***************
** Arguments **
***************
backbone: 
config_file: configs/trainers/ProDA/vit_b16_ep50_c4_BZ4_ProDA.yaml
dataset_config_file: configs/datasets/ucf101.yaml
eval_only: False
head: 
load_epoch: None
model_dir: 
no_train: False
opts: ['DATASET.NUM_SHOTS', '16', 'DATASET.SUBSAMPLE_CLASSES', 'base']
output_dir: output/base2new/train_base/ucf101/vit_b16_ep50_c4_BZ4_ProDA/seed2
resume: 
root: /mnt/hdd/DATA
seed: 2
source_domains: None
target_domains: None
trainer: ProDA
transforms: None
************
** Config **
************
DATALOADER:
  K_TRANSFORMS: 1
  NUM_WORKERS: 8
  RETURN_IMG0: False
  TEST:
    BATCH_SIZE: 100
    SAMPLER: SequentialSampler
  TRAIN_U:
    BATCH_SIZE: 32
    N_DOMAIN: 0
    N_INS: 16
    SAME_AS_X: True
    SAMPLER: RandomSampler
  TRAIN_X:
    BATCH_SIZE: 4
    N_DOMAIN: 0
    N_INS: 16
    SAMPLER: RandomSampler
DATASET:
  ALL_AS_UNLABELED: False
  CIFAR_C_LEVEL: 1
  CIFAR_C_TYPE: 
  NAME: UCF101
  NUM_LABELED: -1
  NUM_SHOTS: 16
  ROOT: /mnt/hdd/DATA
  SOURCE_DOMAINS: ()
  STL10_FOLD: -1
  SUBSAMPLE_CLASSES: base
  TARGET_DOMAINS: ()
  VAL_PERCENT: 0.1
INPUT:
  COLORJITTER_B: 0.4
  COLORJITTER_C: 0.4
  COLORJITTER_H: 0.1
  COLORJITTER_S: 0.4
  CROP_PADDING: 4
  CUTOUT_LEN: 16
  CUTOUT_N: 1
  GB_K: 21
  GB_P: 0.5
  GN_MEAN: 0.0
  GN_STD: 0.15
  INTERPOLATION: bicubic
  NO_TRANSFORM: False
  PIXEL_MEAN: [0.48145466, 0.4578275, 0.40821073]
  PIXEL_STD: [0.26862954, 0.26130258, 0.27577711]
  RANDAUGMENT_M: 10
  RANDAUGMENT_N: 2
  RGS_P: 0.2
  RRCROP_SCALE: (0.08, 1.0)
  SIZE: (224, 224)
  TRANSFORMS: ('random_resized_crop', 'random_flip', 'normalize')
MODEL:
  BACKBONE:
    NAME: ViT-B/16
    PRETRAINED: True
  HEAD:
    ACTIVATION: relu
    BN: True
    DROPOUT: 0.0
    HIDDEN_LAYERS: ()
    NAME: 
  INIT_WEIGHTS: 
OPTIM:
  ADAM_BETA1: 0.9
  ADAM_BETA2: 0.999
  BASE_LR_MULT: 0.1
  GAMMA: 0.1
  LR: 0.002
  LR_SCHEDULER: cosine
  MAX_EPOCH: 50
  MOMENTUM: 0.9
  NAME: sgd
  NEW_LAYERS: ()
  RMSPROP_ALPHA: 0.99
  SGD_DAMPNING: 0
  SGD_NESTEROV: False
  STAGED_LR: False
  STEPSIZE: (-1,)
  WARMUP_CONS_LR: 1e-05
  WARMUP_EPOCH: 5
  WARMUP_MIN_LR: 1e-05
  WARMUP_RECOUNT: True
  WARMUP_TYPE: constant
  WEIGHT_DECAY: 0.0005
OUTPUT_DIR: output/base2new/train_base/ucf101/vit_b16_ep50_c4_BZ4_ProDA/seed2
RESUME: 
SEED: 2
TEST:
  COMPUTE_CMAT: False
  EVALUATOR: Classification
  FINAL_MODEL: last_step
  NO_TEST: False
  PER_CLASS_RESULT: False
  SPLIT: test
TRAIN:
  CHECKPOINT_FREQ: 0
  COUNT_ITER: train_x
  PRINT_FREQ: 20
TRAINER:
  CDAC:
    CLASS_LR_MULTI: 10
    P_THRESH: 0.95
    RAMPUP_COEF: 30
    RAMPUP_ITRS: 1000
    STRONG_TRANSFORMS: ()
    TOPK_MATCH: 5
  COCOOP:
    CTX_INIT: 
    N_CTX: 16
    PREC: fp16
  COOP:
    CLASS_TOKEN_POSITION: end
    CSC: False
    CTX_INIT: 
    N_CTX: 16
    PREC: fp16
  CROSSGRAD:
    ALPHA_D: 0.5
    ALPHA_F: 0.5
    EPS_D: 1.0
    EPS_F: 1.0
  DAEL:
    CONF_THRE: 0.95
    STRONG_TRANSFORMS: ()
    WEIGHT_U: 0.5
  DAELDG:
    CONF_THRE: 0.95
    STRONG_TRANSFORMS: ()
    WEIGHT_U: 0.5
  DDAIG:
    ALPHA: 0.5
    CLAMP: False
    CLAMP_MAX: 1.0
    CLAMP_MIN: -1.0
    G_ARCH: 
    LMDA: 0.3
    WARMUP: 0
  DOMAINMIX:
    ALPHA: 1.0
    BETA: 1.0
    TYPE: crossdomain
  ENTMIN:
    LMDA: 0.001
  FIXMATCH:
    CONF_THRE: 0.95
    STRONG_TRANSFORMS: ()
    WEIGHT_U: 1.0
  IVLP:
    CTX_INIT: a photo of a
    N_CTX_TEXT: 2
    N_CTX_VISION: 2
    PREC: fp16
    PROMPT_DEPTH_TEXT: 9
    PROMPT_DEPTH_VISION: 9
  M3SDA:
    LMDA: 0.5
    N_STEP_F: 4
  MAPLE:
    CTX_INIT: a photo of a
    N_CTX: 4
    PREC: fp16
    PROMPT_DEPTH: 9
  MCD:
    N_STEP_F: 4
  MEANTEACHER:
    EMA_ALPHA: 0.999
    RAMPUP: 5
    WEIGHT_U: 1.0
  MIXMATCH:
    MIXUP_BETA: 0.75
    RAMPUP: 20000
    TEMP: 2.0
    WEIGHT_U: 100.0
  MME:
    LMDA: 0.1
  NAME: ProDA
  ProDA:
    N_CTX: 4
    N_PROMPT: 32
    PREC: fp16
  SE:
    CONF_THRE: 0.95
    EMA_ALPHA: 0.999
    RAMPUP: 300
  VPT:
    CTX_INIT: a photo of a
    N_CTX_VISION: 2
    PREC: fp16
    PROMPT_DEPTH_VISION: 1
USE_CUDA: True
VERBOSE: True
VERSION: 1
Collecting env info ...
** System info **
PyTorch version: 2.2.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Debian GNU/Linux 12 (bookworm) (x86_64)
GCC version: (Debian 12.2.0-14) 12.2.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.36

Python version: 3.11.2 (main, Mar 13 2023, 12:18:29) [GCC 12.2.0] (64-bit runtime)
Python platform: Linux-6.5.13-3-pve-x86_64-with-glibc2.36
Is CUDA available: True
CUDA runtime version: 11.8.89
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA A800 80GB PCIe
GPU 1: NVIDIA A800 80GB PCIe

Nvidia driver version: 525.147.05
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      46 bits physical, 57 bits virtual
Byte Order:                         Little Endian
CPU(s):                             64
On-line CPU(s) list:                18,20,22,23,25-27,29,31,32,34,37,46-49
Off-line CPU(s) list:               0-17,19,21,24,28,30,33,35,36,38-45,50-63
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) Gold 6326 CPU @ 2.90GHz
CPU family:                         6
Model:                              106
Thread(s) per core:                 2
Core(s) per socket:                 16
Socket(s):                          2
Stepping:                           6
CPU(s) scaling MHz:                 98%
CPU max MHz:                        3500.0000
CPU min MHz:                        800.0000
BogoMIPS:                           5800.00
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect wbnoinvd dtherm ida arat pln pts vnmi avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid fsrm md_clear pconfig flush_l1d arch_capabilities
Virtualization:                     VT-x
L1d cache:                          1.5 MiB (32 instances)
L1i cache:                          1 MiB (32 instances)
L2 cache:                           40 MiB (32 instances)
L3 cache:                           48 MiB (2 instances)
NUMA node(s):                       2
NUMA node0 CPU(s):                  0-15,32-47
NUMA node1 CPU(s):                  16-31,48-63
Vulnerability Gather data sampling: Vulnerable: No microcode
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed:             Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Enhanced / Automatic IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] flake8==3.7.9
[pip3] flake8==3.7.9
[pip3] numpy==1.26.4
[pip3] torch==2.2.1
[pip3] torchaudio==2.2.1
[pip3] torchvision==0.17.1
[pip3] triton==2.2.0
[conda] Could not collect
        Pillow (10.2.0)

Loading trainer: ProDA
Loading dataset: UCF101
Reading split from /mnt/hdd/DATA/ucf101/split_zhou_UCF101.json
Loading preprocessed few-shot data from /mnt/hdd/DATA/ucf101/split_fewshot/shot_16_shuffled-seed_2.pkl
SUBSAMPLE BASE CLASSES!
Building transform_train
+ random resized crop (size=(224, 224), scale=(0.08, 1.0))
+ random flip
+ to torch tensor of range [0, 1]
+ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
Building transform_test
+ resize the smaller edge to 224
+ 224x224 center crop
+ to torch tensor of range [0, 1]
+ normalization (mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711])
---------  ------
Dataset    UCF101
# classes  51
# train_x  816
# val      204
# test     1,860
---------  ------
Loading CLIP (backbone: ViT-B/16)
Building custom CLIP
Turning off gradients in both the image and the text encoder
Parameters to be updated: {'prompt_learner.ctx'}
Loading evaluator: Classification
No checkpoint found, train from scratch
Initialize tensorboard (log_dir=output/base2new/train_base/ucf101/vit_b16_ep50_c4_BZ4_ProDA/seed2/tensorboard)
epoch [1/50] batch [20/204] time 0.565 (0.820) data 0.000 (0.031) loss 0.7549 (2.0583) lr 1.0000e-05 eta 2:19:12
epoch [1/50] batch [40/204] time 0.561 (0.689) data 0.000 (0.016) loss 2.0951 (2.0712) lr 1.0000e-05 eta 1:56:44
epoch [1/50] batch [60/204] time 0.554 (0.646) data 0.000 (0.011) loss 2.6168 (2.2027) lr 1.0000e-05 eta 1:49:10
epoch [1/50] batch [80/204] time 0.558 (0.624) data 0.000 (0.008) loss 1.2422 (2.1066) lr 1.0000e-05 eta 1:45:19
epoch [1/50] batch [100/204] time 0.560 (0.611) data 0.000 (0.006) loss 5.1466 (2.1886) lr 1.0000e-05 eta 1:42:54
epoch [1/50] batch [120/204] time 0.560 (0.603) data 0.000 (0.005) loss 3.8982 (2.1590) lr 1.0000e-05 eta 1:41:13
epoch [1/50] batch [140/204] time 0.557 (0.596) data 0.000 (0.005) loss 2.0075 (2.1198) lr 1.0000e-05 eta 1:39:58
epoch [1/50] batch [160/204] time 0.562 (0.592) data 0.000 (0.004) loss 1.5330 (2.1139) lr 1.0000e-05 eta 1:38:59
epoch [1/50] batch [180/204] time 0.557 (0.588) data 0.000 (0.004) loss 3.2516 (2.1006) lr 1.0000e-05 eta 1:38:10
epoch [1/50] batch [200/204] time 0.562 (0.585) data 0.000 (0.003) loss 1.8186 (2.0752) lr 1.0000e-05 eta 1:37:29
epoch [2/50] batch [20/204] time 0.556 (0.582) data 0.000 (0.026) loss 1.7646 (1.9498) lr 1.0000e-05 eta 1:36:48
epoch [2/50] batch [40/204] time 0.551 (0.570) data 0.000 (0.013) loss 1.5448 (1.8731) lr 1.0000e-05 eta 1:34:33
epoch [2/50] batch [60/204] time 0.559 (0.566) data 0.000 (0.009) loss 1.2140 (1.9470) lr 1.0000e-05 eta 1:33:42
epoch [2/50] batch [80/204] time 0.554 (0.564) data 0.000 (0.007) loss 0.2839 (1.9211) lr 1.0000e-05 eta 1:33:11
epoch [2/50] batch [100/204] time 0.559 (0.563) data 0.000 (0.005) loss 1.9059 (1.9423) lr 1.0000e-05 eta 1:32:49
epoch [2/50] batch [120/204] time 0.559 (0.562) data 0.000 (0.005) loss 0.7063 (1.9684) lr 1.0000e-05 eta 1:32:31
epoch [2/50] batch [140/204] time 0.558 (0.562) data 0.000 (0.004) loss 5.0391 (1.9936) lr 1.0000e-05 eta 1:32:14
epoch [2/50] batch [160/204] time 0.557 (0.561) data 0.000 (0.004) loss 1.4623 (1.9582) lr 1.0000e-05 eta 1:32:00
epoch [2/50] batch [180/204] time 0.559 (0.561) data 0.000 (0.003) loss 1.0456 (1.9398) lr 1.0000e-05 eta 1:31:46
epoch [2/50] batch [200/204] time 0.562 (0.561) data 0.000 (0.003) loss 1.5581 (1.9426) lr 1.0000e-05 eta 1:31:33
epoch [3/50] batch [20/204] time 0.557 (0.588) data 0.000 (0.026) loss 2.2058 (1.7793) lr 1.0000e-05 eta 1:35:47
epoch [3/50] batch [40/204] time 0.562 (0.574) data 0.000 (0.013) loss 1.8937 (1.7243) lr 1.0000e-05 eta 1:33:21
epoch [3/50] batch [60/204] time 0.560 (0.569) data 0.000 (0.009) loss 2.5233 (1.7235) lr 1.0000e-05 eta 1:32:22
epoch [3/50] batch [80/204] time 0.556 (0.567) data 0.000 (0.007) loss 1.4425 (1.8050) lr 1.0000e-05 eta 1:31:45
epoch [3/50] batch [100/204] time 0.554 (0.565) data 0.000 (0.005) loss 1.3183 (1.8439) lr 1.0000e-05 eta 1:31:18
epoch [3/50] batch [120/204] time 0.560 (0.564) data 0.000 (0.004) loss 2.1473 (1.8447) lr 1.0000e-05 eta 1:30:58
epoch [3/50] batch [140/204] time 0.565 (0.564) data 0.000 (0.004) loss 1.6947 (1.8405) lr 1.0000e-05 eta 1:30:40
epoch [3/50] batch [160/204] time 0.561 (0.563) data 0.000 (0.003) loss 4.2830 (1.8346) lr 1.0000e-05 eta 1:30:24
epoch [3/50] batch [180/204] time 0.562 (0.563) data 0.000 (0.003) loss 2.7746 (1.8269) lr 1.0000e-05 eta 1:30:09
epoch [3/50] batch [200/204] time 0.561 (0.562) data 0.000 (0.003) loss 3.4298 (1.8236) lr 1.0000e-05 eta 1:29:54
epoch [4/50] batch [20/204] time 0.560 (0.588) data 0.000 (0.027) loss 0.3801 (1.8387) lr 1.0000e-05 eta 1:33:43
epoch [4/50] batch [40/204] time 0.556 (0.574) data 0.000 (0.014) loss 0.9677 (1.8747) lr 1.0000e-05 eta 1:31:19
epoch [4/50] batch [60/204] time 0.559 (0.569) data 0.000 (0.009) loss 1.2430 (1.8818) lr 1.0000e-05 eta 1:30:24
epoch [4/50] batch [80/204] time 0.556 (0.567) data 0.000 (0.007) loss 1.0482 (1.8797) lr 1.0000e-05 eta 1:29:50
epoch [4/50] batch [100/204] time 0.560 (0.565) data 0.000 (0.006) loss 0.4382 (1.7898) lr 1.0000e-05 eta 1:29:24
epoch [4/50] batch [120/204] time 0.561 (0.564) data 0.000 (0.005) loss 1.0892 (1.7931) lr 1.0000e-05 eta 1:29:03
epoch [4/50] batch [140/204] time 0.561 (0.564) data 0.000 (0.004) loss 1.5356 (1.7863) lr 1.0000e-05 eta 1:28:45
epoch [4/50] batch [160/204] time 0.565 (0.563) data 0.000 (0.004) loss 1.3409 (1.7640) lr 1.0000e-05 eta 1:28:29
epoch [4/50] batch [180/204] time 0.565 (0.563) data 0.000 (0.003) loss 1.1748 (1.7471) lr 1.0000e-05 eta 1:28:14
epoch [4/50] batch [200/204] time 0.561 (0.563) data 0.000 (0.003) loss 1.5235 (1.7294) lr 1.0000e-05 eta 1:28:01
epoch [5/50] batch [20/204] time 0.565 (0.587) data 0.000 (0.026) loss 2.6674 (1.9635) lr 1.0000e-05 eta 1:31:39
epoch [5/50] batch [40/204] time 0.563 (0.574) data 0.000 (0.013) loss 0.4176 (1.6509) lr 1.0000e-05 eta 1:29:24
epoch [5/50] batch [60/204] time 0.574 (0.544) data 0.001 (0.009) loss 1.8250 (1.6609) lr 1.0000e-05 eta 1:24:29
epoch [5/50] batch [80/204] time 0.567 (0.548) data 0.000 (0.007) loss 0.6635 (1.5928) lr 1.0000e-05 eta 1:25:00
epoch [5/50] batch [100/204] time 0.556 (0.552) data 0.000 (0.005) loss 2.8658 (1.6755) lr 1.0000e-05 eta 1:25:24
epoch [5/50] batch [120/204] time 0.555 (0.555) data 0.000 (0.005) loss 1.3899 (1.6112) lr 1.0000e-05 eta 1:25:39
epoch [5/50] batch [140/204] time 0.247 (0.549) data 0.000 (0.004) loss 1.2825 (1.6287) lr 1.0000e-05 eta 1:24:30
epoch [5/50] batch [160/204] time 0.557 (0.541) data 0.000 (0.003) loss 0.6353 (1.6594) lr 1.0000e-05 eta 1:23:12
epoch [5/50] batch [180/204] time 0.553 (0.543) data 0.000 (0.003) loss 0.7848 (1.6692) lr 1.0000e-05 eta 1:23:19
epoch [5/50] batch [200/204] time 0.558 (0.545) data 0.000 (0.003) loss 2.1816 (1.6528) lr 1.0000e-05 eta 1:23:23
epoch [6/50] batch [20/204] time 0.564 (0.586) data 0.000 (0.027) loss 1.4418 (1.9174) lr 2.0000e-03 eta 1:29:29
epoch [6/50] batch [40/204] time 0.553 (0.572) data 0.000 (0.014) loss 1.2940 (1.8645) lr 2.0000e-03 eta 1:27:10
epoch [6/50] batch [60/204] time 0.553 (0.568) data 0.000 (0.009) loss 2.3845 (1.8479) lr 2.0000e-03 eta 1:26:18
epoch [6/50] batch [80/204] time 0.566 (0.566) data 0.000 (0.007) loss 1.9824 (1.7836) lr 2.0000e-03 eta 1:25:47
epoch [6/50] batch [100/204] time 0.566 (0.564) data 0.000 (0.006) loss 1.9410 (1.7991) lr 2.0000e-03 eta 1:25:24
epoch [6/50] batch [120/204] time 0.560 (0.564) data 0.000 (0.005) loss 1.7584 (1.7245) lr 2.0000e-03 eta 1:25:05
epoch [6/50] batch [140/204] time 0.557 (0.563) data 0.004 (0.004) loss 2.7944 (1.6648) lr 2.0000e-03 eta 1:24:49
epoch [6/50] batch [160/204] time 0.559 (0.562) data 0.000 (0.004) loss 0.3335 (1.6511) lr 2.0000e-03 eta 1:24:33
epoch [6/50] batch [180/204] time 0.560 (0.562) data 0.000 (0.003) loss 0.3984 (1.6670) lr 2.0000e-03 eta 1:24:19
epoch [6/50] batch [200/204] time 0.567 (0.562) data 0.000 (0.003) loss 0.7071 (1.6441) lr 2.0000e-03 eta 1:24:05
epoch [7/50] batch [20/204] time 0.564 (0.586) data 0.000 (0.025) loss 0.4813 (1.5496) lr 1.9980e-03 eta 1:27:27
epoch [7/50] batch [40/204] time 0.558 (0.573) data 0.000 (0.013) loss 1.0536 (1.5584) lr 1.9980e-03 eta 1:25:17
epoch [7/50] batch [60/204] time 0.560 (0.569) data 0.000 (0.009) loss 1.0344 (1.5681) lr 1.9980e-03 eta 1:24:29
epoch [7/50] batch [80/204] time 0.560 (0.566) data 0.000 (0.006) loss 1.6922 (1.5182) lr 1.9980e-03 eta 1:23:58
epoch [7/50] batch [100/204] time 0.557 (0.565) data 0.000 (0.005) loss 0.5831 (1.4563) lr 1.9980e-03 eta 1:23:35
epoch [7/50] batch [120/204] time 0.559 (0.564) data 0.000 (0.004) loss 0.3856 (1.4048) lr 1.9980e-03 eta 1:23:17
epoch [7/50] batch [140/204] time 0.562 (0.564) data 0.000 (0.004) loss 1.0456 (1.3973) lr 1.9980e-03 eta 1:23:01
epoch [7/50] batch [160/204] time 0.560 (0.563) data 0.000 (0.003) loss 1.3229 (1.3593) lr 1.9980e-03 eta 1:22:45
epoch [7/50] batch [180/204] time 0.561 (0.563) data 0.000 (0.003) loss 2.8896 (1.3653) lr 1.9980e-03 eta 1:22:31
epoch [7/50] batch [200/204] time 0.559 (0.563) data 0.000 (0.003) loss 1.3511 (1.3437) lr 1.9980e-03 eta 1:22:17
epoch [8/50] batch [20/204] time 0.560 (0.587) data 0.000 (0.027) loss 1.8452 (1.4380) lr 1.9921e-03 eta 1:25:39
epoch [8/50] batch [40/204] time 0.562 (0.574) data 0.000 (0.014) loss 1.9754 (1.4042) lr 1.9921e-03 eta 1:23:30
epoch [8/50] batch [60/204] time 0.559 (0.569) data 0.000 (0.009) loss 1.5066 (1.3882) lr 1.9921e-03 eta 1:22:39
epoch [8/50] batch [80/204] time 0.562 (0.567) data 0.000 (0.007) loss 1.4567 (1.3424) lr 1.9921e-03 eta 1:22:07
epoch [8/50] batch [100/204] time 0.558 (0.566) data 0.000 (0.006) loss 1.0160 (1.2694) lr 1.9921e-03 eta 1:21:44
epoch [8/50] batch [120/204] time 0.559 (0.565) data 0.000 (0.005) loss 2.2312 (1.3030) lr 1.9921e-03 eta 1:21:24
epoch [8/50] batch [140/204] time 0.559 (0.564) data 0.000 (0.004) loss 1.0091 (1.3353) lr 1.9921e-03 eta 1:21:06
epoch [8/50] batch [160/204] time 0.561 (0.563) data 0.000 (0.004) loss 1.3175 (1.3393) lr 1.9921e-03 eta 1:20:50
epoch [8/50] batch [180/204] time 0.560 (0.563) data 0.000 (0.003) loss 0.7463 (1.3597) lr 1.9921e-03 eta 1:20:35
epoch [8/50] batch [200/204] time 0.561 (0.563) data 0.000 (0.003) loss 0.6873 (1.3566) lr 1.9921e-03 eta 1:20:21
epoch [9/50] batch [20/204] time 0.556 (0.587) data 0.000 (0.026) loss 0.0500 (1.5496) lr 1.9823e-03 eta 1:23:35
epoch [9/50] batch [40/204] time 0.561 (0.573) data 0.000 (0.013) loss 1.4735 (1.2407) lr 1.9823e-03 eta 1:21:30
epoch [9/50] batch [60/204] time 0.560 (0.569) data 0.000 (0.009) loss 1.9580 (1.2688) lr 1.9823e-03 eta 1:20:38
epoch [9/50] batch [80/204] time 0.564 (0.566) data 0.000 (0.007) loss 1.2301 (1.2877) lr 1.9823e-03 eta 1:20:07
epoch [9/50] batch [100/204] time 0.561 (0.565) data 0.000 (0.005) loss 0.1731 (1.2814) lr 1.9823e-03 eta 1:19:44
epoch [9/50] batch [120/204] time 0.562 (0.564) data 0.000 (0.005) loss 1.8141 (1.2794) lr 1.9823e-03 eta 1:19:25
epoch [9/50] batch [140/204] time 0.562 (0.564) data 0.000 (0.004) loss 1.2217 (1.2500) lr 1.9823e-03 eta 1:19:09
epoch [9/50] batch [160/204] time 0.559 (0.563) data 0.000 (0.003) loss 1.2588 (1.2967) lr 1.9823e-03 eta 1:18:54
epoch [9/50] batch [180/204] time 0.564 (0.563) data 0.000 (0.003) loss 0.7336 (1.2700) lr 1.9823e-03 eta 1:18:40
epoch [9/50] batch [200/204] time 0.564 (0.562) data 0.000 (0.003) loss 0.8216 (1.2594) lr 1.9823e-03 eta 1:18:26
epoch [10/50] batch [20/204] time 0.561 (0.587) data 0.000 (0.029) loss 0.0834 (1.2572) lr 1.9686e-03 eta 1:21:40
epoch [10/50] batch [40/204] time 0.559 (0.574) data 0.000 (0.014) loss 0.9489 (1.3236) lr 1.9686e-03 eta 1:19:34
epoch [10/50] batch [60/204] time 0.559 (0.569) data 0.000 (0.010) loss 1.9836 (1.2756) lr 1.9686e-03 eta 1:18:45
epoch [10/50] batch [80/204] time 0.555 (0.567) data 0.000 (0.007) loss 2.5169 (1.2740) lr 1.9686e-03 eta 1:18:15
epoch [10/50] batch [100/204] time 0.420 (0.564) data 0.000 (0.006) loss 0.3899 (1.2534) lr 1.9686e-03 eta 1:17:39
epoch [10/50] batch [120/204] time 0.567 (0.552) data 0.000 (0.005) loss 1.7147 (1.2110) lr 1.9686e-03 eta 1:15:51
epoch [10/50] batch [140/204] time 0.556 (0.555) data 0.000 (0.004) loss 1.5051 (1.2206) lr 1.9686e-03 eta 1:16:00
epoch [10/50] batch [160/204] time 0.569 (0.556) data 0.000 (0.004) loss 0.6405 (1.2074) lr 1.9686e-03 eta 1:16:04
epoch [10/50] batch [180/204] time 0.563 (0.557) data 0.000 (0.003) loss 1.1939 (1.2178) lr 1.9686e-03 eta 1:16:00
epoch [10/50] batch [200/204] time 0.560 (0.553) data 0.000 (0.003) loss 1.2000 (1.2240) lr 1.9686e-03 eta 1:15:18
epoch [11/50] batch [20/204] time 0.560 (0.586) data 0.000 (0.026) loss 2.4076 (1.3143) lr 1.9511e-03 eta 1:19:31
epoch [11/50] batch [40/204] time 0.562 (0.573) data 0.000 (0.013) loss 1.5593 (1.2772) lr 1.9511e-03 eta 1:17:30
epoch [11/50] batch [60/204] time 0.560 (0.568) data 0.000 (0.009) loss 0.9815 (1.2569) lr 1.9511e-03 eta 1:16:44
epoch [11/50] batch [80/204] time 0.556 (0.567) data 0.000 (0.007) loss 1.2554 (1.1845) lr 1.9511e-03 eta 1:16:17
epoch [11/50] batch [100/204] time 0.553 (0.565) data 0.000 (0.005) loss 0.7276 (1.2192) lr 1.9511e-03 eta 1:15:54
epoch [11/50] batch [120/204] time 0.561 (0.564) data 0.000 (0.005) loss 1.2258 (1.2230) lr 1.9511e-03 eta 1:15:34
epoch [11/50] batch [140/204] time 0.561 (0.563) data 0.000 (0.004) loss 0.8378 (1.2009) lr 1.9511e-03 eta 1:15:18
epoch [11/50] batch [160/204] time 0.561 (0.563) data 0.000 (0.004) loss 0.1350 (1.1856) lr 1.9511e-03 eta 1:15:03
epoch [11/50] batch [180/204] time 0.556 (0.563) data 0.000 (0.003) loss 1.4686 (1.1758) lr 1.9511e-03 eta 1:14:49
epoch [11/50] batch [200/204] time 0.562 (0.562) data 0.000 (0.003) loss 1.4213 (1.1649) lr 1.9511e-03 eta 1:14:35
epoch [12/50] batch [20/204] time 0.563 (0.585) data 0.000 (0.026) loss 2.5135 (1.2171) lr 1.9298e-03 eta 1:17:23
epoch [12/50] batch [40/204] time 0.560 (0.572) data 0.000 (0.013) loss 1.4156 (1.1273) lr 1.9298e-03 eta 1:15:29
epoch [12/50] batch [60/204] time 0.558 (0.568) data 0.000 (0.009) loss 1.7020 (1.0578) lr 1.9298e-03 eta 1:14:44
epoch [12/50] batch [80/204] time 0.559 (0.566) data 0.000 (0.007) loss 1.4865 (1.0179) lr 1.9298e-03 eta 1:14:15
epoch [12/50] batch [100/204] time 0.561 (0.564) data 0.000 (0.005) loss 0.8538 (1.0964) lr 1.9298e-03 eta 1:13:54
epoch [12/50] batch [120/204] time 0.562 (0.564) data 0.000 (0.004) loss 0.6407 (1.0870) lr 1.9298e-03 eta 1:13:37
epoch [12/50] batch [140/204] time 0.562 (0.563) data 0.000 (0.004) loss 0.9959 (1.1133) lr 1.9298e-03 eta 1:13:22
epoch [12/50] batch [160/204] time 0.558 (0.563) data 0.000 (0.003) loss 1.2182 (1.1140) lr 1.9298e-03 eta 1:13:07
epoch [12/50] batch [180/204] time 0.557 (0.563) data 0.000 (0.003) loss 0.4109 (1.1193) lr 1.9298e-03 eta 1:12:54
epoch [12/50] batch [200/204] time 0.557 (0.562) data 0.000 (0.003) loss 2.0904 (1.1027) lr 1.9298e-03 eta 1:12:40
epoch [13/50] batch [20/204] time 0.562 (0.586) data 0.000 (0.026) loss 1.4338 (1.0965) lr 1.9048e-03 eta 1:15:31
epoch [13/50] batch [40/204] time 0.562 (0.572) data 0.000 (0.013) loss 0.2204 (1.1109) lr 1.9048e-03 eta 1:13:34
epoch [13/50] batch [60/204] time 0.555 (0.568) data 0.000 (0.009) loss 0.5861 (1.0476) lr 1.9048e-03 eta 1:12:47
epoch [13/50] batch [80/204] time 0.559 (0.566) data 0.000 (0.007) loss 2.6743 (1.0308) lr 1.9048e-03 eta 1:12:19
epoch [13/50] batch [100/204] time 0.563 (0.564) data 0.000 (0.005) loss 2.0655 (1.0456) lr 1.9048e-03 eta 1:11:58
epoch [13/50] batch [120/204] time 0.564 (0.564) data 0.000 (0.005) loss 0.4026 (1.0965) lr 1.9048e-03 eta 1:11:41
epoch [13/50] batch [140/204] time 0.563 (0.563) data 0.000 (0.004) loss 2.0906 (1.1418) lr 1.9048e-03 eta 1:11:25
epoch [13/50] batch [160/204] time 0.557 (0.562) data 0.000 (0.003) loss 1.2048 (1.1496) lr 1.9048e-03 eta 1:11:09
epoch [13/50] batch [180/204] time 0.559 (0.562) data 0.000 (0.003) loss 0.5738 (1.1404) lr 1.9048e-03 eta 1:10:55
epoch [13/50] batch [200/204] time 0.563 (0.562) data 0.000 (0.003) loss 4.6122 (1.1725) lr 1.9048e-03 eta 1:10:41
epoch [14/50] batch [20/204] time 0.560 (0.586) data 0.000 (0.026) loss 0.4064 (1.0781) lr 1.8763e-03 eta 1:13:29
epoch [14/50] batch [40/204] time 0.562 (0.572) data 0.000 (0.013) loss 0.2477 (1.0638) lr 1.8763e-03 eta 1:11:35
epoch [14/50] batch [60/204] time 0.560 (0.568) data 0.000 (0.009) loss 0.2505 (1.1142) lr 1.8763e-03 eta 1:10:50
epoch [14/50] batch [80/204] time 0.561 (0.565) data 0.000 (0.007) loss 0.9085 (1.1573) lr 1.8763e-03 eta 1:10:23
epoch [14/50] batch [100/204] time 0.563 (0.564) data 0.000 (0.005) loss 0.7893 (1.1085) lr 1.8763e-03 eta 1:10:02
epoch [14/50] batch [120/204] time 0.560 (0.563) data 0.000 (0.005) loss 0.0950 (1.1055) lr 1.8763e-03 eta 1:09:45
epoch [14/50] batch [140/204] time 0.560 (0.563) data 0.000 (0.004) loss 0.1252 (1.0925) lr 1.8763e-03 eta 1:09:29
epoch [14/50] batch [160/204] time 0.560 (0.562) data 0.000 (0.003) loss 0.2013 (1.0703) lr 1.8763e-03 eta 1:09:15
epoch [14/50] batch [180/204] time 0.559 (0.562) data 0.000 (0.003) loss 0.7318 (1.0801) lr 1.8763e-03 eta 1:09:02
epoch [14/50] batch [200/204] time 0.559 (0.562) data 0.000 (0.003) loss 2.3028 (1.1105) lr 1.8763e-03 eta 1:08:49
epoch [15/50] batch [20/204] time 0.559 (0.587) data 0.000 (0.026) loss 0.7629 (1.1091) lr 1.8443e-03 eta 1:11:37
epoch [15/50] batch [40/204] time 0.552 (0.573) data 0.000 (0.013) loss 0.0249 (1.1517) lr 1.8443e-03 eta 1:09:46
epoch [15/50] batch [60/204] time 0.557 (0.568) data 0.000 (0.009) loss 1.2505 (1.1217) lr 1.8443e-03 eta 1:09:00
epoch [15/50] batch [80/204] time 0.554 (0.566) data 0.000 (0.007) loss 0.3900 (1.1655) lr 1.8443e-03 eta 1:08:31
epoch [15/50] batch [100/204] time 0.557 (0.565) data 0.000 (0.005) loss 1.8394 (1.1713) lr 1.8443e-03 eta 1:08:09
epoch [15/50] batch [120/204] time 0.556 (0.563) data 0.000 (0.005) loss 0.6214 (1.1605) lr 1.8443e-03 eta 1:07:50
epoch [15/50] batch [140/204] time 0.559 (0.563) data 0.000 (0.004) loss 0.9929 (1.1755) lr 1.8443e-03 eta 1:07:34
epoch [15/50] batch [160/204] time 0.559 (0.553) data 0.000 (0.003) loss 2.1546 (1.1762) lr 1.8443e-03 eta 1:06:09
epoch [15/50] batch [180/204] time 0.561 (0.554) data 0.000 (0.003) loss 0.3310 (1.1363) lr 1.8443e-03 eta 1:06:10
epoch [15/50] batch [200/204] time 0.561 (0.555) data 0.000 (0.003) loss 0.3936 (1.1319) lr 1.8443e-03 eta 1:06:05
epoch [16/50] batch [20/204] time 0.577 (0.600) data 0.001 (0.029) loss 1.0809 (1.1717) lr 1.8090e-03 eta 1:11:11
epoch [16/50] batch [40/204] time 0.557 (0.519) data 0.000 (0.015) loss 0.7952 (1.1495) lr 1.8090e-03 eta 1:01:23
epoch [16/50] batch [60/204] time 0.559 (0.532) data 0.000 (0.010) loss 0.4881 (1.1371) lr 1.8090e-03 eta 1:02:46
epoch [16/50] batch [80/204] time 0.554 (0.538) data 0.000 (0.008) loss 0.5071 (1.1549) lr 1.8090e-03 eta 1:03:17
epoch [16/50] batch [100/204] time 0.559 (0.542) data 0.003 (0.006) loss 1.7198 (1.1371) lr 1.8090e-03 eta 1:03:35
epoch [16/50] batch [120/204] time 0.564 (0.545) data 0.000 (0.005) loss 1.4508 (1.1126) lr 1.8090e-03 eta 1:03:44
epoch [16/50] batch [140/204] time 0.567 (0.547) data 0.003 (0.004) loss 1.4939 (1.0939) lr 1.8090e-03 eta 1:03:47
epoch [16/50] batch [160/204] time 0.561 (0.548) data 0.000 (0.004) loss 0.6706 (1.0766) lr 1.8090e-03 eta 1:03:46
epoch [16/50] batch [180/204] time 0.556 (0.549) data 0.000 (0.004) loss 1.9706 (1.1005) lr 1.8090e-03 eta 1:03:43
epoch [16/50] batch [200/204] time 0.561 (0.550) data 0.000 (0.003) loss 0.7102 (1.1044) lr 1.8090e-03 eta 1:03:40
epoch [17/50] batch [20/204] time 0.562 (0.586) data 0.000 (0.026) loss 0.4867 (0.8475) lr 1.7705e-03 eta 1:07:33
epoch [17/50] batch [40/204] time 0.562 (0.573) data 0.000 (0.013) loss 0.6770 (0.9997) lr 1.7705e-03 eta 1:05:52
epoch [17/50] batch [60/204] time 0.557 (0.569) data 0.000 (0.009) loss 2.9161 (1.1564) lr 1.7705e-03 eta 1:05:09
epoch [17/50] batch [80/204] time 0.558 (0.566) data 0.000 (0.007) loss 1.8363 (1.1456) lr 1.7705e-03 eta 1:04:42
epoch [17/50] batch [100/204] time 0.555 (0.565) data 0.000 (0.005) loss 1.4808 (1.1245) lr 1.7705e-03 eta 1:04:20
epoch [17/50] batch [120/204] time 0.561 (0.564) data 0.000 (0.004) loss 0.4392 (1.0602) lr 1.7705e-03 eta 1:04:02
epoch [17/50] batch [140/204] time 0.560 (0.563) data 0.000 (0.004) loss 1.1749 (1.0622) lr 1.7705e-03 eta 1:03:46
epoch [17/50] batch [160/204] time 0.560 (0.563) data 0.000 (0.003) loss 1.8319 (1.0472) lr 1.7705e-03 eta 1:03:32
epoch [17/50] batch [180/204] time 0.554 (0.562) data 0.000 (0.003) loss 1.1305 (1.0254) lr 1.7705e-03 eta 1:03:18
epoch [17/50] batch [200/204] time 0.560 (0.562) data 0.000 (0.003) loss 0.3450 (1.0168) lr 1.7705e-03 eta 1:03:04
epoch [18/50] batch [20/204] time 0.560 (0.584) data 0.000 (0.026) loss 0.6624 (0.8826) lr 1.7290e-03 eta 1:05:16
epoch [18/50] batch [40/204] time 0.559 (0.571) data 0.000 (0.013) loss 0.3740 (0.9896) lr 1.7290e-03 eta 1:03:39
epoch [18/50] batch [60/204] time 0.556 (0.567) data 0.000 (0.009) loss 0.8610 (1.0052) lr 1.7290e-03 eta 1:03:00
epoch [18/50] batch [80/204] time 0.556 (0.565) data 0.000 (0.007) loss 0.3805 (0.9935) lr 1.7290e-03 eta 1:02:37
epoch [18/50] batch [100/204] time 0.562 (0.563) data 0.000 (0.005) loss 0.9627 (1.0421) lr 1.7290e-03 eta 1:02:16
epoch [18/50] batch [120/204] time 0.560 (0.563) data 0.000 (0.004) loss 0.9207 (1.0545) lr 1.7290e-03 eta 1:01:59
epoch [18/50] batch [140/204] time 0.559 (0.562) data 0.000 (0.004) loss 0.8629 (1.0786) lr 1.7290e-03 eta 1:01:44
epoch [18/50] batch [160/204] time 0.562 (0.562) data 0.000 (0.003) loss 1.5389 (1.0580) lr 1.7290e-03 eta 1:01:30
epoch [18/50] batch [180/204] time 0.559 (0.561) data 0.000 (0.003) loss 0.0837 (1.0874) lr 1.7290e-03 eta 1:01:17
epoch [18/50] batch [200/204] time 0.560 (0.561) data 0.000 (0.003) loss 0.2891 (1.1082) lr 1.7290e-03 eta 1:01:04
epoch [19/50] batch [20/204] time 0.562 (0.586) data 0.000 (0.026) loss 0.4169 (0.8840) lr 1.6845e-03 eta 1:03:31
epoch [19/50] batch [40/204] time 0.552 (0.573) data 0.000 (0.013) loss 0.9502 (0.8366) lr 1.6845e-03 eta 1:01:57
epoch [19/50] batch [60/204] time 0.563 (0.569) data 0.000 (0.009) loss 1.5361 (0.9653) lr 1.6845e-03 eta 1:01:17
epoch [19/50] batch [80/204] time 0.561 (0.566) data 0.000 (0.007) loss 1.3553 (0.9213) lr 1.6845e-03 eta 1:00:51
epoch [19/50] batch [100/204] time 0.564 (0.565) data 0.000 (0.005) loss 0.6893 (0.9248) lr 1.6845e-03 eta 1:00:32
epoch [19/50] batch [120/204] time 0.560 (0.564) data 0.000 (0.005) loss 2.2909 (0.9467) lr 1.6845e-03 eta 1:00:14
epoch [19/50] batch [140/204] time 0.560 (0.563) data 0.000 (0.004) loss 0.7600 (0.9535) lr 1.6845e-03 eta 0:59:58
epoch [19/50] batch [160/204] time 0.560 (0.563) data 0.000 (0.003) loss 1.7268 (0.9424) lr 1.6845e-03 eta 0:59:43
epoch [19/50] batch [180/204] time 0.560 (0.562) data 0.000 (0.003) loss 0.2624 (0.9614) lr 1.6845e-03 eta 0:59:29
epoch [19/50] batch [200/204] time 0.560 (0.562) data 0.000 (0.003) loss 0.6180 (0.9532) lr 1.6845e-03 eta 0:59:15
epoch [20/50] batch [20/204] time 0.551 (0.585) data 0.000 (0.026) loss 0.8399 (1.2440) lr 1.6374e-03 eta 1:01:30
epoch [20/50] batch [40/204] time 0.563 (0.573) data 0.000 (0.013) loss 0.0960 (1.0074) lr 1.6374e-03 eta 0:59:58
epoch [20/50] batch [60/204] time 0.560 (0.568) data 0.000 (0.009) loss 0.5348 (0.9331) lr 1.6374e-03 eta 0:59:19
epoch [20/50] batch [80/204] time 0.560 (0.566) data 0.000 (0.007) loss 1.5194 (0.9386) lr 1.6374e-03 eta 0:58:54
epoch [20/50] batch [100/204] time 0.561 (0.565) data 0.000 (0.005) loss 0.7116 (0.9600) lr 1.6374e-03 eta 0:58:35
epoch [20/50] batch [120/204] time 0.558 (0.564) data 0.000 (0.005) loss 0.7441 (0.9627) lr 1.6374e-03 eta 0:58:19
epoch [20/50] batch [140/204] time 0.560 (0.563) data 0.000 (0.004) loss 1.5154 (0.9737) lr 1.6374e-03 eta 0:58:04
epoch [20/50] batch [160/204] time 0.563 (0.563) data 0.000 (0.003) loss 1.7274 (1.0120) lr 1.6374e-03 eta 0:57:50
epoch [20/50] batch [180/204] time 0.558 (0.563) data 0.000 (0.003) loss 0.3986 (1.0134) lr 1.6374e-03 eta 0:57:37
epoch [20/50] batch [200/204] time 0.563 (0.554) data 0.000 (0.003) loss 0.9719 (1.0046) lr 1.6374e-03 eta 0:56:35
epoch [21/50] batch [20/204] time 0.562 (0.600) data 0.000 (0.027) loss 0.4577 (0.7658) lr 1.5878e-03 eta 1:00:58
epoch [21/50] batch [40/204] time 0.566 (0.585) data 0.000 (0.014) loss 0.7681 (0.9017) lr 1.5878e-03 eta 0:59:15
epoch [21/50] batch [60/204] time 0.570 (0.581) data 0.001 (0.009) loss 2.2842 (0.9619) lr 1.5878e-03 eta 0:58:43
epoch [21/50] batch [80/204] time 0.560 (0.547) data 0.000 (0.007) loss 1.0878 (0.9594) lr 1.5878e-03 eta 0:55:05
epoch [21/50] batch [100/204] time 0.560 (0.550) data 0.000 (0.006) loss 0.7767 (0.9865) lr 1.5878e-03 eta 0:55:08
epoch [21/50] batch [120/204] time 0.561 (0.551) data 0.000 (0.005) loss 0.7880 (1.0285) lr 1.5878e-03 eta 0:55:07
epoch [21/50] batch [140/204] time 0.558 (0.552) data 0.000 (0.004) loss 0.2224 (1.0175) lr 1.5878e-03 eta 0:55:02
epoch [21/50] batch [160/204] time 0.555 (0.553) data 0.001 (0.004) loss 0.0956 (0.9957) lr 1.5878e-03 eta 0:54:57
epoch [21/50] batch [180/204] time 0.563 (0.554) data 0.000 (0.003) loss 1.3373 (1.0114) lr 1.5878e-03 eta 0:54:50
epoch [21/50] batch [200/204] time 0.562 (0.555) data 0.000 (0.003) loss 0.5281 (1.0098) lr 1.5878e-03 eta 0:54:43
epoch [22/50] batch [20/204] time 0.560 (0.585) data 0.000 (0.026) loss 0.9380 (0.8612) lr 1.5358e-03 eta 0:57:27
epoch [22/50] batch [40/204] time 0.563 (0.572) data 0.000 (0.013) loss 0.0449 (0.8365) lr 1.5358e-03 eta 0:56:02
epoch [22/50] batch [60/204] time 0.561 (0.568) data 0.000 (0.009) loss 1.9883 (0.8967) lr 1.5358e-03 eta 0:55:25
epoch [22/50] batch [80/204] time 0.556 (0.566) data 0.000 (0.007) loss 0.1717 (0.9745) lr 1.5358e-03 eta 0:55:01
epoch [22/50] batch [100/204] time 0.556 (0.564) data 0.000 (0.006) loss 1.6104 (0.9646) lr 1.5358e-03 eta 0:54:41
epoch [22/50] batch [120/204] time 0.553 (0.563) data 0.000 (0.005) loss 0.6688 (0.9450) lr 1.5358e-03 eta 0:54:24
epoch [22/50] batch [140/204] time 0.568 (0.563) data 0.000 (0.004) loss 1.5541 (0.9228) lr 1.5358e-03 eta 0:54:09
epoch [22/50] batch [160/204] time 0.560 (0.562) data 0.000 (0.004) loss 1.3061 (0.9329) lr 1.5358e-03 eta 0:53:54
epoch [22/50] batch [180/204] time 0.557 (0.562) data 0.000 (0.003) loss 0.7499 (0.9427) lr 1.5358e-03 eta 0:53:40
epoch [22/50] batch [200/204] time 0.556 (0.561) data 0.000 (0.003) loss 0.6859 (0.9576) lr 1.5358e-03 eta 0:53:27
epoch [23/50] batch [20/204] time 0.558 (0.585) data 0.000 (0.026) loss 0.5306 (0.9310) lr 1.4818e-03 eta 0:55:29
epoch [23/50] batch [40/204] time 0.559 (0.572) data 0.000 (0.013) loss 1.9946 (0.9007) lr 1.4818e-03 eta 0:54:05
epoch [23/50] batch [60/204] time 0.557 (0.568) data 0.000 (0.009) loss 1.8025 (0.9456) lr 1.4818e-03 eta 0:53:29
epoch [23/50] batch [80/204] time 0.556 (0.566) data 0.000 (0.007) loss 0.9607 (0.9585) lr 1.4818e-03 eta 0:53:06
epoch [23/50] batch [100/204] time 0.564 (0.565) data 0.000 (0.005) loss 1.3774 (0.9896) lr 1.4818e-03 eta 0:52:48
epoch [23/50] batch [120/204] time 0.558 (0.564) data 0.000 (0.005) loss 1.2916 (0.9736) lr 1.4818e-03 eta 0:52:33
epoch [23/50] batch [140/204] time 0.559 (0.563) data 0.000 (0.004) loss 0.6900 (0.9871) lr 1.4818e-03 eta 0:52:19
epoch [23/50] batch [160/204] time 0.557 (0.563) data 0.000 (0.003) loss 1.3015 (0.9821) lr 1.4818e-03 eta 0:52:06
epoch [23/50] batch [180/204] time 0.561 (0.563) data 0.000 (0.003) loss 0.5273 (0.9607) lr 1.4818e-03 eta 0:51:52
epoch [23/50] batch [200/204] time 0.557 (0.562) data 0.000 (0.003) loss 1.1958 (0.9775) lr 1.4818e-03 eta 0:51:39
epoch [24/50] batch [20/204] time 0.565 (0.584) data 0.000 (0.026) loss 2.1127 (1.1217) lr 1.4258e-03 eta 0:53:26
epoch [24/50] batch [40/204] time 0.559 (0.571) data 0.000 (0.013) loss 0.1324 (0.8845) lr 1.4258e-03 eta 0:52:01
epoch [24/50] batch [60/204] time 0.558 (0.567) data 0.000 (0.009) loss 2.4326 (0.9824) lr 1.4258e-03 eta 0:51:27
epoch [24/50] batch [80/204] time 0.559 (0.565) data 0.000 (0.007) loss 1.9232 (1.0462) lr 1.4258e-03 eta 0:51:05
epoch [24/50] batch [100/204] time 0.561 (0.564) data 0.000 (0.005) loss 1.9661 (1.0475) lr 1.4258e-03 eta 0:50:48
epoch [24/50] batch [120/204] time 0.554 (0.563) data 0.000 (0.004) loss 1.0635 (1.0111) lr 1.4258e-03 eta 0:50:33
epoch [24/50] batch [140/204] time 0.561 (0.562) data 0.000 (0.004) loss 0.2201 (0.9910) lr 1.4258e-03 eta 0:50:18
epoch [24/50] batch [160/204] time 0.560 (0.562) data 0.000 (0.003) loss 0.5214 (1.0073) lr 1.4258e-03 eta 0:50:05
epoch [24/50] batch [180/204] time 0.558 (0.562) data 0.000 (0.003) loss 1.3862 (1.0050) lr 1.4258e-03 eta 0:49:52
epoch [24/50] batch [200/204] time 0.560 (0.561) data 0.000 (0.003) loss 0.2770 (0.9862) lr 1.4258e-03 eta 0:49:39
epoch [25/50] batch [20/204] time 0.558 (0.585) data 0.000 (0.026) loss 0.3482 (0.9628) lr 1.3681e-03 eta 0:51:32
epoch [25/50] batch [40/204] time 0.559 (0.573) data 0.000 (0.013) loss 0.6853 (0.9158) lr 1.3681e-03 eta 0:50:13
epoch [25/50] batch [60/204] time 0.558 (0.568) data 0.000 (0.009) loss 0.2635 (0.9224) lr 1.3681e-03 eta 0:49:40
epoch [25/50] batch [80/204] time 0.566 (0.566) data 0.000 (0.007) loss 2.0268 (0.9463) lr 1.3681e-03 eta 0:49:17
epoch [25/50] batch [100/204] time 0.561 (0.565) data 0.000 (0.005) loss 0.0539 (0.9277) lr 1.3681e-03 eta 0:48:59
epoch [25/50] batch [120/204] time 0.560 (0.564) data 0.000 (0.004) loss 1.6554 (0.9404) lr 1.3681e-03 eta 0:48:43
epoch [25/50] batch [140/204] time 0.557 (0.563) data 0.000 (0.004) loss 0.5723 (0.9199) lr 1.3681e-03 eta 0:48:28
epoch [25/50] batch [160/204] time 0.561 (0.563) data 0.000 (0.003) loss 0.6686 (0.9521) lr 1.3681e-03 eta 0:48:15
epoch [25/50] batch [180/204] time 0.562 (0.562) data 0.000 (0.003) loss 1.1188 (0.9857) lr 1.3681e-03 eta 0:48:01
epoch [25/50] batch [200/204] time 0.561 (0.562) data 0.000 (0.003) loss 0.9919 (0.9658) lr 1.3681e-03 eta 0:47:48
epoch [26/50] batch [20/204] time 0.549 (0.583) data 0.000 (0.026) loss 1.4237 (0.9084) lr 1.3090e-03 eta 0:49:23
epoch [26/50] batch [40/204] time 0.572 (0.531) data 0.001 (0.013) loss 1.7488 (0.8765) lr 1.3090e-03 eta 0:44:45
epoch [26/50] batch [60/204] time 0.573 (0.544) data 0.000 (0.009) loss 1.0199 (0.8985) lr 1.3090e-03 eta 0:45:42
epoch [26/50] batch [80/204] time 0.559 (0.551) data 0.000 (0.007) loss 0.8018 (0.9095) lr 1.3090e-03 eta 0:46:08
epoch [26/50] batch [100/204] time 0.598 (0.555) data 0.011 (0.006) loss 0.8116 (0.9585) lr 1.3090e-03 eta 0:46:14
epoch [26/50] batch [120/204] time 0.255 (0.554) data 0.000 (0.005) loss 0.9640 (0.9329) lr 1.3090e-03 eta 0:45:58
epoch [26/50] batch [140/204] time 0.557 (0.541) data 0.000 (0.004) loss 0.5286 (0.9491) lr 1.3090e-03 eta 0:44:42
epoch [26/50] batch [160/204] time 0.560 (0.543) data 0.000 (0.004) loss 2.2171 (0.9599) lr 1.3090e-03 eta 0:44:43
epoch [26/50] batch [180/204] time 0.559 (0.545) data 0.000 (0.003) loss 0.5372 (0.9741) lr 1.3090e-03 eta 0:44:41
epoch [26/50] batch [200/204] time 0.560 (0.546) data 0.000 (0.003) loss 0.1769 (0.9771) lr 1.3090e-03 eta 0:44:37
epoch [27/50] batch [20/204] time 0.559 (0.584) data 0.000 (0.026) loss 2.0776 (1.0673) lr 1.2487e-03 eta 0:47:26
epoch [27/50] batch [40/204] time 0.563 (0.571) data 0.004 (0.013) loss 0.7048 (1.0138) lr 1.2487e-03 eta 0:46:14
epoch [27/50] batch [60/204] time 0.557 (0.567) data 0.000 (0.009) loss 1.6893 (1.0305) lr 1.2487e-03 eta 0:45:42
epoch [27/50] batch [80/204] time 0.562 (0.565) data 0.000 (0.007) loss 0.5528 (0.9665) lr 1.2487e-03 eta 0:45:21
epoch [27/50] batch [100/204] time 0.557 (0.564) data 0.000 (0.006) loss 0.3912 (0.9780) lr 1.2487e-03 eta 0:45:05
epoch [27/50] batch [120/204] time 0.559 (0.563) data 0.000 (0.005) loss 0.0632 (0.9593) lr 1.2487e-03 eta 0:44:49
epoch [27/50] batch [140/204] time 0.560 (0.563) data 0.000 (0.004) loss 0.8710 (0.9607) lr 1.2487e-03 eta 0:44:35
epoch [27/50] batch [160/204] time 0.558 (0.562) data 0.000 (0.004) loss 0.9385 (0.9653) lr 1.2487e-03 eta 0:44:22
epoch [27/50] batch [180/204] time 0.557 (0.562) data 0.000 (0.003) loss 2.0709 (0.9485) lr 1.2487e-03 eta 0:44:09
epoch [27/50] batch [200/204] time 0.562 (0.562) data 0.000 (0.003) loss 1.5111 (0.9506) lr 1.2487e-03 eta 0:43:57
epoch [28/50] batch [20/204] time 0.559 (0.586) data 0.000 (0.026) loss 0.8227 (0.9375) lr 1.1874e-03 eta 0:45:36
epoch [28/50] batch [40/204] time 0.556 (0.573) data 0.000 (0.013) loss 4.1527 (0.9482) lr 1.1874e-03 eta 0:44:24
epoch [28/50] batch [60/204] time 0.553 (0.568) data 0.000 (0.009) loss 0.9218 (0.8934) lr 1.1874e-03 eta 0:43:52
epoch [28/50] batch [80/204] time 0.563 (0.566) data 0.000 (0.007) loss 0.0565 (0.8488) lr 1.1874e-03 eta 0:43:30
epoch [28/50] batch [100/204] time 0.567 (0.565) data 0.000 (0.005) loss 1.8805 (0.8654) lr 1.1874e-03 eta 0:43:13
epoch [28/50] batch [120/204] time 0.559 (0.564) data 0.000 (0.005) loss 0.4556 (0.8808) lr 1.1874e-03 eta 0:42:57
epoch [28/50] batch [140/204] time 0.559 (0.563) data 0.000 (0.004) loss 1.0088 (0.8712) lr 1.1874e-03 eta 0:42:44
epoch [28/50] batch [160/204] time 0.562 (0.563) data 0.000 (0.003) loss 1.2000 (0.8992) lr 1.1874e-03 eta 0:42:30
epoch [28/50] batch [180/204] time 0.563 (0.563) data 0.000 (0.003) loss 0.0485 (0.8814) lr 1.1874e-03 eta 0:42:18
epoch [28/50] batch [200/204] time 0.560 (0.562) data 0.000 (0.003) loss 1.8126 (0.9307) lr 1.1874e-03 eta 0:42:06
epoch [29/50] batch [20/204] time 0.561 (0.585) data 0.000 (0.026) loss 1.4925 (0.8745) lr 1.1253e-03 eta 0:43:33
epoch [29/50] batch [40/204] time 0.561 (0.572) data 0.000 (0.013) loss 3.7655 (1.1665) lr 1.1253e-03 eta 0:42:24
epoch [29/50] batch [60/204] time 0.563 (0.567) data 0.000 (0.009) loss 1.6995 (1.1416) lr 1.1253e-03 eta 0:41:52
epoch [29/50] batch [80/204] time 0.558 (0.565) data 0.000 (0.007) loss 0.6594 (1.0605) lr 1.1253e-03 eta 0:41:31
epoch [29/50] batch [100/204] time 0.558 (0.564) data 0.000 (0.005) loss 0.6841 (1.0176) lr 1.1253e-03 eta 0:41:13
epoch [29/50] batch [120/204] time 0.557 (0.563) data 0.000 (0.004) loss 0.0988 (0.9984) lr 1.1253e-03 eta 0:40:58
epoch [29/50] batch [140/204] time 0.559 (0.562) data 0.000 (0.004) loss 2.4648 (0.9918) lr 1.1253e-03 eta 0:40:44
epoch [29/50] batch [160/204] time 0.559 (0.561) data 0.000 (0.003) loss 0.7054 (0.9750) lr 1.1253e-03 eta 0:40:30
epoch [29/50] batch [180/204] time 0.562 (0.561) data 0.000 (0.003) loss 0.4134 (0.9387) lr 1.1253e-03 eta 0:40:17
epoch [29/50] batch [200/204] time 0.554 (0.561) data 0.000 (0.003) loss 0.4288 (0.9336) lr 1.1253e-03 eta 0:40:05
epoch [30/50] batch [20/204] time 0.560 (0.584) data 0.000 (0.026) loss 1.0580 (0.8524) lr 1.0628e-03 eta 0:41:29
epoch [30/50] batch [40/204] time 0.563 (0.571) data 0.000 (0.013) loss 1.0145 (0.9484) lr 1.0628e-03 eta 0:40:25
epoch [30/50] batch [60/204] time 0.559 (0.567) data 0.000 (0.009) loss 0.2514 (0.9549) lr 1.0628e-03 eta 0:39:56
epoch [30/50] batch [80/204] time 0.560 (0.565) data 0.000 (0.007) loss 0.6528 (0.9621) lr 1.0628e-03 eta 0:39:36
epoch [30/50] batch [100/204] time 0.556 (0.564) data 0.000 (0.005) loss 0.6910 (0.9855) lr 1.0628e-03 eta 0:39:20
epoch [30/50] batch [120/204] time 0.562 (0.563) data 0.000 (0.004) loss 0.4493 (0.9505) lr 1.0628e-03 eta 0:39:04
epoch [30/50] batch [140/204] time 0.559 (0.562) data 0.000 (0.004) loss 0.9497 (0.9312) lr 1.0628e-03 eta 0:38:50
epoch [30/50] batch [160/204] time 0.561 (0.562) data 0.000 (0.003) loss 0.7726 (0.9421) lr 1.0628e-03 eta 0:38:36
epoch [30/50] batch [180/204] time 0.557 (0.561) data 0.000 (0.003) loss 0.2774 (0.9561) lr 1.0628e-03 eta 0:38:24
epoch [30/50] batch [200/204] time 0.556 (0.561) data 0.000 (0.003) loss 0.4473 (0.9548) lr 1.0628e-03 eta 0:38:11
epoch [31/50] batch [20/204] time 0.542 (0.583) data 0.000 (0.026) loss 1.2501 (0.9654) lr 1.0000e-03 eta 0:39:26
epoch [31/50] batch [40/204] time 0.560 (0.570) data 0.000 (0.013) loss 0.7764 (0.9144) lr 1.0000e-03 eta 0:38:23
epoch [31/50] batch [60/204] time 0.562 (0.566) data 0.000 (0.009) loss 0.7508 (0.9852) lr 1.0000e-03 eta 0:37:55
epoch [31/50] batch [80/204] time 0.559 (0.564) data 0.000 (0.007) loss 0.1010 (0.9937) lr 1.0000e-03 eta 0:37:36
epoch [31/50] batch [100/204] time 0.567 (0.548) data 0.000 (0.005) loss 1.0892 (1.0161) lr 1.0000e-03 eta 0:36:22
epoch [31/50] batch [120/204] time 0.577 (0.552) data 0.000 (0.005) loss 1.0716 (1.0235) lr 1.0000e-03 eta 0:36:27
epoch [31/50] batch [140/204] time 0.565 (0.555) data 0.000 (0.004) loss 0.9627 (1.0260) lr 1.0000e-03 eta 0:36:26
epoch [31/50] batch [160/204] time 0.556 (0.556) data 0.000 (0.004) loss 0.9340 (1.0253) lr 1.0000e-03 eta 0:36:21
epoch [31/50] batch [180/204] time 0.557 (0.552) data 0.000 (0.003) loss 0.1752 (1.0067) lr 1.0000e-03 eta 0:35:52
epoch [31/50] batch [200/204] time 0.556 (0.553) data 0.000 (0.003) loss 0.9877 (0.9842) lr 1.0000e-03 eta 0:35:43
epoch [32/50] batch [20/204] time 0.560 (0.584) data 0.000 (0.026) loss 0.8258 (0.7583) lr 9.3721e-04 eta 0:37:33
epoch [32/50] batch [40/204] time 0.559 (0.571) data 0.000 (0.013) loss 1.6622 (0.9675) lr 9.3721e-04 eta 0:36:31
epoch [32/50] batch [60/204] time 0.554 (0.567) data 0.000 (0.009) loss 1.0429 (0.9791) lr 9.3721e-04 eta 0:36:04
epoch [32/50] batch [80/204] time 0.560 (0.565) data 0.000 (0.007) loss 1.9843 (1.0014) lr 9.3721e-04 eta 0:35:44
epoch [32/50] batch [100/204] time 0.563 (0.564) data 0.000 (0.005) loss 1.0811 (0.9570) lr 9.3721e-04 eta 0:35:29
epoch [32/50] batch [120/204] time 0.554 (0.563) data 0.000 (0.005) loss 0.5342 (0.9554) lr 9.3721e-04 eta 0:35:15
epoch [32/50] batch [140/204] time 0.560 (0.563) data 0.000 (0.004) loss 0.5205 (0.9043) lr 9.3721e-04 eta 0:35:02
epoch [32/50] batch [160/204] time 0.559 (0.563) data 0.000 (0.003) loss 0.8588 (0.9456) lr 9.3721e-04 eta 0:34:50
epoch [32/50] batch [180/204] time 0.562 (0.562) data 0.000 (0.003) loss 1.7062 (0.9516) lr 9.3721e-04 eta 0:34:38
epoch [32/50] batch [200/204] time 0.562 (0.562) data 0.000 (0.003) loss 0.3255 (0.9353) lr 9.3721e-04 eta 0:34:26
epoch [33/50] batch [20/204] time 0.560 (0.587) data 0.000 (0.026) loss 0.3682 (0.8853) lr 8.7467e-04 eta 0:35:43
epoch [33/50] batch [40/204] time 0.563 (0.574) data 0.000 (0.013) loss 1.2307 (0.8505) lr 8.7467e-04 eta 0:34:43
epoch [33/50] batch [60/204] time 0.559 (0.569) data 0.000 (0.009) loss 0.8026 (0.8754) lr 8.7467e-04 eta 0:34:14
epoch [33/50] batch [80/204] time 0.563 (0.567) data 0.000 (0.007) loss 1.4156 (0.8637) lr 8.7467e-04 eta 0:33:55
epoch [33/50] batch [100/204] time 0.554 (0.565) data 0.000 (0.005) loss 1.1285 (0.8720) lr 8.7467e-04 eta 0:33:38
epoch [33/50] batch [120/204] time 0.558 (0.564) data 0.000 (0.005) loss 2.4602 (0.8709) lr 8.7467e-04 eta 0:33:24
epoch [33/50] batch [140/204] time 0.560 (0.564) data 0.000 (0.004) loss 0.5900 (0.8641) lr 8.7467e-04 eta 0:33:10
epoch [33/50] batch [160/204] time 0.561 (0.563) data 0.000 (0.003) loss 0.6375 (0.8627) lr 8.7467e-04 eta 0:32:57
epoch [33/50] batch [180/204] time 0.559 (0.563) data 0.000 (0.003) loss 1.5488 (0.8601) lr 8.7467e-04 eta 0:32:45
epoch [33/50] batch [200/204] time 0.565 (0.563) data 0.000 (0.003) loss 1.0077 (0.8831) lr 8.7467e-04 eta 0:32:33
epoch [34/50] batch [20/204] time 0.558 (0.585) data 0.000 (0.026) loss 0.2115 (0.8837) lr 8.1262e-04 eta 0:33:35
epoch [34/50] batch [40/204] time 0.559 (0.572) data 0.000 (0.013) loss 1.1055 (0.9281) lr 8.1262e-04 eta 0:32:41
epoch [34/50] batch [60/204] time 0.557 (0.567) data 0.001 (0.009) loss 0.3847 (0.8010) lr 8.1262e-04 eta 0:32:12
epoch [34/50] batch [80/204] time 0.560 (0.565) data 0.000 (0.007) loss 1.3569 (0.8135) lr 8.1262e-04 eta 0:31:55
epoch [34/50] batch [100/204] time 0.557 (0.564) data 0.000 (0.006) loss 0.1183 (0.8207) lr 8.1262e-04 eta 0:31:39
epoch [34/50] batch [120/204] time 0.553 (0.563) data 0.000 (0.005) loss 1.9160 (0.9008) lr 8.1262e-04 eta 0:31:25
epoch [34/50] batch [140/204] time 0.559 (0.563) data 0.000 (0.004) loss 0.0206 (0.8859) lr 8.1262e-04 eta 0:31:12
epoch [34/50] batch [160/204] time 0.559 (0.562) data 0.000 (0.004) loss 0.5543 (0.9010) lr 8.1262e-04 eta 0:30:59
epoch [34/50] batch [180/204] time 0.558 (0.562) data 0.000 (0.003) loss 0.6161 (0.9046) lr 8.1262e-04 eta 0:30:47
epoch [34/50] batch [200/204] time 0.557 (0.562) data 0.000 (0.003) loss 0.6825 (0.9055) lr 8.1262e-04 eta 0:30:35
epoch [35/50] batch [20/204] time 0.561 (0.590) data 0.000 (0.031) loss 2.7808 (0.9391) lr 7.5131e-04 eta 0:31:54
epoch [35/50] batch [40/204] time 0.558 (0.575) data 0.000 (0.016) loss 0.6093 (0.8964) lr 7.5131e-04 eta 0:30:53
epoch [35/50] batch [60/204] time 0.559 (0.569) data 0.000 (0.010) loss 0.6336 (0.8920) lr 7.5131e-04 eta 0:30:24
epoch [35/50] batch [80/204] time 0.560 (0.566) data 0.000 (0.008) loss 1.8615 (0.9276) lr 7.5131e-04 eta 0:30:02
epoch [35/50] batch [100/204] time 0.559 (0.565) data 0.000 (0.006) loss 1.6781 (0.9853) lr 7.5131e-04 eta 0:29:46
epoch [35/50] batch [120/204] time 0.557 (0.564) data 0.000 (0.005) loss 0.6042 (0.9212) lr 7.5131e-04 eta 0:29:31
epoch [35/50] batch [140/204] time 0.560 (0.563) data 0.000 (0.005) loss 1.2970 (0.9203) lr 7.5131e-04 eta 0:29:18
epoch [35/50] batch [160/204] time 0.568 (0.563) data 0.001 (0.004) loss 0.0526 (0.9341) lr 7.5131e-04 eta 0:29:06
epoch [35/50] batch [180/204] time 0.557 (0.562) data 0.000 (0.004) loss 1.7757 (0.9302) lr 7.5131e-04 eta 0:28:53
epoch [35/50] batch [200/204] time 0.560 (0.562) data 0.000 (0.003) loss 0.5634 (0.9432) lr 7.5131e-04 eta 0:28:41
epoch [36/50] batch [20/204] time 0.561 (0.587) data 0.000 (0.026) loss 0.5044 (0.8229) lr 6.9098e-04 eta 0:29:45
epoch [36/50] batch [40/204] time 0.560 (0.574) data 0.000 (0.013) loss 0.3823 (0.8435) lr 6.9098e-04 eta 0:28:53
epoch [36/50] batch [60/204] time 0.559 (0.570) data 0.000 (0.009) loss 1.3641 (0.8452) lr 6.9098e-04 eta 0:28:28
epoch [36/50] batch [80/204] time 0.555 (0.567) data 0.000 (0.007) loss 0.5088 (0.9198) lr 6.9098e-04 eta 0:28:09
epoch [36/50] batch [100/204] time 0.560 (0.565) data 0.000 (0.006) loss 0.8758 (0.9467) lr 6.9098e-04 eta 0:27:53
epoch [36/50] batch [120/204] time 0.562 (0.564) data 0.000 (0.005) loss 0.2812 (0.9282) lr 6.9098e-04 eta 0:27:39
epoch [36/50] batch [140/204] time 0.555 (0.553) data 0.000 (0.004) loss 1.4241 (0.8950) lr 6.9098e-04 eta 0:26:54
epoch [36/50] batch [160/204] time 0.579 (0.555) data 0.000 (0.004) loss 2.4109 (0.9236) lr 6.9098e-04 eta 0:26:49
epoch [36/50] batch [180/204] time 0.581 (0.556) data 0.000 (0.003) loss 2.0184 (0.9123) lr 6.9098e-04 eta 0:26:41
epoch [36/50] batch [200/204] time 0.569 (0.558) data 0.000 (0.003) loss 1.2007 (0.8967) lr 6.9098e-04 eta 0:26:34
epoch [37/50] batch [20/204] time 0.563 (0.466) data 0.000 (0.026) loss 0.5782 (0.8301) lr 6.3188e-04 eta 0:22:01
epoch [37/50] batch [40/204] time 0.557 (0.513) data 0.000 (0.013) loss 1.2460 (0.7795) lr 6.3188e-04 eta 0:24:05
epoch [37/50] batch [60/204] time 0.556 (0.529) data 0.000 (0.009) loss 0.4688 (0.8122) lr 6.3188e-04 eta 0:24:38
epoch [37/50] batch [80/204] time 0.554 (0.537) data 0.001 (0.007) loss 0.5118 (0.8054) lr 6.3188e-04 eta 0:24:49
epoch [37/50] batch [100/204] time 0.562 (0.541) data 0.000 (0.005) loss 0.5577 (0.8051) lr 6.3188e-04 eta 0:24:51
epoch [37/50] batch [120/204] time 0.559 (0.544) data 0.000 (0.005) loss 1.2835 (0.8169) lr 6.3188e-04 eta 0:24:49
epoch [37/50] batch [140/204] time 0.562 (0.547) data 0.000 (0.004) loss 0.5055 (0.8369) lr 6.3188e-04 eta 0:24:44
epoch [37/50] batch [160/204] time 0.560 (0.548) data 0.000 (0.003) loss 0.5609 (0.8625) lr 6.3188e-04 eta 0:24:38
epoch [37/50] batch [180/204] time 0.563 (0.550) data 0.000 (0.003) loss 0.1642 (0.8795) lr 6.3188e-04 eta 0:24:31
epoch [37/50] batch [200/204] time 0.562 (0.551) data 0.000 (0.003) loss 1.4687 (0.8821) lr 6.3188e-04 eta 0:24:22
epoch [38/50] batch [20/204] time 0.560 (0.586) data 0.000 (0.026) loss 0.6594 (0.8995) lr 5.7422e-04 eta 0:25:42
epoch [38/50] batch [40/204] time 0.558 (0.573) data 0.000 (0.013) loss 0.5108 (0.8711) lr 5.7422e-04 eta 0:24:57
epoch [38/50] batch [60/204] time 0.563 (0.569) data 0.000 (0.009) loss 2.0809 (0.9512) lr 5.7422e-04 eta 0:24:34
epoch [38/50] batch [80/204] time 0.560 (0.567) data 0.000 (0.007) loss 2.5253 (0.9070) lr 5.7422e-04 eta 0:24:17
epoch [38/50] batch [100/204] time 0.556 (0.565) data 0.000 (0.005) loss 1.4787 (0.9308) lr 5.7422e-04 eta 0:24:02
epoch [38/50] batch [120/204] time 0.566 (0.564) data 0.000 (0.004) loss 0.2480 (0.9044) lr 5.7422e-04 eta 0:23:49
epoch [38/50] batch [140/204] time 0.557 (0.564) data 0.000 (0.004) loss 0.6016 (0.8869) lr 5.7422e-04 eta 0:23:36
epoch [38/50] batch [160/204] time 0.559 (0.563) data 0.000 (0.003) loss 0.4367 (0.8873) lr 5.7422e-04 eta 0:23:23
epoch [38/50] batch [180/204] time 0.561 (0.563) data 0.000 (0.003) loss 1.6277 (0.8907) lr 5.7422e-04 eta 0:23:11
epoch [38/50] batch [200/204] time 0.558 (0.563) data 0.000 (0.003) loss 0.7862 (0.8798) lr 5.7422e-04 eta 0:22:59
epoch [39/50] batch [20/204] time 0.563 (0.587) data 0.000 (0.026) loss 1.8125 (1.1576) lr 5.1825e-04 eta 0:23:44
epoch [39/50] batch [40/204] time 0.557 (0.573) data 0.000 (0.013) loss 0.9300 (0.9834) lr 5.1825e-04 eta 0:23:00
epoch [39/50] batch [60/204] time 0.556 (0.569) data 0.000 (0.009) loss 1.2582 (0.9304) lr 5.1825e-04 eta 0:22:38
epoch [39/50] batch [80/204] time 0.562 (0.566) data 0.000 (0.007) loss 0.6458 (0.8925) lr 5.1825e-04 eta 0:22:21
epoch [39/50] batch [100/204] time 0.557 (0.565) data 0.000 (0.005) loss 1.0005 (0.9459) lr 5.1825e-04 eta 0:22:06
epoch [39/50] batch [120/204] time 0.561 (0.564) data 0.000 (0.005) loss 0.0123 (0.8805) lr 5.1825e-04 eta 0:21:53
epoch [39/50] batch [140/204] time 0.557 (0.563) data 0.000 (0.004) loss 1.0903 (0.8932) lr 5.1825e-04 eta 0:21:40
epoch [39/50] batch [160/204] time 0.563 (0.563) data 0.000 (0.003) loss 1.2192 (0.8914) lr 5.1825e-04 eta 0:21:28
epoch [39/50] batch [180/204] time 0.556 (0.563) data 0.000 (0.003) loss 2.7426 (0.8967) lr 5.1825e-04 eta 0:21:16
epoch [39/50] batch [200/204] time 0.560 (0.563) data 0.000 (0.003) loss 0.2353 (0.8766) lr 5.1825e-04 eta 0:21:04
epoch [40/50] batch [20/204] time 0.560 (0.584) data 0.000 (0.026) loss 0.5348 (0.9948) lr 4.6417e-04 eta 0:21:38
epoch [40/50] batch [40/204] time 0.562 (0.570) data 0.000 (0.013) loss 0.5198 (1.0617) lr 4.6417e-04 eta 0:20:56
epoch [40/50] batch [60/204] time 0.565 (0.566) data 0.000 (0.009) loss 1.4933 (0.9512) lr 4.6417e-04 eta 0:20:36
epoch [40/50] batch [80/204] time 0.564 (0.564) data 0.000 (0.007) loss 0.6019 (0.9237) lr 4.6417e-04 eta 0:20:21
epoch [40/50] batch [100/204] time 0.559 (0.563) data 0.000 (0.005) loss 0.1731 (0.9456) lr 4.6417e-04 eta 0:20:07
epoch [40/50] batch [120/204] time 0.559 (0.562) data 0.000 (0.005) loss 1.3466 (0.8940) lr 4.6417e-04 eta 0:19:54
epoch [40/50] batch [140/204] time 0.554 (0.562) data 0.000 (0.004) loss 0.8676 (0.8710) lr 4.6417e-04 eta 0:19:42
epoch [40/50] batch [160/204] time 0.558 (0.561) data 0.000 (0.003) loss 1.3028 (0.8907) lr 4.6417e-04 eta 0:19:29
epoch [40/50] batch [180/204] time 0.561 (0.561) data 0.000 (0.003) loss 0.2184 (0.8818) lr 4.6417e-04 eta 0:19:18
epoch [40/50] batch [200/204] time 0.560 (0.561) data 0.000 (0.003) loss 0.8534 (0.8901) lr 4.6417e-04 eta 0:19:06
epoch [41/50] batch [20/204] time 0.560 (0.585) data 0.000 (0.026) loss 1.7952 (0.7951) lr 4.1221e-04 eta 0:19:41
epoch [41/50] batch [40/204] time 0.557 (0.572) data 0.000 (0.013) loss 0.8185 (0.9340) lr 4.1221e-04 eta 0:19:04
epoch [41/50] batch [60/204] time 0.563 (0.568) data 0.000 (0.009) loss 0.9944 (0.8247) lr 4.1221e-04 eta 0:18:43
epoch [41/50] batch [80/204] time 0.563 (0.566) data 0.000 (0.007) loss 1.7911 (0.9067) lr 4.1221e-04 eta 0:18:28
epoch [41/50] batch [100/204] time 0.564 (0.564) data 0.000 (0.005) loss 0.1950 (0.8817) lr 4.1221e-04 eta 0:18:14
epoch [41/50] batch [120/204] time 0.557 (0.563) data 0.000 (0.004) loss 1.0810 (0.8858) lr 4.1221e-04 eta 0:18:01
epoch [41/50] batch [140/204] time 0.555 (0.563) data 0.000 (0.004) loss 0.4770 (0.8620) lr 4.1221e-04 eta 0:17:49
epoch [41/50] batch [160/204] time 0.559 (0.562) data 0.000 (0.003) loss 0.2242 (0.8595) lr 4.1221e-04 eta 0:17:36
epoch [41/50] batch [180/204] time 0.249 (0.556) data 0.000 (0.003) loss 0.4868 (0.8415) lr 4.1221e-04 eta 0:17:13
epoch [41/50] batch [200/204] time 0.558 (0.554) data 0.000 (0.003) loss 1.6905 (0.8313) lr 4.1221e-04 eta 0:16:59
epoch [42/50] batch [20/204] time 0.556 (0.595) data 0.000 (0.028) loss 1.6800 (0.6723) lr 3.6258e-04 eta 0:18:00
epoch [42/50] batch [40/204] time 0.563 (0.583) data 0.000 (0.014) loss 1.4621 (0.8012) lr 3.6258e-04 eta 0:17:26
epoch [42/50] batch [60/204] time 0.556 (0.561) data 0.000 (0.009) loss 0.9207 (0.7892) lr 3.6258e-04 eta 0:16:36
epoch [42/50] batch [80/204] time 0.560 (0.560) data 0.000 (0.007) loss 0.6079 (0.8485) lr 3.6258e-04 eta 0:16:23
epoch [42/50] batch [100/204] time 0.554 (0.560) data 0.000 (0.006) loss 0.2742 (0.8230) lr 3.6258e-04 eta 0:16:11
epoch [42/50] batch [120/204] time 0.558 (0.560) data 0.000 (0.005) loss 1.0064 (0.8102) lr 3.6258e-04 eta 0:16:00
epoch [42/50] batch [140/204] time 0.562 (0.560) data 0.000 (0.004) loss 0.8695 (0.8010) lr 3.6258e-04 eta 0:15:49
epoch [42/50] batch [160/204] time 0.553 (0.560) data 0.000 (0.004) loss 0.2029 (0.8078) lr 3.6258e-04 eta 0:15:38
epoch [42/50] batch [180/204] time 0.557 (0.560) data 0.000 (0.003) loss 0.5517 (0.8049) lr 3.6258e-04 eta 0:15:27
epoch [42/50] batch [200/204] time 0.561 (0.560) data 0.000 (0.003) loss 1.2983 (0.8271) lr 3.6258e-04 eta 0:15:16
epoch [43/50] batch [20/204] time 0.558 (0.585) data 0.000 (0.026) loss 0.5952 (0.7439) lr 3.1545e-04 eta 0:15:42
epoch [43/50] batch [40/204] time 0.559 (0.572) data 0.000 (0.013) loss 0.0435 (0.8658) lr 3.1545e-04 eta 0:15:10
epoch [43/50] batch [60/204] time 0.559 (0.567) data 0.000 (0.009) loss 0.7620 (0.8494) lr 3.1545e-04 eta 0:14:50
epoch [43/50] batch [80/204] time 0.557 (0.565) data 0.000 (0.007) loss 0.7760 (0.8282) lr 3.1545e-04 eta 0:14:36
epoch [43/50] batch [100/204] time 0.560 (0.564) data 0.000 (0.005) loss 0.4519 (0.8228) lr 3.1545e-04 eta 0:14:23
epoch [43/50] batch [120/204] time 0.560 (0.563) data 0.000 (0.005) loss 1.9882 (0.8309) lr 3.1545e-04 eta 0:14:11
epoch [43/50] batch [140/204] time 0.563 (0.563) data 0.000 (0.004) loss 0.4388 (0.8351) lr 3.1545e-04 eta 0:13:59
epoch [43/50] batch [160/204] time 0.554 (0.562) data 0.000 (0.004) loss 1.0347 (0.8301) lr 3.1545e-04 eta 0:13:47
epoch [43/50] batch [180/204] time 0.558 (0.562) data 0.000 (0.003) loss 0.9773 (0.8223) lr 3.1545e-04 eta 0:13:35
epoch [43/50] batch [200/204] time 0.561 (0.562) data 0.000 (0.003) loss 0.1658 (0.8076) lr 3.1545e-04 eta 0:13:24
epoch [44/50] batch [20/204] time 0.558 (0.585) data 0.000 (0.026) loss 0.6997 (0.7252) lr 2.7103e-04 eta 0:13:43
epoch [44/50] batch [40/204] time 0.556 (0.572) data 0.000 (0.013) loss 0.2349 (0.8100) lr 2.7103e-04 eta 0:13:13
epoch [44/50] batch [60/204] time 0.559 (0.567) data 0.000 (0.009) loss 0.0748 (0.8106) lr 2.7103e-04 eta 0:12:56
epoch [44/50] batch [80/204] time 0.563 (0.565) data 0.000 (0.007) loss 0.9926 (0.8792) lr 2.7103e-04 eta 0:12:41
epoch [44/50] batch [100/204] time 0.554 (0.564) data 0.007 (0.005) loss 0.2496 (0.8660) lr 2.7103e-04 eta 0:12:29
epoch [44/50] batch [120/204] time 0.555 (0.563) data 0.000 (0.005) loss 0.5612 (0.8879) lr 2.7103e-04 eta 0:12:16
epoch [44/50] batch [140/204] time 0.556 (0.563) data 0.000 (0.004) loss 0.4425 (0.8841) lr 2.7103e-04 eta 0:12:04
epoch [44/50] batch [160/204] time 0.567 (0.562) data 0.000 (0.003) loss 0.4479 (0.8506) lr 2.7103e-04 eta 0:11:53
epoch [44/50] batch [180/204] time 0.562 (0.562) data 0.000 (0.003) loss 0.9483 (0.8671) lr 2.7103e-04 eta 0:11:41
epoch [44/50] batch [200/204] time 0.557 (0.562) data 0.000 (0.003) loss 0.5156 (0.8588) lr 2.7103e-04 eta 0:11:30
epoch [45/50] batch [20/204] time 0.564 (0.586) data 0.000 (0.026) loss 2.4256 (0.8299) lr 2.2949e-04 eta 0:11:45
epoch [45/50] batch [40/204] time 0.559 (0.572) data 0.000 (0.013) loss 0.5466 (0.8573) lr 2.2949e-04 eta 0:11:17
epoch [45/50] batch [60/204] time 0.559 (0.568) data 0.000 (0.009) loss 0.6752 (0.9039) lr 2.2949e-04 eta 0:11:01
epoch [45/50] batch [80/204] time 0.561 (0.566) data 0.000 (0.007) loss 0.7633 (0.8798) lr 2.2949e-04 eta 0:10:47
epoch [45/50] batch [100/204] time 0.562 (0.565) data 0.000 (0.005) loss 1.3052 (0.8777) lr 2.2949e-04 eta 0:10:35
epoch [45/50] batch [120/204] time 0.561 (0.564) data 0.000 (0.004) loss 1.5301 (0.8865) lr 2.2949e-04 eta 0:10:23
epoch [45/50] batch [140/204] time 0.561 (0.564) data 0.000 (0.004) loss 0.9334 (0.8892) lr 2.2949e-04 eta 0:10:11
epoch [45/50] batch [160/204] time 0.565 (0.563) data 0.000 (0.003) loss 0.2027 (0.8552) lr 2.2949e-04 eta 0:09:59
epoch [45/50] batch [180/204] time 0.558 (0.563) data 0.000 (0.003) loss 0.7813 (0.8624) lr 2.2949e-04 eta 0:09:47
epoch [45/50] batch [200/204] time 0.561 (0.562) data 0.000 (0.003) loss 0.5944 (0.8701) lr 2.2949e-04 eta 0:09:35
epoch [46/50] batch [20/204] time 0.561 (0.587) data 0.000 (0.026) loss 0.9705 (1.0105) lr 1.9098e-04 eta 0:09:47
epoch [46/50] batch [40/204] time 0.559 (0.574) data 0.000 (0.013) loss 1.3502 (0.9570) lr 1.9098e-04 eta 0:09:22
epoch [46/50] batch [60/204] time 0.561 (0.570) data 0.000 (0.009) loss 0.2035 (0.9359) lr 1.9098e-04 eta 0:09:07
epoch [46/50] batch [80/204] time 0.562 (0.568) data 0.000 (0.007) loss 0.8098 (0.8697) lr 1.9098e-04 eta 0:08:53
epoch [46/50] batch [100/204] time 0.563 (0.566) data 0.000 (0.005) loss 2.7283 (0.8522) lr 1.9098e-04 eta 0:08:41
epoch [46/50] batch [120/204] time 0.562 (0.565) data 0.000 (0.004) loss 0.9172 (0.8794) lr 1.9098e-04 eta 0:08:28
epoch [46/50] batch [140/204] time 0.563 (0.565) data 0.000 (0.004) loss 1.1330 (0.8871) lr 1.9098e-04 eta 0:08:16
epoch [46/50] batch [160/204] time 0.561 (0.564) data 0.000 (0.003) loss 0.6494 (0.8758) lr 1.9098e-04 eta 0:08:05
epoch [46/50] batch [180/204] time 0.561 (0.564) data 0.000 (0.003) loss 0.0093 (0.8871) lr 1.9098e-04 eta 0:07:53
epoch [46/50] batch [200/204] time 0.559 (0.563) data 0.000 (0.003) loss 1.1076 (0.8849) lr 1.9098e-04 eta 0:07:41
epoch [47/50] batch [20/204] time 0.570 (0.508) data 0.000 (0.026) loss 1.7158 (0.7234) lr 1.5567e-04 eta 0:06:44
epoch [47/50] batch [40/204] time 0.581 (0.540) data 0.000 (0.014) loss 0.5843 (0.7281) lr 1.5567e-04 eta 0:06:58
epoch [47/50] batch [60/204] time 0.571 (0.552) data 0.001 (0.009) loss 0.0758 (0.7291) lr 1.5567e-04 eta 0:06:57
epoch [47/50] batch [80/204] time 0.584 (0.558) data 0.000 (0.007) loss 0.4900 (0.8089) lr 1.5567e-04 eta 0:06:50
epoch [47/50] batch [100/204] time 0.253 (0.555) data 0.000 (0.006) loss 3.3577 (0.8727) lr 1.5567e-04 eta 0:06:37
epoch [47/50] batch [120/204] time 0.564 (0.541) data 0.000 (0.005) loss 1.4499 (0.8785) lr 1.5567e-04 eta 0:06:16
epoch [47/50] batch [140/204] time 0.562 (0.544) data 0.000 (0.004) loss 0.8265 (0.8721) lr 1.5567e-04 eta 0:06:07
epoch [47/50] batch [160/204] time 0.560 (0.546) data 0.000 (0.004) loss 0.0456 (0.8610) lr 1.5567e-04 eta 0:05:58
epoch [47/50] batch [180/204] time 0.560 (0.547) data 0.000 (0.003) loss 0.4653 (0.8508) lr 1.5567e-04 eta 0:05:48
epoch [47/50] batch [200/204] time 0.561 (0.549) data 0.000 (0.003) loss 1.4195 (0.8354) lr 1.5567e-04 eta 0:05:37
epoch [48/50] batch [20/204] time 0.560 (0.585) data 0.000 (0.026) loss 1.2242 (0.8566) lr 1.2369e-04 eta 0:05:46
epoch [48/50] batch [40/204] time 0.556 (0.572) data 0.000 (0.013) loss 0.5488 (0.8209) lr 1.2369e-04 eta 0:05:27
epoch [48/50] batch [60/204] time 0.551 (0.568) data 0.000 (0.009) loss 1.4074 (0.7799) lr 1.2369e-04 eta 0:05:13
epoch [48/50] batch [80/204] time 0.557 (0.566) data 0.000 (0.007) loss 0.2766 (0.7819) lr 1.2369e-04 eta 0:05:00
epoch [48/50] batch [100/204] time 0.558 (0.564) data 0.000 (0.005) loss 1.1857 (0.7762) lr 1.2369e-04 eta 0:04:48
epoch [48/50] batch [120/204] time 0.560 (0.563) data 0.000 (0.005) loss 0.4075 (0.7759) lr 1.2369e-04 eta 0:04:37
epoch [48/50] batch [140/204] time 0.559 (0.563) data 0.000 (0.004) loss 1.5609 (0.7854) lr 1.2369e-04 eta 0:04:25
epoch [48/50] batch [160/204] time 0.559 (0.562) data 0.000 (0.003) loss 0.4664 (0.7923) lr 1.2369e-04 eta 0:04:14
epoch [48/50] batch [180/204] time 0.559 (0.562) data 0.000 (0.003) loss 1.3249 (0.7957) lr 1.2369e-04 eta 0:04:02
epoch [48/50] batch [200/204] time 0.560 (0.562) data 0.000 (0.003) loss 0.8349 (0.8052) lr 1.2369e-04 eta 0:03:51
epoch [49/50] batch [20/204] time 0.563 (0.585) data 0.000 (0.026) loss 1.9979 (0.7936) lr 9.5173e-05 eta 0:03:46
epoch [49/50] batch [40/204] time 0.556 (0.572) data 0.000 (0.013) loss 0.0414 (0.7469) lr 9.5173e-05 eta 0:03:30
epoch [49/50] batch [60/204] time 0.555 (0.568) data 0.000 (0.009) loss 0.4630 (0.7239) lr 9.5173e-05 eta 0:03:17
epoch [49/50] batch [80/204] time 0.559 (0.566) data 0.000 (0.007) loss 0.0138 (0.7687) lr 9.5173e-05 eta 0:03:05
epoch [49/50] batch [100/204] time 0.564 (0.564) data 0.000 (0.005) loss 0.8085 (0.7951) lr 9.5173e-05 eta 0:02:53
epoch [49/50] batch [120/204] time 0.555 (0.563) data 0.000 (0.005) loss 0.9946 (0.7849) lr 9.5173e-05 eta 0:02:42
epoch [49/50] batch [140/204] time 0.554 (0.563) data 0.000 (0.004) loss 0.0360 (0.7642) lr 9.5173e-05 eta 0:02:30
epoch [49/50] batch [160/204] time 0.550 (0.562) data 0.000 (0.003) loss 0.7494 (0.7600) lr 9.5173e-05 eta 0:02:19
epoch [49/50] batch [180/204] time 0.563 (0.562) data 0.000 (0.003) loss 0.7629 (0.7801) lr 9.5173e-05 eta 0:02:08
epoch [49/50] batch [200/204] time 0.557 (0.562) data 0.000 (0.003) loss 0.8082 (0.7916) lr 9.5173e-05 eta 0:01:56
epoch [50/50] batch [20/204] time 0.558 (0.584) data 0.000 (0.026) loss 1.2042 (1.0933) lr 7.0224e-05 eta 0:01:47
epoch [50/50] batch [40/204] time 0.558 (0.571) data 0.000 (0.013) loss 0.0683 (1.0766) lr 7.0224e-05 eta 0:01:33
epoch [50/50] batch [60/204] time 0.556 (0.567) data 0.000 (0.009) loss 0.1060 (0.9851) lr 7.0224e-05 eta 0:01:21
epoch [50/50] batch [80/204] time 0.557 (0.565) data 0.000 (0.007) loss 0.3070 (0.9324) lr 7.0224e-05 eta 0:01:10
epoch [50/50] batch [100/204] time 0.556 (0.563) data 0.000 (0.005) loss 0.7358 (0.9239) lr 7.0224e-05 eta 0:00:58
epoch [50/50] batch [120/204] time 0.559 (0.563) data 0.000 (0.004) loss 1.1933 (0.9269) lr 7.0224e-05 eta 0:00:47
epoch [50/50] batch [140/204] time 0.548 (0.562) data 0.000 (0.004) loss 0.3391 (0.9120) lr 7.0224e-05 eta 0:00:35
epoch [50/50] batch [160/204] time 0.555 (0.561) data 0.000 (0.003) loss 0.3089 (0.8625) lr 7.0224e-05 eta 0:00:24
epoch [50/50] batch [180/204] time 0.561 (0.561) data 0.000 (0.003) loss 0.3646 (0.8705) lr 7.0224e-05 eta 0:00:13
epoch [50/50] batch [200/204] time 0.553 (0.561) data 0.000 (0.003) loss 1.0723 (0.8631) lr 7.0224e-05 eta 0:00:02
Checkpoint saved to output/base2new/train_base/ucf101/vit_b16_ep50_c4_BZ4_ProDA/seed2/prompt_learner/model.pth.tar-50
Finish training
Deploy the last-epoch model
Evaluate on the *test* set
=> result
* total: 1,860
* correct: 1,638
* accuracy: 88.06%
* error: 11.94%
* macro_f1: 87.66%
Elapsed: 1:36:48
