Save training artifact classroom_train_20260501_162337

space_training_archive/classroom_train_20260501_162337/training.log

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+[2026-05-01 16:23:37] Trigger training request
+[2026-05-01 16:23:37] Worker background dimulai: classroom_train_20260501_162337
+[2026-05-01 16:23:44] Worker training aktif. PID=72
+[2026-05-01 16:23:44] Preparing dataset dan pseudo-label di background...
+[2026-05-01 16:23:44] Prepare split `train`: total gambar=80
+[2026-05-01 16:23:47] Prepare `train` progress: 10/80 (labeled=10)
+[2026-05-01 16:23:50] Prepare `train` progress: 20/80 (labeled=20)
+[2026-05-01 16:23:53] Prepare `train` progress: 30/80 (labeled=30)
+[2026-05-01 16:23:56] Prepare `train` progress: 40/80 (labeled=40)
+[2026-05-01 16:23:59] Prepare `train` progress: 50/80 (labeled=50)
+[2026-05-01 16:24:01] Prepare `train` progress: 60/80 (labeled=60)
+[2026-05-01 16:24:04] Prepare `train` progress: 70/80 (labeled=70)
+[2026-05-01 16:24:07] Prepare `train` progress: 80/80 (labeled=80)
+[2026-05-01 16:24:07] Prepare split `val`: total gambar=20
+[2026-05-01 16:24:10] Prepare `val` progress: 10/20 (labeled=10)
+[2026-05-01 16:24:13] Prepare `val` progress: 20/20 (labeled=20)
+[2026-05-01 16:24:13] Dataset siap: Dataset siap: train=80 (labeled=80), val=20 (labeled=20), yaml=/app/prepared_dataset/20260501_162344/data.yaml
+[2026-05-01 16:24:13] Start training classroom_train_20260501_162337
+[2026-05-01 16:24:13] Model awal training: YOLOv8n (/app/yolov8n.pt)
+Ultralytics 8.4.45 🚀 Python-3.10.20 torch-2.11.0+cu130 CPU (Intel Xeon Platinum 8375C CPU @ 2.90GHz)
+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=/app/prepared_dataset/20260501_162344/data.yaml, degrees=0.0, deterministic=True, device=cpu, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, end2end=None, epochs=10, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, half=False, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, int8=False, 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=/app/yolov8n.pt, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=classroom_train_20260501_162337, 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=/app/runs_train, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/app/runs_train/classroom_train_20260501_162337, 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=botsort.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=1
+
+                   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    751507  ultralytics.nn.modules.head.Detect           [1, 16, None, [64, 128, 256]] 
+Model summary: 130 layers, 3,011,043 parameters, 3,011,027 gradients, 8.2 GFLOPs
+
+Transferred 319/355 items from pretrained weights
+Freezing layer 'model.22.dfl.conv.weight'
+train: Fast image access ✅ (ping: 0.0±0.0 ms, read: 2738.3±859.6 MB/s, size: 77.6 KB)
+
+train: New cache created: /app/prepared_dataset/20260501_162344/labels/train.cache
+val: Fast image access ✅ (ping: 0.0±0.0 ms, read: 2438.0±511.7 MB/s, size: 83.9 KB)
+
+val: New cache created: /app/prepared_dataset/20260501_162344/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=0.002, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)
+Plotting labels to /app/runs_train/classroom_train_20260501_162337/labels.jpg... 
+Image sizes 640 train, 640 val
+Using 0 dataloader workers
+Logging results to /app/runs_train/classroom_train_20260501_162337
+Starting training for 10 epochs...
+Closing dataloader mosaic
+
+      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
+
+
+                   all         20        101     0.0163       0.97      0.187     0.0641
+
+      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
+
+
+                   all         20        101     0.0162       0.96      0.341      0.143
+
+      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
+
+
+                   all         20        101     0.0163       0.97       0.36      0.156
+
+      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
+
+
+                   all         20        101      0.021       0.95      0.334      0.206
+
+      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
+
+
+                   all         20        101          1      0.154      0.427      0.266
+
+      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
+
+
+                   all         20        101        0.8      0.158      0.443       0.28
+
+      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
+
+
+                   all         20        101       0.92      0.113      0.495      0.332
+
+      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
+
+
+                   all         20        101      0.856      0.235      0.592      0.416
+
+      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
+
+
+                   all         20        101      0.767      0.294      0.604      0.447
+
+      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size
+
+
+                   all         20        101      0.693      0.515      0.614      0.455
+
+10 epochs completed in 0.167 hours.
+Optimizer stripped from /app/runs_train/classroom_train_20260501_162337/weights/last.pt, 6.2MB
+Optimizer stripped from /app/runs_train/classroom_train_20260501_162337/weights/best.pt, 6.2MB
+
+Validating /app/runs_train/classroom_train_20260501_162337/weights/best.pt...
+Ultralytics 8.4.45 🚀 Python-3.10.20 torch-2.11.0+cu130 CPU (Intel Xeon Platinum 8375C CPU @ 2.90GHz)
+Model summary (fused): 73 layers, 3,005,843 parameters, 0 gradients, 8.1 GFLOPs
+
+                   all         20        101      0.693      0.515      0.613      0.455
+Speed: 5.9ms preprocess, 230.2ms inference, 0.0ms loss, 36.9ms postprocess per image
+Results saved to /app/runs_train/classroom_train_20260501_162337
+
+
+
+
  /app/best.pt                :  94%|█████████▍| 5.88MB / 6.24MB            
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  /app/best.pt                :  94%|█████████▍| 5.88MB / 6.24MB            
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  /app/best.pt                : 100%|██████████| 6.24MB / 6.24MB            
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  /app/best.pt                : 100%|██████████| 6.24MB / 6.24MB