***************
** 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/seed1
resume: 
root: /mnt/hdd/DATA
seed: 1
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/seed1
RESUME: 
SEED: 1
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:                 97%
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_1.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     1,946
---------  ------
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/seed1/tensorboard)
epoch [1/50] batch [20/204] time 0.563 (1.087) data 0.001 (0.078) loss 1.5489 (1.9059) lr 1.0000e-05 eta 3:04:28
epoch [1/50] batch [40/204] time 0.571 (0.829) data 0.001 (0.040) loss 3.0142 (2.1313) lr 1.0000e-05 eta 2:20:23
epoch [1/50] batch [60/204] time 0.565 (0.747) data 0.001 (0.027) loss 1.0900 (2.0631) lr 1.0000e-05 eta 2:06:09
epoch [1/50] batch [80/204] time 0.557 (0.702) data 0.000 (0.020) loss 1.1636 (2.0107) lr 1.0000e-05 eta 1:58:21
epoch [1/50] batch [100/204] time 0.569 (0.675) data 0.001 (0.016) loss 1.6195 (1.9348) lr 1.0000e-05 eta 1:53:35
epoch [1/50] batch [120/204] time 0.568 (0.657) data 0.000 (0.014) loss 0.4279 (1.8821) lr 1.0000e-05 eta 1:50:20
epoch [1/50] batch [140/204] time 0.559 (0.644) data 0.001 (0.012) loss 1.1329 (1.8390) lr 1.0000e-05 eta 1:47:57
epoch [1/50] batch [160/204] time 0.556 (0.634) data 0.001 (0.010) loss 4.0005 (1.9060) lr 1.0000e-05 eta 1:46:09
epoch [1/50] batch [180/204] time 0.558 (0.627) data 0.000 (0.009) loss 3.4195 (1.8931) lr 1.0000e-05 eta 1:44:42
epoch [1/50] batch [200/204] time 0.575 (0.621) data 0.000 (0.008) loss 1.1120 (1.9060) lr 1.0000e-05 eta 1:43:29
epoch [2/50] batch [20/204] time 0.584 (0.529) data 0.001 (0.098) loss 2.0755 (1.8063) lr 1.0000e-05 eta 1:27:55
epoch [2/50] batch [40/204] time 0.595 (0.551) data 0.000 (0.049) loss 3.4186 (1.8706) lr 1.0000e-05 eta 1:31:25
epoch [2/50] batch [60/204] time 0.573 (0.558) data 0.001 (0.033) loss 2.0216 (1.8864) lr 1.0000e-05 eta 1:32:25
epoch [2/50] batch [80/204] time 0.572 (0.562) data 0.000 (0.025) loss 3.3752 (1.9271) lr 1.0000e-05 eta 1:32:49
epoch [2/50] batch [100/204] time 0.555 (0.552) data 0.000 (0.020) loss 2.0055 (1.9286) lr 1.0000e-05 eta 1:30:57
epoch [2/50] batch [120/204] time 0.558 (0.553) data 0.000 (0.017) loss 2.6141 (1.9177) lr 1.0000e-05 eta 1:30:58
epoch [2/50] batch [140/204] time 0.559 (0.554) data 0.000 (0.014) loss 0.4300 (1.9479) lr 1.0000e-05 eta 1:30:55
epoch [2/50] batch [160/204] time 0.559 (0.554) data 0.000 (0.013) loss 2.8822 (1.9051) lr 1.0000e-05 eta 1:30:47
epoch [2/50] batch [180/204] time 0.562 (0.554) data 0.000 (0.011) loss 2.8156 (1.8436) lr 1.0000e-05 eta 1:30:39
epoch [2/50] batch [200/204] time 0.563 (0.555) data 0.000 (0.010) loss 1.0609 (1.8157) lr 1.0000e-05 eta 1:30:33
epoch [3/50] batch [20/204] time 0.556 (0.589) data 0.000 (0.031) loss 0.5622 (1.4325) lr 1.0000e-05 eta 1:35:54
epoch [3/50] batch [40/204] time 0.558 (0.574) data 0.000 (0.016) loss 1.2042 (1.5185) lr 1.0000e-05 eta 1:33:16
epoch [3/50] batch [60/204] time 0.558 (0.569) data 0.000 (0.011) loss 2.5520 (1.6248) lr 1.0000e-05 eta 1:32:16
epoch [3/50] batch [80/204] time 0.558 (0.566) data 0.000 (0.008) loss 0.9421 (1.6373) lr 1.0000e-05 eta 1:31:41
epoch [3/50] batch [100/204] time 0.561 (0.565) data 0.000 (0.006) loss 2.6000 (1.6445) lr 1.0000e-05 eta 1:31:16
epoch [3/50] batch [120/204] time 0.557 (0.564) data 0.000 (0.005) loss 2.6315 (1.6737) lr 1.0000e-05 eta 1:30:55
epoch [3/50] batch [140/204] time 0.560 (0.563) data 0.000 (0.005) loss 2.3338 (1.7039) lr 1.0000e-05 eta 1:30:38
epoch [3/50] batch [160/204] time 0.560 (0.563) data 0.000 (0.004) loss 1.8187 (1.7074) lr 1.0000e-05 eta 1:30:23
epoch [3/50] batch [180/204] time 0.560 (0.563) data 0.000 (0.004) loss 0.3803 (1.7098) lr 1.0000e-05 eta 1:30:08
epoch [3/50] batch [200/204] time 0.558 (0.562) data 0.000 (0.003) loss 3.1572 (1.7031) lr 1.0000e-05 eta 1:29:53
epoch [4/50] batch [20/204] time 0.560 (0.588) data 0.000 (0.031) loss 2.1313 (1.9790) lr 1.0000e-05 eta 1:33:49
epoch [4/50] batch [40/204] time 0.558 (0.573) data 0.000 (0.015) loss 0.4050 (1.8923) lr 1.0000e-05 eta 1:31:14
epoch [4/50] batch [60/204] time 0.562 (0.568) data 0.000 (0.010) loss 1.1105 (1.7970) lr 1.0000e-05 eta 1:30:15
epoch [4/50] batch [80/204] time 0.559 (0.566) data 0.000 (0.008) loss 2.5852 (1.6899) lr 1.0000e-05 eta 1:29:41
epoch [4/50] batch [100/204] time 0.563 (0.565) data 0.000 (0.006) loss 1.8211 (1.6482) lr 1.0000e-05 eta 1:29:16
epoch [4/50] batch [120/204] time 0.559 (0.563) data 0.000 (0.005) loss 4.0989 (1.6978) lr 1.0000e-05 eta 1:28:55
epoch [4/50] batch [140/204] time 0.555 (0.563) data 0.000 (0.005) loss 2.1260 (1.7001) lr 1.0000e-05 eta 1:28:36
epoch [4/50] batch [160/204] time 0.559 (0.562) data 0.000 (0.004) loss 1.7501 (1.6941) lr 1.0000e-05 eta 1:28:20
epoch [4/50] batch [180/204] time 0.552 (0.562) data 0.000 (0.004) loss 2.6074 (1.7083) lr 1.0000e-05 eta 1:28:05
epoch [4/50] batch [200/204] time 0.553 (0.561) data 0.000 (0.003) loss 1.7011 (1.6986) lr 1.0000e-05 eta 1:27:51
epoch [5/50] batch [20/204] time 0.559 (0.589) data 0.000 (0.030) loss 1.3954 (1.4548) lr 1.0000e-05 eta 1:31:56
epoch [5/50] batch [40/204] time 0.563 (0.575) data 0.000 (0.015) loss 0.7094 (1.6526) lr 1.0000e-05 eta 1:29:29
epoch [5/50] batch [60/204] time 0.560 (0.570) data 0.000 (0.010) loss 1.7755 (1.6675) lr 1.0000e-05 eta 1:28:32
epoch [5/50] batch [80/204] time 0.558 (0.567) data 0.000 (0.008) loss 3.2033 (1.6943) lr 1.0000e-05 eta 1:27:56
epoch [5/50] batch [100/204] time 0.563 (0.566) data 0.000 (0.006) loss 1.6205 (1.6861) lr 1.0000e-05 eta 1:27:30
epoch [5/50] batch [120/204] time 0.568 (0.564) data 0.000 (0.005) loss 3.3724 (1.6560) lr 1.0000e-05 eta 1:27:09
epoch [5/50] batch [140/204] time 0.558 (0.564) data 0.000 (0.004) loss 3.4416 (1.6749) lr 1.0000e-05 eta 1:26:51
epoch [5/50] batch [160/204] time 0.565 (0.563) data 0.000 (0.004) loss 1.8885 (1.6790) lr 1.0000e-05 eta 1:26:35
epoch [5/50] batch [180/204] time 0.569 (0.563) data 0.000 (0.004) loss 2.1724 (1.6881) lr 1.0000e-05 eta 1:26:21
epoch [5/50] batch [200/204] time 0.557 (0.563) data 0.000 (0.003) loss 1.6891 (1.6761) lr 1.0000e-05 eta 1:26:06
epoch [6/50] batch [20/204] time 0.563 (0.590) data 0.000 (0.030) loss 1.1079 (1.8118) lr 2.0000e-03 eta 1:30:07
epoch [6/50] batch [40/204] time 0.562 (0.575) data 0.000 (0.015) loss 0.6819 (1.7533) lr 2.0000e-03 eta 1:27:31
epoch [6/50] batch [60/204] time 0.557 (0.569) data 0.000 (0.010) loss 2.3429 (1.7939) lr 2.0000e-03 eta 1:26:32
epoch [6/50] batch [80/204] time 0.557 (0.567) data 0.000 (0.008) loss 0.8854 (1.7181) lr 2.0000e-03 eta 1:25:56
epoch [6/50] batch [100/204] time 0.561 (0.565) data 0.000 (0.006) loss 3.7006 (1.7233) lr 2.0000e-03 eta 1:25:34
epoch [6/50] batch [120/204] time 0.558 (0.565) data 0.000 (0.005) loss 1.4411 (1.6570) lr 2.0000e-03 eta 1:25:15
epoch [6/50] batch [140/204] time 0.560 (0.564) data 0.000 (0.005) loss 1.1505 (1.6516) lr 2.0000e-03 eta 1:25:00
epoch [6/50] batch [160/204] time 0.564 (0.564) data 0.000 (0.004) loss 1.6602 (1.6436) lr 2.0000e-03 eta 1:24:45
epoch [6/50] batch [180/204] time 0.557 (0.564) data 0.000 (0.004) loss 2.6176 (1.6448) lr 2.0000e-03 eta 1:24:31
epoch [6/50] batch [200/204] time 0.560 (0.563) data 0.000 (0.003) loss 1.5191 (1.6318) lr 2.0000e-03 eta 1:24:17
epoch [7/50] batch [20/204] time 0.559 (0.589) data 0.000 (0.030) loss 1.8379 (1.5549) lr 1.9980e-03 eta 1:27:58
epoch [7/50] batch [40/204] time 0.561 (0.574) data 0.000 (0.016) loss 0.7530 (1.4427) lr 1.9980e-03 eta 1:25:32
epoch [7/50] batch [60/204] time 0.577 (0.539) data 0.000 (0.010) loss 1.3648 (1.3943) lr 1.9980e-03 eta 1:20:07
epoch [7/50] batch [80/204] time 0.560 (0.548) data 0.000 (0.008) loss 0.7247 (1.3260) lr 1.9980e-03 eta 1:21:12
epoch [7/50] batch [100/204] time 0.543 (0.552) data 0.000 (0.006) loss 0.5683 (1.2837) lr 1.9980e-03 eta 1:21:43
epoch [7/50] batch [120/204] time 0.575 (0.556) data 0.000 (0.005) loss 0.9694 (1.2827) lr 1.9980e-03 eta 1:22:03
epoch [7/50] batch [140/204] time 0.280 (0.551) data 0.000 (0.005) loss 0.1780 (1.3099) lr 1.9980e-03 eta 1:21:08
epoch [7/50] batch [160/204] time 0.557 (0.541) data 0.000 (0.004) loss 0.5148 (1.3511) lr 1.9980e-03 eta 1:19:28
epoch [7/50] batch [180/204] time 0.576 (0.544) data 0.000 (0.004) loss 1.8064 (1.3162) lr 1.9980e-03 eta 1:19:44
epoch [7/50] batch [200/204] time 0.563 (0.546) data 0.000 (0.003) loss 1.2812 (1.3333) lr 1.9980e-03 eta 1:19:52
epoch [8/50] batch [20/204] time 0.252 (0.557) data 0.000 (0.033) loss 2.1025 (1.6223) lr 1.9921e-03 eta 1:21:11
epoch [8/50] batch [40/204] time 0.251 (0.404) data 0.000 (0.017) loss 0.8699 (1.2917) lr 1.9921e-03 eta 0:58:45
epoch [8/50] batch [60/204] time 0.246 (0.353) data 0.000 (0.011) loss 1.2783 (1.3100) lr 1.9921e-03 eta 0:51:12
epoch [8/50] batch [80/204] time 0.284 (0.328) data 0.000 (0.008) loss 1.3502 (1.2962) lr 1.9921e-03 eta 0:47:32
epoch [8/50] batch [100/204] time 0.291 (0.318) data 0.000 (0.007) loss 0.1961 (1.2731) lr 1.9921e-03 eta 0:45:56
epoch [8/50] batch [120/204] time 0.567 (0.333) data 0.000 (0.006) loss 1.5082 (1.2685) lr 1.9921e-03 eta 0:48:05
epoch [8/50] batch [140/204] time 0.565 (0.368) data 0.000 (0.005) loss 2.4446 (1.3019) lr 1.9921e-03 eta 0:52:54
epoch [8/50] batch [160/204] time 0.565 (0.393) data 0.000 (0.004) loss 1.3374 (1.3204) lr 1.9921e-03 eta 0:56:25
epoch [8/50] batch [180/204] time 0.567 (0.413) data 0.000 (0.004) loss 0.4102 (1.2744) lr 1.9921e-03 eta 0:59:09
epoch [8/50] batch [200/204] time 0.251 (0.414) data 0.000 (0.004) loss 1.0282 (1.2553) lr 1.9921e-03 eta 0:59:05
epoch [9/50] batch [20/204] time 0.253 (0.281) data 0.000 (0.030) loss 1.7878 (0.8871) lr 1.9823e-03 eta 0:40:00
epoch [9/50] batch [40/204] time 0.277 (0.275) data 0.002 (0.015) loss 1.4526 (1.0832) lr 1.9823e-03 eta 0:39:08
epoch [9/50] batch [60/204] time 0.451 (0.292) data 0.000 (0.010) loss 1.2376 (1.1094) lr 1.9823e-03 eta 0:41:23
epoch [9/50] batch [80/204] time 0.447 (0.310) data 0.000 (0.008) loss 1.3202 (1.1551) lr 1.9823e-03 eta 0:43:54
epoch [9/50] batch [100/204] time 0.449 (0.317) data 0.000 (0.006) loss 0.4281 (1.1862) lr 1.9823e-03 eta 0:44:45
epoch [9/50] batch [120/204] time 0.456 (0.323) data 0.000 (0.005) loss 2.1045 (1.1658) lr 1.9823e-03 eta 0:45:24
epoch [9/50] batch [140/204] time 0.448 (0.326) data 0.000 (0.005) loss 1.1132 (1.1769) lr 1.9823e-03 eta 0:45:47
epoch [9/50] batch [160/204] time 0.449 (0.328) data 0.000 (0.004) loss 1.7885 (1.2264) lr 1.9823e-03 eta 0:46:01
epoch [9/50] batch [180/204] time 0.456 (0.335) data 0.000 (0.004) loss 0.8687 (1.2174) lr 1.9823e-03 eta 0:46:52
epoch [9/50] batch [200/204] time 0.457 (0.341) data 0.000 (0.003) loss 3.4450 (1.2356) lr 1.9823e-03 eta 0:47:33
epoch [10/50] batch [20/204] time 0.253 (0.305) data 0.000 (0.031) loss 0.6567 (1.3969) lr 1.9686e-03 eta 0:42:27
epoch [10/50] batch [40/204] time 0.253 (0.277) data 0.000 (0.016) loss 0.4221 (1.3085) lr 1.9686e-03 eta 0:38:29
epoch [10/50] batch [60/204] time 0.292 (0.275) data 0.000 (0.010) loss 1.1420 (1.3392) lr 1.9686e-03 eta 0:38:02
epoch [10/50] batch [80/204] time 0.284 (0.276) data 0.000 (0.008) loss 2.7883 (1.3184) lr 1.9686e-03 eta 0:38:04
epoch [10/50] batch [100/204] time 0.251 (0.276) data 0.000 (0.006) loss 1.3193 (1.3018) lr 1.9686e-03 eta 0:38:00
epoch [10/50] batch [120/204] time 0.252 (0.272) data 0.000 (0.005) loss 2.3185 (1.3053) lr 1.9686e-03 eta 0:37:18
epoch [10/50] batch [140/204] time 0.269 (0.271) data 0.000 (0.005) loss 0.1444 (1.2461) lr 1.9686e-03 eta 0:37:07
epoch [10/50] batch [160/204] time 0.473 (0.275) data 0.000 (0.004) loss 0.7497 (1.2428) lr 1.9686e-03 eta 0:37:38
epoch [10/50] batch [180/204] time 0.483 (0.298) data 0.000 (0.004) loss 1.7090 (1.2513) lr 1.9686e-03 eta 0:40:34
epoch [10/50] batch [200/204] time 0.472 (0.308) data 0.000 (0.003) loss 1.4097 (1.2376) lr 1.9686e-03 eta 0:41:54
epoch [11/50] batch [20/204] time 0.474 (0.404) data 0.000 (0.031) loss 0.2692 (1.1695) lr 1.9511e-03 eta 0:54:48
epoch [11/50] batch [40/204] time 0.461 (0.439) data 0.000 (0.015) loss 0.5077 (1.1023) lr 1.9511e-03 eta 0:59:26
epoch [11/50] batch [60/204] time 0.480 (0.417) data 0.000 (0.010) loss 0.3310 (1.1041) lr 1.9511e-03 eta 0:56:16
epoch [11/50] batch [80/204] time 0.342 (0.421) data 0.000 (0.008) loss 1.5797 (1.1633) lr 1.9511e-03 eta 0:56:37
epoch [11/50] batch [100/204] time 0.478 (0.419) data 0.000 (0.006) loss 0.8620 (1.1923) lr 1.9511e-03 eta 0:56:13
epoch [11/50] batch [120/204] time 0.250 (0.413) data 0.000 (0.005) loss 1.2900 (1.2548) lr 1.9511e-03 eta 0:55:22
epoch [11/50] batch [140/204] time 0.469 (0.420) data 0.000 (0.005) loss 1.8954 (1.2394) lr 1.9511e-03 eta 0:56:12
epoch [11/50] batch [160/204] time 0.479 (0.421) data 0.000 (0.004) loss 1.1177 (1.2236) lr 1.9511e-03 eta 0:56:07
epoch [11/50] batch [180/204] time 0.248 (0.424) data 0.000 (0.004) loss 1.2509 (1.2066) lr 1.9511e-03 eta 0:56:26
epoch [11/50] batch [200/204] time 0.476 (0.422) data 0.000 (0.003) loss 1.5449 (1.1899) lr 1.9511e-03 eta 0:55:56
epoch [12/50] batch [20/204] time 0.482 (0.453) data 0.000 (0.031) loss 1.5283 (1.0180) lr 1.9298e-03 eta 0:59:53
epoch [12/50] batch [40/204] time 0.254 (0.440) data 0.000 (0.015) loss 0.7245 (1.0923) lr 1.9298e-03 eta 0:58:05
epoch [12/50] batch [60/204] time 0.478 (0.432) data 0.000 (0.010) loss 1.5904 (1.0814) lr 1.9298e-03 eta 0:56:54
epoch [12/50] batch [80/204] time 0.243 (0.419) data 0.000 (0.008) loss 0.6909 (1.0882) lr 1.9298e-03 eta 0:55:02
epoch [12/50] batch [100/204] time 0.479 (0.428) data 0.000 (0.006) loss 0.7801 (1.0893) lr 1.9298e-03 eta 0:56:04
epoch [12/50] batch [120/204] time 0.479 (0.419) data 0.000 (0.005) loss 2.8577 (1.1501) lr 1.9298e-03 eta 0:54:41
epoch [12/50] batch [140/204] time 0.479 (0.427) data 0.000 (0.005) loss 1.3630 (1.1303) lr 1.9298e-03 eta 0:55:37
epoch [12/50] batch [160/204] time 0.464 (0.426) data 0.000 (0.004) loss 1.4947 (1.1387) lr 1.9298e-03 eta 0:55:19
epoch [12/50] batch [180/204] time 0.452 (0.425) data 0.000 (0.004) loss 1.2716 (1.1401) lr 1.9298e-03 eta 0:55:08
epoch [12/50] batch [200/204] time 0.469 (0.430) data 0.000 (0.003) loss 2.0517 (1.1428) lr 1.9298e-03 eta 0:55:37
epoch [13/50] batch [20/204] time 0.250 (0.335) data 0.000 (0.030) loss 0.9519 (1.0563) lr 1.9048e-03 eta 0:43:06
epoch [13/50] batch [40/204] time 0.250 (0.292) data 0.000 (0.015) loss 0.7915 (1.0558) lr 1.9048e-03 eta 0:37:33
epoch [13/50] batch [60/204] time 0.284 (0.280) data 0.000 (0.010) loss 1.7113 (1.1301) lr 1.9048e-03 eta 0:35:55
epoch [13/50] batch [80/204] time 0.274 (0.280) data 0.000 (0.008) loss 1.6415 (1.2093) lr 1.9048e-03 eta 0:35:44
epoch [13/50] batch [100/204] time 0.252 (0.287) data 0.000 (0.006) loss 1.8921 (1.2109) lr 1.9048e-03 eta 0:36:32
epoch [13/50] batch [120/204] time 0.253 (0.281) data 0.000 (0.005) loss 0.2164 (1.1834) lr 1.9048e-03 eta 0:35:41
epoch [13/50] batch [140/204] time 0.279 (0.277) data 0.000 (0.004) loss 1.1732 (1.1693) lr 1.9048e-03 eta 0:35:08
epoch [13/50] batch [160/204] time 0.289 (0.277) data 0.000 (0.004) loss 1.0140 (1.1186) lr 1.9048e-03 eta 0:35:05
epoch [13/50] batch [180/204] time 0.254 (0.284) data 0.000 (0.004) loss 2.3416 (1.1460) lr 1.9048e-03 eta 0:35:49
epoch [13/50] batch [200/204] time 0.247 (0.288) data 0.000 (0.003) loss 0.9878 (1.1273) lr 1.9048e-03 eta 0:36:17
epoch [14/50] batch [20/204] time 0.252 (0.359) data 0.000 (0.031) loss 0.9630 (1.1476) lr 1.8763e-03 eta 0:45:05
epoch [14/50] batch [40/204] time 0.251 (0.345) data 0.000 (0.015) loss 0.3087 (0.9920) lr 1.8763e-03 eta 0:43:08
epoch [14/50] batch [60/204] time 0.429 (0.355) data 0.000 (0.010) loss 0.7950 (0.9893) lr 1.8763e-03 eta 0:44:15
epoch [14/50] batch [80/204] time 0.247 (0.356) data 0.000 (0.008) loss 0.4983 (1.0566) lr 1.8763e-03 eta 0:44:16
epoch [14/50] batch [100/204] time 0.252 (0.346) data 0.000 (0.006) loss 1.2685 (1.0194) lr 1.8763e-03 eta 0:42:53
epoch [14/50] batch [120/204] time 0.252 (0.330) data 0.000 (0.005) loss 2.4150 (1.0826) lr 1.8763e-03 eta 0:40:47
epoch [14/50] batch [140/204] time 0.285 (0.318) data 0.000 (0.005) loss 0.9850 (1.0867) lr 1.8763e-03 eta 0:39:19
epoch [14/50] batch [160/204] time 0.270 (0.313) data 0.000 (0.004) loss 2.8425 (1.0967) lr 1.8763e-03 eta 0:38:32
epoch [14/50] batch [180/204] time 0.245 (0.313) data 0.000 (0.004) loss 1.3723 (1.0810) lr 1.8763e-03 eta 0:38:29
epoch [14/50] batch [200/204] time 0.249 (0.307) data 0.000 (0.003) loss 0.9001 (1.1058) lr 1.8763e-03 eta 0:37:36
epoch [15/50] batch [20/204] time 0.284 (0.284) data 0.000 (0.030) loss 0.3707 (0.6684) lr 1.8443e-03 eta 0:34:40
epoch [15/50] batch [40/204] time 0.290 (0.282) data 0.000 (0.015) loss 0.9331 (0.8515) lr 1.8443e-03 eta 0:34:18
epoch [15/50] batch [60/204] time 0.474 (0.334) data 0.000 (0.010) loss 0.7196 (0.9947) lr 1.8443e-03 eta 0:40:29
epoch [15/50] batch [80/204] time 0.412 (0.344) data 0.000 (0.008) loss 0.7159 (1.0392) lr 1.8443e-03 eta 0:41:38
epoch [15/50] batch [100/204] time 0.477 (0.370) data 0.000 (0.006) loss 1.0584 (1.0851) lr 1.8443e-03 eta 0:44:40
epoch [15/50] batch [120/204] time 0.478 (0.367) data 0.000 (0.005) loss 0.1685 (1.1063) lr 1.8443e-03 eta 0:44:13
epoch [15/50] batch [140/204] time 0.473 (0.382) data 0.000 (0.005) loss 1.1440 (1.0913) lr 1.8443e-03 eta 0:45:55
epoch [15/50] batch [160/204] time 0.472 (0.379) data 0.000 (0.004) loss 0.3227 (1.0885) lr 1.8443e-03 eta 0:45:21
epoch [15/50] batch [180/204] time 0.479 (0.390) data 0.000 (0.004) loss 0.0878 (1.0647) lr 1.8443e-03 eta 0:46:31
epoch [15/50] batch [200/204] time 0.468 (0.391) data 0.000 (0.003) loss 0.3094 (1.0540) lr 1.8443e-03 eta 0:46:33
epoch [16/50] batch [20/204] time 0.471 (0.436) data 0.000 (0.030) loss 0.0085 (1.0516) lr 1.8090e-03 eta 0:51:43
epoch [16/50] batch [40/204] time 0.251 (0.437) data 0.000 (0.015) loss 1.5056 (1.1208) lr 1.8090e-03 eta 0:51:45
epoch [16/50] batch [60/204] time 0.549 (0.430) data 0.001 (0.010) loss 0.1861 (1.1799) lr 1.8090e-03 eta 0:50:45
epoch [16/50] batch [80/204] time 0.253 (0.452) data 0.000 (0.008) loss 1.0187 (1.0730) lr 1.8090e-03 eta 0:53:10
epoch [16/50] batch [100/204] time 0.243 (0.411) data 0.000 (0.006) loss 0.8308 (1.0972) lr 1.8090e-03 eta 0:48:16
epoch [16/50] batch [120/204] time 0.250 (0.385) data 0.000 (0.005) loss 2.2969 (1.0871) lr 1.8090e-03 eta 0:44:59
epoch [16/50] batch [140/204] time 0.289 (0.368) data 0.000 (0.005) loss 1.8011 (1.0530) lr 1.8090e-03 eta 0:42:57
epoch [16/50] batch [160/204] time 0.288 (0.356) data 0.000 (0.004) loss 0.8656 (1.0459) lr 1.8090e-03 eta 0:41:25
epoch [16/50] batch [180/204] time 0.539 (0.374) data 0.000 (0.004) loss 0.2591 (1.0347) lr 1.8090e-03 eta 0:43:25
epoch [16/50] batch [200/204] time 0.252 (0.377) data 0.000 (0.003) loss 2.0591 (1.0595) lr 1.8090e-03 eta 0:43:39
epoch [17/50] batch [20/204] time 0.254 (0.281) data 0.000 (0.030) loss 1.0865 (0.9640) lr 1.7705e-03 eta 0:32:26
epoch [17/50] batch [40/204] time 0.252 (0.274) data 0.000 (0.015) loss 1.0255 (1.0192) lr 1.7705e-03 eta 0:31:29
epoch [17/50] batch [60/204] time 0.470 (0.289) data 0.000 (0.010) loss 0.3305 (1.0260) lr 1.7705e-03 eta 0:33:05
epoch [17/50] batch [80/204] time 0.471 (0.334) data 0.000 (0.008) loss 1.6524 (0.9958) lr 1.7705e-03 eta 0:38:12
epoch [17/50] batch [100/204] time 0.478 (0.338) data 0.000 (0.006) loss 2.0947 (1.0480) lr 1.7705e-03 eta 0:38:33
epoch [17/50] batch [120/204] time 0.400 (0.360) data 0.000 (0.005) loss 0.3698 (1.0549) lr 1.7705e-03 eta 0:40:56
epoch [17/50] batch [140/204] time 0.479 (0.366) data 0.000 (0.004) loss 1.9298 (1.0589) lr 1.7705e-03 eta 0:41:26
epoch [17/50] batch [160/204] time 0.253 (0.371) data 0.000 (0.004) loss 0.7391 (1.0488) lr 1.7705e-03 eta 0:41:53
epoch [17/50] batch [180/204] time 0.471 (0.376) data 0.000 (0.004) loss 3.5893 (1.0736) lr 1.7705e-03 eta 0:42:18
epoch [17/50] batch [200/204] time 0.249 (0.377) data 0.000 (0.003) loss 0.3076 (1.0640) lr 1.7705e-03 eta 0:42:16
epoch [18/50] batch [20/204] time 0.477 (0.504) data 0.000 (0.030) loss 1.1207 (0.7989) lr 1.7290e-03 eta 0:56:25
epoch [18/50] batch [40/204] time 0.464 (0.425) data 0.000 (0.015) loss 0.8495 (0.8744) lr 1.7290e-03 eta 0:47:24
epoch [18/50] batch [60/204] time 0.248 (0.434) data 0.000 (0.010) loss 1.8100 (0.9074) lr 1.7290e-03 eta 0:48:16
epoch [18/50] batch [80/204] time 0.475 (0.417) data 0.000 (0.008) loss 1.0002 (0.9676) lr 1.7290e-03 eta 0:46:13
epoch [18/50] batch [100/204] time 0.251 (0.420) data 0.000 (0.006) loss 0.0341 (0.9816) lr 1.7290e-03 eta 0:46:24
epoch [18/50] batch [120/204] time 0.473 (0.415) data 0.000 (0.005) loss 1.2325 (1.0125) lr 1.7290e-03 eta 0:45:44
epoch [18/50] batch [140/204] time 0.265 (0.415) data 0.000 (0.005) loss 1.0568 (0.9990) lr 1.7290e-03 eta 0:45:33
epoch [18/50] batch [160/204] time 0.469 (0.420) data 0.000 (0.004) loss 1.1805 (1.0249) lr 1.7290e-03 eta 0:45:57
epoch [18/50] batch [180/204] time 0.271 (0.411) data 0.000 (0.004) loss 2.2150 (1.0498) lr 1.7290e-03 eta 0:44:55
epoch [18/50] batch [200/204] time 0.480 (0.418) data 0.000 (0.003) loss 3.0600 (1.0744) lr 1.7290e-03 eta 0:45:28
epoch [19/50] batch [20/204] time 0.480 (0.466) data 0.000 (0.031) loss 1.4004 (1.0164) lr 1.6845e-03 eta 0:50:35
epoch [19/50] batch [40/204] time 0.251 (0.417) data 0.000 (0.015) loss 0.1455 (1.0140) lr 1.6845e-03 eta 0:45:07
epoch [19/50] batch [60/204] time 0.465 (0.429) data 0.000 (0.010) loss 0.6568 (0.9560) lr 1.6845e-03 eta 0:46:13
epoch [19/50] batch [80/204] time 0.469 (0.420) data 0.000 (0.008) loss 1.5181 (0.9426) lr 1.6845e-03 eta 0:45:09
epoch [19/50] batch [100/204] time 0.477 (0.431) data 0.000 (0.006) loss 1.7470 (0.9864) lr 1.6845e-03 eta 0:46:09
epoch [19/50] batch [120/204] time 0.484 (0.424) data 0.000 (0.005) loss 0.6848 (0.9341) lr 1.6845e-03 eta 0:45:20
epoch [19/50] batch [140/204] time 0.250 (0.425) data 0.000 (0.005) loss 1.0516 (0.9698) lr 1.6845e-03 eta 0:45:13
epoch [19/50] batch [160/204] time 0.253 (0.408) data 0.000 (0.004) loss 0.1672 (0.9632) lr 1.6845e-03 eta 0:43:17
epoch [19/50] batch [180/204] time 0.253 (0.390) data 0.000 (0.004) loss 0.2447 (0.9527) lr 1.6845e-03 eta 0:41:17
epoch [19/50] batch [200/204] time 0.279 (0.376) data 0.000 (0.003) loss 0.6378 (0.9608) lr 1.6845e-03 eta 0:39:41
epoch [20/50] batch [20/204] time 0.293 (0.307) data 0.000 (0.032) loss 0.6215 (1.0528) lr 1.6374e-03 eta 0:32:17
epoch [20/50] batch [40/204] time 0.253 (0.299) data 0.000 (0.016) loss 0.0221 (1.0298) lr 1.6374e-03 eta 0:31:16
epoch [20/50] batch [60/204] time 0.247 (0.282) data 0.000 (0.011) loss 0.7331 (1.0475) lr 1.6374e-03 eta 0:29:28
epoch [20/50] batch [80/204] time 0.297 (0.278) data 0.000 (0.008) loss 0.9649 (1.0240) lr 1.6374e-03 eta 0:28:56
epoch [20/50] batch [100/204] time 0.513 (0.282) data 0.000 (0.007) loss 1.1935 (1.0388) lr 1.6374e-03 eta 0:29:12
epoch [20/50] batch [120/204] time 0.532 (0.323) data 0.000 (0.006) loss 0.4124 (1.0139) lr 1.6374e-03 eta 0:33:25
epoch [20/50] batch [140/204] time 0.519 (0.353) data 0.000 (0.005) loss 1.5585 (1.0401) lr 1.6374e-03 eta 0:36:22
epoch [20/50] batch [160/204] time 0.531 (0.375) data 0.000 (0.004) loss 3.1995 (1.0337) lr 1.6374e-03 eta 0:38:34
epoch [20/50] batch [180/204] time 0.536 (0.393) data 0.000 (0.004) loss 0.0499 (1.0383) lr 1.6374e-03 eta 0:40:15
epoch [20/50] batch [200/204] time 0.536 (0.407) data 0.000 (0.003) loss 1.4791 (1.0190) lr 1.6374e-03 eta 0:41:33
epoch [21/50] batch [20/204] time 0.539 (0.563) data 0.000 (0.030) loss 1.1580 (1.1061) lr 1.5878e-03 eta 0:57:16
epoch [21/50] batch [40/204] time 0.534 (0.549) data 0.000 (0.015) loss 1.1416 (1.0131) lr 1.5878e-03 eta 0:55:35
epoch [21/50] batch [60/204] time 0.531 (0.544) data 0.000 (0.010) loss 1.5291 (0.9142) lr 1.5878e-03 eta 0:54:55
epoch [21/50] batch [80/204] time 0.535 (0.542) data 0.000 (0.008) loss 1.6923 (0.9442) lr 1.5878e-03 eta 0:54:32
epoch [21/50] batch [100/204] time 0.255 (0.512) data 0.000 (0.006) loss 1.4110 (0.9813) lr 1.5878e-03 eta 0:51:21
epoch [21/50] batch [120/204] time 0.534 (0.484) data 0.000 (0.005) loss 0.4573 (0.9940) lr 1.5878e-03 eta 0:48:21
epoch [21/50] batch [140/204] time 0.531 (0.491) data 0.000 (0.005) loss 1.5050 (0.9963) lr 1.5878e-03 eta 0:48:53
epoch [21/50] batch [160/204] time 0.529 (0.496) data 0.000 (0.004) loss 0.6257 (0.9800) lr 1.5878e-03 eta 0:49:16
epoch [21/50] batch [180/204] time 0.539 (0.500) data 0.000 (0.004) loss 0.5814 (0.9708) lr 1.5878e-03 eta 0:49:32
epoch [21/50] batch [200/204] time 0.534 (0.504) data 0.000 (0.003) loss 2.1244 (0.9777) lr 1.5878e-03 eta 0:49:42
epoch [22/50] batch [20/204] time 0.538 (0.567) data 0.000 (0.031) loss 0.8216 (0.9639) lr 1.5358e-03 eta 0:55:42
epoch [22/50] batch [40/204] time 0.531 (0.550) data 0.000 (0.015) loss 0.2255 (0.9376) lr 1.5358e-03 eta 0:53:53
epoch [22/50] batch [60/204] time 0.535 (0.545) data 0.000 (0.010) loss 0.5574 (0.9546) lr 1.5358e-03 eta 0:53:10
epoch [22/50] batch [80/204] time 0.536 (0.542) data 0.000 (0.008) loss 0.9405 (0.9682) lr 1.5358e-03 eta 0:52:42
epoch [22/50] batch [100/204] time 0.535 (0.541) data 0.000 (0.006) loss 0.6416 (0.9557) lr 1.5358e-03 eta 0:52:26
epoch [22/50] batch [120/204] time 0.561 (0.512) data 0.000 (0.005) loss 0.3550 (0.9205) lr 1.5358e-03 eta 0:49:25
epoch [22/50] batch [140/204] time 0.535 (0.500) data 0.000 (0.005) loss 0.2352 (0.9692) lr 1.5358e-03 eta 0:48:10
epoch [22/50] batch [160/204] time 0.530 (0.505) data 0.000 (0.004) loss 1.0324 (0.9593) lr 1.5358e-03 eta 0:48:25
epoch [22/50] batch [180/204] time 0.535 (0.508) data 0.000 (0.004) loss 0.5198 (0.9293) lr 1.5358e-03 eta 0:48:34
epoch [22/50] batch [200/204] time 0.536 (0.511) data 0.000 (0.003) loss 1.6756 (0.9297) lr 1.5358e-03 eta 0:48:38
epoch [23/50] batch [20/204] time 0.538 (0.566) data 0.000 (0.031) loss 1.2275 (0.8503) lr 1.4818e-03 eta 0:53:39
epoch [23/50] batch [40/204] time 0.530 (0.550) data 0.000 (0.016) loss 1.1339 (0.9475) lr 1.4818e-03 eta 0:52:01
epoch [23/50] batch [60/204] time 0.538 (0.545) data 0.001 (0.010) loss 1.2509 (0.9752) lr 1.4818e-03 eta 0:51:22
epoch [23/50] batch [80/204] time 0.544 (0.542) data 0.000 (0.008) loss 0.2085 (1.0348) lr 1.4818e-03 eta 0:50:55
epoch [23/50] batch [100/204] time 0.538 (0.541) data 0.000 (0.006) loss 1.0286 (0.9917) lr 1.4818e-03 eta 0:50:37
epoch [23/50] batch [120/204] time 0.254 (0.536) data 0.000 (0.005) loss 1.5959 (0.9669) lr 1.4818e-03 eta 0:49:56
epoch [23/50] batch [140/204] time 0.253 (0.499) data 0.000 (0.005) loss 0.2350 (0.9924) lr 1.4818e-03 eta 0:46:22
epoch [23/50] batch [160/204] time 0.539 (0.498) data 0.000 (0.004) loss 1.2518 (0.9990) lr 1.4818e-03 eta 0:46:07
epoch [23/50] batch [180/204] time 0.532 (0.502) data 0.000 (0.004) loss 0.9736 (0.9986) lr 1.4818e-03 eta 0:46:19
epoch [23/50] batch [200/204] time 0.532 (0.506) data 0.000 (0.003) loss 0.1578 (0.9887) lr 1.4818e-03 eta 0:46:27
epoch [24/50] batch [20/204] time 0.524 (0.565) data 0.000 (0.030) loss 0.7205 (0.7565) lr 1.4258e-03 eta 0:51:40
epoch [24/50] batch [40/204] time 0.539 (0.551) data 0.000 (0.015) loss 0.1069 (0.6524) lr 1.4258e-03 eta 0:50:10
epoch [24/50] batch [60/204] time 0.537 (0.547) data 0.000 (0.010) loss 2.8986 (0.8230) lr 1.4258e-03 eta 0:49:37
epoch [24/50] batch [80/204] time 0.533 (0.543) data 0.000 (0.008) loss 0.9403 (0.8781) lr 1.4258e-03 eta 0:49:09
epoch [24/50] batch [100/204] time 0.521 (0.542) data 0.000 (0.006) loss 0.3980 (0.9186) lr 1.4258e-03 eta 0:48:49
epoch [24/50] batch [120/204] time 0.528 (0.540) data 0.000 (0.005) loss 1.4106 (0.9385) lr 1.4258e-03 eta 0:48:29
epoch [24/50] batch [140/204] time 0.254 (0.528) data 0.000 (0.004) loss 1.5684 (0.9520) lr 1.4258e-03 eta 0:47:14
epoch [24/50] batch [160/204] time 0.540 (0.505) data 0.000 (0.004) loss 0.5625 (0.9515) lr 1.4258e-03 eta 0:44:59
epoch [24/50] batch [180/204] time 0.537 (0.508) data 0.000 (0.004) loss 0.2312 (0.9638) lr 1.4258e-03 eta 0:45:05
epoch [24/50] batch [200/204] time 0.543 (0.511) data 0.000 (0.003) loss 0.1316 (0.9507) lr 1.4258e-03 eta 0:45:10
epoch [25/50] batch [20/204] time 0.529 (0.562) data 0.000 (0.030) loss 1.1694 (1.0678) lr 1.3681e-03 eta 0:49:28
epoch [25/50] batch [40/204] time 0.532 (0.548) data 0.001 (0.015) loss 1.6131 (0.9365) lr 1.3681e-03 eta 0:48:03
epoch [25/50] batch [60/204] time 0.538 (0.544) data 0.000 (0.010) loss 0.9505 (0.9437) lr 1.3681e-03 eta 0:47:34
epoch [25/50] batch [80/204] time 0.534 (0.542) data 0.000 (0.008) loss 1.5367 (0.9616) lr 1.3681e-03 eta 0:47:12
epoch [25/50] batch [100/204] time 0.539 (0.540) data 0.000 (0.006) loss 0.2182 (0.9499) lr 1.3681e-03 eta 0:46:52
epoch [25/50] batch [120/204] time 0.539 (0.539) data 0.000 (0.005) loss 1.8904 (0.9600) lr 1.3681e-03 eta 0:46:36
epoch [25/50] batch [140/204] time 0.536 (0.539) data 0.000 (0.005) loss 0.2850 (0.9729) lr 1.3681e-03 eta 0:46:24
epoch [25/50] batch [160/204] time 0.547 (0.518) data 0.000 (0.004) loss 0.4759 (0.9605) lr 1.3681e-03 eta 0:44:23
epoch [25/50] batch [180/204] time 0.538 (0.509) data 0.000 (0.004) loss 0.0515 (0.9643) lr 1.3681e-03 eta 0:43:25
epoch [25/50] batch [200/204] time 0.532 (0.511) data 0.000 (0.003) loss 0.7264 (0.9514) lr 1.3681e-03 eta 0:43:29
epoch [26/50] batch [20/204] time 0.538 (0.564) data 0.000 (0.030) loss 0.7282 (0.7508) lr 1.3090e-03 eta 0:47:42
epoch [26/50] batch [40/204] time 0.544 (0.550) data 0.000 (0.015) loss 0.3657 (0.7816) lr 1.3090e-03 eta 0:46:23
epoch [26/50] batch [60/204] time 0.536 (0.545) data 0.000 (0.010) loss 0.2802 (0.8243) lr 1.3090e-03 eta 0:45:49
epoch [26/50] batch [80/204] time 0.536 (0.543) data 0.000 (0.008) loss 0.5484 (0.8651) lr 1.3090e-03 eta 0:45:24
epoch [26/50] batch [100/204] time 0.540 (0.542) data 0.000 (0.006) loss 0.4029 (0.8605) lr 1.3090e-03 eta 0:45:07
epoch [26/50] batch [120/204] time 0.538 (0.541) data 0.000 (0.005) loss 1.1154 (0.8659) lr 1.3090e-03 eta 0:44:52
epoch [26/50] batch [140/204] time 0.539 (0.540) data 0.000 (0.004) loss 0.8567 (0.8458) lr 1.3090e-03 eta 0:44:36
epoch [26/50] batch [160/204] time 0.251 (0.536) data 0.000 (0.004) loss 1.3411 (0.8738) lr 1.3090e-03 eta 0:44:06
epoch [26/50] batch [180/204] time 0.533 (0.509) data 0.000 (0.004) loss 0.7274 (0.8809) lr 1.3090e-03 eta 0:41:45
epoch [26/50] batch [200/204] time 0.538 (0.512) data 0.000 (0.003) loss 0.8394 (0.8800) lr 1.3090e-03 eta 0:41:48
epoch [27/50] batch [20/204] time 0.539 (0.567) data 0.000 (0.031) loss 0.8890 (0.9139) lr 1.2487e-03 eta 0:46:03
epoch [27/50] batch [40/204] time 0.537 (0.552) data 0.000 (0.015) loss 0.3882 (0.8904) lr 1.2487e-03 eta 0:44:40
epoch [27/50] batch [60/204] time 0.533 (0.547) data 0.000 (0.010) loss 0.8336 (0.8792) lr 1.2487e-03 eta 0:44:04
epoch [27/50] batch [80/204] time 0.541 (0.544) data 0.000 (0.008) loss 2.1046 (0.8921) lr 1.2487e-03 eta 0:43:41
epoch [27/50] batch [100/204] time 0.538 (0.543) data 0.000 (0.006) loss 0.7007 (0.8772) lr 1.2487e-03 eta 0:43:24
epoch [27/50] batch [120/204] time 0.541 (0.542) data 0.000 (0.005) loss 0.8754 (0.8728) lr 1.2487e-03 eta 0:43:08
epoch [27/50] batch [140/204] time 0.541 (0.542) data 0.000 (0.005) loss 1.1991 (0.8822) lr 1.2487e-03 eta 0:42:55
epoch [27/50] batch [160/204] time 0.533 (0.541) data 0.000 (0.004) loss 0.7967 (0.8810) lr 1.2487e-03 eta 0:42:43
epoch [27/50] batch [180/204] time 0.254 (0.524) data 0.000 (0.004) loss 1.2499 (0.8891) lr 1.2487e-03 eta 0:41:10
epoch [27/50] batch [200/204] time 0.538 (0.520) data 0.000 (0.003) loss 0.7833 (0.9161) lr 1.2487e-03 eta 0:40:42
epoch [28/50] batch [20/204] time 0.527 (0.566) data 0.000 (0.030) loss 1.2050 (0.9589) lr 1.1874e-03 eta 0:44:03
epoch [28/50] batch [40/204] time 0.534 (0.549) data 0.000 (0.015) loss 1.9289 (0.8337) lr 1.1874e-03 eta 0:42:35
epoch [28/50] batch [60/204] time 0.531 (0.545) data 0.000 (0.010) loss 0.4001 (0.8174) lr 1.1874e-03 eta 0:42:04
epoch [28/50] batch [80/204] time 0.541 (0.543) data 0.000 (0.008) loss 1.8622 (0.8381) lr 1.1874e-03 eta 0:41:44
epoch [28/50] batch [100/204] time 0.530 (0.542) data 0.000 (0.006) loss 0.0622 (0.8556) lr 1.1874e-03 eta 0:41:26
epoch [28/50] batch [120/204] time 0.535 (0.540) data 0.000 (0.005) loss 0.0895 (0.8495) lr 1.1874e-03 eta 0:41:10
epoch [28/50] batch [140/204] time 0.535 (0.540) data 0.000 (0.005) loss 1.6046 (0.8945) lr 1.1874e-03 eta 0:40:56
epoch [28/50] batch [160/204] time 0.539 (0.539) data 0.000 (0.004) loss 0.4717 (0.9028) lr 1.1874e-03 eta 0:40:43
epoch [28/50] batch [180/204] time 0.256 (0.532) data 0.000 (0.004) loss 1.1339 (0.9168) lr 1.1874e-03 eta 0:40:02
epoch [28/50] batch [200/204] time 0.526 (0.518) data 0.000 (0.003) loss 1.4115 (0.9164) lr 1.1874e-03 eta 0:38:48
epoch [29/50] batch [20/204] time 0.535 (0.564) data 0.000 (0.031) loss 0.9643 (1.0342) lr 1.1253e-03 eta 0:41:59
epoch [29/50] batch [40/204] time 0.539 (0.550) data 0.000 (0.015) loss 0.3380 (0.9765) lr 1.1253e-03 eta 0:40:47
epoch [29/50] batch [60/204] time 0.535 (0.545) data 0.000 (0.010) loss 0.2265 (0.8905) lr 1.1253e-03 eta 0:40:13
epoch [29/50] batch [80/204] time 0.540 (0.543) data 0.000 (0.008) loss 0.7660 (0.9187) lr 1.1253e-03 eta 0:39:52
epoch [29/50] batch [100/204] time 0.539 (0.541) data 0.000 (0.006) loss 0.6268 (0.8983) lr 1.1253e-03 eta 0:39:36
epoch [29/50] batch [120/204] time 0.527 (0.540) data 0.000 (0.005) loss 0.7004 (0.8754) lr 1.1253e-03 eta 0:39:18
epoch [29/50] batch [140/204] time 0.536 (0.539) data 0.000 (0.005) loss 2.0944 (0.8893) lr 1.1253e-03 eta 0:39:04
epoch [29/50] batch [160/204] time 0.539 (0.539) data 0.000 (0.004) loss 1.2528 (0.8608) lr 1.1253e-03 eta 0:38:51
epoch [29/50] batch [180/204] time 0.540 (0.538) data 0.000 (0.004) loss 2.2276 (0.8826) lr 1.1253e-03 eta 0:38:38
epoch [29/50] batch [200/204] time 0.247 (0.517) data 0.000 (0.003) loss 1.0316 (0.8847) lr 1.1253e-03 eta 0:36:56
epoch [30/50] batch [20/204] time 0.536 (0.565) data 0.000 (0.031) loss 1.8405 (1.0815) lr 1.0628e-03 eta 0:40:08
epoch [30/50] batch [40/204] time 0.533 (0.550) data 0.000 (0.015) loss 0.9789 (0.9594) lr 1.0628e-03 eta 0:38:53
epoch [30/50] batch [60/204] time 0.522 (0.545) data 0.001 (0.010) loss 0.6048 (0.9241) lr 1.0628e-03 eta 0:38:20
epoch [30/50] batch [80/204] time 0.538 (0.541) data 0.000 (0.008) loss 0.9153 (0.9716) lr 1.0628e-03 eta 0:37:55
epoch [30/50] batch [100/204] time 0.526 (0.540) data 0.000 (0.006) loss 0.0087 (0.9471) lr 1.0628e-03 eta 0:37:38
epoch [30/50] batch [120/204] time 0.532 (0.539) data 0.000 (0.005) loss 0.5406 (0.9216) lr 1.0628e-03 eta 0:37:23
epoch [30/50] batch [140/204] time 0.530 (0.538) data 0.000 (0.005) loss 0.1300 (0.8945) lr 1.0628e-03 eta 0:37:11
epoch [30/50] batch [160/204] time 0.530 (0.538) data 0.000 (0.004) loss 0.0522 (0.8599) lr 1.0628e-03 eta 0:36:58
epoch [30/50] batch [180/204] time 0.539 (0.538) data 0.000 (0.004) loss 1.1832 (0.8480) lr 1.0628e-03 eta 0:36:46
epoch [30/50] batch [200/204] time 0.256 (0.530) data 0.000 (0.003) loss 0.3957 (0.8673) lr 1.0628e-03 eta 0:36:06
epoch [31/50] batch [20/204] time 0.539 (0.541) data 0.000 (0.031) loss 1.2375 (0.8891) lr 1.0000e-03 eta 0:36:37
epoch [31/50] batch [40/204] time 0.531 (0.538) data 0.000 (0.016) loss 1.3285 (1.0114) lr 1.0000e-03 eta 0:36:14
epoch [31/50] batch [60/204] time 0.537 (0.537) data 0.001 (0.011) loss 0.5840 (0.9378) lr 1.0000e-03 eta 0:35:58
epoch [31/50] batch [80/204] time 0.538 (0.536) data 0.000 (0.008) loss 1.4055 (0.9251) lr 1.0000e-03 eta 0:35:42
epoch [31/50] batch [100/204] time 0.536 (0.535) data 0.000 (0.006) loss 2.2079 (0.9339) lr 1.0000e-03 eta 0:35:30
epoch [31/50] batch [120/204] time 0.532 (0.535) data 0.000 (0.005) loss 0.8565 (0.9792) lr 1.0000e-03 eta 0:35:18
epoch [31/50] batch [140/204] time 0.535 (0.535) data 0.000 (0.005) loss 0.2102 (0.9777) lr 1.0000e-03 eta 0:35:07
epoch [31/50] batch [160/204] time 0.536 (0.535) data 0.000 (0.004) loss 1.6347 (0.9655) lr 1.0000e-03 eta 0:34:56
epoch [31/50] batch [180/204] time 0.539 (0.535) data 0.000 (0.004) loss 0.5087 (0.9514) lr 1.0000e-03 eta 0:34:46
epoch [31/50] batch [200/204] time 0.534 (0.535) data 0.000 (0.003) loss 0.2319 (0.9422) lr 1.0000e-03 eta 0:34:35
epoch [32/50] batch [20/204] time 0.538 (0.471) data 0.000 (0.030) loss 0.0279 (0.6101) lr 9.3721e-04 eta 0:30:15
epoch [32/50] batch [40/204] time 0.531 (0.503) data 0.000 (0.015) loss 0.6605 (0.8134) lr 9.3721e-04 eta 0:32:10
epoch [32/50] batch [60/204] time 0.541 (0.514) data 0.001 (0.010) loss 0.3838 (0.7923) lr 9.3721e-04 eta 0:32:42
epoch [32/50] batch [80/204] time 0.540 (0.520) data 0.000 (0.008) loss 0.2108 (0.7772) lr 9.3721e-04 eta 0:32:53
epoch [32/50] batch [100/204] time 0.533 (0.523) data 0.000 (0.006) loss 1.2299 (0.7815) lr 9.3721e-04 eta 0:32:55
epoch [32/50] batch [120/204] time 0.524 (0.525) data 0.000 (0.005) loss 1.0473 (0.8106) lr 9.3721e-04 eta 0:32:52
epoch [32/50] batch [140/204] time 0.533 (0.526) data 0.000 (0.004) loss 0.9662 (0.8178) lr 9.3721e-04 eta 0:32:46
epoch [32/50] batch [160/204] time 0.540 (0.528) data 0.000 (0.004) loss 2.9277 (0.8240) lr 9.3721e-04 eta 0:32:40
epoch [32/50] batch [180/204] time 0.538 (0.528) data 0.000 (0.004) loss 1.3749 (0.8351) lr 9.3721e-04 eta 0:32:31
epoch [32/50] batch [200/204] time 0.532 (0.529) data 0.000 (0.003) loss 1.2238 (0.8557) lr 9.3721e-04 eta 0:32:23
epoch [33/50] batch [20/204] time 0.256 (0.314) data 0.000 (0.029) loss 1.3312 (0.7291) lr 8.7467e-04 eta 0:19:07
epoch [33/50] batch [40/204] time 0.467 (0.298) data 0.000 (0.015) loss 0.3210 (0.9206) lr 8.7467e-04 eta 0:18:01
epoch [33/50] batch [60/204] time 0.330 (0.304) data 0.007 (0.010) loss 0.7606 (0.9314) lr 8.7467e-04 eta 0:18:19
epoch [33/50] batch [80/204] time 0.255 (0.306) data 0.000 (0.008) loss 0.9647 (0.9265) lr 8.7467e-04 eta 0:18:19
epoch [33/50] batch [100/204] time 0.486 (0.313) data 0.000 (0.006) loss 0.0905 (0.8899) lr 8.7467e-04 eta 0:18:37
epoch [33/50] batch [120/204] time 0.255 (0.316) data 0.000 (0.005) loss 0.7687 (0.9010) lr 8.7467e-04 eta 0:18:41
epoch [33/50] batch [140/204] time 0.249 (0.312) data 0.000 (0.005) loss 1.8323 (0.8784) lr 8.7467e-04 eta 0:18:21
epoch [33/50] batch [160/204] time 0.248 (0.304) data 0.000 (0.004) loss 2.6209 (0.8892) lr 8.7467e-04 eta 0:17:48
epoch [33/50] batch [180/204] time 0.289 (0.299) data 0.000 (0.004) loss 0.4190 (0.8918) lr 8.7467e-04 eta 0:17:23
epoch [33/50] batch [200/204] time 0.257 (0.296) data 0.000 (0.003) loss 0.1721 (0.8875) lr 8.7467e-04 eta 0:17:07
epoch [34/50] batch [20/204] time 0.444 (0.378) data 0.000 (0.031) loss 1.0127 (1.0142) lr 8.1262e-04 eta 0:21:44
epoch [34/50] batch [40/204] time 0.254 (0.353) data 0.000 (0.016) loss 0.2753 (0.9607) lr 8.1262e-04 eta 0:20:11
epoch [34/50] batch [60/204] time 0.253 (0.348) data 0.001 (0.011) loss 0.9778 (0.8920) lr 8.1262e-04 eta 0:19:45
epoch [34/50] batch [80/204] time 0.268 (0.346) data 0.000 (0.008) loss 0.4856 (0.8492) lr 8.1262e-04 eta 0:19:30
epoch [34/50] batch [100/204] time 0.253 (0.331) data 0.000 (0.007) loss 0.4256 (0.8421) lr 8.1262e-04 eta 0:18:35
epoch [34/50] batch [120/204] time 0.252 (0.318) data 0.000 (0.005) loss 0.2484 (0.8760) lr 8.1262e-04 eta 0:17:43
epoch [34/50] batch [140/204] time 0.353 (0.311) data 0.000 (0.005) loss 2.0714 (0.8820) lr 8.1262e-04 eta 0:17:16
epoch [34/50] batch [160/204] time 0.500 (0.312) data 0.000 (0.004) loss 0.2290 (0.8651) lr 8.1262e-04 eta 0:17:11
epoch [34/50] batch [180/204] time 0.495 (0.333) data 0.000 (0.004) loss 0.1886 (0.8503) lr 8.1262e-04 eta 0:18:14
epoch [34/50] batch [200/204] time 0.504 (0.349) data 0.000 (0.003) loss 0.9306 (0.8801) lr 8.1262e-04 eta 0:19:01
epoch [35/50] batch [20/204] time 0.252 (0.437) data 0.000 (0.028) loss 1.0891 (1.1967) lr 7.5131e-04 eta 0:23:38
epoch [35/50] batch [40/204] time 0.501 (0.437) data 0.000 (0.014) loss 1.0680 (1.0551) lr 7.5131e-04 eta 0:23:28
epoch [35/50] batch [60/204] time 0.503 (0.458) data 0.000 (0.010) loss 0.3632 (1.0340) lr 7.5131e-04 eta 0:24:28
epoch [35/50] batch [80/204] time 0.498 (0.469) data 0.000 (0.007) loss 1.2283 (0.9339) lr 7.5131e-04 eta 0:24:52
epoch [35/50] batch [100/204] time 0.245 (0.456) data 0.000 (0.006) loss 0.9787 (0.9006) lr 7.5131e-04 eta 0:24:02
epoch [35/50] batch [120/204] time 0.501 (0.452) data 0.000 (0.005) loss 1.5244 (0.8729) lr 7.5131e-04 eta 0:23:40
epoch [35/50] batch [140/204] time 0.500 (0.459) data 0.000 (0.004) loss 0.8148 (0.9247) lr 7.5131e-04 eta 0:23:53
epoch [35/50] batch [160/204] time 0.489 (0.464) data 0.000 (0.004) loss 0.9457 (0.9825) lr 7.5131e-04 eta 0:24:00
epoch [35/50] batch [180/204] time 0.252 (0.457) data 0.000 (0.003) loss 1.5104 (0.9533) lr 7.5131e-04 eta 0:23:28
epoch [35/50] batch [200/204] time 0.502 (0.455) data 0.000 (0.003) loss 0.3634 (0.9512) lr 7.5131e-04 eta 0:23:15
epoch [36/50] batch [20/204] time 0.499 (0.528) data 0.000 (0.028) loss 0.1809 (1.0829) lr 6.9098e-04 eta 0:26:44
epoch [36/50] batch [40/204] time 0.498 (0.512) data 0.000 (0.014) loss 1.5484 (0.8008) lr 6.9098e-04 eta 0:25:47
epoch [36/50] batch [60/204] time 0.509 (0.455) data 0.001 (0.009) loss 1.2159 (0.8795) lr 6.9098e-04 eta 0:22:45
epoch [36/50] batch [80/204] time 0.500 (0.466) data 0.000 (0.007) loss 0.4328 (0.9033) lr 6.9098e-04 eta 0:23:09
epoch [36/50] batch [100/204] time 0.502 (0.472) data 0.000 (0.006) loss 0.0791 (0.8595) lr 6.9098e-04 eta 0:23:18
epoch [36/50] batch [120/204] time 0.498 (0.477) data 0.000 (0.005) loss 1.1898 (0.8648) lr 6.9098e-04 eta 0:23:22
epoch [36/50] batch [140/204] time 0.500 (0.458) data 0.000 (0.004) loss 0.1306 (0.8577) lr 6.9098e-04 eta 0:22:16
epoch [36/50] batch [160/204] time 0.495 (0.463) data 0.000 (0.004) loss 0.6214 (0.8517) lr 6.9098e-04 eta 0:22:22
epoch [36/50] batch [180/204] time 0.501 (0.467) data 0.000 (0.003) loss 0.8969 (0.8725) lr 6.9098e-04 eta 0:22:24
epoch [36/50] batch [200/204] time 0.385 (0.470) data 0.000 (0.003) loss 1.2193 (0.8679) lr 6.9098e-04 eta 0:22:23
epoch [37/50] batch [20/204] time 0.496 (0.538) data 0.000 (0.055) loss 0.1868 (0.6629) lr 6.3188e-04 eta 0:25:27
epoch [37/50] batch [40/204] time 0.497 (0.519) data 0.000 (0.028) loss 0.0623 (0.5957) lr 6.3188e-04 eta 0:24:20
epoch [37/50] batch [60/204] time 0.496 (0.512) data 0.000 (0.018) loss 0.0755 (0.6972) lr 6.3188e-04 eta 0:23:52
epoch [37/50] batch [80/204] time 0.252 (0.471) data 0.000 (0.014) loss 1.7838 (0.7666) lr 6.3188e-04 eta 0:21:48
epoch [37/50] batch [100/204] time 0.496 (0.475) data 0.000 (0.011) loss 0.9716 (0.7500) lr 6.3188e-04 eta 0:21:49
epoch [37/50] batch [120/204] time 0.501 (0.479) data 0.000 (0.009) loss 0.3902 (0.8137) lr 6.3188e-04 eta 0:21:50
epoch [37/50] batch [140/204] time 0.498 (0.482) data 0.000 (0.008) loss 0.3812 (0.8354) lr 6.3188e-04 eta 0:21:48
epoch [37/50] batch [160/204] time 0.247 (0.463) data 0.000 (0.007) loss 0.2295 (0.8653) lr 6.3188e-04 eta 0:20:49
epoch [37/50] batch [180/204] time 0.500 (0.468) data 0.000 (0.006) loss 0.6642 (0.8523) lr 6.3188e-04 eta 0:20:51
epoch [37/50] batch [200/204] time 0.496 (0.471) data 0.000 (0.006) loss 0.4672 (0.8320) lr 6.3188e-04 eta 0:20:50
epoch [38/50] batch [20/204] time 0.247 (0.482) data 0.000 (0.028) loss 0.0244 (0.8647) lr 5.7422e-04 eta 0:21:08
epoch [38/50] batch [40/204] time 0.499 (0.461) data 0.000 (0.014) loss 1.4776 (0.7858) lr 5.7422e-04 eta 0:20:02
epoch [38/50] batch [60/204] time 0.499 (0.473) data 0.000 (0.009) loss 1.5017 (0.7560) lr 5.7422e-04 eta 0:20:26
epoch [38/50] batch [80/204] time 0.501 (0.479) data 0.000 (0.007) loss 0.3069 (0.8217) lr 5.7422e-04 eta 0:20:32
epoch [38/50] batch [100/204] time 0.246 (0.463) data 0.000 (0.006) loss 0.3354 (0.8343) lr 5.7422e-04 eta 0:19:42
epoch [38/50] batch [120/204] time 0.501 (0.469) data 0.000 (0.005) loss 1.0132 (0.8358) lr 5.7422e-04 eta 0:19:46
epoch [38/50] batch [140/204] time 0.500 (0.473) data 0.000 (0.004) loss 0.2246 (0.8122) lr 5.7422e-04 eta 0:19:48
epoch [38/50] batch [160/204] time 0.500 (0.476) data 0.000 (0.004) loss 1.8988 (0.8136) lr 5.7422e-04 eta 0:19:46
epoch [38/50] batch [180/204] time 0.246 (0.461) data 0.000 (0.003) loss 0.4173 (0.8184) lr 5.7422e-04 eta 0:18:59
epoch [38/50] batch [200/204] time 0.247 (0.452) data 0.000 (0.003) loss 1.4274 (0.8311) lr 5.7422e-04 eta 0:18:28
epoch [39/50] batch [20/204] time 0.250 (0.279) data 0.000 (0.028) loss 0.1686 (0.7380) lr 5.1825e-04 eta 0:11:16
epoch [39/50] batch [40/204] time 0.285 (0.270) data 0.000 (0.014) loss 0.2435 (0.7441) lr 5.1825e-04 eta 0:10:49
epoch [39/50] batch [60/204] time 0.276 (0.273) data 0.000 (0.010) loss 1.7882 (0.8145) lr 5.1825e-04 eta 0:10:50
epoch [39/50] batch [80/204] time 0.253 (0.300) data 0.000 (0.007) loss 0.0734 (0.9011) lr 5.1825e-04 eta 0:11:51
epoch [39/50] batch [100/204] time 0.251 (0.290) data 0.000 (0.006) loss 1.8941 (0.8937) lr 5.1825e-04 eta 0:11:21
epoch [39/50] batch [120/204] time 0.251 (0.284) data 0.000 (0.005) loss 0.4790 (0.8840) lr 5.1825e-04 eta 0:11:00
epoch [39/50] batch [140/204] time 0.279 (0.282) data 0.000 (0.004) loss 0.2221 (0.8794) lr 5.1825e-04 eta 0:10:51
epoch [39/50] batch [160/204] time 0.477 (0.293) data 0.000 (0.004) loss 0.6348 (0.8955) lr 5.1825e-04 eta 0:11:09
epoch [39/50] batch [180/204] time 0.251 (0.308) data 0.000 (0.003) loss 2.6928 (0.9256) lr 5.1825e-04 eta 0:11:39
epoch [39/50] batch [200/204] time 0.473 (0.319) data 0.000 (0.003) loss 0.1788 (0.9125) lr 5.1825e-04 eta 0:11:57
epoch [40/50] batch [20/204] time 0.483 (0.387) data 0.002 (0.029) loss 0.7657 (0.8049) lr 4.6417e-04 eta 0:14:20
epoch [40/50] batch [40/204] time 0.322 (0.410) data 0.000 (0.015) loss 1.0659 (0.8561) lr 4.6417e-04 eta 0:15:03
epoch [40/50] batch [60/204] time 0.477 (0.422) data 0.000 (0.010) loss 0.0319 (0.7796) lr 4.6417e-04 eta 0:15:21
epoch [40/50] batch [80/204] time 0.480 (0.405) data 0.000 (0.007) loss 0.1942 (0.7902) lr 4.6417e-04 eta 0:14:36
epoch [40/50] batch [100/204] time 0.478 (0.419) data 0.000 (0.006) loss 0.8630 (0.7781) lr 4.6417e-04 eta 0:14:58
epoch [40/50] batch [120/204] time 0.483 (0.417) data 0.000 (0.005) loss 0.0851 (0.7940) lr 4.6417e-04 eta 0:14:45
epoch [40/50] batch [140/204] time 0.367 (0.419) data 0.000 (0.004) loss 0.7058 (0.7872) lr 4.6417e-04 eta 0:14:41
epoch [40/50] batch [160/204] time 0.472 (0.423) data 0.000 (0.004) loss 1.9282 (0.8129) lr 4.6417e-04 eta 0:14:41
epoch [40/50] batch [180/204] time 0.486 (0.416) data 0.000 (0.003) loss 0.9614 (0.8133) lr 4.6417e-04 eta 0:14:17
epoch [40/50] batch [200/204] time 0.251 (0.402) data 0.000 (0.003) loss 0.4406 (0.8000) lr 4.6417e-04 eta 0:13:41
epoch [41/50] batch [20/204] time 0.259 (0.278) data 0.004 (0.028) loss 0.0969 (0.8378) lr 4.1221e-04 eta 0:09:21
epoch [41/50] batch [40/204] time 0.275 (0.279) data 0.000 (0.014) loss 1.5427 (0.8699) lr 4.1221e-04 eta 0:09:17
epoch [41/50] batch [60/204] time 0.252 (0.283) data 0.000 (0.009) loss 0.7546 (0.8737) lr 4.1221e-04 eta 0:09:19
epoch [41/50] batch [80/204] time 0.252 (0.274) data 0.000 (0.007) loss 1.3237 (0.8749) lr 4.1221e-04 eta 0:08:57
epoch [41/50] batch [100/204] time 0.253 (0.270) data 0.000 (0.006) loss 1.2575 (0.8617) lr 4.1221e-04 eta 0:08:42
epoch [41/50] batch [120/204] time 0.278 (0.271) data 0.000 (0.005) loss 0.7156 (0.8662) lr 4.1221e-04 eta 0:08:40
epoch [41/50] batch [140/204] time 0.251 (0.275) data 0.000 (0.004) loss 0.2501 (0.8204) lr 4.1221e-04 eta 0:08:42
epoch [41/50] batch [160/204] time 0.347 (0.276) data 0.000 (0.004) loss 0.7420 (0.8273) lr 4.1221e-04 eta 0:08:39
epoch [41/50] batch [180/204] time 0.422 (0.277) data 0.000 (0.003) loss 0.4991 (0.8465) lr 4.1221e-04 eta 0:08:34
epoch [41/50] batch [200/204] time 0.248 (0.278) data 0.000 (0.003) loss 0.0914 (0.8496) lr 4.1221e-04 eta 0:08:32
epoch [42/50] batch [20/204] time 0.251 (0.355) data 0.000 (0.030) loss 0.5146 (0.9598) lr 3.6258e-04 eta 0:10:45
epoch [42/50] batch [40/204] time 0.250 (0.302) data 0.000 (0.015) loss 1.1900 (0.9649) lr 3.6258e-04 eta 0:09:02
epoch [42/50] batch [60/204] time 0.288 (0.289) data 0.000 (0.010) loss 1.3361 (1.0734) lr 3.6258e-04 eta 0:08:32
epoch [42/50] batch [80/204] time 0.279 (0.286) data 0.000 (0.008) loss 0.3235 (0.9732) lr 3.6258e-04 eta 0:08:21
epoch [42/50] batch [100/204] time 0.251 (0.301) data 0.000 (0.006) loss 0.8859 (0.9716) lr 3.6258e-04 eta 0:08:41
epoch [42/50] batch [120/204] time 0.251 (0.292) data 0.000 (0.005) loss 0.2114 (0.9986) lr 3.6258e-04 eta 0:08:21
epoch [42/50] batch [140/204] time 0.263 (0.286) data 0.000 (0.005) loss 1.6126 (0.9482) lr 3.6258e-04 eta 0:08:05
epoch [42/50] batch [160/204] time 0.259 (0.285) data 0.000 (0.004) loss 1.4234 (0.9420) lr 3.6258e-04 eta 0:07:58
epoch [42/50] batch [180/204] time 0.474 (0.299) data 0.000 (0.004) loss 1.7747 (0.9288) lr 3.6258e-04 eta 0:08:15
epoch [42/50] batch [200/204] time 0.245 (0.308) data 0.000 (0.003) loss 1.1014 (0.9305) lr 3.6258e-04 eta 0:08:23
epoch [43/50] batch [20/204] time 0.474 (0.499) data 0.000 (0.028) loss 0.7416 (0.7552) lr 3.1545e-04 eta 0:13:24
epoch [43/50] batch [40/204] time 0.245 (0.406) data 0.000 (0.014) loss 0.5888 (0.7852) lr 3.1545e-04 eta 0:10:46
epoch [43/50] batch [60/204] time 0.471 (0.428) data 0.000 (0.010) loss 0.7940 (0.8320) lr 3.1545e-04 eta 0:11:12
epoch [43/50] batch [80/204] time 0.478 (0.411) data 0.000 (0.007) loss 0.4134 (0.8229) lr 3.1545e-04 eta 0:10:37
epoch [43/50] batch [100/204] time 0.478 (0.423) data 0.000 (0.006) loss 0.9784 (0.8225) lr 3.1545e-04 eta 0:10:47
epoch [43/50] batch [120/204] time 0.469 (0.403) data 0.000 (0.005) loss 0.8546 (0.8347) lr 3.1545e-04 eta 0:10:09
epoch [43/50] batch [140/204] time 0.474 (0.414) data 0.000 (0.004) loss 0.4617 (0.8685) lr 3.1545e-04 eta 0:10:16
epoch [43/50] batch [160/204] time 0.473 (0.407) data 0.000 (0.004) loss 0.7406 (0.8681) lr 3.1545e-04 eta 0:09:58
epoch [43/50] batch [180/204] time 0.251 (0.412) data 0.000 (0.003) loss 2.2079 (0.8766) lr 3.1545e-04 eta 0:09:58
epoch [43/50] batch [200/204] time 0.476 (0.404) data 0.000 (0.003) loss 0.5408 (0.8476) lr 3.1545e-04 eta 0:09:38
epoch [44/50] batch [20/204] time 0.249 (0.392) data 0.000 (0.028) loss 0.6087 (0.8371) lr 2.7103e-04 eta 0:09:12
epoch [44/50] batch [40/204] time 0.472 (0.404) data 0.000 (0.014) loss 0.4393 (0.7658) lr 2.7103e-04 eta 0:09:20
epoch [44/50] batch [60/204] time 0.249 (0.394) data 0.000 (0.010) loss 0.0199 (0.7455) lr 2.7103e-04 eta 0:08:58
epoch [44/50] batch [80/204] time 0.466 (0.409) data 0.000 (0.007) loss 0.4351 (0.8062) lr 2.7103e-04 eta 0:09:11
epoch [44/50] batch [100/204] time 0.472 (0.399) data 0.000 (0.006) loss 0.6662 (0.8053) lr 2.7103e-04 eta 0:08:50
epoch [44/50] batch [120/204] time 0.472 (0.411) data 0.000 (0.005) loss 0.4426 (0.8105) lr 2.7103e-04 eta 0:08:58
epoch [44/50] batch [140/204] time 0.253 (0.395) data 0.000 (0.004) loss 0.1688 (0.8043) lr 2.7103e-04 eta 0:08:28
epoch [44/50] batch [160/204] time 0.257 (0.380) data 0.001 (0.004) loss 0.9234 (0.8280) lr 2.7103e-04 eta 0:08:01
epoch [44/50] batch [180/204] time 0.250 (0.368) data 0.000 (0.003) loss 1.5826 (0.8344) lr 2.7103e-04 eta 0:07:39
epoch [44/50] batch [200/204] time 0.245 (0.356) data 0.000 (0.003) loss 0.2669 (0.8215) lr 2.7103e-04 eta 0:07:17
epoch [45/50] batch [20/204] time 0.252 (0.301) data 0.000 (0.030) loss 2.5291 (1.0560) lr 2.2949e-04 eta 0:06:02
epoch [45/50] batch [40/204] time 0.274 (0.280) data 0.000 (0.015) loss 0.8982 (0.8890) lr 2.2949e-04 eta 0:05:30
epoch [45/50] batch [60/204] time 0.249 (0.290) data 0.000 (0.010) loss 0.8565 (0.8928) lr 2.2949e-04 eta 0:05:37
epoch [45/50] batch [80/204] time 0.247 (0.280) data 0.000 (0.008) loss 0.8519 (0.9001) lr 2.2949e-04 eta 0:05:19
epoch [45/50] batch [100/204] time 0.251 (0.273) data 0.000 (0.006) loss 1.7418 (0.8817) lr 2.2949e-04 eta 0:05:07
epoch [45/50] batch [120/204] time 0.288 (0.270) data 0.000 (0.005) loss 1.0510 (0.9004) lr 2.2949e-04 eta 0:04:58
epoch [45/50] batch [140/204] time 0.276 (0.272) data 0.000 (0.005) loss 1.5243 (0.8825) lr 2.2949e-04 eta 0:04:54
epoch [45/50] batch [160/204] time 0.557 (0.300) data 0.000 (0.004) loss 0.1949 (0.9185) lr 2.2949e-04 eta 0:05:19
epoch [45/50] batch [180/204] time 0.559 (0.329) data 0.000 (0.004) loss 0.5523 (0.9191) lr 2.2949e-04 eta 0:05:43
epoch [45/50] batch [200/204] time 0.557 (0.352) data 0.000 (0.003) loss 0.4473 (0.9241) lr 2.2949e-04 eta 0:06:00
epoch [46/50] batch [20/204] time 0.563 (0.586) data 0.000 (0.027) loss 1.0806 (0.8111) lr 1.9098e-04 eta 0:09:46
epoch [46/50] batch [40/204] time 0.556 (0.572) data 0.000 (0.014) loss 0.1793 (0.7353) lr 1.9098e-04 eta 0:09:20
epoch [46/50] batch [60/204] time 0.563 (0.568) data 0.000 (0.009) loss 1.1116 (0.8788) lr 1.9098e-04 eta 0:09:05
epoch [46/50] batch [80/204] time 0.559 (0.565) data 0.000 (0.007) loss 0.2905 (0.8857) lr 1.9098e-04 eta 0:08:51
epoch [46/50] batch [100/204] time 0.558 (0.564) data 0.000 (0.006) loss 1.2743 (0.8997) lr 1.9098e-04 eta 0:08:39
epoch [46/50] batch [120/204] time 0.559 (0.563) data 0.000 (0.005) loss 0.5824 (0.9168) lr 1.9098e-04 eta 0:08:27
epoch [46/50] batch [140/204] time 0.558 (0.563) data 0.000 (0.004) loss 1.8958 (0.8981) lr 1.9098e-04 eta 0:08:15
epoch [46/50] batch [160/204] time 0.561 (0.563) data 0.000 (0.004) loss 1.4619 (0.9222) lr 1.9098e-04 eta 0:08:03
epoch [46/50] batch [180/204] time 0.558 (0.562) data 0.000 (0.003) loss 0.8564 (0.9207) lr 1.9098e-04 eta 0:07:52
epoch [46/50] batch [200/204] time 0.564 (0.562) data 0.000 (0.003) loss 0.1282 (0.9047) lr 1.9098e-04 eta 0:07:40
epoch [47/50] batch [20/204] time 0.558 (0.587) data 0.000 (0.028) loss 1.4810 (0.7293) lr 1.5567e-04 eta 0:07:47
epoch [47/50] batch [40/204] time 0.560 (0.573) data 0.000 (0.014) loss 0.2653 (0.7429) lr 1.5567e-04 eta 0:07:24
epoch [47/50] batch [60/204] time 0.560 (0.568) data 0.000 (0.009) loss 0.7851 (0.7745) lr 1.5567e-04 eta 0:07:09
epoch [47/50] batch [80/204] time 0.558 (0.565) data 0.000 (0.007) loss 1.2463 (0.8239) lr 1.5567e-04 eta 0:06:55
epoch [47/50] batch [100/204] time 0.561 (0.564) data 0.000 (0.006) loss 0.4636 (0.8061) lr 1.5567e-04 eta 0:06:43
epoch [47/50] batch [120/204] time 0.561 (0.563) data 0.000 (0.005) loss 0.8483 (0.8175) lr 1.5567e-04 eta 0:06:31
epoch [47/50] batch [140/204] time 0.560 (0.562) data 0.000 (0.004) loss 0.3105 (0.8480) lr 1.5567e-04 eta 0:06:19
epoch [47/50] batch [160/204] time 0.557 (0.562) data 0.000 (0.004) loss 0.7057 (0.8388) lr 1.5567e-04 eta 0:06:08
epoch [47/50] batch [180/204] time 0.560 (0.561) data 0.000 (0.003) loss 0.7554 (0.8390) lr 1.5567e-04 eta 0:05:56
epoch [47/50] batch [200/204] time 0.555 (0.561) data 0.000 (0.003) loss 0.7118 (0.8212) lr 1.5567e-04 eta 0:05:45
epoch [48/50] batch [20/204] time 0.559 (0.584) data 0.000 (0.028) loss 1.3526 (0.9552) lr 1.2369e-04 eta 0:05:45
epoch [48/50] batch [40/204] time 0.565 (0.571) data 0.002 (0.014) loss 0.2937 (0.8065) lr 1.2369e-04 eta 0:05:26
epoch [48/50] batch [60/204] time 0.561 (0.567) data 0.000 (0.010) loss 0.4728 (0.7421) lr 1.2369e-04 eta 0:05:12
epoch [48/50] batch [80/204] time 0.553 (0.565) data 0.000 (0.007) loss 0.0663 (0.7615) lr 1.2369e-04 eta 0:05:00
epoch [48/50] batch [100/204] time 0.561 (0.564) data 0.000 (0.006) loss 0.6768 (0.7838) lr 1.2369e-04 eta 0:04:48
epoch [48/50] batch [120/204] time 0.561 (0.563) data 0.000 (0.005) loss 0.4174 (0.8194) lr 1.2369e-04 eta 0:04:36
epoch [48/50] batch [140/204] time 0.563 (0.562) data 0.000 (0.004) loss 0.0909 (0.8113) lr 1.2369e-04 eta 0:04:25
epoch [48/50] batch [160/204] time 0.558 (0.562) data 0.000 (0.004) loss 1.1026 (0.8162) lr 1.2369e-04 eta 0:04:13
epoch [48/50] batch [180/204] time 0.562 (0.562) data 0.000 (0.003) loss 0.4271 (0.7976) lr 1.2369e-04 eta 0:04:02
epoch [48/50] batch [200/204] time 0.556 (0.561) data 0.000 (0.003) loss 0.7012 (0.7919) lr 1.2369e-04 eta 0:03:51
epoch [49/50] batch [20/204] time 0.553 (0.586) data 0.000 (0.028) loss 0.0096 (0.7179) lr 9.5173e-05 eta 0:03:47
epoch [49/50] batch [40/204] time 0.559 (0.572) data 0.000 (0.014) loss 1.1090 (0.6089) lr 9.5173e-05 eta 0:03:30
epoch [49/50] batch [60/204] time 0.557 (0.567) data 0.000 (0.010) loss 0.0539 (0.6923) lr 9.5173e-05 eta 0:03:17
epoch [49/50] batch [80/204] time 0.558 (0.565) data 0.000 (0.007) loss 0.5399 (0.7543) lr 9.5173e-05 eta 0:03:05
epoch [49/50] batch [100/204] time 0.554 (0.563) data 0.000 (0.006) loss 1.6003 (0.7467) lr 9.5173e-05 eta 0:02:53
epoch [49/50] batch [120/204] time 0.557 (0.562) data 0.000 (0.005) loss 0.7033 (0.7818) lr 9.5173e-05 eta 0:02:41
epoch [49/50] batch [140/204] time 0.556 (0.562) data 0.000 (0.004) loss 2.6085 (0.7764) lr 9.5173e-05 eta 0:02:30
epoch [49/50] batch [160/204] time 0.557 (0.561) data 0.000 (0.004) loss 1.9484 (0.8025) lr 9.5173e-05 eta 0:02:19
epoch [49/50] batch [180/204] time 0.562 (0.561) data 0.000 (0.003) loss 1.0426 (0.8106) lr 9.5173e-05 eta 0:02:07
epoch [49/50] batch [200/204] time 0.558 (0.561) data 0.000 (0.003) loss 1.0834 (0.8037) lr 9.5173e-05 eta 0:01:56
epoch [50/50] batch [20/204] time 0.561 (0.587) data 0.000 (0.028) loss 0.3733 (0.8251) lr 7.0224e-05 eta 0:01:48
epoch [50/50] batch [40/204] time 0.553 (0.571) data 0.000 (0.014) loss 0.5425 (0.8229) lr 7.0224e-05 eta 0:01:33
epoch [50/50] batch [60/204] time 0.555 (0.567) data 0.000 (0.010) loss 1.1390 (0.8722) lr 7.0224e-05 eta 0:01:21
epoch [50/50] batch [80/204] time 0.563 (0.565) data 0.001 (0.007) loss 0.4317 (0.9360) lr 7.0224e-05 eta 0:01:10
epoch [50/50] batch [100/204] time 0.252 (0.560) data 0.000 (0.006) loss 0.3066 (0.9246) lr 7.0224e-05 eta 0:00:58
epoch [50/50] batch [120/204] time 0.576 (0.547) data 0.000 (0.005) loss 0.3364 (0.8709) lr 7.0224e-05 eta 0:00:45
epoch [50/50] batch [140/204] time 0.575 (0.550) data 0.000 (0.004) loss 0.2714 (0.8759) lr 7.0224e-05 eta 0:00:35
epoch [50/50] batch [160/204] time 0.582 (0.552) data 0.000 (0.004) loss 0.9171 (0.8846) lr 7.0224e-05 eta 0:00:24
epoch [50/50] batch [180/204] time 0.575 (0.554) data 0.000 (0.003) loss 2.5218 (0.8776) lr 7.0224e-05 eta 0:00:13
epoch [50/50] batch [200/204] time 0.560 (0.548) data 0.000 (0.003) loss 0.5013 (0.8704) lr 7.0224e-05 eta 0:00:02
Checkpoint saved to output/base2new/train_base/ucf101/vit_b16_ep50_c4_BZ4_ProDA/seed1/prompt_learner/model.pth.tar-50
Finish training
Deploy the last-epoch model
Evaluate on the *test* set
=> result
* total: 1,946
* correct: 1,721
* accuracy: 88.44%
* error: 11.56%
* macro_f1: 87.90%
Elapsed: 1:18:41
