diff --git a/src/BayesNet/BaseClassifier.h b/src/BayesNet/BaseClassifier.h
index 2921f11..9d0a404 100644
--- a/src/BayesNet/BaseClassifier.h
+++ b/src/BayesNet/BaseClassifier.h
@@ -11,6 +11,9 @@ namespace bayesnet {
         vector<int> virtual predict(vector<vector<int>>& X) = 0;
         float virtual score(vector<vector<int>>& X, vector<int>& y) = 0;
         float virtual score(torch::Tensor& X, torch::Tensor& y) = 0;
+        int virtual getNumberOfNodes() = 0;
+        int virtual getNumberOfEdges() = 0;
+        int virtual getNumberOfStates() = 0;
         vector<string> virtual show() = 0;
         vector<string> virtual graph(string title = "") = 0;
         virtual ~BaseClassifier() = default;
diff --git a/src/BayesNet/Classifier.cc b/src/BayesNet/Classifier.cc
index c23e29e..d77c2c8 100644
--- a/src/BayesNet/Classifier.cc
+++ b/src/BayesNet/Classifier.cc
@@ -141,4 +141,8 @@ namespace bayesnet {
     {
         return fitted ? model.getEdges().size() : 0;
     }
+    int Classifier::getNumberOfStates()
+    {
+        return fitted ? model.getStates() : 0;
+    }
 }
\ No newline at end of file
diff --git a/src/BayesNet/Classifier.h b/src/BayesNet/Classifier.h
index 578b9ed..ad56336 100644
--- a/src/BayesNet/Classifier.h
+++ b/src/BayesNet/Classifier.h
@@ -32,8 +32,9 @@ namespace bayesnet {
         Classifier& fit(vector<vector<int>>& X, vector<int>& y, vector<string>& features, string className, map<string, vector<int>>& states) override;
         Classifier& fit(torch::Tensor& X, torch::Tensor& y, vector<string>& features, string className, map<string, vector<int>>& states) override;
         void addNodes();
-        int getNumberOfNodes();
-        int getNumberOfEdges();
+        int getNumberOfNodes() override;
+        int getNumberOfEdges() override;
+        int getNumberOfStates() override;
         Tensor predict(Tensor& X);
         vector<int> predict(vector<vector<int>>& X) override;
         float score(Tensor& X, Tensor& y) override;
diff --git a/src/BayesNet/Ensemble.cc b/src/BayesNet/Ensemble.cc
index b8c6418..8aa2518 100644
--- a/src/BayesNet/Ensemble.cc
+++ b/src/BayesNet/Ensemble.cc
@@ -130,4 +130,28 @@ namespace bayesnet {
         }
         return result;
     }
+    int Ensemble::getNumberOfNodes()
+    {
+        int nodes = 0;
+        for (auto i = 0; i < n_models; ++i) {
+            nodes += models[i]->getNumberOfNodes();
+        }
+        return nodes;
+    }
+    int Ensemble::getNumberOfEdges()
+    {
+        int edges = 0;
+        for (auto i = 0; i < n_models; ++i) {
+            edges += models[i]->getNumberOfEdges();
+        }
+        return edges;
+    }
+    int Ensemble::getNumberOfStates()
+    {
+        int states = 0;
+        for (auto i = 0; i < n_models; ++i) {
+            states += models[i]->getNumberOfStates();
+        }
+        return states;
+    }
 }
\ No newline at end of file
diff --git a/src/BayesNet/Ensemble.h b/src/BayesNet/Ensemble.h
index e25ee75..d45575d 100644
--- a/src/BayesNet/Ensemble.h
+++ b/src/BayesNet/Ensemble.h
@@ -36,6 +36,9 @@ namespace bayesnet {
         vector<int> predict(vector<vector<int>>& X) override;
         float score(Tensor& X, Tensor& y) override;
         float score(vector<vector<int>>& X, vector<int>& y) override;
+        int getNumberOfNodes() override;
+        int getNumberOfEdges() override;
+        int getNumberOfStates() override;
         vector<string> show() override;
         vector<string> graph(string title) override;
     };
diff --git a/src/Platform/Experiment.cc b/src/Platform/Experiment.cc
index aa1159d..583f460 100644
--- a/src/Platform/Experiment.cc
+++ b/src/Platform/Experiment.cc
@@ -2,36 +2,48 @@
 
 namespace platform {
     using json = nlohmann::json;
-    string get_date_time()
+    string get_date()
     {
         time_t rawtime;
         tm* timeinfo;
         time(&rawtime);
         timeinfo = std::localtime(&rawtime);
-
         std::ostringstream oss;
-        oss << std::put_time(timeinfo, "%Y-%m-%d_%H:%M:%S");
+        oss << std::put_time(timeinfo, "%Y-%m-%d");
+        return oss.str();
+    }
+    string get_time()
+    {
+        time_t rawtime;
+        tm* timeinfo;
+        time(&rawtime);
+        timeinfo = std::localtime(&rawtime);
+        std::ostringstream oss;
+        oss << std::put_time(timeinfo, "%H:%M:%S");
         return oss.str();
     }
     string Experiment::get_file_name()
     {
-        string date_time = get_date_time();
-        string result = "results_" + score_name + "_" + model + "_" + platform + "_" + date_time + "_" + (stratified ? "1" : "0") + ".json";
+        string result = "results_" + score_name + "_" + model + "_" + platform + "_" + get_date() + "_" + get_time() + "_" + (stratified ? "1" : "0") + ".json";
         return result;
     }
+
     json Experiment::build_json()
     {
         json result;
         result["title"] = title;
+        result["date"] = get_date();
+        result["time"] = get_time();
         result["model"] = model;
+        result["version"] = model_version;
         result["platform"] = platform;
         result["score_name"] = score_name;
-        result["model_version"] = model_version;
+        result["language"] = language;
         result["language_version"] = language_version;
         result["discretized"] = discretized;
         result["stratified"] = stratified;
-        result["nfolds"] = nfolds;
-        result["random_seeds"] = random_seeds;
+        result["folds"] = nfolds;
+        result["seeds"] = random_seeds;
         result["duration"] = duration;
         result["results"] = json::array();
         for (auto& r : results) {
@@ -43,12 +55,19 @@ namespace platform {
             j["classes"] = r.getClasses();
             j["score_train"] = r.getScoreTrain();
             j["score_test"] = r.getScoreTest();
+            j["score"] = r.getScoreTest();
+            j["score_std"] = r.getScoreTestStd();
             j["score_train_std"] = r.getScoreTrainStd();
             j["score_test_std"] = r.getScoreTestStd();
             j["train_time"] = r.getTrainTime();
             j["train_time_std"] = r.getTrainTimeStd();
             j["test_time"] = r.getTestTime();
             j["test_time_std"] = r.getTestTimeStd();
+            j["time"] = r.getTestTime() + r.getTrainTime();
+            j["time_std"] = r.getTestTimeStd() + r.getTrainTimeStd();
+            j["nodes"] = r.getNodes();
+            j["leaves"] = r.getLeaves();
+            j["depth"] = r.getDepth();
             result["results"].push_back(j);
         }
         return result;
@@ -69,11 +88,16 @@ namespace platform {
         );
         auto Xt = torch::transpose(X, 0, 1);
         auto result = Result();
+        auto [values, counts] = at::_unique(y);
+        result.setSamples(X.size(0)).setFeatures(X.size(1)).setClasses(values.size(0));
         auto k = fold->getNumberOfFolds();
         auto accuracy_test = torch::zeros({ k }, torch::kFloat64);
         auto accuracy_train = torch::zeros({ k }, torch::kFloat64);
         auto train_time = torch::zeros({ k }, torch::kFloat64);
         auto test_time = torch::zeros({ k }, torch::kFloat64);
+        auto nodes = torch::zeros({ k }, torch::kFloat64);
+        auto edges = torch::zeros({ k }, torch::kFloat64);
+        auto num_states = torch::zeros({ k }, torch::kFloat64);
         Timer train_timer, test_timer;
         for (int i = 0; i < k; i++) {
             bayesnet::BaseClassifier* model = classifiers[model_name];
@@ -86,6 +110,9 @@ namespace platform {
             auto X_test = Xt.index({ "...", test_t });
             auto y_test = y.index({ test_t });
             model->fit(X_train, y_train, features, className, states);
+            nodes[i] = model->getNumberOfNodes();
+            edges[i] = model->getNumberOfEdges();
+            num_states[i] = model->getNumberOfStates();
             cout << "Training Fold " << i + 1 << endl;
             cout << "X_train: " << X_train.sizes() << endl;
             cout << "y_train: " << y_train.sizes() << endl;
@@ -102,6 +129,7 @@ namespace platform {
         result.setScoreTest(torch::mean(accuracy_test).item<double>()).setScoreTrain(torch::mean(accuracy_train).item<double>());
         result.setScoreTestStd(torch::std(accuracy_test).item<double>()).setScoreTrainStd(torch::std(accuracy_train).item<double>());
         result.setTrainTime(torch::mean(train_time).item<double>()).setTestTime(torch::mean(test_time).item<double>());
+        result.setNodes(torch::mean(nodes).item<double>()).setLeaves(torch::mean(edges).item<double>()).setDepth(torch::mean(num_states).item<double>());
         return result;
     }
 }
\ No newline at end of file
diff --git a/src/Platform/Experiment.h b/src/Platform/Experiment.h
index ce68052..bfd3b5f 100644
--- a/src/Platform/Experiment.h
+++ b/src/Platform/Experiment.h
@@ -20,13 +20,14 @@ namespace platform {
         Timer() = default;
         ~Timer() = default;
         void start() { begin = chrono::high_resolution_clock::now(); }
-        float getDuration() { return chrono::duration_cast<chrono::milliseconds>(chrono::high_resolution_clock::now() - begin).count(); }
+        float getDuration() { return chrono::duration_cast<chrono::milliseconds>(chrono::high_resolution_clock::now() - begin).count() / 1000; }
     };
     class Result {
     private:
         string dataset, hyperparameters;
         int samples, features, classes;
         float score_train, score_test, score_train_std, score_test_std, train_time, train_time_std, test_time, test_time_std;
+        float nodes, leaves, depth;
     public:
         Result() = default;
         Result& setDataset(string dataset) { this->dataset = dataset; return *this; }
@@ -42,6 +43,9 @@ namespace platform {
         Result& setTrainTimeStd(float train_time_std) { this->train_time_std = train_time_std; return *this; }
         Result& setTestTime(float test_time) { this->test_time = test_time; return *this; }
         Result& setTestTimeStd(float test_time_std) { this->test_time_std = test_time_std; return *this; }
+        Result& setNodes(float nodes) { this->nodes = nodes; return *this; }
+        Result& setLeaves(float leaves) { this->leaves = leaves; return *this; }
+        Result& setDepth(float depth) { this->depth = depth; return *this; }
         const float get_score_train() const { return score_train; }
         float get_score_test() { return score_test; }
         const string& getDataset() const { return dataset; }
@@ -57,10 +61,13 @@ namespace platform {
         const float getTrainTimeStd() const { return train_time_std; }
         const float getTestTime() const { return test_time; }
         const float getTestTimeStd() const { return test_time_std; }
+        const float getNodes() const { return nodes; }
+        const float getLeaves() const { return leaves; }
+        const float getDepth() const { return depth; }
     };
     class Experiment {
     private:
-        string title, model, platform, score_name, model_version, language_version;
+        string title, model, platform, score_name, model_version, language_version, language;
         bool discretized, stratified;
         vector<Result> results;
         vector<int> random_seeds;
@@ -74,6 +81,7 @@ namespace platform {
         Experiment& setPlatform(string platform) { this->platform = platform; return *this; }
         Experiment& setScoreName(string score_name) { this->score_name = score_name; return *this; }
         Experiment& setModelVersion(string model_version) { this->model_version = model_version; return *this; }
+        Experiment& setLanguage(string language) { this->language = language; return *this; }
         Experiment& setLanguageVersion(string language_version) { this->language_version = language_version; return *this; }
         Experiment& setDiscretized(bool discretized) { this->discretized = discretized; return *this; }
         Experiment& setStratified(bool stratified) { this->stratified = stratified; return *this; }
diff --git a/src/Platform/main.cc b/src/Platform/main.cc
index b2f78b7..d54d8ea 100644
--- a/src/Platform/main.cc
+++ b/src/Platform/main.cc
@@ -18,8 +18,6 @@
 
 using namespace std;
 
-
-
 int main(int argc, char** argv)
 {
     map<string, bool> datasets = {
@@ -60,6 +58,7 @@ int main(int argc, char** argv)
         throw runtime_error("Model must be one of {AODE, KDB, SPODE, TAN}");
             }
     );
+    program.add_argument("--title").required().help("Experiment title");
     program.add_argument("--discretize").help("Discretize input dataset").default_value(false).implicit_value(true);
     program.add_argument("--stratified").help("If Stratified KFold is to be done").default_value(false).implicit_value(true);
     program.add_argument("-f", "--folds").help("Number of folds").default_value(5).scan<'i', int>().action([](const string& value) {
@@ -79,7 +78,7 @@ int main(int argc, char** argv)
     program.add_argument("-s", "--seed").help("Random seed").default_value(-1).scan<'i', int>();
     bool class_last, discretize_dataset, stratified;
     int n_folds, seed;
-    string model_name, file_name, path, complete_file_name;
+    string model_name, file_name, path, complete_file_name, title;
     try {
         program.parse_args(argc, argv);
         file_name = program.get<string>("dataset");
@@ -91,6 +90,7 @@ int main(int argc, char** argv)
         seed = program.get<int>("seed");
         complete_file_name = path + file_name + ".arff";
         class_last = datasets[file_name];
+        title = program.get<string>("title");
         if (!file_exists(complete_file_name)) {
             throw runtime_error("Data File " + path + file_name + ".arff" + " does not exist");
         }
@@ -110,7 +110,8 @@ int main(int argc, char** argv)
     else
         fold = new KFold(n_folds, y.numel(), seed);
     auto experiment = platform::Experiment();
-    experiment.setDiscretized(discretize_dataset).setModel(model_name).setPlatform("cpp");
+    experiment.setTitle(title).setLanguage("cpp").setLanguageVersion("1.0.0");
+    experiment.setDiscretized(discretize_dataset).setModel(model_name).setModelVersion("1...0").setPlatform("BayesNet");
     experiment.setStratified(stratified).setNFolds(n_folds).addRandomSeed(seed).setScoreName("accuracy");
     platform::Timer timer;
     timer.start();