diff --git a/onert-micro/onert-micro/include/OMConfig.h b/onert-micro/onert-micro/include/OMConfig.h
index 0ffbf024b1f..2038b57a1e7 100644
--- a/onert-micro/onert-micro/include/OMConfig.h
+++ b/onert-micro/onert-micro/include/OMConfig.h
@@ -41,6 +41,7 @@ enum OMMetrics
   MAE_METRICS,
   CROSS_ENTROPY_METRICS,
   ACCURACY,
+  SPARSE_CROSS_ENTROPY_ACCURACY,
 };
 
 /*
diff --git a/onert-micro/onert-micro/include/train/metrics/SparseCrossEntropyAccuracy.h b/onert-micro/onert-micro/include/train/metrics/SparseCrossEntropyAccuracy.h
new file mode 100644
index 00000000000..64c73ae20ea
--- /dev/null
+++ b/onert-micro/onert-micro/include/train/metrics/SparseCrossEntropyAccuracy.h
@@ -0,0 +1,43 @@
+/*
+ * Copyright (c) 2024 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ONERT_MICRO_TRAIN_METRICS_SPARSE_CROSS_ENTROPY_ACCURACY_H
+#define ONERT_MICRO_TRAIN_METRICS_SPARSE_CROSS_ENTROPY_ACCURACY_H
+
+#include "OMStatus.h"
+
+#include <cstdint>
+
+namespace onert_micro
+{
+namespace train
+{
+namespace metrics
+{
+
+// Accuracy metric
+struct SparseCrossEntropyAccuracy
+{
+  // Calculate accuracy metric between calculated and target data
+  static float calculateValue(const uint32_t flat_size, const float *calculated_data,
+                              const float *target_data);
+};
+
+} // namespace metrics
+} // namespace train
+} // namespace onert_micro
+
+#endif // ONERT_MICRO_TRAIN_METRICS_SPARSE_CROSS_ENTROPY_ACCURACY_H
diff --git a/onert-micro/onert-micro/src/core/train/OMTrainingHandler.cpp b/onert-micro/onert-micro/src/core/train/OMTrainingHandler.cpp
index 24535625a02..8ab4a9eb60b 100644
--- a/onert-micro/onert-micro/src/core/train/OMTrainingHandler.cpp
+++ b/onert-micro/onert-micro/src/core/train/OMTrainingHandler.cpp
@@ -23,6 +23,7 @@
 #include "train/metrics/CrossEntropy.h"
 #include "train/metrics/Accuracy.h"
 #include "train/metrics/MAE.h"
+#include "train/metrics/SparseCrossEntropyAccuracy.h"
 
 using namespace onert_micro::core::train;
 using namespace onert_micro::core;
@@ -222,6 +223,12 @@ OMStatus OMTrainingHandler::evaluateMetric(OMMetrics metric, void *metric_val,
     assert(calculated_data != nullptr);
 
     // Get target data
+    /** NOTE:
+     * This offset will always return 0 if the MODEL OUTPUT is returning 1 value of prediction.
+     * (forward_output->size() == length of output vector.)
+     * one-hot: size == target_numbers
+     * Sparse cross : size == 1
+     */
     size_t offset = batch_num * sizeof(core::OMDataType(forward_output_tensor->type())) * flat_size;
     uint8_t *target_data = _training_storage.getTargetData(i) + offset;
 
@@ -261,6 +268,14 @@ OMStatus OMTrainingHandler::evaluateMetric(OMMetrics metric, void *metric_val,
                                             reinterpret_cast<float *>(target_data));
         break;
       }
+      case SPARSE_CROSS_ENTROPY_ACCURACY:
+      {
+        // Note: sum up new calculated value for current sample
+        *f_metric_val += metrics::SparseCrossEntropyAccuracy::calculateValue(
+          flat_size, reinterpret_cast<float *>(calculated_data),
+          reinterpret_cast<float *>(target_data));
+        break;
+      }
       default:
       {
         assert(false && "Unsupported loss type");
diff --git a/onert-micro/onert-micro/src/train/CMakeLists.txt b/onert-micro/onert-micro/src/train/CMakeLists.txt
index 6374a9dfc9e..1df3a864ef3 100644
--- a/onert-micro/onert-micro/src/train/CMakeLists.txt
+++ b/onert-micro/onert-micro/src/train/CMakeLists.txt
@@ -18,6 +18,7 @@ set(SOURCES
         metrics/MAE.cpp
         metrics/MSE.cpp
         metrics/Accuracy.cpp
+        metrics/SparseCrossEntropyAccuracy.cpp
         train_optimizers/SGD.cpp
         train_optimizers/Adam.cpp
         )
diff --git a/onert-micro/onert-micro/src/train/metrics/SparseCrossEntropyAccuracy.cpp b/onert-micro/onert-micro/src/train/metrics/SparseCrossEntropyAccuracy.cpp
new file mode 100644
index 00000000000..260e66ba2fe
--- /dev/null
+++ b/onert-micro/onert-micro/src/train/metrics/SparseCrossEntropyAccuracy.cpp
@@ -0,0 +1,47 @@
+/*
+ * Copyright (c) 2024 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "train/metrics/SparseCrossEntropyAccuracy.h"
+
+using namespace onert_micro;
+using namespace onert_micro::train;
+using namespace onert_micro::train::metrics;
+
+/*
+ * return 1.0 if predicted class equals to target
+ * return 0.0 otherwise
+ */
+float SparseCrossEntropyAccuracy::calculateValue(const uint32_t flat_size,
+                                                 const float *calculated_data,
+                                                 const float *target_data)
+{
+  // Find target class
+  uint32_t target_class = static_cast<uint32_t>(target_data[0]);
+
+  // Find predicted class
+  float pred_class = 0.f;
+  float pred_max_val = calculated_data[0];
+  for (uint32_t i = 0; i < flat_size; ++i)
+  {
+    if (pred_max_val < calculated_data[i])
+    {
+      pred_max_val = calculated_data[i];
+      pred_class = static_cast<float>(i);
+    }
+  }
+
+  return pred_class == target_class ? 1.0f : 0.0f;
+}