ INFO] - Train: 22 [1500/1521 ( 99%)] Loss: 1.997683 (1.1061) Acc@1: 50.0000 (72.2893) Acc@5: 87.5000 (94.7160) Time: 0.131s, 122.15/s LR: 1.875e-02 P_Replacement: 0.18976721731091825
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2023-08-14 13:29:47,374 - train: [ INFO] - Train: 22 [1520/1521 (100%)] Loss: 1.841894 (1.1094) Acc@1: 56.2500 (72.2058) Acc@5: 93.7500 (94.6992) Time: 0.131s, 122.08/s LR: 1.875e-02 P_Replacement: 0.19009307245813262
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2023-08-14 13:29:47,733 - train: [ INFO] - Test: [ 0/507] Time: 0.239 (0.239) Loss: 2.2893 (2.2893) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (31.2500)Acc@5: 87.5000 (87.5000)
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2023-08-14 13:30:02,834 - train: [ INFO] - Test: [ 500/507] Time: 0.024 (0.031) Loss: 4.0494 (2.3606) cLoss: 0.0000 (0.0000) Acc@1: 25.0000 (46.9187)Acc@5: 56.2500 (75.9232)
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2023-08-14 13:30:03,017 - train: [ INFO] - Test: [ 507/507] Time: 0.026 (0.031) Loss: 1.2228 (2.3590) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (46.8515)Acc@5: 100.0000 (75.9827)
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2023-08-14 13:30:03,608 - train: [ INFO] - Train: 23 [ 0/1521 ( 0%)] Loss: 0.666056 (0.6661) Acc@1: 93.7500 (93.7500) Acc@5: 100.0000 (100.0000) Time: 0.494s, 32.38/s LR: 1.875e-02 P_Replacement: 0.19010937499999997
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2023-08-14 13:31:08,441 - train: [ INFO] - Train: 23 [ 500/1521 ( 33%)] Loss: 0.992611 (0.8671) Acc@1: 68.7500 (78.8298) Acc@5: 100.0000 (97.1183) Time: 0.130s, 122.71/s LR: 1.875e-02 P_Replacement: 0.19837794065322018
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2023-08-14 13:32:14,453 - train: [ INFO] - Train: 23 [1000/1521 ( 66%)] Loss: 1.157369 (0.9913) Acc@1: 81.2500 (75.7305) Acc@5: 100.0000 (95.9603) Time: 0.131s, 121.95/s LR: 1.875e-02 P_Replacement: 0.20688284997593898
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2023-08-14 13:33:18,835 - train: [ INFO] - Train: 23 [1500/1521 ( 99%)] Loss: 1.587563 (1.0989) Acc@1: 56.2500 (72.7640) Acc@5: 93.7500 (94.7368) Time: 0.130s, 122.71/s LR: 1.875e-02 P_Replacement: 0.21562743334706314
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2023-08-14 13:33:21,359 - train: [ INFO] - Train: 23 [1520/1521 (100%)] Loss: 1.423226 (1.1043) Acc@1: 56.2500 (72.5797) Acc@5: 93.7500 (94.6992) Time: 0.130s, 122.77/s LR: 1.875e-02 P_Replacement: 0.21598224900699428
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2023-08-14 13:33:21,725 - train: [ INFO] - Test: [ 0/507] Time: 0.245 (0.245) Loss: 2.1133 (2.1133) cLoss: 0.0000 (0.0000) Acc@1: 37.5000 (37.5000)Acc@5: 93.7500 (93.7500)
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2023-08-14 13:33:36,612 - train: [ INFO] - Test: [ 500/507] Time: 0.027 (0.030) Loss: 3.2270 (2.2734) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (49.1143)Acc@5: 62.5000 (76.6717)
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2023-08-14 13:33:36,812 - train: [ INFO] - Test: [ 507/507] Time: 0.028 (0.030) Loss: 0.0340 (2.2723) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (49.0943)Acc@5: 100.0000 (76.7221)
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2023-08-14 13:33:36,934 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-23.pth.tar', 49.094269870609985)
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2023-08-14 13:33:37,456 - train: [ INFO] - Train: 24 [ 0/1521 ( 0%)] Loss: 0.760782 (0.7608) Acc@1: 75.0000 (75.0000) Acc@5: 100.0000 (100.0000) Time: 0.521s, 30.70/s LR: 1.875e-02 P_Replacement: 0.21599999999999997
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2023-08-14 13:34:42,347 - train: [ INFO] - Train: 24 [ 500/1521 ( 33%)] Loss: 0.725038 (0.8408) Acc@1: 81.2500 (79.3663) Acc@5: 100.0000 (97.4301) Time: 0.131s, 122.56/s LR: 1.875e-02 P_Replacement: 0.22499786685973464
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2023-08-14 13:35:47,530 - train: [ INFO] - Train: 24 [1000/1521 ( 66%)] Loss: 1.004727 (0.9821) Acc@1: 75.0000 (75.5744) Acc@5: 93.7500 (96.0914) Time: 0.130s, 122.65/s LR: 1.875e-02 P_Replacement: 0.23424220840160231
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2023-08-14 13:36:53,756 - train: [ INFO] - Train: 24 [1500/1521 ( 99%)] Loss: 1.169445 (1.0895) Acc@1: 56.2500 (72.6724) Acc@5: 100.0000 (95.0700) Time: 0.131s, 122.03/s LR: 1.875e-02 P_Replacement: 0.2437363550045098
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2023-08-14 13:36:56,670 - train: [ INFO] - Train: 24 [1520/1521 (100%)] Loss: 1.650397 (1.0913) Acc@1: 56.2500 (72.6044) Acc@5: 87.5000 (95.0567) Time: 0.131s, 121.85/s LR: 1.875e-02 P_Replacement: 0.24412136391877493
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2023-08-14 13:36:57,025 - train: [ INFO] - Test: [ 0/507] Time: 0.240 (0.240) Loss: 1.1217 (1.1217) cLoss: 0.0000 (0.0000) Acc@1: 62.5000 (62.5000)Acc@5: 93.7500 (93.7500)
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2023-08-14 13:37:12,074 - train: [ INFO] - Test: [ 500/507] Time: 0.035 (0.031) Loss: 3.6052 (2.2872) cLoss: 0.0000 (0.0000) Acc@1: 25.0000 (49.0145)Acc@5: 68.7500 (76.8338)
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2023-08-14 13:37:12,284 - train: [ INFO] - Test: [ 507/507] Time: 0.025 (0.031) Loss: 0.1055 (2.2900) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (48.9094)Acc@5: 100.0000 (76.7961)
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2023-08-14 13:37:12,946 - train: [ INFO] - Train: 25 [ 0/1521 ( 0%)] Loss: 0.837595 (0.8376) Acc@1: 68.7500 (68.7500) Acc@5: 100.0000 (100.0000) Time: 0.539s, 29.68/s LR: 1.875e-02 P_Replacement: 0.244140625
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2023-08-14 13:38:18,917 - train: [ INFO] - Train: 25 [ 500/1521 ( 33%)] Loss: 1.545297 (0.8672) Acc@1: 62.5000 (79.0918) Acc@5: 100.0000 (97.0808) Time: 0.133s, 120.53/s LR: 1.875e-02 P_Replacement: 0.25389861160668303
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2023-08-14 13:39:24,873 - train: [ INFO] - Train: 25 [1000/1521 ( 66%)] Loss: 1.417230 (1.0010) Acc@1: 62.5000 (75.3059) Acc@5: 93.7500 (95.8791) Time: 0.132s, 120.91/s LR: 1.875e-02 P_Replacement: 0.26391320390813355
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2023-08-14 13:40:30,383 - train: [ INFO] - Train: 25 [1500/1521 ( 99%)] Loss: 1.827742 (1.1017) Acc@1: 56.2500 (72.5433) Acc@5: 87.5000 (94.7660) Time: 0.132s, 121.32/s LR: 1.875e-02 P_Replacement: 0.2741877322832582
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2023-08-14 13:40:32,821 - train: [ INFO] - Train: 25 [1520/1521 (100%)] Loss: 1.089617 (1.1061) Acc@1: 68.7500 (72.4154) Acc@5: 100.0000 (94.7362) Time: 0.132s, 121.44/s LR: 1.875e-02 P_Replacement: 0.27460416719347486
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2023-08-14 13:40:33,171 - train: [ INFO] - Test: [ 0/507] Time: 0.241 (0.241) Loss: 3.3891 (3.3891) cLoss: 0.0000 (0.0000) Acc@1: 37.5000 (37.5000)Acc@5: 75.0000 (75.0000)
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2023-08-14 13:40:48,269 - train: [ INFO] - Test: [ 500/507] Time: 0.045 (0.031) Loss: 3.1025 (2.3614) cLoss: 0.0000 (0.0000) Acc@1: 25.0000 (47.2305)Acc@5: 43.7500 (75.7485)
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2023-08-14 13:40:48,469 - train: [ INFO] - Test: [ 507/507] Time: 0.031 (0.031) Loss: 0.1241 (2.3572) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (47.1596)Acc@5: 100.0000 (75.8595)
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2023-08-14 13:40:49,083 - train: [ INFO] - Train: 26 [ 0/1521 ( 0%)] Loss: 0.616352 (0.6164) Acc@1: 81.2500 (81.2500) Acc@5: 100.0000 (100.0000) Time: 0.518s, 30.90/s LR: 1.875e-02 P_Replacement: 0.274625
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2023-08-14 13:41:55,147 - train: [ INFO] - Train: 26 [ 500/1521 ( 33%)] Loss: 1.639535 (0.8310) Acc@1: 62.5000 (79.5908) Acc@5: 87.5000 (97.4925) Time: 0.133s, 120.40/s LR: 1.875e-02 P_Replacement: 0.2851739248940654
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2023-08-14 13:43:00,280 - train: [ INFO] - Train: 26 [1000/1521 ( 66%)] Loss: 1.710462 (0.9612) Acc@1: 68.7500 (76.1051) Acc@5: 81.2500 (96.2288) Time: 0.132s, 121.61/s LR: 1.875e-02 P_Replacement: 0.2959895864955326
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2023-08-14 13:44:06,486 - train: [ INFO] - Train: 26 [1500/1521 ( 99%)] Loss: 0.821008 (1.0683) Acc@1: 75.0000 (73.1554) Acc@5: 100.0000 (95.0700) Time: 0.132s, 121.35/s LR: 1.875e-02 P_Replacement: 0.30707531518330844
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2023-08-14 13:44:09,269 - train: [ INFO] - Train: 26 [1520/1521 (100%)] Loss: 1.615203 (1.0723) Acc@1: 62.5000 (73.0810) Acc@5: 81.2500 (95.0321) Time: 0.132s, 121.26/s LR: 1.875e-02 P_Replacement: 0.3075244088310939
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2023-08-14 13:44:09,618 - train: [ INFO] - Test: [ 0/507] Time: 0.235 (0.235) Loss: 1.5464 (1.5464) cLoss: 0.0000 (0.0000) Acc@1: 56.2500 (56.2500)Acc@5: 100.0000 (100.0000)
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2023-08-14 13:44:24,115 - train: [ INFO] - Test: [ 500/507] Time: 0.027 (0.029) Loss: 4.1435 (2.3473) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (48.4780)Acc@5: 50.0000 (76.3598)
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2023-08-14 13:44:24,314 - train: [ INFO] - Test: [ 507/507] Time: 0.029 (0.029) Loss: 0.7641 (2.3449) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (48.4288)Acc@5: 100.0000 (76.4140)
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2023-08-14 13:44:24,982 - train: [ INFO] - Train: 27 [ 0/1521 ( 0%)] Loss: 0.698573 (0.6986) Acc@1: 81.2500 (81.2500) Acc@5: 100.0000 (100.0000) Time: 0.541s, 29.57/s LR: 1.875e-02 P_Replacement: 0.30754687500000005
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2023-08-14 13:45:31,625 - train: [ INFO] - Train: 27 [ 500/1521 ( 33%)] Loss: 1.204109 (0.8479) Acc@1: 62.5000 (79.0669) Acc@5: 93.7500 (97.5674) Time: 0.134s, 119.32/s LR: 1.875e-02 P_Replacement: 0.31891755672188166
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2023-08-14 13:46:37,315 - train: [ INFO] - Train: 27 [1000/1521 ( 66%)] Loss: 1.348299 (0.9821) Acc@1: 56.2500 (75.7493) Acc@5: 87.5000 (96.1039) Time: 0.133s, 120.54/s LR: 1.875e-02 P_Replacement: 0.3305651061637995
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2023-08-14 13:47:42,934 - train: [ INFO] - Train: 27 [1500/1521 ( 99%)] Loss: 1.249376 (1.0842) Acc@1: 68.7500 (73.1429) Acc@5: 87.5000 (94.8909) Time: 0.132s, 121.00/s LR: 1.875e-02 P_Replacement: 0.34249285370466026
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2023-08-14 13:47:45,443 - train: [ INFO] - Train: 27 [1520/1521 (100%)] Loss: 2.085837 (1.0887) Acc@1: 50.0000 (73.0030) Acc@5: 75.0000 (94.8389) Time: 0.132s, 121.08/s LR: 1.875e-02 P_Replacement: 0.34297583883163213
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2023-08-14 13:47:45,788 - train: [ INFO] - Test: [ 0/507] Time: 0.233 (0.233) Loss: 2.2989 (2.2989) cLoss: 0.0000 (0.0000) Acc@1: 43.7500 (43.7500)Acc@5: 75.0000 (75.0000)
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2023-08-14 13:48:00,568 - train: [ INFO] - Test: [ 500/507] Time: 0.027 (0.030) Loss: 3.4948 (2.3420) cLoss: 0.0000 (0.0000) Acc@1: 25.0000 (48.0165)Acc@5: 68.7500 (76.5095)
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2023-08-14 13:48:00,788 - train: [ INFO] - Test: [ 507/507] Time: 0.029 (0.030) Loss: 2.0625 (2.3458) cLoss: 0.0000 (0.0000) Acc@1: 0.0000 (47.8990)Acc@5: 100.0000 (76.4633)
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2023-08-14 13:48:01,454 - train: [ INFO] - Train: 28 [ 0/1521 ( 0%)] Loss: 0.779550 (0.7795) Acc@1: 81.2500 (81.2500) Acc@5: 100.0000 (100.0000) Time: 0.538s, 29.76/s LR: 1.875e-02 P_Replacement: 0.3429999999999999
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2023-08-14 13:49:08,445 - train: [ INFO] - Train: 28 [ 500/1521 ( 33%)] Loss: 2.154797 (0.8297) Acc@1: 50.0000 (79.5659) Acc@5: 93.7500 (97.3927) Time: 0.135s, 118.71/s LR: 1.875e-02 P_Replacement: 0.35522325709013164
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2023-08-14 13:50:14,975 - train: [ INFO] - Train: 28 [1000/1521 ( 66%)] Loss: 0.569038 (0.9546) Acc@1: 87.5000 (76.0115) Acc@5: 100.0000 (96.1226) Time: 0.134s, 119.48/s LR: 1.875e-02 P_Replacement: 0.3677335129129341
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2023-08-14 13:51:21,021 - train: [ INFO] - Train: 28 [1500/1521 ( 99%)] Loss: 1.095794 (1.0610) Acc@1: 81.2500 (73.3594) Acc@5: 93.7500 (94.9992) Time: 0.133s, 120.03/s LR: 1.875e-02 P_Replacement: 0.38053409784731407
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2023-08-14 13:51:23,486 - train: [ INFO] - Train: 28 [1520/1521 (100%)] Loss: 1.223005 (1.0642) Acc@1: 68.7500 (73.2824) Acc@5: 87.5000 (94.9786) Time: 0.133s, 120.15/s LR: 1.875e-02 P_Replacement: 0.3810522071950894
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2023-08-14 13:51:23,847 - train: [ INFO] - Test: [ 0/507] Time: 0.242 (0.242) Loss: 2.2075 (2.2075) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (31.2500)Acc@5: 81.2500 (81.2500)
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2023-08-14 13:51:39,380 - train: [ INFO] - Test: [ 500/507] Time: 0.026 (0.031) Loss: 3.1520 (2.3419) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (47.9416)Acc@5: 68.7500 (76.6218)
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2023-08-14 13:51:39,588 - train: [ INFO] - Test: [ 507/507] Time: 0.039 (0.031) Loss: 1.6030 (2.3490) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (47.7880)Acc@5: 100.0000 (76.5496)
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2023-08-14 13:51:40,207 - train: [ INFO] - Train: 29 [ 0/1521 ( 0%)] Loss: 0.961755 (0.9618) Acc@1: 68.7500 (68.7500) Acc@5: 100.0000 (100.0000) Time: 0.510s, 31.35/s LR: 1.875e-02 P_Replacement: 0.381078125
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2023-08-14 13:52:46,090 - train: [ INFO] - Train: 29 [ 500/1521 ( 33%)] Loss: 0.711268 (0.8529) Acc@1: 75.0000 (78.8174) Acc@5: 100.0000 (97.3927) Time: 0.133s, 120.74/s LR: 1.875e-02 P_Replacement: 0.3941847759988158
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2023-08-14 13:53:51,448 - train: [ INFO] - Train: 29 [1000/1521 ( 66%)] Loss: 0.783226 (0.9561) Acc@1: 75.0000 (76.1551) Acc@5: 93.7500 (96.2912) Time: 0.132s, 121.57/s LR: 1.875e-02 P_Replacement: 0.4075885567429367
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2023-08-14 13:54:56,469 - train: [ INFO] - Train: 29 [1500/1521 ( 99%)] Loss: 1.619079 (1.0800) Acc@1: 68.7500 (72.8723) Acc@5: 87.5000 (94.8451) Time: 0.131s, 122.06/s LR: 1.875e-02 P_Replacement: 0.4212927976112696
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2023-08-14 13:54:59,308 - train: [ INFO] - Train: 29 [1520/1521 (100%)] Loss: 1.060915 (1.0848) Acc@1: 68.7500 (72.7153) Acc@5: 100.0000 (94.7937) Time: 0.131s, 121.93/s LR: 1.875e-02 P_Replacement: 0.4218472639214657
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2023-08-14 13:54:59,626 - train: [ INFO] - Test: [ 0/507] Time: 0.231 (0.231) Loss: 1.2968 (1.2968) cLoss: 0.0000 (0.0000) Acc@1: 62.5000 (62.5000)Acc@5: 93.7500 (93.7500)
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2023-08-14 13:55:14,089 - train: [ INFO] - Test: [ 500/507] Time: 0.032 (0.029) Loss: 4.6325 (2.3718) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (47.0309)Acc@5: 56.2500 (75.1497)
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2023-08-14 13:55:14,297 - train: [ INFO] - Test: [ 507/507] Time: 0.029 (0.029) Loss: 2.1875 (2.3738) cLoss: 0.0000 (0.0000) Acc@1: 0.0000 (46.8885)Acc@5: 100.0000 (75.1571)
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2023-08-14 13:55:14,953 - train: [ INFO] - Train: 30 [ 0/1521 ( 0%)] Loss: 0.698490 (0.6985) Acc@1: 81.2500 (81.2500) Acc@5: 100.0000 (100.0000) Time: 0.531s, 30.11/s LR: 1.875e-02 P_Replacement: 0.421875
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2023-08-14 13:56:20,310 - train: [ INFO] - Train: 30 [ 500/1521 ( 33%)] Loss: 1.174629 (0.8494) Acc@1: 75.0000 (78.9421) Acc@5: 93.7500 (97.2056) Time: 0.132s, 121.67/s LR: 1.875e-02 P_Replacement: 0.4358958634479338
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2023-08-14 13:57:25,904 - train: [ INFO] - Train: 30 [1000/1521 ( 66%)] Loss: 0.812522 (0.9534) Acc@1: 81.2500 (75.8866) Acc@5: 100.0000 (96.3536) Time: 0.131s, 121.82/s LR: 1.875e-02 P_Replacement: 0.45022398765380717
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2023-08-14 13:58:31,428 - train: [ INFO] - Train: 30 [1500/1521 ( 99%)] Loss: 1.501364 (1.0483) Acc@1: 75.0000 (73.2845) Acc@5: 81.2500 (95.2906) Time: 0.131s, 121.91/s LR: 1.875e-02 P_Replacement: 0.46486270299652693
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2023-08-14 13:58:33,960 - train: [ INFO] - Train: 30 [1520/1521 (100%)] Loss: 1.042851 (1.0515) Acc@1: 68.7500 (73.1509) Acc@5: 100.0000 (95.2498) Time: 0.131s, 121.97/s LR: 1.875e-02 P_Replacement: 0.4654547590107613
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2023-08-14 13:58:34,315 - train: [ INFO] - Test: [ 0/507] Time: 0.239 (0.239) Loss: 2.4132 (2.4132) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (50.0000)Acc@5: 93.7500 (93.7500)
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2023-08-14 13:58:49,532 - train: [ INFO] - Test: [ 500/507] Time: 0.031 (0.031) Loss: 3.9286 (2.3181) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (48.7151)Acc@5: 50.0000 (76.4845)
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2023-08-14 13:58:49,765 - train: [ INFO] - Test: [ 507/507] Time: 0.025 (0.031) Loss: 0.1933 (2.3208) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (48.5890)Acc@5: 100.0000 (76.4387)
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2023-08-14 13:58:50,483 - train: [ INFO] - Train: 31 [ 0/1521 ( 0%)] Loss: 0.574919 (0.5749) Acc@1: 87.5000 (87.5000) Acc@5: 100.0000 (100.0000) Time: 0.607s, 26.35/s LR: 1.875e-02 P_Replacement: 0.46548437500000006
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2023-08-14 13:59:55,242 - train: [ INFO] - Train: 31 [ 500/1521 ( 33%)] Loss: 0.857131 (0.8153) Acc@1: 75.0000 (79.5659) Acc@5: 93.7500 (97.3927) Time: 0.130s, 122.64/s LR: 1.875e-02 P_Replacement: 0.48045026943748576
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2023-08-14 14:01:00,145 - train: [ INFO] - Train: 31 [1000/1521 ( 66%)] Loss: 0.544183 (0.9429) Acc@1: 93.7500 (75.9178) Acc@5: 100.0000 (96.1601) Time: 0.130s, 122.95/s LR: 1.875e-02 P_Replacement: 0.4957335556455455
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2023-08-14 14:02:04,344 - train: [ INFO] - Train: 31 [1500/1521 ( 99%)] Loss: 1.395115 (1.0484) Acc@1: 62.5000 (73.0388) Acc@5: 93.7500 (95.0117) Time: 0.130s, 123.51/s LR: 1.875e-02 P_Replacement: 0.511337564003086
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2023-08-14 14:02:06,859 - train: [ INFO] - Train: 31 [1520/1521 (100%)] Loss: 1.272944 (1.0528) Acc@1: 75.0000 (72.9126) Acc@5: 87.5000 (94.9622) Time: 0.129s, 123.55/s LR: 1.875e-02 P_Replacement: 0.511968442462976
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2023-08-14 14:02:07,219 - train: [ INFO] - Test: [ 0/507] Time: 0.244 (0.244) Loss: 2.0748 (2.0748) cLoss: 0.0000 (0.0000) Acc@1: 37.5000 (37.5000)Acc@5: 87.5000 (87.5000)
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2023-08-14 14:02:22,945 - train: [ INFO] - Test: [ 500/507] Time: 0.026 (0.032) Loss: 3.0733 (2.3259) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (47.8169)Acc@5: 62.5000 (76.0604)
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2023-08-14 14:02:23,181 - train: [ INFO] - Test: [ 507/507] Time: 0.025 (0.032) Loss: 0.6939 (2.3244) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (47.8127)Acc@5: 100.0000 (76.0320)
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2023-08-14 14:02:23,843 - train: [ INFO] - Train: 32 [ 0/1521 ( 0%)] Loss: 1.050715 (1.0507) Acc@1: 56.2500 (56.2500) Acc@5: 100.0000 (100.0000) Time: 0.535s, 29.88/s LR: 1.875e-02 P_Replacement: 0.5120000000000001
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2023-08-14 14:03:27,929 - train: [ INFO] - Train: 32 [ 500/1521 ( 33%)] Loss: 0.702395 (0.7925) Acc@1: 87.5000 (79.9651) Acc@5: 93.7500 (97.3303) Time: 0.129s, 124.05/s LR: 1.875e-02 P_Replacement: 0.5279417439674716
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2023-08-14 14:04:33,325 - train: [ INFO] - Train: 32 [1000/1521 ( 66%)] Loss: 0.530952 (0.9221) Acc@1: 87.5000 (76.6796) Acc@5: 100.0000 (96.2413) Time: 0.130s, 123.19/s LR: 1.875e-02 P_Replacement: 0.5442110107181517
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2023-08-14 14:05:38,552 - train: [ INFO] - Train: 32 [1500/1521 ( 99%)] Loss: 0.691042 (1.0218) Acc@1: 87.5000 (73.8091) Acc@5: 93.7500 (95.2407) Time: 0.130s, 123.01/s LR: 1.875e-02 P_Replacement: 0.5608111306309467
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2023-08-14 14:05:41,194 - train: [ INFO] - Train: 32 [1520/1521 (100%)] Loss: 1.204515 (1.0255) Acc@1: 68.7500 (73.6686) Acc@5: 81.2500 (95.2005) Time: 0.130s, 122.99/s LR: 1.875e-02 P_Replacement: 0.5614820642781099
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2023-08-14 14:05:41,602 - train: [ INFO] - Test: [ 0/507] Time: 0.306 (0.306) Loss: 2.9105 (2.9105) cLoss: 0.0000 (0.0000) Acc@1: 37.5000 (37.5000)Acc@5: 81.2500 (81.2500)
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2023-08-14 14:05:56,912 - train: [ INFO] - Test: [ 500/507] Time: 0.027 (0.031) Loss: 2.6416 (2.3460) cLoss: 0.0000 (0.0000) Acc@1: 25.0000 (47.6297)Acc@5: 62.5000 (76.8463)
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2023-08-14 14:05:57,112 - train: [ INFO] - Test: [ 507/507] Time: 0.024 (0.031) Loss: 1.3093 (2.3481) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (47.4677)Acc@5: 100.0000 (76.8084)
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2023-08-14 14:05:57,719 - train: [ INFO] - Train: 33 [ 0/1521 ( 0%)] Loss: 0.727866 (0.7279) Acc@1: 75.0000 (75.0000) Acc@5: 93.7500 (93.7500) Time: 0.522s, 30.64/s LR: 1.875e-02 P_Replacement: 0.561515625
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2023-08-14 14:07:03,970 - train: [ INFO] - Train: 33 [ 500/1521 ( 33%)] Loss: 1.579485 (0.8271) Acc@1: 56.2500 (78.8298) Acc@5: 81.2500 (97.2181) Time: 0.133s, 120.06/s LR: 1.875e-02 P_Replacement: 0.5784640370378913
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2023-08-14 14:08:09,320 - train: [ INFO] - Train: 33 [1000/1521 ( 66%)] Loss: 1.031810 (0.9404) Acc@1: 68.7500 (75.9366) Acc@5: 93.7500 (96.0914) Time: 0.132s, 121.23/s LR: 1.875e-02 P_Replacement: 0.5957501028716254
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2023-08-14 14:09:14,604 - train: [ INFO] - Train: 33 [1500/1521 ( 99%)] Loss: 2.091160 (1.0420) Acc@1: 50.0000 (73.1762) Acc@5: 62.5000 (94.8201) Time: 0.132s, 121.67/s LR: 1.875e-02 P_Replacement: 0.6133771528801093
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2023-08-14 14:09:17,302 - train: [ INFO] - Train: 33 [1520/1521 (100%)] Loss: 0.873181 (1.0452) Acc@1: 75.0000 (73.1139) Acc@5: 93.7500 (94.7896) Time: 0.132s, 121.63/s LR: 1.875e-02 P_Replacement: 0.6140893744561629
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2023-08-14 14:09:17,652 - train: [ INFO] - Test: [ 0/507] Time: 0.233 (0.233) Loss: 1.4601 (1.4601) cLoss: 0.0000 (0.0000) Acc@1: 56.2500 (56.2500)Acc@5: 93.7500 (93.7500)
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2023-08-14 14:09:32,553 - train: [ INFO] - Test: [ 500/507] Time: 0.025 (0.030) Loss: 3.4475 (2.2782) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (49.7505)Acc@5: 43.7500 (77.0709)
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2023-08-14 14:09:32,752 - train: [ INFO] - Test: [ 507/507] Time: 0.024 (0.030) Loss: 1.1344 (2.2797) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (49.7104)Acc@5: 66.6667 (77.0302)
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2023-08-14 14:09:32,841 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
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('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-33.pth.tar', 49.71041281765358)
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2023-08-14 14:09:33,446 - train: [ INFO] - Train: 34 [ 0/1521 ( 0%)] Loss: 0.751162 (0.7512) Acc@1: 75.0000 (75.0000) Acc@5: 100.0000 (100.0000) Time: 0.604s, 26.50/s LR: 1.875e-02 P_Replacement: 0.6141249999999999
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2023-08-14 14:10:37,293 - train: [ INFO] - Train: 34 [ 500/1521 ( 33%)] Loss: 0.975406 (0.8055) Acc@1: 62.5000 (79.1292) Acc@5: 93.7500 (97.5299) Time: 0.129s, 124.39/s LR: 1.875e-02 P_Replacement: 0.632110898648745
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2023-08-14 14:11:41,335 - train: [ INFO] - Train: 34 [1000/1521 ( 66%)] Loss: 0.675635 (0.9120) Acc@1: 75.0000 (76.0739) Acc@5: 100.0000 (96.4598) Time: 0.128s, 124.66/s LR: 1.875e-02 P_Replacement: 0.6504445821059673
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2023-08-14 14:12:46,373 - train: [ INFO] - Train: 34 [1500/1521 ( 99%)] Loss: 1.554642 (1.0137) Acc@1: 68.7500 (73.2970) Acc@5: 87.5000 (95.2448) Time: 0.129s, 124.10/s LR: 1.875e-02 P_Replacement: 0.6691293807505738
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2023-08-14 14:12:48,851 - train: [ INFO] - Train: 34 [1520/1521 (100%)] Loss: 1.089791 (1.0163) Acc@1: 68.7500 (73.2577) Acc@5: 100.0000 (95.1964) Time: 0.129s, 124.17/s LR: 1.875e-02 P_Replacement: 0.6698841229971347
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2023-08-14 14:12:49,202 - train: [ INFO] - Test: [ 0/507] Time: 0.237 (0.237) Loss: 1.9943 (1.9943) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (50.0000)Acc@5: 87.5000 (87.5000)
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2023-08-14 14:13:04,969 - train: [ INFO] - Test: [ 500/507] Time: 0.028 (0.032) Loss: 3.8496 (2.2731) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (49.4636)Acc@5: 43.7500 (77.1831)
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2023-08-14 14:13:05,189 - train: [ INFO] - Test: [ 507/507] Time: 0.025 (0.032) Loss: 1.6344 (2.2752) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (49.3530)Acc@5: 66.6667 (77.1534)
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2023-08-14 14:13:05,913 - train: [ INFO] - Train: 35 [ 0/1521 ( 0%)] Loss: 0.861641 (0.8616) Acc@1: 81.2500 (81.2500) Acc@5: 93.7500 (93.7500) Time: 0.527s, 30.37/s LR: 1.875e-02 P_Replacement: 0.669921875
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2023-08-14 14:14:11,510 - train: [ INFO] - Train: 35 [ 500/1521 ( 33%)] Loss: 1.719881 (0.7773) Acc@1: 68.7500 (79.1292) Acc@5: 81.2500 (97.5175) Time: 0.132s, 121.24/s LR: 1.875e-02 P_Replacement: 0.6889760788000326
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2023-08-14 14:15:17,592 - train: [ INFO] - Train: 35 [1000/1521 ( 66%)] Loss: 1.050637 (0.9178) Acc@1: 75.0000 (75.6681) Acc@5: 87.5000 (96.0977) Time: 0.132s, 121.15/s LR: 1.875e-02 P_Replacement: 0.7083881984211771
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2023-08-14 14:16:23,772 - train: [ INFO] - Train: 35 [1500/1521 ( 99%)] Loss: 1.436481 (1.0127) Acc@1: 56.2500 (73.1138) Acc@5: 93.7500 (95.1574) Time: 0.132s, 121.07/s LR: 1.875e-02 P_Replacement: 0.72816156424234
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2023-08-14 14:16:26,385 - train: [ INFO] - Train: 35 [1520/1521 (100%)] Loss: 1.644636 (1.0145) Acc@1: 62.5000 (73.0605) Acc@5: 81.2500 (95.1430) Time: 0.132s, 121.08/s LR: 1.875e-02 P_Replacement: 0.7289600599010261
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2023-08-14 14:16:26,731 - train: [ INFO] - Test: [ 0/507] Time: 0.235 (0.235) Loss: 3.0705 (3.0705) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (31.2500)Acc@5: 75.0000 (75.0000)
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2023-08-14 14:16:42,021 - train: [ INFO] - Test: [ 500/507] Time: 0.028 (0.031) Loss: 4.6466 (2.3316) cLoss: 0.0000 (0.0000) Acc@1: 18.7500 (48.5279)Acc@5: 37.5000 (76.4970)
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2023-08-14 14:16:42,237 - train: [ INFO] - Test: [ 507/507] Time: 0.034 (0.031) Loss: 0.6757 (2.3266) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (48.6014)Acc@5: 100.0000 (76.5496)
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2023-08-14 14:16:42,882 - train: [ INFO] - Train: 36 [ 0/1521 ( 0%)] Loss: 0.488105 (0.4881) Acc@1: 87.5000 (87.5000) Acc@5: 100.0000 (100.0000) Time: 0.522s, 30.62/s LR: 1.875e-02 P_Replacement: 0.7290000000000001
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2023-08-14 14:17:47,885 - train: [ INFO] - Train: 36 [ 500/1521 ( 33%)] Loss: 0.617947 (0.7648) Acc@1: 87.5000 (79.9027) Acc@5: 87.5000 (97.1682) Time: 0.131s, 122.34/s LR: 1.875e-02 P_Replacement: 0.7491533274917543
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2023-08-14 14:18:54,610 - train: [ INFO] - Train: 36 [1000/1521 ( 66%)] Loss: 0.425831 (0.8903) Acc@1: 100.0000 (76.5672) Acc@5: 100.0000 (96.1538) Time: 0.132s, 121.11/s LR: 1.875e-02 P_Replacement: 0.7696747018172547
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2023-08-14 14:20:00,403 - train: [ INFO] - Train: 36 [1500/1521 ( 99%)] Loss: 1.398581 (0.9849) Acc@1: 68.7500 (73.8508) Acc@5: 93.7500 (95.2906) Time: 0.132s, 121.28/s LR: 1.875e-02 P_Replacement: 0.790567453355408
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2023-08-14 14:20:02,953 - train: [ INFO] - Train: 36 [1520/1521 (100%)] Loss: 0.966132 (0.9896) Acc@1: 75.0000 (73.7262) Acc@5: 93.7500 (95.2252) Time: 0.132s, 121.33/s LR: 1.875e-02 P_Replacement: 0.7914109351678364
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2023-08-14 14:20:03,296 - train: [ INFO] - Test: [ 0/507] Time: 0.235 (0.235) Loss: 1.5155 (1.5155) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (50.0000)Acc@5: 93.7500 (93.7500)
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2023-08-14 14:20:18,604 - train: [ INFO] - Test: [ 500/507] Time: 0.026 (0.031) Loss: 4.4560 (2.3536) cLoss: 0.0000 (0.0000) Acc@1: 12.5000 (48.0165)Acc@5: 56.2500 (76.2475)
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2023-08-14 14:20:18,820 - train: [ INFO] - Test: [ 507/507] Time: 0.035 (0.031) Loss: 0.9410 (2.3535) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (47.9975)Acc@5: 100.0000 (76.3155)
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2023-08-14 14:20:19,479 - train: [ INFO] - Train: 37 [ 0/1521 ( 0%)] Loss: 1.045815 (1.0458) Acc@1: 56.2500 (56.2500) Acc@5: 100.0000 (100.0000) Time: 0.545s, 29.37/s LR: 1.875e-02 P_Replacement: 0.7914531250000001
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2023-08-14 14:21:23,483 - train: [ INFO] - Train: 37 [ 500/1521 ( 33%)] Loss: 1.084580 (0.7901) Acc@1: 62.5000 (78.4930) Acc@5: 100.0000 (97.2929) Time: 0.129s, 124.20/s LR: 1.875e-02 P_Replacement: 0.8127363947239098
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2023-08-14 14:22:28,710 - train: [ INFO] - Train: 37 [1000/1521 ( 66%)] Loss: 0.565967 (0.8982) Acc@1: 87.5000 (75.7805) Acc@5: 93.7500 (96.2100) Time: 0.130s, 123.42/s LR: 1.875e-02 P_Replacement: 0.8343978422942001
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2023-08-14 14:23:32,846 - train: [ INFO] - Train: 37 [1500/1521 ( 99%)] Loss: 1.235666 (0.9778) Acc@1: 68.7500 (73.6342) Acc@5: 93.7500 (95.3364) Time: 0.129s, 123.86/s LR: 1.875e-02 P_Replacement: 0.8564407980897775
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2023-08-14 14:23:35,329 - train: [ INFO] - Train: 37 [1520/1521 (100%)] Loss: 1.871498 (0.9845) Acc@1: 50.0000 (73.4632) Acc@5: 81.2500 (95.2663) Time: 0.129s, 123.92/s LR: 1.875e-02 P_Replacement: 0.857330498797566
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2023-08-14 14:23:35,658 - train: [ INFO] - Test: [ 0/507] Time: 0.230 (0.230) Loss: 0.7574 (0.7574) cLoss: 0.0000 (0.0000) Acc@1: 68.7500 (68.7500)Acc@5: 100.0000 (100.0000)
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2023-08-14 14:23:50,495 - train: [ INFO] - Test: [ 500/507] Time: 0.030 (0.030) Loss: 2.9018 (2.2294) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (49.0020)Acc@5: 68.7500 (77.6697)
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2023-08-14 14:23:50,694 - train: [ INFO] - Test: [ 507/507] Time: 0.030 (0.030) Loss: 2.9606 (2.2279) cLoss: 0.0000 (0.0000) Acc@1: 33.3333 (48.9834)Acc@5: 66.6667 (77.6710)
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2023-08-14 14:23:51,462 - train: [ INFO] - Train: 38 [ 0/1521 ( 0%)] Loss: 0.572535 (0.5725) Acc@1: 87.5000 (87.5000) Acc@5: 100.0000 (100.0000) Time: 0.663s, 24.12/s LR: 1.875e-02 P_Replacement: 0.8573749999999999
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2023-08-14 14:24:58,097 - train: [ INFO] - Train: 38 [ 500/1521 ( 33%)] Loss: 0.787792 (0.7405) Acc@1: 81.2500 (80.4017) Acc@5: 93.7500 (97.5175) Time: 0.134s, 119.12/s LR: 1.875e-02 P_Replacement: 0.879819030496499
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2023-08-14 14:26:05,067 - train: [ INFO] - Train: 38 [1000/1521 ( 66%)] Loss: 0.790147 (0.8766) Acc@1: 75.0000 (75.8304) Acc@5: 93.7500 (96.2662) Time: 0.134s, 119.30/s LR: 1.875e-02 P_Replacement: 0.9026513698520131
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2023-08-14 14:27:12,060 - train: [ INFO] - Train: 38 [1500/1521 ( 99%)] Loss: 1.675580 (0.9670) Acc@1: 62.5000 (73.5093) Acc@5: 87.5000 (95.2115) Time: 0.134s, 119.34/s LR: 1.875e-02 P_Replacement: 0.9258753484454489
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2023-08-14 14:27:14,768 - train: [ INFO] - Train: 38 [1520/1521 (100%)] Loss: 1.889177 (0.9716) Acc@1: 56.2500 (73.4180) Acc@5: 75.0000 (95.1183) Time: 0.134s, 119.32/s LR: 1.875e-02 P_Replacement: 0.9268125007902147
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2023-08-14 14:27:15,219 - train: [ INFO] - Test: [ 0/507] Time: 0.275 (0.275) Loss: 1.5943 (1.5943) cLoss: 0.0000 (0.0000) Acc@1: 43.7500 (43.7500)Acc@5: 93.7500 (93.7500)
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2023-08-14 14:27:30,439 - train: [ INFO] - Test: [ 500/507] Time: 0.037 (0.031) Loss: 3.5793 (2.2583) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (49.3762)Acc@5: 62.5000 (77.4825)
|
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2023-08-14 14:27:30,657 - train: [ INFO] - Test: [ 507/507] Time: 0.031 (0.031) Loss: 1.4415 (2.2586) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (49.3407)Acc@5: 100.0000 (77.5354)
|
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2023-08-14 14:27:31,445 - train: [ INFO] - Train: 39 [ 0/1521 ( 0%)] Loss: 0.499059 (0.4991) Acc@1: 87.5000 (87.5000) Acc@5: 100.0000 (100.0000) Time: 0.632s, 25.30/s LR: 1.875e-02 P_Replacement: 0.9268593749999999
|
| 667 |
+
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+
2023-08-14 14:28:36,367 - train: [ INFO] - Train: 39 [ 500/1521 ( 33%)] Loss: 1.233812 (0.7477) Acc@1: 68.7500 (79.6282) Acc@5: 87.5000 (97.1557) Time: 0.131s, 122.29/s LR: 1.875e-02 P_Replacement: 0.9504949848095224
|
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2023-08-14 14:29:43,254 - train: [ INFO] - Train: 39 [1000/1521 ( 66%)] Loss: 0.422805 (0.8393) Acc@1: 87.5000 (76.7295) Acc@5: 100.0000 (96.3099) Time: 0.132s, 120.94/s LR: 1.875e-02 P_Replacement: 0.9745290344906943
|
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2023-08-14 14:30:49,651 - train: [ INFO] - Train: 39 [1500/1521 ( 99%)] Loss: 1.597075 (0.9524) Acc@1: 50.0000 (73.5635) Acc@5: 87.5000 (95.1324) Time: 0.132s, 120.79/s LR: 1.875e-02 P_Replacement: 0.9989648544224223
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2023-08-14 14:30:52,380 - train: [ INFO] - Train: 39 [1520/1521 (100%)] Loss: 1.230930 (0.9567) Acc@1: 68.7500 (73.4426) Acc@5: 93.7500 (95.1101) Time: 0.133s, 120.75/s LR: 1.875e-02 P_Replacement: 0.9999506911457822
|
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+
2023-08-14 14:30:52,778 - train: [ INFO] - Test: [ 0/507] Time: 0.255 (0.255) Loss: 0.9897 (0.9897) cLoss: 0.0000 (0.0000) Acc@1: 75.0000 (75.0000)Acc@5: 93.7500 (93.7500)
|
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2023-08-14 14:31:08,111 - train: [ INFO] - Test: [ 500/507] Time: 0.032 (0.031) Loss: 2.4661 (2.3217) cLoss: 0.0000 (0.0000) Acc@1: 43.7500 (48.6402)Acc@5: 81.2500 (76.8962)
|
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2023-08-14 14:31:08,332 - train: [ INFO] - Test: [ 507/507] Time: 0.030 (0.031) Loss: 1.4950 (2.3228) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (48.6014)Acc@5: 66.6667 (76.8700)
|
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+
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2023-08-14 14:31:09,006 - train: [ INFO] - Train: 40 [ 0/1521 ( 0%)] Loss: 0.583683 (0.5837) Acc@1: 81.2500 (81.2500) Acc@5: 100.0000 (100.0000) Time: 0.535s, 29.90/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:32:17,409 - train: [ INFO] - Train: 40 [ 500/1521 ( 33%)] Loss: 0.128729 (0.4460) Acc@1: 100.0000 (88.6228) Acc@5: 100.0000 (98.8897) Time: 0.138s, 116.29/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:33:23,676 - train: [ INFO] - Train: 40 [1000/1521 ( 66%)] Loss: 0.122964 (0.3696) Acc@1: 100.0000 (90.7717) Acc@5: 100.0000 (99.2320) Time: 0.135s, 118.47/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:34:29,707 - train: [ INFO] - Train: 40 [1500/1521 ( 99%)] Loss: 0.225854 (0.3236) Acc@1: 93.7500 (92.2219) Acc@5: 100.0000 (99.3962) Time: 0.134s, 119.36/s LR: 1.875e-03 P_Replacement: 1.0
|
| 689 |
+
|
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+
2023-08-14 14:34:32,495 - train: [ INFO] - Train: 40 [1520/1521 (100%)] Loss: 0.209393 (0.3220) Acc@1: 93.7500 (92.2748) Acc@5: 100.0000 (99.4001) Time: 0.134s, 119.29/s LR: 1.875e-03 P_Replacement: 1.0
|
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+
|
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+
2023-08-14 14:34:32,952 - train: [ INFO] - Test: [ 0/507] Time: 0.313 (0.313) Loss: 1.1929 (1.1929) cLoss: 0.0000 (0.0000) Acc@1: 62.5000 (62.5000)Acc@5: 93.7500 (93.7500)
|
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2023-08-14 14:34:48,385 - train: [ INFO] - Test: [ 500/507] Time: 0.039 (0.031) Loss: 2.9647 (1.6381) cLoss: 0.0000 (0.0000) Acc@1: 37.5000 (62.6372)Acc@5: 68.7500 (85.1672)
|
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2023-08-14 14:34:48,592 - train: [ INFO] - Test: [ 507/507] Time: 0.028 (0.031) Loss: 0.5608 (1.6362) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (62.6001)Acc@5: 100.0000 (85.2002)
|
| 697 |
+
|
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+
2023-08-14 14:34:48,721 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 699 |
+
('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-40.pth.tar', 62.600123228589034)
|
| 700 |
+
|
| 701 |
+
2023-08-14 14:34:49,537 - train: [ INFO] - Train: 41 [ 0/1521 ( 0%)] Loss: 0.361155 (0.3612) Acc@1: 93.7500 (93.7500) Acc@5: 100.0000 (100.0000) Time: 0.814s, 19.66/s LR: 1.875e-03 P_Replacement: 1.0
|
| 702 |
+
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+
2023-08-14 14:35:54,975 - train: [ INFO] - Train: 41 [ 500/1521 ( 33%)] Loss: 0.073216 (0.1633) Acc@1: 100.0000 (97.2181) Acc@5: 100.0000 (99.9376) Time: 0.132s, 121.00/s LR: 1.875e-03 P_Replacement: 1.0
|
| 704 |
+
|
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+
2023-08-14 14:37:00,860 - train: [ INFO] - Train: 41 [1000/1521 ( 66%)] Loss: 0.119861 (0.1615) Acc@1: 100.0000 (97.2028) Acc@5: 100.0000 (99.9500) Time: 0.132s, 121.22/s LR: 1.875e-03 P_Replacement: 1.0
|
| 706 |
+
|
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+
2023-08-14 14:38:06,621 - train: [ INFO] - Train: 41 [1500/1521 ( 99%)] Loss: 0.162110 (0.1630) Acc@1: 100.0000 (97.0187) Acc@5: 100.0000 (99.9250) Time: 0.132s, 121.37/s LR: 1.875e-03 P_Replacement: 1.0
|
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|
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2023-08-14 14:38:09,111 - train: [ INFO] - Train: 41 [1520/1521 (100%)] Loss: 0.302251 (0.1629) Acc@1: 100.0000 (97.0455) Acc@5: 100.0000 (99.9260) Time: 0.132s, 121.46/s LR: 1.875e-03 P_Replacement: 1.0
|
| 710 |
+
|
| 711 |
+
2023-08-14 14:38:09,581 - train: [ INFO] - Test: [ 0/507] Time: 0.325 (0.325) Loss: 0.8320 (0.8320) cLoss: 0.0000 (0.0000) Acc@1: 75.0000 (75.0000)Acc@5: 100.0000 (100.0000)
|
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2023-08-14 14:38:24,707 - train: [ INFO] - Test: [ 500/507] Time: 0.035 (0.031) Loss: 2.6881 (1.6214) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (62.5873)Acc@5: 62.5000 (85.6537)
|
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2023-08-14 14:38:24,911 - train: [ INFO] - Test: [ 507/507] Time: 0.024 (0.031) Loss: 0.3537 (1.6186) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (62.5755)Acc@5: 100.0000 (85.6685)
|
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2023-08-14 14:38:25,702 - train: [ INFO] - Train: 42 [ 0/1521 ( 0%)] Loss: 0.081359 (0.0814) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.652s, 24.55/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:39:30,750 - train: [ INFO] - Train: 42 [ 500/1521 ( 33%)] Loss: 0.111643 (0.1125) Acc@1: 100.0000 (98.6776) Acc@5: 100.0000 (99.9750) Time: 0.131s, 122.02/s LR: 1.875e-03 P_Replacement: 1.0
|
| 720 |
+
|
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2023-08-14 14:40:37,144 - train: [ INFO] - Train: 42 [1000/1521 ( 66%)] Loss: 0.251945 (0.1164) Acc@1: 87.5000 (98.4328) Acc@5: 100.0000 (99.9750) Time: 0.132s, 121.26/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:41:43,181 - train: [ INFO] - Train: 42 [1500/1521 ( 99%)] Loss: 0.105602 (0.1212) Acc@1: 100.0000 (98.2595) Acc@5: 100.0000 (99.9667) Time: 0.132s, 121.23/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:41:45,862 - train: [ INFO] - Train: 42 [1520/1521 (100%)] Loss: 0.183886 (0.1214) Acc@1: 93.7500 (98.2454) Acc@5: 100.0000 (99.9671) Time: 0.132s, 121.20/s LR: 1.875e-03 P_Replacement: 1.0
|
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|
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+
2023-08-14 14:41:46,289 - train: [ INFO] - Test: [ 0/507] Time: 0.294 (0.294) Loss: 1.1542 (1.1542) cLoss: 0.0000 (0.0000) Acc@1: 62.5000 (62.5000)Acc@5: 100.0000 (100.0000)
|
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2023-08-14 14:42:01,462 - train: [ INFO] - Test: [ 500/507] Time: 0.031 (0.031) Loss: 2.5874 (1.6031) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (62.7994)Acc@5: 62.5000 (85.8782)
|
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2023-08-14 14:42:01,644 - train: [ INFO] - Test: [ 507/507] Time: 0.026 (0.031) Loss: 0.7505 (1.6015) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (62.7110)Acc@5: 100.0000 (85.9026)
|
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|
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2023-08-14 14:42:01,786 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 734 |
+
('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-42.pth.tar', 62.71102896059874)
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2023-08-14 14:42:02,448 - train: [ INFO] - Train: 43 [ 0/1521 ( 0%)] Loss: 0.070323 (0.0703) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.660s, 24.26/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:43:08,009 - train: [ INFO] - Train: 43 [ 500/1521 ( 33%)] Loss: 0.088067 (0.0847) Acc@1: 100.0000 (99.3014) Acc@5: 100.0000 (100.0000) Time: 0.132s, 121.06/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:44:13,751 - train: [ INFO] - Train: 43 [1000/1521 ( 66%)] Loss: 0.036223 (0.0901) Acc@1: 100.0000 (99.1259) Acc@5: 100.0000 (99.9813) Time: 0.132s, 121.38/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:45:18,849 - train: [ INFO] - Train: 43 [1500/1521 ( 99%)] Loss: 0.047923 (0.0952) Acc@1: 100.0000 (98.9674) Acc@5: 100.0000 (99.9875) Time: 0.131s, 121.88/s LR: 1.875e-03 P_Replacement: 1.0
|
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|
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+
2023-08-14 14:45:21,238 - train: [ INFO] - Train: 43 [1520/1521 (100%)] Loss: 0.084566 (0.0952) Acc@1: 100.0000 (98.9809) Acc@5: 100.0000 (99.9877) Time: 0.131s, 122.03/s LR: 1.875e-03 P_Replacement: 1.0
|
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|
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+
2023-08-14 14:45:21,691 - train: [ INFO] - Test: [ 0/507] Time: 0.306 (0.306) Loss: 1.0768 (1.0768) cLoss: 0.0000 (0.0000) Acc@1: 56.2500 (56.2500)Acc@5: 100.0000 (100.0000)
|
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2023-08-14 14:45:37,304 - train: [ INFO] - Test: [ 500/507] Time: 0.034 (0.032) Loss: 2.9254 (1.5924) cLoss: 0.0000 (0.0000) Acc@1: 31.2500 (63.5479)Acc@5: 68.7500 (86.3648)
|
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+
2023-08-14 14:45:37,514 - train: [ INFO] - Test: [ 507/507] Time: 0.029 (0.032) Loss: 1.2399 (1.5900) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (63.5243)Acc@5: 100.0000 (86.3956)
|
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|
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+
2023-08-14 14:45:37,649 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 753 |
+
('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-43.pth.tar', 63.52433764821427)
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+
2023-08-14 14:45:38,320 - train: [ INFO] - Train: 44 [ 0/1521 ( 0%)] Loss: 0.035756 (0.0358) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.669s, 23.91/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:46:44,412 - train: [ INFO] - Train: 44 [ 500/1521 ( 33%)] Loss: 0.085219 (0.0702) Acc@1: 100.0000 (99.5259) Acc@5: 100.0000 (100.0000) Time: 0.133s, 120.08/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:47:50,751 - train: [ INFO] - Train: 44 [1000/1521 ( 66%)] Loss: 0.024447 (0.0739) Acc@1: 100.0000 (99.4131) Acc@5: 100.0000 (100.0000) Time: 0.133s, 120.34/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:48:57,892 - train: [ INFO] - Train: 44 [1500/1521 ( 99%)] Loss: 0.059046 (0.0792) Acc@1: 100.0000 (99.3171) Acc@5: 100.0000 (99.9917) Time: 0.133s, 119.95/s LR: 1.875e-03 P_Replacement: 1.0
|
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|
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+
2023-08-14 14:49:00,377 - train: [ INFO] - Train: 44 [1520/1521 (100%)] Loss: 0.033084 (0.0794) Acc@1: 100.0000 (99.3097) Acc@5: 100.0000 (99.9918) Time: 0.133s, 120.06/s LR: 1.875e-03 P_Replacement: 1.0
|
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|
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+
2023-08-14 14:49:00,801 - train: [ INFO] - Test: [ 0/507] Time: 0.301 (0.301) Loss: 1.4080 (1.4080) cLoss: 0.0000 (0.0000) Acc@1: 62.5000 (62.5000)Acc@5: 100.0000 (100.0000)
|
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2023-08-14 14:49:16,304 - train: [ INFO] - Test: [ 500/507] Time: 0.027 (0.032) Loss: 2.7201 (1.5906) cLoss: 0.0000 (0.0000) Acc@1: 43.7500 (63.4980)Acc@5: 75.0000 (86.4271)
|
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+
|
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+
2023-08-14 14:49:16,491 - train: [ INFO] - Test: [ 507/507] Time: 0.024 (0.031) Loss: 0.5978 (1.5899) cLoss: 0.0000 (0.0000) Acc@1: 66.6667 (63.4134)Acc@5: 100.0000 (86.4079)
|
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2023-08-14 14:49:17,256 - train: [ INFO] - Train: 45 [ 0/1521 ( 0%)] Loss: 0.019535 (0.0195) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.646s, 24.78/s LR: 1.875e-03 P_Replacement: 1.0
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2023-08-14 14:50:22,286 - train: [ INFO] - Train: 45 [ 500/1521 ( 33%)] Loss: 0.058951 (0.0604) Acc@1: 100.0000 (99.7255) Acc@5: 100.0000 (100.0000) Time: 0.131s, 122.07/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:51:27,613 - train: [ INFO] - Train: 45 [1000/1521 ( 66%)] Loss: 0.101837 (0.0636) Acc@1: 100.0000 (99.7003) Acc@5: 100.0000 (100.0000) Time: 0.131s, 122.27/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:52:32,862 - train: [ INFO] - Train: 45 [1500/1521 ( 99%)] Loss: 0.046677 (0.0675) Acc@1: 100.0000 (99.5878) Acc@5: 100.0000 (100.0000) Time: 0.131s, 122.38/s LR: 1.875e-03 P_Replacement: 1.0
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2023-08-14 14:52:35,391 - train: [ INFO] - Train: 45 [1520/1521 (100%)] Loss: 0.043385 (0.0677) Acc@1: 100.0000 (99.5768) Acc@5: 100.0000 (100.0000) Time: 0.131s, 122.44/s LR: 1.875e-03 P_Replacement: 1.0
|
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2023-08-14 14:52:35,937 - train: [ INFO] - Test: [ 0/507] Time: 0.388 (0.388) Loss: 0.9461 (0.9461) cLoss: 0.0000 (0.0000) Acc@1: 68.7500 (68.7500)Acc@5: 100.0000 (100.0000)
|
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2023-08-14 14:52:51,310 - train: [ INFO] - Test: [ 500/507] Time: 0.031 (0.031) Loss: 2.4672 (1.5895) cLoss: 0.0000 (0.0000) Acc@1: 43.7500 (63.3483)Acc@5: 75.0000 (86.2774)
|
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2023-08-14 14:52:51,509 - train: [ INFO] - Test: [ 507/507] Time: 0.024 (0.031) Loss: 0.3347 (1.5881) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (63.3148)Acc@5: 100.0000 (86.2723)
|
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2023-08-14 14:52:52,292 - train: [ INFO] - Train: 46 [ 0/1521 ( 0%)] Loss: 0.041471 (0.0415) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.663s, 24.13/s LR: 1.875e-03 P_Replacement: 1.0
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2023-08-14 14:53:58,269 - train: [ INFO] - Train: 46 [ 500/1521 ( 33%)] Loss: 0.034691 (0.0513) Acc@1: 100.0000 (99.8129) Acc@5: 100.0000 (100.0000) Time: 0.133s, 120.30/s LR: 1.875e-03 P_Replacement: 1.0
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2023-08-14 14:55:03,161 - train: [ INFO] - Train: 46 [1000/1521 ( 66%)] Loss: 0.082953 (0.0560) Acc@1: 100.0000 (99.6254) Acc@5: 100.0000 (99.9875) Time: 0.131s, 121.78/s LR: 1.875e-03 P_Replacement: 1.0
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2023-08-14 14:56:07,764 - train: [ INFO] - Train: 46 [1500/1521 ( 99%)] Loss: 0.071765 (0.0598) Acc@1: 100.0000 (99.6003) Acc@5: 100.0000 (99.9875) Time: 0.131s, 122.46/s LR: 1.875e-03 P_Replacement: 1.0
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| 795 |
+
2023-08-14 14:56:10,416 - train: [ INFO] - Train: 46 [1520/1521 (100%)] Loss: 0.082075 (0.0600) Acc@1: 100.0000 (99.6055) Acc@5: 100.0000 (99.9877) Time: 0.131s, 122.43/s LR: 1.875e-03 P_Replacement: 1.0
|
| 796 |
+
|
| 797 |
+
2023-08-14 14:56:10,827 - train: [ INFO] - Test: [ 0/507] Time: 0.299 (0.299) Loss: 0.9256 (0.9256) cLoss: 0.0000 (0.0000) Acc@1: 68.7500 (68.7500)Acc@5: 100.0000 (100.0000)
|
| 798 |
+
|
| 799 |
+
2023-08-14 14:56:25,816 - train: [ INFO] - Test: [ 500/507] Time: 0.034 (0.031) Loss: 2.4014 (1.5769) cLoss: 0.0000 (0.0000) Acc@1: 56.2500 (63.6228)Acc@5: 75.0000 (86.3273)
|
| 800 |
+
|
| 801 |
+
2023-08-14 14:56:26,002 - train: [ INFO] - Test: [ 507/507] Time: 0.023 (0.030) Loss: 0.5537 (1.5740) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (63.6352)Acc@5: 100.0000 (86.3339)
|
| 802 |
+
|
| 803 |
+
2023-08-14 14:56:26,124 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 804 |
+
('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-46.pth.tar', 63.635243376463336)
|
| 805 |
+
|
| 806 |
+
2023-08-14 14:56:26,878 - train: [ INFO] - Train: 47 [ 0/1521 ( 0%)] Loss: 0.051671 (0.0517) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.753s, 21.25/s LR: 1.875e-03 P_Replacement: 1.0
|
| 807 |
+
|
| 808 |
+
2023-08-14 14:57:32,189 - train: [ INFO] - Train: 47 [ 500/1521 ( 33%)] Loss: 0.043981 (0.0446) Acc@1: 100.0000 (99.7754) Acc@5: 100.0000 (100.0000) Time: 0.132s, 121.35/s LR: 1.875e-03 P_Replacement: 1.0
|
| 809 |
+
|
| 810 |
+
2023-08-14 14:58:37,741 - train: [ INFO] - Train: 47 [1000/1521 ( 66%)] Loss: 0.048198 (0.0491) Acc@1: 100.0000 (99.7190) Acc@5: 100.0000 (99.9938) Time: 0.131s, 121.70/s LR: 1.875e-03 P_Replacement: 1.0
|
| 811 |
+
|
| 812 |
+
2023-08-14 14:59:43,021 - train: [ INFO] - Train: 47 [1500/1521 ( 99%)] Loss: 0.126728 (0.0534) Acc@1: 100.0000 (99.6794) Acc@5: 100.0000 (99.9958) Time: 0.131s, 121.99/s LR: 1.875e-03 P_Replacement: 1.0
|
| 813 |
+
|
| 814 |
+
2023-08-14 14:59:45,605 - train: [ INFO] - Train: 47 [1520/1521 (100%)] Loss: 0.060515 (0.0535) Acc@1: 100.0000 (99.6795) Acc@5: 100.0000 (99.9959) Time: 0.131s, 122.01/s LR: 1.875e-03 P_Replacement: 1.0
|
| 815 |
+
|
| 816 |
+
2023-08-14 14:59:46,055 - train: [ INFO] - Test: [ 0/507] Time: 0.294 (0.294) Loss: 1.4176 (1.4176) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (50.0000)Acc@5: 100.0000 (100.0000)
|
| 817 |
+
|
| 818 |
+
2023-08-14 15:00:01,082 - train: [ INFO] - Test: [ 500/507] Time: 0.037 (0.031) Loss: 2.8542 (1.5884) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (63.8473)Acc@5: 68.7500 (86.4022)
|
| 819 |
+
|
| 820 |
+
2023-08-14 15:00:01,301 - train: [ INFO] - Test: [ 507/507] Time: 0.037 (0.031) Loss: 0.2313 (1.5856) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (63.8571)Acc@5: 100.0000 (86.4079)
|
| 821 |
+
|
| 822 |
+
2023-08-14 15:00:01,439 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 823 |
+
('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-47.pth.tar', 63.85705483672212)
|
| 824 |
+
|
| 825 |
+
2023-08-14 15:00:02,088 - train: [ INFO] - Train: 48 [ 0/1521 ( 0%)] Loss: 0.038063 (0.0381) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.647s, 24.73/s LR: 1.875e-03 P_Replacement: 1.0
|
| 826 |
+
|
| 827 |
+
2023-08-14 15:01:08,400 - train: [ INFO] - Train: 48 [ 500/1521 ( 33%)] Loss: 0.037126 (0.0418) Acc@1: 100.0000 (99.7505) Acc@5: 100.0000 (100.0000) Time: 0.134s, 119.73/s LR: 1.875e-03 P_Replacement: 1.0
|
| 828 |
+
|
| 829 |
+
2023-08-14 15:02:14,410 - train: [ INFO] - Train: 48 [1000/1521 ( 66%)] Loss: 0.214418 (0.0454) Acc@1: 93.7500 (99.7502) Acc@5: 100.0000 (100.0000) Time: 0.133s, 120.46/s LR: 1.875e-03 P_Replacement: 1.0
|
| 830 |
+
|
| 831 |
+
2023-08-14 15:03:20,855 - train: [ INFO] - Train: 48 [1500/1521 ( 99%)] Loss: 0.073138 (0.0485) Acc@1: 100.0000 (99.7210) Acc@5: 100.0000 (100.0000) Time: 0.133s, 120.44/s LR: 1.875e-03 P_Replacement: 1.0
|
| 832 |
+
|
| 833 |
+
2023-08-14 15:03:23,352 - train: [ INFO] - Train: 48 [1520/1521 (100%)] Loss: 0.081833 (0.0486) Acc@1: 100.0000 (99.7247) Acc@5: 100.0000 (100.0000) Time: 0.133s, 120.54/s LR: 1.875e-03 P_Replacement: 1.0
|
| 834 |
+
|
| 835 |
+
2023-08-14 15:03:23,784 - train: [ INFO] - Test: [ 0/507] Time: 0.295 (0.295) Loss: 1.0537 (1.0537) cLoss: 0.0000 (0.0000) Acc@1: 62.5000 (62.5000)Acc@5: 100.0000 (100.0000)
|
| 836 |
+
|
| 837 |
+
2023-08-14 15:03:38,875 - train: [ INFO] - Test: [ 500/507] Time: 0.025 (0.031) Loss: 2.7912 (1.6034) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (64.0843)Acc@5: 68.7500 (86.1652)
|
| 838 |
+
|
| 839 |
+
2023-08-14 15:03:39,058 - train: [ INFO] - Test: [ 507/507] Time: 0.027 (0.031) Loss: 0.4911 (1.6012) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (64.0912)Acc@5: 100.0000 (86.1738)
|
| 840 |
+
|
| 841 |
+
2023-08-14 15:03:39,199 - timm.utils.checkpoint_saver: [ INFO] - Current checkpoints:
|
| 842 |
+
('/home/hexiang/DomainAdaptation_DVS/Results3/train_DomainAdaptation/Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/checkpoint-48.pth.tar', 64.09118915588417)
|
| 843 |
+
|
| 844 |
+
2023-08-14 15:03:39,921 - train: [ INFO] - Train: 49 [ 0/1521 ( 0%)] Loss: 0.025467 (0.0255) Acc@1: 100.0000 (100.0000) Acc@5: 100.0000 (100.0000) Time: 0.721s, 22.19/s LR: 1.875e-03 P_Replacement: 1.0
|
| 845 |
+
|
| 846 |
+
2023-08-14 15:04:40,118 - train: [ INFO] - Train: 49 [ 500/1521 ( 33%)] Loss: 0.037965 (0.0374) Acc@1: 100.0000 (99.9002) Acc@5: 100.0000 (100.0000) Time: 0.122s, 131.60/s LR: 1.875e-03 P_Replacement: 1.0
|
| 847 |
+
|
| 848 |
+
2023-08-14 15:05:31,179 - train: [ INFO] - Train: 49 [1000/1521 ( 66%)] Loss: 0.038346 (0.0403) Acc@1: 100.0000 (99.8751) Acc@5: 100.0000 (100.0000) Time: 0.112s, 143.04/s LR: 1.875e-03 P_Replacement: 1.0
|
| 849 |
+
|
| 850 |
+
2023-08-14 15:06:16,089 - train: [ INFO] - Train: 49 [1500/1521 ( 99%)] Loss: 0.039026 (0.0441) Acc@1: 100.0000 (99.8210) Acc@5: 100.0000 (100.0000) Time: 0.105s, 153.09/s LR: 1.875e-03 P_Replacement: 1.0
|
| 851 |
+
|
| 852 |
+
2023-08-14 15:06:17,921 - train: [ INFO] - Train: 49 [1520/1521 (100%)] Loss: 0.047950 (0.0444) Acc@1: 100.0000 (99.8233) Acc@5: 100.0000 (100.0000) Time: 0.104s, 153.34/s LR: 1.875e-03 P_Replacement: 1.0
|
| 853 |
+
|
| 854 |
+
2023-08-14 15:06:18,329 - train: [ INFO] - Test: [ 0/507] Time: 0.289 (0.289) Loss: 1.1659 (1.1659) cLoss: 0.0000 (0.0000) Acc@1: 50.0000 (50.0000)Acc@5: 100.0000 (100.0000)
|
| 855 |
+
|
| 856 |
+
2023-08-14 15:06:31,774 - train: [ INFO] - Test: [ 500/507] Time: 0.025 (0.027) Loss: 2.7243 (1.5873) cLoss: 0.0000 (0.0000) Acc@1: 56.2500 (63.7475)Acc@5: 62.5000 (86.5519)
|
| 857 |
+
|
| 858 |
+
2023-08-14 15:06:31,944 - train: [ INFO] - Test: [ 507/507] Time: 0.023 (0.027) Loss: 0.4845 (1.5855) cLoss: 0.0000 (0.0000) Acc@1: 100.0000 (63.7338)Acc@5: 100.0000 (86.5311)
|
| 859 |
+
|
| 860 |
+
2023-08-14 15:06:32,082 - train: [ INFO] - *** Best metric: 64.09118915588417 (epoch 48)
|
Transfer_SCNN-nomni-12-bs_16-seed_1024-DA_False-ls_0.0-domainLoss_True_coefficient0.5-traindataratio_1.0-rgbdataratio_1.0-TET_loss_False-hsv_True-sl_True-regularization_False/model_best.pth.tar
ADDED
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version https://git-lfs.github.com/spec/v1
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size 8375463
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ADDED
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|
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|
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| 48 |
+
46,0.06000318294935991,-8.657238561646637e-09,0.06000318725879337,0.06000318725879337,1.5740210607620353,63.635243376463336
|
| 49 |
+
47,0.053538750592597134,-6.955834833390481e-09,0.0535387540613298,0.0535387540613298,1.5856033258429296,63.85705483672212
|
| 50 |
+
48,0.04861620124147802,-8.0106398093135e-09,0.04861620518873047,0.04861620518873047,1.601195175858537,64.09118915588417
|
| 51 |
+
49,0.04436570025777186,-8.849911886672985e-09,0.044365704683544095,0.044365704683544095,1.5855276326265,63.733826247689464
|