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Hi - excellent video! I'm trying to recreate, but I can't see the weights.hdf5 file on your github. What model architecture did you train to get such high performance for the binary classification? My accuracy is only around 65% when following the exact notebook :) Edit: My mistake, I think. I ran with too few epochs. Anyone that's following along, ensure you change the epochs=1 in the fit line :)
@@codewithkristi previously I ran this program the model ran fine. but now it shows error for the same code. /content/sign-language--1 Ultralytics YOLOv8.0.230 🚀 Python-3.10.12 torch-2.1.0+cu121 CUDA:0 (Tesla T4, 15102MiB) engine/trainer: task=detect, mode=train, model=/content/yolov8s.pt, data=/content/sign-language--1/data.yaml, epochs=25, time=None, patience=50, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, 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, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, 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, tracker=botsort.yaml, save_dir=runs/detect/train Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/ultralytics/engine/trainer.py", line 116, in __init__ self.data = check_det_dataset(self.args.data) File "/usr/local/lib/python3.10/dist-packages/ultralytics/data/utils.py", line 312, in check_det_dataset raise FileNotFoundError(m) FileNotFoundError: Dataset '/content/sign-language--1/data.yaml' images not found ⚠, missing path '/content/sign-language--1/sign-language--1/valid/images' Note dataset download directory is '/content/datasets'. You can update this in '/root/.config/Ultralytics/settings.yaml' The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/usr/local/bin/yolo", line 8, in <module> sys.exit(entrypoint()) File "/usr/local/lib/python3.10/dist-packages/ultralytics/cfg/__init__.py", line 448, in entrypoint getattr(model, mode)(**overrides) # default args from model File "/usr/local/lib/python3.10/dist-packages/ultralytics/engine/model.py", line 351, in train self.trainer = (trainer or self._smart_load('trainer'))(overrides=args, _callbacks=self.callbacks) File "/usr/local/lib/python3.10/dist-packages/ultralytics/engine/trainer.py", line 120, in __init__ raise RuntimeError(emojis(f"Dataset '{clean_url(self.args.data)}' error ❌ {e}")) from e RuntimeError: Dataset '/content/sign-language--1/data.yaml' error ❌ Dataset '/content/sign-language--1/data.yaml' images not found ⚠, missing path '/content/sign-language--1/sign-language--1/valid/images' Note dataset download directory is '/content/datasets'. You can update this in '/root/.config/Ultralytics/settings.yaml' this is the error i am getting. what to do?
