diff --git a/src/learn/learn.cpp b/src/learn/learn.cpp
index b0ae62f6..3faab0ea 100644
--- a/src/learn/learn.cpp
+++ b/src/learn/learn.cpp
@@ -141,12 +141,12 @@ namespace Learner
             template <typename StreamT>
             void print(const std::string& prefix, StreamT& s) const
             {
-                s << "==> " << prefix << "_cross_entropy_eval = " << cross_entropy_eval / count << endl;
-                s << "==> " << prefix << "_cross_entropy_win  = " << cross_entropy_win / count << endl;
-                s << "==> " << prefix << "_entropy_eval       = " << entropy_eval / count << endl;
-                s << "==> " << prefix << "_entropy_win        = " << entropy_win / count << endl;
-                s << "==> " << prefix << "_cross_entropy      = " << cross_entropy / count << endl;
-                s << "==> " << prefix << "_entropy            = " << entropy / count << endl;
+                s << "  - " << prefix << "_cross_entropy_eval = " << cross_entropy_eval / count << endl;
+                s << "  - " << prefix << "_cross_entropy_win  = " << cross_entropy_win / count << endl;
+                s << "  - " << prefix << "_entropy_eval       = " << entropy_eval / count << endl;
+                s << "  - " << prefix << "_entropy_win        = " << entropy_win / count << endl;
+                s << "  - " << prefix << "_cross_entropy      = " << cross_entropy / count << endl;
+                s << "  - " << prefix << "_entropy            = " << entropy / count << endl;
             }
         };
     }
@@ -687,7 +687,7 @@ namespace Learner
              << ", epoch " << epoch
              << endl;
 
-        out << "==> learning rate = " << global_learning_rate << endl;
+        out << "  - learning rate = " << global_learning_rate << endl;
 
         // For calculation of verification data loss
         AtomicLoss test_loss_sum{};
@@ -704,7 +704,7 @@ namespace Learner
             auto& pos = th.rootPos;
             StateInfo si;
             pos.set(StartFEN, false, &si, &th);
-            out << "==> startpos eval = " << Eval::evaluate(pos) << endl;
+            out << "  - startpos eval = " << Eval::evaluate(pos) << endl;
         });
         mainThread->wait_for_worker_finished();
 
@@ -734,8 +734,8 @@ namespace Learner
                 learn_loss_sum.print("learn", out);
             }
 
-            out << "==> norm = " << sum_norm << endl;
-            out << "==> move accuracy = " << (move_accord_count * 100.0 / psv.size()) << "%" << endl;
+            out << "  - norm = " << sum_norm << endl;
+            out << "  - move accuracy = " << (move_accord_count * 100.0 / psv.size()) << "%" << endl;
         }
         else
         {
@@ -852,7 +852,7 @@ namespace Learner
                 latest_loss_sum = 0.0;
                 latest_loss_count = 0;
                 cout << "INFO (learning_rate):" << endl;
-                cout << "==> loss = " << latest_loss;
+                cout << "  - loss = " << latest_loss;
                 auto tot = total_done;
                 if (auto_lr_drop)
                 {
@@ -882,7 +882,7 @@ namespace Learner
                     if (--trials > 0 && !is_final)
                     {
                         cout
-                            << "==> reducing learning rate from " << global_learning_rate
+                            << "  - reducing learning rate from " << global_learning_rate
                             << " to " << (global_learning_rate * newbob_decay)
                             << " (" << trials << " more trials)" << endl;
 
@@ -892,7 +892,7 @@ namespace Learner
 
                 if (trials == 0)
                 {
-                    cout << "==> converged" << endl;
+                    cout << "  - converged" << endl;
                     return true;
                 }
             }
@@ -980,6 +980,8 @@ namespace Learner
         string validation_set_file_name;
         string seed;
 
+        auto out = sync_region_cout.new_region();
+
         // Assume the filenames are staggered.
         while (true)
         {
@@ -1083,7 +1085,7 @@ namespace Learner
             else if (option == "verbose") verbose = true;
             else
             {
-                cout << "Unknown option: " << option << ". Ignoring.\n";
+                out << "INFO: Unknown option: " << option << ". Ignoring.\n";
             }
         }
 
@@ -1092,11 +1094,14 @@ namespace Learner
             loss_output_interval = LEARN_RMSE_OUTPUT_INTERVAL * mini_batch_size;
         }
 
-        cout << "learn command , ";
+        // If reduction_gameply is set to 0, rand(0) will be divided by 0, so correct it to 1.
+        reduction_gameply = max(reduction_gameply, 1);
+
+        out << "INFO: Executing learn command\n";
 
         // Issue a warning if OpenMP is disabled.
 #if !defined(_OPENMP)
-        cout << "Warning! OpenMP disabled." << endl;
+        out << "WARNING: OpenMP disabled." << endl;
 #endif
 
         // Right now we only have the individual files.
@@ -1107,65 +1112,80 @@ namespace Learner
         }
         rebase_files(filenames, base_dir);
 
-        cout << "learn from ";
+        out << "INFO: Input files:\n";
         for (auto s : filenames)
-            cout << s << " , ";
+            out << "  - " << s << '\n';
 
-        cout << endl;
+        out << "INFO: Parameters:\n";
         if (!validation_set_file_name.empty())
         {
-            cout << "validation set  : " << validation_set_file_name << endl;
+            out << "  - validation set           : " << validation_set_file_name << endl;
         }
 
-        cout << "base dir        : " << base_dir << endl;
-        cout << "target dir      : " << target_dir << endl;
+        out << "  - epochs                   : " << epochs << endl;
+        out << "  - epochs * minibatch size  : " << epochs * mini_batch_size << endl;
+        out << "  - eval_limit               : " << eval_limit << endl;
+        out << "  - save_only_once           : " << (save_only_once ? "true" : "false") << endl;
+        out << "  - shuffle on read          : " << (no_shuffle ? "false" : "true") << endl;
 
-        cout << "epochs            : " << epochs << endl;
-        cout << "eval_limit        : " << eval_limit << endl;
-        cout << "save_only_once    : " << (save_only_once ? "true" : "false") << endl;
-        cout << "no_shuffle        : " << (no_shuffle ? "true" : "false") << endl;
+        out << "  - Loss Function            : " << LOSS_FUNCTION << endl;
+        out << "  - minibatch size           : " << mini_batch_size << endl;
 
-        cout << "Loss Function     : " << LOSS_FUNCTION << endl;
-        cout << "mini-batch size   : " << mini_batch_size << endl;
+        out << "  - nn_batch_size            : " << nn_batch_size << endl;
+        out << "  - nn_options               : " << nn_options << endl;
 
-        cout << "nn_batch_size     : " << nn_batch_size << endl;
-        cout << "nn_options        : " << nn_options << endl;
+        out << "  - learning rate            : " << global_learning_rate << endl;
+        out << "  - use draws in training    : " << use_draw_games_in_training << endl;
+        out << "  - use draws in validation  : " << use_draw_games_in_validation << endl;
+        out << "  - skip repeated positions  : " << skip_duplicated_positions_in_training << endl;
 
-        cout << "learning rate     : " << global_learning_rate << endl;
-        cout << "use_draw_games_in_training : " << use_draw_games_in_training << endl;
-        cout << "use_draw_games_in_validation : " << use_draw_games_in_validation << endl;
-        cout << "skip_duplicated_positions_in_training : " << skip_duplicated_positions_in_training << endl;
+        out << "  - winning prob coeff       : " << winning_probability_coefficient << endl;
+        out << "  - use_wdl                  : " << use_wdl << endl;
 
-        if (newbob_decay != 1.0) {
-            cout << "scheduling        : newbob with decay = " << newbob_decay
-                << ", " << newbob_num_trials << " trials" << endl;
+        out << "  - src_score_min_value      : " << src_score_min_value << endl;
+        out << "  - src_score_max_value      : " << src_score_max_value << endl;
+        out << "  - dest_score_min_value     : " << dest_score_min_value << endl;
+        out << "  - dest_score_max_value     : " << dest_score_max_value << endl;
+
+        out << "  - reduction_gameply        : " << reduction_gameply << endl;
+
+        out << "  - LAMBDA                   : " << ELMO_LAMBDA << endl;
+        out << "  - LAMBDA2                  : " << ELMO_LAMBDA2 << endl;
+        out << "  - LAMBDA_LIMIT             : " << ELMO_LAMBDA_LIMIT << endl;
+        out << "  - eval_save_interval       : " << eval_save_interval << " sfens" << endl;
+        out << "  - loss_output_interval     : " << loss_output_interval << " sfens" << endl;
+
+        out << "  - sfen_read_size           : " << sfen_read_size << endl;
+        out << "  - thread_buffer_size       : " << thread_buffer_size << endl;
+
+        out << "  - seed                     : " << seed << endl;
+        out << "  - verbose                  : " << (verbose ? "true" : "false") << endl;
+
+        if (auto_lr_drop) {
+            out << "  - learning rate scheduling : every " << auto_lr_drop << " sfens" << endl;
+        }
+        else if (newbob_decay != 1.0) {
+            out << "  - learning rate scheduling : newbob with decay" << endl;
+            out << "  - newbob_decay             : " << newbob_decay << endl;
+            out << "  - newbob_num_trials        : " << newbob_num_trials << endl;
         }
         else {
-            cout << "scheduling        : default" << endl;
+            out << "  - learning rate scheduling : fixed learning rate" << endl;
         }
 
-        // If reduction_gameply is set to 0, rand(0) will be divided by 0, so correct it to 1.
-        reduction_gameply = max(reduction_gameply, 1);
-        cout << "reduction_gameply : " << reduction_gameply << endl;
-
-        cout << "LAMBDA            : " << ELMO_LAMBDA << endl;
-        cout << "LAMBDA2           : " << ELMO_LAMBDA2 << endl;
-        cout << "LAMBDA_LIMIT      : " << ELMO_LAMBDA_LIMIT << endl;
-        cout << "eval_save_interval  : " << eval_save_interval << " sfens" << endl;
-        cout << "loss_output_interval: " << loss_output_interval << " sfens" << endl;
+        out << endl;
 
         // -----------------------------------
         // various initialization
         // -----------------------------------
 
-        cout << "init.." << endl;
+        out << "INFO: Started initialization." << endl;
 
         Threads.main()->ponder = false;
 
         set_learning_search_limits();
 
-        cout << "init_training.." << endl;
-        Eval::NNUE::initialize_training(seed);
+        Eval::NNUE::initialize_training(seed, out);
         Eval::NNUE::set_batch_size(nn_batch_size);
         Eval::NNUE::set_options(nn_options);
 
@@ -1204,7 +1224,9 @@ namespace Learner
 
         learn_think.verbose = verbose;
 
-        cout << "init done." << endl;
+        out << "Finished initialization." << endl;
+
+        out.unlock();
 
         // Start learning.
         learn_think.learn(epochs);
diff --git a/src/learn/sfen_reader.h b/src/learn/sfen_reader.h
index 3547b6bb..512f1165 100644
--- a/src/learn/sfen_reader.h
+++ b/src/learn/sfen_reader.h
@@ -221,7 +221,7 @@ namespace Learner{
                         // in case the file is empty or was deleted.
                         if (sfen_input_stream->eof())
                         {
-                            out << "==> File empty, nothing to read.\n";
+                            out << "  - File empty, nothing to read.\n";
                         }
                         else
                         {
diff --git a/src/misc.h b/src/misc.h
index 4c99cc2b..3e6dc5b0 100644
--- a/src/misc.h
+++ b/src/misc.h
@@ -78,27 +78,23 @@ std::ostream& operator<<(std::ostream&, SyncCout);
 // current region releases the lock.
 struct SynchronizedRegionLogger
 {
-private:
   using RegionId = std::uint64_t;
 
-  struct RegionLock
+  struct Region
   {
-    RegionLock(SynchronizedRegionLogger& log, RegionId id) :
-      logger(&log), region_id(id), is_held(true)
-    {
-    }
+    friend struct SynchronizedRegionLogger;
 
-    RegionLock(const RegionLock&) = delete;
-    RegionLock& operator=(const RegionLock&) = delete;
+    Region(const Region&) = delete;
+    Region& operator=(const Region&) = delete;
 
-    RegionLock(RegionLock&& other) :
+    Region(Region&& other) :
       logger(other.logger), region_id(other.region_id), is_held(other.is_held)
     {
       other.logger = nullptr;
       other.is_held = false;
     }
 
-    RegionLock& operator=(RegionLock&& other) {
+    Region& operator=(Region&& other) {
       if (is_held && logger != nullptr)
       {
         logger->release_region(region_id);
@@ -113,7 +109,7 @@ private:
       return *this;
     }
 
-    ~RegionLock() { unlock(); }
+    ~Region() { unlock(); }
 
     void unlock() {
       if (is_held) {
@@ -124,7 +120,7 @@ private:
       }
     }
 
-    RegionLock& operator << (std::ostream&(*pManip)(std::ostream&)) {
+    Region& operator << (std::ostream&(*pManip)(std::ostream&)) {
       if (logger != nullptr)
         logger->write(region_id, pManip);
 
@@ -132,7 +128,7 @@ private:
     }
 
     template <typename T>
-    RegionLock& operator << (const T& value) {
+    Region& operator << (const T& value) {
       if (logger != nullptr)
         logger->write(region_id, value);
 
@@ -143,11 +139,17 @@ private:
     SynchronizedRegionLogger* logger;
     RegionId region_id;
     bool is_held;
+
+    Region(SynchronizedRegionLogger& log, RegionId id) :
+      logger(&log), region_id(id), is_held(true)
+    {
+    }
   };
 
-  struct Region
+private:
+  struct RegionBookkeeping
   {
-    Region(RegionId rid) : id(rid), is_held(true) {}
+    RegionBookkeeping(RegionId rid) : id(rid), is_held(true) {}
 
     std::vector<std::string> pending_parts;
     RegionId id;
@@ -215,16 +217,16 @@ private:
 
   std::ostream& out;
 
-  std::deque<Region> regions;
+  std::deque<RegionBookkeeping> regions;
 
   std::mutex mutex;
 
-  Region* find_region_nolock(RegionId id) {
+  RegionBookkeeping* find_region_nolock(RegionId id) {
     // Linear search because the amount of concurrent regions should be small.
     auto it = std::find_if(
       regions.begin(),
       regions.end(),
-      [id](const Region& r) { return r.id == id; });
+      [id](const RegionBookkeeping& r) { return r.id == id; });
 
     if (it == regions.end())
       return nullptr;
@@ -269,9 +271,9 @@ public:
   {
   }
 
-  [[nodiscard]] RegionLock new_region() {
+  [[nodiscard]] Region new_region() {
     const auto id = init_next_region();
-    return RegionLock(*this, id);
+    return Region(*this, id);
   }
 
 };
diff --git a/src/nnue/evaluate_nnue_learner.cpp b/src/nnue/evaluate_nnue_learner.cpp
index 0151b3f8..7a72ea19 100644
--- a/src/nnue/evaluate_nnue_learner.cpp
+++ b/src/nnue/evaluate_nnue_learner.cpp
@@ -54,23 +54,28 @@ namespace Eval::NNUE {
     }  // namespace
 
     // Initialize learning
-    void initialize_training(const std::string& seed) {
-        std::cout << "Initializing NN training for "
-                  << get_architecture_string() << std::endl;
+    void initialize_training(
+        const std::string& seed,
+        SynchronizedRegionLogger::Region& out) {
 
-        std::cout << std::endl;
+        out << "INFO (initialize_training): Initializing NN training for "
+            << get_architecture_string() << std::endl;
 
-        std::cout << "Layers:\n"
-                  << get_layers_info() << std::endl;
+        out << std::endl;
 
-        std::cout << std::endl;
+        out << "Layers:\n"
+            << get_layers_info() << std::endl;
+
+        out << std::endl;
 
         assert(feature_transformer);
         assert(network);
+
         trainer = Trainer<Network>::create(network.get(), feature_transformer.get());
         rng.seed(PRNG(seed).rand<uint64_t>());
 
         if (Options["SkipLoadingEval"]) {
+            out << "INFO (initialize_training): Performing random net initialization.\n";
             trainer->initialize(rng);
         }
     }
diff --git a/src/nnue/evaluate_nnue_learner.h b/src/nnue/evaluate_nnue_learner.h
index 03a23c83..91d2aa99 100644
--- a/src/nnue/evaluate_nnue_learner.h
+++ b/src/nnue/evaluate_nnue_learner.h
@@ -3,11 +3,15 @@
 
 #include "learn/learn.h"
 
+#include "misc.h"
+
 // Interface used for learning NNUE evaluation function
 namespace Eval::NNUE {
 
     // Initialize learning
-    void initialize_training(const std::string& seed);
+    void initialize_training(
+        const std::string& seed,
+        SynchronizedRegionLogger::Region& out);
 
     // set the number of samples in the mini-batch
     void set_batch_size(uint64_t size);
diff --git a/src/nnue/layers/affine_transform.h b/src/nnue/layers/affine_transform.h
index e734580e..1227efff 100644
--- a/src/nnue/layers/affine_transform.h
+++ b/src/nnue/layers/affine_transform.h
@@ -82,9 +82,9 @@ namespace Eval::NNUE::Layers {
 
         static std::string get_layers_info() {
             std::string info = PreviousLayer::get_layers_info();
-            info += '\n';
+            info += "\n  - ";
             info += std::to_string(kLayerIndex);
-            info += ": ";
+            info += " - ";
             info += get_name();
             return info;
         }
diff --git a/src/nnue/layers/clipped_relu.h b/src/nnue/layers/clipped_relu.h
index 5fbd66cc..40185b13 100644
--- a/src/nnue/layers/clipped_relu.h
+++ b/src/nnue/layers/clipped_relu.h
@@ -76,9 +76,9 @@ namespace Eval::NNUE::Layers {
 
         static std::string get_layers_info() {
             std::string info = PreviousLayer::get_layers_info();
-            info += '\n';
+            info += "\n  - ";
             info += std::to_string(kLayerIndex);
-            info += ": ";
+            info += " - ";
             info += get_name();
             return info;
         }
diff --git a/src/nnue/layers/input_slice.h b/src/nnue/layers/input_slice.h
index 56c738af..3dc613b9 100644
--- a/src/nnue/layers/input_slice.h
+++ b/src/nnue/layers/input_slice.h
@@ -65,8 +65,9 @@ namespace Eval::NNUE::Layers {
         }
 
         static std::string get_layers_info() {
-            std::string info = std::to_string(kLayerIndex);
-            info += ": ";
+            std::string info = "  - ";
+            info += std::to_string(kLayerIndex);
+            info += " - ";
             info += get_name();
             return info;
         }
diff --git a/src/nnue/layers/sum.h b/src/nnue/layers/sum.h
index 0f71bd61..261dbee1 100644
--- a/src/nnue/layers/sum.h
+++ b/src/nnue/layers/sum.h
@@ -60,9 +60,9 @@ namespace Eval::NNUE::Layers {
 
         static std::string get_layers_info() {
             std::string info = Tail::get_layers_info();
-            info += '\n';
+            info += "\n  - ";
             info += std::to_string(kLayerIndex);
-            info += ": ";
+            info += " - ";
             info += get_name();
             return info;
         }
diff --git a/src/nnue/nnue_feature_transformer.h b/src/nnue/nnue_feature_transformer.h
index 3e18e68a..2089ab1c 100644
--- a/src/nnue/nnue_feature_transformer.h
+++ b/src/nnue/nnue_feature_transformer.h
@@ -130,8 +130,9 @@ namespace Eval::NNUE {
         }
 
         static std::string get_layers_info() {
-            std::string info = std::to_string(kLayerIndex);
-            info += ": ";
+            std::string info = "  - ";
+            info += std::to_string(kLayerIndex);
+            info += " - ";
             info += get_name();
             return info;
         }
diff --git a/src/nnue/trainer/trainer_clipped_relu.h b/src/nnue/trainer/trainer_clipped_relu.h
index 49b715db..f9bbd833 100644
--- a/src/nnue/trainer/trainer_clipped_relu.h
+++ b/src/nnue/trainer/trainer_clipped_relu.h
@@ -107,7 +107,7 @@ namespace Eval::NNUE {
                 << " - " << LayerType::get_name()
                 << std::endl;
 
-            out << "==> largest min activation = " << largest_min_activation
+            out << "  - largest min activation = " << largest_min_activation
                 << " , smallest max activation = " << smallest_max_activation
                 << std::endl;
 
diff --git a/src/nnue/trainer/trainer_feature_transformer.h b/src/nnue/trainer/trainer_feature_transformer.h
index 34c423b4..ffde6eba 100644
--- a/src/nnue/trainer/trainer_feature_transformer.h
+++ b/src/nnue/trainer/trainer_feature_transformer.h
@@ -347,17 +347,17 @@ namespace Eval::NNUE {
                 << " - " << LayerType::get_name()
                 << std::endl;
 
-            out << "==> observed " << observed_features.count()
+            out << "  - observed " << observed_features.count()
                 << " (out of " << kInputDimensions << ") features"
                 << std::endl;
 
-            out << "==> (min, max) of pre-activations = "
+            out << "  - (min, max) of pre-activations = "
                 << min_pre_activation_ << ", "
                 << max_pre_activation_ << " (limit = "
                 << kPreActivationLimit << ")"
                 << std::endl;
 
-            out << "==> largest min activation = " << largest_min_activation
+            out << "  - largest min activation = " << largest_min_activation
                 << " , smallest max activation = " << smallest_max_activation
                 << std::endl;