diff --git a/assets/training/finetune_acft_hf_nlp/components/finetune/chat_completion/spec.yaml b/assets/training/finetune_acft_hf_nlp/components/finetune/chat_completion/spec.yaml
index 003380c4f0..83c9f28f15 100644
--- a/assets/training/finetune_acft_hf_nlp/components/finetune/chat_completion/spec.yaml
+++ b/assets/training/finetune_acft_hf_nlp/components/finetune/chat_completion/spec.yaml
@@ -213,7 +213,7 @@ inputs:
     enum:
     - epoch
     - steps
-    - "no"
+    - disable
     description: The evaluation strategy to adopt during training. If set to "steps", either the `evaluation_steps_interval` or `eval_steps` needs to be specified, which helps to determine the step at which the model evaluation needs to be computed else evaluation happens at end of each epoch.
 
   evaluation_steps_interval:
diff --git a/assets/training/finetune_acft_hf_nlp/components/pipeline_components/chat_completion/spec.yaml b/assets/training/finetune_acft_hf_nlp/components/pipeline_components/chat_completion/spec.yaml
index 91017e77fb..104485780c 100644
--- a/assets/training/finetune_acft_hf_nlp/components/pipeline_components/chat_completion/spec.yaml
+++ b/assets/training/finetune_acft_hf_nlp/components/pipeline_components/chat_completion/spec.yaml
@@ -321,7 +321,7 @@ inputs:
     enum:
     - epoch
     - steps
-    - "no"
+    - disable
     description: The evaluation strategy to adopt during training. If set to "steps", either the `evaluation_steps_interval` or `eval_steps` needs to be specified, which helps to determine the step at which the model evaluation needs to be computed else evaluation happens at end of each epoch.
 
   evaluation_steps_interval:
diff --git a/assets/training/finetune_acft_hf_nlp/src/finetune/finetune.py b/assets/training/finetune_acft_hf_nlp/src/finetune/finetune.py
index 35bca4dfb4..619a65256f 100644
--- a/assets/training/finetune_acft_hf_nlp/src/finetune/finetune.py
+++ b/assets/training/finetune_acft_hf_nlp/src/finetune/finetune.py
@@ -442,7 +442,7 @@ def get_parser():
         type=str,
         default="epoch",
         choices=(
-                    "no",
+                    "disable",
                     "steps",
                     "epoch",
                 ),
@@ -1275,6 +1275,10 @@ def finetune(args: Namespace):
 
     validate_learning_rate(args)
 
+    # Fix: Ev2 rollout fails when using no as string in the spec.
+    if args.evaluation_strategy == 'disable':
+        args.evaluation_strategy = 'no'
+
     if not hasattr(args, "eval_strategy"):
         args.eval_strategy = args.evaluation_strategy
     # validate early stop settings