projekt_widzenie_komputerowe/runs/train/results_6/results.csv

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2023-01-31 18:36:44 +01:00
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, 0.088747, 0.013486, 0.035328, 0.48098, 0.20986, 0.1441, 0.061546, 0.064393, 0.0078718, 0.023488, 0.070085, 0.0033239, 0.0033239
1, 0.058438, 0.011951, 0.023984, 0.5898, 0.25482, 0.26328, 0.13231, 0.060662, 0.007082, 0.01869, 0.039425, 0.0059982, 0.0059982
2, 0.053591, 0.011235, 0.0191, 0.56778, 0.24853, 0.27684, 0.134, 0.053592, 0.0072559, 0.017413, 0.0081064, 0.0080125, 0.0080125
3, 0.050726, 0.011181, 0.017684, 0.64627, 0.28311, 0.31118, 0.16046, 0.051076, 0.0071247, 0.01801, 0.00703, 0.00703, 0.00703
4, 0.048493, 0.01088, 0.015352, 0.65466, 0.32505, 0.32784, 0.1698, 0.051364, 0.0067966, 0.015725, 0.00703, 0.00703, 0.00703
5, 0.045655, 0.01056, 0.014044, 0.42375, 0.41639, 0.36913, 0.19269, 0.047876, 0.0067158, 0.014229, 0.00604, 0.00604, 0.00604
6, 0.042586, 0.010138, 0.011871, 0.4344, 0.43674, 0.39772, 0.2087, 0.046564, 0.0066062, 0.01276, 0.00505, 0.00505, 0.00505
7, 0.039962, 0.0099789, 0.0098593, 0.61441, 0.4483, 0.4848, 0.2713, 0.042678, 0.0063287, 0.011581, 0.00406, 0.00406, 0.00406
8, 0.03696, 0.0094761, 0.0089893, 0.68112, 0.49743, 0.51699, 0.28992, 0.04077, 0.0061885, 0.010641, 0.00307, 0.00307, 0.00307
9, 0.0346, 0.0092088, 0.0075677, 0.65343, 0.4742, 0.51803, 0.29082, 0.038619, 0.0060215, 0.0097588, 0.00208, 0.00208, 0.00208