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  1. .gitattributes +18 -0
  2. flejes-15/runs/detect/train/F1_curve.png +3 -0
  3. flejes-15/runs/detect/train/PR_curve.png +3 -0
  4. flejes-15/runs/detect/train/P_curve.png +3 -0
  5. flejes-15/runs/detect/train/R_curve.png +3 -0
  6. flejes-15/runs/detect/train/args.yaml +98 -0
  7. flejes-15/runs/detect/train/confusion_matrix.png +3 -0
  8. flejes-15/runs/detect/train/confusion_matrix_normalized.png +3 -0
  9. flejes-15/runs/detect/train/labels.jpg +3 -0
  10. flejes-15/runs/detect/train/labels_correlogram.jpg +3 -0
  11. flejes-15/runs/detect/train/results.csv +104 -0
  12. flejes-15/runs/detect/train/results.png +3 -0
  13. flejes-15/runs/detect/train/train_batch0.jpg +3 -0
  14. flejes-15/runs/detect/train/train_batch1.jpg +3 -0
  15. flejes-15/runs/detect/train/train_batch2.jpg +3 -0
  16. flejes-15/runs/detect/train/val_batch0_labels.jpg +3 -0
  17. flejes-15/runs/detect/train/val_batch0_pred.jpg +3 -0
  18. flejes-15/runs/detect/train/val_batch1_labels.jpg +3 -0
  19. flejes-15/runs/detect/train/val_batch1_pred.jpg +3 -0
  20. flejes-15/runs/detect/train/val_batch2_labels.jpg +3 -0
  21. flejes-15/runs/detect/train/val_batch2_pred.jpg +3 -0
  22. flejes-15/runs/detect/train/weights/best.pt +3 -0
  23. flejes-15/runs/detect/train/weights/last.pt +3 -0
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+ task: detect
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+ mode: train
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+ model: yolov8m.pt
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+ data: /home/ec2-user/SageMaker/datasets/flejes-15/data.yaml
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+ epochs: 300
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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, 2.1129, 2.0725, 1.6047, 0.71752, 0.48644, 0.52213, 0.3279, 1.5895, 0.97365, 1.2287, 0.0033322, 0.0033322, 0.0033322
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+ 2, 1.9668, 1.5723, 1.4209, 0.70404, 0.58383, 0.63478, 0.39773, 1.6121, 0.89759, 1.229, 0.0066435, 0.0066435, 0.0066435
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+ 3, 1.918, 1.4621, 1.3822, 0.80715, 0.59081, 0.63258, 0.39495, 1.5531, 0.92432, 1.2137, 0.0099329, 0.0099329, 0.0099329
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+ 4, 1.9058, 1.4109, 1.3731, 0.79488, 0.58118, 0.65617, 0.42613, 1.5639, 0.84839, 1.2206, 0.009901, 0.009901, 0.009901
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+ 5, 1.8635, 1.3203, 1.3441, 0.73313, 0.66811, 0.70314, 0.44837, 1.5712, 0.85127, 1.2079, 0.009901, 0.009901, 0.009901
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+ 7, 1.8039, 1.2134, 1.3098, 0.69021, 0.70561, 0.76786, 0.48853, 1.5275, 0.79194, 1.1969, 0.009835, 0.009835, 0.009835
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+ 8, 1.7896, 1.1871, 1.3035, 0.78378, 0.71857, 0.74775, 0.47498, 1.5445, 0.78231, 1.1935, 0.009802, 0.009802, 0.009802
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+ 9, 1.7699, 1.1505, 1.2911, 0.76895, 0.77295, 0.78783, 0.50702, 1.5474, 0.71106, 1.1989, 0.009769, 0.009769, 0.009769
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+ 10, 1.7525, 1.1224, 1.2816, 0.81537, 0.72132, 0.81077, 0.52402, 1.5311, 0.72155, 1.1894, 0.009736, 0.009736, 0.009736
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+ 11, 1.736, 1.0905, 1.2753, 0.79104, 0.74466, 0.79215, 0.51594, 1.5377, 0.71701, 1.2032, 0.009703, 0.009703, 0.009703
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+ 12, 1.7262, 1.0737, 1.2713, 0.78768, 0.71654, 0.79339, 0.51675, 1.5431, 0.71625, 1.2002, 0.00967, 0.00967, 0.00967
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+ 13, 1.7094, 1.0449, 1.2581, 0.72707, 0.80836, 0.79043, 0.52669, 1.5348, 0.68732, 1.1932, 0.009637, 0.009637, 0.009637
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+ 14, 1.7015, 1.0312, 1.2544, 0.81823, 0.78617, 0.83815, 0.54518, 1.5274, 0.68456, 1.1859, 0.009604, 0.009604, 0.009604
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+ 15, 1.6863, 1.0117, 1.2483, 0.85564, 0.76615, 0.79725, 0.51584, 1.5024, 0.7358, 1.1806, 0.009571, 0.009571, 0.009571
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+ 16, 1.6781, 0.99641, 1.2424, 0.86693, 0.80094, 0.85594, 0.54969, 1.5184, 0.67334, 1.1927, 0.009538, 0.009538, 0.009538
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+ 17, 1.6677, 0.98157, 1.2358, 0.85111, 0.80679, 0.83138, 0.54449, 1.5094, 0.6666, 1.1936, 0.009505, 0.009505, 0.009505
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+ 20, 1.6415, 0.94756, 1.2259, 0.85866, 0.76207, 0.79017, 0.51964, 1.523, 0.66596, 1.1948, 0.009406, 0.009406, 0.009406
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+ 22, 1.6301, 0.93283, 1.2181, 0.81149, 0.80186, 0.80514, 0.53113, 1.5165, 0.65159, 1.1893, 0.00934, 0.00934, 0.00934
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+ 45, 1.5175, 0.76905, 1.1755, 0.87226, 0.81392, 0.84618, 0.56784, 1.5765, 0.56308, 1.2265, 0.008581, 0.008581, 0.008581
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+ 46, 1.5163, 0.7642, 1.1746, 0.79463, 0.86558, 0.86563, 0.57351, 1.5793, 0.56113, 1.2287, 0.008548, 0.008548, 0.008548
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