Tuner: Initialized Tuner instance with 'tune_dir=/kaggle/working/runs/detect/tune' Tuner: 💡 Learn about tuning at https://docs.ultralytics.com/guides/hyperparameter-tuning Tuner: Starting iteration 1/300 with hyperparameters: {'lr0': 0.01} Ultralytics 8.3.224 🚀 Python-3.11.13 torch-2.6.0+cu124 CUDA:0 (Tesla T4, 15095MiB) engine/trainer: agnostic_nms=False, amp=True, augment=False, auto_augment=randaugment, batch=16, bgr=0.0, box=7.5, cache=False, cfg=None, classes=None, close_mosaic=10, cls=0.5, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/kaggle/input/pvelad-2/pvelad-2/data.yaml, degrees=0.0, deterministic=True, device=None, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=30, 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=224, 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=/kaggle/input/convnext-yolo-100/pytorch/default/1/vit-100e-best.pt, momentum=0.937, mosaic=1.0, multi_scale=False, name=train, nbs=64, nms=False, opset=None, optimize=False, optimizer=AdamW, overlap_mask=True, patience=100, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=None, rect=False, resume=False, retina_masks=False, save=False, save_conf=False, save_crop=False, save_dir=/kaggle/working/runs/detect/train, 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=False, 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 A module that was compiled using NumPy 1.x cannot be run in NumPy 2.2.6 as it may crash. To support both 1.x and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuild instead e.g. with 'pybind11>=2.12'. If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules will need time to support NumPy 2. Traceback (most recent call last): File "", line 198, in _run_module_as_main File "", line 88, in _run_code File "/usr/local/lib/python3.11/dist-packages/ultralytics/cfg/__init__.py", line 1019, in entrypoint(debug="") File "/usr/local/lib/python3.11/dist-packages/ultralytics/cfg/__init__.py", line 978, in entrypoint getattr(model, mode)(**overrides) # default args from model File "/usr/local/lib/python3.11/dist-packages/ultralytics/engine/model.py", line 772, in train self.trainer = (trainer or self._smart_load("trainer"))(overrides=args, _callbacks=self.callbacks) File "/usr/local/lib/python3.11/dist-packages/ultralytics/models/yolo/detect/train.py", line 63, in __init__ super().__init__(cfg, overrides, _callbacks) File "/usr/local/lib/python3.11/dist-packages/ultralytics/engine/trainer.py", line 158, in __init__ self.data = self.get_dataset() File "/usr/local/lib/python3.11/dist-packages/ultralytics/engine/trainer.py", line 644, in get_dataset data = check_det_dataset(self.args.data) File "/usr/local/lib/python3.11/dist-packages/ultralytics/data/utils.py", line 475, in check_det_dataset check_font("Arial.ttf" if is_ascii(data["names"]) else "Arial.Unicode.ttf") # download fonts File "/usr/local/lib/python3.11/dist-packages/ultralytics/utils/__init__.py", line 491, in decorated return f(*args, **kwargs) File "/usr/local/lib/python3.11/dist-packages/ultralytics/utils/checks.py", line 318, in check_font from matplotlib import font_manager # scope for faster 'import ultralytics' File "/usr/local/lib/python3.11/dist-packages/matplotlib/__init__.py", line 129, in from . import _api, _version, cbook, _docstring, rcsetup File "/usr/local/lib/python3.11/dist-packages/matplotlib/rcsetup.py", line 27, in from matplotlib.colors import Colormap, is_color_like File "/usr/local/lib/python3.11/dist-packages/matplotlib/colors.py", line 56, in from matplotlib import _api, _cm, cbook, scale File "/usr/local/lib/python3.11/dist-packages/matplotlib/scale.py", line 22, in from matplotlib.ticker import ( File "/usr/local/lib/python3.11/dist-packages/matplotlib/ticker.py", line 138, in from matplotlib import transforms as mtransforms File "/usr/local/lib/python3.11/dist-packages/matplotlib/transforms.py", line 49, in from matplotlib._path import ( AttributeError: _ARRAY_API not found Traceback (most recent call last): File "/usr/local/lib/python3.11/dist-packages/ultralytics/engine/trainer.py", line 644, in get_dataset data = check_det_dataset(self.args.data) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/ultralytics/data/utils.py", line 475, in check_det_dataset check_font("Arial.ttf" if is_ascii(data["names"]) else "Arial.Unicode.ttf") # download fonts ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/ultralytics/utils/__init__.py", line 491, in decorated return f(*args, **kwargs) ^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/ultralytics/utils/checks.py", line 318, in check_font from matplotlib import font_manager # scope for faster 'import ultralytics' ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/matplotlib/__init__.py", line 129, in from . import _api, _version, cbook, _docstring, rcsetup File "/usr/local/lib/python3.11/dist-packages/matplotlib/rcsetup.py", line 27, in from matplotlib.colors import Colormap, is_color_like File "/usr/local/lib/python3.11/dist-packages/matplotlib/colors.py", line 56, in from matplotlib import _api, _cm, cbook, scale File "/usr/local/lib/python3.11/dist-packages/matplotlib/scale.py", line 22, in from matplotlib.ticker import ( File "/usr/local/lib/python3.11/dist-packages/matplotlib/ticker.py", line 138, in from matplotlib import transforms as mtransforms File "/usr/local/lib/python3.11/dist-packages/matplotlib/transforms.py", line 49, in from matplotlib._path import ( ImportError: numpy.core.multiarray failed to import The above exception was the direct cause of the following exception: Traceback (most recent call last): File "", line 198, in _run_module_as_main File "", line 88, in _run_code File "/usr/local/lib/python3.11/dist-packages/ultralytics/cfg/__init__.py", line 1019, in entrypoint(debug="") File "/usr/local/lib/python3.11/dist-packages/ultralytics/cfg/__init__.py", line 978, in entrypoint getattr(model, mode)(**overrides) # default args from model ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/ultralytics/engine/model.py", line 772, in train self.trainer = (trainer or self._smart_load("trainer"))(overrides=args, _callbacks=self.callbacks) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/ultralytics/models/yolo/detect/train.py", line 63, in __init__ super().__init__(cfg, overrides, _callbacks) File "/usr/local/lib/python3.11/dist-packages/ultralytics/engine/trainer.py", line 158, in __init__ self.data = self.get_dataset() ^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/ultralytics/engine/trainer.py", line 648, in get_dataset raise RuntimeError(emojis(f"Dataset '{clean_url(self.args.data)}' error ❌ {e}")) from e RuntimeError: Dataset '/kaggle/input/pvelad-2/pvelad-2/data.yaml' error ❌ numpy.core.multiarray failed to import ERROR ❌ training failure for hyperparameter tuning iteration 1 Command '['/usr/bin/python3', '-m', 'ultralytics.cfg.__init__', 'train', 'task=detect', 'mode=train', 'model=/kaggle/input/convnext-yolo-100/pytorch/default/1/vit-100e-best.pt', 'data=/kaggle/input/pvelad-2/pvelad-2/data.yaml', 'epochs=30', 'time=None', 'patience=100', 'batch=16', 'imgsz=224', 'save=False', 'save_period=-1', 'cache=False', 'device=None', 'workers=8', 'project=None', 'name=None', 'exist_ok=False', 'pretrained=True', 'optimizer=AdamW', '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', 'multi_scale=False', 'compile=False', 'overlap_mask=True', 'mask_ratio=4', 'dropout=0.0', 'val=False', 'split=val', 'save_json=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=True', 'opset=None', 'workspace=None', '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', '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', 'bgr=0.0', 'mosaic=1.0', 'mixup=0.0', 'cutmix=0.0', 'copy_paste=0.0', 'copy_paste_mode=flip', 'auto_augment=randaugment', 'erasing=0.4', 'cfg=None', 'tracker=botsort.yaml']' returned non-zero exit status 1. /usr/local/lib/python3.11/dist-packages/ultralytics/utils/plotting.py:980: RuntimeWarning: Mean of empty slice. mean, std = fitness.mean(), fitness.std() /usr/local/lib/python3.11/dist-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide /usr/local/lib/python3.11/dist-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice /usr/local/lib/python3.11/dist-packages/numpy/core/_methods.py:163: RuntimeWarning: invalid value encountered in divide /usr/local/lib/python3.11/dist-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide --------------------------------------------------------------------------- ValueError Traceback (most recent call last) /tmp/ipykernel_37/3790921447.py in () 5 6 # Tune hyperparameters on COCO8 for 30 epochs ----> 7 model.tune( 8 data="/kaggle/input/pvelad-2/pvelad-2/data.yaml", 9 epochs=30, /usr/local/lib/python3.11/dist-packages/ultralytics/engine/model.py in tune(self, use_ray, iterations, *args, **kwargs) 829 custom = {} # method defaults 830 args = {**self.overrides, **custom, **kwargs, "mode": "train"} # highest priority args on the right --> 831 return Tuner(args=args, _callbacks=self.callbacks)(model=self, iterations=iterations) 832 833 def _apply(self, fn) -> Model: /usr/local/lib/python3.11/dist-packages/ultralytics/engine/tuner.py in __call__(self, model, iterations, cleanup) 430 431 # Plot tune results --> 432 plot_tune_results(str(self.tune_csv)) 433 434 # Save and print tune results /usr/local/lib/python3.11/dist-packages/ultralytics/utils/__init__.py in wrapper(*args, **kwargs) 370 try: 371 with plt.rc_context(rcparams): --> 372 result = func(*args, **kwargs) 373 finally: 374 if switch: /usr/local/lib/python3.11/dist-packages/ultralytics/utils/plotting.py in plot_tune_results(csv_file, exclude_zero_fitness_points) 984 break 985 x, fitness = x[mask], fitness[mask] --> 986 j = np.argmax(fitness) # max fitness index 987 n = math.ceil(len(keys) ** 0.5) # columns and rows in plot 988 plt.figure(figsize=(10, 10), tight_layout=True) /usr/local/lib/python3.11/dist-packages/numpy/core/fromnumeric.py in argmax(a, axis, out, keepdims) /usr/local/lib/python3.11/dist-packages/numpy/core/fromnumeric.py in _wrapfunc(obj, method, *args, **kwds) ValueError: attempt to get argmax of an empty sequence