Train
Train¶
You can simply train a hub by calling train method of Hub class.
Create hub or load hub¶
In [1]:
Copied!
from waffle_hub.hub import Hub
hub = Hub.new(
name="detector",
backend="ultralytics",
task="OBJECT_DETECTION",
model_type="yolov8",
model_size="n",
categories=["1", "2"]
)
from waffle_hub.hub import Hub
hub = Hub.new(
name="detector",
backend="ultralytics",
task="OBJECT_DETECTION",
model_type="yolov8",
model_size="n",
categories=["1", "2"]
)
/home/lhj/anaconda3/envs/waffle/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html from .autonotebook import tqdm as notebook_tqdm
In [2]:
Copied!
hub = Hub.load("detector")
hub = Hub.load("detector")
In [3]:
Copied!
hub
hub
Out[3]:
ModelConfig(name='detector', backend='ultralytics', version='8.0.112', task='OBJECT_DETECTION', model_type='yolov8', model_size='n', categories=[{'supercategory': 'object', 'name': '1'}, {'supercategory': 'object', 'name': '2'}])
Load Dataset¶
In [5]:
Copied!
# Use sample dataset for this tutorial
from waffle_hub.dataset import Dataset
dataset = Dataset.sample("sample_dataset", task="object_detection")
# Use sample dataset for this tutorial
from waffle_hub.dataset import Dataset
dataset = Dataset.sample("sample_dataset", task="object_detection")
loading annotations into memory... Done (t=0.00s) creating index... index created!
1it [00:00, 59.89it/s]: 0%| | 0/100 [00:00<?, ?it/s] Importing coco dataset: 100%|██████████| 100/100 [00:00<00:00, 5698.47it/s]
In [6]:
Copied!
dataset.split(0.8, 0.2)
dataset.split(0.8, 0.2)
train¶
In [7]:
Copied!
hub.train(dataset, epochs=50)
hub.train(dataset, epochs=50)
New https://pypi.org/project/ultralytics/8.0.123 available 😃 Update with 'pip install -U ultralytics' Ultralytics YOLOv8.0.112 🚀 Python-3.9.16 torch-1.13.1+cu117 CUDA:0 (NVIDIA GeForce RTX 4090, 24215MiB) WARNING ⚠️ Upgrade to torch>=2.0.0 for deterministic training. yolo/engine/trainer: task=detect, mode=train, model=yolov8n.pt, data=/home/lhj/ws/release/waffle/docs/tutorials/hub/datasets/sample_dataset/exports/YOLO/data.yaml, epochs=50, patience=50, batch=64, imgsz=[640, 640], save=True, save_period=-1, cache=False, device=0, workers=2, project=hubs/detector, name=artifacts, exist_ok=False, pretrained=False, optimizer=SGD, verbose=True, seed=0, deterministic=True, single_cls=False, rect=True, cos_lr=False, close_mosaic=0, resume=False, amp=True, fraction=1.0, profile=False, overlap_mask=True, mask_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_labels=True, show_conf=True, vid_stride=1, line_width=None, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, boxes=True, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=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=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=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0, cfg=None, v5loader=False, tracker=botsort.yaml, save_dir=hubs/detector/artifacts Overriding model.yaml nc=80 with nc=2 from n params module arguments 0 -1 1 464 ultralytics.nn.modules.conv.Conv [3, 16, 3, 2] 1 -1 1 4672 ultralytics.nn.modules.conv.Conv [16, 32, 3, 2] 2 -1 1 7360 ultralytics.nn.modules.block.C2f [32, 32, 1, True] 3 -1 1 18560 ultralytics.nn.modules.conv.Conv [32, 64, 3, 2] 4 -1 2 49664 ultralytics.nn.modules.block.C2f [64, 64, 2, True] 5 -1 1 73984 ultralytics.nn.modules.conv.Conv [64, 128, 3, 2] 6 -1 2 197632 ultralytics.nn.modules.block.C2f [128, 128, 2, True] 7 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2] 8 -1 1 460288 ultralytics.nn.modules.block.C2f [256, 256, 1, True] 9 -1 1 164608 ultralytics.nn.modules.block.SPPF [256, 256, 5] 10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] 11 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1] 12 -1 1 148224 ultralytics.nn.modules.block.C2f [384, 128, 1] 13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] 14 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1] 15 -1 1 37248 ultralytics.nn.modules.block.C2f [192, 64, 1] 16 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2] 17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1] 18 -1 1 123648 ultralytics.nn.modules.block.C2f [192, 128, 1] 19 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2] 20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1] 21 -1 1 493056 ultralytics.nn.modules.block.C2f [384, 256, 1] 22 [15, 18, 21] 1 751702 ultralytics.nn.modules.head.Detect [2, [64, 128, 256]] Model summary: 225 layers, 3011238 parameters, 3011222 gradients, 8.2 GFLOPs Transferred 319/355 items from pretrained weights TensorBoard: Start with 'tensorboard --logdir hubs/detector/artifacts', view at http://localhost:6006/ AMP: running Automatic Mixed Precision (AMP) checks with YOLOv8n... AMP: checks passed ✅ WARNING ⚠️ updating to 'imgsz=640'. 'train' and 'val' imgsz must be an integer, while 'predict' and 'export' imgsz may be a [h, w] list or an integer, i.e. 'yolo export imgsz=640,480' or 'yolo export imgsz=640' optimizer: SGD(lr=0.01) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias train: Scanning /home/lhj/ws/release/waffle/docs/tutorials/hub/datasets/sample_dataset/exports/YOLO/train/labels... 79 images, 0 backgrounds, 0 corrupt: 100%|██████████| 79/79 [00:00<00:00, 6366.12it/s] train: New cache created: /home/lhj/ws/release/waffle/docs/tutorials/hub/datasets/sample_dataset/exports/YOLO/train/labels.cache albumentations: Blur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8)) WARNING ⚠️ 'rect=True' is incompatible with DataLoader shuffle, setting shuffle=False val: Scanning /home/lhj/ws/release/waffle/docs/tutorials/hub/datasets/sample_dataset/exports/YOLO/val/labels... 21 images, 0 backgrounds, 0 corrupt: 100%|██████████| 21/21 [00:00<00:00, 4837.72it/s] val: New cache created: /home/lhj/ws/release/waffle/docs/tutorials/hub/datasets/sample_dataset/exports/YOLO/val/labels.cache Plotting labels to hubs/detector/artifacts/labels.jpg... Image sizes 640 train, 640 val Using 2 dataloader workers Logging results to hubs/detector/artifacts Starting training for 50 epochs... Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 1/50 8.05G 1.35 4.646 1.035 15 640: 100%|██████████| 2/2 [00:00<00:00, 3.37it/s] /home/lhj/anaconda3/envs/waffle/lib/python3.9/site-packages/torch/optim/lr_scheduler.py:138: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`. Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate warnings.warn("Detected call of `lr_scheduler.step()` before `optimizer.step()`. " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 7.96it/s] all 21 21 0.00268 0.8 0.279 0.221 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 2/50 8.05G 1.575 5.092 1.179 15 640: 100%|██████████| 2/2 [00:00<00:00, 4.89it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.11it/s] all 21 21 0.00301 0.9 0.287 0.235 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 3/50 8.05G 1.409 4.601 1.086 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.85it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 18.04it/s] all 21 21 0.00318 0.95 0.3 0.243 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 4/50 8.05G 1.395 4.785 1.085 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.81it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.71it/s] all 21 21 0.00317 0.95 0.3 0.256 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 5/50 8.05G 1.462 4.589 1.095 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.82it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.09it/s] all 21 21 0.00317 0.95 0.293 0.27 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 6/50 8.05G 1.396 4.978 1.08 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.68it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 18.11it/s] all 21 21 0.00333 1 0.297 0.241 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 7/50 8.07G 1.209 4.545 0.9995 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.50it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 16.24it/s] all 21 21 0.00337 1 0.262 0.219 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 8/50 8.07G 0.9826 4.332 0.945 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.70it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.77it/s] all 21 21 0.00337 1 0.234 0.214 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 9/50 8.07G 0.6574 4.055 0.8496 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.68it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.63it/s] all 21 21 0.00333 1 0.385 0.331 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 10/50 8.07G 0.6343 3.874 0.833 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.65it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.79it/s] all 21 21 0.00337 1 0.515 0.452 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 11/50 8.07G 0.6128 3.512 0.7921 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.65it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.66it/s] all 21 21 0.00339 1 0.602 0.494 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 12/50 8.07G 0.6772 2.915 0.8324 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.75it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.65it/s] all 21 21 0.00338 1 0.696 0.582 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 13/50 8.07G 0.6111 2.222 0.8684 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.72it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.61it/s] all 21 21 0.0034 1 0.716 0.605 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 14/50 8.07G 0.5946 1.971 0.8091 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.68it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.25it/s] all 21 21 0.00339 1 0.754 0.595 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 15/50 8.07G 0.7179 1.955 0.9884 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.25it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.20it/s] all 21 21 0.0034 1 0.774 0.653 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 16/50 8.07G 0.6793 1.752 0.8643 15 640: 100%|██████████| 2/2 [00:00<00:00, 6.15it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 17.96it/s] all 21 21 0.00338 1 0.813 0.692 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 17/50 8.07G 0.6969 1.592 0.9367 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.69it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 20.51it/s] all 21 21 0.00336 1 0.857 0.687 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 18/50 8.07G 0.6333 1.443 0.8665 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.69it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.41it/s] all 21 21 0.00339 1 0.877 0.731 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 19/50 8.07G 0.5324 1.451 0.8002 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.66it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.42it/s] all 21 21 0.0034 1 0.867 0.712 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 20/50 8.07G 0.5891 1.397 0.8683 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.75it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.55it/s] all 21 21 0.00346 1 0.879 0.732 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 21/50 8.07G 0.53 1.273 0.8027 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.76it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.48it/s] all 21 21 0.00371 1 0.952 0.834 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 22/50 8.07G 0.6902 1.273 0.896 13 640: 100%|██████████| 2/2 [00:00<00:00, 7.77it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.69it/s] all 21 21 0.00391 1 0.948 0.787 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 23/50 8.07G 0.6887 1.321 0.8982 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.72it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.86it/s] all 21 21 0.00383 1 0.972 0.838 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 24/50 8.07G 0.6426 1.132 0.9158 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.75it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.73it/s] all 21 21 0.0037 1 0.959 0.801 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 25/50 8.07G 0.6047 1.1 0.8697 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.66it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 21.90it/s] all 21 21 0.00355 1 0.99 0.795 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 26/50 8.07G 0.6092 1.041 0.8788 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.70it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.18it/s] all 21 21 0.00349 1 0.977 0.834 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 27/50 8.07G 0.5892 1.029 0.8259 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.70it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.47it/s] all 21 21 0.0034 1 0.981 0.82 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 28/50 8.07G 0.5722 0.9661 0.873 13 640: 100%|██████████| 2/2 [00:00<00:00, 7.74it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.48it/s] all 21 21 0.00338 1 0.995 0.846 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 29/50 8.07G 0.5316 0.9626 0.8278 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.75it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 21.96it/s] all 21 21 0.00336 1 0.97 0.822 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 30/50 8.07G 0.5911 0.9537 0.8898 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.72it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.47it/s] all 21 21 0.00363 1 0.978 0.823 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 31/50 8.07G 0.5412 0.9979 0.8238 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.71it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.31it/s] all 21 21 0.00342 1 0.995 0.852 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 32/50 8.07G 0.5441 0.847 0.8341 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.70it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.03it/s] all 21 21 0.00339 1 0.995 0.804 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 33/50 8.07G 0.5497 0.8736 0.8077 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.71it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.46it/s] all 21 21 0.00334 1 0.995 0.859 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 34/50 8.07G 0.494 0.8033 0.8161 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.75it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 21.80it/s] all 21 21 0.00353 1 0.995 0.875 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 35/50 8.07G 0.5713 0.8376 0.8583 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.72it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.59it/s] all 21 21 0.975 1 0.995 0.811 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 36/50 8.07G 0.5074 0.7759 0.8489 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.78it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.54it/s] all 21 21 1 0.556 0.995 0.842 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 37/50 8.07G 0.5478 0.9739 0.8804 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.73it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 23.31it/s] all 21 21 0.00335 1 0.995 0.884 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 38/50 8.07G 0.5109 0.793 0.8102 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.69it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.82it/s] all 21 21 0.947 1 0.995 0.879 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 39/50 8.07G 0.5767 0.8693 0.8706 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.76it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.38it/s] all 21 21 0.986 0.837 0.995 0.874 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 40/50 8.07G 0.5938 0.8053 0.8787 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.77it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 23.14it/s] all 21 21 1 0.444 0.99 0.889 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 41/50 8.07G 0.4485 0.8481 0.813 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.28it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.44it/s] all 21 21 1 0.35 0.972 0.86 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 42/50 8.07G 0.5216 0.7309 0.8386 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.74it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.28it/s] all 21 21 1 0.57 0.981 0.888 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 43/50 8.07G 0.4611 0.7521 0.8164 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.76it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.30it/s] all 21 21 0.944 0.618 0.981 0.85 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 44/50 8.07G 0.4799 0.8456 0.816 15 640: 100%|██████████| 2/2 [00:00<00:00, 6.64it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 20.08it/s] all 21 21 0.961 0.727 0.986 0.878 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 45/50 8.07G 0.4227 0.6774 0.8516 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.66it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.60it/s] all 21 21 1 0.681 0.986 0.886 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 46/50 8.07G 0.4401 0.6882 0.7938 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.69it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 20.89it/s] all 21 21 1 0.76 0.995 0.903 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 47/50 8.07G 0.4235 0.6814 0.8128 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.70it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.19it/s] all 21 21 1 0.841 0.995 0.9 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 48/50 8.07G 0.4322 0.6854 0.8143 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.75it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 21.71it/s] all 21 21 0.993 0.97 0.995 0.906 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 49/50 8.07G 0.3993 0.6641 0.8059 15 640: 100%|██████████| 2/2 [00:00<00:00, 7.75it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 22.18it/s] all 21 21 0.995 0.982 0.995 0.892 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 50/50 8.07G 0.4161 0.6213 0.809 14 640: 100%|██████████| 2/2 [00:00<00:00, 7.65it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 15.49it/s] all 21 21 0.991 1 0.995 0.907 50 epochs completed in 0.009 hours. Optimizer stripped from hubs/detector/artifacts/weights/last.pt, 6.2MB Optimizer stripped from hubs/detector/artifacts/weights/best.pt, 6.2MB Validating hubs/detector/artifacts/weights/best.pt... Ultralytics YOLOv8.0.112 🚀 Python-3.9.16 torch-1.13.1+cu117 CUDA:0 (NVIDIA GeForce RTX 4090, 24215MiB) Model summary (fused): 168 layers, 3006038 parameters, 0 gradients, 8.1 GFLOPs Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 1/1 [00:00<00:00, 16.60it/s] all 21 21 0.992 1 0.995 0.907 1 21 10 0.992 1 0.995 0.883 2 21 11 0.992 1 0.995 0.932 Speed: 0.1ms preprocess, 0.8ms inference, 0.0ms loss, 0.3ms postprocess per image Results saved to hubs/detector/artifacts 100%|██████████| 1/1 [00:01<00:00, 1.27s/it]
Out[7]:
TrainResult(best_ckpt_file=PosixPath('hubs/detector/weights/best_ckpt.pt'), last_ckpt_file=PosixPath('hubs/detector/weights/last_ckpt.pt'), metrics=[[{'tag': 'epoch', 'value': 0.0}, {'tag': 'train/box_loss', 'value': 1.3501}, {'tag': 'train/cls_loss', 'value': 4.6464}, {'tag': 'train/dfl_loss', 'value': 1.0351}, {'tag': 'metrics/precision(B)', 'value': 0.00268}, {'tag': 'metrics/recall(B)', 'value': 0.8}, {'tag': 'metrics/mAP50(B)', 'value': 0.27948}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.22095}, {'tag': 'val/box_loss', 'value': 0.43408}, {'tag': 'val/cls_loss', 'value': 3.8634}, {'tag': 'val/dfl_loss', 'value': 0.82598}, {'tag': 'lr/pg0', 'value': 0.0991}, {'tag': 'lr/pg1', 'value': 0.0001}, {'tag': 'lr/pg2', 'value': 0.0001}], [{'tag': 'epoch', 'value': 1.0}, {'tag': 'train/box_loss', 'value': 1.5745}, {'tag': 'train/cls_loss', 'value': 5.0921}, {'tag': 'train/dfl_loss', 'value': 1.1791}, {'tag': 'metrics/precision(B)', 'value': 0.00301}, {'tag': 'metrics/recall(B)', 'value': 0.9}, {'tag': 'metrics/mAP50(B)', 'value': 0.28713}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.23503}, {'tag': 'val/box_loss', 'value': 0.42816}, {'tag': 'val/cls_loss', 'value': 3.8297}, {'tag': 'val/dfl_loss', 'value': 0.81922}, {'tag': 'lr/pg0', 'value': 0.097294}, {'tag': 'lr/pg1', 'value': 0.00029406}, {'tag': 'lr/pg2', 'value': 0.00029406}], [{'tag': 'epoch', 'value': 2.0}, {'tag': 'train/box_loss', 'value': 1.4092}, {'tag': 'train/cls_loss', 'value': 4.601}, {'tag': 'train/dfl_loss', 'value': 1.0856}, {'tag': 'metrics/precision(B)', 'value': 0.00318}, {'tag': 'metrics/recall(B)', 'value': 0.95}, {'tag': 'metrics/mAP50(B)', 'value': 0.29955}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.2428}, {'tag': 'val/box_loss', 'value': 0.44174}, {'tag': 'val/cls_loss', 'value': 3.8018}, {'tag': 'val/dfl_loss', 'value': 0.80306}, {'tag': 'lr/pg0', 'value': 0.09548}, {'tag': 'lr/pg1', 'value': 0.0004802}, {'tag': 'lr/pg2', 'value': 0.0004802}], [{'tag': 'epoch', 'value': 3.0}, {'tag': 'train/box_loss', 'value': 1.3949}, {'tag': 'train/cls_loss', 'value': 4.7847}, {'tag': 'train/dfl_loss', 'value': 1.0853}, {'tag': 'metrics/precision(B)', 'value': 0.00317}, {'tag': 'metrics/recall(B)', 'value': 0.95}, {'tag': 'metrics/mAP50(B)', 'value': 0.30017}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.25635}, {'tag': 'val/box_loss', 'value': 0.4457}, {'tag': 'val/cls_loss', 'value': 3.7635}, {'tag': 'val/dfl_loss', 'value': 0.79997}, {'tag': 'lr/pg0', 'value': 0.093658}, {'tag': 'lr/pg1', 'value': 0.00065842}, {'tag': 'lr/pg2', 'value': 0.00065842}], [{'tag': 'epoch', 'value': 4.0}, {'tag': 'train/box_loss', 'value': 1.4621}, {'tag': 'train/cls_loss', 'value': 4.5888}, {'tag': 'train/dfl_loss', 'value': 1.0952}, {'tag': 'metrics/precision(B)', 'value': 0.00317}, {'tag': 'metrics/recall(B)', 'value': 0.95}, {'tag': 'metrics/mAP50(B)', 'value': 0.29295}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.2701}, {'tag': 'val/box_loss', 'value': 0.43005}, {'tag': 'val/cls_loss', 'value': 3.7548}, {'tag': 'val/dfl_loss', 'value': 0.80128}, {'tag': 'lr/pg0', 'value': 0.091829}, {'tag': 'lr/pg1', 'value': 0.00082872}, {'tag': 'lr/pg2', 'value': 0.00082872}], [{'tag': 'epoch', 'value': 5.0}, {'tag': 'train/box_loss', 'value': 1.3964}, {'tag': 'train/cls_loss', 'value': 4.9783}, {'tag': 'train/dfl_loss', 'value': 1.0798}, {'tag': 'metrics/precision(B)', 'value': 0.00333}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.29703}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.24147}, {'tag': 'val/box_loss', 'value': 0.41959}, {'tag': 'val/cls_loss', 'value': 3.7923}, {'tag': 'val/dfl_loss', 'value': 0.8005}, {'tag': 'lr/pg0', 'value': 0.089991}, {'tag': 'lr/pg1', 'value': 0.0009911}, {'tag': 'lr/pg2', 'value': 0.0009911}], [{'tag': 'epoch', 'value': 6.0}, {'tag': 'train/box_loss', 'value': 1.2091}, {'tag': 'train/cls_loss', 'value': 4.5448}, {'tag': 'train/dfl_loss', 'value': 0.99952}, {'tag': 'metrics/precision(B)', 'value': 0.00337}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.2619}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.21933}, {'tag': 'val/box_loss', 'value': 0.42009}, {'tag': 'val/cls_loss', 'value': 3.8168}, {'tag': 'val/dfl_loss', 'value': 0.81327}, {'tag': 'lr/pg0', 'value': 0.088146}, {'tag': 'lr/pg1', 'value': 0.0011456}, {'tag': 'lr/pg2', 'value': 0.0011456}], [{'tag': 'epoch', 'value': 7.0}, {'tag': 'train/box_loss', 'value': 0.98263}, {'tag': 'train/cls_loss', 'value': 4.3317}, {'tag': 'train/dfl_loss', 'value': 0.94503}, {'tag': 'metrics/precision(B)', 'value': 0.00337}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.23364}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.21407}, {'tag': 'val/box_loss', 'value': 0.49657}, {'tag': 'val/cls_loss', 'value': 3.792}, {'tag': 'val/dfl_loss', 'value': 0.82097}, {'tag': 'lr/pg0', 'value': 0.086292}, {'tag': 'lr/pg1', 'value': 0.0012921}, {'tag': 'lr/pg2', 'value': 0.0012921}], [{'tag': 'epoch', 'value': 8.0}, {'tag': 'train/box_loss', 'value': 0.65743}, {'tag': 'train/cls_loss', 'value': 4.0554}, {'tag': 'train/dfl_loss', 'value': 0.84959}, {'tag': 'metrics/precision(B)', 'value': 0.00333}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.38451}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.3307}, {'tag': 'val/box_loss', 'value': 0.58206}, {'tag': 'val/cls_loss', 'value': 3.7688}, {'tag': 'val/dfl_loss', 'value': 0.82093}, {'tag': 'lr/pg0', 'value': 0.084431}, {'tag': 'lr/pg1', 'value': 0.0014307}, {'tag': 'lr/pg2', 'value': 0.0014307}], [{'tag': 'epoch', 'value': 9.0}, {'tag': 'train/box_loss', 'value': 0.63434}, {'tag': 'train/cls_loss', 'value': 3.8742}, {'tag': 'train/dfl_loss', 'value': 0.83304}, {'tag': 'metrics/precision(B)', 'value': 0.00337}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.515}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.45197}, {'tag': 'val/box_loss', 'value': 0.60736}, {'tag': 'val/cls_loss', 'value': 3.6357}, {'tag': 'val/dfl_loss', 'value': 0.81601}, {'tag': 'lr/pg0', 'value': 0.082561}, {'tag': 'lr/pg1', 'value': 0.0015614}, {'tag': 'lr/pg2', 'value': 0.0015614}], [{'tag': 'epoch', 'value': 10.0}, {'tag': 'train/box_loss', 'value': 0.61282}, {'tag': 'train/cls_loss', 'value': 3.512}, {'tag': 'train/dfl_loss', 'value': 0.79209}, {'tag': 'metrics/precision(B)', 'value': 0.00339}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.60177}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.49371}, {'tag': 'val/box_loss', 'value': 0.64081}, {'tag': 'val/cls_loss', 'value': 3.4475}, {'tag': 'val/dfl_loss', 'value': 0.80918}, {'tag': 'lr/pg0', 'value': 0.080684}, {'tag': 'lr/pg1', 'value': 0.0016842}, {'tag': 'lr/pg2', 'value': 0.0016842}], [{'tag': 'epoch', 'value': 11.0}, {'tag': 'train/box_loss', 'value': 0.67718}, {'tag': 'train/cls_loss', 'value': 2.9147}, {'tag': 'train/dfl_loss', 'value': 0.83244}, {'tag': 'metrics/precision(B)', 'value': 0.00338}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.69629}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.582}, {'tag': 'val/box_loss', 'value': 0.59014}, {'tag': 'val/cls_loss', 'value': 3.2775}, {'tag': 'val/dfl_loss', 'value': 0.78841}, {'tag': 'lr/pg0', 'value': 0.078799}, {'tag': 'lr/pg1', 'value': 0.0017991}, {'tag': 'lr/pg2', 'value': 0.0017991}], [{'tag': 'epoch', 'value': 12.0}, {'tag': 'train/box_loss', 'value': 0.61112}, {'tag': 'train/cls_loss', 'value': 2.2224}, {'tag': 'train/dfl_loss', 'value': 0.86835}, {'tag': 'metrics/precision(B)', 'value': 0.0034}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.71624}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.60464}, {'tag': 'val/box_loss', 'value': 0.57163}, {'tag': 'val/cls_loss', 'value': 3.2206}, {'tag': 'val/dfl_loss', 'value': 0.79575}, {'tag': 'lr/pg0', 'value': 0.076906}, {'tag': 'lr/pg1', 'value': 0.001906}, {'tag': 'lr/pg2', 'value': 0.001906}], [{'tag': 'epoch', 'value': 13.0}, {'tag': 'train/box_loss', 'value': 0.59459}, {'tag': 'train/cls_loss', 'value': 1.9712}, {'tag': 'train/dfl_loss', 'value': 0.80912}, {'tag': 'metrics/precision(B)', 'value': 0.00339}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.75376}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.59454}, {'tag': 'val/box_loss', 'value': 0.60448}, {'tag': 'val/cls_loss', 'value': 3.2301}, {'tag': 'val/dfl_loss', 'value': 0.79842}, {'tag': 'lr/pg0', 'value': 0.075005}, {'tag': 'lr/pg1', 'value': 0.002005}, {'tag': 'lr/pg2', 'value': 0.002005}], [{'tag': 'epoch', 'value': 14.0}, {'tag': 'train/box_loss', 'value': 0.71785}, {'tag': 'train/cls_loss', 'value': 1.9547}, {'tag': 'train/dfl_loss', 'value': 0.98837}, {'tag': 'metrics/precision(B)', 'value': 0.0034}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.77386}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.65288}, {'tag': 'val/box_loss', 'value': 0.49612}, {'tag': 'val/cls_loss', 'value': 3.2141}, {'tag': 'val/dfl_loss', 'value': 0.79957}, {'tag': 'lr/pg0', 'value': 0.073096}, {'tag': 'lr/pg1', 'value': 0.0020961}, {'tag': 'lr/pg2', 'value': 0.0020961}], [{'tag': 'epoch', 'value': 15.0}, {'tag': 'train/box_loss', 'value': 0.6793}, {'tag': 'train/cls_loss', 'value': 1.7516}, {'tag': 'train/dfl_loss', 'value': 0.86429}, {'tag': 'metrics/precision(B)', 'value': 0.00338}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.81266}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.69205}, {'tag': 'val/box_loss', 'value': 0.57349}, {'tag': 'val/cls_loss', 'value': 3.2207}, {'tag': 'val/dfl_loss', 'value': 0.81375}, {'tag': 'lr/pg0', 'value': 0.071179}, {'tag': 'lr/pg1', 'value': 0.0021793}, {'tag': 'lr/pg2', 'value': 0.0021793}], [{'tag': 'epoch', 'value': 16.0}, {'tag': 'train/box_loss', 'value': 0.69685}, {'tag': 'train/cls_loss', 'value': 1.5918}, {'tag': 'train/dfl_loss', 'value': 0.93667}, {'tag': 'metrics/precision(B)', 'value': 0.00336}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.8569}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.68663}, {'tag': 'val/box_loss', 'value': 0.58732}, {'tag': 'val/cls_loss', 'value': 3.2442}, {'tag': 'val/dfl_loss', 'value': 0.8026}, {'tag': 'lr/pg0', 'value': 0.069255}, {'tag': 'lr/pg1', 'value': 0.0022546}, {'tag': 'lr/pg2', 'value': 0.0022546}], [{'tag': 'epoch', 'value': 17.0}, {'tag': 'train/box_loss', 'value': 0.63334}, {'tag': 'train/cls_loss', 'value': 1.4425}, {'tag': 'train/dfl_loss', 'value': 0.86646}, {'tag': 'metrics/precision(B)', 'value': 0.00339}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.87667}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.73053}, {'tag': 'val/box_loss', 'value': 0.50378}, {'tag': 'val/cls_loss', 'value': 3.2284}, {'tag': 'val/dfl_loss', 'value': 0.8031}, {'tag': 'lr/pg0', 'value': 0.067322}, {'tag': 'lr/pg1', 'value': 0.0023219}, {'tag': 'lr/pg2', 'value': 0.0023219}], [{'tag': 'epoch', 'value': 18.0}, {'tag': 'train/box_loss', 'value': 0.53245}, {'tag': 'train/cls_loss', 'value': 1.4508}, {'tag': 'train/dfl_loss', 'value': 0.80017}, {'tag': 'metrics/precision(B)', 'value': 0.0034}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.86682}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.71193}, {'tag': 'val/box_loss', 'value': 0.5868}, {'tag': 'val/cls_loss', 'value': 3.2135}, {'tag': 'val/dfl_loss', 'value': 0.81075}, {'tag': 'lr/pg0', 'value': 0.065381}, {'tag': 'lr/pg1', 'value': 0.0023813}, {'tag': 'lr/pg2', 'value': 0.0023813}], [{'tag': 'epoch', 'value': 19.0}, {'tag': 'train/box_loss', 'value': 0.58909}, {'tag': 'train/cls_loss', 'value': 1.3975}, {'tag': 'train/dfl_loss', 'value': 0.86834}, {'tag': 'metrics/precision(B)', 'value': 0.00346}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.87881}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.73247}, {'tag': 'val/box_loss', 'value': 0.60195}, {'tag': 'val/cls_loss', 'value': 3.237}, {'tag': 'val/dfl_loss', 'value': 0.81828}, {'tag': 'lr/pg0', 'value': 0.063433}, {'tag': 'lr/pg1', 'value': 0.0024328}, {'tag': 'lr/pg2', 'value': 0.0024328}], [{'tag': 'epoch', 'value': 20.0}, {'tag': 'train/box_loss', 'value': 0.53003}, {'tag': 'train/cls_loss', 'value': 1.2732}, {'tag': 'train/dfl_loss', 'value': 0.80269}, {'tag': 'metrics/precision(B)', 'value': 0.00371}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.95167}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.83357}, {'tag': 'val/box_loss', 'value': 0.50689}, {'tag': 'val/cls_loss', 'value': 3.202}, {'tag': 'val/dfl_loss', 'value': 0.8019}, {'tag': 'lr/pg0', 'value': 0.061476}, {'tag': 'lr/pg1', 'value': 0.0024764}, {'tag': 'lr/pg2', 'value': 0.0024764}], [{'tag': 'epoch', 'value': 21.0}, {'tag': 'train/box_loss', 'value': 0.69022}, {'tag': 'train/cls_loss', 'value': 1.2731}, {'tag': 'train/dfl_loss', 'value': 0.89605}, {'tag': 'metrics/precision(B)', 'value': 0.00391}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.94833}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.78659}, {'tag': 'val/box_loss', 'value': 0.60027}, {'tag': 'val/cls_loss', 'value': 3.2329}, {'tag': 'val/dfl_loss', 'value': 0.82252}, {'tag': 'lr/pg0', 'value': 0.059512}, {'tag': 'lr/pg1', 'value': 0.0025121}, {'tag': 'lr/pg2', 'value': 0.0025121}], [{'tag': 'epoch', 'value': 22.0}, {'tag': 'train/box_loss', 'value': 0.68866}, {'tag': 'train/cls_loss', 'value': 1.321}, {'tag': 'train/dfl_loss', 'value': 0.89818}, {'tag': 'metrics/precision(B)', 'value': 0.00383}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.97227}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.83799}, {'tag': 'val/box_loss', 'value': 0.56671}, {'tag': 'val/cls_loss', 'value': 3.2398}, {'tag': 'val/dfl_loss', 'value': 0.8096}, {'tag': 'lr/pg0', 'value': 0.05754}, {'tag': 'lr/pg1', 'value': 0.0025398}, {'tag': 'lr/pg2', 'value': 0.0025398}], [{'tag': 'epoch', 'value': 23.0}, {'tag': 'train/box_loss', 'value': 0.64262}, {'tag': 'train/cls_loss', 'value': 1.1323}, {'tag': 'train/dfl_loss', 'value': 0.91579}, {'tag': 'metrics/precision(B)', 'value': 0.0037}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.95864}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.80125}, {'tag': 'val/box_loss', 'value': 0.53914}, {'tag': 'val/cls_loss', 'value': 3.2466}, {'tag': 'val/dfl_loss', 'value': 0.80866}, {'tag': 'lr/pg0', 'value': 0.05556}, {'tag': 'lr/pg1', 'value': 0.0025596}, {'tag': 'lr/pg2', 'value': 0.0025596}], [{'tag': 'epoch', 'value': 24.0}, {'tag': 'train/box_loss', 'value': 0.60471}, {'tag': 'train/cls_loss', 'value': 1.1004}, {'tag': 'train/dfl_loss', 'value': 0.86974}, {'tag': 'metrics/precision(B)', 'value': 0.00355}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.99045}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.79496}, {'tag': 'val/box_loss', 'value': 0.6285}, {'tag': 'val/cls_loss', 'value': 3.173}, {'tag': 'val/dfl_loss', 'value': 0.81681}, {'tag': 'lr/pg0', 'value': 0.053572}, {'tag': 'lr/pg1', 'value': 0.0025715}, {'tag': 'lr/pg2', 'value': 0.0025715}], [{'tag': 'epoch', 'value': 25.0}, {'tag': 'train/box_loss', 'value': 0.60922}, {'tag': 'train/cls_loss', 'value': 1.0412}, {'tag': 'train/dfl_loss', 'value': 0.87879}, {'tag': 'metrics/precision(B)', 'value': 0.00349}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.97682}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.83378}, {'tag': 'val/box_loss', 'value': 0.58855}, {'tag': 'val/cls_loss', 'value': 3.1961}, {'tag': 'val/dfl_loss', 'value': 0.81326}, {'tag': 'lr/pg0', 'value': 0.051576}, {'tag': 'lr/pg1', 'value': 0.0025755}, {'tag': 'lr/pg2', 'value': 0.0025755}], [{'tag': 'epoch', 'value': 26.0}, {'tag': 'train/box_loss', 'value': 0.58924}, {'tag': 'train/cls_loss', 'value': 1.0289}, {'tag': 'train/dfl_loss', 'value': 0.82589}, {'tag': 'metrics/precision(B)', 'value': 0.0034}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.98136}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.82034}, {'tag': 'val/box_loss', 'value': 0.64944}, {'tag': 'val/cls_loss', 'value': 3.1635}, {'tag': 'val/dfl_loss', 'value': 0.81535}, {'tag': 'lr/pg0', 'value': 0.049572}, {'tag': 'lr/pg1', 'value': 0.0025716}, {'tag': 'lr/pg2', 'value': 0.0025716}], [{'tag': 'epoch', 'value': 27.0}, {'tag': 'train/box_loss', 'value': 0.57216}, {'tag': 'train/cls_loss', 'value': 0.96613}, {'tag': 'train/dfl_loss', 'value': 0.87305}, {'tag': 'metrics/precision(B)', 'value': 0.00338}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.84577}, {'tag': 'val/box_loss', 'value': 0.56407}, {'tag': 'val/cls_loss', 'value': 3.0513}, {'tag': 'val/dfl_loss', 'value': 0.8024}, {'tag': 'lr/pg0', 'value': 0.04756}, {'tag': 'lr/pg1', 'value': 0.0025597}, {'tag': 'lr/pg2', 'value': 0.0025597}], [{'tag': 'epoch', 'value': 28.0}, {'tag': 'train/box_loss', 'value': 0.53161}, {'tag': 'train/cls_loss', 'value': 0.96257}, {'tag': 'train/dfl_loss', 'value': 0.82785}, {'tag': 'metrics/precision(B)', 'value': 0.00336}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.9699}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.82215}, {'tag': 'val/box_loss', 'value': 0.58077}, {'tag': 'val/cls_loss', 'value': 3.0708}, {'tag': 'val/dfl_loss', 'value': 0.80563}, {'tag': 'lr/pg0', 'value': 0.04554}, {'tag': 'lr/pg1', 'value': 0.0025399}, {'tag': 'lr/pg2', 'value': 0.0025399}], [{'tag': 'epoch', 'value': 29.0}, {'tag': 'train/box_loss', 'value': 0.59106}, {'tag': 'train/cls_loss', 'value': 0.95372}, {'tag': 'train/dfl_loss', 'value': 0.8898}, {'tag': 'metrics/precision(B)', 'value': 0.00363}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.97761}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.82256}, {'tag': 'val/box_loss', 'value': 0.63684}, {'tag': 'val/cls_loss', 'value': 2.9952}, {'tag': 'val/dfl_loss', 'value': 0.81421}, {'tag': 'lr/pg0', 'value': 0.043512}, {'tag': 'lr/pg1', 'value': 0.0025122}, {'tag': 'lr/pg2', 'value': 0.0025122}], [{'tag': 'epoch', 'value': 30.0}, {'tag': 'train/box_loss', 'value': 0.54118}, {'tag': 'train/cls_loss', 'value': 0.99789}, {'tag': 'train/dfl_loss', 'value': 0.82375}, {'tag': 'metrics/precision(B)', 'value': 0.00342}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.85187}, {'tag': 'val/box_loss', 'value': 0.5704}, {'tag': 'val/cls_loss', 'value': 2.8481}, {'tag': 'val/dfl_loss', 'value': 0.80421}, {'tag': 'lr/pg0', 'value': 0.041477}, {'tag': 'lr/pg1', 'value': 0.0024766}, {'tag': 'lr/pg2', 'value': 0.0024766}], [{'tag': 'epoch', 'value': 31.0}, {'tag': 'train/box_loss', 'value': 0.5441}, {'tag': 'train/cls_loss', 'value': 0.84697}, {'tag': 'train/dfl_loss', 'value': 0.83413}, {'tag': 'metrics/precision(B)', 'value': 0.00339}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.80418}, {'tag': 'val/box_loss', 'value': 0.65833}, {'tag': 'val/cls_loss', 'value': 2.6579}, {'tag': 'val/dfl_loss', 'value': 0.81958}, {'tag': 'lr/pg0', 'value': 0.039433}, {'tag': 'lr/pg1', 'value': 0.0024331}, {'tag': 'lr/pg2', 'value': 0.0024331}], [{'tag': 'epoch', 'value': 32.0}, {'tag': 'train/box_loss', 'value': 0.54969}, {'tag': 'train/cls_loss', 'value': 0.87359}, {'tag': 'train/dfl_loss', 'value': 0.80767}, {'tag': 'metrics/precision(B)', 'value': 0.00334}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.85862}, {'tag': 'val/box_loss', 'value': 0.53264}, {'tag': 'val/cls_loss', 'value': 2.622}, {'tag': 'val/dfl_loss', 'value': 0.7936}, {'tag': 'lr/pg0', 'value': 0.037382}, {'tag': 'lr/pg1', 'value': 0.0023816}, {'tag': 'lr/pg2', 'value': 0.0023816}], [{'tag': 'epoch', 'value': 33.0}, {'tag': 'train/box_loss', 'value': 0.494}, {'tag': 'train/cls_loss', 'value': 0.80329}, {'tag': 'train/dfl_loss', 'value': 0.81615}, {'tag': 'metrics/precision(B)', 'value': 0.00353}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.87549}, {'tag': 'val/box_loss', 'value': 0.52511}, {'tag': 'val/cls_loss', 'value': 2.6191}, {'tag': 'val/dfl_loss', 'value': 0.78882}, {'tag': 'lr/pg0', 'value': 0.035322}, {'tag': 'lr/pg1', 'value': 0.0023222}, {'tag': 'lr/pg2', 'value': 0.0023222}], [{'tag': 'epoch', 'value': 34.0}, {'tag': 'train/box_loss', 'value': 0.57125}, {'tag': 'train/cls_loss', 'value': 0.83759}, {'tag': 'train/dfl_loss', 'value': 0.85834}, {'tag': 'metrics/precision(B)', 'value': 0.97521}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.81067}, {'tag': 'val/box_loss', 'value': 0.63479}, {'tag': 'val/cls_loss', 'value': 2.5756}, {'tag': 'val/dfl_loss', 'value': 0.80614}, {'tag': 'lr/pg0', 'value': 0.033255}, {'tag': 'lr/pg1', 'value': 0.0022549}, {'tag': 'lr/pg2', 'value': 0.0022549}], [{'tag': 'epoch', 'value': 35.0}, {'tag': 'train/box_loss', 'value': 0.5074}, {'tag': 'train/cls_loss', 'value': 0.77593}, {'tag': 'train/dfl_loss', 'value': 0.84894}, {'tag': 'metrics/precision(B)', 'value': 1.0}, {'tag': 'metrics/recall(B)', 'value': 0.55576}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.84226}, {'tag': 'val/box_loss', 'value': 0.59675}, {'tag': 'val/cls_loss', 'value': 2.3746}, {'tag': 'val/dfl_loss', 'value': 0.79787}, {'tag': 'lr/pg0', 'value': 0.03118}, {'tag': 'lr/pg1', 'value': 0.0021797}, {'tag': 'lr/pg2', 'value': 0.0021797}], [{'tag': 'epoch', 'value': 36.0}, {'tag': 'train/box_loss', 'value': 0.5478}, {'tag': 'train/cls_loss', 'value': 0.9739}, {'tag': 'train/dfl_loss', 'value': 0.8804}, {'tag': 'metrics/precision(B)', 'value': 0.00335}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.88408}, {'tag': 'val/box_loss', 'value': 0.49261}, {'tag': 'val/cls_loss', 'value': 2.5684}, {'tag': 'val/dfl_loss', 'value': 0.7895}, {'tag': 'lr/pg0', 'value': 0.029097}, {'tag': 'lr/pg1', 'value': 0.0020966}, {'tag': 'lr/pg2', 'value': 0.0020966}], [{'tag': 'epoch', 'value': 37.0}, {'tag': 'train/box_loss', 'value': 0.5109}, {'tag': 'train/cls_loss', 'value': 0.79298}, {'tag': 'train/dfl_loss', 'value': 0.81025}, {'tag': 'metrics/precision(B)', 'value': 0.94683}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.87914}, {'tag': 'val/box_loss', 'value': 0.53933}, {'tag': 'val/cls_loss', 'value': 2.4032}, {'tag': 'val/dfl_loss', 'value': 0.79472}, {'tag': 'lr/pg0', 'value': 0.027006}, {'tag': 'lr/pg1', 'value': 0.0020055}, {'tag': 'lr/pg2', 'value': 0.0020055}], [{'tag': 'epoch', 'value': 38.0}, {'tag': 'train/box_loss', 'value': 0.5767}, {'tag': 'train/cls_loss', 'value': 0.86935}, {'tag': 'train/dfl_loss', 'value': 0.87058}, {'tag': 'metrics/precision(B)', 'value': 0.98576}, {'tag': 'metrics/recall(B)', 'value': 0.83699}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.87418}, {'tag': 'val/box_loss', 'value': 0.59056}, {'tag': 'val/cls_loss', 'value': 2.3744}, {'tag': 'val/dfl_loss', 'value': 0.79638}, {'tag': 'lr/pg0', 'value': 0.024907}, {'tag': 'lr/pg1', 'value': 0.0019065}, {'tag': 'lr/pg2', 'value': 0.0019065}], [{'tag': 'epoch', 'value': 39.0}, {'tag': 'train/box_loss', 'value': 0.59383}, {'tag': 'train/cls_loss', 'value': 0.80533}, {'tag': 'train/dfl_loss', 'value': 0.87874}, {'tag': 'metrics/precision(B)', 'value': 1.0}, {'tag': 'metrics/recall(B)', 'value': 0.4442}, {'tag': 'metrics/mAP50(B)', 'value': 0.99045}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.88933}, {'tag': 'val/box_loss', 'value': 0.58402}, {'tag': 'val/cls_loss', 'value': 2.2775}, {'tag': 'val/dfl_loss', 'value': 0.81}, {'tag': 'lr/pg0', 'value': 0.0228}, {'tag': 'lr/pg1', 'value': 0.0017996}, {'tag': 'lr/pg2', 'value': 0.0017996}], [{'tag': 'epoch', 'value': 40.0}, {'tag': 'train/box_loss', 'value': 0.4485}, {'tag': 'train/cls_loss', 'value': 0.84811}, {'tag': 'train/dfl_loss', 'value': 0.81296}, {'tag': 'metrics/precision(B)', 'value': 1.0}, {'tag': 'metrics/recall(B)', 'value': 0.35018}, {'tag': 'metrics/mAP50(B)', 'value': 0.97167}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.8598}, {'tag': 'val/box_loss', 'value': 0.58368}, {'tag': 'val/cls_loss', 'value': 2.2709}, {'tag': 'val/dfl_loss', 'value': 0.81143}, {'tag': 'lr/pg0', 'value': 0.020685}, {'tag': 'lr/pg1', 'value': 0.0016848}, {'tag': 'lr/pg2', 'value': 0.0016848}], [{'tag': 'epoch', 'value': 41.0}, {'tag': 'train/box_loss', 'value': 0.5216}, {'tag': 'train/cls_loss', 'value': 0.7309}, {'tag': 'train/dfl_loss', 'value': 0.8386}, {'tag': 'metrics/precision(B)', 'value': 1.0}, {'tag': 'metrics/recall(B)', 'value': 0.56993}, {'tag': 'metrics/mAP50(B)', 'value': 0.98136}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.88798}, {'tag': 'val/box_loss', 'value': 0.56186}, {'tag': 'val/cls_loss', 'value': 2.1034}, {'tag': 'val/dfl_loss', 'value': 0.80235}, {'tag': 'lr/pg0', 'value': 0.018562}, {'tag': 'lr/pg1', 'value': 0.0015621}, {'tag': 'lr/pg2', 'value': 0.0015621}], [{'tag': 'epoch', 'value': 42.0}, {'tag': 'train/box_loss', 'value': 0.46109}, {'tag': 'train/cls_loss', 'value': 0.75215}, {'tag': 'train/dfl_loss', 'value': 0.81637}, {'tag': 'metrics/precision(B)', 'value': 0.94392}, {'tag': 'metrics/recall(B)', 'value': 0.61791}, {'tag': 'metrics/mAP50(B)', 'value': 0.98136}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.85015}, {'tag': 'val/box_loss', 'value': 0.64211}, {'tag': 'val/cls_loss', 'value': 1.9825}, {'tag': 'val/dfl_loss', 'value': 0.81823}, {'tag': 'lr/pg0', 'value': 0.016431}, {'tag': 'lr/pg1', 'value': 0.0014314}, {'tag': 'lr/pg2', 'value': 0.0014314}], [{'tag': 'epoch', 'value': 43.0}, {'tag': 'train/box_loss', 'value': 0.47991}, {'tag': 'train/cls_loss', 'value': 0.84562}, {'tag': 'train/dfl_loss', 'value': 0.816}, {'tag': 'metrics/precision(B)', 'value': 0.96134}, {'tag': 'metrics/recall(B)', 'value': 0.72676}, {'tag': 'metrics/mAP50(B)', 'value': 0.98591}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.8781}, {'tag': 'val/box_loss', 'value': 0.55408}, {'tag': 'val/cls_loss', 'value': 1.8485}, {'tag': 'val/dfl_loss', 'value': 0.796}, {'tag': 'lr/pg0', 'value': 0.014293}, {'tag': 'lr/pg1', 'value': 0.0012928}, {'tag': 'lr/pg2', 'value': 0.0012928}], [{'tag': 'epoch', 'value': 44.0}, {'tag': 'train/box_loss', 'value': 0.42274}, {'tag': 'train/cls_loss', 'value': 0.67743}, {'tag': 'train/dfl_loss', 'value': 0.85156}, {'tag': 'metrics/precision(B)', 'value': 1.0}, {'tag': 'metrics/recall(B)', 'value': 0.68122}, {'tag': 'metrics/mAP50(B)', 'value': 0.98591}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.88629}, {'tag': 'val/box_loss', 'value': 0.59008}, {'tag': 'val/cls_loss', 'value': 1.8945}, {'tag': 'val/dfl_loss', 'value': 0.80049}, {'tag': 'lr/pg0', 'value': 0.012146}, {'tag': 'lr/pg1', 'value': 0.0011463}, {'tag': 'lr/pg2', 'value': 0.0011463}], [{'tag': 'epoch', 'value': 45.0}, {'tag': 'train/box_loss', 'value': 0.44008}, {'tag': 'train/cls_loss', 'value': 0.68818}, {'tag': 'train/dfl_loss', 'value': 0.79383}, {'tag': 'metrics/precision(B)', 'value': 1.0}, {'tag': 'metrics/recall(B)', 'value': 0.75958}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.90281}, {'tag': 'val/box_loss', 'value': 0.48885}, {'tag': 'val/cls_loss', 'value': 1.8046}, {'tag': 'val/dfl_loss', 'value': 0.78786}, {'tag': 'lr/pg0', 'value': 0.0099919}, {'tag': 'lr/pg1', 'value': 0.0009919}, {'tag': 'lr/pg2', 'value': 0.0009919}], [{'tag': 'epoch', 'value': 46.0}, {'tag': 'train/box_loss', 'value': 0.42351}, {'tag': 'train/cls_loss', 'value': 0.68141}, {'tag': 'train/dfl_loss', 'value': 0.81276}, {'tag': 'metrics/precision(B)', 'value': 1.0}, {'tag': 'metrics/recall(B)', 'value': 0.84113}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.90002}, {'tag': 'val/box_loss', 'value': 0.52886}, {'tag': 'val/cls_loss', 'value': 1.6638}, {'tag': 'val/dfl_loss', 'value': 0.79098}, {'tag': 'lr/pg0', 'value': 0.0078296}, {'tag': 'lr/pg1', 'value': 0.00082956}, {'tag': 'lr/pg2', 'value': 0.00082956}], [{'tag': 'epoch', 'value': 47.0}, {'tag': 'train/box_loss', 'value': 0.43221}, {'tag': 'train/cls_loss', 'value': 0.68535}, {'tag': 'train/dfl_loss', 'value': 0.81431}, {'tag': 'metrics/precision(B)', 'value': 0.99289}, {'tag': 'metrics/recall(B)', 'value': 0.97043}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.90593}, {'tag': 'val/box_loss', 'value': 0.48647}, {'tag': 'val/cls_loss', 'value': 1.5789}, {'tag': 'val/dfl_loss', 'value': 0.78382}, {'tag': 'lr/pg0', 'value': 0.0056593}, {'tag': 'lr/pg1', 'value': 0.0006593}, {'tag': 'lr/pg2', 'value': 0.0006593}], [{'tag': 'epoch', 'value': 48.0}, {'tag': 'train/box_loss', 'value': 0.39935}, {'tag': 'train/cls_loss', 'value': 0.66413}, {'tag': 'train/dfl_loss', 'value': 0.80588}, {'tag': 'metrics/precision(B)', 'value': 0.99488}, {'tag': 'metrics/recall(B)', 'value': 0.98173}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.8921}, {'tag': 'val/box_loss', 'value': 0.50336}, {'tag': 'val/cls_loss', 'value': 1.557}, {'tag': 'val/dfl_loss', 'value': 0.78832}, {'tag': 'lr/pg0', 'value': 0.0034811}, {'tag': 'lr/pg1', 'value': 0.00048112}, {'tag': 'lr/pg2', 'value': 0.00048112}], [{'tag': 'epoch', 'value': 49.0}, {'tag': 'train/box_loss', 'value': 0.41614}, {'tag': 'train/cls_loss', 'value': 0.62133}, {'tag': 'train/dfl_loss', 'value': 0.809}, {'tag': 'metrics/precision(B)', 'value': 0.99142}, {'tag': 'metrics/recall(B)', 'value': 1.0}, {'tag': 'metrics/mAP50(B)', 'value': 0.995}, {'tag': 'metrics/mAP50-95(B)', 'value': 0.9074}, {'tag': 'val/box_loss', 'value': 0.49075}, {'tag': 'val/cls_loss', 'value': 1.4943}, {'tag': 'val/dfl_loss', 'value': 0.78682}, {'tag': 'lr/pg0', 'value': 0.001295}, {'tag': 'lr/pg1', 'value': 0.00029502}, {'tag': 'lr/pg2', 'value': 0.00029502}]], eval_metrics=[{'tag': 'mAP', 'value': 0.3143564462661743}])
In [8]:
Copied!
hub.get_metrics()
hub.get_metrics()
Out[8]:
[[{'tag': 'epoch', 'value': 0.0},
{'tag': 'train/box_loss', 'value': 1.3501},
{'tag': 'train/cls_loss', 'value': 4.6464},
{'tag': 'train/dfl_loss', 'value': 1.0351},
{'tag': 'metrics/precision(B)', 'value': 0.00268},
{'tag': 'metrics/recall(B)', 'value': 0.8},
{'tag': 'metrics/mAP50(B)', 'value': 0.27948},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.22095},
{'tag': 'val/box_loss', 'value': 0.43408},
{'tag': 'val/cls_loss', 'value': 3.8634},
{'tag': 'val/dfl_loss', 'value': 0.82598},
{'tag': 'lr/pg0', 'value': 0.0991},
{'tag': 'lr/pg1', 'value': 0.0001},
{'tag': 'lr/pg2', 'value': 0.0001}],
[{'tag': 'epoch', 'value': 1.0},
{'tag': 'train/box_loss', 'value': 1.5745},
{'tag': 'train/cls_loss', 'value': 5.0921},
{'tag': 'train/dfl_loss', 'value': 1.1791},
{'tag': 'metrics/precision(B)', 'value': 0.00301},
{'tag': 'metrics/recall(B)', 'value': 0.9},
{'tag': 'metrics/mAP50(B)', 'value': 0.28713},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.23503},
{'tag': 'val/box_loss', 'value': 0.42816},
{'tag': 'val/cls_loss', 'value': 3.8297},
{'tag': 'val/dfl_loss', 'value': 0.81922},
{'tag': 'lr/pg0', 'value': 0.097294},
{'tag': 'lr/pg1', 'value': 0.00029406},
{'tag': 'lr/pg2', 'value': 0.00029406}],
[{'tag': 'epoch', 'value': 2.0},
{'tag': 'train/box_loss', 'value': 1.4092},
{'tag': 'train/cls_loss', 'value': 4.601},
{'tag': 'train/dfl_loss', 'value': 1.0856},
{'tag': 'metrics/precision(B)', 'value': 0.00318},
{'tag': 'metrics/recall(B)', 'value': 0.95},
{'tag': 'metrics/mAP50(B)', 'value': 0.29955},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.2428},
{'tag': 'val/box_loss', 'value': 0.44174},
{'tag': 'val/cls_loss', 'value': 3.8018},
{'tag': 'val/dfl_loss', 'value': 0.80306},
{'tag': 'lr/pg0', 'value': 0.09548},
{'tag': 'lr/pg1', 'value': 0.0004802},
{'tag': 'lr/pg2', 'value': 0.0004802}],
[{'tag': 'epoch', 'value': 3.0},
{'tag': 'train/box_loss', 'value': 1.3949},
{'tag': 'train/cls_loss', 'value': 4.7847},
{'tag': 'train/dfl_loss', 'value': 1.0853},
{'tag': 'metrics/precision(B)', 'value': 0.00317},
{'tag': 'metrics/recall(B)', 'value': 0.95},
{'tag': 'metrics/mAP50(B)', 'value': 0.30017},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.25635},
{'tag': 'val/box_loss', 'value': 0.4457},
{'tag': 'val/cls_loss', 'value': 3.7635},
{'tag': 'val/dfl_loss', 'value': 0.79997},
{'tag': 'lr/pg0', 'value': 0.093658},
{'tag': 'lr/pg1', 'value': 0.00065842},
{'tag': 'lr/pg2', 'value': 0.00065842}],
[{'tag': 'epoch', 'value': 4.0},
{'tag': 'train/box_loss', 'value': 1.4621},
{'tag': 'train/cls_loss', 'value': 4.5888},
{'tag': 'train/dfl_loss', 'value': 1.0952},
{'tag': 'metrics/precision(B)', 'value': 0.00317},
{'tag': 'metrics/recall(B)', 'value': 0.95},
{'tag': 'metrics/mAP50(B)', 'value': 0.29295},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.2701},
{'tag': 'val/box_loss', 'value': 0.43005},
{'tag': 'val/cls_loss', 'value': 3.7548},
{'tag': 'val/dfl_loss', 'value': 0.80128},
{'tag': 'lr/pg0', 'value': 0.091829},
{'tag': 'lr/pg1', 'value': 0.00082872},
{'tag': 'lr/pg2', 'value': 0.00082872}],
[{'tag': 'epoch', 'value': 5.0},
{'tag': 'train/box_loss', 'value': 1.3964},
{'tag': 'train/cls_loss', 'value': 4.9783},
{'tag': 'train/dfl_loss', 'value': 1.0798},
{'tag': 'metrics/precision(B)', 'value': 0.00333},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.29703},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.24147},
{'tag': 'val/box_loss', 'value': 0.41959},
{'tag': 'val/cls_loss', 'value': 3.7923},
{'tag': 'val/dfl_loss', 'value': 0.8005},
{'tag': 'lr/pg0', 'value': 0.089991},
{'tag': 'lr/pg1', 'value': 0.0009911},
{'tag': 'lr/pg2', 'value': 0.0009911}],
[{'tag': 'epoch', 'value': 6.0},
{'tag': 'train/box_loss', 'value': 1.2091},
{'tag': 'train/cls_loss', 'value': 4.5448},
{'tag': 'train/dfl_loss', 'value': 0.99952},
{'tag': 'metrics/precision(B)', 'value': 0.00337},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.2619},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.21933},
{'tag': 'val/box_loss', 'value': 0.42009},
{'tag': 'val/cls_loss', 'value': 3.8168},
{'tag': 'val/dfl_loss', 'value': 0.81327},
{'tag': 'lr/pg0', 'value': 0.088146},
{'tag': 'lr/pg1', 'value': 0.0011456},
{'tag': 'lr/pg2', 'value': 0.0011456}],
[{'tag': 'epoch', 'value': 7.0},
{'tag': 'train/box_loss', 'value': 0.98263},
{'tag': 'train/cls_loss', 'value': 4.3317},
{'tag': 'train/dfl_loss', 'value': 0.94503},
{'tag': 'metrics/precision(B)', 'value': 0.00337},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.23364},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.21407},
{'tag': 'val/box_loss', 'value': 0.49657},
{'tag': 'val/cls_loss', 'value': 3.792},
{'tag': 'val/dfl_loss', 'value': 0.82097},
{'tag': 'lr/pg0', 'value': 0.086292},
{'tag': 'lr/pg1', 'value': 0.0012921},
{'tag': 'lr/pg2', 'value': 0.0012921}],
[{'tag': 'epoch', 'value': 8.0},
{'tag': 'train/box_loss', 'value': 0.65743},
{'tag': 'train/cls_loss', 'value': 4.0554},
{'tag': 'train/dfl_loss', 'value': 0.84959},
{'tag': 'metrics/precision(B)', 'value': 0.00333},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.38451},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.3307},
{'tag': 'val/box_loss', 'value': 0.58206},
{'tag': 'val/cls_loss', 'value': 3.7688},
{'tag': 'val/dfl_loss', 'value': 0.82093},
{'tag': 'lr/pg0', 'value': 0.084431},
{'tag': 'lr/pg1', 'value': 0.0014307},
{'tag': 'lr/pg2', 'value': 0.0014307}],
[{'tag': 'epoch', 'value': 9.0},
{'tag': 'train/box_loss', 'value': 0.63434},
{'tag': 'train/cls_loss', 'value': 3.8742},
{'tag': 'train/dfl_loss', 'value': 0.83304},
{'tag': 'metrics/precision(B)', 'value': 0.00337},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.515},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.45197},
{'tag': 'val/box_loss', 'value': 0.60736},
{'tag': 'val/cls_loss', 'value': 3.6357},
{'tag': 'val/dfl_loss', 'value': 0.81601},
{'tag': 'lr/pg0', 'value': 0.082561},
{'tag': 'lr/pg1', 'value': 0.0015614},
{'tag': 'lr/pg2', 'value': 0.0015614}],
[{'tag': 'epoch', 'value': 10.0},
{'tag': 'train/box_loss', 'value': 0.61282},
{'tag': 'train/cls_loss', 'value': 3.512},
{'tag': 'train/dfl_loss', 'value': 0.79209},
{'tag': 'metrics/precision(B)', 'value': 0.00339},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.60177},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.49371},
{'tag': 'val/box_loss', 'value': 0.64081},
{'tag': 'val/cls_loss', 'value': 3.4475},
{'tag': 'val/dfl_loss', 'value': 0.80918},
{'tag': 'lr/pg0', 'value': 0.080684},
{'tag': 'lr/pg1', 'value': 0.0016842},
{'tag': 'lr/pg2', 'value': 0.0016842}],
[{'tag': 'epoch', 'value': 11.0},
{'tag': 'train/box_loss', 'value': 0.67718},
{'tag': 'train/cls_loss', 'value': 2.9147},
{'tag': 'train/dfl_loss', 'value': 0.83244},
{'tag': 'metrics/precision(B)', 'value': 0.00338},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.69629},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.582},
{'tag': 'val/box_loss', 'value': 0.59014},
{'tag': 'val/cls_loss', 'value': 3.2775},
{'tag': 'val/dfl_loss', 'value': 0.78841},
{'tag': 'lr/pg0', 'value': 0.078799},
{'tag': 'lr/pg1', 'value': 0.0017991},
{'tag': 'lr/pg2', 'value': 0.0017991}],
[{'tag': 'epoch', 'value': 12.0},
{'tag': 'train/box_loss', 'value': 0.61112},
{'tag': 'train/cls_loss', 'value': 2.2224},
{'tag': 'train/dfl_loss', 'value': 0.86835},
{'tag': 'metrics/precision(B)', 'value': 0.0034},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.71624},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.60464},
{'tag': 'val/box_loss', 'value': 0.57163},
{'tag': 'val/cls_loss', 'value': 3.2206},
{'tag': 'val/dfl_loss', 'value': 0.79575},
{'tag': 'lr/pg0', 'value': 0.076906},
{'tag': 'lr/pg1', 'value': 0.001906},
{'tag': 'lr/pg2', 'value': 0.001906}],
[{'tag': 'epoch', 'value': 13.0},
{'tag': 'train/box_loss', 'value': 0.59459},
{'tag': 'train/cls_loss', 'value': 1.9712},
{'tag': 'train/dfl_loss', 'value': 0.80912},
{'tag': 'metrics/precision(B)', 'value': 0.00339},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.75376},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.59454},
{'tag': 'val/box_loss', 'value': 0.60448},
{'tag': 'val/cls_loss', 'value': 3.2301},
{'tag': 'val/dfl_loss', 'value': 0.79842},
{'tag': 'lr/pg0', 'value': 0.075005},
{'tag': 'lr/pg1', 'value': 0.002005},
{'tag': 'lr/pg2', 'value': 0.002005}],
[{'tag': 'epoch', 'value': 14.0},
{'tag': 'train/box_loss', 'value': 0.71785},
{'tag': 'train/cls_loss', 'value': 1.9547},
{'tag': 'train/dfl_loss', 'value': 0.98837},
{'tag': 'metrics/precision(B)', 'value': 0.0034},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.77386},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.65288},
{'tag': 'val/box_loss', 'value': 0.49612},
{'tag': 'val/cls_loss', 'value': 3.2141},
{'tag': 'val/dfl_loss', 'value': 0.79957},
{'tag': 'lr/pg0', 'value': 0.073096},
{'tag': 'lr/pg1', 'value': 0.0020961},
{'tag': 'lr/pg2', 'value': 0.0020961}],
[{'tag': 'epoch', 'value': 15.0},
{'tag': 'train/box_loss', 'value': 0.6793},
{'tag': 'train/cls_loss', 'value': 1.7516},
{'tag': 'train/dfl_loss', 'value': 0.86429},
{'tag': 'metrics/precision(B)', 'value': 0.00338},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.81266},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.69205},
{'tag': 'val/box_loss', 'value': 0.57349},
{'tag': 'val/cls_loss', 'value': 3.2207},
{'tag': 'val/dfl_loss', 'value': 0.81375},
{'tag': 'lr/pg0', 'value': 0.071179},
{'tag': 'lr/pg1', 'value': 0.0021793},
{'tag': 'lr/pg2', 'value': 0.0021793}],
[{'tag': 'epoch', 'value': 16.0},
{'tag': 'train/box_loss', 'value': 0.69685},
{'tag': 'train/cls_loss', 'value': 1.5918},
{'tag': 'train/dfl_loss', 'value': 0.93667},
{'tag': 'metrics/precision(B)', 'value': 0.00336},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.8569},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.68663},
{'tag': 'val/box_loss', 'value': 0.58732},
{'tag': 'val/cls_loss', 'value': 3.2442},
{'tag': 'val/dfl_loss', 'value': 0.8026},
{'tag': 'lr/pg0', 'value': 0.069255},
{'tag': 'lr/pg1', 'value': 0.0022546},
{'tag': 'lr/pg2', 'value': 0.0022546}],
[{'tag': 'epoch', 'value': 17.0},
{'tag': 'train/box_loss', 'value': 0.63334},
{'tag': 'train/cls_loss', 'value': 1.4425},
{'tag': 'train/dfl_loss', 'value': 0.86646},
{'tag': 'metrics/precision(B)', 'value': 0.00339},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.87667},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.73053},
{'tag': 'val/box_loss', 'value': 0.50378},
{'tag': 'val/cls_loss', 'value': 3.2284},
{'tag': 'val/dfl_loss', 'value': 0.8031},
{'tag': 'lr/pg0', 'value': 0.067322},
{'tag': 'lr/pg1', 'value': 0.0023219},
{'tag': 'lr/pg2', 'value': 0.0023219}],
[{'tag': 'epoch', 'value': 18.0},
{'tag': 'train/box_loss', 'value': 0.53245},
{'tag': 'train/cls_loss', 'value': 1.4508},
{'tag': 'train/dfl_loss', 'value': 0.80017},
{'tag': 'metrics/precision(B)', 'value': 0.0034},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.86682},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.71193},
{'tag': 'val/box_loss', 'value': 0.5868},
{'tag': 'val/cls_loss', 'value': 3.2135},
{'tag': 'val/dfl_loss', 'value': 0.81075},
{'tag': 'lr/pg0', 'value': 0.065381},
{'tag': 'lr/pg1', 'value': 0.0023813},
{'tag': 'lr/pg2', 'value': 0.0023813}],
[{'tag': 'epoch', 'value': 19.0},
{'tag': 'train/box_loss', 'value': 0.58909},
{'tag': 'train/cls_loss', 'value': 1.3975},
{'tag': 'train/dfl_loss', 'value': 0.86834},
{'tag': 'metrics/precision(B)', 'value': 0.00346},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.87881},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.73247},
{'tag': 'val/box_loss', 'value': 0.60195},
{'tag': 'val/cls_loss', 'value': 3.237},
{'tag': 'val/dfl_loss', 'value': 0.81828},
{'tag': 'lr/pg0', 'value': 0.063433},
{'tag': 'lr/pg1', 'value': 0.0024328},
{'tag': 'lr/pg2', 'value': 0.0024328}],
[{'tag': 'epoch', 'value': 20.0},
{'tag': 'train/box_loss', 'value': 0.53003},
{'tag': 'train/cls_loss', 'value': 1.2732},
{'tag': 'train/dfl_loss', 'value': 0.80269},
{'tag': 'metrics/precision(B)', 'value': 0.00371},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.95167},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.83357},
{'tag': 'val/box_loss', 'value': 0.50689},
{'tag': 'val/cls_loss', 'value': 3.202},
{'tag': 'val/dfl_loss', 'value': 0.8019},
{'tag': 'lr/pg0', 'value': 0.061476},
{'tag': 'lr/pg1', 'value': 0.0024764},
{'tag': 'lr/pg2', 'value': 0.0024764}],
[{'tag': 'epoch', 'value': 21.0},
{'tag': 'train/box_loss', 'value': 0.69022},
{'tag': 'train/cls_loss', 'value': 1.2731},
{'tag': 'train/dfl_loss', 'value': 0.89605},
{'tag': 'metrics/precision(B)', 'value': 0.00391},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.94833},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.78659},
{'tag': 'val/box_loss', 'value': 0.60027},
{'tag': 'val/cls_loss', 'value': 3.2329},
{'tag': 'val/dfl_loss', 'value': 0.82252},
{'tag': 'lr/pg0', 'value': 0.059512},
{'tag': 'lr/pg1', 'value': 0.0025121},
{'tag': 'lr/pg2', 'value': 0.0025121}],
[{'tag': 'epoch', 'value': 22.0},
{'tag': 'train/box_loss', 'value': 0.68866},
{'tag': 'train/cls_loss', 'value': 1.321},
{'tag': 'train/dfl_loss', 'value': 0.89818},
{'tag': 'metrics/precision(B)', 'value': 0.00383},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.97227},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.83799},
{'tag': 'val/box_loss', 'value': 0.56671},
{'tag': 'val/cls_loss', 'value': 3.2398},
{'tag': 'val/dfl_loss', 'value': 0.8096},
{'tag': 'lr/pg0', 'value': 0.05754},
{'tag': 'lr/pg1', 'value': 0.0025398},
{'tag': 'lr/pg2', 'value': 0.0025398}],
[{'tag': 'epoch', 'value': 23.0},
{'tag': 'train/box_loss', 'value': 0.64262},
{'tag': 'train/cls_loss', 'value': 1.1323},
{'tag': 'train/dfl_loss', 'value': 0.91579},
{'tag': 'metrics/precision(B)', 'value': 0.0037},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.95864},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.80125},
{'tag': 'val/box_loss', 'value': 0.53914},
{'tag': 'val/cls_loss', 'value': 3.2466},
{'tag': 'val/dfl_loss', 'value': 0.80866},
{'tag': 'lr/pg0', 'value': 0.05556},
{'tag': 'lr/pg1', 'value': 0.0025596},
{'tag': 'lr/pg2', 'value': 0.0025596}],
[{'tag': 'epoch', 'value': 24.0},
{'tag': 'train/box_loss', 'value': 0.60471},
{'tag': 'train/cls_loss', 'value': 1.1004},
{'tag': 'train/dfl_loss', 'value': 0.86974},
{'tag': 'metrics/precision(B)', 'value': 0.00355},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.99045},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.79496},
{'tag': 'val/box_loss', 'value': 0.6285},
{'tag': 'val/cls_loss', 'value': 3.173},
{'tag': 'val/dfl_loss', 'value': 0.81681},
{'tag': 'lr/pg0', 'value': 0.053572},
{'tag': 'lr/pg1', 'value': 0.0025715},
{'tag': 'lr/pg2', 'value': 0.0025715}],
[{'tag': 'epoch', 'value': 25.0},
{'tag': 'train/box_loss', 'value': 0.60922},
{'tag': 'train/cls_loss', 'value': 1.0412},
{'tag': 'train/dfl_loss', 'value': 0.87879},
{'tag': 'metrics/precision(B)', 'value': 0.00349},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.97682},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.83378},
{'tag': 'val/box_loss', 'value': 0.58855},
{'tag': 'val/cls_loss', 'value': 3.1961},
{'tag': 'val/dfl_loss', 'value': 0.81326},
{'tag': 'lr/pg0', 'value': 0.051576},
{'tag': 'lr/pg1', 'value': 0.0025755},
{'tag': 'lr/pg2', 'value': 0.0025755}],
[{'tag': 'epoch', 'value': 26.0},
{'tag': 'train/box_loss', 'value': 0.58924},
{'tag': 'train/cls_loss', 'value': 1.0289},
{'tag': 'train/dfl_loss', 'value': 0.82589},
{'tag': 'metrics/precision(B)', 'value': 0.0034},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.98136},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.82034},
{'tag': 'val/box_loss', 'value': 0.64944},
{'tag': 'val/cls_loss', 'value': 3.1635},
{'tag': 'val/dfl_loss', 'value': 0.81535},
{'tag': 'lr/pg0', 'value': 0.049572},
{'tag': 'lr/pg1', 'value': 0.0025716},
{'tag': 'lr/pg2', 'value': 0.0025716}],
[{'tag': 'epoch', 'value': 27.0},
{'tag': 'train/box_loss', 'value': 0.57216},
{'tag': 'train/cls_loss', 'value': 0.96613},
{'tag': 'train/dfl_loss', 'value': 0.87305},
{'tag': 'metrics/precision(B)', 'value': 0.00338},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.84577},
{'tag': 'val/box_loss', 'value': 0.56407},
{'tag': 'val/cls_loss', 'value': 3.0513},
{'tag': 'val/dfl_loss', 'value': 0.8024},
{'tag': 'lr/pg0', 'value': 0.04756},
{'tag': 'lr/pg1', 'value': 0.0025597},
{'tag': 'lr/pg2', 'value': 0.0025597}],
[{'tag': 'epoch', 'value': 28.0},
{'tag': 'train/box_loss', 'value': 0.53161},
{'tag': 'train/cls_loss', 'value': 0.96257},
{'tag': 'train/dfl_loss', 'value': 0.82785},
{'tag': 'metrics/precision(B)', 'value': 0.00336},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.9699},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.82215},
{'tag': 'val/box_loss', 'value': 0.58077},
{'tag': 'val/cls_loss', 'value': 3.0708},
{'tag': 'val/dfl_loss', 'value': 0.80563},
{'tag': 'lr/pg0', 'value': 0.04554},
{'tag': 'lr/pg1', 'value': 0.0025399},
{'tag': 'lr/pg2', 'value': 0.0025399}],
[{'tag': 'epoch', 'value': 29.0},
{'tag': 'train/box_loss', 'value': 0.59106},
{'tag': 'train/cls_loss', 'value': 0.95372},
{'tag': 'train/dfl_loss', 'value': 0.8898},
{'tag': 'metrics/precision(B)', 'value': 0.00363},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.97761},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.82256},
{'tag': 'val/box_loss', 'value': 0.63684},
{'tag': 'val/cls_loss', 'value': 2.9952},
{'tag': 'val/dfl_loss', 'value': 0.81421},
{'tag': 'lr/pg0', 'value': 0.043512},
{'tag': 'lr/pg1', 'value': 0.0025122},
{'tag': 'lr/pg2', 'value': 0.0025122}],
[{'tag': 'epoch', 'value': 30.0},
{'tag': 'train/box_loss', 'value': 0.54118},
{'tag': 'train/cls_loss', 'value': 0.99789},
{'tag': 'train/dfl_loss', 'value': 0.82375},
{'tag': 'metrics/precision(B)', 'value': 0.00342},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.85187},
{'tag': 'val/box_loss', 'value': 0.5704},
{'tag': 'val/cls_loss', 'value': 2.8481},
{'tag': 'val/dfl_loss', 'value': 0.80421},
{'tag': 'lr/pg0', 'value': 0.041477},
{'tag': 'lr/pg1', 'value': 0.0024766},
{'tag': 'lr/pg2', 'value': 0.0024766}],
[{'tag': 'epoch', 'value': 31.0},
{'tag': 'train/box_loss', 'value': 0.5441},
{'tag': 'train/cls_loss', 'value': 0.84697},
{'tag': 'train/dfl_loss', 'value': 0.83413},
{'tag': 'metrics/precision(B)', 'value': 0.00339},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.80418},
{'tag': 'val/box_loss', 'value': 0.65833},
{'tag': 'val/cls_loss', 'value': 2.6579},
{'tag': 'val/dfl_loss', 'value': 0.81958},
{'tag': 'lr/pg0', 'value': 0.039433},
{'tag': 'lr/pg1', 'value': 0.0024331},
{'tag': 'lr/pg2', 'value': 0.0024331}],
[{'tag': 'epoch', 'value': 32.0},
{'tag': 'train/box_loss', 'value': 0.54969},
{'tag': 'train/cls_loss', 'value': 0.87359},
{'tag': 'train/dfl_loss', 'value': 0.80767},
{'tag': 'metrics/precision(B)', 'value': 0.00334},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.85862},
{'tag': 'val/box_loss', 'value': 0.53264},
{'tag': 'val/cls_loss', 'value': 2.622},
{'tag': 'val/dfl_loss', 'value': 0.7936},
{'tag': 'lr/pg0', 'value': 0.037382},
{'tag': 'lr/pg1', 'value': 0.0023816},
{'tag': 'lr/pg2', 'value': 0.0023816}],
[{'tag': 'epoch', 'value': 33.0},
{'tag': 'train/box_loss', 'value': 0.494},
{'tag': 'train/cls_loss', 'value': 0.80329},
{'tag': 'train/dfl_loss', 'value': 0.81615},
{'tag': 'metrics/precision(B)', 'value': 0.00353},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.87549},
{'tag': 'val/box_loss', 'value': 0.52511},
{'tag': 'val/cls_loss', 'value': 2.6191},
{'tag': 'val/dfl_loss', 'value': 0.78882},
{'tag': 'lr/pg0', 'value': 0.035322},
{'tag': 'lr/pg1', 'value': 0.0023222},
{'tag': 'lr/pg2', 'value': 0.0023222}],
[{'tag': 'epoch', 'value': 34.0},
{'tag': 'train/box_loss', 'value': 0.57125},
{'tag': 'train/cls_loss', 'value': 0.83759},
{'tag': 'train/dfl_loss', 'value': 0.85834},
{'tag': 'metrics/precision(B)', 'value': 0.97521},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.81067},
{'tag': 'val/box_loss', 'value': 0.63479},
{'tag': 'val/cls_loss', 'value': 2.5756},
{'tag': 'val/dfl_loss', 'value': 0.80614},
{'tag': 'lr/pg0', 'value': 0.033255},
{'tag': 'lr/pg1', 'value': 0.0022549},
{'tag': 'lr/pg2', 'value': 0.0022549}],
[{'tag': 'epoch', 'value': 35.0},
{'tag': 'train/box_loss', 'value': 0.5074},
{'tag': 'train/cls_loss', 'value': 0.77593},
{'tag': 'train/dfl_loss', 'value': 0.84894},
{'tag': 'metrics/precision(B)', 'value': 1.0},
{'tag': 'metrics/recall(B)', 'value': 0.55576},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.84226},
{'tag': 'val/box_loss', 'value': 0.59675},
{'tag': 'val/cls_loss', 'value': 2.3746},
{'tag': 'val/dfl_loss', 'value': 0.79787},
{'tag': 'lr/pg0', 'value': 0.03118},
{'tag': 'lr/pg1', 'value': 0.0021797},
{'tag': 'lr/pg2', 'value': 0.0021797}],
[{'tag': 'epoch', 'value': 36.0},
{'tag': 'train/box_loss', 'value': 0.5478},
{'tag': 'train/cls_loss', 'value': 0.9739},
{'tag': 'train/dfl_loss', 'value': 0.8804},
{'tag': 'metrics/precision(B)', 'value': 0.00335},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.88408},
{'tag': 'val/box_loss', 'value': 0.49261},
{'tag': 'val/cls_loss', 'value': 2.5684},
{'tag': 'val/dfl_loss', 'value': 0.7895},
{'tag': 'lr/pg0', 'value': 0.029097},
{'tag': 'lr/pg1', 'value': 0.0020966},
{'tag': 'lr/pg2', 'value': 0.0020966}],
[{'tag': 'epoch', 'value': 37.0},
{'tag': 'train/box_loss', 'value': 0.5109},
{'tag': 'train/cls_loss', 'value': 0.79298},
{'tag': 'train/dfl_loss', 'value': 0.81025},
{'tag': 'metrics/precision(B)', 'value': 0.94683},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.87914},
{'tag': 'val/box_loss', 'value': 0.53933},
{'tag': 'val/cls_loss', 'value': 2.4032},
{'tag': 'val/dfl_loss', 'value': 0.79472},
{'tag': 'lr/pg0', 'value': 0.027006},
{'tag': 'lr/pg1', 'value': 0.0020055},
{'tag': 'lr/pg2', 'value': 0.0020055}],
[{'tag': 'epoch', 'value': 38.0},
{'tag': 'train/box_loss', 'value': 0.5767},
{'tag': 'train/cls_loss', 'value': 0.86935},
{'tag': 'train/dfl_loss', 'value': 0.87058},
{'tag': 'metrics/precision(B)', 'value': 0.98576},
{'tag': 'metrics/recall(B)', 'value': 0.83699},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.87418},
{'tag': 'val/box_loss', 'value': 0.59056},
{'tag': 'val/cls_loss', 'value': 2.3744},
{'tag': 'val/dfl_loss', 'value': 0.79638},
{'tag': 'lr/pg0', 'value': 0.024907},
{'tag': 'lr/pg1', 'value': 0.0019065},
{'tag': 'lr/pg2', 'value': 0.0019065}],
[{'tag': 'epoch', 'value': 39.0},
{'tag': 'train/box_loss', 'value': 0.59383},
{'tag': 'train/cls_loss', 'value': 0.80533},
{'tag': 'train/dfl_loss', 'value': 0.87874},
{'tag': 'metrics/precision(B)', 'value': 1.0},
{'tag': 'metrics/recall(B)', 'value': 0.4442},
{'tag': 'metrics/mAP50(B)', 'value': 0.99045},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.88933},
{'tag': 'val/box_loss', 'value': 0.58402},
{'tag': 'val/cls_loss', 'value': 2.2775},
{'tag': 'val/dfl_loss', 'value': 0.81},
{'tag': 'lr/pg0', 'value': 0.0228},
{'tag': 'lr/pg1', 'value': 0.0017996},
{'tag': 'lr/pg2', 'value': 0.0017996}],
[{'tag': 'epoch', 'value': 40.0},
{'tag': 'train/box_loss', 'value': 0.4485},
{'tag': 'train/cls_loss', 'value': 0.84811},
{'tag': 'train/dfl_loss', 'value': 0.81296},
{'tag': 'metrics/precision(B)', 'value': 1.0},
{'tag': 'metrics/recall(B)', 'value': 0.35018},
{'tag': 'metrics/mAP50(B)', 'value': 0.97167},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.8598},
{'tag': 'val/box_loss', 'value': 0.58368},
{'tag': 'val/cls_loss', 'value': 2.2709},
{'tag': 'val/dfl_loss', 'value': 0.81143},
{'tag': 'lr/pg0', 'value': 0.020685},
{'tag': 'lr/pg1', 'value': 0.0016848},
{'tag': 'lr/pg2', 'value': 0.0016848}],
[{'tag': 'epoch', 'value': 41.0},
{'tag': 'train/box_loss', 'value': 0.5216},
{'tag': 'train/cls_loss', 'value': 0.7309},
{'tag': 'train/dfl_loss', 'value': 0.8386},
{'tag': 'metrics/precision(B)', 'value': 1.0},
{'tag': 'metrics/recall(B)', 'value': 0.56993},
{'tag': 'metrics/mAP50(B)', 'value': 0.98136},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.88798},
{'tag': 'val/box_loss', 'value': 0.56186},
{'tag': 'val/cls_loss', 'value': 2.1034},
{'tag': 'val/dfl_loss', 'value': 0.80235},
{'tag': 'lr/pg0', 'value': 0.018562},
{'tag': 'lr/pg1', 'value': 0.0015621},
{'tag': 'lr/pg2', 'value': 0.0015621}],
[{'tag': 'epoch', 'value': 42.0},
{'tag': 'train/box_loss', 'value': 0.46109},
{'tag': 'train/cls_loss', 'value': 0.75215},
{'tag': 'train/dfl_loss', 'value': 0.81637},
{'tag': 'metrics/precision(B)', 'value': 0.94392},
{'tag': 'metrics/recall(B)', 'value': 0.61791},
{'tag': 'metrics/mAP50(B)', 'value': 0.98136},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.85015},
{'tag': 'val/box_loss', 'value': 0.64211},
{'tag': 'val/cls_loss', 'value': 1.9825},
{'tag': 'val/dfl_loss', 'value': 0.81823},
{'tag': 'lr/pg0', 'value': 0.016431},
{'tag': 'lr/pg1', 'value': 0.0014314},
{'tag': 'lr/pg2', 'value': 0.0014314}],
[{'tag': 'epoch', 'value': 43.0},
{'tag': 'train/box_loss', 'value': 0.47991},
{'tag': 'train/cls_loss', 'value': 0.84562},
{'tag': 'train/dfl_loss', 'value': 0.816},
{'tag': 'metrics/precision(B)', 'value': 0.96134},
{'tag': 'metrics/recall(B)', 'value': 0.72676},
{'tag': 'metrics/mAP50(B)', 'value': 0.98591},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.8781},
{'tag': 'val/box_loss', 'value': 0.55408},
{'tag': 'val/cls_loss', 'value': 1.8485},
{'tag': 'val/dfl_loss', 'value': 0.796},
{'tag': 'lr/pg0', 'value': 0.014293},
{'tag': 'lr/pg1', 'value': 0.0012928},
{'tag': 'lr/pg2', 'value': 0.0012928}],
[{'tag': 'epoch', 'value': 44.0},
{'tag': 'train/box_loss', 'value': 0.42274},
{'tag': 'train/cls_loss', 'value': 0.67743},
{'tag': 'train/dfl_loss', 'value': 0.85156},
{'tag': 'metrics/precision(B)', 'value': 1.0},
{'tag': 'metrics/recall(B)', 'value': 0.68122},
{'tag': 'metrics/mAP50(B)', 'value': 0.98591},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.88629},
{'tag': 'val/box_loss', 'value': 0.59008},
{'tag': 'val/cls_loss', 'value': 1.8945},
{'tag': 'val/dfl_loss', 'value': 0.80049},
{'tag': 'lr/pg0', 'value': 0.012146},
{'tag': 'lr/pg1', 'value': 0.0011463},
{'tag': 'lr/pg2', 'value': 0.0011463}],
[{'tag': 'epoch', 'value': 45.0},
{'tag': 'train/box_loss', 'value': 0.44008},
{'tag': 'train/cls_loss', 'value': 0.68818},
{'tag': 'train/dfl_loss', 'value': 0.79383},
{'tag': 'metrics/precision(B)', 'value': 1.0},
{'tag': 'metrics/recall(B)', 'value': 0.75958},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.90281},
{'tag': 'val/box_loss', 'value': 0.48885},
{'tag': 'val/cls_loss', 'value': 1.8046},
{'tag': 'val/dfl_loss', 'value': 0.78786},
{'tag': 'lr/pg0', 'value': 0.0099919},
{'tag': 'lr/pg1', 'value': 0.0009919},
{'tag': 'lr/pg2', 'value': 0.0009919}],
[{'tag': 'epoch', 'value': 46.0},
{'tag': 'train/box_loss', 'value': 0.42351},
{'tag': 'train/cls_loss', 'value': 0.68141},
{'tag': 'train/dfl_loss', 'value': 0.81276},
{'tag': 'metrics/precision(B)', 'value': 1.0},
{'tag': 'metrics/recall(B)', 'value': 0.84113},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.90002},
{'tag': 'val/box_loss', 'value': 0.52886},
{'tag': 'val/cls_loss', 'value': 1.6638},
{'tag': 'val/dfl_loss', 'value': 0.79098},
{'tag': 'lr/pg0', 'value': 0.0078296},
{'tag': 'lr/pg1', 'value': 0.00082956},
{'tag': 'lr/pg2', 'value': 0.00082956}],
[{'tag': 'epoch', 'value': 47.0},
{'tag': 'train/box_loss', 'value': 0.43221},
{'tag': 'train/cls_loss', 'value': 0.68535},
{'tag': 'train/dfl_loss', 'value': 0.81431},
{'tag': 'metrics/precision(B)', 'value': 0.99289},
{'tag': 'metrics/recall(B)', 'value': 0.97043},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.90593},
{'tag': 'val/box_loss', 'value': 0.48647},
{'tag': 'val/cls_loss', 'value': 1.5789},
{'tag': 'val/dfl_loss', 'value': 0.78382},
{'tag': 'lr/pg0', 'value': 0.0056593},
{'tag': 'lr/pg1', 'value': 0.0006593},
{'tag': 'lr/pg2', 'value': 0.0006593}],
[{'tag': 'epoch', 'value': 48.0},
{'tag': 'train/box_loss', 'value': 0.39935},
{'tag': 'train/cls_loss', 'value': 0.66413},
{'tag': 'train/dfl_loss', 'value': 0.80588},
{'tag': 'metrics/precision(B)', 'value': 0.99488},
{'tag': 'metrics/recall(B)', 'value': 0.98173},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.8921},
{'tag': 'val/box_loss', 'value': 0.50336},
{'tag': 'val/cls_loss', 'value': 1.557},
{'tag': 'val/dfl_loss', 'value': 0.78832},
{'tag': 'lr/pg0', 'value': 0.0034811},
{'tag': 'lr/pg1', 'value': 0.00048112},
{'tag': 'lr/pg2', 'value': 0.00048112}],
[{'tag': 'epoch', 'value': 49.0},
{'tag': 'train/box_loss', 'value': 0.41614},
{'tag': 'train/cls_loss', 'value': 0.62133},
{'tag': 'train/dfl_loss', 'value': 0.809},
{'tag': 'metrics/precision(B)', 'value': 0.99142},
{'tag': 'metrics/recall(B)', 'value': 1.0},
{'tag': 'metrics/mAP50(B)', 'value': 0.995},
{'tag': 'metrics/mAP50-95(B)', 'value': 0.9074},
{'tag': 'val/box_loss', 'value': 0.49075},
{'tag': 'val/cls_loss', 'value': 1.4943},
{'tag': 'val/dfl_loss', 'value': 0.78682},
{'tag': 'lr/pg0', 'value': 0.001295},
{'tag': 'lr/pg1', 'value': 0.00029502},
{'tag': 'lr/pg2', 'value': 0.00029502}]]
In [9]:
Copied!
hub.get_evaluate_result()
hub.get_evaluate_result()
Out[9]:
[{'tag': 'mAP', 'value': 0.3143564462661743}]
In [10]:
Copied!
hub.best_ckpt_file
hub.best_ckpt_file
Out[10]:
PosixPath('hubs/detector/weights/best_ckpt.pt')
In [ ]:
Copied!