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Browse files- best.pt +3 -0
- events.out.tfevents.1728535715.93c1ca2ff9c3.30.0 +3 -0
- results.csv +31 -0
- results.png +0 -0
- sample_prediction/train_batch0.jpg +0 -0
- sample_prediction/train_batch1.jpg +0 -0
- sample_prediction/train_batch2.jpg +0 -0
- sample_prediction/train_batch5520.jpg +0 -0
- sample_prediction/train_batch5521.jpg +0 -0
- sample_prediction/train_batch5522.jpg +0 -0
- sample_prediction/val_batch0_labels.jpg +0 -0
- sample_prediction/val_batch0_pred.jpg +0 -0
- sample_prediction/val_batch1_labels.jpg +0 -0
- sample_prediction/val_batch1_pred.jpg +0 -0
- sample_prediction/val_batch2_labels.jpg +0 -0
- sample_prediction/val_batch2_pred.jpg +0 -0
best.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:b54849bf811af7c9043b6ec1331e16649757e908cf1610e2b6f5e352f7c3475e
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size 51326162
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events.out.tfevents.1728535715.93c1ca2ff9c3.30.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:b99674260484ff749250d690af572724fd3704b7d7f69cc114e67fb8995683a7
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size 552471
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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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1,382.136,1.15824,1.48844,1.47801,0.43577,0.08711,0.06213,0.0309,1.62344,3.22756,2.05582,0.0668207,3.32126e-05,3.32126e-05
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2,753.578,1.02052,0.99416,1.35343,0.55331,0.16745,0.13821,0.07395,1.55998,2.41145,2.0592,0.0335205,6.63654e-05,6.63654e-05
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3,1123.69,0.91639,0.87374,1.30297,0.61052,0.20887,0.19124,0.10163,1.52959,2.26447,2.02061,0.000219572,9.87988e-05,9.87988e-05
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4,1493.64,0.82825,0.78525,1.21782,0.5133,0.27068,0.2396,0.12957,1.51489,1.99057,1.95714,9.75773e-05,9.75773e-05,9.75773e-05
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5,1863.4,0.76282,0.71169,1.17988,0.48481,0.30518,0.28651,0.16257,1.47343,1.82348,1.88977,9.57205e-05,9.57205e-05,9.57205e-05
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6,2233.81,0.71368,0.66645,1.15727,0.55264,0.33728,0.30438,0.1712,1.49252,1.74973,1.89747,9.33683e-05,9.33683e-05,9.33683e-05
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7,2603.83,0.68403,0.63754,1.132,0.53782,0.36613,0.34621,0.1982,1.45296,1.64166,1.87148,9.05463e-05,9.05463e-05,9.05463e-05
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8,2973.87,0.65017,0.60295,1.11511,0.48743,0.35802,0.37814,0.21755,1.44564,1.55575,1.85476,8.72857e-05,8.72857e-05,8.72857e-05
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9,3344.08,0.61701,0.57505,1.0969,0.49594,0.38929,0.37987,0.21929,1.43122,1.51338,1.8272,8.3622e-05,8.3622e-05,8.3622e-05
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10,3713.96,0.59644,0.55391,1.0871,0.5328,0.3886,0.39485,0.23121,1.42706,1.4898,1.82444,7.95954e-05,7.95954e-05,7.95954e-05
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11,4084.69,0.57919,0.53644,1.08317,0.43635,0.44579,0.40598,0.23414,1.44523,1.45023,1.85047,7.525e-05,7.525e-05,7.525e-05
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12,4454.85,0.57012,0.52444,1.07785,0.42351,0.46724,0.42506,0.24461,1.44038,1.46838,1.8305,7.06335e-05,7.06335e-05,7.06335e-05
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13,4825.29,0.54448,0.50908,1.06167,0.49486,0.45468,0.44849,0.26397,1.42419,1.39854,1.81855,6.57963e-05,6.57963e-05,6.57963e-05
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14,5195.95,0.53579,0.49575,1.05715,0.46647,0.47685,0.45152,0.26419,1.42873,1.35885,1.81516,6.07916e-05,6.07916e-05,6.07916e-05
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15,5565.89,0.51705,0.47849,1.04611,0.47263,0.48582,0.47983,0.28712,1.40781,1.32987,1.79124,5.56742e-05,5.56742e-05,5.56742e-05
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19,7050.46,0.47655,0.43352,1.02356,0.47089,0.51338,0.50921,0.31305,1.37287,1.27737,1.77513,3.52037e-05,3.52037e-05,3.52037e-05
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20,7422.19,0.46463,0.42424,1.02121,0.42275,0.56677,0.51242,0.31458,1.36598,1.24903,1.75969,3.03665e-05,3.03665e-05,3.03665e-05
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21,7796.96,1.20663,1.19886,1.59749,0.52719,0.50566,0.54318,0.34284,1.33113,1.1853,1.70371,2.575e-05,2.575e-05,2.575e-05
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22,8169.5,1.16363,1.08061,1.5485,0.43723,0.59453,0.56069,0.35689,1.32467,1.15609,1.69552,2.14046e-05,2.14046e-05,2.14046e-05
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23,8541.9,1.13645,1.02524,1.52529,0.48961,0.57122,0.562,0.35362,1.32656,1.13813,1.69646,1.7378e-05,1.7378e-05,1.7378e-05
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24,8913.69,1.1183,0.98618,1.50787,0.53398,0.52698,0.56411,0.36052,1.32332,1.14367,1.69944,1.37143e-05,1.37143e-05,1.37143e-05
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25,9285.33,1.10306,0.95662,1.49651,0.46649,0.60175,0.59544,0.38282,1.31661,1.12457,1.69129,1.04537e-05,1.04537e-05,1.04537e-05
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26,9657.13,1.0922,0.93032,1.49152,0.53433,0.55851,0.58999,0.37547,1.31602,1.11906,1.68999,7.63174e-06,7.63174e-06,7.63174e-06
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27,10029,1.08089,0.91507,1.48199,0.49053,0.58267,0.58717,0.37463,1.31547,1.1236,1.69279,5.2795e-06,5.2795e-06,5.2795e-06
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28,10401.3,1.07127,0.8988,1.47205,0.50563,0.57613,0.58578,0.37577,1.31619,1.12215,1.6936,3.4227e-06,3.4227e-06,3.4227e-06
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29,10773.5,1.06519,0.88931,1.46905,0.51747,0.57143,0.58698,0.37679,1.31432,1.1221,1.69278,2.08169e-06,2.08169e-06,2.08169e-06
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30,11145.3,1.06167,0.88254,1.4691,0.51678,0.57249,0.59638,0.38515,1.31275,1.11663,1.6927,1.27117e-06,1.27117e-06,1.27117e-06
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results.png
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sample_prediction/train_batch0.jpg
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sample_prediction/train_batch1.jpg
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sample_prediction/train_batch2.jpg
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sample_prediction/train_batch5520.jpg
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sample_prediction/train_batch5521.jpg
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sample_prediction/train_batch5522.jpg
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sample_prediction/val_batch0_labels.jpg
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sample_prediction/val_batch0_pred.jpg
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sample_prediction/val_batch1_labels.jpg
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sample_prediction/val_batch1_pred.jpg
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sample_prediction/val_batch2_labels.jpg
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sample_prediction/val_batch2_pred.jpg
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