diff --git a/spacy/cli/debug_model.py b/spacy/cli/debug_model.py
index 58908c5e8..04a14bdc9 100644
--- a/spacy/cli/debug_model.py
+++ b/spacy/cli/debug_model.py
@@ -60,13 +60,12 @@ def debug_model_cli(
         msg.info(f"Fixing random seed: {seed}")
         fix_random_seed(seed)
     pipe = nlp.get_pipe(component)
-    if hasattr(pipe, "model"):
-        model = pipe.model
-    else:
+    if not hasattr(pipe, "model"):
         msg.fail(
             f"The component '{component}' does not specify an object that holds a Model.",
             exits=1,
         )
+    model = pipe.model
     debug_model(model, print_settings=print_settings)
 
 
@@ -87,7 +86,7 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
 
     # STEP 1: Initializing the model and printing again
     X = _get_docs()
-    Y = _get_output(model.ops.xp)
+    Y = _get_output(model.ops)
     # The output vector might differ from the official type of the output layer
     with data_validation(False):
         model.initialize(X=X, Y=Y)
@@ -113,9 +112,11 @@ def debug_model(model: Model, *, print_settings: Optional[Dict[str, Any]] = None
         msg.divider(f"STEP 3 - prediction")
         msg.info(str(prediction))
 
+    msg.good(f"Succesfully ended analysis - model looks good!")
+
 
 def get_gradient(model, Y):
-    goldY = _get_output(model.ops.xp)
+    goldY = _get_output(model.ops)
     return Y - goldY
 
 
@@ -133,8 +134,14 @@ def _get_docs(lang: str = "en"):
     return list(nlp.pipe(_sentences()))
 
 
-def _get_output(xp):
-    return xp.asarray([i + 10 for i, _ in enumerate(_get_docs())], dtype="float32")
+def _get_output(ops):
+    docs = len(_get_docs())
+    labels = 6
+    output = ops.alloc2f(d0=docs, d1=labels)
+    for i in range(docs):
+        for j in range(labels):
+            output[i, j] = 1 / (i+j+0.01)
+    return ops.xp.asarray(output)
 
 
 def _print_model(model, print_settings):