Update docs/src/optimization_packages/ode.md

Author: ChrisRackauckas

docs/src/optimization_packages/ode.md

@@ -53,10 +53,3 @@ You can also define a custom optimizer using the generic `ODEOptimizer(solver; d
 
 All optimizers require gradient information (either via automatic differentiation or manually provided `grad!`). The optimization is performed by integrating the ODE defined by the negative gradient until a steady state is reached.
 
-### Keyword Arguments
-
-* `dt` — time step size (only for `ODEGradientDescent`).
-* `maxiters` — maximum number of ODE steps.
-* `callback` — function to observe progress.
-* `progress=true` — enables live progress display.
-