im tryting to run this code:  python train.py --img 640 --batch-size 16 --epochs 50 --data data.yaml --weights yolov5s6.pt --evolve 15


it gives out this error:
Transferred 450/459 items from yolov5s6.pt
G:\MachineLearning\FireYolo\xml_to_textYolo\yolov5\models\common.py:869: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with amp.autocast(autocast):
G:\MachineLearning\FireYolo\xml_to_textYolo\yolov5\models\common.py:869: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with amp.autocast(autocast):
AMP: checks passed 
optimizer: SGD(lr=0.01) with parameter groups 75 weight(decay=0.0), 79 weight(decay=0.0005), 79 bias
train: Scanning G:\MachineLearning\FireYolo\xml_to_textYolo\yolov5\data\fire2\train\labels.cache... 1004 images, 2 backgrounds, 0 corrupt: 100%|██████████| 1004/1004 [00:00<?, ?it/s]
val: Scanning G:\MachineLearning\FireYolo\xml_to_textYolo\yolov5\data\fire2\valid\labels.cache... 754 images, 2 backgrounds, 0 corrupt: 100%|██████████| 754/754 [00:00<?, ?it/s]

AutoAnchor: 0.02 anchors/target, 0.003 Best Possible Recall (BPR). Anchors are a poor fit to dataset , attempting to improve...
AutoAnchor: WARNING  Extremely small objects found: 2 of 1538 labels are <3 pixels in size
AutoAnchor: Running kmeans for 12 anchors on 1538 points...
AutoAnchor: Evolving anchors with Genetic Algorithm: fitness = 0.7776: 100%|██████████| 1000/1000 [00:00<00:00, 1445.08it/s]
AutoAnchor: thr=0.25: 0.9974 best possible recall, 8.13 anchors past thr
AutoAnchor: n=12, img_size=640, metric_all=0.377/0.778-mean/best, past_thr=0.481-mean: 29,55, 68,62, 66,122, 137,101, 71,211, 130,180, 94,293, 244,127, 149,352, 247,266, 460,315, 315,514
AutoAnchor: Done  (optional: update model *.yaml to use these anchors in the future)
Plotting labels to runs\evolve\exp6\labels.jpg... 
G:\MachineLearning\FireYolo\xml_to_textYolo\yolov5\train.py:355: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  scaler = torch.cuda.amp.GradScaler(enabled=amp)
Image sizes 640 train, 640 val
Using 8 dataloader workers
Logging results to runs\evolve\exp6
Starting training for 50 epochs...

      Epoch    GPU_mem   box_loss   obj_loss   cls_loss  Instances       Size
  0%|          | 0/63 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "G:\MachineLearning\FireYolo\xml_to_textYolo\yolov5\train.py", line 986, in <module>
    main(opt)
  File "G:\MachineLearning\FireYolo\xml_to_textYolo\yolov5\train.py", line 819, in main
    results = train(hyp.copy(), opt, device, callbacks)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "G:\MachineLearning\FireYolo\xml_to_textYolo\yolov5\train.py", line 387, in train
    for i, (imgs, targets, paths, _) in pbar:  # batch -------------------------------------------------------------
  File "G:\MachineLearning\FireYolo\yolov5_env\Lib\site-packages\tqdm\std.py", line 1181, in __iter__
    for obj in iterable:
  File "G:\MachineLearning\FireYolo\xml_to_textYolo\yolov5\utils\dataloaders.py", line 240, in __iter__
    yield next(self.iterator)
          ^^^^^^^^^^^^^^^^^^^
  File "G:\MachineLearning\FireYolo\yolov5_env\Lib\site-packages\torch\utils\data\dataloader.py", line 630, in __next__
    data = self._next_data()
           ^^^^^^^^^^^^^^^^^
  File "G:\MachineLearning\FireYolo\yolov5_env\Lib\site-packages\torch\utils\data\dataloader.py", line 1344, in _next_data
    return self._process_data(data)
           ^^^^^^^^^^^^^^^^^^^^^^^^
  File "G:\MachineLearning\FireYolo\yolov5_env\Lib\site-packages\torch\utils\data\dataloader.py", line 1370, in _process_data
    data.reraise()
  File "G:\MachineLearning\FireYolo\yolov5_env\Lib\site-packages\torch\_utils.py", line 706, in reraise
    raise exception
ValueError: Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File "G:\MachineLearning\FireYolo\yolov5_env\Lib\site-packages\torch\utils\data\_utils\worker.py", line 309, in _worker_loop
    data = fetcher.fetch(index)  # type: ignore[possibly-undefined]
           ^^^^^^^^^^^^^^^^^^^^
  File "G:\MachineLearning\FireYolo\yolov5_env\Lib\site-packages\torch\utils\data\_utils\fetch.py", line 52, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "G:\MachineLearning\FireYolo\yolov5_env\Lib\site-packages\torch\utils\data\_utils\fetch.py", line 52, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
            ~~~~~~~~~~~~^^^^^
  File "G:\MachineLearning\FireYolo\xml_to_textYolo\yolov5\utils\dataloaders.py", line 779, in __getitem__
    img, labels = mixup(img, labels, *self.load_mosaic(random.choice(self.indices)))
                                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Program Files\Python311\Lib\random.py", line 369, in choice
    if not seq:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()