diff --git a/arc_finetuning_st/finetuning/finetuning_example.py b/arc_finetuning_st/finetuning/finetuning_example.py
index 72f5102..aba77c0 100644
--- a/arc_finetuning_st/finetuning/finetuning_example.py
+++ b/arc_finetuning_st/finetuning/finetuning_example.py
@@ -3,7 +3,7 @@
 from typing import Annotated, Any, Callable, List, Optional
 
 from llama_index.core.base.llms.types import ChatMessage, MessageRole
-from llama_index.core.bridge.pydantic import BaseModel, WrapSerializer
+from llama_index.core.bridge.pydantic import BaseModel, Field, WrapSerializer
 
 from arc_finetuning_st.finetuning.templates import (
     ASSISTANT_TEMPLATE,
@@ -26,10 +26,12 @@ class FineTuningExample(BaseModel):
     messages: List[
         Annotated[ChatMessage, WrapSerializer(remove_additional_kwargs)]
     ]
+    task_name: str = Field(exclude=True)
 
     @classmethod
     def from_attempts(
         cls,
+        task_name: str,
         examples: str,
         test_input: str,
         attempts: List[Attempt],
@@ -65,7 +67,7 @@ def from_attempts(
                     ),
                 ]
             )
-        return cls(messages=messages)
+        return cls(messages=messages, task_name=task_name)
 
     def to_json(self) -> str:
         data = self.model_dump()
@@ -79,5 +81,5 @@ def write_json(
         data = self.model_dump()
         dir = Path(dirpath or Path(__file__).parents[2].absolute(), dirname)
         dir.mkdir(exist_ok=True, parents=True)
-        with open(Path(dir, "test.json"), "w") as f:
+        with open(Path(dir, self.task_name), "w") as f:
             json.dump(data, f)
diff --git a/arc_finetuning_st/streamlit/controller.py b/arc_finetuning_st/streamlit/controller.py
index 76b579a..87a08ac 100644
--- a/arc_finetuning_st/streamlit/controller.py
+++ b/arc_finetuning_st/streamlit/controller.py
@@ -1,7 +1,6 @@
 import asyncio
 import json
 import logging
-import uuid
 from os import listdir
 from pathlib import Path
 from typing import Any, List, Literal, Optional, cast
@@ -27,9 +26,9 @@ def __init__(self) -> None:
         self._handler: Optional[WorkflowHandler] = None
         self._attempts: List[Attempt] = []
         self._passing_results: List[bool] = []
-        parent_path = Path(__file__).parents[2].absolute()
-        self._data_path = Path(parent_path, "data", "training")
-        self._attempts_history_df_key = str(uuid.uuid4())
+        self._data_path = Path(
+            Path(__file__).parents[2].absolute(), "data", "training"
+        )
 
     def reset(self) -> None:
         # clear prediction
@@ -159,10 +158,6 @@ def passing(self) -> Optional[bool]:
             return self._passing_results[-1]
         return None
 
-    @property
-    def attempts_history_df_key(self) -> str:
-        return self._attempts_history_df_key
-
     @property
     def attempts_history_df(
         self,
@@ -246,6 +241,7 @@ def _display_finetuning_example() -> None:
                 nonlocal prompt_vars
 
                 finetuning_example = FineTuningExample.from_attempts(
+                    task_name=st.session_state.selected_task,
                     attempts=self._attempts,
                     examples=prompt_vars["examples"],
                     test_input=prompt_vars["test_input"],
@@ -256,9 +252,6 @@ def _display_finetuning_example() -> None:
                     with save_col:
                         if st.button("Save", use_container_width=True):
                             finetuning_example.write_json()
-                            st.success(
-                                "Successfully saved finetuning example."
-                            )
                             st.session_state.show_finetuning_preview_dialog = (
                                 False
                             )