diff --git a/studio/backend/utils/datasets/dataset_utils.py b/studio/backend/utils/datasets/dataset_utils.py
index 9d15b86ca1..7703488878 100644
--- a/studio/backend/utils/datasets/dataset_utils.py
+++ b/studio/backend/utils/datasets/dataset_utils.py
@@ -80,9 +80,6 @@ def check_dataset_format(dataset, is_vlm: bool = False) -> dict:
     multimodal_info = detect_multimodal_dataset(dataset)
     is_audio = multimodal_info.get("is_audio", False)
 
-    if multimodal_info["is_image"]:
-        is_vlm = True  # Route to VLM detection for image datasets
-
     # Common audio fields for all return paths
     audio_fields = {
         "is_audio": is_audio,
@@ -153,8 +150,8 @@ def check_dataset_format(dataset, is_vlm: bool = False) -> dict:
                 "suggested_mapping": heuristic_mapping,
                 "detected_image_column": None,
                 "detected_text_column": None,
-                "is_image": False,
-                "multimodal_columns": None,
+                "is_image": multimodal_info["is_image"],
+                "multimodal_columns": multimodal_info.get("multimodal_columns"),
                 **audio_fields,
             }
         else:
@@ -166,8 +163,8 @@ def check_dataset_format(dataset, is_vlm: bool = False) -> dict:
                 "suggested_mapping": None,
                 "detected_image_column": None,
                 "detected_text_column": None,
-                "is_image": False,
-                "multimodal_columns": None,
+                "is_image": multimodal_info["is_image"],
+                "multimodal_columns": multimodal_info.get("multimodal_columns"),
                 "warning": (
                     f"Could not auto-detect column roles for columns: {columns}. "
                     "Please assign roles manually, or use AI Assist."
@@ -183,8 +180,8 @@ def check_dataset_format(dataset, is_vlm: bool = False) -> dict:
         "suggested_mapping": None,
         "detected_image_column": None,
         "detected_text_column": None,
-        "is_image": False,
-        "multimodal_columns": None,
+        "is_image": multimodal_info["is_image"],
+        "multimodal_columns": multimodal_info.get("multimodal_columns"),
         **audio_fields,
     }
 
diff --git a/studio/frontend/src/features/studio/sections/training-section.tsx b/studio/frontend/src/features/studio/sections/training-section.tsx
index d1cec00e22..a47654d290 100644
--- a/studio/frontend/src/features/studio/sections/training-section.tsx
+++ b/studio/frontend/src/features/studio/sections/training-section.tsx
@@ -46,7 +46,8 @@ export function TrainingSection() {
   const store = useTrainingConfigStore();
   const { isStarting, startError, startTrainingRun } = useTrainingActions();
   const isIncompatible =
-    !store.isVisionModel && store.isDatasetImage === true;
+    (!store.isVisionModel && store.isDatasetImage === true) ||
+    (!store.isAudioModel && store.isDatasetAudio === true);
   const configValidation = validateTrainingConfig(store);
   const fileInputRef = useRef<HTMLInputElement>(null);
 
@@ -155,10 +156,10 @@ export function TrainingSection() {
           data-tour="studio-start"
           className="w-full cursor-pointer bg-gradient-to-r from-emerald-500 to-teal-500 text-white hover:from-emerald-600 hover:to-teal-600"
           onClick={() => void startTrainingRun()}
-          disabled={isStarting || isIncompatible || !configValidation.ok}
+          disabled={isStarting || isIncompatible || store.isCheckingDataset || !configValidation.ok}
         >
           <HugeiconsIcon icon={Rocket01Icon} className="size-4" />
-          {isStarting ? "Starting..." : "Start Training"}
+          {isStarting ? "Starting..." : store.isCheckingDataset ? "Checking dataset..." : "Start Training"}
         </Button>
         {startError && (
           <p className="text-xs text-red-500 leading-relaxed">{startError}</p>
diff --git a/studio/frontend/src/features/training/stores/training-config-store.ts b/studio/frontend/src/features/training/stores/training-config-store.ts
index 212dc78e6c..e1b8d4b1a2 100644
--- a/studio/frontend/src/features/training/stores/training-config-store.ts
+++ b/studio/frontend/src/features/training/stores/training-config-store.ts
@@ -210,6 +210,7 @@ export const useTrainingConfigStore = create<TrainingConfigStore>()(
           hfToken: state.hfToken.trim() || null,
           subset: state.datasetSubset,
           split,
+          isVlm: state.isVisionModel,
         })
           .then((res) => {
             if (controller.signal.aborted) return;