Fixed misguiding weight mode documentation (#7746)

### Description

DeepSupervisionLoss has a small typo in the documentation for 'exp'
weight mode. The correct weights for this mode should be starting at 1,
not 0 and then decrease by power of two. Might be worth fixing as it
made me check the source code.

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

Signed-off-by: Simon Jensen <61684806+simojens@users.noreply.github.com>

monai/losses/ds_loss.py

@@ -33,7 +33,7 @@ def __init__(self, loss: _Loss, weight_mode: str = "exp", weights: list[float] |
             weight_mode: {``"same"``, ``"exp"``, ``"two"``}
                 Specifies the weights calculation for each image level. Defaults to ``"exp"``.
                 - ``"same"``: all weights are equal to 1.
-                - ``"exp"``: exponentially decreasing weights by a power of 2: 0, 0.5, 0.25, 0.125, etc .
+                - ``"exp"``: exponentially decreasing weights by a power of 2: 1, 0.5, 0.25, 0.125, etc .
                 - ``"two"``: equal smaller weights for lower levels: 1, 0.5, 0.5, 0.5, 0.5, etc
             weights: a list of weights to apply to each deeply supervised sub-loss, if provided, this will be used
                 regardless of the weight_mode