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MVP with Tensorboard

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IDONTSUDO 2024-12-01 16:12:08 +00:00 • committed by Igor Brylev
parent 5b9b51ad59
commit a0d089d5bb
549 changed files with 39977 additions and 31449 deletions
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task: detect
mode: train
model: /home/shalenikol/fork_work/webservice/server/build/public/4c4f3909-74b0-4206-aec1-fc4acd3a1081/weights/od_w01/yolov8n.pt
data: /home/shalenikol/fork_work/webservice/server/build/public/4c4f3909-74b0-4206-aec1-fc4acd3a1081/weights/od_w01/rbs_train.yaml
epochs: 33
time: null
patience: 50
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: null
workers: 8
project: /home/shalenikol/fork_work/webservice/server/build/public/4c4f3909-74b0-4206-aec1-fc4acd3a1081/weights/od_w01
name: train
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
save_hybrid: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: false
opset: null
workspace: 4
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
label_smoothing: 0.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
mosaic: 1.0
mixup: 0.0
copy_paste: 0.0
auto_augment: randaugment
erasing: 0.4
crop_fraction: 1.0
cfg: null
tracker: botsort.yaml
save_dir: /home/shalenikol/fork_work/webservice/server/build/public/4c4f3909-74b0-4206-aec1-fc4acd3a1081/weights/od_w01/train

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epoch, train/box_loss, train/cls_loss, train/dfl_loss, metrics/precision(B), metrics/recall(B), metrics/mAP50(B), metrics/mAP50-95(B), val/box_loss, val/cls_loss, val/dfl_loss, lr/pg0, lr/pg1, lr/pg2
1, 0.62674, 1.281, 0.92555, 0.99239, 0.99448, 0.99323, 0.90966, 0.40212, 0.8264, 0.80447, 0.00066247, 0.00066247, 0.00066247
2, 0.60996, 0.71899, 0.93387, 0.9945, 0.99945, 0.99484, 0.91551, 0.43253, 0.60301, 0.8228, 0.0012893, 0.0012893, 0.0012893
3, 0.58648, 0.54879, 0.92909, 1, 0.98871, 0.99494, 0.9213, 0.40211, 0.39327, 0.81593, 0.0018761, 0.0018761, 0.0018761
4, 0.58195, 0.48301, 0.92375, 0.99087, 0.9337, 0.97172, 0.89393, 0.41614, 0.46785, 0.82069, 0.00182, 0.00182, 0.00182
5, 0.56201, 0.44926, 0.92381, 0.99447, 0.99385, 0.99494, 0.94951, 0.34807, 0.32406, 0.8013, 0.00182, 0.00182, 0.00182
6, 0.52696, 0.40581, 0.9068, 0.95813, 0.98343, 0.99281, 0.94494, 0.33023, 0.48053, 0.79401, 0.00176, 0.00176, 0.00176
7, 0.51017, 0.3952, 0.90752, 0.99889, 1, 0.995, 0.95388, 0.3192, 0.33973, 0.7992, 0.0017, 0.0017, 0.0017
8, 0.50772, 0.37889, 0.90238, 0.98351, 0.98842, 0.98581, 0.94918, 0.30154, 0.28504, 0.79667, 0.00164, 0.00164, 0.00164
9, 0.47737, 0.3576, 0.89251, 0.99946, 0.99448, 0.995, 0.97205, 0.28135, 0.23642, 0.79101, 0.00158, 0.00158, 0.00158
10, 0.46587, 0.34547, 0.89324, 0.99948, 1, 0.995, 0.96897, 0.28021, 0.28522, 0.78694, 0.00152, 0.00152, 0.00152
11, 0.45881, 0.33452, 0.89055, 0.99954, 1, 0.995, 0.97012, 0.26364, 0.21443, 0.7813, 0.00146, 0.00146, 0.00146
12, 0.44939, 0.32887, 0.89206, 0.9996, 1, 0.995, 0.98382, 0.24486, 0.20614, 0.78109, 0.0014, 0.0014, 0.0014
13, 0.44388, 0.32289, 0.88796, 0.99932, 1, 0.995, 0.97195, 0.27681, 0.21443, 0.77933, 0.00134, 0.00134, 0.00134
14, 0.43847, 0.31282, 0.88496, 0.99965, 1, 0.995, 0.98019, 0.25014, 0.20255, 0.7775, 0.00128, 0.00128, 0.00128
15, 0.41585, 0.30067, 0.8774, 0.99943, 1, 0.995, 0.97609, 0.25842, 0.21239, 0.78006, 0.00122, 0.00122, 0.00122
16, 0.41436, 0.29784, 0.87488, 0.99964, 1, 0.995, 0.97823, 0.25499, 0.19837, 0.78004, 0.00116, 0.00116, 0.00116
17, 0.414, 0.29771, 0.87575, 0.99943, 1, 0.995, 0.98746, 0.2251, 0.203, 0.77468, 0.0011, 0.0011, 0.0011
18, 0.39273, 0.29075, 0.86927, 0.99445, 1, 0.995, 0.98597, 0.22693, 0.19648, 0.77208, 0.00104, 0.00104, 0.00104
19, 0.40052, 0.28802, 0.87804, 0.99958, 1, 0.995, 0.98541, 0.22268, 0.18749, 0.77233, 0.00098, 0.00098, 0.00098
20, 0.38066, 0.27951, 0.86666, 0.99969, 1, 0.995, 0.98901, 0.20959, 0.1775, 0.7697, 0.00092, 0.00092, 0.00092
21, 0.38115, 0.27813, 0.8658, 0.99964, 1, 0.995, 0.98895, 0.20699, 0.1779, 0.77073, 0.00086, 0.00086, 0.00086
22, 0.37441, 0.27094, 0.87121, 0.99965, 1, 0.995, 0.98975, 0.20138, 0.17235, 0.76785, 0.0008, 0.0008, 0.0008
23, 0.36808, 0.26148, 0.86426, 0.99965, 1, 0.995, 0.98829, 0.19861, 0.1628, 0.76706, 0.00074, 0.00074, 0.00074
24, 0.25547, 0.199, 0.77555, 0.99955, 1, 0.995, 0.98791, 0.21853, 0.18063, 0.76972, 0.00068, 0.00068, 0.00068
25, 0.24799, 0.1969, 0.78404, 0.99958, 1, 0.995, 0.98812, 0.23069, 0.18178, 0.76985, 0.00062, 0.00062, 0.00062
26, 0.24232, 0.1915, 0.78022, 0.99968, 1, 0.995, 0.99024, 0.20883, 0.16788, 0.76752, 0.00056, 0.00056, 0.00056
27, 0.23288, 0.1839, 0.77463, 0.99968, 1, 0.995, 0.99151, 0.2026, 0.16501, 0.76809, 0.0005, 0.0005, 0.0005
28, 0.23066, 0.18012, 0.77547, 0.99961, 1, 0.995, 0.98912, 0.19388, 0.1534, 0.76246, 0.00044, 0.00044, 0.00044
29, 0.22286, 0.17062, 0.77932, 0.9997, 1, 0.995, 0.99039, 0.20566, 0.14978, 0.76601, 0.00038, 0.00038, 0.00038
30, 0.21427, 0.16357, 0.77529, 0.9997, 1, 0.995, 0.99215, 0.18345, 0.14148, 0.76206, 0.00032, 0.00032, 0.00032
31, 0.20895, 0.16067, 0.77189, 0.9997, 1, 0.995, 0.99187, 0.17027, 0.13746, 0.76124, 0.00026, 0.00026, 0.00026
32, 0.20248, 0.15421, 0.77526, 0.9997, 1, 0.995, 0.99246, 0.17229, 0.13828, 0.76056, 0.0002, 0.0002, 0.0002
33, 0.19494, 0.15005, 0.76361, 0.99971, 1, 0.995, 0.99302, 0.16442, 0.12543, 0.76043, 0.00014, 0.00014, 0.00014
1 epoch train/box_loss train/cls_loss train/dfl_loss metrics/precision(B) metrics/recall(B) metrics/mAP50(B) metrics/mAP50-95(B) val/box_loss val/cls_loss val/dfl_loss lr/pg0 lr/pg1 lr/pg2
2 1 0.62674 1.281 0.92555 0.99239 0.99448 0.99323 0.90966 0.40212 0.8264 0.80447 0.00066247 0.00066247 0.00066247
3 2 0.60996 0.71899 0.93387 0.9945 0.99945 0.99484 0.91551 0.43253 0.60301 0.8228 0.0012893 0.0012893 0.0012893
4 3 0.58648 0.54879 0.92909 1 0.98871 0.99494 0.9213 0.40211 0.39327 0.81593 0.0018761 0.0018761 0.0018761
5 4 0.58195 0.48301 0.92375 0.99087 0.9337 0.97172 0.89393 0.41614 0.46785 0.82069 0.00182 0.00182 0.00182
6 5 0.56201 0.44926 0.92381 0.99447 0.99385 0.99494 0.94951 0.34807 0.32406 0.8013 0.00182 0.00182 0.00182
7 6 0.52696 0.40581 0.9068 0.95813 0.98343 0.99281 0.94494 0.33023 0.48053 0.79401 0.00176 0.00176 0.00176
8 7 0.51017 0.3952 0.90752 0.99889 1 0.995 0.95388 0.3192 0.33973 0.7992 0.0017 0.0017 0.0017
9 8 0.50772 0.37889 0.90238 0.98351 0.98842 0.98581 0.94918 0.30154 0.28504 0.79667 0.00164 0.00164 0.00164
10 9 0.47737 0.3576 0.89251 0.99946 0.99448 0.995 0.97205 0.28135 0.23642 0.79101 0.00158 0.00158 0.00158
11 10 0.46587 0.34547 0.89324 0.99948 1 0.995 0.96897 0.28021 0.28522 0.78694 0.00152 0.00152 0.00152
12 11 0.45881 0.33452 0.89055 0.99954 1 0.995 0.97012 0.26364 0.21443 0.7813 0.00146 0.00146 0.00146
13 12 0.44939 0.32887 0.89206 0.9996 1 0.995 0.98382 0.24486 0.20614 0.78109 0.0014 0.0014 0.0014
14 13 0.44388 0.32289 0.88796 0.99932 1 0.995 0.97195 0.27681 0.21443 0.77933 0.00134 0.00134 0.00134
15 14 0.43847 0.31282 0.88496 0.99965 1 0.995 0.98019 0.25014 0.20255 0.7775 0.00128 0.00128 0.00128
16 15 0.41585 0.30067 0.8774 0.99943 1 0.995 0.97609 0.25842 0.21239 0.78006 0.00122 0.00122 0.00122
17 16 0.41436 0.29784 0.87488 0.99964 1 0.995 0.97823 0.25499 0.19837 0.78004 0.00116 0.00116 0.00116
18 17 0.414 0.29771 0.87575 0.99943 1 0.995 0.98746 0.2251 0.203 0.77468 0.0011 0.0011 0.0011
19 18 0.39273 0.29075 0.86927 0.99445 1 0.995 0.98597 0.22693 0.19648 0.77208 0.00104 0.00104 0.00104
20 19 0.40052 0.28802 0.87804 0.99958 1 0.995 0.98541 0.22268 0.18749 0.77233 0.00098 0.00098 0.00098
21 20 0.38066 0.27951 0.86666 0.99969 1 0.995 0.98901 0.20959 0.1775 0.7697 0.00092 0.00092 0.00092
22 21 0.38115 0.27813 0.8658 0.99964 1 0.995 0.98895 0.20699 0.1779 0.77073 0.00086 0.00086 0.00086
23 22 0.37441 0.27094 0.87121 0.99965 1 0.995 0.98975 0.20138 0.17235 0.76785 0.0008 0.0008 0.0008
24 23 0.36808 0.26148 0.86426 0.99965 1 0.995 0.98829 0.19861 0.1628 0.76706 0.00074 0.00074 0.00074
25 24 0.25547 0.199 0.77555 0.99955 1 0.995 0.98791 0.21853 0.18063 0.76972 0.00068 0.00068 0.00068
26 25 0.24799 0.1969 0.78404 0.99958 1 0.995 0.98812 0.23069 0.18178 0.76985 0.00062 0.00062 0.00062
27 26 0.24232 0.1915 0.78022 0.99968 1 0.995 0.99024 0.20883 0.16788 0.76752 0.00056 0.00056 0.00056
28 27 0.23288 0.1839 0.77463 0.99968 1 0.995 0.99151 0.2026 0.16501 0.76809 0.0005 0.0005 0.0005
29 28 0.23066 0.18012 0.77547 0.99961 1 0.995 0.98912 0.19388 0.1534 0.76246 0.00044 0.00044 0.00044
30 29 0.22286 0.17062 0.77932 0.9997 1 0.995 0.99039 0.20566 0.14978 0.76601 0.00038 0.00038 0.00038
31 30 0.21427 0.16357 0.77529 0.9997 1 0.995 0.99215 0.18345 0.14148 0.76206 0.00032 0.00032 0.00032
32 31 0.20895 0.16067 0.77189 0.9997 1 0.995 0.99187 0.17027 0.13746 0.76124 0.00026 0.00026 0.00026
33 32 0.20248 0.15421 0.77526 0.9997 1 0.995 0.99246 0.17229 0.13828 0.76056 0.0002 0.0002 0.0002
34 33 0.19494 0.15005 0.76361 0.99971 1 0.995 0.99302 0.16442 0.12543 0.76043 0.00014 0.00014 0.00014

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