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 results.csv

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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
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1, 0.90423, 3.3216, 1.3802, 0.92221, 0.05407, 0.14767, 0.11301, 0.83409, 3.8852, 1.3505, 0.00023367, 0.00023367, 0.00023367
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2, 0.90117, 2.5725, 1.4059, 0.68385, 0.19431, 0.17301, 0.11562, 1.0658, 3.4699, 1.6392, 0.0004133, 0.0004133, 0.0004133
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3, 0.92167, 2.3286, 1.3986, 0.59534, 0.17825, 0.17458, 0.12628, 1.0146, 3.2687, 1.5477, 0.00053403, 0.00053403, 0.00053403
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4, 0.92607, 2.2327, 1.3982, 0.68164, 0.20237, 0.23913, 0.17542, 0.88674, 2.6142, 1.3688, 0.00044893, 0.00044893, 0.00044893
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5, 0.8854, 2.063, 1.3547, 0.33178, 0.32252, 0.27037, 0.19785, 0.8801, 2.5789, 1.3452, 0.00036057, 0.00036057, 0.00036057
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6, 0.80498, 1.9081, 1.3098, 0.43014, 0.32835, 0.29925, 0.21855, 0.87377, 2.3285, 1.3348, 0.00027221, 0.00027221, 0.00027221
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7, 0.81098, 1.8558, 1.3211, 0.46645, 0.34425, 0.33164, 0.25541, 0.73, 2.1602, 1.2014, 0.00018385, 0.00018385, 0.00018385
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8, 0.74259, 1.7301, 1.2668, 0.3049, 0.40168, 0.37117, 0.29191, 0.68279, 1.9705, 1.1528, 9.5498e-05, 9.5498e-05, 9.5498e-05
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