diff --git a/tests/unit/algorithms/common/adapters/torch/utils/test_automatic_bs.py b/tests/unit/algorithms/common/adapters/torch/utils/test_automatic_bs.py
new file mode 100644
index 00000000000..959481c7f04
--- /dev/null
+++ b/tests/unit/algorithms/common/adapters/torch/utils/test_automatic_bs.py
@@ -0,0 +1,51 @@
+import pytest
+
+from otx.algorithms.common.adapters.torch.utils import adapt_batch_size
+from otx.algorithms.common.adapters.torch.utils import automatic_bs
+
+
+def test_adapt_batch_size(mocker):
+    mocker_torch = mocker.patch.object(automatic_bs, "torch")
+    mocker_torch.cuda.mem_get_info.return_value = (1, 10000)
+
+    def mock_train_func(batch_size):
+        if batch_size > 100:
+            mocker_torch.cuda.max_memory_allocated.return_value = 10000
+            raise RuntimeError("CUDA out of memory.")
+        elif batch_size > 80:
+            mocker_torch.cuda.max_memory_allocated.return_value = 9000
+        else:
+            mocker_torch.cuda.max_memory_allocated.return_value = 1000
+
+    adapted_bs = adapt_batch_size(mock_train_func, 128, 1000)
+
+    assert adapted_bs == 80
+
+
+def test_adapt_batch_size_gpu_memory_too_small(mocker):
+    mocker_torch = mocker.patch.object(automatic_bs, "torch")
+    mocker_torch.cuda.mem_get_info.return_value = (1, 10000)
+
+    def mock_train_func(batch_size):
+        if batch_size > 4:
+            mocker_torch.cuda.max_memory_allocated.return_value = 10000
+            raise RuntimeError("CUDA out of memory.")
+        elif batch_size >= 2:
+            mocker_torch.cuda.max_memory_allocated.return_value = 9000
+        else:
+            mocker_torch.cuda.max_memory_allocated.return_value = 1000
+
+    with pytest.raises(RuntimeError):
+        adapt_batch_size(mock_train_func, 128, 1000)
+
+
+@pytest.mark.parametrize("default_bs", [-1, 0])
+def test_adapt_batch_size_wrong_default_bs(mocker, default_bs):
+    with pytest.raises(ValueError):
+        adapt_batch_size(mocker.MagicMock(), default_bs, 1000)
+
+
+@pytest.mark.parametrize("trainset_size", [-1, 0])
+def test_adapt_batch_size_wrong_trainset_size(mocker, trainset_size):
+    with pytest.raises(ValueError):
+        adapt_batch_size(mocker.MagicMock(), 8, trainset_size)