diff --git a/docs/src/developer/optimizer.md b/docs/src/developer/optimizer.md
index 0a85eb6a..9e01ac87 100644
--- a/docs/src/developer/optimizer.md
+++ b/docs/src/developer/optimizer.md
@@ -16,7 +16,7 @@ SemOptimizer{:Name}(args...; kwargs...) = SemOptimizerName(args...; kwargs...)
 
 SemOptimizerName(;
     algorithm = LBFGS(),
-    options = Optim.Options(; f_tol = 1e-10, x_tol = 1.5e-8),
+    options = Optim.Options(; f_reltol = 1e-10, x_abstol = 1.5e-8),
     kwargs...,
 ) = SemOptimizerName(algorithm, options)
 
@@ -40,7 +40,7 @@ Similarly, `SemOptimizer{:Name}(args...; kwargs...) = SemOptimizerName(args...;
 ```julia
 SemOptimizerName(;
     algorithm = LBFGS(),
-    options = Optim.Options(; f_tol = 1e-10, x_tol = 1.5e-8),
+    options = Optim.Options(; f_reltol = 1e-10, x_abstol = 1.5e-8),
     kwargs...,
 ) = SemOptimizerName(algorithm, options)
 ```
diff --git a/src/optimizer/optim.jl b/src/optimizer/optim.jl
index e01a606d..bd57942d 100644
--- a/src/optimizer/optim.jl
+++ b/src/optimizer/optim.jl
@@ -12,7 +12,7 @@ Connects to `Optim.jl` as the optimization backend.
 
     SemOptimizerOptim(;
         algorithm = LBFGS(),
-        options = Optim.Options(;f_tol = 1e-10, x_tol = 1.5e-8),
+        options = Optim.Options(;f_reltol = 1e-10, x_abstol = 1.5e-8),
         kwargs...)
 
 # Arguments
@@ -67,7 +67,7 @@ SemOptimizer{:Optim}(args...; kwargs...) = SemOptimizerOptim(args...; kwargs...)
 
 SemOptimizerOptim(;
     algorithm = LBFGS(),
-    options = Optim.Options(; f_tol = 1e-10, x_tol = 1.5e-8),
+    options = Optim.Options(;f_reltol = 1e-10, x_abstol = 1.5e-8),
     kwargs...,
 ) = SemOptimizerOptim(algorithm, options)
 
diff --git a/test/examples/recover_parameters/recover_parameters_twofact.jl b/test/examples/recover_parameters/recover_parameters_twofact.jl
index a3e426cb..a7b4cec9 100644
--- a/test/examples/recover_parameters/recover_parameters_twofact.jl
+++ b/test/examples/recover_parameters/recover_parameters_twofact.jl
@@ -70,7 +70,7 @@ objective!(model_ml, true_val)
 
 optimizer = SemOptimizerOptim(
     BFGS(; linesearch = BackTracking(order = 3), alphaguess = InitialHagerZhang()),# m = 100),
-    Optim.Options(; f_tol = 1e-10, x_tol = 1.5e-8),
+    Optim.Options(; f_reltol = 1e-10, x_abstol = 1.5e-8),
 )
 
 solution_ml = fit(optimizer, model_ml)