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  1. yolo detect train data=D:\workspace\ultralytics\my_coco.yaml model=yolov8n.yaml epochs=100 imgsz=256 workers=2 close_mosaic=100 project='bd' flipud=0.5 mosaic=0.0
  2.  
  3. from n params module arguments
  4. 0 -1 1 464 ultralytics.nn.modules.Conv [3, 16, 3, 2]
  5. 1 -1 1 4672 ultralytics.nn.modules.Conv [16, 32, 3, 2]
  6. 2 -1 1 7360 ultralytics.nn.modules.C2f [32, 32, 1, True]
  7. 3 -1 1 18560 ultralytics.nn.modules.Conv [32, 64, 3, 2]
  8. 4 -1 2 49664 ultralytics.nn.modules.C2f [64, 64, 2, True]
  9. 5 -1 1 73984 ultralytics.nn.modules.Conv [64, 128, 3, 2]
  10. 6 -1 2 197632 ultralytics.nn.modules.C2f [128, 128, 2, True]
  11. 7 -1 1 295424 ultralytics.nn.modules.Conv [128, 256, 3, 2]
  12. 8 -1 1 460288 ultralytics.nn.modules.C2f [256, 256, 1, True]
  13. 9 -1 1 164608 ultralytics.nn.modules.SPPF [256, 256, 5]
  14. 10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
  15. 11 [-1, 6] 1 0 ultralytics.nn.modules.Concat [1]
  16. 12 -1 1 148224 ultralytics.nn.modules.C2f [384, 128, 1]
  17. 13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
  18. 14 [-1, 4] 1 0 ultralytics.nn.modules.Concat [1]
  19. 15 -1 1 37248 ultralytics.nn.modules.C2f [192, 64, 1]
  20. 16 -1 1 36992 ultralytics.nn.modules.Conv [64, 64, 3, 2]
  21. 17 [-1, 12] 1 0 ultralytics.nn.modules.Concat [1]
  22. 18 -1 1 123648 ultralytics.nn.modules.C2f [192, 128, 1]
  23. 19 -1 1 147712 ultralytics.nn.modules.Conv [128, 128, 3, 2]
  24. 20 [-1, 9] 1 0 ultralytics.nn.modules.Concat [1]
  25. 21 -1 1 493056 ultralytics.nn.modules.C2f [384, 256, 1]
  26. 22 [15, 18, 21] 1 897664 ultralytics.nn.modules.Detect [80, [64, 128, 256]]
  27. YOLOv8n summary: 225 layers, 3157200 parameters, 3157184 gradients, 8.9 GFLOPs
  28.  
  29. New https://pypi.org/project/ultralytics/8.0.107 available Update with 'pip install -U ultralytics'
  30. Ultralytics YOLOv8.0.88 Python-3.10.10 torch-2.0.0+cu117 CUDA:0 (NVIDIA GeForce GTX 1660 Ti, 6144MiB)
  31. yolo\engine\trainer: task=detect, mode=train, model=yolov8n.yaml, data=D:\workspace\ultralytics\my_coco.yaml, epochs=100, patience=50, batch=16, imgsz=256, save=True, save_period=-1, cache=False, device=None, workers=2, project=bd,
  32. name=None, exist_ok=False, pretrained=False, optimizer=SGD, verbose=True, seed=0, deterministic=True, single_cls=False, image_weights=False, rect=False, cos_lr=False, close_mosaic=100, resume=False, amp=True, overlap_mask=True, mask
  33. _ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, show=False, save_txt=False, save_conf=False, save_crop=False, show_labe
  34. ls=True, show_conf=True, vid_stride=1, line_thickness=3, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, boxes=True, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, s
  35. implify=False, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=
  36. 0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.5, fliplr=0.5, mosaic=0.0, mixup=0.0, copy_paste=0.0, cfg=None, v5loader=False, tracker=botsort.yaml, save_dir=bd\train
  37. Overriding model.yaml nc=80 with nc=1
  38.  
  39. from n params module arguments
  40. 0 -1 1 464 ultralytics.nn.modules.Conv [3, 16, 3, 2]
  41. 1 -1 1 4672 ultralytics.nn.modules.Conv [16, 32, 3, 2]
  42. 2 -1 1 7360 ultralytics.nn.modules.C2f [32, 32, 1, True]
  43. 3 -1 1 18560 ultralytics.nn.modules.Conv [32, 64, 3, 2]
  44. 4 -1 2 49664 ultralytics.nn.modules.C2f [64, 64, 2, True]
  45. 5 -1 1 73984 ultralytics.nn.modules.Conv [64, 128, 3, 2]
  46. 6 -1 2 197632 ultralytics.nn.modules.C2f [128, 128, 2, True]
  47. 7 -1 1 295424 ultralytics.nn.modules.Conv [128, 256, 3, 2]
  48. 8 -1 1 460288 ultralytics.nn.modules.C2f [256, 256, 1, True]
  49. 9 -1 1 164608 ultralytics.nn.modules.SPPF [256, 256, 5]
  50. 10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
  51. 11 [-1, 6] 1 0 ultralytics.nn.modules.Concat [1]
  52. 12 -1 1 148224 ultralytics.nn.modules.C2f [384, 128, 1]
  53. 13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
  54. 14 [-1, 4] 1 0 ultralytics.nn.modules.Concat [1]
  55. 15 -1 1 37248 ultralytics.nn.modules.C2f [192, 64, 1]
  56. 16 -1 1 36992 ultralytics.nn.modules.Conv [64, 64, 3, 2]
  57. 17 [-1, 12] 1 0 ultralytics.nn.modules.Concat [1]
  58. 18 -1 1 123648 ultralytics.nn.modules.C2f [192, 128, 1]
  59. 19 -1 1 147712 ultralytics.nn.modules.Conv [128, 128, 3, 2]
  60. 20 [-1, 9] 1 0 ultralytics.nn.modules.Concat [1]
  61. 21 -1 1 493056 ultralytics.nn.modules.C2f [384, 256, 1]
  62. 22 [15, 18, 21] 1 751507 ultralytics.nn.modules.Detect [1, [64, 128, 256]]
  63. YOLOv8n summary: 225 layers, 3011043 parameters, 3011027 gradients, 8.2 GFLOPs
  64.  
  65. AMP: running Automatic Mixed Precision (AMP) checks with YOLOv8n...
  66. AMP: checks passed
  67. optimizer: SGD(lr=0.01) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias
  68. train: Scanning D:\workspace\ultralytics\datasets\data\labels\train.cache... 4270 images, 0 backgrounds, 0 corrupt: 100%|██████████| 4270/4270 [00:00<?, ?it/s]
  69. val: Scanning D:\workspace\ultralytics\datasets\data\labels\test.cache... 1391 images, 0 backgrounds, 0 corrupt: 100%|██████████| 1391/1391 [00:00<?, ?it/s]
  70. Plotting labels to bd\train\labels.jpg...
  71. Image sizes 256 train, 256 val
  72. Using 2 dataloader workers
  73. Logging results to bd\train
  74. Starting training for 100 epochs...
  75. Closing dataloader mosaic
  76.  
  77. Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
  78. 1/100 1.33G nan nan nan 183 256: 100%|██████████| 267/267 [00:42<00:00, 6.26it/s]
  79. Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 44/44 [00:05<00:00, 8.18it/s]
  80. all 1391 26278 0 0 0 0
  81.  
  82. Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
  83. 2/100 1.51G nan nan nan 725 256: 100%|██████████| 267/267 [00:40<00:00, 6.54it/s]
  84. Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 44/44 [00:05<00:00, 7.99it/s]
  85. all 1391 26278 0 0 0 0
  86.  
  87. Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
  88. 3/100 1.33G nan nan nan 159 256: 100%|██████████| 267/267 [00:40<00:00, 6.53it/s]
  89. Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 44/44 [00:05<00:00, 7.94it/s]
  90. all 1391 26278 0 0 0 0
  91.  
  92. Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
  93. 4/100 1.59G nan nan nan 195 256: 100%|██████████| 267/267 [00:41<00:00, 6.48it/s]
  94. Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 44/44 [00:05<00:00, 7.84it/s]
  95. all 1391 26278 0 0 0 0
  96.  
  97. Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
  98. 5/100 1.53G nan nan nan 404 256: 100%|██████████| 267/267 [00:42<00:00, 6.26it/s]
  99. Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 44/44 [00:05<00:00, 7.81it/s]
  100. all 1391 26278 0 0 0 0
  101.  
  102. Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
  103. 6/100 1.6G nan nan nan 605 256: 100%|██████████| 267/267 [00:42<00:00, 6.35it/s]
  104. Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 44/44 [00:05<00:00, 7.81it/s]
  105. all 1391 26278 0 0 0 0
  106.  
  107. Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
  108. 7/100 1.44G nan nan nan 198 256: 100%|██████████| 267/267 [00:42<00:00, 6.34it/s]
  109. Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 44/44 [00:05<00:00, 7.81it/s]
  110. all 1391 26278 0 0 0 0
  111.  
  112. Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
  113. 8/100 1.43G nan nan nan 159 256: 100%|██████████| 267/267 [00:47<00:00, 5.66it/s]
  114. Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 44/44 [00:05<00:00, 7.43it/s]
  115. all 1391 26278 0 0 0 0
  116.  
  117. Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
  118. 9/100 1.27G nan nan nan 905 256: 100%|██████████| 267/267 [00:44<00:00, 6.03it/s]
  119. Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 44/44 [00:06<00:00, 7.13it/s]
  120. all 1391 26278 0 0 0 0
  121.  
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