epoch, train/box_loss, train/cls_loss, train/dfl_loss, metrics/precision, metrics/recall, metrics/mAP_0.5,metrics/mAP_0.5:0.95, val/box_loss, val/cls_loss, val/dfl_loss, x/lr0, x/lr1, x/lr2 0, 2.5634, 2.502, 1.8226, 0.64906, 0.56085, 0.60864, 0.28348, 1.7915, 1.4259, 1.4801, 0.070213, 0.0033097, 0.0033097 1, 2.1689, 1.7402, 1.4855, 0.68457, 0.53701, 0.61222, 0.2912, 1.8191, 1.8341, 1.4462, 0.039555, 0.0059854, 0.0059854 2, 2.1419, 1.6757, 1.4529, 0.65502, 0.61702, 0.64527, 0.29307, 1.8275, 1.3895, 1.3894, 0.0082374, 0.008001, 0.008001 3, 2.132, 1.6826, 1.421, 0.70865, 0.61341, 0.67064, 0.30331, 1.854, 1.3796, 1.4102, 0.00703, 0.00703, 0.00703 4, 2.1047, 1.6321, 1.4184, 0.64815, 0.62233, 0.66508, 0.28499, 1.9095, 1.3856, 1.45, 0.00703, 0.00703, 0.00703 5, 2.0873, 1.6013, 1.4144, 0.68189, 0.65245, 0.68849, 0.31198, 1.8463, 1.4795, 1.4181, 0.00604, 0.00604, 0.00604 6, 2.0596, 1.5668, 1.4011, 0.69575, 0.67001, 0.70186, 0.32011, 1.8395, 1.2747, 1.4069, 0.00505, 0.00505, 0.00505 7, 2.0202, 1.5038, 1.3767, 0.7267, 0.68632, 0.73055, 0.3598, 1.724, 1.1529, 1.3414, 0.00406, 0.00406, 0.00406 8, 1.981, 1.4407, 1.3504, 0.71203, 0.64868, 0.72021, 0.34556, 1.7684, 1.184, 1.3627, 0.00307, 0.00307, 0.00307 9, 1.9478, 1.4049, 1.3281, 0.71606, 0.6926, 0.74638, 0.36735, 1.7095, 1.1228, 1.3287, 0.00208, 0.00208, 0.00208