diff --git a/bench/barite/barite_200ai_surrogate_input_script.R b/bench/barite/barite_200ai_surrogate_input_script.R
index 63b8f66ad..93e8e0191 100644
--- a/bench/barite/barite_200ai_surrogate_input_script.R
+++ b/bench/barite/barite_200ai_surrogate_input_script.R
@@ -38,7 +38,7 @@ mass_balance <- function(predictors, prediction) {
 }
 
 validate_predictions <- function(predictors, prediction) {
-  epsilon <- 0.00003
+  epsilon <- 0.000000003
   mb <- mass_balance(predictors, prediction)
   msgm("Mass balance mean:", mean(mb))
   msgm("Mass balance variance:", var(mb))
diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
index 66dc48a50..24c10c834 100644
--- a/src/CMakeLists.txt
+++ b/src/CMakeLists.txt
@@ -83,4 +83,3 @@ target_link_libraries(poet_init PRIVATE POETLib RRuntime)
 target_include_directories(poet_init PRIVATE "${CMAKE_CURRENT_BINARY_DIR}")
 
 install(TARGETS poet poet_init DESTINATION bin)
-
diff --git a/src/poet.cpp b/src/poet.cpp
index 65264c746..5ee6260fc 100644
--- a/src/poet.cpp
+++ b/src/poet.cpp
@@ -289,9 +289,6 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
       // Predict
       R.parseEval("predictors_scaled <- preprocess(predictors)");
 
-      R.parseEval("print('PREDICTORS:')");
-      R.parseEval("print(head(predictors))");
-
       R.parseEval("prediction <- preprocess(prediction_step(model, predictors_scaled),\
                                             backtransform = TRUE,\
                                             outputs = TRUE)");
@@ -327,9 +324,6 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
       
       // TODO: Check how to get the correct columns
       R.parseEval("target_scaled <- preprocess(targets, outputs = TRUE)");
-      
-      R.parseEval("print('TARGET:')");
-      R.parseEval("print(head(target_scaled))");
 
       R.parseEval("training_step(model, predictors_scaled, target_scaled, validity_vector)");
       double ai_end_t = MPI_Wtime();