diff --git a/docs/CHANGELOG.asciidoc b/docs/CHANGELOG.asciidoc
index 66c0b43f50..c0812d01c4 100644
--- a/docs/CHANGELOG.asciidoc
+++ b/docs/CHANGELOG.asciidoc
@@ -35,6 +35,11 @@
 * Upgrade PyTorch to version 1.11. (See {ml-pull}2233[#2233], {ml-pull}2235[#2235]
   and {ml-pull}2238[#2238].)
 
+=== Bug Fixes
+
+* Correct logic for restart from failover fine tuning hyperparameters for training
+  classification and regression models. (See {ml-pull}2251[#2251].)
+
 == {es} version 8.2.0
 
 === Enhancements
diff --git a/include/maths/analytics/CBoostedTreeHyperparameters.h b/include/maths/analytics/CBoostedTreeHyperparameters.h
index afa7aebc7d..b70bed2d49 100644
--- a/include/maths/analytics/CBoostedTreeHyperparameters.h
+++ b/include/maths/analytics/CBoostedTreeHyperparameters.h
@@ -440,6 +440,7 @@ class MATHS_ANALYTICS_EXPORT CBoostedTreeHyperparameters {
     static const std::string SOFT_TREE_DEPTH_LIMIT_TAG;
     static const std::string SOFT_TREE_DEPTH_TOLERANCE_TAG;
     static const std::string STOP_HYPERPARAMETER_OPTIMIZATION_EARLY_TAG;
+    static const std::string STOPPED_HYPERPARAMETER_OPTIMIZATION_EARLY_TAG;
     static const std::string TRAIN_FRACTION_PER_FOLD_TAG;
     static const std::string TREE_SIZE_PENALTY_MULTIPLIER_TAG;
 
@@ -580,7 +581,10 @@ class MATHS_ANALYTICS_EXPORT CBoostedTreeHyperparameters {
     void startSearch();
 
     //! Check if the search for the best hyperparameter values has finished.
-    bool searchNotFinished() const { return m_CurrentRound < m_NumberRounds; }
+    bool searchNotFinished() const {
+        return m_StoppedHyperparameterOptimizationEarly == false &&
+               m_CurrentRound < m_NumberRounds;
+    }
 
     //! Start a new round of hyperparameter search.
     void startNextSearchRound() { ++m_CurrentRound; }
@@ -701,6 +705,7 @@ class MATHS_ANALYTICS_EXPORT CBoostedTreeHyperparameters {
     //@ \name Hyperparameter Optimisation
     //@{
     bool m_StopHyperparameterOptimizationEarly{true};
+    bool m_StoppedHyperparameterOptimizationEarly{false};
     bool m_ScalingDisabled{false};
     std::size_t m_MaximumOptimisationRoundsPerHyperparameter{2};
     TOptionalSize m_BayesianOptimisationRestarts;
diff --git a/lib/maths/analytics/CBoostedTreeHyperparameters.cc b/lib/maths/analytics/CBoostedTreeHyperparameters.cc
index a1bccaf44d..0559a73970 100644
--- a/lib/maths/analytics/CBoostedTreeHyperparameters.cc
+++ b/lib/maths/analytics/CBoostedTreeHyperparameters.cc
@@ -389,6 +389,7 @@ bool CBoostedTreeHyperparameters::selectNext(const TMeanVarAccumulator& testLoss
         parameters = minBoundary + parameters.cwiseProduct(maxBoundary - minBoundary);
     } else if (m_StopHyperparameterOptimizationEarly &&
                m_BayesianOptimization->anovaTotalCoefficientOfVariation() < 1e-3) {
+        m_StoppedHyperparameterOptimizationEarly = true;
         return false;
     } else {
         std::tie(parameters, std::ignore) =
@@ -626,6 +627,8 @@ void CBoostedTreeHyperparameters::acceptPersistInserter(core::CStatePersistInser
                                  m_SoftTreeDepthTolerance, inserter);
     core::CPersistUtils::persist(STOP_HYPERPARAMETER_OPTIMIZATION_EARLY_TAG,
                                  m_StopHyperparameterOptimizationEarly, inserter);
+    core::CPersistUtils::persist(STOPPED_HYPERPARAMETER_OPTIMIZATION_EARLY_TAG,
+                                 m_StoppedHyperparameterOptimizationEarly, inserter);
     core::CPersistUtils::persist(TREE_SIZE_PENALTY_MULTIPLIER_TAG,
                                  m_TreeSizePenaltyMultiplier, inserter);
     // m_TunableHyperparameters is not persisted explicitly, it is re-generated
@@ -683,6 +686,9 @@ bool CBoostedTreeHyperparameters::acceptRestoreTraverser(core::CStateRestoreTrav
         RESTORE(STOP_HYPERPARAMETER_OPTIMIZATION_EARLY_TAG,
                 core::CPersistUtils::restore(STOP_HYPERPARAMETER_OPTIMIZATION_EARLY_TAG,
                                              m_StopHyperparameterOptimizationEarly, traverser))
+        RESTORE(STOPPED_HYPERPARAMETER_OPTIMIZATION_EARLY_TAG,
+                core::CPersistUtils::restore(STOPPED_HYPERPARAMETER_OPTIMIZATION_EARLY_TAG,
+                                             m_StoppedHyperparameterOptimizationEarly, traverser))
         RESTORE(TREE_SIZE_PENALTY_MULTIPLIER_TAG,
                 core::CPersistUtils::restore(TREE_SIZE_PENALTY_MULTIPLIER_TAG,
                                              m_TreeSizePenaltyMultiplier, traverser))
@@ -858,6 +864,7 @@ const std::string CBoostedTreeHyperparameters::NUMBER_ROUNDS_TAG{"number_rounds"
 const std::string CBoostedTreeHyperparameters::SOFT_TREE_DEPTH_LIMIT_TAG{"soft_tree_depth_limit"};
 const std::string CBoostedTreeHyperparameters::SOFT_TREE_DEPTH_TOLERANCE_TAG{"soft_tree_depth_tolerance"};
 const std::string CBoostedTreeHyperparameters::STOP_HYPERPARAMETER_OPTIMIZATION_EARLY_TAG{"stop_hyperparameter_optimization_early"};
+const std::string CBoostedTreeHyperparameters::STOPPED_HYPERPARAMETER_OPTIMIZATION_EARLY_TAG{"stopped_hyperparameter_optimization_early"};
 const std::string CBoostedTreeHyperparameters::TREE_SIZE_PENALTY_MULTIPLIER_TAG{"tree_size_penalty_multiplier"};
 // clang-format on
 }
diff --git a/lib/maths/analytics/CBoostedTreeImpl.cc b/lib/maths/analytics/CBoostedTreeImpl.cc
index ae27dfd18f..7af36bff96 100644
--- a/lib/maths/analytics/CBoostedTreeImpl.cc
+++ b/lib/maths/analytics/CBoostedTreeImpl.cc
@@ -204,11 +204,10 @@ void CBoostedTreeImpl::train(core::CDataFrame& frame,
 
     this->checkTrainInvariants(frame);
 
-    if (m_Loss->isRegression()) {
-        m_Instrumentation->type(CDataFrameTrainBoostedTreeInstrumentationInterface::E_Regression);
-    } else {
-        m_Instrumentation->type(CDataFrameTrainBoostedTreeInstrumentationInterface::E_Classification);
-    }
+    m_Instrumentation->type(
+        m_Loss->isRegression()
+            ? CDataFrameTrainBoostedTreeInstrumentationInterface::E_Regression
+            : CDataFrameTrainBoostedTreeInstrumentationInterface::E_Classification);
 
     LOG_TRACE(<< "Main training loop...");
 
@@ -308,11 +307,10 @@ void CBoostedTreeImpl::train(core::CDataFrame& frame,
             m_Hyperparameters.restoreBest();
             m_Hyperparameters.recordHyperparameters(*m_Instrumentation);
             m_Hyperparameters.captureScale();
+            this->startProgressMonitoringFinalTrain();
             this->scaleRegularizationMultipliers(this->allTrainingRowsMask().manhattan() /
                                                  this->meanNumberTrainingRowsPerFold());
 
-            this->startProgressMonitoringFinalTrain();
-
             // Reinitialize random number generator for reproducible results.
             m_Rng.seed(m_Seed);
 
@@ -321,6 +319,8 @@ void CBoostedTreeImpl::train(core::CDataFrame& frame,
                                .s_Forest;
 
             this->recordState(recordTrainStateCallback);
+        } else {
+            this->skipProgressMonitoringFinalTrain();
         }
         m_Instrumentation->iteration(m_Hyperparameters.currentRound());
         m_Instrumentation->flush(TRAIN_FINAL_FOREST);