Add best.pt and results to yolo-trained
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best.pt
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train_temp/BoxF1_curve.png
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train_temp/BoxPR_curve.png
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train_temp/BoxP_curve.png
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train_temp/BoxR_curve.png
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train_temp/args.yaml
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task: detect
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mode: train
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model: /home/jovyan/model/leejaewoo/yolo11/yolo11m.pt
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data: data.yaml
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epochs: 20
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time: null
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patience: 100
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batch: 16
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imgsz: 640
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save: true
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save_period: -1
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cache: false
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device: null
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workers: 8
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project: /home/jovyan/model/leejaewoo/yolo11
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name: train_temp
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exist_ok: true
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pretrained: true
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optimizer: auto
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verbose: true
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seed: 0
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deterministic: true
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single_cls: false
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rect: false
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cos_lr: false
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close_mosaic: 10
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resume: false
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amp: true
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fraction: 1.0
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profile: false
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freeze: null
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multi_scale: 0.0
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compile: false
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overlap_mask: true
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mask_ratio: 4
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dropout: 0.0
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val: true
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split: val
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save_json: false
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conf: null
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iou: 0.7
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max_det: 300
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half: false
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dnn: false
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plots: true
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end2end: null
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source: null
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vid_stride: 1
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stream_buffer: false
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visualize: false
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augment: false
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agnostic_nms: false
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classes: null
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retina_masks: false
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embed: null
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show: false
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save_frames: false
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save_txt: false
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save_conf: false
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save_crop: false
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show_labels: true
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show_conf: true
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show_boxes: true
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line_width: null
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format: torchscript
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keras: false
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optimize: false
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int8: false
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dynamic: false
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simplify: true
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opset: null
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workspace: null
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nms: false
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lr0: 0.01
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lrf: 0.01
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momentum: 0.937
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weight_decay: 0.0005
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warmup_epochs: 3.0
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warmup_momentum: 0.8
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warmup_bias_lr: 0.1
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box: 7.5
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cls: 0.5
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dfl: 1.5
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pose: 12.0
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kobj: 1.0
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rle: 1.0
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angle: 1.0
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nbs: 64
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hsv_h: 0.015
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hsv_s: 0.7
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hsv_v: 0.4
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degrees: 0.0
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translate: 0.1
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scale: 0.5
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shear: 0.0
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perspective: 0.0
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flipud: 0.0
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fliplr: 0.5
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bgr: 0.0
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mosaic: 1.0
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mixup: 0.0
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cutmix: 0.0
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copy_paste: 0.0
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copy_paste_mode: flip
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auto_augment: randaugment
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erasing: 0.4
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cfg: null
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tracker: botsort.yaml
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save_dir: /home/jovyan/model/leejaewoo/yolo11/train_temp
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train_temp/confusion_matrix.png
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train_temp/confusion_matrix_normalized.png
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train_temp/labels.jpg
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train_temp/results.csv
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epoch,time,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
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1,1.67206,1.20329,2.63505,1.60228,0.00426,0.33333,0.33801,0.23587,1.68014,2.95409,1.18407,0,0,0
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2,2.49076,1.71571,3.1574,2.06722,0.00432,0.33333,0.33804,0.23588,1.68943,2.93518,1.18411,1.901e-05,1.901e-05,1.901e-05
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3,3.44053,1.28664,2.76427,1.80032,0.00394,0.33333,0.338,0.23586,1.68377,2.92535,1.18199,3.604e-05,3.604e-05,3.604e-05
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4,4.22345,2.02959,2.78247,2.12608,0.00384,0.33333,0.33802,0.23588,1.68336,2.91587,1.18185,5.109e-05,5.109e-05,5.109e-05
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5,5.11071,1.29589,2.4997,1.52708,0.00378,0.33333,0.33801,0.23587,1.62366,2.8887,1.17599,6.416e-05,6.416e-05,6.416e-05
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6,5.89156,1.51277,3.06007,1.79636,0.00367,0.33333,0.3393,0.27007,1.62356,2.88391,1.17534,7.525e-05,7.525e-05,7.525e-05
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7,6.78513,1.16295,2.88673,1.43502,0.00701,0.66667,0.34071,0.27069,1.61951,2.85114,1.17647,8.436e-05,8.436e-05,8.436e-05
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8,7.69055,1.80226,3.3897,2.19002,0.005,1,0.34149,0.27104,1.61407,2.82281,1.17371,9.149e-05,9.149e-05,9.149e-05
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9,8.66732,1.36534,2.83636,1.59469,1,0.92064,0.995,0.66472,1.44301,1.35205,1.08568,9.664e-05,9.664e-05,9.664e-05
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10,10.4185,0.83717,1.591,1.14281,0.97649,1,0.995,0.73056,0.99007,1.32467,0.99136,9.981e-05,9.981e-05,9.981e-05
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11,13.2569,1.13175,2.83905,1.40507,0.96256,1,0.995,0.50029,1.23615,1.68106,1.01363,0.000101,0.000101,0.000101
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12,14.6748,0.61373,2.15461,1.21324,0.96159,1,0.995,0.69789,1.21433,1.15714,0.97342,0.00010021,0.00010021,0.00010021
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13,16.0372,1.13271,2.03106,1.14791,0.9764,0.66667,0.83,0.47642,1.27881,1.4907,1.08621,9.744e-05,9.744e-05,9.744e-05
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14,17.3915,1.0798,2.2862,1.60101,0.74727,0.98909,0.83,0.61522,1.12672,1.55495,1.0186,9.269e-05,9.269e-05,9.269e-05
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15,18.7863,0.69968,1.19794,1.06678,0.66158,0.66667,0.56147,0.50237,1.08498,1.72119,1.02719,8.596e-05,8.596e-05,8.596e-05
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16,20.142,0.58534,1.12073,0.99467,0.66516,0.66366,0.44389,0.32753,1.57405,2.30618,1.12398,7.725e-05,7.725e-05,7.725e-05
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17,21.4689,0.62205,0.87617,0.97014,0.66389,0.66112,0.55556,0.36689,1.89155,2.11945,1.19579,6.656e-05,6.656e-05,6.656e-05
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18,22.8171,0.53723,0.9658,0.69231,0.66389,0.66112,0.55556,0.36689,1.89155,2.11945,1.19579,5.389e-05,5.389e-05,5.389e-05
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19,24.237,0.70819,0.95772,1.17249,0.66353,0.66039,0.56738,0.36925,1.6714,1.91917,1.13025,3.924e-05,3.924e-05,3.924e-05
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20,25.5601,0.67334,0.98455,0.87524,0.66353,0.66039,0.56738,0.36925,1.6714,1.91917,1.13025,2.261e-05,2.261e-05,2.261e-05
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train_temp/results.png
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train_temp/train_batch0.jpg
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train_temp/train_batch1.jpg
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train_temp/train_batch10.jpg
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train_temp/train_batch11.jpg
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train_temp/train_batch12.jpg
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train_temp/train_batch2.jpg
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train_temp/val_batch0_labels.jpg
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train_temp/val_batch0_pred.jpg
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