diff --git a/tests/models/demucs_test.py b/tests/models/demucs_test.py
index f5a0ec4..29e030e 100644
--- a/tests/models/demucs_test.py
+++ b/tests/models/demucs_test.py
@@ -30,7 +30,7 @@ def test_forward(batch_size, samples):
 
     data = torch.rand(batch_size, 2, samples, requires_grad=False)
     with torch.no_grad():
-        with pytest.raises(TypeError):
+        with pytest.raises(ValueError):
             _ = model(data)
 
 
diff --git a/tests/models/test_dccrn.py b/tests/models/test_dccrn.py
new file mode 100644
index 0000000..96a853b
--- /dev/null
+++ b/tests/models/test_dccrn.py
@@ -0,0 +1,43 @@
+import pytest
+import torch
+
+from enhancer.data.dataset import EnhancerDataset
+from enhancer.models.dccrn import DCCRN
+from enhancer.utils.config import Files
+
+
+@pytest.fixture
+def vctk_dataset():
+    root_dir = "tests/data/vctk"
+    files = Files(
+        train_clean="clean_testset_wav",
+        train_noisy="noisy_testset_wav",
+        test_clean="clean_testset_wav",
+        test_noisy="noisy_testset_wav",
+    )
+    dataset = EnhancerDataset(name="vctk", root_dir=root_dir, files=files)
+    return dataset
+
+
+@pytest.mark.parametrize("batch_size,samples", [(1, 1000)])
+def test_forward(batch_size, samples):
+    model = DCCRN()
+    model.eval()
+
+    data = torch.rand(batch_size, 1, samples, requires_grad=False)
+    with torch.no_grad():
+        _ = model(data)
+
+    data = torch.rand(batch_size, 2, samples, requires_grad=False)
+    with torch.no_grad():
+        with pytest.raises(ValueError):
+            _ = model(data)
+
+
+@pytest.mark.parametrize(
+    "dataset,channels,loss",
+    [(pytest.lazy_fixture("vctk_dataset"), 1, ["mae", "mse"])],
+)
+def test_demucs_init(dataset, channels, loss):
+    with torch.no_grad():
+        _ = DCCRN(num_channels=channels, dataset=dataset, loss=loss)