diff --git a/bayesnet/classifiers/KDBLd.cc b/bayesnet/classifiers/KDBLd.cc
index 1b96bce..dbda394 100644
--- a/bayesnet/classifiers/KDBLd.cc
+++ b/bayesnet/classifiers/KDBLd.cc
@@ -8,7 +8,7 @@
 #include <memory>
 
 namespace bayesnet {
-    KDBLd::KDBLd(int k) : KDB(k), Proposal(dataset, features, className)
+    KDBLd::KDBLd(int k) : KDB(k), Proposal(dataset, features, className, KDB::notes)
     {
         validHyperparameters = validHyperparameters_ld;
         validHyperparameters.push_back("k");
diff --git a/bayesnet/classifiers/Proposal.cc b/bayesnet/classifiers/Proposal.cc
index b634b6e..b3c7639 100644
--- a/bayesnet/classifiers/Proposal.cc
+++ b/bayesnet/classifiers/Proposal.cc
@@ -16,7 +16,7 @@
 #include "TANLd.h"
 
 namespace bayesnet {
-    Proposal::Proposal(torch::Tensor& dataset_, std::vector<std::string>& features_, std::string& className_) : pDataset(dataset_), pFeatures(features_), pClassName(className_)
+    Proposal::Proposal(torch::Tensor& dataset_, std::vector<std::string>& features_, std::string& className_, std::vector<std::string>& notes_) : pDataset(dataset_), pFeatures(features_), pClassName(className_), notes(notes_)
     {
     }
     void Proposal::setHyperparameters(nlohmann::json& hyperparameters)
@@ -215,6 +215,8 @@ namespace bayesnet {
                 if (convergence_params.verbose) {
                     std::cout << "Converged after " << (iteration + 1) << " iterations" << std::endl;
                 }
+                notes.push_back("Converged after " + std::to_string(iteration + 1) + " of "
+                    + std::to_string(convergence_params.maxIterations) + " iterations");
                 break;
             }
 
diff --git a/bayesnet/classifiers/Proposal.h b/bayesnet/classifiers/Proposal.h
index 9f23283..bb53776 100644
--- a/bayesnet/classifiers/Proposal.h
+++ b/bayesnet/classifiers/Proposal.h
@@ -18,7 +18,7 @@
 namespace bayesnet {
     class Proposal {
     public:
-        Proposal(torch::Tensor& pDataset, std::vector<std::string>& features_, std::string& className_);
+        Proposal(torch::Tensor& pDataset, std::vector<std::string>& features_, std::string& className_, std::vector<std::string>& notes);
         void setHyperparameters(nlohmann::json& hyperparameters_);
     protected:
         void checkInput(const torch::Tensor& X, const torch::Tensor& y);
@@ -61,6 +61,7 @@ namespace bayesnet {
         };
     private:
         std::vector<int> factorize(const std::vector<std::string>& labels_t);
+        std::vector<std::string>& notes; // Notes during fit from BaseClassifier
         torch::Tensor& pDataset; // (n+1)xm tensor
         std::vector<std::string>& pFeatures;
         std::string& pClassName;
diff --git a/bayesnet/classifiers/SPODELd.cc b/bayesnet/classifiers/SPODELd.cc
index 8cdbdec..0cffe63 100644
--- a/bayesnet/classifiers/SPODELd.cc
+++ b/bayesnet/classifiers/SPODELd.cc
@@ -7,7 +7,7 @@
 #include "SPODELd.h"
 
 namespace bayesnet {
-    SPODELd::SPODELd(int root) : SPODE(root), Proposal(dataset, features, className)
+    SPODELd::SPODELd(int root) : SPODE(root), Proposal(dataset, features, className, SPODE::notes)
     {
         validHyperparameters = validHyperparameters_ld; // Inherits the valid hyperparameters from Proposal
     }
diff --git a/bayesnet/classifiers/TANLd.cc b/bayesnet/classifiers/TANLd.cc
index b415b0f..c9de329 100644
--- a/bayesnet/classifiers/TANLd.cc
+++ b/bayesnet/classifiers/TANLd.cc
@@ -8,7 +8,7 @@
 #include <memory>
 
 namespace bayesnet {
-    TANLd::TANLd() : TAN(), Proposal(dataset, features, className)
+    TANLd::TANLd() : TAN(), Proposal(dataset, features, className, TAN::notes)
     {
         validHyperparameters = validHyperparameters_ld; // Inherits the valid hyperparameters from Proposal
     }
diff --git a/bayesnet/ensembles/AODELd.cc b/bayesnet/ensembles/AODELd.cc
index 3dc80bf..4f0f0cd 100644
--- a/bayesnet/ensembles/AODELd.cc
+++ b/bayesnet/ensembles/AODELd.cc
@@ -7,7 +7,7 @@
 #include "AODELd.h"
 
 namespace bayesnet {
-    AODELd::AODELd(bool predict_voting) : Ensemble(predict_voting), Proposal(dataset, features, className)
+    AODELd::AODELd(bool predict_voting) : Ensemble(predict_voting), Proposal(dataset, features, className, Ensemble::notes)
     {
         validHyperparameters = validHyperparameters_ld; // Inherits the valid hyperparameters from Proposal
     }
diff --git a/tests/TestBayesModels.cc b/tests/TestBayesModels.cc
index 26cd773..4473c35 100644
--- a/tests/TestBayesModels.cc
+++ b/tests/TestBayesModels.cc
@@ -407,14 +407,15 @@ TEST_CASE("Check proposal checkInput", "[Models]")
 {
     class testProposal : public bayesnet::Proposal {
     public:
-        testProposal(torch::Tensor& dataset_, std::vector<std::string>& features_, std::string& className_)
-            : Proposal(dataset_, features_, className_)
+        testProposal(torch::Tensor& dataset_, std::vector<std::string>& features_, std::string& className_, std::vector<std::string>& notes_)
+            : Proposal(dataset_, features_, className_, notes_)
         {
         }
         void test_X_y(const torch::Tensor& X, const torch::Tensor& y) { checkInput(X, y); }
     };
     auto raw = RawDatasets("iris", true);
-    auto clf = testProposal(raw.dataset, raw.features, raw.className);
+    std::vector<std::string> notes;
+    auto clf = testProposal(raw.dataset, raw.features, raw.className, notes);
     torch::Tensor X = torch::randint(0, 3, { 10, 4 });
     torch::Tensor y = torch::rand({ 10 });
     INFO("Check X is not float");