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500 epochs runs
  • Loading branch information
meruna-yugarajah committed Jan 21, 2026
commit df029892e6d1d7b65a1f2e26dbac38fd7b73a74e
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Original file line number Diff line number Diff line change
@@ -0,0 +1,105 @@
task: segment
mode: train
model: /workspace/src/arlab/code/arlab_computer_vision/arlab_computer_vision/training/yolo_weights/yolo11n-seg.pt
data: /workspace/src/arlab/code/arlab_computer_vision/arlab_computer_vision/trainingYCB/dataset/data.yaml
epochs: 500
time: null
patience: 30
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: null
name: baseline
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
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: true
opset: null
workspace: null
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
nbs: 64
hsv_h: 0.03
hsv_s: 0.6
hsv_v: 0.5
degrees: 0.0
translate: 0.1
scale: 0.1
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: runs/segment/baseline

Large diffs are not rendered by default.

Original file line number Diff line number Diff line change
@@ -0,0 +1,105 @@
task: segment
mode: train
model: /workspace/src/arlab/code/arlab_computer_vision/arlab_computer_vision/training/yolo_weights/yolo11n-seg.pt
data: /workspace/src/arlab/code/arlab_computer_vision/arlab_computer_vision/trainingYCB/dataset/data.yaml
epochs: 500
time: null
patience: 30
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: null
name: moderate_geom
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
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: true
opset: null
workspace: null
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
nbs: 64
hsv_h: 0.02
hsv_s: 0.4
hsv_v: 0.4
degrees: 10.0
translate: 0.15
scale: 0.2
shear: 0.0
perspective: 0.0
flipud: 0.1
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: runs/segment/moderate_geom
Original file line number Diff line number Diff line change
@@ -0,0 +1,89 @@
epoch,time,train/box_loss,train/seg_loss,train/cls_loss,train/dfl_loss,metrics/precision(B),metrics/recall(B),metrics/mAP50(B),metrics/mAP50-95(B),metrics/precision(M),metrics/recall(M),metrics/mAP50(M),metrics/mAP50-95(M),val/box_loss,val/seg_loss,val/cls_loss,val/dfl_loss,lr/pg0,lr/pg1,lr/pg2
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43,27378.3,0.53806,1.05157,0.44507,0.82967,0.95518,0.76081,0.79986,0.7683,0.93494,0.75525,0.79344,0.69537,0.38145,0.74528,0.27737,0.78907,0.0091684,0.0091684,0.0091684
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47,29917.7,0.53352,1.03913,0.44059,0.83025,0.95546,0.76161,0.80041,0.76935,0.93416,0.75603,0.79378,0.69584,0.3764,0.7383,0.27342,0.78821,0.0090892,0.0090892,0.0090892
48,30552.9,0.53351,1.03624,0.44114,0.82959,0.95605,0.76177,0.80044,0.76926,0.93281,0.75632,0.79374,0.69599,0.37559,0.737,0.273,0.78814,0.0090694,0.0090694,0.0090694
49,31188.2,0.53333,1.04145,0.43955,0.82905,0.9526,0.76247,0.80035,0.76928,0.93351,0.75623,0.79369,0.69593,0.375,0.73578,0.2722,0.78802,0.0090496,0.0090496,0.0090496
50,31823.3,0.53015,1.03493,0.43804,0.82851,0.95232,0.76262,0.8005,0.76959,0.93257,0.75615,0.79354,0.69579,0.37439,0.73457,0.27119,0.78798,0.0090298,0.0090298,0.0090298
51,32458.7,0.53097,1.03781,0.43856,0.82908,0.95278,0.76259,0.80047,0.76965,0.93339,0.75615,0.79367,0.6957,0.37381,0.7335,0.27044,0.78784,0.00901,0.00901,0.00901
52,33092.9,0.52799,1.03176,0.4343,0.82864,0.95286,0.7628,0.80083,0.77006,0.93282,0.75639,0.79392,0.6961,0.37319,0.73203,0.26951,0.78765,0.0089902,0.0089902,0.0089902
53,33727.8,0.52918,1.03751,0.43415,0.82881,0.95237,0.76296,0.80112,0.77054,0.93198,0.75644,0.79392,0.69629,0.37235,0.73105,0.26869,0.78753,0.0089704,0.0089704,0.0089704
54,34363.9,0.52957,1.03366,0.43611,0.82849,0.95195,0.7633,0.80142,0.77077,0.93177,0.75691,0.79435,0.69654,0.37143,0.72945,0.26801,0.78733,0.0089506,0.0089506,0.0089506
55,34999.5,0.52668,1.02729,0.43369,0.82784,0.95078,0.76366,0.80153,0.77087,0.9318,0.75713,0.79434,0.69681,0.37052,0.72797,0.26795,0.78722,0.0089308,0.0089308,0.0089308
56,35634.4,0.52823,1.03292,0.43419,0.8285,0.9505,0.76374,0.80157,0.77088,0.93171,0.75697,0.79435,0.69663,0.36965,0.72703,0.26873,0.78712,0.008911,0.008911,0.008911
57,36269.9,0.52954,1.03788,0.43673,0.82915,0.95065,0.76385,0.80146,0.77082,0.93016,0.75719,0.79405,0.69642,0.36907,0.72577,0.26939,0.787,0.0088912,0.0088912,0.0088912
58,36905,0.52458,1.03026,0.4298,0.82734,0.94915,0.76409,0.80177,0.7712,0.93026,0.75738,0.79452,0.69683,0.36834,0.72466,0.26806,0.78685,0.0088714,0.0088714,0.0088714
59,37540.6,0.52377,1.02282,0.43093,0.82729,0.94916,0.76403,0.80185,0.77112,0.92954,0.75724,0.79433,0.6967,0.36788,0.72323,0.26628,0.78678,0.0088516,0.0088516,0.0088516
60,38174.9,0.52427,1.02843,0.42997,0.82735,0.9479,0.76436,0.80176,0.77094,0.93024,0.75751,0.79462,0.6967,0.36745,0.72194,0.26472,0.78668,0.0088318,0.0088318,0.0088318
61,38809.6,0.52228,1.02075,0.42873,0.82729,0.94699,0.76457,0.80182,0.77111,0.9293,0.75777,0.79478,0.69688,0.36682,0.72085,0.26336,0.78658,0.008812,0.008812,0.008812
62,39444.1,0.52482,1.03149,0.43161,0.82723,0.94772,0.76458,0.80188,0.77121,0.93037,0.75778,0.79469,0.69655,0.36616,0.71998,0.26207,0.7865,0.0087922,0.0087922,0.0087922
63,40079.4,0.5244,1.03429,0.43094,0.82791,0.94772,0.7646,0.80192,0.77133,0.93075,0.75786,0.79471,0.6966,0.36555,0.71861,0.26113,0.78641,0.0087724,0.0087724,0.0087724
64,40713.9,0.52544,1.03076,0.43169,0.828,0.9484,0.76454,0.80171,0.7712,0.93227,0.7576,0.7945,0.69636,0.36487,0.7179,0.26015,0.7864,0.0087526,0.0087526,0.0087526
65,41349.8,0.52249,1.0215,0.42924,0.82719,0.94881,0.76456,0.80163,0.77112,0.93244,0.75755,0.79448,0.69616,0.36386,0.71694,0.2593,0.78622,0.0087328,0.0087328,0.0087328
66,41985.4,0.52122,1.02364,0.42794,0.82764,0.94874,0.76451,0.80124,0.7708,0.93167,0.75759,0.79403,0.69565,0.36323,0.7161,0.25862,0.7861,0.008713,0.008713,0.008713
67,42620.6,0.52224,1.02532,0.42863,0.82698,0.94817,0.7649,0.80116,0.77066,0.93162,0.75761,0.79391,0.69555,0.3625,0.71498,0.25797,0.78597,0.0086932,0.0086932,0.0086932
68,43256.9,0.51907,1.02161,0.42572,0.82667,0.94852,0.76485,0.80107,0.77054,0.93128,0.75771,0.79375,0.69521,0.362,0.71417,0.25754,0.78585,0.0086734,0.0086734,0.0086734
69,43891.2,0.52212,1.02593,0.4305,0.82784,0.94746,0.76532,0.80126,0.77075,0.92997,0.75797,0.79366,0.69513,0.36136,0.71338,0.25694,0.78577,0.0086536,0.0086536,0.0086536
70,44525.7,0.51754,1.01811,0.42736,0.82645,0.94781,0.76524,0.80121,0.77068,0.93072,0.7578,0.79363,0.69499,0.3609,0.71272,0.25642,0.78575,0.0086338,0.0086338,0.0086338
71,45161.3,0.5179,1.02392,0.42463,0.82603,0.94766,0.76538,0.80137,0.77087,0.93028,0.75761,0.79343,0.69495,0.36042,0.71188,0.25593,0.7857,0.008614,0.008614,0.008614
72,45796.7,0.51866,1.02186,0.42384,0.8249,0.94731,0.76565,0.80159,0.77126,0.92999,0.75784,0.79379,0.69537,0.35989,0.71099,0.25603,0.78556,0.0085942,0.0085942,0.0085942
73,46432,0.51588,1.01947,0.42307,0.82568,0.94714,0.76556,0.80174,0.77163,0.9292,0.75815,0.7942,0.69547,0.35942,0.71014,0.25655,0.78549,0.0085744,0.0085744,0.0085744
74,47067.8,0.51625,1.02442,0.42396,0.82536,0.94684,0.76579,0.80164,0.77142,0.92856,0.75847,0.79407,0.69503,0.35903,0.70954,0.25733,0.78538,0.0085546,0.0085546,0.0085546
75,47703.1,0.51656,1.02209,0.42278,0.82512,0.94747,0.76579,0.80174,0.77131,0.92855,0.75844,0.79389,0.69481,0.35877,0.70898,0.25872,0.78528,0.0085348,0.0085348,0.0085348
76,48337.7,0.51305,1.0131,0.42044,0.82507,0.94817,0.76568,0.80185,0.77147,0.9288,0.75859,0.79421,0.69477,0.35791,0.70852,0.26075,0.78506,0.008515,0.008515,0.008515
77,48974,0.5155,1.02012,0.42288,0.8252,0.94812,0.76593,0.80188,0.77135,0.92852,0.75871,0.79415,0.69468,0.35718,0.70819,0.26341,0.7848,0.0084952,0.0084952,0.0084952
78,49609.7,0.5131,1.01549,0.41842,0.82475,0.94193,0.7651,0.80185,0.7714,0.92046,0.75849,0.7941,0.69463,0.35623,0.70737,0.26446,0.78452,0.0084754,0.0084754,0.0084754
79,50245.9,0.51208,1.0109,0.41926,0.8246,0.9435,0.76676,0.80207,0.77154,0.92514,0.75936,0.79441,0.6947,0.35555,0.70653,0.26241,0.78435,0.0084556,0.0084556,0.0084556
80,50881.2,0.51218,1.01533,0.41962,0.82472,0.94919,0.7659,0.80211,0.77151,0.9306,0.75825,0.79423,0.6946,0.35544,0.70584,0.26031,0.78429,0.0084358,0.0084358,0.0084358
81,51517.3,0.51156,1.01554,0.41979,0.82437,0.94996,0.76595,0.80216,0.77161,0.93007,0.75844,0.79445,0.69478,0.35491,0.70504,0.25872,0.78417,0.008416,0.008416,0.008416
82,52153.7,0.5122,1.01736,0.41805,0.82417,0.95014,0.76589,0.80224,0.77178,0.9307,0.75822,0.79421,0.69472,0.35451,0.70425,0.25771,0.78407,0.0083962,0.0083962,0.0083962
83,52789.6,0.511,1.0101,0.41714,0.82439,0.94881,0.76607,0.80232,0.77195,0.93073,0.75831,0.79416,0.69495,0.35365,0.70346,0.25604,0.784,0.0083764,0.0083764,0.0083764
84,53425.9,0.51221,1.0157,0.41818,0.82476,0.94926,0.76629,0.80262,0.77219,0.93104,0.75828,0.79418,0.6953,0.35345,0.70261,0.25464,0.78396,0.0083566,0.0083566,0.0083566
85,54061.7,0.51159,1.0164,0.41586,0.82476,0.9496,0.76635,0.80269,0.77221,0.93131,0.75833,0.79442,0.69535,0.35305,0.70208,0.25293,0.78401,0.0083368,0.0083368,0.0083368
86,54698,0.5104,1.01376,0.41612,0.82499,0.95089,0.766,0.80276,0.77234,0.9304,0.75867,0.79441,0.69541,0.35241,0.70112,0.25183,0.78402,0.008317,0.008317,0.008317
87,55333.9,0.50852,1.01042,0.41583,0.82426,0.94989,0.7664,0.80276,0.7723,0.93025,0.7587,0.79437,0.69563,0.35199,0.70093,0.25077,0.78393,0.0082972,0.0082972,0.0082972
88,55968.9,0.50978,1.01265,0.41545,0.82516,0.9497,0.76662,0.80263,0.77227,0.92908,0.75876,0.79417,0.69545,0.35141,0.70047,0.24994,0.78384,0.0082774,0.0082774,0.0082774
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