In [1]:
# Confirm CUDA is True or YOLO will run on CPU which is much slower than GPU
import torch
#print("Python:", os.sys.version)
print("Torch:", torch.__version__)
print("CUDA available:", torch.cuda.is_available())
if torch.cuda.is_available():
print("Device:", torch.cuda.get_device_name(0))
Torch: 2.5.1+cu121 CUDA available: True Device: NVIDIA GeForce RTX 2070 SUPER
In [2]:
# CUDA is false whenever python version > 3.10.20 had to force a new environment & kernel
import os
from ultralytics import YOLO
print("Python version:", os.sys.version)
print("Torch version:", torch.__version__)
print("CUDA available:", torch.cuda.is_available())
if torch.cuda.is_available():
print("CUDA device:", torch.cuda.get_device_name(0))
else:
print("Running on CPU")
Python version: 3.10.20 | packaged by Anaconda, Inc. | (main, Jun 11 2026, 15:13:20) [MSC v.1942 64 bit (AMD64)] Torch version: 2.5.1+cu121 CUDA available: True CUDA device: NVIDIA GeForce RTX 2070 SUPER
In [10]:
# Check if file path contains yaml file since moving device
# Almost forgot the file path on this device INSIDE the yaml file as well
DATASET = r"D:\Independent_Project\Raw_Data_Graph_images\data.yaml"
print("\nChecking dataset path...")
if os.path.exists(DATASET):
print(" data.yaml found:", DATASET)
else:
print("data.yaml NOT found — check the path")
raise FileNotFoundError(DATASET)
Checking dataset path... data.yaml found: D:\Independent_Project\Raw_Data_Graph_images\data.yaml
In [11]:
# Check or load YOLO model n is for nano
print("\nLoading YOLOv11 model...")
model = YOLO("yolo11n.pt") # Auto download if missing
print("Model loaded")
Loading YOLOv11 model... Model loaded
In [12]:
import time
print("\nStarting YOLOv11 training...")
start_time = time.time()
results = model.train(
data=DATASET,
epochs=50,
imgsz=640,
batch=8,
name="raw_graph_classifier",
device=0 # force to use GPU if available (auto would otherwise reluctantly use CPU)
)
end_time = time.time()
print(f"\nTraining completed in {(end_time - start_time)/60:.2f} minutes")
Starting YOLOv11 training... New https://pypi.org/project/ultralytics/8.4.104 available Update with 'pip install -U ultralytics' Ultralytics 8.4.87 Python-3.10.20 torch-2.5.1+cu121 CUDA:0 (NVIDIA GeForce RTX 2070 SUPER, 8192MiB) engine\trainer: agnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=8, bgr=0.0, box=7.5, cache=False, cfg=None, classes=None, close_mosaic=10, cls=0.5, cls_pw=0.0, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=D:\Independent_Project\Raw_Data_Graph_images\data.yaml, degrees=0.0, deterministic=True, device=0, dfl=1.5, dis=6.0, distill_model=None, dnn=False, dropout=0.0, dynamic=False, embed=None, end2end=None, epochs=50, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=yolo11n.pt, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=raw_graph_classifier-2, nbs=64, nms=False, opset=None, optimize=False, optimizer=auto, overlap_mask=True, patience=100, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=None, quantize=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=C:\Users\siane\runs\detect\raw_graph_classifier-2, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=tracktrack.yaml, translate=0.1, val=True, verbose=True, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=8, workspace=None Overriding model.yaml nc=80 with nc=3 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 6640 ultralytics.nn.modules.block.C3k2 [32, 64, 1, False, 0.25] 3 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2] 4 -1 1 26080 ultralytics.nn.modules.block.C3k2 [64, 128, 1, False, 0.25] 5 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2] 6 -1 1 87040 ultralytics.nn.modules.block.C3k2 [128, 128, 1, True] 7 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2] 8 -1 1 346112 ultralytics.nn.modules.block.C3k2 [256, 256, 1, True] 9 -1 1 164608 ultralytics.nn.modules.block.SPPF [256, 256, 5] 10 -1 1 249728 ultralytics.nn.modules.block.C2PSA [256, 256, 1] 11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] 12 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1] 13 -1 1 111296 ultralytics.nn.modules.block.C3k2 [384, 128, 1, False] 14 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] 15 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1] 16 -1 1 32096 ultralytics.nn.modules.block.C3k2 [256, 64, 1, False] 17 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2] 18 [-1, 13] 1 0 ultralytics.nn.modules.conv.Concat [1] 19 -1 1 86720 ultralytics.nn.modules.block.C3k2 [192, 128, 1, False] 20 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2] 21 [-1, 10] 1 0 ultralytics.nn.modules.conv.Concat [1] 22 -1 1 378880 ultralytics.nn.modules.block.C3k2 [384, 256, 1, True] 23 [16, 19, 22] 1 431257 ultralytics.nn.modules.head.Detect [3, 16, None, [64, 128, 256]] YOLO11n summary: 182 layers, 2,590,425 parameters, 2,590,409 gradients, 6.4 GFLOPs Transferred 448/499 items from pretrained weights Freezing layer 'model.23.dfl.conv.weight' AMP: running Automatic Mixed Precision (AMP) checks... AMP: checks passed train: Fast image access (ping: 0.20.2 ms, read: 122.342.1 MB/s, size: 14.3 KB) train: Scanning D:\Independent_Project\Raw_Data_Graph_images\labels\train... 112 images, 48 backgrounds, 0 corrupt: 100% ━━━━━━━━━━━━ 160/160 1.3Kit/s 0.1s.3s train: New cache created: D:\Independent_Project\Raw_Data_Graph_images\labels\train.cache WARNING val: Slow image access detected (ping: 0.30.4 ms, read: 29.618.1 MB/s, size: 13.1 KB). Use local storage instead of remote/mounted storage for better performance. See https://docs.ultralytics.com/guides/model-training-tips/ val: Scanning D:\Independent_Project\Raw_Data_Graph_images\labels\val... 27 images, 13 backgrounds, 0 corrupt: 100% ━━━━━━━━━━━━ 40/40 371.1it/s 0.1s7s val: New cache created: D:\Independent_Project\Raw_Data_Graph_images\labels\val.cache optimizer: 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... optimizer: AdamW(lr=0.001429, momentum=0.9) with parameter groups 81 weight(decay=0.0), 88 weight(decay=0.0005), 87 bias(decay=0.0) Plotting labels to C:\Users\siane\runs\detect\raw_graph_classifier-2\labels.jpg... Image sizes 640 train, 640 val Using 8 dataloader workers Logging results to C:\Users\siane\runs\detect\raw_graph_classifier-2 Starting training for 50 epochs... Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 1/50 1.22G 2.375 4.833 1.842 25 640: 100% ━━━━━━━━━━━━ 20/20 3.8it/s 5.2s0.1s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 1.2it/s 2.5s1.8ss all 40 54 0.00454 0.824 0.0496 0.0113 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 2/50 1.29G 2.132 3.849 1.603 26 640: 100% ━━━━━━━━━━━━ 20/20 10.6it/s 1.9s0.1s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 11.9it/s 0.3s.8s all 40 54 0.00328 0.441 0.056 0.0128 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 3/50 1.29G 2.056 3.15 1.601 50 640: 100% ━━━━━━━━━━━━ 20/20 10.5it/s 1.9s0.1s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.3it/s 0.2s.3s all 40 54 0.00444 0.696 0.115 0.0355 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 4/50 1.29G 2.012 3.206 1.614 27 640: 100% ━━━━━━━━━━━━ 20/20 10.8it/s 1.9s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.6it/s 0.2s.2s all 40 54 0.00356 0.304 0.102 0.0396 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 5/50 1.29G 1.988 2.948 1.515 28 640: 100% ━━━━━━━━━━━━ 20/20 11.6it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.0it/s 0.2s.2s all 40 54 0.851 0.098 0.172 0.0695 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 6/50 1.29G 1.906 2.86 1.485 27 640: 100% ━━━━━━━━━━━━ 20/20 11.7it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 13.6it/s 0.2s.3s all 40 54 0.706 0.245 0.215 0.097 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 7/50 1.29G 1.913 2.656 1.494 23 640: 100% ━━━━━━━━━━━━ 20/20 11.6it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 11.7it/s 0.3s.3s all 40 54 0.749 0.225 0.225 0.0859 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 8/50 1.29G 1.898 2.485 1.526 26 640: 100% ━━━━━━━━━━━━ 20/20 11.7it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 13.9it/s 0.2s.3s all 40 54 0.73 0.255 0.254 0.103 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 9/50 1.29G 1.856 2.578 1.459 37 640: 100% ━━━━━━━━━━━━ 20/20 11.6it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.2it/s 0.2s.3s all 40 54 0.744 0.265 0.226 0.0994 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 10/50 1.29G 1.705 2.415 1.422 21 640: 100% ━━━━━━━━━━━━ 20/20 10.9it/s 1.8s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.5it/s 0.2s.2s all 40 54 0.723 0.228 0.194 0.0709 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 11/50 1.29G 1.781 2.469 1.417 30 640: 100% ━━━━━━━━━━━━ 20/20 11.4it/s 1.8s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.4it/s 0.2s.3s all 40 54 0.409 0.51 0.359 0.146 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 12/50 1.29G 1.72 2.167 1.397 21 640: 100% ━━━━━━━━━━━━ 20/20 11.7it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.7it/s 0.2s.2s all 40 54 0.33 0.5 0.529 0.222 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 13/50 1.29G 1.68 2.084 1.328 32 640: 100% ━━━━━━━━━━━━ 20/20 11.2it/s 1.8s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.6it/s 0.2s.2s all 40 54 0.671 0.45 0.476 0.168 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 14/50 1.29G 1.698 2.296 1.405 18 640: 100% ━━━━━━━━━━━━ 20/20 11.3it/s 1.8s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.6it/s 0.2s.2s all 40 54 0.372 0.775 0.384 0.153 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 15/50 1.29G 1.67 2.117 1.371 34 640: 100% ━━━━━━━━━━━━ 20/20 10.6it/s 1.9s.1ss Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 9.1it/s 0.3s1.2s all 40 54 0.642 0.51 0.594 0.256 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 16/50 1.29G 1.612 1.939 1.345 15 640: 100% ━━━━━━━━━━━━ 20/20 10.2it/s 2.0s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 12.3it/s 0.2s.3s all 40 54 0.529 0.539 0.478 0.175 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 17/50 1.29G 1.619 1.988 1.33 28 640: 100% ━━━━━━━━━━━━ 20/20 10.5it/s 1.9s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.7it/s 0.2s.2s all 40 54 0.5 0.5 0.411 0.14 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 18/50 1.29G 1.672 2.089 1.359 26 640: 100% ━━━━━━━━━━━━ 20/20 11.6it/s 1.7s0.1s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.5it/s 0.2s.2s all 40 54 0.395 0.497 0.489 0.204 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 19/50 1.29G 1.61 2.122 1.292 14 640: 100% ━━━━━━━━━━━━ 20/20 11.1it/s 1.8s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.6it/s 0.2s.2s all 40 54 0.383 0.5 0.448 0.233 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 20/50 1.29G 1.609 2.027 1.295 24 640: 100% ━━━━━━━━━━━━ 20/20 11.7it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.4it/s 0.2s.3s all 40 54 0.582 0.392 0.543 0.196 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 21/50 1.29G 1.58 1.914 1.342 23 640: 100% ━━━━━━━━━━━━ 20/20 11.8it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.4it/s 0.2s.2s all 40 54 0.563 0.706 0.702 0.308 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 22/50 1.29G 1.623 1.949 1.361 19 640: 100% ━━━━━━━━━━━━ 20/20 11.9it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.6it/s 0.2s.2s all 40 54 0.396 0.765 0.71 0.334 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 23/50 1.29G 1.587 1.805 1.367 40 640: 100% ━━━━━━━━━━━━ 20/20 11.6it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.7it/s 0.2s.2s all 40 54 0.604 0.556 0.484 0.148 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 24/50 1.29G 1.498 1.885 1.325 24 640: 100% ━━━━━━━━━━━━ 20/20 10.4it/s 1.9s.1ss Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 11.3it/s 0.3s.8s all 40 54 0.231 0.569 0.36 0.138 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 25/50 1.29G 1.503 1.825 1.309 17 640: 100% ━━━━━━━━━━━━ 20/20 8.5it/s 2.3s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 11.9it/s 0.3s.3s all 40 54 0.549 0.794 0.692 0.279 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 26/50 1.29G 1.456 1.699 1.258 28 640: 100% ━━━━━━━━━━━━ 20/20 10.4it/s 1.9s.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 11.1it/s 0.3s.3s all 40 54 0.495 0.696 0.738 0.271 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 27/50 1.29G 1.474 1.66 1.262 24 640: 100% ━━━━━━━━━━━━ 20/20 11.3it/s 1.8s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 12.7it/s 0.2s.2s all 40 54 0.378 0.804 0.713 0.296 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 28/50 1.29G 1.474 1.649 1.235 25 640: 100% ━━━━━━━━━━━━ 20/20 11.7it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.3it/s 0.2s.2s all 40 54 0.824 0.51 0.699 0.32 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 29/50 1.29G 1.468 1.661 1.274 44 640: 100% ━━━━━━━━━━━━ 20/20 11.8it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.3it/s 0.2s.2s all 40 54 0.673 0.404 0.49 0.23 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 30/50 1.29G 1.454 1.745 1.225 10 640: 100% ━━━━━━━━━━━━ 20/20 11.9it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.1it/s 0.2s.2s all 40 54 0.441 0.804 0.56 0.263 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 31/50 1.29G 1.491 1.722 1.269 22 640: 100% ━━━━━━━━━━━━ 20/20 11.6it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.4it/s 0.2s.2s all 40 54 0.506 0.572 0.503 0.208 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 32/50 1.29G 1.425 1.707 1.265 12 640: 100% ━━━━━━━━━━━━ 20/20 12.3it/s 1.6s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.7it/s 0.2s.2s all 40 54 0.616 0.615 0.506 0.218 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 33/50 1.29G 1.37 1.574 1.24 28 640: 100% ━━━━━━━━━━━━ 20/20 11.8it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.2it/s 0.2s.2s all 40 54 0.71 0.637 0.675 0.252 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 34/50 1.29G 1.413 1.571 1.198 23 640: 100% ━━━━━━━━━━━━ 20/20 12.0it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.9it/s 0.2s.2s all 40 54 0.774 0.618 0.694 0.286 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 35/50 1.29G 1.282 1.54 1.178 26 640: 100% ━━━━━━━━━━━━ 20/20 11.8it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 13.5it/s 0.2s.2s all 40 54 0.583 0.773 0.747 0.381 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 36/50 1.29G 1.292 1.487 1.177 17 640: 100% ━━━━━━━━━━━━ 20/20 12.1it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.0it/s 0.2s.2s all 40 54 0.722 0.597 0.753 0.332 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 37/50 1.29G 1.367 1.559 1.205 16 640: 100% ━━━━━━━━━━━━ 20/20 12.0it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.8it/s 0.2s.2s all 40 54 0.817 0.625 0.724 0.319 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 38/50 1.29G 1.298 1.576 1.196 20 640: 100% ━━━━━━━━━━━━ 20/20 11.5it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.7it/s 0.2s.2s all 40 54 0.844 0.663 0.737 0.279 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 39/50 1.29G 1.361 1.465 1.207 10 640: 100% ━━━━━━━━━━━━ 20/20 11.5it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.8it/s 0.2s.2s all 40 54 0.733 0.833 0.812 0.371 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 40/50 1.29G 1.336 1.434 1.211 15 640: 100% ━━━━━━━━━━━━ 20/20 12.1it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.0it/s 0.2s.2s all 40 54 0.869 0.765 0.849 0.344 Closing dataloader mosaic Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 41/50 1.29G 1.264 1.664 1.182 11 640: 100% ━━━━━━━━━━━━ 20/20 3.6it/s 5.5s<0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.1it/s 0.2s.2s all 40 54 0.612 0.814 0.752 0.316 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 42/50 1.29G 1.262 1.637 1.206 7 640: 100% ━━━━━━━━━━━━ 20/20 11.6it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.3it/s 0.2s.3s all 40 54 0.671 0.762 0.736 0.295 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 43/50 1.29G 1.265 1.606 1.202 12 640: 100% ━━━━━━━━━━━━ 20/20 11.5it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.2it/s 0.2s.2s all 40 54 0.632 0.745 0.744 0.329 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 44/50 1.29G 1.139 1.498 1.124 9 640: 100% ━━━━━━━━━━━━ 20/20 12.3it/s 1.6s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.0it/s 0.2s.2s all 40 54 0.616 0.759 0.753 0.388 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 45/50 1.29G 1.249 1.583 1.167 8 640: 100% ━━━━━━━━━━━━ 20/20 11.6it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.6it/s 0.2s.2s all 40 54 0.838 0.677 0.827 0.405 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 46/50 1.29G 1.168 1.512 1.17 11 640: 100% ━━━━━━━━━━━━ 20/20 12.2it/s 1.6s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.1it/s 0.2s.2s all 40 54 0.845 0.728 0.828 0.397 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 47/50 1.29G 1.166 1.499 1.138 6 640: 100% ━━━━━━━━━━━━ 20/20 11.9it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.3it/s 0.2s.2s all 40 54 0.811 0.714 0.825 0.376 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 48/50 1.29G 1.187 1.479 1.14 9 640: 100% ━━━━━━━━━━━━ 20/20 11.9it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 15.3it/s 0.2s.2s all 40 54 0.841 0.686 0.828 0.384 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 49/50 1.29G 1.188 1.481 1.184 9 640: 100% ━━━━━━━━━━━━ 20/20 11.6it/s 1.7s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 14.4it/s 0.2s.2s all 40 54 0.892 0.632 0.825 0.351 Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size 50/50 1.29G 1.227 1.511 1.144 12 640: 100% ━━━━━━━━━━━━ 20/20 12.1it/s 1.6s0.2s Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 12.7it/s 0.2s.2s all 40 54 0.836 0.676 0.823 0.371 50 epochs completed in 0.038 hours. Optimizer stripped from C:\Users\siane\runs\detect\raw_graph_classifier-2\weights\last.pt, 5.4MB Optimizer stripped from C:\Users\siane\runs\detect\raw_graph_classifier-2\weights\best.pt, 5.4MB Validating C:\Users\siane\runs\detect\raw_graph_classifier-2\weights\best.pt... Ultralytics 8.4.87 Python-3.10.20 torch-2.5.1+cu121 CUDA:0 (NVIDIA GeForce RTX 2070 SUPER, 8192MiB) YOLO11n summary (fused): 101 layers, 2,582,737 parameters, 0 gradients, 6.3 GFLOPs Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 3/3 6.1it/s 0.5s0.3s all 40 54 0.838 0.677 0.826 0.406 dry_spill 2 3 0.893 1 0.995 0.439 wet_spill 26 51 0.783 0.353 0.658 0.373 Speed: 2.0ms preprocess, 1.8ms inference, 0.0ms loss, 1.0ms postprocess per image Results saved to C:\Users\siane\runs\detect\raw_graph_classifier-2 Training completed in 2.43 minutes
In [ ]: