diff --git a/src/axolotl/utils/config/__init__.py b/src/axolotl/utils/config/__init__.py
index 4de606565..4e26a257d 100644
--- a/src/axolotl/utils/config/__init__.py
+++ b/src/axolotl/utils/config/__init__.py
@@ -115,6 +115,7 @@ def normalize_config(cfg):
         "chrf",
     ]
     choose_device(cfg)
+    cfg.ddp = cfg.ddp if cfg.ddp is not None else cfg.world_size != 1
     if cfg.world_size != 1:
         cfg.device_map = {"": int(os.environ.get("LOCAL_RANK", 0))}
         if cfg.fsdp or cfg.fsdp_config or cfg.ddp:
diff --git a/tests/test_train.py b/tests/test_train.py
new file mode 100644
index 000000000..291e9136b
--- /dev/null
+++ b/tests/test_train.py
@@ -0,0 +1,44 @@
+"""Test for batch size calculation for multi-gpu training."""
+
+import pytest
+
+from axolotl.utils.config import normalize_config, validate_config
+from axolotl.utils.dict import DictDefault
+
+
+@pytest.fixture(name="train_base_cfg")
+def fixture_train_base_cfg():
+    return DictDefault(
+        base_model="gpt2",
+        learning_rate=1e-3,
+        datasets=[
+            {
+                "path": "mhenrichsen/alpaca_2k_test",
+                "type": "alpaca",
+            },
+        ],
+        micro_batch_size=2,
+        gradient_accumulation_steps=4,
+        sequence_len=2048,
+        sample_packing=True,
+        num_epochs=1,
+    )
+
+
+class TestTrain:
+    """test class for train related tests"""
+
+    @pytest.mark.parametrize(
+        "world_size, expected_batch_size",
+        [
+            (1, 8),
+            (4, 32),
+        ],
+    )
+    def test_batch_size_ddp(
+        self, train_base_cfg, monkeypatch, world_size, expected_batch_size
+    ):
+        monkeypatch.setenv("WORLD_SIZE", str(world_size))
+        cfg = validate_config(train_base_cfg)
+        normalize_config(cfg)
+        assert cfg.batch_size == expected_batch_size