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cub_inc.log
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2023-02-02 22:52:24,855 - mmcls - INFO - Environment info:
------------------------------------------------------------
sys.platform: linux
Python: 3.8.13 | packaged by conda-forge | (default, Mar 25 2022, 06:04:10) [GCC 10.3.0]
CUDA available: True
GPU 0,1,2,3,4,5,6,7: A100-SXM4-40GB
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 11.7, V11.7.99
GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
PyTorch: 1.13.0a0+340c412
PyTorch compiling details: PyTorch built with:
- GCC 9.4
- C++ Version: 201402
- Intel(R) Math Kernel Library Version 2020.0.4 Product Build 20200917 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v2.6.0 (Git Hash N/A)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- LAPACK is enabled (usually provided by MKL)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 11.7
- NVCC architecture flags: -gencode;arch=compute_52,code=sm_52;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_86,code=compute_86
- CuDNN 8.4.1 (built against CUDA 11.6)
- Magma 2.6.2
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.7, CUDNN_VERSION=8.4.1, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS=-fno-gnu-unique -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.13.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=ON, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,
TorchVision: 0.13.0a0
OpenCV: 3.4.11
MMCV: 1.6.1
MMCV Compiler: GCC 9.4
MMCV CUDA Compiler: 11.7
MMClassification: 0.23.2_71ef7ba+24f49fc
------------------------------------------------------------
2023-02-02 22:52:24,855 - mmcls - INFO - Distributed training: True
2023-02-02 22:52:24,855 - mmcls - INFO - Set random seed to 0, deterministic: True
2023-02-02 22:52:24,962 - mmcls - INFO - ETF head : evaluating 100 out of 200 classes.
2023-02-02 22:52:24,962 - mmcls - INFO - ETF head : with_len : False
2023-02-02 22:52:24,977 - mmcls - INFO - load checkpoint from local path: /opt/logger/cub_etf/best.pth
2023-02-02 22:52:25,063 - mmcls - INFO - The model config:
type = 'ImageClassifierCIL'
backbone = dict(
type='ResNet',
depth=18,
frozen_stages=1,
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet18'),
norm_cfg=dict(type='BN', requires_grad=True))
neck = dict(type='MLPFFNNeck', in_channels=512, out_channels=512)
head = dict(
type='ETFHead',
num_classes=200,
eval_classes=100,
in_channels=512,
loss=dict(type='DRLoss', loss_weight=10.0),
topk=(1, 5),
cal_acc=True,
with_len=False)
2023-02-02 22:52:41,479 - mmcls - INFO - The feat dataset config is :
{'type': 'CUBFSCILDataset', 'data_prefix': '/opt/data/CUB_200_2011', 'pipeline': [{'type': 'LoadImageFromFile'}, {'type': 'Resize', 'size': (256, -1)}, {'type': 'CenterCrop', 'crop_size': 224}, {'type': 'Normalize', 'mean': [123.675, 116.28, 103.53], 'std': [58.395, 57.12, 57.375], 'to_rgb': True}, {'type': 'ImageToTensor', 'keys': ['img']}, {'type': 'Collect', 'keys': ['img', 'gt_label'], 'meta_keys': ('filename', 'ori_filename', 'ori_shape', 'img_shape', 'flip', 'flip_direction', 'img_norm_cfg', 'cls_id', 'img_id')}], 'num_cls': 100, 'subset': 'train'}
2023-02-02 22:52:54,191 - mmcls - INFO - Feat init done with 100 classes
2023-02-02 22:53:00,324 - mmcls - INFO - Memory done with 100 classes
2023-02-02 22:53:00,401 - mmcls - INFO - The test dataset config is :
{'type': 'CUBFSCILDataset', 'data_prefix': '/opt/data/CUB_200_2011', 'pipeline': [{'type': 'LoadImageFromFile'}, {'type': 'Resize', 'size': (256, -1)}, {'type': 'CenterCrop', 'crop_size': 224}, {'type': 'Normalize', 'mean': [123.675, 116.28, 103.53], 'std': [58.395, 57.12, 57.375], 'to_rgb': True}, {'type': 'ImageToTensor', 'keys': ['img']}, {'type': 'Collect', 'keys': ['img', 'gt_label'], 'meta_keys': ('filename', 'ori_filename', 'ori_shape', 'img_shape', 'flip', 'flip_direction', 'img_norm_cfg', 'cls_id', 'img_id')}], 'num_cls': 200, 'subset': 'test'}
2023-02-02 22:53:10,966 - mmcls - INFO - Test memory done with 200 classes
2023-02-02 22:53:11,069 - mmcls - INFO - The incremental dataset config is :
{'type': 'CUBFSCILDataset', 'data_prefix': '/opt/data/CUB_200_2011', 'pipeline': [{'type': 'LoadImageFromFile'}, {'type': 'Resize', 'size': (256, -1)}, {'type': 'CenterCrop', 'crop_size': 224}, {'type': 'Normalize', 'mean': [123.675, 116.28, 103.53], 'std': [58.395, 57.12, 57.375], 'to_rgb': True}, {'type': 'ImageToTensor', 'keys': ['img']}, {'type': 'Collect', 'keys': ['img', 'gt_label'], 'meta_keys': ('filename', 'ori_filename', 'ori_shape', 'img_shape', 'flip', 'flip_direction', 'img_norm_cfg', 'cls_id', 'img_id')}], 'num_cls': 100, 'subset': 'train', 'few_cls': (100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199)}
2023-02-02 22:53:15,310 - mmcls - INFO - Incremental memory done with 100 classes
2023-02-02 22:53:15,570 - mmcls - INFO - Evaluating session 1, from 0 to 100.
2023-02-02 22:53:18,272 - mmcls - INFO - [01]Evaluation results : acc : 80.45 ; acc_base : 80.45 ; acc_inc : nan
2023-02-02 22:53:18,273 - mmcls - INFO - [01]Evaluation results : acc_incremental_old : nan ; acc_incremental_new : 81.21
2023-02-02 22:53:18,291 - mmcls - INFO - Start to execute the incremental sessions.
2023-02-02 22:53:18,354 - mmcls - INFO - Starting session : 2 ------------------------------------------------------------
2023-02-02 22:53:18,354 - mmcls - INFO - Newly added classes are from 100 to 110.
2023-02-02 22:53:18,354 - mmcls - INFO - Model now can classify 110 classes
2023-02-02 22:53:18,354 - mmcls - INFO - 105 steps
2023-02-02 22:53:18,354 - mmcls - INFO - Extracting mean neck feat from 100 to 100
2023-02-02 22:53:18,354 - mmcls - INFO - Copy 1 duplications.
2023-02-02 22:53:18,362 - mmcls - INFO - Session : 2 ; The dataset has 150 samples.
2023-02-02 22:53:18,362 - mmcls - INFO - Labels : [100, 100, 100, 100, 100, 101, 101, 101, 101, 101, 102, 102, 102, 102, 102, 103, 103, 103, 103, 103, 104, 104, 104, 104, 104, 105, 105, 105, 105, 105, 106, 106, 106, 106, 106, 107, 107, 107, 107, 107, 108, 108, 108, 108, 108, 109, 109, 109, 109, 109, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
2023-02-02 22:53:19,813 - mmcls - INFO - [001/105] Training session : 2 ; lr : 0.013996580463334516 ; loss : 3.286500930786133 ; acc@1 : 37.5
2023-02-02 22:53:19,872 - mmcls - INFO - [002/105] Training session : 2 ; lr : 0.02297753430315587 ; loss : 1.964250087738037 ; acc@1 : 62.5
2023-02-02 22:53:22,471 - mmcls - INFO - [003/105] Training session : 2 ; lr : 0.031929701519312785 ; loss : 2.4199702739715576 ; acc@1 : 37.5
2023-02-02 22:53:22,559 - mmcls - INFO - [004/105] Training session : 2 ; lr : 0.04083996786317733 ; loss : 1.1719365119934082 ; acc@1 : 62.5
2023-02-02 22:53:24,613 - mmcls - INFO - [005/105] Training session : 2 ; lr : 0.04969528642972966 ; loss : 1.0685603618621826 ; acc@1 : 62.5
2023-02-02 22:53:24,657 - mmcls - INFO - [006/105] Training session : 2 ; lr : 0.049561609455535054 ; loss : 1.0445739030838013 ; acc@1 : 75.0
2023-02-02 22:53:26,860 - mmcls - INFO - [007/105] Training session : 2 ; lr : 0.049403939857984004 ; loss : 0.9587773084640503 ; acc@1 : 100.0
2023-02-02 22:53:26,914 - mmcls - INFO - [008/105] Training session : 2 ; lr : 0.04922243323793362 ; loss : 0.7616921663284302 ; acc@1 : 100.0
2023-02-02 22:53:29,124 - mmcls - INFO - [009/105] Training session : 2 ; lr : 0.049017268720504346 ; loss : 0.8058239221572876 ; acc@1 : 75.0
2023-02-02 22:53:29,156 - mmcls - INFO - [010/105] Training session : 2 ; lr : 0.048788648778305056 ; loss : 0.4859812557697296 ; acc@1 : 100.0
2023-02-02 22:53:31,860 - mmcls - INFO - [011/105] Training session : 2 ; lr : 0.04853679903161708 ; loss : 0.3232855200767517 ; acc@1 : 87.5
2023-02-02 22:53:31,883 - mmcls - INFO - [012/105] Training session : 2 ; lr : 0.04826196802573422 ; loss : 0.47530466318130493 ; acc@1 : 87.5
2023-02-02 22:53:34,314 - mmcls - INFO - [013/105] Training session : 2 ; lr : 0.047964426985678536 ; loss : 0.6220536828041077 ; acc@1 : 75.0
2023-02-02 22:53:34,341 - mmcls - INFO - [014/105] Training session : 2 ; lr : 0.047644469548533984 ; loss : 0.2263334095478058 ; acc@1 : 100.0
2023-02-02 22:53:36,762 - mmcls - INFO - [015/105] Training session : 2 ; lr : 0.047302411473662105 ; loss : 0.6917569041252136 ; acc@1 : 87.5
2023-02-02 22:53:36,818 - mmcls - INFO - [016/105] Training session : 2 ; lr : 0.046938590331085626 ; loss : 0.5628376007080078 ; acc@1 : 87.5
2023-02-02 22:53:39,812 - mmcls - INFO - [017/105] Training session : 2 ; lr : 0.046553365168347606 ; loss : 0.23016107082366943 ; acc@1 : 87.5
2023-02-02 22:53:39,857 - mmcls - INFO - [018/105] Training session : 2 ; lr : 0.046147116156174874 ; loss : 0.33004269003868103 ; acc@1 : 87.5
2023-02-02 22:53:43,188 - mmcls - INFO - [019/105] Training session : 2 ; lr : 0.0457202442132954 ; loss : 0.40612858533859253 ; acc@1 : 100.0
2023-02-02 22:53:43,233 - mmcls - INFO - [020/105] Training session : 2 ; lr : 0.04527317061077995 ; loss : 0.4589177966117859 ; acc@1 : 75.0
2023-02-02 22:53:46,256 - mmcls - INFO - [021/105] Training session : 2 ; lr : 0.04480633655629834 ; loss : 0.47109559178352356 ; acc@1 : 87.5
2023-02-02 22:53:46,286 - mmcls - INFO - [022/105] Training session : 2 ; lr : 0.044320202758700786 ; loss : 0.5115469098091125 ; acc@1 : 87.5
2023-02-02 22:53:48,305 - mmcls - INFO - [023/105] Training session : 2 ; lr : 0.04381524897335388 ; loss : 0.24503134191036224 ; acc@1 : 100.0
2023-02-02 22:53:48,751 - mmcls - INFO - [024/105] Training session : 2 ; lr : 0.04329197352867994 ; loss : 0.6900866031646729 ; acc@1 : 62.5
2023-02-02 22:53:51,478 - mmcls - INFO - [025/105] Training session : 2 ; lr : 0.04275089283436705 ; loss : 0.2451249659061432 ; acc@1 : 87.5
2023-02-02 22:53:51,517 - mmcls - INFO - [026/105] Training session : 2 ; lr : 0.042192540871735046 ; loss : 0.15726597607135773 ; acc@1 : 100.0
2023-02-02 22:53:53,614 - mmcls - INFO - [027/105] Training session : 2 ; lr : 0.04161746866676039 ; loss : 0.3654751777648926 ; acc@1 : 100.0
2023-02-02 22:53:53,669 - mmcls - INFO - [028/105] Training session : 2 ; lr : 0.041026243746280076 ; loss : 0.13274294137954712 ; acc@1 : 100.0
2023-02-02 22:53:55,714 - mmcls - INFO - [029/105] Training session : 2 ; lr : 0.04041944957791117 ; loss : 0.2877197563648224 ; acc@1 : 100.0
2023-02-02 22:53:55,946 - mmcls - INFO - [030/105] Training session : 2 ; lr : 0.03979768499423871 ; loss : 0.16928309202194214 ; acc@1 : 100.0
2023-02-02 22:53:58,304 - mmcls - INFO - [031/105] Training session : 2 ; lr : 0.039161563601840234 ; loss : 0.14114466309547424 ; acc@1 : 100.0
2023-02-02 22:53:58,345 - mmcls - INFO - [032/105] Training session : 2 ; lr : 0.03851171317573017 ; loss : 0.16396895051002502 ; acc@1 : 100.0
2023-02-02 22:54:00,305 - mmcls - INFO - [033/105] Training session : 2 ; lr : 0.037848775039821696 ; loss : 0.11629868298768997 ; acc@1 : 100.0
2023-02-02 22:54:00,349 - mmcls - INFO - [034/105] Training session : 2 ; lr : 0.037173403434017455 ; loss : 0.11085197329521179 ; acc@1 : 100.0
2023-02-02 22:54:02,237 - mmcls - INFO - [035/105] Training session : 2 ; lr : 0.03648626486855378 ; loss : 0.11950893700122833 ; acc@1 : 100.0
2023-02-02 22:54:02,309 - mmcls - INFO - [036/105] Training session : 2 ; lr : 0.03578803746623555 ; loss : 0.23046085238456726 ; acc@1 : 87.5
2023-02-02 22:54:04,478 - mmcls - INFO - [037/105] Training session : 2 ; lr : 0.03507941029321082 ; loss : 0.10603529214859009 ; acc@1 : 100.0
2023-02-02 22:54:04,508 - mmcls - INFO - [038/105] Training session : 2 ; lr : 0.03436108267894578 ; loss : 0.11474210768938065 ; acc@1 : 100.0
2023-02-02 22:54:06,250 - mmcls - INFO - [039/105] Training session : 2 ; lr : 0.03363376352607097 ; loss : 0.1086842268705368 ; acc@1 : 100.0
2023-02-02 22:54:06,269 - mmcls - INFO - [040/105] Training session : 2 ; lr : 0.03289817061077995 ; loss : 0.1097194105386734 ; acc@1 : 100.0
2023-02-02 22:54:08,768 - mmcls - INFO - [041/105] Training session : 2 ; lr : 0.03215502987447093 ; loss : 0.09597238153219223 ; acc@1 : 100.0
2023-02-02 22:54:08,777 - mmcls - INFO - [042/105] Training session : 2 ; lr : 0.031405074707330165 ; loss : 0.12455995380878448 ; acc@1 : 100.0
2023-02-02 22:54:10,969 - mmcls - INFO - [043/105] Training session : 2 ; lr : 0.030649045224564433 ; loss : 0.23367264866828918 ; acc@1 : 87.5
2023-02-02 22:54:11,007 - mmcls - INFO - [044/105] Training session : 2 ; lr : 0.02988768753599669 ; loss : 0.19089697301387787 ; acc@1 : 100.0
2023-02-02 22:54:12,765 - mmcls - INFO - [045/105] Training session : 2 ; lr : 0.02912175300974572 ; loss : 0.1337914764881134 ; acc@1 : 100.0
2023-02-02 22:54:12,910 - mmcls - INFO - [046/105] Training session : 2 ; lr : 0.028351997530716534 ; loss : 0.19977150857448578 ; acc@1 : 100.0
2023-02-02 22:54:15,068 - mmcls - INFO - [047/105] Training session : 2 ; lr : 0.027579180754633236 ; loss : 0.1496385782957077 ; acc@1 : 100.0
2023-02-02 22:54:15,100 - mmcls - INFO - [048/105] Training session : 2 ; lr : 0.02680406535835051 ; loss : 0.10606132447719574 ; acc@1 : 100.0
2023-02-02 22:54:17,320 - mmcls - INFO - [049/105] Training session : 2 ; lr : 0.026027416287183677 ; loss : 0.10013772547245026 ; acc@1 : 100.0
2023-02-02 22:54:17,491 - mmcls - INFO - [050/105] Training session : 2 ; lr : 0.02525 ; loss : 0.08235478401184082 ; acc@1 : 100.0
2023-02-02 22:54:19,062 - mmcls - INFO - [051/105] Training session : 2 ; lr : 0.024472583712816326 ; loss : 0.05960825830698013 ; acc@1 : 100.0
2023-02-02 22:54:19,088 - mmcls - INFO - [052/105] Training session : 2 ; lr : 0.023695934641649496 ; loss : 0.09206221997737885 ; acc@1 : 100.0
2023-02-02 22:54:21,564 - mmcls - INFO - [053/105] Training session : 2 ; lr : 0.02292081924536677 ; loss : 0.0943697839975357 ; acc@1 : 100.0
2023-02-02 22:54:21,621 - mmcls - INFO - [054/105] Training session : 2 ; lr : 0.02214800246928347 ; loss : 0.08314836770296097 ; acc@1 : 100.0
2023-02-02 22:54:24,384 - mmcls - INFO - [055/105] Training session : 2 ; lr : 0.02137824699025428 ; loss : 0.07730897516012192 ; acc@1 : 100.0
2023-02-02 22:54:24,411 - mmcls - INFO - [056/105] Training session : 2 ; lr : 0.020612312464003312 ; loss : 0.093951016664505 ; acc@1 : 100.0
2023-02-02 22:54:26,814 - mmcls - INFO - [057/105] Training session : 2 ; lr : 0.01985095477543558 ; loss : 0.1289103776216507 ; acc@1 : 100.0
2023-02-02 22:54:26,856 - mmcls - INFO - [058/105] Training session : 2 ; lr : 0.01909492529266985 ; loss : 0.06651660054922104 ; acc@1 : 100.0
2023-02-02 22:54:28,569 - mmcls - INFO - [059/105] Training session : 2 ; lr : 0.01834497012552908 ; loss : 0.052859216928482056 ; acc@1 : 100.0
2023-02-02 22:54:28,680 - mmcls - INFO - [060/105] Training session : 2 ; lr : 0.017601829389220055 ; loss : 0.08541389554738998 ; acc@1 : 100.0
2023-02-02 22:54:30,513 - mmcls - INFO - [061/105] Training session : 2 ; lr : 0.01686623647392904 ; loss : 0.059888120740652084 ; acc@1 : 100.0
2023-02-02 22:54:30,697 - mmcls - INFO - [062/105] Training session : 2 ; lr : 0.016138917321054224 ; loss : 0.07462304085493088 ; acc@1 : 100.0
2023-02-02 22:54:32,406 - mmcls - INFO - [063/105] Training session : 2 ; lr : 0.015420589706789183 ; loss : 0.06065264344215393 ; acc@1 : 100.0
2023-02-02 22:54:32,469 - mmcls - INFO - [064/105] Training session : 2 ; lr : 0.014711962533764453 ; loss : 0.06691773980855942 ; acc@1 : 100.0
2023-02-02 22:54:35,140 - mmcls - INFO - [065/105] Training session : 2 ; lr : 0.01401373513144622 ; loss : 0.05416536703705788 ; acc@1 : 100.0
2023-02-02 22:54:35,191 - mmcls - INFO - [066/105] Training session : 2 ; lr : 0.013326596565982543 ; loss : 0.06254229694604874 ; acc@1 : 100.0
2023-02-02 22:54:37,387 - mmcls - INFO - [067/105] Training session : 2 ; lr : 0.012651224960178311 ; loss : 0.06377306580543518 ; acc@1 : 100.0
2023-02-02 22:54:37,395 - mmcls - INFO - [068/105] Training session : 2 ; lr : 0.011988286824269829 ; loss : 0.07012422382831573 ; acc@1 : 100.0
2023-02-02 22:54:40,099 - mmcls - INFO - [069/105] Training session : 2 ; lr : 0.011338436398159775 ; loss : 0.061678580939769745 ; acc@1 : 100.0
2023-02-02 22:54:40,112 - mmcls - INFO - [070/105] Training session : 2 ; lr : 0.010702315005761293 ; loss : 0.06727185100317001 ; acc@1 : 100.0
2023-02-02 22:54:42,719 - mmcls - INFO - [071/105] Training session : 2 ; lr : 0.010080550422088838 ; loss : 0.11649445444345474 ; acc@1 : 100.0
2023-02-02 22:54:42,753 - mmcls - INFO - [072/105] Training session : 2 ; lr : 0.00947375625371993 ; loss : 0.05861330404877663 ; acc@1 : 100.0
2023-02-02 22:54:44,705 - mmcls - INFO - [073/105] Training session : 2 ; lr : 0.00888253133323962 ; loss : 0.08542508631944656 ; acc@1 : 100.0
2023-02-02 22:54:44,777 - mmcls - INFO - [074/105] Training session : 2 ; lr : 0.008307459128264954 ; loss : 0.0433538481593132 ; acc@1 : 100.0
2023-02-02 22:54:46,683 - mmcls - INFO - [075/105] Training session : 2 ; lr : 0.00774910716563295 ; loss : 0.1128557026386261 ; acc@1 : 100.0
2023-02-02 22:54:46,720 - mmcls - INFO - [076/105] Training session : 2 ; lr : 0.007208026471320069 ; loss : 0.04902224242687225 ; acc@1 : 100.0
2023-02-02 22:54:49,006 - mmcls - INFO - [077/105] Training session : 2 ; lr : 0.0066847510266461255 ; loss : 0.05426690727472305 ; acc@1 : 100.0
2023-02-02 22:54:49,027 - mmcls - INFO - [078/105] Training session : 2 ; lr : 0.006179797241299219 ; loss : 0.05557336285710335 ; acc@1 : 100.0
2023-02-02 22:54:51,204 - mmcls - INFO - [079/105] Training session : 2 ; lr : 0.005693663443701662 ; loss : 0.11674437671899796 ; acc@1 : 100.0
2023-02-02 22:54:51,244 - mmcls - INFO - [080/105] Training session : 2 ; lr : 0.005226829389220054 ; loss : 0.04662245884537697 ; acc@1 : 100.0
2023-02-02 22:54:53,239 - mmcls - INFO - [081/105] Training session : 2 ; lr : 0.004779755786704592 ; loss : 0.05962803214788437 ; acc@1 : 100.0
2023-02-02 22:54:53,282 - mmcls - INFO - [082/105] Training session : 2 ; lr : 0.004352883843825133 ; loss : 0.056258007884025574 ; acc@1 : 100.0
2023-02-02 22:54:55,514 - mmcls - INFO - [083/105] Training session : 2 ; lr : 0.003946634831652397 ; loss : 0.050242602825164795 ; acc@1 : 100.0
2023-02-02 22:54:55,549 - mmcls - INFO - [084/105] Training session : 2 ; lr : 0.003561409668914382 ; loss : 0.05779450759291649 ; acc@1 : 100.0
2023-02-02 22:54:57,637 - mmcls - INFO - [085/105] Training session : 2 ; lr : 0.0031975885263378972 ; loss : 0.0851137563586235 ; acc@1 : 100.0
2023-02-02 22:54:57,789 - mmcls - INFO - [086/105] Training session : 2 ; lr : 0.002855530451466021 ; loss : 0.045548830181360245 ; acc@1 : 100.0
2023-02-02 22:55:00,158 - mmcls - INFO - [087/105] Training session : 2 ; lr : 0.002535573014321467 ; loss : 0.05351432412862778 ; acc@1 : 100.0
2023-02-02 22:55:00,203 - mmcls - INFO - [088/105] Training session : 2 ; lr : 0.0022380319742657793 ; loss : 0.0634019672870636 ; acc@1 : 100.0
2023-02-02 22:55:02,062 - mmcls - INFO - [089/105] Training session : 2 ; lr : 0.00196320096838292 ; loss : 0.05467429757118225 ; acc@1 : 100.0
2023-02-02 22:55:02,075 - mmcls - INFO - [090/105] Training session : 2 ; lr : 0.0017113512216949502 ; loss : 0.05086154118180275 ; acc@1 : 100.0
2023-02-02 22:55:04,647 - mmcls - INFO - [091/105] Training session : 2 ; lr : 0.0014827312794956592 ; loss : 0.06145728752017021 ; acc@1 : 100.0
2023-02-02 22:55:04,707 - mmcls - INFO - [092/105] Training session : 2 ; lr : 0.0012775667620663809 ; loss : 0.07360727339982986 ; acc@1 : 100.0
2023-02-02 22:55:06,341 - mmcls - INFO - [093/105] Training session : 2 ; lr : 0.001096060142016001 ; loss : 0.06628254055976868 ; acc@1 : 100.0
2023-02-02 22:55:06,370 - mmcls - INFO - [094/105] Training session : 2 ; lr : 0.0009383905444649569 ; loss : 0.07454881072044373 ; acc@1 : 100.0
2023-02-02 22:55:08,162 - mmcls - INFO - [095/105] Training session : 2 ; lr : 0.000804713570270343 ; loss : 0.054232873022556305 ; acc@1 : 100.0
2023-02-02 22:55:08,177 - mmcls - INFO - [096/105] Training session : 2 ; lr : 0.0006951611424666753 ; loss : 0.04755683243274689 ; acc@1 : 100.0
2023-02-02 22:55:10,447 - mmcls - INFO - [097/105] Training session : 2 ; lr : 0.0006098413760737701 ; loss : 0.06737587600946426 ; acc@1 : 100.0
2023-02-02 22:55:10,471 - mmcls - INFO - [098/105] Training session : 2 ; lr : 0.0005488384714002789 ; loss : 0.06362807750701904 ; acc@1 : 100.0
2023-02-02 22:55:12,422 - mmcls - INFO - [099/105] Training session : 2 ; lr : 0.0005122126309481429 ; loss : 0.06739547848701477 ; acc@1 : 100.0
2023-02-02 22:55:12,446 - mmcls - INFO - [100/105] Training session : 2 ; lr : 0.0005 ; loss : 0.04944496601819992 ; acc@1 : 100.0
2023-02-02 22:55:14,364 - mmcls - INFO - [101/105] Training session : 2 ; lr : 5e-05 ; loss : 0.06654848158359528 ; acc@1 : 100.0
2023-02-02 22:55:14,383 - mmcls - INFO - [102/105] Training session : 2 ; lr : 5e-05 ; loss : 0.07766858488321304 ; acc@1 : 100.0
2023-02-02 22:55:16,890 - mmcls - INFO - [103/105] Training session : 2 ; lr : 5e-05 ; loss : 0.08628268539905548 ; acc@1 : 100.0
2023-02-02 22:55:16,927 - mmcls - INFO - [104/105] Training session : 2 ; lr : 5e-05 ; loss : 0.10454295575618744 ; acc@1 : 100.0
2023-02-02 22:55:18,490 - mmcls - INFO - [105/105] Training session : 2 ; lr : 5e-05 ; loss : 0.03920227661728859 ; acc@1 : 100.0
2023-02-02 22:55:18,490 - mmcls - INFO - Evaluating session 2, from 0 to 110.
2023-02-02 22:55:21,198 - mmcls - INFO - [02]Evaluation results : acc : 75.98 ; acc_base : 76.89 ; acc_inc : 66.67
2023-02-02 22:55:21,198 - mmcls - INFO - [02]Evaluation results : acc_incremental_old : 62.79 ; acc_incremental_new : 70.00
2023-02-02 22:55:21,304 - mmcls - INFO - Starting session : 3 ------------------------------------------------------------
2023-02-02 22:55:21,305 - mmcls - INFO - Newly added classes are from 110 to 120.
2023-02-02 22:55:21,305 - mmcls - INFO - Model now can classify 120 classes
2023-02-02 22:55:21,305 - mmcls - INFO - 110 steps
2023-02-02 22:55:21,305 - mmcls - INFO - Extracting mean neck feat from 100 to 110
2023-02-02 22:55:21,305 - mmcls - INFO - Copy 2 duplications.
2023-02-02 22:55:21,326 - mmcls - INFO - Session : 3 ; The dataset has 170 samples.
2023-02-02 22:55:21,326 - mmcls - INFO - Labels : [110, 110, 110, 110, 110, 111, 111, 111, 111, 111, 112, 112, 112, 112, 112, 113, 113, 113, 113, 113, 114, 114, 114, 114, 114, 115, 115, 115, 115, 115, 116, 116, 116, 116, 116, 117, 117, 117, 117, 117, 118, 118, 118, 118, 118, 119, 119, 119, 119, 119, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
2023-02-02 22:55:23,276 - mmcls - INFO - [001/110] Training session : 3 ; lr : 0.013996898355724674 ; loss : 0.6865054965019226 ; acc@1 : 87.5
2023-02-02 22:55:23,327 - mmcls - INFO - [002/110] Training session : 3 ; lr : 0.022979622327405663 ; loss : 1.2556777000427246 ; acc@1 : 75.0
2023-02-02 22:55:25,010 - mmcls - INFO - [003/110] Training session : 3 ; lr : 0.03193623281688458 ; loss : 0.5872669219970703 ; acc@1 : 87.5
2023-02-02 22:55:25,482 - mmcls - INFO - [004/110] Training session : 3 ; lr : 0.04085482837010759 ; loss : 0.9076582789421082 ; acc@1 : 75.0
2023-02-02 22:55:27,562 - mmcls - INFO - [005/110] Training session : 3 ; lr : 0.04972356294907193 ; loss : 0.6981518268585205 ; acc@1 : 100.0
2023-02-02 22:55:27,614 - mmcls - INFO - [006/110] Training session : 3 ; lr : 0.04960225731781609 ; loss : 0.9777036309242249 ; acc@1 : 87.5
2023-02-02 22:55:29,728 - mmcls - INFO - [007/110] Training session : 3 ; lr : 0.049459153118161694 ; loss : 0.8252471089363098 ; acc@1 : 87.5
2023-02-02 22:55:29,765 - mmcls - INFO - [008/110] Training session : 3 ; lr : 0.04929437844774847 ; loss : 0.9032278060913086 ; acc@1 : 87.5
2023-02-02 22:55:32,435 - mmcls - INFO - [009/110] Training session : 3 ; lr : 0.04910808080222237 ; loss : 0.7032055854797363 ; acc@1 : 100.0
2023-02-02 22:55:32,464 - mmcls - INFO - [010/110] Training session : 3 ; lr : 0.04890042694320699 ; loss : 0.7427146434783936 ; acc@1 : 100.0
2023-02-02 22:55:35,250 - mmcls - INFO - [011/110] Training session : 3 ; lr : 0.04867160274902931 ; loss : 0.6711583137512207 ; acc@1 : 87.5
2023-02-02 22:55:35,437 - mmcls - INFO - [012/110] Training session : 3 ; lr : 0.0484218130483335 ; loss : 0.6619877815246582 ; acc@1 : 87.5
2023-02-02 22:55:37,023 - mmcls - INFO - [013/110] Training session : 3 ; lr : 0.04815128143673142 ; loss : 0.5582448244094849 ; acc@1 : 100.0
2023-02-02 22:55:37,102 - mmcls - INFO - [014/110] Training session : 3 ; lr : 0.04786025007665437 ; loss : 0.42587217688560486 ; acc@1 : 100.0
2023-02-02 22:55:39,557 - mmcls - INFO - [015/110] Training session : 3 ; lr : 0.047548979480584876 ; loss : 0.41349467635154724 ; acc@1 : 100.0
2023-02-02 22:55:39,584 - mmcls - INFO - [016/110] Training session : 3 ; lr : 0.047217748277862716 ; loss : 0.4159131646156311 ; acc@1 : 87.5
2023-02-02 22:55:42,025 - mmcls - INFO - [017/110] Training session : 3 ; lr : 0.046866852965273965 ; loss : 0.31071025133132935 ; acc@1 : 100.0
2023-02-02 22:55:42,269 - mmcls - INFO - [018/110] Training session : 3 ; lr : 0.04649660764164619 ; loss : 0.25615638494491577 ; acc@1 : 100.0
2023-02-02 22:55:43,844 - mmcls - INFO - [019/110] Training session : 3 ; lr : 0.04610734372668747 ; loss : 0.32906708121299744 ; acc@1 : 100.0
2023-02-02 22:55:43,877 - mmcls - INFO - [020/110] Training session : 3 ; lr : 0.04569940966432088 ; loss : 0.4191216230392456 ; acc@1 : 100.0
2023-02-02 22:55:46,422 - mmcls - INFO - [021/110] Training session : 3 ; lr : 0.04527317061077995 ; loss : 0.2682168483734131 ; acc@1 : 100.0
2023-02-02 22:55:46,457 - mmcls - INFO - [022/110] Training session : 3 ; lr : 0.044829008107744456 ; loss : 0.293165385723114 ; acc@1 : 100.0
2023-02-02 22:55:48,434 - mmcls - INFO - [023/110] Training session : 3 ; lr : 0.04436731974080884 ; loss : 0.3048434555530548 ; acc@1 : 100.0
2023-02-02 22:55:48,478 - mmcls - INFO - [024/110] Training session : 3 ; lr : 0.043888518783589375 ; loss : 0.25146669149398804 ; acc@1 : 100.0
2023-02-02 22:55:50,277 - mmcls - INFO - [025/110] Training session : 3 ; lr : 0.043393033827788204 ; loss : 0.27829718589782715 ; acc@1 : 100.0
2023-02-02 22:55:50,805 - mmcls - INFO - [026/110] Training session : 3 ; lr : 0.042881308399545785 ; loss : 0.1593140959739685 ; acc@1 : 100.0
2023-02-02 22:55:52,651 - mmcls - INFO - [027/110] Training session : 3 ; lr : 0.0423538005624249 ; loss : 0.15855121612548828 ; acc@1 : 100.0
2023-02-02 22:55:52,673 - mmcls - INFO - [028/110] Training session : 3 ; lr : 0.041810982507381744 ; loss : 0.16799405217170715 ; acc@1 : 100.0
2023-02-02 22:55:55,005 - mmcls - INFO - [029/110] Training session : 3 ; lr : 0.04125334013009104 ; loss : 0.21161121129989624 ; acc@1 : 100.0
2023-02-02 22:55:55,040 - mmcls - INFO - [030/110] Training session : 3 ; lr : 0.040681372596003657 ; loss : 0.14118525385856628 ; acc@1 : 100.0
2023-02-02 22:55:57,605 - mmcls - INFO - [031/110] Training session : 3 ; lr : 0.040095591893525864 ; loss : 0.19253122806549072 ; acc@1 : 100.0
2023-02-02 22:55:57,635 - mmcls - INFO - [032/110] Training session : 3 ; lr : 0.039496522375720426 ; loss : 0.23866024613380432 ; acc@1 : 87.5
2023-02-02 22:56:00,028 - mmcls - INFO - [033/110] Training session : 3 ; lr : 0.03888470029093954 ; loss : 0.16446378827095032 ; acc@1 : 100.0
2023-02-02 22:56:00,075 - mmcls - INFO - [034/110] Training session : 3 ; lr : 0.03826067330280999 ; loss : 0.1119966208934784 ; acc@1 : 100.0
2023-02-02 22:56:02,532 - mmcls - INFO - [035/110] Training session : 3 ; lr : 0.037625000000000006 ; loss : 0.08467012643814087 ; acc@1 : 100.0
2023-02-02 22:56:02,553 - mmcls - INFO - [036/110] Training session : 3 ; lr : 0.03697824939620672 ; loss : 0.1404711902141571 ; acc@1 : 100.0
2023-02-02 22:56:04,441 - mmcls - INFO - [037/110] Training session : 3 ; lr : 0.036321000420811905 ; loss : 0.09009771049022675 ; acc@1 : 100.0
2023-02-02 22:56:04,509 - mmcls - INFO - [038/110] Training session : 3 ; lr : 0.03565384140066175 ; loss : 0.1412317007780075 ; acc@1 : 100.0
2023-02-02 22:56:06,474 - mmcls - INFO - [039/110] Training session : 3 ; lr : 0.03497736953343461 ; loss : 0.09580270946025848 ; acc@1 : 100.0
2023-02-02 22:56:06,482 - mmcls - INFO - [040/110] Training session : 3 ; lr : 0.03429219035306828 ; loss : 0.11318209767341614 ; acc@1 : 100.0
2023-02-02 22:56:09,113 - mmcls - INFO - [041/110] Training session : 3 ; lr : 0.03359891718772505 ; loss : 0.07494843006134033 ; acc@1 : 100.0
2023-02-02 22:56:09,152 - mmcls - INFO - [042/110] Training session : 3 ; lr : 0.03289817061077995 ; loss : 0.11138218641281128 ; acc@1 : 100.0
2023-02-02 22:56:11,865 - mmcls - INFO - [043/110] Training session : 3 ; lr : 0.03219057788532357 ; loss : 0.09020507335662842 ; acc@1 : 100.0
2023-02-02 22:56:11,893 - mmcls - INFO - [044/110] Training session : 3 ; lr : 0.03147677240267659 ; loss : 0.09948361665010452 ; acc@1 : 100.0
2023-02-02 22:56:13,595 - mmcls - INFO - [045/110] Training session : 3 ; lr : 0.030757393115418783 ; loss : 0.07669463753700256 ; acc@1 : 100.0
2023-02-02 22:56:13,633 - mmcls - INFO - [046/110] Training session : 3 ; lr : 0.030033083965439945 ; loss : 0.10751437395811081 ; acc@1 : 100.0
2023-02-02 22:56:16,222 - mmcls - INFO - [047/110] Training session : 3 ; lr : 0.02930449330752466 ; loss : 0.05575541779398918 ; acc@1 : 100.0
2023-02-02 22:56:16,257 - mmcls - INFO - [048/110] Training session : 3 ; lr : 0.028572273328986975 ; loss : 0.052986420691013336 ; acc@1 : 100.0
2023-02-02 22:56:18,932 - mmcls - INFO - [049/110] Training session : 3 ; lr : 0.027837079465874427 ; loss : 0.08617036044597626 ; acc@1 : 100.0
2023-02-02 22:56:18,979 - mmcls - INFO - [050/110] Training session : 3 ; lr : 0.027099569816264005 ; loss : 0.06817776709794998 ; acc@1 : 100.0
2023-02-02 22:56:20,743 - mmcls - INFO - [051/110] Training session : 3 ; lr : 0.02636040455117525 ; loss : 0.06541135907173157 ; acc@1 : 100.0
2023-02-02 22:56:20,774 - mmcls - INFO - [052/110] Training session : 3 ; lr : 0.025620245323627777 ; loss : 0.09246248751878738 ; acc@1 : 100.0
2023-02-02 22:56:23,333 - mmcls - INFO - [053/110] Training session : 3 ; lr : 0.024879754676372233 ; loss : 0.07907573878765106 ; acc@1 : 100.0
2023-02-02 22:56:23,391 - mmcls - INFO - [054/110] Training session : 3 ; lr : 0.024139595448824765 ; loss : 0.05118783563375473 ; acc@1 : 100.0
2023-02-02 22:56:25,190 - mmcls - INFO - [055/110] Training session : 3 ; lr : 0.023400430183736002 ; loss : 0.060890503227710724 ; acc@1 : 100.0
2023-02-02 22:56:25,656 - mmcls - INFO - [056/110] Training session : 3 ; lr : 0.022662920534125584 ; loss : 0.05122780799865723 ; acc@1 : 100.0
2023-02-02 22:56:27,441 - mmcls - INFO - [057/110] Training session : 3 ; lr : 0.021927726671013035 ; loss : 0.041127972304821014 ; acc@1 : 100.0
2023-02-02 22:56:27,601 - mmcls - INFO - [058/110] Training session : 3 ; lr : 0.021195506692475344 ; loss : 0.045693203806877136 ; acc@1 : 100.0
2023-02-02 22:56:30,037 - mmcls - INFO - [059/110] Training session : 3 ; lr : 0.02046691603456006 ; loss : 0.06646907329559326 ; acc@1 : 100.0
2023-02-02 22:56:30,090 - mmcls - INFO - [060/110] Training session : 3 ; lr : 0.01974260688458122 ; loss : 0.06378932297229767 ; acc@1 : 100.0
2023-02-02 22:56:31,765 - mmcls - INFO - [061/110] Training session : 3 ; lr : 0.019023227597323417 ; loss : 0.058728523552417755 ; acc@1 : 100.0
2023-02-02 22:56:31,973 - mmcls - INFO - [062/110] Training session : 3 ; lr : 0.018309422114676437 ; loss : 0.05986541509628296 ; acc@1 : 100.0
2023-02-02 22:56:34,168 - mmcls - INFO - [063/110] Training session : 3 ; lr : 0.017601829389220055 ; loss : 0.03764524310827255 ; acc@1 : 100.0
2023-02-02 22:56:34,185 - mmcls - INFO - [064/110] Training session : 3 ; lr : 0.01690108281227496 ; loss : 0.05667947977781296 ; acc@1 : 100.0
2023-02-02 22:56:36,107 - mmcls - INFO - [065/110] Training session : 3 ; lr : 0.016207809646931724 ; loss : 0.06137923151254654 ; acc@1 : 100.0
2023-02-02 22:56:36,136 - mmcls - INFO - [066/110] Training session : 3 ; lr : 0.015522630466565393 ; loss : 0.04337410628795624 ; acc@1 : 100.0
2023-02-02 22:56:38,472 - mmcls - INFO - [067/110] Training session : 3 ; lr : 0.01484615859933826 ; loss : 0.03684309497475624 ; acc@1 : 100.0
2023-02-02 22:56:38,502 - mmcls - INFO - [068/110] Training session : 3 ; lr : 0.014178999579188091 ; loss : 0.06054229289293289 ; acc@1 : 100.0
2023-02-02 22:56:40,293 - mmcls - INFO - [069/110] Training session : 3 ; lr : 0.013521750603793285 ; loss : 0.043168146163225174 ; acc@1 : 100.0
2023-02-02 22:56:40,343 - mmcls - INFO - [070/110] Training session : 3 ; lr : 0.012875000000000006 ; loss : 0.05129893124103546 ; acc@1 : 100.0
2023-02-02 22:56:42,338 - mmcls - INFO - [071/110] Training session : 3 ; lr : 0.012239326697190007 ; loss : 0.03893673047423363 ; acc@1 : 100.0
2023-02-02 22:56:42,405 - mmcls - INFO - [072/110] Training session : 3 ; lr : 0.011615299709060466 ; loss : 0.07326146960258484 ; acc@1 : 100.0
2023-02-02 22:56:44,748 - mmcls - INFO - [073/110] Training session : 3 ; lr : 0.011003477624279584 ; loss : 0.043781258165836334 ; acc@1 : 100.0
2023-02-02 22:56:44,770 - mmcls - INFO - [074/110] Training session : 3 ; lr : 0.010404408106474137 ; loss : 0.05257096141576767 ; acc@1 : 100.0
2023-02-02 22:56:46,871 - mmcls - INFO - [075/110] Training session : 3 ; lr : 0.009818627403996347 ; loss : 0.04104161262512207 ; acc@1 : 100.0
2023-02-02 22:56:46,893 - mmcls - INFO - [076/110] Training session : 3 ; lr : 0.009246659869908963 ; loss : 0.04194077104330063 ; acc@1 : 100.0
2023-02-02 22:56:49,112 - mmcls - INFO - [077/110] Training session : 3 ; lr : 0.008689017492618268 ; loss : 0.04430133104324341 ; acc@1 : 100.0
2023-02-02 22:56:49,133 - mmcls - INFO - [078/110] Training session : 3 ; lr : 0.008146199437575101 ; loss : 0.03533109277486801 ; acc@1 : 100.0
2023-02-02 22:56:51,433 - mmcls - INFO - [079/110] Training session : 3 ; lr : 0.007618691600454221 ; loss : 0.06516877561807632 ; acc@1 : 100.0
2023-02-02 22:56:51,440 - mmcls - INFO - [080/110] Training session : 3 ; lr : 0.007106966172211803 ; loss : 0.06828252226114273 ; acc@1 : 100.0
2023-02-02 22:56:53,866 - mmcls - INFO - [081/110] Training session : 3 ; lr : 0.006611481216410631 ; loss : 0.02886013127863407 ; acc@1 : 100.0
2023-02-02 22:56:53,887 - mmcls - INFO - [082/110] Training session : 3 ; lr : 0.006132680259191165 ; loss : 0.0539579801261425 ; acc@1 : 100.0
2023-02-02 22:56:56,231 - mmcls - INFO - [083/110] Training session : 3 ; lr : 0.005670991892255561 ; loss : 0.035555966198444366 ; acc@1 : 100.0
2023-02-02 22:56:56,269 - mmcls - INFO - [084/110] Training session : 3 ; lr : 0.005226829389220054 ; loss : 0.03796316310763359 ; acc@1 : 100.0
2023-02-02 22:56:58,222 - mmcls - INFO - [085/110] Training session : 3 ; lr : 0.0048005903356791325 ; loss : 0.0326957032084465 ; acc@1 : 100.0
2023-02-02 22:56:58,254 - mmcls - INFO - [086/110] Training session : 3 ; lr : 0.004392656273312531 ; loss : 0.061325013637542725 ; acc@1 : 100.0
2023-02-02 22:57:01,144 - mmcls - INFO - [087/110] Training session : 3 ; lr : 0.004003392358353814 ; loss : 0.03951974958181381 ; acc@1 : 100.0
2023-02-02 22:57:01,178 - mmcls - INFO - [088/110] Training session : 3 ; lr : 0.0036331470347260413 ; loss : 0.03891431912779808 ; acc@1 : 100.0
2023-02-02 22:57:02,545 - mmcls - INFO - [089/110] Training session : 3 ; lr : 0.0032822517221372865 ; loss : 0.03840537741780281 ; acc@1 : 100.0
2023-02-02 22:57:02,568 - mmcls - INFO - [090/110] Training session : 3 ; lr : 0.002951020519415129 ; loss : 0.04007316380739212 ; acc@1 : 100.0
2023-02-02 22:57:04,873 - mmcls - INFO - [091/110] Training session : 3 ; lr : 0.002639749923345626 ; loss : 0.043368011713027954 ; acc@1 : 100.0
2023-02-02 22:57:04,885 - mmcls - INFO - [092/110] Training session : 3 ; lr : 0.0023487185632685816 ; loss : 0.04369230940937996 ; acc@1 : 100.0
2023-02-02 22:57:06,684 - mmcls - INFO - [093/110] Training session : 3 ; lr : 0.0020781869516665044 ; loss : 0.057364046573638916 ; acc@1 : 100.0
2023-02-02 22:57:06,739 - mmcls - INFO - [094/110] Training session : 3 ; lr : 0.0018283972509706848 ; loss : 0.034076590090990067 ; acc@1 : 100.0
2023-02-02 22:57:08,553 - mmcls - INFO - [095/110] Training session : 3 ; lr : 0.0015995730567930156 ; loss : 0.03568952530622482 ; acc@1 : 100.0
2023-02-02 22:57:08,673 - mmcls - INFO - [096/110] Training session : 3 ; lr : 0.0013919191977776323 ; loss : 0.03858252987265587 ; acc@1 : 100.0
2023-02-02 22:57:10,780 - mmcls - INFO - [097/110] Training session : 3 ; lr : 0.0012056215522515293 ; loss : 0.030131051316857338 ; acc@1 : 100.0
2023-02-02 22:57:10,803 - mmcls - INFO - [098/110] Training session : 3 ; lr : 0.0010408468818383092 ; loss : 0.03795560076832771 ; acc@1 : 100.0
2023-02-02 22:57:13,208 - mmcls - INFO - [099/110] Training session : 3 ; lr : 0.0008977426821839157 ; loss : 0.02870987169444561 ; acc@1 : 100.0
2023-02-02 22:57:13,249 - mmcls - INFO - [100/110] Training session : 3 ; lr : 0.0007764370509280691 ; loss : 0.05166562274098396 ; acc@1 : 100.0
2023-02-02 22:57:16,057 - mmcls - INFO - [101/110] Training session : 3 ; lr : 0.0006770385730395255 ; loss : 0.04001477733254433 ; acc@1 : 100.0
2023-02-02 22:57:16,107 - mmcls - INFO - [102/110] Training session : 3 ; lr : 0.0005996362236178331 ; loss : 0.047607775777578354 ; acc@1 : 100.0
2023-02-02 22:57:19,377 - mmcls - INFO - [103/110] Training session : 3 ; lr : 0.000544299288248555 ; loss : 0.03118962049484253 ; acc@1 : 100.0
2023-02-02 22:57:19,397 - mmcls - INFO - [104/110] Training session : 3 ; lr : 0.0005110773009832927 ; loss : 0.040684230625629425 ; acc@1 : 100.0
2023-02-02 22:57:22,106 - mmcls - INFO - [105/110] Training session : 3 ; lr : 0.0005 ; loss : 0.05919530615210533 ; acc@1 : 100.0
2023-02-02 22:57:22,130 - mmcls - INFO - [106/110] Training session : 3 ; lr : 5e-05 ; loss : 0.043173227459192276 ; acc@1 : 100.0
2023-02-02 22:57:24,321 - mmcls - INFO - [107/110] Training session : 3 ; lr : 5e-05 ; loss : 0.05576450005173683 ; acc@1 : 100.0
2023-02-02 22:57:24,393 - mmcls - INFO - [108/110] Training session : 3 ; lr : 5e-05 ; loss : 0.04569336399435997 ; acc@1 : 100.0
2023-02-02 22:57:25,853 - mmcls - INFO - [109/110] Training session : 3 ; lr : 5e-05 ; loss : 0.033740706741809845 ; acc@1 : 100.0
2023-02-02 22:57:25,910 - mmcls - INFO - [110/110] Training session : 3 ; lr : 5e-05 ; loss : 0.0415797233581543 ; acc@1 : 100.0
2023-02-02 22:57:25,911 - mmcls - INFO - Evaluating session 3, from 0 to 120.
2023-02-02 22:57:28,533 - mmcls - INFO - [03]Evaluation results : acc : 72.30 ; acc_base : 77.62 ; acc_inc : 45.41
2023-02-02 22:57:28,533 - mmcls - INFO - [03]Evaluation results : acc_incremental_old : 45.22 ; acc_incremental_new : 45.95
2023-02-02 22:57:28,613 - mmcls - INFO - Starting session : 4 ------------------------------------------------------------
2023-02-02 22:57:28,613 - mmcls - INFO - Newly added classes are from 120 to 130.
2023-02-02 22:57:28,613 - mmcls - INFO - Model now can classify 130 classes
2023-02-02 22:57:28,613 - mmcls - INFO - 115 steps
2023-02-02 22:57:28,613 - mmcls - INFO - Extracting mean neck feat from 100 to 120
2023-02-02 22:57:28,613 - mmcls - INFO - Copy 3 duplications.
2023-02-02 22:57:28,649 - mmcls - INFO - Session : 4 ; The dataset has 210 samples.
2023-02-02 22:57:28,649 - mmcls - INFO - Labels : [120, 120, 120, 120, 120, 121, 121, 121, 121, 121, 122, 122, 122, 122, 122, 123, 123, 123, 123, 123, 124, 124, 124, 124, 124, 125, 125, 125, 125, 125, 126, 126, 126, 126, 126, 127, 127, 127, 127, 127, 128, 128, 128, 128, 128, 129, 129, 129, 129, 129, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
2023-02-02 22:57:30,933 - mmcls - INFO - [001/115] Training session : 4 ; lr : 0.013997173896299347 ; loss : 0.6514333486557007 ; acc@1 : 87.5
2023-02-02 22:57:31,018 - mmcls - INFO - [002/115] Training session : 4 ; lr : 0.02298143224819905 ; loss : 0.6313866972923279 ; acc@1 : 87.5
2023-02-02 22:57:31,043 - mmcls - INFO - [003/115] Training session : 4 ; lr : 0.03194189461686503 ; loss : 0.040417611598968506 ; acc@1 : 100.0
2023-02-02 22:57:32,637 - mmcls - INFO - [004/115] Training session : 4 ; lr : 0.040867711818898825 ; loss : 0.4449644684791565 ; acc@1 : 87.5
2023-02-02 22:57:33,229 - mmcls - INFO - [005/115] Training session : 4 ; lr : 0.04974808068655309 ; loss : 0.6918048858642578 ; acc@1 : 87.5
2023-02-02 22:57:33,255 - mmcls - INFO - [006/115] Training session : 4 ; lr : 0.0496375074372304 ; loss : 0.4707404375076294 ; acc@1 : 100.0
2023-02-02 22:57:35,096 - mmcls - INFO - [007/115] Training session : 4 ; lr : 0.04950704338703674 ; loss : 1.2975633144378662 ; acc@1 : 75.0
2023-02-02 22:57:35,139 - mmcls - INFO - [008/115] Training session : 4 ; lr : 0.04935679494432276 ; loss : 0.3592638671398163 ; acc@1 : 100.0
2023-02-02 22:57:35,657 - mmcls - INFO - [009/115] Training session : 4 ; lr : 0.04918688465387345 ; loss : 0.5654870271682739 ; acc@1 : 100.0
2023-02-02 22:57:38,053 - mmcls - INFO - [010/115] Training session : 4 ; lr : 0.04899745109695881 ; loss : 0.5084919333457947 ; acc@1 : 100.0
2023-02-02 22:57:38,070 - mmcls - INFO - [011/115] Training session : 4 ; lr : 0.048788648778305056 ; loss : 0.18872040510177612 ; acc@1 : 100.0
2023-02-02 22:57:38,122 - mmcls - INFO - [012/115] Training session : 4 ; lr : 0.04856064800007824 ; loss : 0.6502208113670349 ; acc@1 : 87.5
2023-02-02 22:57:40,527 - mmcls - INFO - [013/115] Training session : 4 ; lr : 0.04831363472298345 ; loss : 0.24742096662521362 ; acc@1 : 100.0
2023-02-02 22:57:40,569 - mmcls - INFO - [014/115] Training session : 4 ; lr : 0.048047810414592544 ; loss : 0.5275337100028992 ; acc@1 : 100.0
2023-02-02 22:57:40,628 - mmcls - INFO - [015/115] Training session : 4 ; lr : 0.047763391885024334 ; loss : 0.2506081461906433 ; acc@1 : 100.0
2023-02-02 22:57:43,142 - mmcls - INFO - [016/115] Training session : 4 ; lr : 0.04746061111011112 ; loss : 0.2888331711292267 ; acc@1 : 100.0
2023-02-02 22:57:43,176 - mmcls - INFO - [017/115] Training session : 4 ; lr : 0.047139715042195905 ; loss : 0.3008604049682617 ; acc@1 : 100.0
2023-02-02 22:57:43,208 - mmcls - INFO - [018/115] Training session : 4 ; lr : 0.04680096540871449 ; loss : 0.3273838758468628 ; acc@1 : 100.0
2023-02-02 22:57:45,757 - mmcls - INFO - [019/115] Training session : 4 ; lr : 0.046444638498726834 ; loss : 0.155238538980484 ; acc@1 : 100.0
2023-02-02 22:57:45,789 - mmcls - INFO - [020/115] Training session : 4 ; lr : 0.04607102493757174 ; loss : 0.2190510630607605 ; acc@1 : 100.0
2023-02-02 22:57:45,818 - mmcls - INFO - [021/115] Training session : 4 ; lr : 0.045680429449828655 ; loss : 0.4700276255607605 ; acc@1 : 100.0
2023-02-02 22:57:47,355 - mmcls - INFO - [022/115] Training session : 4 ; lr : 0.04527317061077995 ; loss : 0.1115751639008522 ; acc@1 : 100.0
2023-02-02 22:57:47,636 - mmcls - INFO - [023/115] Training session : 4 ; lr : 0.04484958058657631 ; loss : 0.2539396286010742 ; acc@1 : 100.0
2023-02-02 22:57:47,701 - mmcls - INFO - [024/115] Training session : 4 ; lr : 0.044410004863317296 ; loss : 0.24894627928733826 ; acc@1 : 100.0
2023-02-02 22:57:49,497 - mmcls - INFO - [025/115] Training session : 4 ; lr : 0.043954801965267895 ; loss : 0.20152580738067627 ; acc@1 : 100.0
2023-02-02 22:57:49,916 - mmcls - INFO - [026/115] Training session : 4 ; lr : 0.04348434316244102 ; loss : 0.2537769377231598 ; acc@1 : 100.0
2023-02-02 22:57:49,956 - mmcls - INFO - [027/115] Training session : 4 ; lr : 0.04299901216778435 ; loss : 0.1982741355895996 ; acc@1 : 100.0
2023-02-02 22:57:52,004 - mmcls - INFO - [028/115] Training session : 4 ; lr : 0.04249920482421852 ; loss : 0.18325719237327576 ; acc@1 : 100.0
2023-02-02 22:57:52,099 - mmcls - INFO - [029/115] Training session : 4 ; lr : 0.04198532878178198 ; loss : 0.24151864647865295 ; acc@1 : 100.0
2023-02-02 22:57:52,128 - mmcls - INFO - [030/115] Training session : 4 ; lr : 0.04145780316514581 ; loss : 0.16005443036556244 ; acc@1 : 100.0
2023-02-02 22:57:54,753 - mmcls - INFO - [031/115] Training session : 4 ; lr : 0.04091705823176955 ; loss : 0.10690329968929291 ; acc@1 : 100.0
2023-02-02 22:57:54,783 - mmcls - INFO - [032/115] Training session : 4 ; lr : 0.0403635350209771 ; loss : 0.17342166602611542 ; acc@1 : 100.0
2023-02-02 22:57:54,814 - mmcls - INFO - [033/115] Training session : 4 ; lr : 0.03979768499423871 ; loss : 0.19140951335430145 ; acc@1 : 100.0
2023-02-02 22:57:56,853 - mmcls - INFO - [034/115] Training session : 4 ; lr : 0.03921996966695254 ; loss : 0.12289103865623474 ; acc@1 : 100.0
2023-02-02 22:57:56,876 - mmcls - INFO - [035/115] Training session : 4 ; lr : 0.03863086023202605 ; loss : 0.08658759295940399 ; acc@1 : 100.0
2023-02-02 22:57:56,892 - mmcls - INFO - [036/115] Training session : 4 ; lr : 0.03803083717556431 ; loss : 0.16737058758735657 ; acc@1 : 100.0
2023-02-02 22:57:59,006 - mmcls - INFO - [037/115] Training session : 4 ; lr : 0.0374203898849787 ; loss : 0.09589788317680359 ; acc@1 : 100.0
2023-02-02 22:57:59,016 - mmcls - INFO - [038/115] Training session : 4 ; lr : 0.03680001624983543 ; loss : 0.09984248876571655 ; acc@1 : 100.0
2023-02-02 22:57:59,026 - mmcls - INFO - [039/115] Training session : 4 ; lr : 0.03617022225576973 ; loss : 0.09218728542327881 ; acc@1 : 100.0
2023-02-02 22:58:00,990 - mmcls - INFO - [040/115] Training session : 4 ; lr : 0.0355315215717967 ; loss : 0.09023328125476837 ; acc@1 : 100.0
2023-02-02 22:58:01,006 - mmcls - INFO - [041/115] Training session : 4 ; lr : 0.034884435131355446 ; loss : 0.06205466389656067 ; acc@1 : 100.0
2023-02-02 22:58:01,029 - mmcls - INFO - [042/115] Training session : 4 ; lr : 0.03422949070742837 ; loss : 0.0904512107372284 ; acc@1 : 100.0
2023-02-02 22:58:03,157 - mmcls - INFO - [043/115] Training session : 4 ; lr : 0.033567222482081896 ; loss : 0.068080835044384 ; acc@1 : 100.0
2023-02-02 22:58:03,391 - mmcls - INFO - [044/115] Training session : 4 ; lr : 0.03289817061077995 ; loss : 0.07177652418613434 ; acc@1 : 100.0
2023-02-02 22:58:03,428 - mmcls - INFO - [045/115] Training session : 4 ; lr : 0.032222880781825385 ; loss : 0.07240895926952362 ; acc@1 : 100.0
2023-02-02 22:58:06,091 - mmcls - INFO - [046/115] Training session : 4 ; lr : 0.03154190377128881 ; loss : 0.08213813602924347 ; acc@1 : 100.0
2023-02-02 22:58:06,146 - mmcls - INFO - [047/115] Training session : 4 ; lr : 0.030855794993787673 ; loss : 0.06505301594734192 ; acc@1 : 100.0
2023-02-02 22:58:06,217 - mmcls - INFO - [048/115] Training session : 4 ; lr : 0.0301651140494822 ; loss : 0.05783788114786148 ; acc@1 : 100.0
2023-02-02 22:58:08,463 - mmcls - INFO - [049/115] Training session : 4 ; lr : 0.029470424267657443 ; loss : 0.05574272572994232 ; acc@1 : 100.0
2023-02-02 22:58:08,503 - mmcls - INFO - [050/115] Training session : 4 ; lr : 0.02877229224726381 ; loss : 0.03916650637984276 ; acc@1 : 100.0
2023-02-02 22:58:08,538 - mmcls - INFO - [051/115] Training session : 4 ; lr : 0.02807128739479088 ; loss : 0.07270628213882446 ; acc@1 : 100.0
2023-02-02 22:58:10,437 - mmcls - INFO - [052/115] Training session : 4 ; lr : 0.02736798145985129 ; loss : 0.03784862905740738 ; acc@1 : 100.0
2023-02-02 22:58:10,463 - mmcls - INFO - [053/115] Training session : 4 ; lr : 0.026662948068853512 ; loss : 0.05022961646318436 ; acc@1 : 100.0
2023-02-02 22:58:10,500 - mmcls - INFO - [054/115] Training session : 4 ; lr : 0.02595676225714398 ; loss : 0.05132140964269638 ; acc@1 : 100.0
2023-02-02 22:58:12,642 - mmcls - INFO - [055/115] Training session : 4 ; lr : 0.02525 ; loss : 0.05549359694123268 ; acc@1 : 100.0
2023-02-02 22:58:12,677 - mmcls - INFO - [056/115] Training session : 4 ; lr : 0.024543237742856022 ; loss : 0.03443421423435211 ; acc@1 : 100.0
2023-02-02 22:58:12,709 - mmcls - INFO - [057/115] Training session : 4 ; lr : 0.02383705193114649 ; loss : 0.05786239355802536 ; acc@1 : 100.0
2023-02-02 22:58:15,316 - mmcls - INFO - [058/115] Training session : 4 ; lr : 0.023132018540148725 ; loss : 0.03693108260631561 ; acc@1 : 100.0
2023-02-02 22:58:15,345 - mmcls - INFO - [059/115] Training session : 4 ; lr : 0.022428712605209122 ; loss : 0.05990838631987572 ; acc@1 : 100.0
2023-02-02 22:58:15,361 - mmcls - INFO - [060/115] Training session : 4 ; lr : 0.021727707752736195 ; loss : 0.06543028354644775 ; acc@1 : 100.0
2023-02-02 22:58:17,802 - mmcls - INFO - [061/115] Training session : 4 ; lr : 0.021029575732342563 ; loss : 0.032563500106334686 ; acc@1 : 100.0
2023-02-02 22:58:17,829 - mmcls - INFO - [062/115] Training session : 4 ; lr : 0.020334885950517807 ; loss : 0.050674229860305786 ; acc@1 : 100.0
2023-02-02 22:58:17,849 - mmcls - INFO - [063/115] Training session : 4 ; lr : 0.01964420500621233 ; loss : 0.04216141253709793 ; acc@1 : 100.0
2023-02-02 22:58:19,529 - mmcls - INFO - [064/115] Training session : 4 ; lr : 0.018958096228711203 ; loss : 0.05796191096305847 ; acc@1 : 100.0
2023-02-02 22:58:19,669 - mmcls - INFO - [065/115] Training session : 4 ; lr : 0.018277119218174615 ; loss : 0.04988214001059532 ; acc@1 : 100.0
2023-02-02 22:58:19,820 - mmcls - INFO - [066/115] Training session : 4 ; lr : 0.017601829389220055 ; loss : 0.04979905113577843 ; acc@1 : 100.0
2023-02-02 22:58:21,879 - mmcls - INFO - [067/115] Training session : 4 ; lr : 0.016932777517918104 ; loss : 0.0261992234736681 ; acc@1 : 100.0
2023-02-02 22:58:22,118 - mmcls - INFO - [068/115] Training session : 4 ; lr : 0.01627050929257164 ; loss : 0.04825250804424286 ; acc@1 : 100.0
2023-02-02 22:58:22,495 - mmcls - INFO - [069/115] Training session : 4 ; lr : 0.015615564868644563 ; loss : 0.05446542799472809 ; acc@1 : 100.0
2023-02-02 22:58:24,061 - mmcls - INFO - [070/115] Training session : 4 ; lr : 0.014968478428203315 ; loss : 0.041689928621053696 ; acc@1 : 100.0
2023-02-02 22:58:24,146 - mmcls - INFO - [071/115] Training session : 4 ; lr : 0.014329777744230268 ; loss : 0.03788908198475838 ; acc@1 : 100.0
2023-02-02 22:58:24,168 - mmcls - INFO - [072/115] Training session : 4 ; lr : 0.013699983750164577 ; loss : 0.03265925496816635 ; acc@1 : 100.0
2023-02-02 22:58:26,609 - mmcls - INFO - [073/115] Training session : 4 ; lr : 0.013079610115021303 ; loss : 0.030921582132577896 ; acc@1 : 100.0
2023-02-02 22:58:26,820 - mmcls - INFO - [074/115] Training session : 4 ; lr : 0.012469162824435696 ; loss : 0.032379958778619766 ; acc@1 : 100.0
2023-02-02 22:58:26,951 - mmcls - INFO - [075/115] Training session : 4 ; lr : 0.01186913976797397 ; loss : 0.04308059439063072 ; acc@1 : 100.0
2023-02-02 22:58:28,865 - mmcls - INFO - [076/115] Training session : 4 ; lr : 0.01128003033304747 ; loss : 0.030938824638724327 ; acc@1 : 100.0
2023-02-02 22:58:28,931 - mmcls - INFO - [077/115] Training session : 4 ; lr : 0.010702315005761293 ; loss : 0.03281756490468979 ; acc@1 : 100.0
2023-02-02 22:58:28,962 - mmcls - INFO - [078/115] Training session : 4 ; lr : 0.010136464979022906 ; loss : 0.055348727852106094 ; acc@1 : 100.0
2023-02-02 22:58:31,297 - mmcls - INFO - [079/115] Training session : 4 ; lr : 0.009582941768230461 ; loss : 0.022659316658973694 ; acc@1 : 100.0
2023-02-02 22:58:31,340 - mmcls - INFO - [080/115] Training session : 4 ; lr : 0.009042196834854197 ; loss : 0.037806570529937744 ; acc@1 : 100.0
2023-02-02 22:58:31,369 - mmcls - INFO - [081/115] Training session : 4 ; lr : 0.008514671218218027 ; loss : 0.03950615972280502 ; acc@1 : 100.0
2023-02-02 22:58:33,676 - mmcls - INFO - [082/115] Training session : 4 ; lr : 0.00800079517578149 ; loss : 0.036833297461271286 ; acc@1 : 100.0
2023-02-02 22:58:33,686 - mmcls - INFO - [083/115] Training session : 4 ; lr : 0.007500987832215655 ; loss : 0.02294786646962166 ; acc@1 : 100.0
2023-02-02 22:58:33,695 - mmcls - INFO - [084/115] Training session : 4 ; lr : 0.007015656837558976 ; loss : 0.023543743416666985 ; acc@1 : 100.0
2023-02-02 22:58:35,526 - mmcls - INFO - [085/115] Training session : 4 ; lr : 0.006545198034732112 ; loss : 0.038275912404060364 ; acc@1 : 100.0
2023-02-02 22:58:35,575 - mmcls - INFO - [086/115] Training session : 4 ; lr : 0.006089995136682709 ; loss : 0.037128474563360214 ; acc@1 : 100.0
2023-02-02 22:58:35,600 - mmcls - INFO - [087/115] Training session : 4 ; lr : 0.005650419413423695 ; loss : 0.033469028770923615 ; acc@1 : 100.0
2023-02-02 22:58:37,841 - mmcls - INFO - [088/115] Training session : 4 ; lr : 0.005226829389220054 ; loss : 0.025910452008247375 ; acc@1 : 100.0
2023-02-02 22:58:37,889 - mmcls - INFO - [089/115] Training session : 4 ; lr : 0.004819570550171343 ; loss : 0.019735638052225113 ; acc@1 : 100.0
2023-02-02 22:58:37,907 - mmcls - INFO - [090/115] Training session : 4 ; lr : 0.004428975062428262 ; loss : 0.03201856464147568 ; acc@1 : 100.0
2023-02-02 22:58:40,548 - mmcls - INFO - [091/115] Training session : 4 ; lr : 0.004055361501273174 ; loss : 0.03056463971734047 ; acc@1 : 100.0
2023-02-02 22:58:40,630 - mmcls - INFO - [092/115] Training session : 4 ; lr : 0.0036990345912855187 ; loss : 0.027439821511507034 ; acc@1 : 100.0
2023-02-02 22:58:40,649 - mmcls - INFO - [093/115] Training session : 4 ; lr : 0.0033602849578040967 ; loss : 0.02845177799463272 ; acc@1 : 100.0
2023-02-02 22:58:42,921 - mmcls - INFO - [094/115] Training session : 4 ; lr : 0.003039388889888884 ; loss : 0.03683331981301308 ; acc@1 : 100.0
2023-02-02 22:58:43,329 - mmcls - INFO - [095/115] Training session : 4 ; lr : 0.0027366081149756685 ; loss : 0.03387024626135826 ; acc@1 : 100.0
2023-02-02 22:58:43,351 - mmcls - INFO - [096/115] Training session : 4 ; lr : 0.0024521895854074625 ; loss : 0.03734736889600754 ; acc@1 : 100.0
2023-02-02 22:58:45,472 - mmcls - INFO - [097/115] Training session : 4 ; lr : 0.0021863652770165564 ; loss : 0.042633745819330215 ; acc@1 : 100.0
2023-02-02 22:58:45,512 - mmcls - INFO - [098/115] Training session : 4 ; lr : 0.0019393519999217658 ; loss : 0.05364782363176346 ; acc@1 : 100.0
2023-02-02 22:58:45,558 - mmcls - INFO - [099/115] Training session : 4 ; lr : 0.0017113512216949502 ; loss : 0.03153080493211746 ; acc@1 : 100.0
2023-02-02 22:58:47,556 - mmcls - INFO - [100/115] Training session : 4 ; lr : 0.0015025489030411929 ; loss : 0.027256406843662262 ; acc@1 : 100.0
2023-02-02 22:58:47,587 - mmcls - INFO - [101/115] Training session : 4 ; lr : 0.001313115346126563 ; loss : 0.018522728234529495 ; acc@1 : 100.0
2023-02-02 22:58:47,616 - mmcls - INFO - [102/115] Training session : 4 ; lr : 0.0011432050556772467 ; loss : 0.03482620790600777 ; acc@1 : 100.0
2023-02-02 22:58:50,545 - mmcls - INFO - [103/115] Training session : 4 ; lr : 0.0009929566129632623 ; loss : 0.02757113240659237 ; acc@1 : 100.0
2023-02-02 22:58:50,558 - mmcls - INFO - [104/115] Training session : 4 ; lr : 0.0008624925627695987 ; loss : 0.04181100055575371 ; acc@1 : 100.0
2023-02-02 22:58:50,586 - mmcls - INFO - [105/115] Training session : 4 ; lr : 0.0007519193134469161 ; loss : 0.02993261069059372 ; acc@1 : 100.0
2023-02-02 22:58:53,118 - mmcls - INFO - [106/115] Training session : 4 ; lr : 0.0006613270501233821 ; loss : 0.031251948326826096 ; acc@1 : 100.0
2023-02-02 22:58:53,207 - mmcls - INFO - [107/115] Training session : 4 ; lr : 0.0005907896611483895 ; loss : 0.026414955034852028 ; acc@1 : 100.0
2023-02-02 22:58:53,271 - mmcls - INFO - [108/115] Training session : 4 ; lr : 0.0005403646778281427 ; loss : 0.03016963228583336 ; acc@1 : 100.0
2023-02-02 22:58:55,423 - mmcls - INFO - [109/115] Training session : 4 ; lr : 0.0005100932275023166 ; loss : 0.031715042889118195 ; acc@1 : 100.0
2023-02-02 22:58:55,514 - mmcls - INFO - [110/115] Training session : 4 ; lr : 0.0005 ; loss : 0.024681715294718742 ; acc@1 : 100.0
2023-02-02 22:58:55,528 - mmcls - INFO - [111/115] Training session : 4 ; lr : 5e-05 ; loss : 0.05560159683227539 ; acc@1 : 100.0
2023-02-02 22:58:57,174 - mmcls - INFO - [112/115] Training session : 4 ; lr : 5e-05 ; loss : 0.044296205043792725 ; acc@1 : 100.0
2023-02-02 22:58:57,264 - mmcls - INFO - [113/115] Training session : 4 ; lr : 5e-05 ; loss : 0.03735294193029404 ; acc@1 : 100.0
2023-02-02 22:58:57,304 - mmcls - INFO - [114/115] Training session : 4 ; lr : 5e-05 ; loss : 0.03039734810590744 ; acc@1 : 100.0
2023-02-02 22:58:58,993 - mmcls - INFO - [115/115] Training session : 4 ; lr : 5e-05 ; loss : 0.02997337281703949 ; acc@1 : 100.0
2023-02-02 22:58:58,994 - mmcls - INFO - Evaluating session 4, from 0 to 130.
2023-02-02 22:59:01,895 - mmcls - INFO - [04]Evaluation results : acc : 70.28 ; acc_base : 78.63 ; acc_inc : 42.59
2023-02-02 22:59:01,895 - mmcls - INFO - [04]Evaluation results : acc_incremental_old : 41.32 ; acc_incremental_new : 48.67
2023-02-02 22:59:01,979 - mmcls - INFO - Starting session : 5 ------------------------------------------------------------
2023-02-02 22:59:01,979 - mmcls - INFO - Newly added classes are from 130 to 140.
2023-02-02 22:59:01,979 - mmcls - INFO - Model now can classify 140 classes
2023-02-02 22:59:01,979 - mmcls - INFO - 120 steps
2023-02-02 22:59:01,979 - mmcls - INFO - Extracting mean neck feat from 100 to 130
2023-02-02 22:59:01,979 - mmcls - INFO - Copy 4 duplications.
2023-02-02 22:59:02,028 - mmcls - INFO - Session : 5 ; The dataset has 270 samples.
2023-02-02 22:59:02,029 - mmcls - INFO - Labels : [130, 130, 130, 130, 130, 131, 131, 131, 131, 131, 132, 132, 132, 132, 132, 133, 133, 133, 133, 133, 134, 134, 134, 134, 134, 135, 135, 135, 135, 135, 136, 136, 136, 136, 136, 137, 137, 137, 137, 137, 138, 138, 138, 138, 138, 139, 139, 139, 139, 139, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
2023-02-02 22:59:04,165 - mmcls - INFO - [001/120] Training session : 5 ; lr : 0.013997414287145037 ; loss : 1.8263583183288574 ; acc@1 : 62.5
2023-02-02 22:59:04,191 - mmcls - INFO - [002/120] Training session : 5 ; lr : 0.022983011342651995 ; loss : 1.2357258796691895 ; acc@1 : 75.0
2023-02-02 22:59:04,212 - mmcls - INFO - [003/120] Training session : 5 ; lr : 0.03194683465188679 ; loss : 0.5909823775291443 ; acc@1 : 87.5
2023-02-02 22:59:04,254 - mmcls - INFO - [004/120] Training session : 5 ; lr : 0.04087895386647757 ; loss : 1.0280858278274536 ; acc@1 : 75.0
2023-02-02 22:59:06,014 - mmcls - INFO - [005/120] Training session : 5 ; lr : 0.04976947716439919 ; loss : 1.1081690788269043 ; acc@1 : 87.5
2023-02-02 22:59:06,378 - mmcls - INFO - [006/120] Training session : 5 ; lr : 0.049668274212044956 ; loss : 0.7349777221679688 ; acc@1 : 75.0
2023-02-02 22:59:06,432 - mmcls - INFO - [007/120] Training session : 5 ; lr : 0.049548849428370074 ; loss : 0.48005199432373047 ; acc@1 : 100.0
2023-02-02 22:59:06,714 - mmcls - INFO - [008/120] Training session : 5 ; lr : 0.04941129193262373 ; loss : 0.6305485367774963 ; acc@1 : 87.5
2023-02-02 22:59:08,986 - mmcls - INFO - [009/120] Training session : 5 ; lr : 0.04925570437536437 ; loss : 0.5463549494743347 ; acc@1 : 100.0
2023-02-02 22:59:09,011 - mmcls - INFO - [010/120] Training session : 5 ; lr : 0.049082202861858035 ; loss : 0.14243753254413605 ; acc@1 : 100.0
2023-02-02 22:59:09,046 - mmcls - INFO - [011/120] Training session : 5 ; lr : 0.04889091686543629 ; loss : 0.10396667569875717 ; acc@1 : 100.0
2023-02-02 22:59:09,077 - mmcls - INFO - [012/120] Training session : 5 ; lr : 0.04868198913087833 ; loss : 0.6457587480545044 ; acc@1 : 87.5
2023-02-02 22:59:11,282 - mmcls - INFO - [013/120] Training session : 5 ; lr : 0.04845557556788951 ; loss : 0.3222641944885254 ; acc@1 : 100.0
2023-02-02 22:59:11,314 - mmcls - INFO - [014/120] Training session : 5 ; lr : 0.04821184513475562 ; loss : 0.2676328718662262 ; acc@1 : 87.5
2023-02-02 22:59:11,330 - mmcls - INFO - [015/120] Training session : 5 ; lr : 0.047950979712259964 ; loss : 0.3537680506706238 ; acc@1 : 100.0
2023-02-02 22:59:11,347 - mmcls - INFO - [016/120] Training session : 5 ; lr : 0.047673173967957054 ; loss : 0.1933668851852417 ; acc@1 : 100.0
2023-02-02 22:59:13,361 - mmcls - INFO - [017/120] Training session : 5 ; lr : 0.047378635210904366 ; loss : 0.22315694391727448 ; acc@1 : 100.0
2023-02-02 22:59:13,395 - mmcls - INFO - [018/120] Training session : 5 ; lr : 0.04706758323696062 ; loss : 0.14271533489227295 ; acc@1 : 100.0
2023-02-02 22:59:13,426 - mmcls - INFO - [019/120] Training session : 5 ; lr : 0.04674025016476581 ; loss : 0.36205604672431946 ; acc@1 : 100.0
2023-02-02 22:59:13,449 - mmcls - INFO - [020/120] Training session : 5 ; lr : 0.04639688026252559 ; loss : 0.31288594007492065 ; acc@1 : 87.5
2023-02-02 22:59:15,729 - mmcls - INFO - [021/120] Training session : 5 ; lr : 0.046037729765729216 ; loss : 0.09840360283851624 ; acc@1 : 100.0
2023-02-02 22:59:15,756 - mmcls - INFO - [022/120] Training session : 5 ; lr : 0.04566306668593697 ; loss : 0.1935160905122757 ; acc@1 : 100.0
2023-02-02 22:59:15,800 - mmcls - INFO - [023/120] Training session : 5 ; lr : 0.04527317061077995 ; loss : 0.15368147194385529 ; acc@1 : 100.0
2023-02-02 22:59:15,833 - mmcls - INFO - [024/120] Training session : 5 ; lr : 0.04486833249532124 ; loss : 0.3079337477684021 ; acc@1 : 87.5
2023-02-02 22:59:17,777 - mmcls - INFO - [025/120] Training session : 5 ; lr : 0.0444488544449344 ; loss : 0.14985986053943634 ; acc@1 : 100.0
2023-02-02 22:59:17,801 - mmcls - INFO - [026/120] Training session : 5 ; lr : 0.04401504948986103 ; loss : 0.1252690553665161 ; acc@1 : 100.0
2023-02-02 22:59:17,827 - mmcls - INFO - [027/120] Training session : 5 ; lr : 0.043567241351615986 ; loss : 0.17002850770950317 ; acc@1 : 100.0
2023-02-02 22:59:18,056 - mmcls - INFO - [028/120] Training session : 5 ; lr : 0.04310576420141416 ; loss : 0.10623536258935928 ; acc@1 : 100.0
2023-02-02 22:59:19,970 - mmcls - INFO - [029/120] Training session : 5 ; lr : 0.042630962410799424 ; loss : 0.09390208125114441 ; acc@1 : 100.0
2023-02-02 22:59:19,999 - mmcls - INFO - [030/120] Training session : 5 ; lr : 0.042143190294661695 ; loss : 0.07295292615890503 ; acc@1 : 100.0
2023-02-02 22:59:20,020 - mmcls - INFO - [031/120] Training session : 5 ; lr : 0.04164281184683387 ; loss : 0.1227453351020813 ; acc@1 : 100.0
2023-02-02 22:59:20,045 - mmcls - INFO - [032/120] Training session : 5 ; lr : 0.04113020046846599 ; loss : 0.08413691073656082 ; acc@1 : 100.0
2023-02-02 22:59:22,125 - mmcls - INFO - [033/120] Training session : 5 ; lr : 0.04060573868937931 ; loss : 0.13431477546691895 ; acc@1 : 100.0
2023-02-02 22:59:22,162 - mmcls - INFO - [034/120] Training session : 5 ; lr : 0.04006981788260821 ; loss : 0.0880715623497963 ; acc@1 : 100.0
2023-02-02 22:59:22,213 - mmcls - INFO - [035/120] Training session : 5 ; lr : 0.03952283797234297 ; loss : 0.09657952934503555 ; acc@1 : 100.0
2023-02-02 22:59:22,262 - mmcls - INFO - [036/120] Training session : 5 ; lr : 0.03896520713549133 ; loss : 0.10782547295093536 ; acc@1 : 100.0
2023-02-02 22:59:24,112 - mmcls - INFO - [037/120] Training session : 5 ; lr : 0.038397341497081634 ; loss : 0.08519949018955231 ; acc@1 : 100.0
2023-02-02 22:59:24,144 - mmcls - INFO - [038/120] Training session : 5 ; lr : 0.03781966481973471 ; loss : 0.0848250538110733 ; acc@1 : 100.0
2023-02-02 22:59:24,150 - mmcls - INFO - [039/120] Training session : 5 ; lr : 0.037232608187436275 ; loss : 0.14637883007526398 ; acc@1 : 100.0
2023-02-02 22:59:24,160 - mmcls - INFO - [040/120] Training session : 5 ; lr : 0.036636609683846015 ; loss : 0.04099978506565094 ; acc@1 : 100.0
2023-02-02 22:59:26,837 - mmcls - INFO - [041/120] Training session : 5 ; lr : 0.03603211406538305 ; loss : 0.042894672602415085 ; acc@1 : 100.0
2023-02-02 22:59:26,867 - mmcls - INFO - [042/120] Training session : 5 ; lr : 0.03541957242933207 ; loss : 0.06885484606027603 ; acc@1 : 100.0
2023-02-02 22:59:26,908 - mmcls - INFO - [043/120] Training session : 5 ; lr : 0.034799441877217605 ; loss : 0.09617970883846283 ; acc@1 : 100.0
2023-02-02 22:59:26,959 - mmcls - INFO - [044/120] Training session : 5 ; lr : 0.034172185173697765 ; loss : 0.0389413982629776 ; acc@1 : 100.0
2023-02-02 22:59:28,929 - mmcls - INFO - [045/120] Training session : 5 ; lr : 0.033538270401231904 ; loss : 0.03987009823322296 ; acc@1 : 100.0
2023-02-02 22:59:28,964 - mmcls - INFO - [046/120] Training session : 5 ; lr : 0.03289817061077995 ; loss : 0.10918322950601578 ; acc@1 : 100.0
2023-02-02 22:59:29,041 - mmcls - INFO - [047/120] Training session : 5 ; lr : 0.03225236346879402 ; loss : 0.039202477782964706 ; acc@1 : 100.0
2023-02-02 22:59:29,313 - mmcls - INFO - [048/120] Training session : 5 ; lr : 0.03160133090076585 ; loss : 0.04951326549053192 ; acc@1 : 100.0
2023-02-02 22:59:30,914 - mmcls - INFO - [049/120] Training session : 5 ; lr : 0.030945558731595917 ; loss : 0.03408599644899368 ; acc@1 : 100.0
2023-02-02 22:59:31,191 - mmcls - INFO - [050/120] Training session : 5 ; lr : 0.03028553632305269 ; loss : 0.05348856747150421 ; acc@1 : 100.0
2023-02-02 22:59:31,235 - mmcls - INFO - [051/120] Training session : 5 ; lr : 0.029621756208592545 ; loss : 0.052334316074848175 ; acc@1 : 100.0
2023-02-02 22:59:31,289 - mmcls - INFO - [052/120] Training session : 5 ; lr : 0.028954713725812823 ; loss : 0.0603938028216362 ; acc@1 : 100.0
2023-02-02 22:59:33,491 - mmcls - INFO - [053/120] Training session : 5 ; lr : 0.028284906646812387 ; loss : 0.044533468782901764 ; acc@1 : 100.0
2023-02-02 22:59:33,516 - mmcls - INFO - [054/120] Training session : 5 ; lr : 0.027612834806735403 ; loss : 0.014230655506253242 ; acc@1 : 100.0
2023-02-02 22:59:33,541 - mmcls - INFO - [055/120] Training session : 5 ; lr : 0.026938999730775612 ; loss : 0.024742240086197853 ; acc@1 : 100.0
2023-02-02 22:59:33,566 - mmcls - INFO - [056/120] Training session : 5 ; lr : 0.026263904259919455 ; loss : 0.040436938405036926 ; acc@1 : 100.0
2023-02-02 22:59:35,247 - mmcls - INFO - [057/120] Training session : 5 ; lr : 0.02558805217570729 ; loss : 0.035698890686035156 ; acc@1 : 100.0
2023-02-02 22:59:35,261 - mmcls - INFO - [058/120] Training session : 5 ; lr : 0.024911947824292718 ; loss : 0.038336481899023056 ; acc@1 : 100.0
2023-02-02 22:59:35,306 - mmcls - INFO - [059/120] Training session : 5 ; lr : 0.024236095740080548 ; loss : 0.03366513550281525 ; acc@1 : 100.0
2023-02-02 22:59:35,351 - mmcls - INFO - [060/120] Training session : 5 ; lr : 0.0235610002692244 ; loss : 0.05126767233014107 ; acc@1 : 100.0
2023-02-02 22:59:37,268 - mmcls - INFO - [061/120] Training session : 5 ; lr : 0.022887165193264603 ; loss : 0.06383763253688812 ; acc@1 : 100.0
2023-02-02 22:59:37,638 - mmcls - INFO - [062/120] Training session : 5 ; lr : 0.02221509335318762 ; loss : 0.042367372661828995 ; acc@1 : 100.0
2023-02-02 22:59:37,842 - mmcls - INFO - [063/120] Training session : 5 ; lr : 0.02154528627418719 ; loss : 0.057744599878787994 ; acc@1 : 100.0
2023-02-02 22:59:37,881 - mmcls - INFO - [064/120] Training session : 5 ; lr : 0.020878243791407465 ; loss : 0.0536065399646759 ; acc@1 : 100.0
2023-02-02 22:59:39,557 - mmcls - INFO - [065/120] Training session : 5 ; lr : 0.02021446367694732 ; loss : 0.047332871705293655 ; acc@1 : 100.0
2023-02-02 22:59:39,583 - mmcls - INFO - [066/120] Training session : 5 ; lr : 0.01955444126840409 ; loss : 0.028640786185860634 ; acc@1 : 100.0
2023-02-02 22:59:40,160 - mmcls - INFO - [067/120] Training session : 5 ; lr : 0.01889866909923416 ; loss : 0.033861756324768066 ; acc@1 : 100.0
2023-02-02 22:59:40,183 - mmcls - INFO - [068/120] Training session : 5 ; lr : 0.01824763653120598 ; loss : 0.02138066291809082 ; acc@1 : 100.0
2023-02-02 22:59:41,693 - mmcls - INFO - [069/120] Training session : 5 ; lr : 0.017601829389220055 ; loss : 0.02803281880915165 ; acc@1 : 100.0
2023-02-02 22:59:41,713 - mmcls - INFO - [070/120] Training session : 5 ; lr : 0.016961729598768092 ; loss : 0.048357270658016205 ; acc@1 : 100.0
2023-02-02 22:59:41,769 - mmcls - INFO - [071/120] Training session : 5 ; lr : 0.01632781482630224 ; loss : 0.02752596139907837 ; acc@1 : 100.0
2023-02-02 22:59:41,827 - mmcls - INFO - [072/120] Training session : 5 ; lr : 0.015700558122782395 ; loss : 0.053156644105911255 ; acc@1 : 100.0
2023-02-02 22:59:44,081 - mmcls - INFO - [073/120] Training session : 5 ; lr : 0.015080427570667933 ; loss : 0.016358599066734314 ; acc@1 : 100.0
2023-02-02 22:59:44,113 - mmcls - INFO - [074/120] Training session : 5 ; lr : 0.01446788593461695 ; loss : 0.04977630451321602 ; acc@1 : 100.0
2023-02-02 22:59:44,142 - mmcls - INFO - [075/120] Training session : 5 ; lr : 0.013863390316153985 ; loss : 0.0158042311668396 ; acc@1 : 100.0
2023-02-02 22:59:44,162 - mmcls - INFO - [076/120] Training session : 5 ; lr : 0.013267391812563738 ; loss : 0.047330036759376526 ; acc@1 : 100.0
2023-02-02 22:59:46,225 - mmcls - INFO - [077/120] Training session : 5 ; lr : 0.0126803351802653 ; loss : 0.026878835633397102 ; acc@1 : 100.0
2023-02-02 22:59:46,257 - mmcls - INFO - [078/120] Training session : 5 ; lr : 0.012102658502918372 ; loss : 0.0288225244730711 ; acc@1 : 100.0
2023-02-02 22:59:46,267 - mmcls - INFO - [079/120] Training session : 5 ; lr : 0.011534792864508678 ; loss : 0.02325785532593727 ; acc@1 : 100.0
2023-02-02 22:59:46,430 - mmcls - INFO - [080/120] Training session : 5 ; lr : 0.01097716202765704 ; loss : 0.045552365481853485 ; acc@1 : 100.0
2023-02-02 22:59:48,832 - mmcls - INFO - [081/120] Training session : 5 ; lr : 0.010430182117391794 ; loss : 0.020697295665740967 ; acc@1 : 100.0
2023-02-02 22:59:48,854 - mmcls - INFO - [082/120] Training session : 5 ; lr : 0.00989426131062069 ; loss : 0.014405859634280205 ; acc@1 : 100.0
2023-02-02 22:59:48,858 - mmcls - INFO - [083/120] Training session : 5 ; lr : 0.009369799531534013 ; loss : 0.045226458460092545 ; acc@1 : 100.0
2023-02-02 22:59:49,211 - mmcls - INFO - [084/120] Training session : 5 ; lr : 0.008857188153166141 ; loss : 0.04324043169617653 ; acc@1 : 100.0
2023-02-02 22:59:51,274 - mmcls - INFO - [085/120] Training session : 5 ; lr : 0.008356809705338317 ; loss : 0.03270766884088516 ; acc@1 : 100.0
2023-02-02 22:59:51,305 - mmcls - INFO - [086/120] Training session : 5 ; lr : 0.007869037589200585 ; loss : 0.04416750743985176 ; acc@1 : 100.0
2023-02-02 22:59:51,399 - mmcls - INFO - [087/120] Training session : 5 ; lr : 0.0073942357985858475 ; loss : 0.03696710243821144 ; acc@1 : 100.0
2023-02-02 22:59:51,430 - mmcls - INFO - [088/120] Training session : 5 ; lr : 0.0069327586483840156 ; loss : 0.04638921469449997 ; acc@1 : 100.0
2023-02-02 22:59:54,153 - mmcls - INFO - [089/120] Training session : 5 ; lr : 0.006484950510138976 ; loss : 0.03469333052635193 ; acc@1 : 100.0
2023-02-02 22:59:54,193 - mmcls - INFO - [090/120] Training session : 5 ; lr : 0.006051145555065607 ; loss : 0.04383224621415138 ; acc@1 : 100.0
2023-02-02 22:59:54,228 - mmcls - INFO - [091/120] Training session : 5 ; lr : 0.005631667504678762 ; loss : 0.016421794891357422 ; acc@1 : 100.0
2023-02-02 22:59:54,275 - mmcls - INFO - [092/120] Training session : 5 ; lr : 0.005226829389220054 ; loss : 0.02918965369462967 ; acc@1 : 100.0
2023-02-02 22:59:56,620 - mmcls - INFO - [093/120] Training session : 5 ; lr : 0.004836933314063029 ; loss : 0.026393957436084747 ; acc@1 : 100.0
2023-02-02 22:59:56,635 - mmcls - INFO - [094/120] Training session : 5 ; lr : 0.004462270234270788 ; loss : 0.027834026142954826 ; acc@1 : 100.0
2023-02-02 22:59:56,643 - mmcls - INFO - [095/120] Training session : 5 ; lr : 0.0041031197374744085 ; loss : 0.02644258737564087 ; acc@1 : 100.0
2023-02-02 22:59:56,669 - mmcls - INFO - [096/120] Training session : 5 ; lr : 0.0037597498352341945 ; loss : 0.03050321899354458 ; acc@1 : 100.0
2023-02-02 22:59:58,333 - mmcls - INFO - [097/120] Training session : 5 ; lr : 0.003432416763039379 ; loss : 0.02418859675526619 ; acc@1 : 100.0
2023-02-02 22:59:58,379 - mmcls - INFO - [098/120] Training session : 5 ; lr : 0.003121364789095634 ; loss : 0.024004096165299416 ; acc@1 : 100.0
2023-02-02 22:59:58,390 - mmcls - INFO - [099/120] Training session : 5 ; lr : 0.0028268260320429544 ; loss : 0.02289879135787487 ; acc@1 : 100.0
2023-02-02 22:59:58,406 - mmcls - INFO - [100/120] Training session : 5 ; lr : 0.0025490202877400427 ; loss : 0.029615100473165512 ; acc@1 : 100.0
2023-02-02 23:00:01,270 - mmcls - INFO - [101/120] Training session : 5 ; lr : 0.002288154865244382 ; loss : 0.047675181180238724 ; acc@1 : 100.0
2023-02-02 23:00:01,290 - mmcls - INFO - [102/120] Training session : 5 ; lr : 0.002044424432110499 ; loss : 0.024625450372695923 ; acc@1 : 100.0
2023-02-02 23:00:01,304 - mmcls - INFO - [103/120] Training session : 5 ; lr : 0.0018180108691216665 ; loss : 0.0410793162882328 ; acc@1 : 100.0
2023-02-02 23:00:01,330 - mmcls - INFO - [104/120] Training session : 5 ; lr : 0.001609083134563711 ; loss : 0.01757320947945118 ; acc@1 : 100.0
2023-02-02 23:00:03,536 - mmcls - INFO - [105/120] Training session : 5 ; lr : 0.0014177971381419715 ; loss : 0.03342601656913757 ; acc@1 : 100.0
2023-02-02 23:00:03,572 - mmcls - INFO - [106/120] Training session : 5 ; lr : 0.0012442956246356367 ; loss : 0.028893038630485535 ; acc@1 : 100.0
2023-02-02 23:00:03,793 - mmcls - INFO - [107/120] Training session : 5 ; lr : 0.0010887080673762724 ; loss : 0.016090799123048782 ; acc@1 : 100.0
2023-02-02 23:00:04,175 - mmcls - INFO - [108/120] Training session : 5 ; lr : 0.0009511505716299263 ; loss : 0.013473723083734512 ; acc@1 : 100.0
2023-02-02 23:00:05,884 - mmcls - INFO - [109/120] Training session : 5 ; lr : 0.0008317257879550524 ; loss : 0.037442516535520554 ; acc@1 : 100.0
2023-02-02 23:00:06,125 - mmcls - INFO - [110/120] Training session : 5 ; lr : 0.0007305228356008139 ; loss : 0.018873702734708786 ; acc@1 : 100.0
2023-02-02 23:00:06,139 - mmcls - INFO - [111/120] Training session : 5 ; lr : 0.000647617236002961 ; loss : 0.04440877586603165 ; acc@1 : 100.0
2023-02-02 23:00:06,376 - mmcls - INFO - [112/120] Training session : 5 ; lr : 0.000583070856426893 ; loss : 0.015216993167996407 ; acc@1 : 100.0
2023-02-02 23:00:07,818 - mmcls - INFO - [113/120] Training session : 5 ; lr : 0.0005369318638000077 ; loss : 0.03974027931690216 ; acc@1 : 100.0
2023-02-02 23:00:07,904 - mmcls - INFO - [114/120] Training session : 5 ; lr : 0.0005092346887677106 ; loss : 0.018849443644285202 ; acc@1 : 100.0
2023-02-02 23:00:07,930 - mmcls - INFO - [115/120] Training session : 5 ; lr : 0.0005 ; loss : 0.04548037424683571 ; acc@1 : 100.0
2023-02-02 23:00:08,255 - mmcls - INFO - [116/120] Training session : 5 ; lr : 5e-05 ; loss : 0.03313285857439041 ; acc@1 : 100.0
2023-02-02 23:00:10,279 - mmcls - INFO - [117/120] Training session : 5 ; lr : 5e-05 ; loss : 0.02835935354232788 ; acc@1 : 100.0
2023-02-02 23:00:10,325 - mmcls - INFO - [118/120] Training session : 5 ; lr : 5e-05 ; loss : 0.06731129437685013 ; acc@1 : 100.0
2023-02-02 23:00:10,355 - mmcls - INFO - [119/120] Training session : 5 ; lr : 5e-05 ; loss : 0.021860726177692413 ; acc@1 : 100.0
2023-02-02 23:00:10,382 - mmcls - INFO - [120/120] Training session : 5 ; lr : 5e-05 ; loss : 0.07225285470485687 ; acc@1 : 100.0
2023-02-02 23:00:10,383 - mmcls - INFO - Evaluating session 5, from 0 to 140.
2023-02-02 23:00:13,175 - mmcls - INFO - [05]Evaluation results : acc : 68.17 ; acc_base : 77.23 ; acc_inc : 45.88
2023-02-02 23:00:13,175 - mmcls - INFO - [05]Evaluation results : acc_incremental_old : 41.91 ; acc_incremental_new : 72.67
2023-02-02 23:00:13,263 - mmcls - INFO - Starting session : 6 ------------------------------------------------------------
2023-02-02 23:00:13,263 - mmcls - INFO - Newly added classes are from 140 to 150.
2023-02-02 23:00:13,263 - mmcls - INFO - Model now can classify 150 classes
2023-02-02 23:00:13,263 - mmcls - INFO - 125 steps
2023-02-02 23:00:13,264 - mmcls - INFO - Extracting mean neck feat from 100 to 140
2023-02-02 23:00:13,264 - mmcls - INFO - Copy 5 duplications.
2023-02-02 23:00:13,327 - mmcls - INFO - Session : 6 ; The dataset has 350 samples.
2023-02-02 23:00:13,328 - mmcls - INFO - Labels : [140, 140, 140, 140, 140, 141, 141, 141, 141, 141, 142, 142, 142, 142, 142, 143, 143, 143, 143, 143, 144, 144, 144, 144, 144, 145, 145, 145, 145, 145, 146, 146, 146, 146, 146, 147, 147, 147, 147, 147, 148, 148, 148, 148, 148, 149, 149, 149, 149, 149, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
2023-02-02 23:00:15,587 - mmcls - INFO - [001/125] Training session : 6 ; lr : 0.013997625262080607 ; loss : 0.6462738513946533 ; acc@1 : 87.5
2023-02-02 23:00:15,637 - mmcls - INFO - [002/125] Training session : 6 ; lr : 0.02298439725318082 ; loss : 0.6418622732162476 ; acc@1 : 87.5
2023-02-02 23:00:15,666 - mmcls - INFO - [003/125] Training session : 6 ; lr : 0.031951170566332746 ; loss : 1.0684912204742432 ; acc@1 : 75.0
2023-02-02 23:00:15,684 - mmcls - INFO - [004/125] Training session : 6 ; lr : 0.04088882186649911 ; loss : 0.6208070516586304 ; acc@1 : 87.5
2023-02-02 23:00:15,750 - mmcls - INFO - [005/125] Training session : 6 ; lr : 0.04978826031900181 ; loss : 0.12071624398231506 ; acc@1 : 100.0
2023-02-02 23:00:17,768 - mmcls - INFO - [006/125] Training session : 6 ; lr : 0.04969528642972966 ; loss : 0.41392946243286133 ; acc@1 : 100.0
2023-02-02 23:00:17,863 - mmcls - INFO - [007/125] Training session : 6 ; lr : 0.049585558962207885 ; loss : 0.4487714469432831 ; acc@1 : 100.0
2023-02-02 23:00:18,484 - mmcls - INFO - [008/125] Training session : 6 ; lr : 0.049459153118161694 ; loss : 0.5615746378898621 ; acc@1 : 100.0
2023-02-02 23:00:18,544 - mmcls - INFO - [009/125] Training session : 6 ; lr : 0.0493161555298425 ; loss : 0.405373215675354 ; acc@1 : 87.5
2023-02-02 23:00:18,678 - mmcls - INFO - [010/125] Training session : 6 ; lr : 0.04915666420065444 ; loss : 0.1326390951871872 ; acc@1 : 100.0
2023-02-02 23:00:20,697 - mmcls - INFO - [011/125] Training session : 6 ; lr : 0.04898078843798778 ; loss : 0.5682417154312134 ; acc@1 : 100.0
2023-02-02 23:00:20,730 - mmcls - INFO - [012/125] Training session : 6 ; lr : 0.048788648778305056 ; loss : 0.58106929063797 ; acc@1 : 87.5
2023-02-02 23:00:20,856 - mmcls - INFO - [013/125] Training session : 6 ; lr : 0.048580376904531423 ; loss : 0.5338651537895203 ; acc@1 : 100.0
2023-02-02 23:00:21,160 - mmcls - INFO - [014/125] Training session : 6 ; lr : 0.04835611555580574 ; loss : 0.11691297590732574 ; acc@1 : 100.0
2023-02-02 23:00:21,275 - mmcls - INFO - [015/125] Training session : 6 ; lr : 0.04811601842965435 ; loss : 0.09433238953351974 ; acc@1 : 100.0
2023-02-02 23:00:22,961 - mmcls - INFO - [016/125] Training session : 6 ; lr : 0.04786025007665437 ; loss : 0.1114395260810852 ; acc@1 : 100.0
2023-02-02 23:00:23,669 - mmcls - INFO - [017/125] Training session : 6 ; lr : 0.047588985787659056 ; loss : 0.07903674244880676 ; acc@1 : 100.0
2023-02-02 23:00:23,732 - mmcls - INFO - [018/125] Training session : 6 ; lr : 0.047302411473662105 ; loss : 0.059532590210437775 ; acc@1 : 100.0
2023-02-02 23:00:23,738 - mmcls - INFO - [019/125] Training session : 6 ; lr : 0.047000723538383644 ; loss : 0.3547821044921875 ; acc@1 : 100.0
2023-02-02 23:00:23,744 - mmcls - INFO - [020/125] Training session : 6 ; lr : 0.046684128743664864 ; loss : 0.12618102133274078 ; acc@1 : 100.0
2023-02-02 23:00:26,093 - mmcls - INFO - [021/125] Training session : 6 ; lr : 0.046352844067763785 ; loss : 0.25226765871047974 ; acc@1 : 87.5
2023-02-02 23:00:26,113 - mmcls - INFO - [022/125] Training session : 6 ; lr : 0.046007096556649245 ; loss : 0.3614235520362854 ; acc@1 : 100.0
2023-02-02 23:00:26,118 - mmcls - INFO - [023/125] Training session : 6 ; lr : 0.045647123168394886 ; loss : 0.11009731888771057 ; acc@1 : 100.0
2023-02-02 23:00:26,122 - mmcls - INFO - [024/125] Training session : 6 ; lr : 0.04527317061077995 ; loss : 0.21218067407608032 ; acc@1 : 100.0
2023-02-02 23:00:26,127 - mmcls - INFO - [025/125] Training session : 6 ; lr : 0.04488549517220807 ; loss : 0.11950695514678955 ; acc@1 : 100.0
2023-02-02 23:00:27,959 - mmcls - INFO - [026/125] Training session : 6 ; lr : 0.04448436254606003 ; loss : 0.38385242223739624 ; acc@1 : 100.0
2023-02-02 23:00:27,964 - mmcls - INFO - [027/125] Training session : 6 ; lr : 0.04407004764860077 ; loss : 0.14993271231651306 ; acc@1 : 100.0
2023-02-02 23:00:27,971 - mmcls - INFO - [028/125] Training session : 6 ; lr : 0.04364283443056551 ; loss : 0.22838634252548218 ; acc@1 : 100.0
2023-02-02 23:00:28,027 - mmcls - INFO - [029/125] Training session : 6 ; lr : 0.04320301568255412 ; loss : 0.11548222601413727 ; acc@1 : 100.0
2023-02-02 23:00:28,341 - mmcls - INFO - [030/125] Training session : 6 ; lr : 0.04275089283436705 ; loss : 0.18765583634376526 ; acc@1 : 100.0
2023-02-02 23:00:30,178 - mmcls - INFO - [031/125] Training session : 6 ; lr : 0.042286775748420415 ; loss : 0.04397789016366005 ; acc@1 : 100.0
2023-02-02 23:00:30,207 - mmcls - INFO - [032/125] Training session : 6 ; lr : 0.041810982507381744 ; loss : 0.0860452800989151 ; acc@1 : 100.0
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2023-02-02 23:00:30,566 - mmcls - INFO - [035/125] Training session : 6 ; lr : 0.040316845367965835 ; loss : 0.05126167833805084 ; acc@1 : 100.0
2023-02-02 23:00:32,529 - mmcls - INFO - [036/125] Training session : 6 ; lr : 0.03979768499423871 ; loss : 0.03141789510846138 ; acc@1 : 100.0
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2023-02-02 23:00:37,620 - mmcls - INFO - [046/125] Training session : 6 ; lr : 0.03411960675124618 ; loss : 0.14263714849948883 ; acc@1 : 100.0
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2023-02-02 23:00:37,674 - mmcls - INFO - [048/125] Training session : 6 ; lr : 0.03289817061077995 ; loss : 0.10832705348730087 ; acc@1 : 100.0
2023-02-02 23:00:37,701 - mmcls - INFO - [049/125] Training session : 6 ; lr : 0.03227937978142209 ; loss : 0.024406064301729202 ; acc@1 : 100.0
2023-02-02 23:00:37,731 - mmcls - INFO - [050/125] Training session : 6 ; lr : 0.03165577136628739 ; loss : 0.042644351720809937 ; acc@1 : 100.0
2023-02-02 23:00:40,126 - mmcls - INFO - [051/125] Training session : 6 ; lr : 0.031027772755433662 ; loss : 0.010961068794131279 ; acc@1 : 100.0
2023-02-02 23:00:40,156 - mmcls - INFO - [052/125] Training session : 6 ; lr : 0.030395814347739542 ; loss : 0.056846484541893005 ; acc@1 : 100.0
2023-02-02 23:00:40,167 - mmcls - INFO - [053/125] Training session : 6 ; lr : 0.029760329255930657 ; loss : 0.03271567448973656 ; acc@1 : 100.0
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2023-02-02 23:00:40,221 - mmcls - INFO - [055/125] Training session : 6 ; lr : 0.028480523257446284 ; loss : 0.01603977382183075 ; acc@1 : 100.0
2023-02-02 23:00:42,141 - mmcls - INFO - [056/125] Training session : 6 ; lr : 0.027837079465874427 ; loss : 0.029750153422355652 ; acc@1 : 100.0
2023-02-02 23:00:42,176 - mmcls - INFO - [057/125] Training session : 6 ; lr : 0.027191862619264165 ; loss : 0.04730060696601868 ; acc@1 : 100.0
2023-02-02 23:00:42,699 - mmcls - INFO - [058/125] Training session : 6 ; lr : 0.026545314917012865 ; loss : 0.052567366510629654 ; acc@1 : 100.0
2023-02-02 23:00:42,732 - mmcls - INFO - [059/125] Training session : 6 ; lr : 0.025897879470619865 ; loss : 0.0482984334230423 ; acc@1 : 100.0
2023-02-02 23:00:42,764 - mmcls - INFO - [060/125] Training session : 6 ; lr : 0.02525 ; loss : 0.016916343942284584 ; acc@1 : 100.0
2023-02-02 23:00:44,374 - mmcls - INFO - [061/125] Training session : 6 ; lr : 0.024602120529380146 ; loss : 0.08806086331605911 ; acc@1 : 100.0
2023-02-02 23:00:44,422 - mmcls - INFO - [062/125] Training session : 6 ; lr : 0.02395468508298714 ; loss : 0.029919616878032684 ; acc@1 : 100.0
2023-02-02 23:00:44,458 - mmcls - INFO - [063/125] Training session : 6 ; lr : 0.023308137380735842 ; loss : 0.02048661932349205 ; acc@1 : 100.0
2023-02-02 23:00:44,801 - mmcls - INFO - [064/125] Training session : 6 ; lr : 0.022662920534125584 ; loss : 0.0726085975766182 ; acc@1 : 100.0
2023-02-02 23:00:45,079 - mmcls - INFO - [065/125] Training session : 6 ; lr : 0.02201947674255373 ; loss : 0.09872861206531525 ; acc@1 : 100.0
2023-02-02 23:00:46,695 - mmcls - INFO - [066/125] Training session : 6 ; lr : 0.02137824699025428 ; loss : 0.05626814812421799 ; acc@1 : 100.0
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2023-02-02 23:00:46,750 - mmcls - INFO - [068/125] Training session : 6 ; lr : 0.02010418565226046 ; loss : 0.048985663801431656 ; acc@1 : 100.0
2023-02-02 23:00:47,286 - mmcls - INFO - [069/125] Training session : 6 ; lr : 0.01947222724456635 ; loss : 0.022365357726812363 ; acc@1 : 100.0
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2023-02-02 23:00:50,028 - mmcls - INFO - [071/125] Training session : 6 ; lr : 0.018220620218577916 ; loss : 0.011548112146556377 ; acc@1 : 100.0
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2023-02-02 23:00:50,078 - mmcls - INFO - [073/125] Training session : 6 ; lr : 0.016988280233964172 ; loss : 0.025542300194501877 ; acc@1 : 100.0
2023-02-02 23:00:50,116 - mmcls - INFO - [074/125] Training session : 6 ; lr : 0.01638039324875382 ; loss : 0.08265472948551178 ; acc@1 : 100.0
2023-02-02 23:00:50,164 - mmcls - INFO - [075/125] Training session : 6 ; lr : 0.01577858504896403 ; loss : 0.04693823307752609 ; acc@1 : 100.0
2023-02-02 23:00:51,868 - mmcls - INFO - [076/125] Training session : 6 ; lr : 0.015183268083873951 ; loss : 0.019435305148363113 ; acc@1 : 100.0
2023-02-02 23:00:51,892 - mmcls - INFO - [077/125] Training session : 6 ; lr : 0.01459485035399469 ; loss : 0.05147266387939453 ; acc@1 : 100.0
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2023-02-02 23:00:52,151 - mmcls - INFO - [079/125] Training session : 6 ; lr : 0.013440320683574692 ; loss : 0.05863368511199951 ; acc@1 : 100.0
2023-02-02 23:00:52,234 - mmcls - INFO - [080/125] Training session : 6 ; lr : 0.012875000000000006 ; loss : 0.02371545508503914 ; acc@1 : 100.0
2023-02-02 23:00:54,199 - mmcls - INFO - [081/125] Training session : 6 ; lr : 0.012318160523280268 ; loss : 0.04563117027282715 ; acc@1 : 100.0
2023-02-02 23:00:54,240 - mmcls - INFO - [082/125] Training session : 6 ; lr : 0.01177018388337808 ; loss : 0.03384258970618248 ; acc@1 : 100.0
2023-02-02 23:00:54,592 - mmcls - INFO - [083/125] Training session : 6 ; lr : 0.011231445636110393 ; loss : 0.02395348623394966 ; acc@1 : 100.0
2023-02-02 23:00:54,664 - mmcls - INFO - [084/125] Training session : 6 ; lr : 0.010702315005761293 ; loss : 0.029359159991145134 ; acc@1 : 100.0
2023-02-02 23:00:54,706 - mmcls - INFO - [085/125] Training session : 6 ; lr : 0.010183154632034164 ; loss : 0.035453613847494125 ; acc@1 : 100.0
2023-02-02 23:00:56,414 - mmcls - INFO - [086/125] Training session : 6 ; lr : 0.009674320321516529 ; loss : 0.02923423796892166 ; acc@1 : 100.0
2023-02-02 23:00:56,442 - mmcls - INFO - [087/125] Training session : 6 ; lr : 0.009176160803827958 ; loss : 0.029279952868819237 ; acc@1 : 100.0
2023-02-02 23:00:56,485 - mmcls - INFO - [088/125] Training session : 6 ; lr : 0.008689017492618268 ; loss : 0.022856639698147774 ; acc@1 : 100.0
2023-02-02 23:00:56,507 - mmcls - INFO - [089/125] Training session : 6 ; lr : 0.008213224251579585 ; loss : 0.02274385094642639 ; acc@1 : 100.0
2023-02-02 23:00:56,817 - mmcls - INFO - [090/125] Training session : 6 ; lr : 0.00774910716563295 ; loss : 0.03350287303328514 ; acc@1 : 100.0
2023-02-02 23:00:58,443 - mmcls - INFO - [091/125] Training session : 6 ; lr : 0.007296984317445887 ; loss : 0.05021803081035614 ; acc@1 : 100.0
2023-02-02 23:00:58,471 - mmcls - INFO - [092/125] Training session : 6 ; lr : 0.006857165569434489 ; loss : 0.030280007049441338 ; acc@1 : 100.0
2023-02-02 23:00:58,553 - mmcls - INFO - [093/125] Training session : 6 ; lr : 0.006429952351399235 ; loss : 0.058958426117897034 ; acc@1 : 100.0
2023-02-02 23:00:58,680 - mmcls - INFO - [094/125] Training session : 6 ; lr : 0.00601563745393997 ; loss : 0.01405767910182476 ; acc@1 : 100.0
2023-02-02 23:00:58,737 - mmcls - INFO - [095/125] Training session : 6 ; lr : 0.005614504827791933 ; loss : 0.030305972322821617 ; acc@1 : 100.0
2023-02-02 23:01:01,236 - mmcls - INFO - [096/125] Training session : 6 ; lr : 0.005226829389220054 ; loss : 0.017519772052764893 ; acc@1 : 100.0
2023-02-02 23:01:01,248 - mmcls - INFO - [097/125] Training session : 6 ; lr : 0.004852876831605112 ; loss : 0.021347617730498314 ; acc@1 : 100.0
2023-02-02 23:01:01,255 - mmcls - INFO - [098/125] Training session : 6 ; lr : 0.004492903443350758 ; loss : 0.032863423228263855 ; acc@1 : 100.0
2023-02-02 23:01:01,261 - mmcls - INFO - [099/125] Training session : 6 ; lr : 0.004147155932236218 ; loss : 0.04319416731595993 ; acc@1 : 100.0
2023-02-02 23:01:01,291 - mmcls - INFO - [100/125] Training session : 6 ; lr : 0.003815871256335142 ; loss : 0.015927769243717194 ; acc@1 : 100.0
2023-02-02 23:01:03,737 - mmcls - INFO - [101/125] Training session : 6 ; lr : 0.0034992764616163597 ; loss : 0.01190720871090889 ; acc@1 : 100.0
2023-02-02 23:01:03,764 - mmcls - INFO - [102/125] Training session : 6 ; lr : 0.0031975885263378972 ; loss : 0.03965497016906738 ; acc@1 : 100.0
2023-02-02 23:01:03,783 - mmcls - INFO - [103/125] Training session : 6 ; lr : 0.002911014212340955 ; loss : 0.02225077711045742 ; acc@1 : 100.0
2023-02-02 23:01:03,802 - mmcls - INFO - [104/125] Training session : 6 ; lr : 0.002639749923345626 ; loss : 0.028999868780374527 ; acc@1 : 100.0
2023-02-02 23:01:03,825 - mmcls - INFO - [105/125] Training session : 6 ; lr : 0.0023839815703456534 ; loss : 0.03520060330629349 ; acc@1 : 100.0
2023-02-02 23:01:06,111 - mmcls - INFO - [106/125] Training session : 6 ; lr : 0.00214388444419426 ; loss : 0.01719122752547264 ; acc@1 : 100.0
2023-02-02 23:01:06,175 - mmcls - INFO - [107/125] Training session : 6 ; lr : 0.0019196230954685839 ; loss : 0.037023693323135376 ; acc@1 : 100.0
2023-02-02 23:01:06,205 - mmcls - INFO - [108/125] Training session : 6 ; lr : 0.0017113512216949502 ; loss : 0.0175317469984293 ; acc@1 : 100.0
2023-02-02 23:01:06,231 - mmcls - INFO - [109/125] Training session : 6 ; lr : 0.001519211562012222 ; loss : 0.026536431163549423 ; acc@1 : 100.0
2023-02-02 23:01:06,261 - mmcls - INFO - [110/125] Training session : 6 ; lr : 0.0013433357993455622 ; loss : 0.014566939324140549 ; acc@1 : 100.0
2023-02-02 23:01:08,436 - mmcls - INFO - [111/125] Training session : 6 ; lr : 0.0011838444701575052 ; loss : 0.031861089169979095 ; acc@1 : 100.0
2023-02-02 23:01:08,474 - mmcls - INFO - [112/125] Training session : 6 ; lr : 0.0010408468818383092 ; loss : 0.028863735496997833 ; acc@1 : 100.0
2023-02-02 23:01:08,552 - mmcls - INFO - [113/125] Training session : 6 ; lr : 0.000914441037792126 ; loss : 0.02906952053308487 ; acc@1 : 100.0
2023-02-02 23:01:08,597 - mmcls - INFO - [114/125] Training session : 6 ; lr : 0.000804713570270343 ; loss : 0.032566528767347336 ; acc@1 : 100.0
2023-02-02 23:01:08,622 - mmcls - INFO - [115/125] Training session : 6 ; lr : 0.000711739680998193 ; loss : 0.024076318368315697 ; acc@1 : 100.0
2023-02-02 23:01:10,389 - mmcls - INFO - [116/125] Training session : 6 ; lr : 0.0006355830896352361 ; loss : 0.011789409443736076 ; acc@1 : 100.0
2023-02-02 23:01:10,676 - mmcls - INFO - [117/125] Training session : 6 ; lr : 0.0005762959901050829 ; loss : 0.01787366159260273 ; acc@1 : 100.0
2023-02-02 23:01:10,716 - mmcls - INFO - [118/125] Training session : 6 ; lr : 0.0005339190148242976 ; loss : 0.02010492980480194 ; acc@1 : 100.0
2023-02-02 23:01:10,738 - mmcls - INFO - [119/125] Training session : 6 ; lr : 0.0005084812068549578 ; loss : 0.04839908704161644 ; acc@1 : 100.0
2023-02-02 23:01:10,916 - mmcls - INFO - [120/125] Training session : 6 ; lr : 0.0005 ; loss : 0.026969637721776962 ; acc@1 : 100.0
2023-02-02 23:01:12,732 - mmcls - INFO - [121/125] Training session : 6 ; lr : 5e-05 ; loss : 0.040882937610149384 ; acc@1 : 100.0
2023-02-02 23:01:12,752 - mmcls - INFO - [122/125] Training session : 6 ; lr : 5e-05 ; loss : 0.02011704258620739 ; acc@1 : 100.0
2023-02-02 23:01:12,761 - mmcls - INFO - [123/125] Training session : 6 ; lr : 5e-05 ; loss : 0.06845825910568237 ; acc@1 : 100.0
2023-02-02 23:01:12,787 - mmcls - INFO - [124/125] Training session : 6 ; lr : 5e-05 ; loss : 0.024805966764688492 ; acc@1 : 100.0
2023-02-02 23:01:12,818 - mmcls - INFO - [125/125] Training session : 6 ; lr : 5e-05 ; loss : 0.058099448680877686 ; acc@1 : 100.0
2023-02-02 23:01:12,818 - mmcls - INFO - Evaluating session 6, from 0 to 150.
2023-02-02 23:01:15,586 - mmcls - INFO - [06]Evaluation results : acc : 65.16 ; acc_base : 77.13 ; acc_inc : 41.72
2023-02-02 23:01:15,586 - mmcls - INFO - [06]Evaluation results : acc_incremental_old : 38.39 ; acc_incremental_new : 71.14
2023-02-02 23:01:15,656 - mmcls - INFO - Starting session : 7 ------------------------------------------------------------
2023-02-02 23:01:15,656 - mmcls - INFO - Newly added classes are from 150 to 160.
2023-02-02 23:01:15,656 - mmcls - INFO - Model now can classify 160 classes
2023-02-02 23:01:15,657 - mmcls - INFO - 130 steps
2023-02-02 23:01:15,657 - mmcls - INFO - Extracting mean neck feat from 100 to 150
2023-02-02 23:01:15,657 - mmcls - INFO - Copy 6 duplications.
2023-02-02 23:01:15,737 - mmcls - INFO - Session : 7 ; The dataset has 450 samples.
2023-02-02 23:01:15,737 - mmcls - INFO - Labels : [150, 150, 150, 150, 150, 151, 151, 151, 151, 151, 152, 152, 152, 152, 152, 153, 153, 153, 153, 153, 154, 154, 154, 154, 154, 155, 155, 155, 155, 155, 156, 156, 156, 156, 156, 157, 157, 157, 157, 157, 158, 158, 158, 158, 158, 159, 159, 159, 159, 159, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
2023-02-02 23:01:18,273 - mmcls - INFO - [001/130] Training session : 7 ; lr : 0.013997811431733264 ; loss : 1.323150873184204 ; acc@1 : 75.0
2023-02-02 23:01:18,325 - mmcls - INFO - [002/130] Training session : 7 ; lr : 0.02298562025095951 ; loss : 0.02232045866549015 ; acc@1 : 100.0
2023-02-02 23:01:18,378 - mmcls - INFO - [003/130] Training session : 7 ; lr : 0.03195499698012812 ; loss : 0.01788836158812046 ; acc@1 : 100.0
2023-02-02 23:01:18,401 - mmcls - INFO - [004/130] Training session : 7 ; lr : 0.04089753088963549 ; loss : 0.4543055295944214 ; acc@1 : 87.5
2023-02-02 23:01:18,436 - mmcls - INFO - [005/130] Training session : 7 ; lr : 0.04980483885753333 ; loss : 0.42846548557281494 ; acc@1 : 87.5
2023-02-02 23:01:18,473 - mmcls - INFO - [006/130] Training session : 7 ; lr : 0.04971913068226337 ; loss : 0.13420595228672028 ; acc@1 : 100.0
2023-02-02 23:01:18,492 - mmcls - INFO - [007/130] Training session : 7 ; lr : 0.04961796727959784 ; loss : 0.4004077911376953 ; acc@1 : 87.5
2023-02-02 23:01:20,288 - mmcls - INFO - [008/130] Training session : 7 ; lr : 0.04950141254651011 ; loss : 0.6093189716339111 ; acc@1 : 100.0
2023-02-02 23:01:20,328 - mmcls - INFO - [009/130] Training session : 7 ; lr : 0.04936954010146779 ; loss : 0.13660036027431488 ; acc@1 : 100.0
2023-02-02 23:01:20,366 - mmcls - INFO - [010/130] Training session : 7 ; lr : 0.04922243323793362 ; loss : 0.08917121589183807 ; acc@1 : 100.0
2023-02-02 23:01:20,403 - mmcls - INFO - [011/130] Training session : 7 ; lr : 0.049060184871755626 ; loss : 0.20348818600177765 ; acc@1 : 100.0
2023-02-02 23:01:20,651 - mmcls - INFO - [012/130] Training session : 7 ; lr : 0.04888289748247942 ; loss : 0.2758401930332184 ; acc@1 : 100.0
2023-02-02 23:01:20,671 - mmcls - INFO - [013/130] Training session : 7 ; lr : 0.048690683048619926 ; loss : 0.08050733804702759 ; acc@1 : 100.0
2023-02-02 23:01:20,703 - mmcls - INFO - [014/130] Training session : 7 ; lr : 0.04848366297693339 ; loss : 0.22064454853534698 ; acc@1 : 100.0
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2023-02-02 23:01:22,981 - mmcls - INFO - [019/130] Training session : 7 ; lr : 0.04723137710813523 ; loss : 0.27295076847076416 ; acc@1 : 87.5
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2023-02-02 23:01:23,223 - mmcls - INFO - [021/130] Training session : 7 ; lr : 0.04663210457552267 ; loss : 0.057454511523246765 ; acc@1 : 100.0
2023-02-02 23:01:25,482 - mmcls - INFO - [022/130] Training session : 7 ; lr : 0.04631211342441863 ; loss : 0.08012477308511734 ; acc@1 : 100.0
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2023-02-02 23:01:40,406 - mmcls - INFO - [066/130] Training session : 7 ; lr : 0.023075682885369108 ; loss : 0.011747067794203758 ; acc@1 : 100.0
2023-02-02 23:01:40,425 - mmcls - INFO - [067/130] Training session : 7 ; lr : 0.02245680447438133 ; loss : 0.014613949693739414 ; acc@1 : 100.0
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2023-02-02 23:01:47,508 - mmcls - INFO - [086/130] Training session : 7 ; lr : 0.011467328491917358 ; loss : 0.060858260840177536 ; acc@1 : 100.0
2023-02-02 23:01:47,518 - mmcls - INFO - [087/130] Training session : 7 ; lr : 0.010955075590298883 ; loss : 0.026125937700271606 ; acc@1 : 100.0
2023-02-02 23:01:47,569 - mmcls - INFO - [088/130] Training session : 7 ; lr : 0.010451851669326419 ; loss : 0.019505834206938744 ; acc@1 : 100.0
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2023-02-02 23:01:59,911 - mmcls - INFO - [124/130] Training session : 7 ; lr : 0.0005078163152383265 ; loss : 0.0043029822409152985 ; acc@1 : 100.0
2023-02-02 23:02:00,083 - mmcls - INFO - [125/130] Training session : 7 ; lr : 0.0005 ; loss : 0.024257471784949303 ; acc@1 : 100.0
2023-02-02 23:02:00,132 - mmcls - INFO - [126/130] Training session : 7 ; lr : 5e-05 ; loss : 0.0363975465297699 ; acc@1 : 100.0
2023-02-02 23:02:02,031 - mmcls - INFO - [127/130] Training session : 7 ; lr : 5e-05 ; loss : 0.01373731717467308 ; acc@1 : 100.0
2023-02-02 23:02:02,084 - mmcls - INFO - [128/130] Training session : 7 ; lr : 5e-05 ; loss : 0.004773618187755346 ; acc@1 : 100.0
2023-02-02 23:02:02,151 - mmcls - INFO - [129/130] Training session : 7 ; lr : 5e-05 ; loss : 0.04712668061256409 ; acc@1 : 100.0
2023-02-02 23:02:02,215 - mmcls - INFO - [130/130] Training session : 7 ; lr : 5e-05 ; loss : 0.019456705078482628 ; acc@1 : 100.0
2023-02-02 23:02:02,216 - mmcls - INFO - Evaluating session 7, from 0 to 160.
2023-02-02 23:02:04,678 - mmcls - INFO - [07]Evaluation results : acc : 64.43 ; acc_base : 76.85 ; acc_inc : 44.11
2023-02-02 23:02:04,679 - mmcls - INFO - [07]Evaluation results : acc_incremental_old : 40.57 ; acc_incremental_new : 82.43
2023-02-02 23:02:04,745 - mmcls - INFO - Starting session : 8 ------------------------------------------------------------
2023-02-02 23:02:04,745 - mmcls - INFO - Newly added classes are from 160 to 170.
2023-02-02 23:02:04,745 - mmcls - INFO - Model now can classify 170 classes
2023-02-02 23:02:04,745 - mmcls - INFO - 135 steps
2023-02-02 23:02:04,745 - mmcls - INFO - Extracting mean neck feat from 100 to 160
2023-02-02 23:02:04,745 - mmcls - INFO - Copy 7 duplications.
2023-02-02 23:02:04,851 - mmcls - INFO - Session : 8 ; The dataset has 570 samples.
2023-02-02 23:02:04,852 - mmcls - INFO - Labels : [160, 160, 160, 160, 160, 161, 161, 161, 161, 161, 162, 162, 162, 162, 162, 163, 163, 163, 163, 163, 164, 164, 164, 164, 164, 165, 165, 165, 165, 165, 166, 166, 166, 166, 166, 167, 167, 167, 167, 167, 168, 168, 168, 168, 168, 169, 169, 169, 169, 169, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
2023-02-02 23:02:06,874 - mmcls - INFO - [001/135] Training session : 8 ; lr : 0.013997976537575734 ; loss : 0.6667928695678711 ; acc@1 : 87.5
2023-02-02 23:02:06,892 - mmcls - INFO - [002/135] Training session : 8 ; lr : 0.02298670490248604 ; loss : 1.2672065496444702 ; acc@1 : 75.0
2023-02-02 23:02:06,907 - mmcls - INFO - [003/135] Training session : 8 ; lr : 0.03195839069111322 ; loss : 0.008605370298027992 ; acc@1 : 100.0
2023-02-02 23:02:06,916 - mmcls - INFO - [004/135] Training session : 8 ; lr : 0.040905255526594686 ; loss : 0.5982720255851746 ; acc@1 : 87.5
2023-02-02 23:02:06,954 - mmcls - INFO - [005/135] Training session : 8 ; lr : 0.049819544633926835 ; loss : 0.032410282641649246 ; acc@1 : 100.0
2023-02-02 23:02:06,959 - mmcls - INFO - [006/135] Training session : 8 ; lr : 0.049740283386413515 ; loss : 0.6239379644393921 ; acc@1 : 87.5
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2023-02-02 23:02:10,110 - mmcls - INFO - [010/135] Training session : 8 ; lr : 0.04928080998129479 ; loss : 0.37683072686195374 ; acc@1 : 87.5
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2023-02-02 23:02:11,941 - mmcls - INFO - [018/135] Training session : 8 ; lr : 0.047695140431051004 ; loss : 0.8730100393295288 ; acc@1 : 87.5
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2023-02-02 23:02:15,946 - mmcls - INFO - [029/135] Training session : 8 ; lr : 0.044166814083509746 ; loss : 0.03581018000841141 ; acc@1 : 100.0
2023-02-02 23:02:15,988 - mmcls - INFO - [030/135] Training session : 8 ; lr : 0.04377564101723475 ; loss : 0.4035812318325043 ; acc@1 : 87.5
2023-02-02 23:02:16,054 - mmcls - INFO - [031/135] Training session : 8 ; lr : 0.0433736494982949 ; loss : 0.3203992545604706 ; acc@1 : 100.0
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2023-02-02 23:02:25,923 - mmcls - INFO - [068/135] Training session : 8 ; lr : 0.023457238695996384 ; loss : 0.017939306795597076 ; acc@1 : 100.0
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2023-02-02 23:02:26,348 - mmcls - INFO - [070/135] Training session : 8 ; lr : 0.02226671716368076 ; loss : 0.012260647490620613 ; acc@1 : 100.0
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2023-02-02 23:02:39,229 - mmcls - INFO - [108/135] Training session : 8 ; lr : 0.003916250744718781 ; loss : 0.011691106483340263 ; acc@1 : 100.0
2023-02-02 23:02:40,446 - mmcls - INFO - [109/135] Training session : 8 ; lr : 0.003619291192493682 ; loss : 0.013077279552817345 ; acc@1 : 100.0
2023-02-02 23:02:40,481 - mmcls - INFO - [110/135] Training session : 8 ; lr : 0.003334963365083058 ; loss : 0.014893929474055767 ; acc@1 : 100.0
2023-02-02 23:02:40,560 - mmcls - INFO - [111/135] Training session : 8 ; lr : 0.003063433301931332 ; loss : 0.018551060929894447 ; acc@1 : 100.0
2023-02-02 23:02:41,052 - mmcls - INFO - [112/135] Training session : 8 ; lr : 0.0028048595689490015 ; loss : 0.004927389789372683 ; acc@1 : 100.0
2023-02-02 23:02:41,289 - mmcls - INFO - [113/135] Training session : 8 ; lr : 0.0025593931659145855 ; loss : 0.08353591710329056 ; acc@1 : 100.0
2023-02-02 23:02:41,353 - mmcls - INFO - [114/135] Training session : 8 ; lr : 0.0023271774382950354 ; loss : 0.05486356467008591 ; acc@1 : 100.0
2023-02-02 23:02:41,398 - mmcls - INFO - [115/135] Training session : 8 ; lr : 0.0021083479935359857 ; loss : 0.029309548437595367 ; acc@1 : 100.0
2023-02-02 23:02:41,434 - mmcls - INFO - [116/135] Training session : 8 ; lr : 0.001903032621870857 ; loss : 0.024731077253818512 ; acc@1 : 100.0
2023-02-02 23:02:41,461 - mmcls - INFO - [117/135] Training session : 8 ; lr : 0.0017113512216949502 ; loss : 0.021159730851650238 ; acc@1 : 100.0
2023-02-02 23:02:43,169 - mmcls - INFO - [118/135] Training session : 8 ; lr : 0.001533415729548136 ; loss : 0.005302015691995621 ; acc@1 : 100.0
2023-02-02 23:02:43,190 - mmcls - INFO - [119/135] Training session : 8 ; lr : 0.0013693300547471042 ; loss : 0.039718739688396454 ; acc@1 : 100.0
2023-02-02 23:02:43,224 - mmcls - INFO - [120/135] Training session : 8 ; lr : 0.0012191900187052127 ; loss : 0.02401178702712059 ; acc@1 : 100.0
2023-02-02 23:02:44,025 - mmcls - INFO - [121/135] Training session : 8 ; lr : 0.0010830832989755152 ; loss : 0.0066088661551475525 ; acc@1 : 100.0
2023-02-02 23:02:44,074 - mmcls - INFO - [122/135] Training session : 8 ; lr : 0.0009610893780495175 ; loss : 0.0276203416287899 ; acc@1 : 100.0
2023-02-02 23:02:44,120 - mmcls - INFO - [123/135] Training session : 8 ; lr : 0.0008532794969416423 ; loss : 0.02903558686375618 ; acc@1 : 100.0
2023-02-02 23:02:44,141 - mmcls - INFO - [124/135] Training session : 8 ; lr : 0.0007597166135864847 ; loss : 0.03514653816819191 ; acc@1 : 100.0
2023-02-02 23:02:44,188 - mmcls - INFO - [125/135] Training session : 8 ; lr : 0.0006804553660731641 ; loss : 0.014038561843335629 ; acc@1 : 100.0
2023-02-02 23:02:44,449 - mmcls - INFO - [126/135] Training session : 8 ; lr : 0.0006155420407381965 ; loss : 0.13949516415596008 ; acc@1 : 100.0
2023-02-02 23:02:46,197 - mmcls - INFO - [127/135] Training session : 8 ; lr : 0.0005650145451355967 ; loss : 0.06008407473564148 ; acc@1 : 100.0
2023-02-02 23:02:46,214 - mmcls - INFO - [128/135] Training session : 8 ; lr : 0.0005289023858999156 ; loss : 0.07348643988370895 ; acc@1 : 100.0
2023-02-02 23:02:46,497 - mmcls - INFO - [129/135] Training session : 8 ; lr : 0.0005072266515152247 ; loss : 0.03774327039718628 ; acc@1 : 100.0
2023-02-02 23:02:46,527 - mmcls - INFO - [130/135] Training session : 8 ; lr : 0.0005 ; loss : 0.016059646382927895 ; acc@1 : 100.0
2023-02-02 23:02:46,540 - mmcls - INFO - [131/135] Training session : 8 ; lr : 5e-05 ; loss : 0.019512996077537537 ; acc@1 : 100.0
2023-02-02 23:02:46,548 - mmcls - INFO - [132/135] Training session : 8 ; lr : 5e-05 ; loss : 0.02250586822628975 ; acc@1 : 100.0
2023-02-02 23:02:46,554 - mmcls - INFO - [133/135] Training session : 8 ; lr : 5e-05 ; loss : 0.005188296549022198 ; acc@1 : 100.0
2023-02-02 23:02:46,671 - mmcls - INFO - [134/135] Training session : 8 ; lr : 5e-05 ; loss : 0.05689729377627373 ; acc@1 : 100.0
2023-02-02 23:02:46,684 - mmcls - INFO - [135/135] Training session : 8 ; lr : 5e-05 ; loss : 0.005943605210632086 ; acc@1 : 100.0
2023-02-02 23:02:46,684 - mmcls - INFO - Evaluating session 8, from 0 to 170.
2023-02-02 23:02:49,322 - mmcls - INFO - [08]Evaluation results : acc : 63.25 ; acc_base : 76.29 ; acc_inc : 44.99
2023-02-02 23:02:49,322 - mmcls - INFO - [08]Evaluation results : acc_incremental_old : 43.37 ; acc_incremental_new : 65.99
2023-02-02 23:02:49,396 - mmcls - INFO - Starting session : 9 ------------------------------------------------------------
2023-02-02 23:02:49,396 - mmcls - INFO - Newly added classes are from 170 to 180.
2023-02-02 23:02:49,396 - mmcls - INFO - Model now can classify 180 classes
2023-02-02 23:02:49,396 - mmcls - INFO - 140 steps
2023-02-02 23:02:49,396 - mmcls - INFO - Extracting mean neck feat from 100 to 170
2023-02-02 23:02:49,396 - mmcls - INFO - Copy 8 duplications.
2023-02-02 23:02:49,511 - mmcls - INFO - Session : 9 ; The dataset has 710 samples.
2023-02-02 23:02:49,511 - mmcls - INFO - Labels : [170, 170, 170, 170, 170, 171, 171, 171, 171, 171, 172, 172, 172, 172, 172, 173, 173, 173, 173, 173, 174, 174, 174, 174, 174, 175, 175, 175, 175, 175, 176, 176, 176, 176, 176, 177, 177, 177, 177, 177, 178, 178, 178, 178, 178, 179, 179, 179, 179, 179, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
2023-02-02 23:02:51,833 - mmcls - INFO - [001/140] Training session : 9 ; lr : 0.013998123641373665 ; loss : 0.044589534401893616 ; acc@1 : 100.0
2023-02-02 23:02:51,862 - mmcls - INFO - [002/140] Training session : 9 ; lr : 0.0229876713125891 ; loss : 0.008381363935768604 ; acc@1 : 100.0
2023-02-02 23:02:51,888 - mmcls - INFO - [003/140] Training session : 9 ; lr : 0.03196141455611561 ; loss : 0.6852813959121704 ; acc@1 : 87.5
2023-02-02 23:02:51,919 - mmcls - INFO - [004/140] Training session : 9 ; lr : 0.04091213869623778 ; loss : 0.5025943517684937 ; acc@1 : 87.5