diff --git a/src/fabricator/prompts/base.py b/src/fabricator/prompts/base.py
index 1f218e0..9179fc0 100644
--- a/src/fabricator/prompts/base.py
+++ b/src/fabricator/prompts/base.py
@@ -192,9 +192,9 @@ def get_prompt_text(self, labels: Union[str, List[str]] = None, examples: Option
         if examples:
             # due to small_model training fewshot_examples appear after some iterations
             if self.relevant_columns_for_fewshot_examples is None:
-                self.relevant_columns_for_fewshot_examples = examples.column_names
+                self.relevant_columns_for_fewshot_examples = ['text']
                 self.fewshot_prompt = self.inner_fewshot_example_separator.join(
-                    [f"{var}: {{{var}}}" for var in self.relevant_columns_for_fewshot_examples]
+                    [f"{{{var}}}" for var in self.relevant_columns_for_fewshot_examples]
                 )
             examples = self.filter_examples_by_columns(examples, self.relevant_columns_for_fewshot_examples)
             formatted_examples = [self.fewshot_prompt.format(**example) for example in examples]
diff --git a/src/small_model_training/iterative_dataset_synthesis_movies.py b/src/small_model_training/iterative_dataset_synthesis_movies.py
index c97a130..8563c29 100644
--- a/src/small_model_training/iterative_dataset_synthesis_movies.py
+++ b/src/small_model_training/iterative_dataset_synthesis_movies.py
@@ -5,13 +5,16 @@
 label_options = ["positive", "negative"]
 
 prompt = BasePrompt(
-    task_description="Generate a {} movie review.",
+    task_description="You are writing a movie review. Write only one {} movie review similar to the following examples.",
     label_options=label_options,
+    target_formatting_template="",
 )
 
 prompt_node = PromptNode(
     model_name_or_path="mistralai/Mistral-7B-Instruct-v0.1",
-    max_length=100,
+    max_length=500,
+    model_kwargs={"temperature": 0.9},
+
 )
 
 generator = DatasetGenerator(prompt_node)