Fix Sophia neural network training documentation example

Addresses issue #937 by updating the tutorial to properly use DataLoader with minibatching.

Changes made:
- Keep DataLoader as the third parameter to OptimizationProblem
- Ensure loss function properly unpacks batch data as (x_batch, y_batch)
- Add epochs parameter to solve() to iterate over the DataLoader properly
- Fix callback string interpolation to use $(state.iter) instead of %5d format

This follows the correct Optimization.jl minibatching pattern as used in the minibatch tutorial.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

Author: ChrisRackauckas

docs/src/optimization_packages/optimization.md

@@ -76,17 +76,18 @@ ps_ca = ComponentArray(ps)
 smodel = StatefulLuxLayer{true}(model, nothing, st)
 
 function callback(state, l)
-    state.iter % 25 == 1 && @show "Iteration: %5d, Loss: %.6e\n" state.iter l
+    state.iter % 25 == 1 && @show "Iteration: $(state.iter), Loss: $l"
     return l < 1e-1 ## Terminate if loss is small
 end
 
 function loss(ps, data)
-    ypred = [smodel([data[1][i]], ps)[1] for i in eachindex(data[1])]
-    return sum(abs2, ypred .- data[2])
+    x_batch, y_batch = data
+    ypred = [smodel([x_batch[i]], ps)[1] for i in eachindex(x_batch)]
+    return sum(abs2, ypred .- y_batch)
 end
 
 optf = OptimizationFunction(loss, AutoZygote())
 prob = OptimizationProblem(optf, ps_ca, data)
 
-res = Optimization.solve(prob, Optimization.Sophia(), callback = callback)
+res = Optimization.solve(prob, Optimization.Sophia(), callback = callback, epochs = 100)
 ```