projekt_widzenie_komputerowe/runs/train/results_2/results.csv

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epoch, train/box_loss, train/obj_loss, train/cls_loss, metrics/precision, metrics/recall, metrics/mAP_0.5,metrics/mAP_0.5:0.95, val/box_loss, val/obj_loss, val/cls_loss, x/lr0, x/lr1, x/lr2
0, 0.098228, 0.012357, 0.036802, 0.62232, 0.13214, 0.089418, 0.031717, 0.069472, 0.0084662, 0.026016, 0.070085, 0.0033239, 0.0033239
1, 0.064986, 0.012415, 0.026262, 0.47876, 0.20632, 0.20372, 0.093663, 0.06131, 0.0074715, 0.020762, 0.039425, 0.0059982, 0.0059982
2, 0.059795, 0.011698, 0.023483, 0.78277, 0.23639, 0.25321, 0.12511, 0.057626, 0.0075234, 0.019741, 0.0081064, 0.0080125, 0.0080125
3, 0.056145, 0.011598, 0.021579, 0.60885, 0.22664, 0.25942, 0.121, 0.05491, 0.0073363, 0.018609, 0.00703, 0.00703, 0.00703
4, 0.054804, 0.011486, 0.019281, 0.38738, 0.26263, 0.27304, 0.13919, 0.056767, 0.0073017, 0.017728, 0.00703, 0.00703, 0.00703
5, 0.051905, 0.011198, 0.017605, 0.36187, 0.29068, 0.28888, 0.13626, 0.052654, 0.0071156, 0.016426, 0.00604, 0.00604, 0.00604
6, 0.04872, 0.010922, 0.014859, 0.45057, 0.294, 0.33001, 0.17172, 0.049964, 0.0068282, 0.014044, 0.00505, 0.00505, 0.00505
7, 0.046367, 0.010882, 0.013431, 0.44414, 0.31033, 0.34637, 0.17963, 0.048657, 0.0068655, 0.013022, 0.00406, 0.00406, 0.00406
8, 0.043878, 0.010567, 0.012109, 0.44949, 0.36892, 0.36669, 0.1957, 0.046189, 0.0066921, 0.012831, 0.00307, 0.00307, 0.00307
9, 0.042023, 0.010427, 0.01088, 0.52229, 0.41697, 0.40722, 0.21311, 0.0449, 0.0065999, 0.011437, 0.00208, 0.00208, 0.00208