diff --git a/src/nnue/evaluate_nnue_learner.cpp b/src/nnue/evaluate_nnue_learner.cpp
index 78446af2..6e0572dd 100644
--- a/src/nnue/evaluate_nnue_learner.cpp
+++ b/src/nnue/evaluate_nnue_learner.cpp
@@ -214,7 +214,7 @@ namespace Eval::NNUE {
         std::vector<double> gradient_norm_local(thread_pool.size(), 0.0);
 
         auto prev_batch_begin = examples.end();
-        while (prev_batch_begin - examples.begin() >= batch_size) {
+        while ((long)(prev_batch_begin - examples.begin()) >= (long)batch_size) {
             auto batch_begin = prev_batch_begin - batch_size;
             auto batch_end = prev_batch_begin;
             auto size = batch_end - batch_begin;
diff --git a/src/nnue/trainer/trainer_affine_transform.h b/src/nnue/trainer/trainer_affine_transform.h
index b6d70aa4..53e8f904 100644
--- a/src/nnue/trainer/trainer_affine_transform.h
+++ b/src/nnue/trainer/trainer_affine_transform.h
@@ -95,7 +95,7 @@ namespace Eval::NNUE {
         {
             const auto size = batch_end - batch_begin;
 
-            if (output_.size() < kOutputDimensions * size) {
+            if ((long)output_.size() < (long)kOutputDimensions * size) {
                 output_.resize(kOutputDimensions * size);
                 gradients_.resize(kInputDimensions * size);
             }
diff --git a/src/nnue/trainer/trainer_clipped_relu.h b/src/nnue/trainer/trainer_clipped_relu.h
index eae35df6..ff883afc 100644
--- a/src/nnue/trainer/trainer_clipped_relu.h
+++ b/src/nnue/trainer/trainer_clipped_relu.h
@@ -46,7 +46,7 @@ namespace Eval::NNUE {
         {
             const auto size = batch_end - batch_begin;
 
-            if (output_.size() < kOutputDimensions * size) {
+            if ((long)output_.size() < (long)kOutputDimensions * size) {
               output_.resize(kOutputDimensions * size);
               gradients_.resize(kInputDimensions * size);
             }
diff --git a/src/nnue/trainer/trainer_feature_transformer.h b/src/nnue/trainer/trainer_feature_transformer.h
index 877a74bc..9afda728 100644
--- a/src/nnue/trainer/trainer_feature_transformer.h
+++ b/src/nnue/trainer/trainer_feature_transformer.h
@@ -93,7 +93,7 @@ namespace Eval::NNUE {
         {
             const auto size = batch_end - batch_begin;
 
-            if (output_.size() < kOutputDimensions * size) {
+            if ((long)output_.size() < (long)kOutputDimensions * size) {
                 output_.resize(kOutputDimensions * size);
                 gradients_.resize(kOutputDimensions * size);
             }
diff --git a/src/nnue/trainer/trainer_input_slice.h b/src/nnue/trainer/trainer_input_slice.h
index ad681d57..a94cae93 100644
--- a/src/nnue/trainer/trainer_input_slice.h
+++ b/src/nnue/trainer/trainer_input_slice.h
@@ -66,8 +66,8 @@ namespace Eval::NNUE {
         const LearnFloatType* step_start(ThreadPool& thread_pool, std::vector<Example>::const_iterator batch_begin, std::vector<Example>::const_iterator batch_end)
         {
             const auto size = batch_end - batch_begin;
-            
-            if (gradients_.size() < kInputDimensions * size) {
+
+            if ((long)gradients_.size() < (long)kInputDimensions * size) {
                 gradients_.resize(kInputDimensions * size);
             }
 
@@ -244,7 +244,7 @@ namespace Eval::NNUE {
         {
             const auto size = batch_end - batch_begin;
 
-            if (output_.size() < kOutputDimensions * size) {
+            if ((long)output_.size() < (long)kOutputDimensions * size) {
               output_.resize(kOutputDimensions * size);
               gradients_.resize(kInputDimensions * size);
             }