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ft_k400_log.txt
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[2022-11-08 08:36:20 eva-1b/14] (main_k722.py 473): INFO working dir: /home/binhuixie/outputs/cvpr/K722_1b_ft/k400/k722init_allft-1108-01
[2022-11-08 08:36:27 eva-1b/14] (main_k722.py 499): INFO AUG:
COLOR_JITTER: 0.8
CUTMIX: 0.0
GRAY_SCALE: 0.2
LABEL_SMOOTH: 0.1
MIXUP: 0.0
MIXUP_SWITCH_PROB: 0.5
BASE: ['']
DATA:
DATASET: kinetics400
INPUT_SIZE: 224
LABEL_LIST: labels/kinetics_400_labels.csv
NUM_CLASSES: 400
NUM_FRAMES: 16
ROOT: data/
TRAIN_FILE: data/k400_train.txt
TUBELET_SIZE: 1
VAL_FILE: data/k400_val.txt
LOCAL_RANK: 0
MODEL:
ARCH: eva-1b/14
CLASS_MAPPING: data/k722_to_k400_mapping.npy
DROP_PATH_RATE: 0.2
FIX_FINE_TUNE: 0
FIX_TEXT: True
INIT_VALUES: 0.0
PRETRAINED: /home/binhuixie/outputs/cvpr/K722_1b/k722_ft_1104/ckpt_epoch_39.pth
PRETRAINED_MODE: eva_k722
RESUME: None
MYCLIP:
CHECKPOINT_SEGMENTS: 3
FT_FRAMES: 8
FT_IMAGE_SIZE: 224
NUM_EXTRA_TOKENS: 1
STOP_GRAD_CONV1: False
USE_GLOBAL_ATTEN: True
USE_LEARNABLE_POS_EMB: True
USE_MEAN_POOLING: True
USE_SAME_PE: False
USE_TEXT_EMBED: False
OUTPUT: /home/binhuixie/outputs/cvpr/K722_1b_ft/k400/k722init_allft-1108-01
PRINT_FREQ: 10
SAVE_FREQ: 1
SEED: 1024
TEST:
BATCH_SIZE: 2
MULTI_VIEW: False
NUM_CLIP: 4
NUM_CROP: 3
ONLY_TEST: False
TRAIN:
ACCUMULATION_STEPS: 2
AUTO_RESUME: False
BATCH_SIZE: 1
BETAS: (0.9, 0.98)
EPOCHS: 1
EPS: 1e-06
LAYER_WISE_DECAY: 0.95
LR: 1e-06
LR_MIN: 1e-06
LR_SCHEDULER: cosine
LR_SCHEDULER_WARMUP_PREFIX: True
OPTIMIZER: adamw
OPT_LEVEL: O1
USE_CHECKPOINT: True
WARMUP_EPOCHS: 0.0
WARMUP_START_LR: 1e-06
WEIGHT_DECAY: 0.05
WANDB: True
[2022-11-08 08:36:55 eva-1b/14] (yclip_mae.py 295): INFO Loading masked key head.weight from data/k722_to_k400_mapping.npy
[2022-11-08 08:36:55 eva-1b/14] (yclip_mae.py 295): INFO Loading masked key head.bias from data/k722_to_k400_mapping.npy
[2022-11-08 08:36:57 eva-1b/14] (main_k722.py 142): INFO cls_token requires_grad = True
[2022-11-08 08:36:57 eva-1b/14] (main_k722.py 142): INFO pos_embed requires_grad = True
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[2022-11-08 08:36:58 eva-1b/14] (main_k722.py 142): INFO blocks.7.attn.qkv.weight requires_grad = True
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[2022-11-08 08:36:58 eva-1b/14] (main_k722.py 142): INFO blocks.39.norm2.bias requires_grad = True
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[2022-11-08 08:36:58 eva-1b/14] (main_k722.py 142): INFO blocks.39.mlp.fc2.weight requires_grad = True
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[2022-11-08 08:36:58 eva-1b/14] (main_k722.py 142): INFO fc_norm.weight requires_grad = True
[2022-11-08 08:36:58 eva-1b/14] (main_k722.py 142): INFO fc_norm.bias requires_grad = True
[2022-11-08 08:36:58 eva-1b/14] (main_k722.py 142): INFO head.weight requires_grad = True
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[2022-11-08 08:36:58 eva-1b/14] (main_k722.py 148): INFO number of params: 1017.1164MB
[2022-11-08 08:36:58 eva-1b/14] (main_k722.py 159): INFO Assigned values: [0.12208654873684796, 0.12851215656510312, 0.13527595427905592, 0.14239574134637467, 0.14989025404881545, 0.1577792147882268, 0.16608338398760716, 0.174824614723797, 0.18402591023557582, 0.19371148445850087, 0.2039068257457904, 0.21463876394293727, 0.22593554099256555, 0.23782688525533216, 0.2503440897424549, 0.26352009446574204, 0.27738957312183377, 0.2919890243387724, 0.3073568677250236, 0.323533544973709, 0.3405616262881148, 0.3584859224085419, 0.37735360253530725, 0.3972143184582182, 0.4181203352191771, 0.44012666865176536, 0.46329123015975304, 0.48767497911552954, 0.5133420832795048, 0.5403600876626367, 0.5688000922764597, 0.5987369392383787, 0.6302494097246091, 0.6634204312890623, 0.6983372960937497, 0.7350918906249998, 0.7737809374999998, 0.8145062499999999, 0.8573749999999999, 0.9025, 0.95, 1.0]
[2022-11-08 08:37:17 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][0/916] eta 4:57:08 lr_first 0.000000122 lr_last 0.000001000 time 19.4634 (19.4634) tot_loss 0.7260 (0.7260) mem 15881MB
[2022-11-08 08:37:54 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][5/916] eta 1:17:35 lr_first 0.000000122 lr_last 0.000001000 time 3.5334 (5.1107) tot_loss 1.8200 (0.6581) mem 27546MB
[2022-11-08 08:38:30 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][10/916] eta 1:06:34 lr_first 0.000000122 lr_last 0.000001000 time 3.5318 (4.4091) tot_loss 0.4714 (0.5930) mem 27546MB
[2022-11-08 08:39:06 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][15/916] eta 1:02:13 lr_first 0.000000122 lr_last 0.000001000 time 3.5228 (4.1439) tot_loss 0.4663 (0.5630) mem 27550MB
[2022-11-08 08:39:42 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][20/916] eta 0:59:49 lr_first 0.000000122 lr_last 0.000001000 time 3.5439 (4.0063) tot_loss 0.4677 (0.5558) mem 27557MB
[2022-11-08 08:40:18 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][25/916] eta 0:58:24 lr_first 0.000000122 lr_last 0.000001000 time 3.6179 (3.9333) tot_loss 0.4693 (0.5462) mem 27557MB
[2022-11-08 08:40:54 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][30/916] eta 0:57:13 lr_first 0.000000122 lr_last 0.000001000 time 3.5516 (3.8755) tot_loss 0.5247 (0.5462) mem 27557MB
[2022-11-08 08:41:30 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][35/916] eta 0:56:18 lr_first 0.000000122 lr_last 0.000001000 time 3.5431 (3.8346) tot_loss 0.4673 (0.5629) mem 27557MB
[2022-11-08 08:42:07 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][40/916] eta 0:55:40 lr_first 0.000000122 lr_last 0.000001000 time 3.5216 (3.8137) tot_loss 0.4635 (0.5635) mem 27557MB
[2022-11-08 08:42:43 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][45/916] eta 0:55:00 lr_first 0.000000122 lr_last 0.000001000 time 3.5268 (3.7895) tot_loss 0.4872 (0.5798) mem 27557MB
[2022-11-08 08:43:18 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][50/916] eta 0:54:23 lr_first 0.000000122 lr_last 0.000001000 time 3.5285 (3.7689) tot_loss 0.4657 (0.5759) mem 27557MB
[2022-11-08 08:43:54 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][55/916] eta 0:53:49 lr_first 0.000000122 lr_last 0.000001000 time 3.5191 (3.7512) tot_loss 0.4844 (0.5704) mem 27557MB
[2022-11-08 08:44:30 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][60/916] eta 0:53:22 lr_first 0.000000122 lr_last 0.000001000 time 3.5577 (3.7416) tot_loss 0.4694 (0.5782) mem 27557MB
[2022-11-08 08:45:06 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][65/916] eta 0:52:53 lr_first 0.000000122 lr_last 0.000001000 time 3.5534 (3.7296) tot_loss 0.4687 (0.5724) mem 27557MB
[2022-11-08 08:45:42 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][70/916] eta 0:52:27 lr_first 0.000000122 lr_last 0.000001000 time 3.5559 (3.7203) tot_loss 0.4667 (0.5652) mem 27557MB
[2022-11-08 08:46:18 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][75/916] eta 0:52:00 lr_first 0.000000122 lr_last 0.000001000 time 3.5318 (3.7106) tot_loss 0.4715 (0.5629) mem 27557MB
[2022-11-08 08:46:55 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][80/916] eta 0:51:40 lr_first 0.000000122 lr_last 0.000001000 time 3.5904 (3.7091) tot_loss 0.8115 (0.5634) mem 27557MB
[2022-11-08 08:47:32 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][85/916] eta 0:51:20 lr_first 0.000000122 lr_last 0.000001000 time 3.5757 (3.7075) tot_loss 0.5431 (0.5602) mem 27557MB
[2022-11-08 08:48:08 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][90/916] eta 0:50:59 lr_first 0.000000122 lr_last 0.000001000 time 3.5740 (3.7035) tot_loss 0.4670 (0.5609) mem 27557MB
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[2022-11-08 08:49:20 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][100/916] eta 0:50:12 lr_first 0.000000122 lr_last 0.000001000 time 3.5354 (3.6915) tot_loss 0.4684 (0.5703) mem 27557MB
[2022-11-08 08:49:56 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][105/916] eta 0:49:51 lr_first 0.000000122 lr_last 0.000001000 time 3.5532 (3.6891) tot_loss 0.4671 (0.5685) mem 27557MB
[2022-11-08 08:50:32 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][110/916] eta 0:49:30 lr_first 0.000000122 lr_last 0.000001000 time 3.5259 (3.6849) tot_loss 0.7451 (0.5668) mem 27557MB
[2022-11-08 08:51:08 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][115/916] eta 0:49:09 lr_first 0.000000122 lr_last 0.000001000 time 3.8029 (3.6822) tot_loss 0.4733 (0.5627) mem 27557MB
[2022-11-08 08:51:44 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][120/916] eta 0:48:48 lr_first 0.000000122 lr_last 0.000001000 time 3.5645 (3.6791) tot_loss 0.5857 (0.5618) mem 27557MB
[2022-11-08 08:52:20 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][125/916] eta 0:48:27 lr_first 0.000000122 lr_last 0.000001000 time 3.5799 (3.6759) tot_loss 0.4682 (0.5591) mem 27557MB
[2022-11-08 08:52:56 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][130/916] eta 0:48:06 lr_first 0.000000122 lr_last 0.000001000 time 3.6234 (3.6729) tot_loss 0.4778 (0.5590) mem 27557MB
[2022-11-08 08:53:33 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][135/916] eta 0:47:49 lr_first 0.000000122 lr_last 0.000001000 time 3.5220 (3.6740) tot_loss 0.4635 (0.5711) mem 27557MB
[2022-11-08 08:54:09 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][140/916] eta 0:47:28 lr_first 0.000000122 lr_last 0.000001000 time 3.5207 (3.6705) tot_loss 0.4714 (0.5680) mem 27557MB
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[2022-11-08 08:55:22 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][150/916] eta 0:46:50 lr_first 0.000000122 lr_last 0.000001000 time 3.5597 (3.6685) tot_loss 0.7580 (0.5687) mem 27557MB
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[2022-11-08 08:56:33 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][160/916] eta 0:46:09 lr_first 0.000000122 lr_last 0.000001000 time 3.5345 (3.6627) tot_loss 0.4689 (0.5652) mem 27557MB
[2022-11-08 08:57:10 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][165/916] eta 0:45:50 lr_first 0.000000122 lr_last 0.000001000 time 3.5513 (3.6618) tot_loss 0.6730 (0.5647) mem 27557MB
[2022-11-08 08:57:46 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][170/916] eta 0:45:31 lr_first 0.000000122 lr_last 0.000001000 time 3.5724 (3.6611) tot_loss 0.5153 (0.5661) mem 27557MB
[2022-11-08 08:58:22 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][175/916] eta 0:45:11 lr_first 0.000000122 lr_last 0.000001000 time 3.5353 (3.6591) tot_loss 0.4660 (0.5657) mem 27557MB
[2022-11-08 08:58:59 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][180/916] eta 0:44:53 lr_first 0.000000122 lr_last 0.000001000 time 3.9741 (3.6595) tot_loss 0.4634 (0.5630) mem 27557MB
[2022-11-08 08:59:35 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][185/916] eta 0:44:33 lr_first 0.000000122 lr_last 0.000001000 time 3.5545 (3.6579) tot_loss 0.4745 (0.5673) mem 27557MB
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[2022-11-08 10:23:02 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][880/916] eta 0:02:10 lr_first 0.000000122 lr_last 0.000001000 time 3.5461 (3.6138) tot_loss 0.5332 (0.5879) mem 27557MB
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[2022-11-08 10:24:14 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][890/916] eta 0:01:33 lr_first 0.000000122 lr_last 0.000001000 time 3.5460 (3.6136) tot_loss 0.4890 (0.5872) mem 27557MB
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[2022-11-08 10:25:25 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][900/916] eta 0:00:57 lr_first 0.000000122 lr_last 0.000001000 time 3.6009 (3.6134) tot_loss 0.4643 (0.5903) mem 27557MB
[2022-11-08 10:26:02 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][905/916] eta 0:00:39 lr_first 0.000000122 lr_last 0.000001000 time 3.5189 (3.6136) tot_loss 0.4917 (0.5897) mem 27557MB
[2022-11-08 10:26:38 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][910/916] eta 0:00:21 lr_first 0.000000122 lr_last 0.000001000 time 3.5197 (3.6135) tot_loss 1.2161 (0.5910) mem 27557MB
[2022-11-08 10:27:14 eva-1b/14] (main_k722.py 359): INFO Train: [0/10][915/916] eta 0:00:03 lr_first 0.000000122 lr_last 0.000001000 time 3.5483 (3.6136) tot_loss 0.4742 (0.5904) mem 27557MB
[2022-11-08 10:27:22 eva-1b/14] (main_k722.py 378): INFO EPOCH 0 training takes 1:50:24
[2022-11-08 10:27:22 eva-1b/14] (main_k722.py 398): INFO 4 * 3 views inference
[2022-11-08 10:27:45 eva-1b/14] (main_k722.py 436): INFO Test: [0/78] Acc@1: 100.000 Acc@5: 100.000
[2022-11-08 10:30:40 eva-1b/14] (main_k722.py 436): INFO Test: [10/78] Acc@1: 90.909 Acc@5: 100.000
[2022-11-08 10:33:35 eva-1b/14] (main_k722.py 436): INFO Test: [20/78] Acc@1: 90.476 Acc@5: 97.619
[2022-11-08 10:36:30 eva-1b/14] (main_k722.py 436): INFO Test: [30/78] Acc@1: 87.097 Acc@5: 96.774
[2022-11-08 10:39:25 eva-1b/14] (main_k722.py 436): INFO Test: [40/78] Acc@1: 89.024 Acc@5: 96.341
[2022-11-08 10:42:20 eva-1b/14] (main_k722.py 436): INFO Test: [50/78] Acc@1: 84.314 Acc@5: 96.078
[2022-11-08 10:45:14 eva-1b/14] (main_k722.py 436): INFO Test: [60/78] Acc@1: 85.246 Acc@5: 96.721
[2022-11-08 10:48:09 eva-1b/14] (main_k722.py 436): INFO Test: [70/78] Acc@1: 85.915 Acc@5: 96.479
[2022-11-08 10:50:10 eva-1b/14] (main_k722.py 442): INFO * Acc@1 89.686 Acc@5 98.264
[2022-11-08 10:50:10 eva-1b/14] (main_k722.py 219): INFO Accuracy of the network on (19760) test videos: 89.7% (acc@1) / 98.3% (acc@5)
[2022-11-08 10:50:10 eva-1b/14] (main_k722.py 243): INFO Max accuracy: 89.69%
[2022-11-08 10:50:10 eva-1b/14] (tools.py 57): INFO /home/binhuixie/outputs/cvpr/K722_1b_ft/k400/k722init_allft-1108-01/ckpt_epoch_0.pth saving......
[2022-11-08 10:50:33 eva-1b/14] (tools.py 59): INFO /home/binhuixie/outputs/cvpr/K722_1b_ft/k400/k722init_allft-1108-01/ckpt_epoch_0.pth saved !!!
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