From 0adef07413bbc7c1af9c51fdacd416e38699df8c Mon Sep 17 00:00:00 2001 From: Molly He Date: Fri, 6 Mar 2026 14:35:14 -0800 Subject: [PATCH 01/11] Intermediary checkpoint --- .../src/sagemaker/core/resources.py | 22 +- sagemaker-train/pyproject.toml | 3 + .../src/sagemaker/train/__init__.py | 12 + .../sagemaker/train/common_utils/constants.py | 1 + .../train/common_utils/finetune_utils.py | 1 + .../train/common_utils/metrics_visualizer.py | 142 ++++ .../train/common_utils/mlflow_metrics_util.py | 4 +- .../train/common_utils/trainer_wait.py | 139 +++- ...dpo_trainer_example_notebook_v3_prod.ipynb | 6 +- ...uning_example_notebook_pysdk_prod_v3.ipynb | 509 ++++++++++++-- ...io-nova-training-job-sample-notebook.ipynb | 637 +++++++++++++++++- 11 files changed, 1379 insertions(+), 97 deletions(-) create mode 100644 sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py diff --git a/sagemaker-core/src/sagemaker/core/resources.py b/sagemaker-core/src/sagemaker/core/resources.py index 66b13e112a..61e0f9c677 100644 --- a/sagemaker-core/src/sagemaker/core/resources.py +++ b/sagemaker-core/src/sagemaker/core/resources.py @@ -35788,7 +35788,7 @@ def stop(self) -> None: ResourceNotFound: Resource being access is not found. """ - client = SageMakerClient().client + client = SageMakerClient().sagemaker_client operation_input_args = { "TrainingJobName": self.training_job_name, @@ -35833,15 +35833,17 @@ def wait( progress.add_task("Waiting for TrainingJob...") status = Status("Current status:") - instance_count = ( - sum( - instance_group.instance_count - for instance_group in self.resource_config.instance_groups - ) - if self.resource_config.instance_groups - and not isinstance(self.resource_config.instance_groups, Unassigned) - else self.resource_config.instance_count - ) + instance_count = 1 # Default + if not isinstance(self.resource_config, Unassigned): + if (hasattr(self.resource_config, 'instance_groups') and + self.resource_config.instance_groups and + not isinstance(self.resource_config.instance_groups, Unassigned)): + instance_count = sum( + instance_group.instance_count + for instance_group in self.resource_config.instance_groups + ) + elif hasattr(self.resource_config, 'instance_count'): + instance_count = self.resource_config.instance_count if logs: multi_stream_logger = MultiLogStreamHandler( diff --git a/sagemaker-train/pyproject.toml b/sagemaker-train/pyproject.toml index 9a51ef9aa2..64eace3585 100644 --- a/sagemaker-train/pyproject.toml +++ b/sagemaker-train/pyproject.toml @@ -43,6 +43,9 @@ dependencies = [ "sagemaker-mlflow>=0.0.1,<1.0.0", "mlflow>=3.0.0,<4.0.0", "nest_asyncio>=1.5.0", + "ipywidgets>=8.0.0", + "rich>=13.0.0", + "matplotlib>=3.5.0", ] [project.urls] diff --git a/sagemaker-train/src/sagemaker/train/__init__.py b/sagemaker-train/src/sagemaker/train/__init__.py index 74518dc65a..38a6fda76d 100644 --- a/sagemaker-train/src/sagemaker/train/__init__.py +++ b/sagemaker-train/src/sagemaker/train/__init__.py @@ -56,4 +56,16 @@ def __getattr__(name): elif name == "get_builtin_metrics": from sagemaker.train.evaluate import get_builtin_metrics return get_builtin_metrics + elif name == "plot_training_metrics": + from sagemaker.train.common_utils.metrics_visualizer import plot_training_metrics + return plot_training_metrics + elif name == "get_available_metrics": + from sagemaker.train.common_utils.metrics_visualizer import get_available_metrics + return get_available_metrics + elif name == "get_studio_url": + from sagemaker.train.common_utils.metrics_visualizer import get_studio_url + return get_studio_url + elif name == "get_mlflow_url": + from sagemaker.train.common_utils.trainer_wait import get_mlflow_url + return get_mlflow_url raise AttributeError(f"module '{__name__}' has no attribute '{name}'") diff --git a/sagemaker-train/src/sagemaker/train/common_utils/constants.py b/sagemaker-train/src/sagemaker/train/common_utils/constants.py index 8de3ab4638..b96c58134c 100644 --- a/sagemaker-train/src/sagemaker/train/common_utils/constants.py +++ b/sagemaker-train/src/sagemaker/train/common_utils/constants.py @@ -20,6 +20,7 @@ class _MLflowConstants: # Metric names TOTAL_LOSS_METRIC = 'total_loss' + LOSS_METRIC_KEYWORDS = ('loss',) EPOCH_KEYWORD = 'epoch' # MLflow run tags diff --git a/sagemaker-train/src/sagemaker/train/common_utils/finetune_utils.py b/sagemaker-train/src/sagemaker/train/common_utils/finetune_utils.py index 3fd17c3ac0..c6e89e19c8 100644 --- a/sagemaker-train/src/sagemaker/train/common_utils/finetune_utils.py +++ b/sagemaker-train/src/sagemaker/train/common_utils/finetune_utils.py @@ -376,6 +376,7 @@ def _get_fine_tuning_options_and_model_arn(model_name: str, customization_techni except Exception as e: logger.error("Exception getting fine-tuning options: %s", e) + raise def _create_input_channels(dataset: str, content_type: Optional[str] = None, diff --git a/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py b/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py new file mode 100644 index 0000000000..0b617601e2 --- /dev/null +++ b/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py @@ -0,0 +1,142 @@ +"""MLflow metrics visualization utilities for SageMaker training jobs.""" + +import logging +from typing import Optional, List, Dict, Any +import boto3 +from sagemaker.core.resources import TrainingJob + +logger = logging.getLogger(__name__) + + +def get_studio_url(training_job: TrainingJob, domain_id: str = None) -> str: + """Get SageMaker Studio URL for training job logs. + + Args: + training_job: SageMaker TrainingJob object or job name string + domain_id: Studio domain ID (e.g., 'd-xxxxxxxxxxxx'). If not provided, attempts to auto-detect + + Returns: + Studio URL pointing to the training job details + + Example: + >>> from sagemaker.train import get_studio_url + >>> url = get_studio_url('my-training-job') + """ + if isinstance(training_job, str): + training_job = TrainingJob.get(training_job_name=training_job) + + region = training_job.region if hasattr(training_job, 'region') and training_job.region else 'us-east-1' + job_name = training_job.training_job_name + + sm_client = boto3.client('sagemaker', region_name=region) + + # Auto-detect domain if not provided + if not domain_id: + try: + domains = sm_client.list_domains()['Domains'] + if domains: + domain_id = domains[0]['DomainId'] + except Exception: + pass + + if not domain_id: + # Fallback to console URL + return f"https://{region}.console.aws.amazon.com/sagemaker/home?region={region}#/jobs/{job_name}" + + # Studio URL format: https://studio-{domain_id}.studio.{region}.sagemaker.aws/jobs/train/{job_name} + return f"https://studio-{domain_id}.studio.{region}.sagemaker.aws/jobs/train/{job_name}" + + +def plot_training_metrics( + training_job: TrainingJob, + metrics: Optional[List[str]] = None, + figsize: tuple = (12, 6) +) -> None: + """Plot training metrics from MLflow for a completed training job. + + Args: + training_job: SageMaker TrainingJob object or job name string + metrics: List of metric names to plot. If None, plots all available metrics. + figsize: Figure size as (width, height) + """ + import matplotlib.pyplot as plt + import mlflow + from mlflow.tracking import MlflowClient + from IPython.display import display + import logging + + logging.getLogger('botocore.credentials').setLevel(logging.WARNING) + + if isinstance(training_job, str): + training_job = TrainingJob.get(training_job_name=training_job) + + run_id = training_job.mlflow_details.mlflow_run_id + + mlflow.set_tracking_uri(training_job.mlflow_config.mlflow_resource_arn) + client = MlflowClient() + + run = mlflow.get_run(run_id) + available_metrics = list(run.data.metrics.keys()) + metrics_to_plot = metrics if metrics else available_metrics + + # Fetch metric histories + metric_data = {} + for metric_name in metrics_to_plot: + history = client.get_metric_history(run_id, metric_name) + if history: + metric_data[metric_name] = history + + # Plot + num_metrics = len(metric_data) + rows = (num_metrics + 1) // 2 + fig, axes = plt.subplots(rows, 2, figsize=(figsize[0], figsize[1] * rows)) + axes = axes.flatten() if num_metrics > 1 else [axes] + + for idx, (metric_name, history) in enumerate(metric_data.items()): + steps = [h.step for h in history] + values = [h.value for h in history] + axes[idx].plot(steps, values, linewidth=2, marker='o', markersize=4) + axes[idx].set_xlabel('Step') + axes[idx].set_ylabel('Value') + axes[idx].set_title(metric_name, fontweight='bold') + axes[idx].grid(True, alpha=0.3) + + for idx in range(len(metric_data), len(axes)): + axes[idx].set_visible(False) + + plt.suptitle(f'Training Metrics: {training_job.training_job_name}', fontweight='bold', fontsize=14) + plt.tight_layout(rect=[0, 0, 1, 0.98]) # Leave small space for suptitle + display(fig) + plt.close() + + +def get_available_metrics(training_job: TrainingJob) -> List[str]: + """Get list of available metrics for a training job. + + Args: + training_job: SageMaker TrainingJob object or job name string + + Returns: + List of metric names + """ + try: + import mlflow + except ImportError: + logger.error("mlflow package not installed") + return [] + + # Handle string input + if isinstance(training_job, str): + training_job = TrainingJob.get(training_job_name=training_job) + + if not hasattr(training_job, 'mlflow_config') or not training_job.mlflow_config: + return [] + + mlflow_details = training_job.mlflow_details + if not mlflow_details or not mlflow_details.mlflow_run_id: + return [] + + mlflow.set_tracking_uri(training_job.mlflow_config.mlflow_resource_arn) + run = mlflow.get_run(mlflow_details.mlflow_run_id) + + return list(run.data.metrics.keys()) diff --git a/sagemaker-train/src/sagemaker/train/common_utils/mlflow_metrics_util.py b/sagemaker-train/src/sagemaker/train/common_utils/mlflow_metrics_util.py index 43cc5e3847..8d15731977 100644 --- a/sagemaker-train/src/sagemaker/train/common_utils/mlflow_metrics_util.py +++ b/sagemaker-train/src/sagemaker/train/common_utils/mlflow_metrics_util.py @@ -154,7 +154,7 @@ def _get_loss_metrics( loss_data = [] for metric_key in run.data.metrics: - if _MLflowConstants.TOTAL_LOSS_METRIC == metric_key.lower(): + if any(kw in metric_key.lower() for kw in _MLflowConstants.LOSS_METRIC_KEYWORDS): metric_history = client.get_metric_history(rid, metric_key) loss_data.append({ 'metric_name': metric_key, @@ -335,7 +335,7 @@ def _get_most_recent_total_loss( for rid, metrics in loss_metrics.items(): for metric in metrics: - if metric['metric_name'].lower() == _MLflowConstants.TOTAL_LOSS_METRIC: + if any(kw in metric['metric_name'].lower() for kw in _MLflowConstants.LOSS_METRIC_KEYWORDS): if metric['history']: # Get the most recent entry (last in history) return metric['history'][-1]['value'] diff --git a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py index 900f13d4c6..002793fab1 100644 --- a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py +++ b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py @@ -40,6 +40,10 @@ def _setup_mlflow_integration(training_job: TrainingJob) -> Tuple[ try: import boto3 + # Check if mlflow_config exists and is assigned + if not hasattr(training_job, 'mlflow_config') or _is_unassigned_attribute(training_job.mlflow_config): + return None, None, None + sm_client = boto3.client('sagemaker') mlflow_arn = training_job.mlflow_config.mlflow_resource_arn @@ -56,7 +60,11 @@ def _setup_mlflow_integration(training_job: TrainingJob) -> Tuple[ return mlflow_url, metrics_util, mlflow_run_name - except Exception: + except Exception as e: + # Log the exception for debugging + import logging + logger = logging.getLogger(__name__) + logger.debug(f"MLflow integration setup failed: {e}") return None, None, None @@ -154,6 +162,59 @@ def _calculate_transition_duration(trans) -> Tuple[str, str]: return duration, check +def get_mlflow_url(training_job) -> str: + """Get presigned MLflow URL for training job experiment. + + Args: + training_job: SageMaker TrainingJob object or job name string + + Returns: + Presigned MLflow URL to experiment (valid for 5 minutes) + + Example: + >>> from sagemaker.train import get_mlflow_url + >>> url = get_mlflow_url('my-training-job') + >>> print(url) + """ + if isinstance(training_job, str): + training_job = TrainingJob.get(training_job_name=training_job) + + if not hasattr(training_job, 'mlflow_config') or _is_unassigned_attribute(training_job.mlflow_config): + raise ValueError("Training job does not have MLflow configured") + + import boto3 + import os + from mlflow.tracking import MlflowClient + import mlflow + + mlflow_arn = training_job.mlflow_config.mlflow_resource_arn + exp_name = training_job.mlflow_config.mlflow_experiment_name + + # Get presigned base URL + sm_client = boto3.client('sagemaker') + response = sm_client.create_presigned_mlflow_app_url(Arn=mlflow_arn) + base_url = response.get('AuthorizedUrl') + + # Try to get experiment ID and append to URL + try: + os.environ['MLFLOW_TRACKING_URI'] = mlflow_arn + mlflow.set_tracking_uri(mlflow_arn) + + mlflow_client = MlflowClient(tracking_uri=mlflow_arn) + experiment = mlflow_client.get_experiment_by_name(exp_name) + + if experiment: + # Format: base_url#/experiments/{id} + # The base_url already has /auth?authToken=... + return f"{base_url}#/experiments/{experiment.experiment_id}" + except Exception: + pass + + return base_url + + + + def wait( training_job: TrainingJob, poll: int = 5, @@ -188,28 +249,84 @@ def wait( from rich.console import Group with _suppress_info_logging(): console = Console(force_jupyter=True) + + # MLflow link caching + mlflow_link_cache = {'url': None, 'timestamp': 0, 'error': None} + has_mlflow_config = (hasattr(training_job, 'mlflow_config') and + not _is_unassigned_attribute(training_job.mlflow_config)) + + def get_cached_mlflow_url(): + """Get cached MLflow URL or generate new one if expired.""" + current_time = time.time() + # Regenerate every 4 minutes (before 5-minute expiration) + if mlflow_link_cache['url'] is None or (current_time - mlflow_link_cache['timestamp']) > 240: + try: + mlflow_link_cache['url'] = get_mlflow_url(training_job) + mlflow_link_cache['error'] = None + except Exception as e: + mlflow_link_cache['error'] = str(e) + mlflow_link_cache['timestamp'] = current_time + return mlflow_link_cache['url'] + + # Track last rendered state to avoid unnecessary refreshes + last_status = None + last_secondary_status = None iteration = 0 while True: iteration += 1 - time.sleep(1) - if iteration == poll: + time.sleep(0.5) + if iteration >= poll * 2: training_job.refresh() iteration = 0 - clear_output(wait=True) - + status = training_job.training_job_status secondary_status = training_job.secondary_status elapsed = time.time() - start_time + + # Only re-render if status changed or every 2 seconds (for elapsed time) + should_render = ( + status != last_status or + secondary_status != last_secondary_status or + iteration % 4 == 0 # Every 2 seconds (4 * 0.5s) + ) + + if not should_render: + continue + + last_status = status + last_secondary_status = secondary_status + + clear_output(wait=True) - # Header section with training job name and MLFlow URL + # Header section with training job name header_table = Table(show_header=False, box=None, padding=(0, 1)) header_table.add_column("Property", style="cyan bold", width=20) - header_table.add_column("Value", style="white") - header_table.add_row("TrainingJob Name", f"[bold green]{training_job.training_job_name}[/bold green]") - if mlflow_url: - header_table.add_row("MLFlow URL", - f"[link={mlflow_url}][bold bright_blue underline]{mlflow_run_name}(link valid for 5 mins)[/bright_blue bold underline][/link]") + header_table.add_column("Value", style="white", overflow="fold") + + # Add Studio job link + try: + from sagemaker.train.common_utils.metrics_visualizer import get_studio_url + studio_url = get_studio_url(training_job) + header_table.add_row("TrainingJob Name", f"[link={studio_url}]🔗 {training_job.training_job_name}[/link]") + except Exception: + header_table.add_row("TrainingJob Name", f"[bold green]{training_job.training_job_name}[/bold green]") + + header_table.add_row("TrainingJob ARN", f"[dim]{training_job.training_job_arn}[/dim]") + + # Add MLflow link to header if available + if has_mlflow_config: + cached_url = get_cached_mlflow_url() + if cached_url: + exp_name = training_job.mlflow_config.mlflow_experiment_name if hasattr(training_job, 'mlflow_config') else None + if exp_name and not _is_unassigned_attribute(exp_name): + link_text = exp_name + else: + link_text = "MLflow Experiment" + + header_table.add_row("MLflow Experiment", f"[link={cached_url}]🔗 {link_text}[/link]") + elif mlflow_link_cache['error']: + header_table.add_row("MLflow Experiment", f"[red]{mlflow_link_cache['error']}[/red]") status_table = Table(show_header=False, box=None, padding=(0, 1)) status_table.add_column("Property", style="cyan bold", width=20) diff --git a/v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod.ipynb b/v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod.ipynb index e5fbe4cd99..130991834a 100644 --- a/v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod.ipynb +++ b/v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod.ipynb @@ -58,8 +58,8 @@ "# This creates a versioned dataset that can be referenced by ARN\n", "# Provide a source (it can be local file path or S3 URL)\n", "dataset = DataSet.create(\n", - " name=\"demo-6\",\n", - " source=\"s3://nova-mlflow-us-west-2/dataset/preference_dataset_train_256.jsonl\"\n", + " name=\"demo-2\",\n", + " source=\"s3://sagemaker-us-west-2-529088288990/dataset/preference_dataset_train_256.jsonl\"\n", ")\n", "\n", "print(f\"Dataset ARN: {dataset.arn}\")" @@ -292,7 +292,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.10" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb b/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb index 946debc7d7..887f60a3d9 100644 --- a/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb +++ b/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb @@ -35,10 +35,30 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "a51be0b5-fd33-4fa0-af2b-d08ce0dc7a8e", + "execution_count": 1, + "id": "989646bf", "metadata": {}, "outputs": [], + "source": [ + "import logging\n", + "logging.basicConfig(level=logging.WARNING)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a51be0b5-fd33-4fa0-af2b-d08ce0dc7a8e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sagemaker.config INFO - Not applying SDK defaults from location: /Library/Application Support/sagemaker/config.yaml\n", + "sagemaker.config INFO - Not applying SDK defaults from location: /Users/mollyhe/Library/Application Support/sagemaker/config.yaml\n" + ] + } + ], "source": [ "from sagemaker.train.sft_trainer import SFTTrainer\n", "from sagemaker.train.common import TrainingType\n", @@ -53,7 +73,7 @@ "\n", "\n", "# For MLFlow native metrics in Trainer wait, run below line with approriate region\n", - "os.environ[\"SAGEMAKER_MLFLOW_CUSTOM_ENDPOINT\"] = \"https://mlflow.sagemaker.us-west-2.app.aws\"\n", + "os.environ[\"SAGEMAKER_MLFLOW_CUSTOM_ENDPOINT\"] = \"https://mlflow.sagemaker.us-east-1.app.aws\"\n", "\n" ] }, @@ -76,10 +96,55 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "ef4f0e61-de4d-4228-b7a1-ea7497dad547", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b7310bb3f485478f905417b421e7ae11", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
Final Resource Status: Available\n",
+       "
\n" + ], + "text/plain": [ + "Final Resource Status: Available\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dataset ARN: arn:aws:sagemaker:us-east-1:529088288990:hub-content/G82247CBEQ6TN0FI3J1SAJU59UURMT3H3EKG48C6VQGDINNRNGU0/DataSet/demo-1/28.0.0\n"
+     ]
+    }
+   ],
    "source": [
     "from sagemaker.ai_registry.dataset import DataSet\n",
     "from sagemaker.ai_registry.dataset_utils import CustomizationTechnique\n",
@@ -91,7 +156,7 @@
     "# Provide a source (it can be local file path or S3 URL)\n",
     "dataset = DataSet.create(\n",
     "    name=\"demo-1\",\n",
-    "    source=\"s3://mc-flows-sdk-testing/input_data/sft/sample_data_256_final.jsonl\"\n",
+    "    source=\"s3://sagemaker-us-east-1-529088288990/nova1_SFT.jsonl\"\n",
     ")\n",
     "\n",
     "print(f\"Dataset ARN: {dataset.arn}\")"
@@ -107,14 +172,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "d6937550-f721-43ff-82dd-c513c328dd17",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING:sagemaker.core.utils.utils:No region provided. Using default region.\n"
+     ]
+    }
+   ],
    "source": [
     "from sagemaker.core.resources import ModelPackage, ModelPackageGroup\n",
     "\n",
-    "model_package_group=ModelPackageGroup.create(model_package_group_name=\"test-model-package-group\")"
+    "# model_package_group=ModelPackageGroup.create(model_package_group_name=\"model-package-group-nova13\")\n",
+    "model_package_group=ModelPackageGroup.get(model_package_group_name=\"model-package-group-nova13\")"
    ]
   },
   {
@@ -150,20 +224,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "88fe8360-de50-481d-932f-564a32be66a0",
    "metadata": {},
    "outputs": [],
    "source": [
     "# For fine-tuning \n",
     "sft_trainer = SFTTrainer(\n",
-    "    model=\"meta-textgeneration-llama-3-2-1b-instruct\", \n",
-    "    training_type=TrainingType.LORA, \n",
+    "    model=\"nova-textgeneration-lite\", \n",
+    "    training_type=TrainingType.FULL, \n",
     "    model_package_group=model_package_group, # or use an existing model package group arn\n",
     "    mlflow_experiment_name=\"test-finetuned-models-exp\", \n",
     "    mlflow_run_name=\"test-finetuned-models-run\", \n",
     "    training_dataset=dataset.arn, \n",
-    "    s3_output_path=\"s3://mc-flows-sdk-testing/output/\",\n",
+    "    s3_output_path=\"s3://sagemaker-us-east-1-529088288990/output/\",\n",
     "    accept_eula=True\n",
     ")\n"
    ]
@@ -201,7 +275,7 @@
    "outputs": [],
    "source": [
     "# To update any hyperparameter, simply assign the value, example:\n",
-    "sft_trainer.hyperparameters.global_batch_size=16"
+    "sft_trainer.hyperparameters.global_batch_size=32"
    ]
   },
   {
@@ -214,7 +288,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "4d3b6441-9abb-447b-9307-9606a8c0fabd",
    "metadata": {
     "jupyter": {
@@ -222,28 +296,327 @@
     },
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
╭────────────────────────────────── Training Job Status ───────────────────────────────────╮\n",
+       "│  TrainingJob Name      🔗 nova-textgeneration-lite-sft-20260305152839                    │\n",
+       "│  TrainingJob ARN       arn:aws:sagemaker:us-east-1:529088288990:training-job/nova-textg  │\n",
+       "│                        eneration-lite-sft-20260305152839                                 │\n",
+       "│  MLflow Experiment     🔗 test-finetuned-models-exp                                      │\n",
+       "│                                                                                          │\n",
+       "│  Job Status            InProgress                                                        │\n",
+       "│  Secondary Status      Pending                                                           │\n",
+       "│  Elapsed Time          10.3s                                                             │\n",
+       "│                                                                                          │\n",
+       "│ Status Transitions                                                                       │\n",
+       "│                                                                                          │\n",
+       "│        Step              Details                               Duration                  │\n",
+       "│  ───────────────────────────────────────────────────────────────────────────             │\n",
+       "│   ✓    Starting          Starting the training job             1.8s                      │\n",
+       "│   ⋯    Pending           Training job waiting for capacity     Running...                │\n",
+       "│                                                                                          │\n",
+       "╰──────────────────────────────────────────────────────────────────────────────────────────╯\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;172m╭─\u001b[0m\u001b[38;5;172m─────────────────────────────────\u001b[0m\u001b[38;5;172m \u001b[0m\u001b[1;94mTraining Job Status\u001b[0m\u001b[38;5;172m \u001b[0m\u001b[38;5;172m──────────────────────────────────\u001b[0m\u001b[38;5;172m─╮\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mTrainingJob Name    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b]8;id=315550;https://studio-d-ingyyaeglvki.studio.us-east-1.sagemaker.aws/jobs/train/nova-textgeneration-lite-sft-20260305152839\u001b\\\u001b[37m🔗 nova-textgeneration-lite-sft-20260305152839\u001b[0m\u001b]8;;\u001b\\\u001b[37m                  \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mTrainingJob ARN     \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[2;37marn:aws:sagemaker:us-east-1:529088288990:training-job/nova-textg\u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m                      \u001b[0m\u001b[37m \u001b[0m\u001b[2;37meneration-lite-sft-20260305152839\u001b[0m\u001b[37m                               \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mMLflow Experiment   \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b]8;id=794600;https://app-2SV6Q35HTCBO.mlflow.sagemaker.us-east-1.app.aws/auth?authToken=eyJhbGciOiJIUzI1NiJ9.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.X2ERSgvF5-bTlp7a-wWjG7vQiNNi9RJ-dreP8RUI4n8#/experiments/2\u001b\\\u001b[37m🔗 test-finetuned-models-exp\u001b[0m\u001b]8;;\u001b\\\u001b[37m                                    \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mJob Status          \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;38;5;172mInProgress\u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mSecondary Status    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;33mPending\u001b[0m\u001b[37m   \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mElapsed Time        \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;91m10.3s\u001b[0m\u001b[37m     \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;35mStatus Transitions\u001b[0m                                                                       \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[1;35m \u001b[0m\u001b[1;35m  \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mStep           \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mDetails                            \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mDuration    \u001b[0m\u001b[1;35m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  ───────────────────────────────────────────────────────────────────────────             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m✓ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mStarting       \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mStarting the training job          \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m1.8s        \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m⋯ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mPending        \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mTraining job waiting for capacity  \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32mRunning...  \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m╰──────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮\n",
+       "│ in <module>:1                                                                                    │\n",
+       "│                                                                                                  │\n",
+       "│ ❱ 1 training_job = sft_trainer.train(                                                            │\n",
+       "│   2 │   wait=True                                                                                │\n",
+       "│   3 )                                                                                            │\n",
+       "│   4                                                                                              │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/ │\n",
+       "│ telemetry/telemetry_logging.py:180 in wrapper                                                    │\n",
+       "│                                                                                                  │\n",
+       "│   177 │   │   │   │   │   \"sagemaker_session is not provided or not valid.\",                     │\n",
+       "│   178 │   │   │   │   │   func_name,                                                             │\n",
+       "│   179 │   │   │   │   )                                                                          │\n",
+       "│ ❱ 180 │   │   │   │   return func(*args, **kwargs)                                               │\n",
+       "│   181 │   │                                                                                      │\n",
+       "│   182 │   │   return wrapper                                                                     │\n",
+       "│   183                                                                                            │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai │\n",
+       "│ n/sft_trainer.py:280 in train                                                                    │\n",
+       "│                                                                                                  │\n",
+       "│   277 │   │   │   from sagemaker.train.common_utils.trainer_wait import wait as _wait            │\n",
+       "│   278 │   │   │   from sagemaker.core.utils.exceptions import TimeoutExceededError               │\n",
+       "│   279 │   │   │   try :                                                                          │\n",
+       "│ ❱ 280 │   │   │   │   _wait(training_job)                                                        │\n",
+       "│   281 │   │   │   except TimeoutExceededError as e:                                              │\n",
+       "│   282 │   │   │   │   logger.error(\"Error: %s\", e)                                               │\n",
+       "│   283                                                                                            │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai │\n",
+       "│ n/common_utils/trainer_wait.py:272 in wait                                                       │\n",
+       "│                                                                                                  │\n",
+       "│   269 │   │   │   │   iteration = 0                                                              │\n",
+       "│   270 │   │   │   │   while True:                                                                │\n",
+       "│   271 │   │   │   │   │   iteration += 1                                                         │\n",
+       "│ ❱ 272 │   │   │   │   │   time.sleep(0.5)                                                        │\n",
+       "│   273 │   │   │   │   │   if iteration >= poll * 2:                                              │\n",
+       "│   274 │   │   │   │   │   │   training_job.refresh()                                             │\n",
+       "│   275 │   │   │   │   │   │   iteration = 0                                                      │\n",
+       "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
+       "KeyboardInterrupt\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[38;2;255;0;0m╭─\u001b[0m\u001b[38;2;255;0;0m──────────────────────────────\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[1;38;2;255;0;0mTraceback \u001b[0m\u001b[1;2;38;2;255;0;0m(most recent call last)\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[38;2;255;0;0m───────────────────────────────\u001b[0m\u001b[38;2;255;0;0m─╮\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m in \u001b[92m\u001b[0m:\u001b[94m1\u001b[0m                                                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m1 training_job = sft_trainer.train(                                                            \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m2 \u001b[0m\u001b[2m│   \u001b[0mwait=\u001b[94mTrue\u001b[0m                                                                                \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m3 \u001b[0m)                                                                                            \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m4 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mtelemetry/\u001b[0m\u001b[1;33mtelemetry_logging.py\u001b[0m:\u001b[94m180\u001b[0m in \u001b[92mwrapper\u001b[0m                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m177 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[33m\"\u001b[0m\u001b[33msagemaker_session is not provided or not valid.\u001b[0m\u001b[33m\"\u001b[0m,                     \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m178 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mfunc_name,                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m179 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m)                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m180 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m func(*args, **kwargs)                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m181 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m182 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m wrapper                                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m183 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mn/\u001b[0m\u001b[1;33msft_trainer.py\u001b[0m:\u001b[94m280\u001b[0m in \u001b[92mtrain\u001b[0m                                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m277 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mfrom\u001b[0m\u001b[90m \u001b[0m\u001b[4;96msagemaker\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mtrain\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mcommon_utils\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mtrainer_wait\u001b[0m\u001b[90m \u001b[0m\u001b[94mimport\u001b[0m wait \u001b[94mas\u001b[0m _wait            \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m278 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mfrom\u001b[0m\u001b[90m \u001b[0m\u001b[4;96msagemaker\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mcore\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mutils\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mexceptions\u001b[0m\u001b[90m \u001b[0m\u001b[94mimport\u001b[0m TimeoutExceededError               \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m279 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mtry\u001b[0m :                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m280 \u001b[2m│   │   │   │   \u001b[0m_wait(training_job)                                                        \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m281 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mexcept\u001b[0m TimeoutExceededError \u001b[94mas\u001b[0m e:                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m282 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mlogger.error(\u001b[33m\"\u001b[0m\u001b[33mError: \u001b[0m\u001b[33m%s\u001b[0m\u001b[33m\"\u001b[0m, e)                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m283 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mn/common_utils/\u001b[0m\u001b[1;33mtrainer_wait.py\u001b[0m:\u001b[94m272\u001b[0m in \u001b[92mwait\u001b[0m                                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m269 \u001b[0m\u001b[2m│   │   │   │   \u001b[0miteration = \u001b[94m0\u001b[0m                                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m270 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mwhile\u001b[0m \u001b[94mTrue\u001b[0m:                                                                \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m271 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0miteration += \u001b[94m1\u001b[0m                                                         \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m272 \u001b[2m│   │   │   │   │   \u001b[0mtime.sleep(\u001b[94m0.5\u001b[0m)                                                        \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m273 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mif\u001b[0m iteration >= poll * \u001b[94m2\u001b[0m:                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m274 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0mtraining_job.refresh()                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m275 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0miteration = \u001b[94m0\u001b[0m                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
+       "\u001b[1;91mKeyboardInterrupt\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "training_job = sft_trainer.train(\n",
-    "    wait=True,\n",
+    "    wait=True\n",
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "64d68d6f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
[03/05/26 15:52:42] WARNING  No region provided. Using default region.                                 utils.py:356\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m[03/05/26 15:52:42]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;215;175;0mWARNING \u001b[0m No region provided. Using default region.                                 \u001b]8;id=398978;file:///Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/utils/utils.py\u001b\\\u001b[2mutils.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=927295;file:///Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/utils/utils.py#356\u001b\\\u001b[2m356\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
                    INFO     Runs on sagemaker prod, region:us-east-1                                  utils.py:370\n",
+       "
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+      ],
+      "text/plain": [
+       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Runs on sagemaker prod, region:us-east-\u001b[1;36m1\u001b[0m                                  \u001b]8;id=459862;file:///Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/utils/utils.py\u001b\\\u001b[2mutils.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=910567;file:///Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/utils/utils.py#370\u001b\\\u001b[2m370\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
                    INFO     Found credentials in shared credentials file: ~/.aws/credentials   credentials.py:1392\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=500109;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=207687;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
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+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
                    INFO     Found credentials in shared credentials file: ~/.aws/credentials   credentials.py:1392\n",
+       "
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+      ],
+      "text/plain": [
+       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=615220;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=20168;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
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+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
[03/05/26 15:52:46] INFO     Found credentials in shared credentials file: ~/.aws/credentials   credentials.py:1392\n",
+       "
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+      ],
+      "text/plain": [
+       "\u001b[2;36m[03/05/26 15:52:46]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=639090;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=958918;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "https://app-2SV6Q35HTCBO.mlflow.sagemaker.us-east-1.app.aws/auth?authToken=eyJhbGciOiJIUzI1NiJ9.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.4TwUDjNP53N-JIHofgyV8hq_6HKftycvEWoOxoqk7fc#/experiments/2\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sagemaker.train import get_mlflow_url\n",
+    "\n",
+    "# Get MLflow URL for a training job\n",
+    "url = get_mlflow_url(\"nova-textgeneration-micro-sft-20260303164831\")\n",
+    "print(url)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "fef3d01d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "https://studio-d-ingyyaeglvki.studio.us-east-1.sagemaker.aws/jobs/train/nova-textgeneration-micro-sft-20260302144611\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sagemaker.train import get_studio_url\n",
+    "\n",
+    "\n",
+    "# Still working on getting the specific training job\n",
+    "url = get_studio_url('nova-textgeneration-micro-sft-20260302144611')\n",
+    "print(url)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0373cea6-7419-47f1-a59e-1cb441324dc3",
+   "id": "9b50b630",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sagemaker.core.resources import TrainingJob\n",
+    "\n",
+    "training_job = TrainingJob.get(training_job_name='nova-textgeneration-micro-sft-20260303161941')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8fa20618",
    "metadata": {},
    "outputs": [],
    "source": [
+    "from sagemaker.train import get_studio_url\n",
     "\n",
+    "# Studio URL (job details)\n",
+    "studio_url = get_studio_url(training_job)\n",
+    "print(studio_url)\n",
+    "\n",
+    "# CloudWatch Logs URL (view logs directly)\n",
+    "url = get_studio_url(training_job, direct=True)\n",
+    "print(url)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "591d5e98",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "job.stop()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da489ad0-36b8-44e7-9f65-2ffd359e5225",
+   "metadata": {},
+   "source": [
+    "### View any Training job details\n",
+    "\n",
+    "We can get any training job details and its status with TrainingJob.get(...)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0373cea6-7419-47f1-a59e-1cb441324dc3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "\n",
     "import json\n",
     "import re\n",
     "from sagemaker.core.utils.utils import Unassigned\n",
-    "from sagemaker.core.resources import TrainingJob\n",
-    "\n",
-    "response = TrainingJob.get(training_job_name=\"meta-textgeneration-llama-3-2-1b-instruct-sft-20251201114921\")\n",
     "\n",
     "def pretty_print(obj):\n",
     "    def parse_unassigned(item):\n",
@@ -260,62 +633,78 @@
     "        return item\n",
     "\n",
     "    cleaned = parse_unassigned(obj.__dict__ if hasattr(obj, '__dict__') else obj)\n",
-    "    print(json.dumps(cleaned, indent=2, default=str))\n",
-    "\n",
-    "pretty_print(response)"
+    "    print(json.dumps(cleaned, indent=2, default=str))"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e9ee7f8e-b26c-4579-9dbc-f08124f2e944",
-   "metadata": {},
+   "id": "6bbe96b4-c8cd-4de3-b4c0-a66fd3086eb2",
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
    "source": [
-    "#In order to skip waiting and monitor the training Job later\n",
+    "from sagemaker.core.resources import TrainingJob\n",
     "\n",
-    "'''\n",
-    "training_job = sft_trainer.train(\n",
-    "    wait=False,\n",
-    ")\n",
-    "'''"
+    "response = TrainingJob.get(training_job_name=\"nova-textgeneration-micro-sft-20260302144611\")\n",
+    "pretty_print(response)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8d25735e",
+   "metadata": {},
+   "source": [
+    "## Visualize Training Metrics\n",
+    "\n",
+    "After training completes, you can visualize metrics logged to MLflow:\n",
+    "\n",
+    "- **`get_available_metrics(job)`** - List all available metrics\n",
+    "- **`plot_training_metrics(job)`** - Plot all metrics\n",
+    "- **`plot_training_metrics(job, metrics=['reduced_train_loss', 'global_step'])`** - Plot specific metrics"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0d99f212-f0bd-43c1-be21-30202fb4a152",
-   "metadata": {
-    "scrolled": true
-   },
+   "id": "b8a9256c",
+   "metadata": {},
    "outputs": [],
    "source": [
-    "pretty_print(training_job)"
+    "from sagemaker.train import get_available_metrics\n",
+    "\n",
+    "get_available_metrics('nova-textgeneration-micro-sft-20260302144611')"
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "da489ad0-36b8-44e7-9f65-2ffd359e5225",
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f1a794ba",
    "metadata": {},
+   "outputs": [],
    "source": [
-    "### View any Training job details\n",
+    "from sagemaker.train import plot_training_metrics\n",
     "\n",
-    "We can get any training job details and its status with TrainingJob.get(...)"
+    "# Simple - plot all metrics\n",
+    "plot_training_metrics('nova-textgeneration-micro-sft-20260302144611')"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6bbe96b4-c8cd-4de3-b4c0-a66fd3086eb2",
-   "metadata": {
-    "scrolled": true
-   },
+   "id": "2f7ed9d7",
+   "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker.core.resources import TrainingJob\n",
+    "from sagemaker.train import plot_training_metrics\n",
     "\n",
-    "response = TrainingJob.get(training_job_name=\"meta-textgeneration-llama-3-2-1b-instruct-sft-20251123162832\")\n",
-    "pretty_print(response)"
+    "# Advanced - plot specific metrics\n",
+    "plot_training_metrics(\n",
+    "    training_job='nova-textgeneration-micro-sft-20260302144611',\n",
+    "    metrics=['reduced_train_loss', 'global_step'],\n",
+    "    figsize=(14, 6)\n",
+    ")"
    ]
   },
   {
@@ -464,11 +853,31 @@
     "    wait=True,\n",
     ")"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "be4dc095",
+   "metadata": {},
+   "source": [
+    "### Stop Training Job"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fb92815b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sagemaker.core.resources import TrainingJob\n",
+    "job = TrainingJob.get(training_job_name='nova-textgeneration-pro-sft-20260304135114')\n",
+    "job.stop()"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "py3.10.14",
    "language": "python",
    "name": "python3"
   },
@@ -482,7 +891,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.10"
+   "version": "3.10.14"
   }
  },
  "nbformat": 4,
diff --git a/v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook.ipynb b/v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook.ipynb
index 4e49266323..a5f83647cc 100644
--- a/v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook.ipynb
+++ b/v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook.ipynb
@@ -47,10 +47,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "234f7398-fd6b-4d02-a406-0491924c461d",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
[03/02/26 14:23:42] INFO     Found credentials in shared credentials file: ~/.aws/credentials   credentials.py:1392\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m[03/02/26 14:23:42]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=981430;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=408099;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "sagemaker.config INFO - Not applying SDK defaults from location: /Library/Application Support/sagemaker/config.yaml\n",
+      "sagemaker.config INFO - Not applying SDK defaults from location: /Users/mollyhe/Library/Application Support/sagemaker/config.yaml\n",
+      "Region: us-east-1\n"
+     ]
+    }
+   ],
    "source": [
     "\n",
     "import os\n",
@@ -82,10 +105,110 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "39aaeb1d",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
[03/02/26 14:23:45] INFO     Found credentials in shared credentials file: ~/.aws/credentials   credentials.py:1392\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m[03/02/26 14:23:45]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=437588;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=570403;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
[03/02/26 14:23:46] INFO     SageMaker Python SDK will collect telemetry to help us better  telemetry_logging.py:92\n",
+       "                             understand our user's needs, diagnose issues, and deliver                             \n",
+       "                             additional features.                                                                  \n",
+       "                             To opt out of telemetry, please disable via TelemetryOptOut                           \n",
+       "                             parameter in SDK defaults config. For more information, refer                         \n",
+       "                             to                                                                                    \n",
+       "                             https://sagemaker.readthedocs.io/en/stable/overview.html#confi                        \n",
+       "                             guring-and-using-defaults-with-the-sagemaker-python-sdk.                              \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m[03/02/26 14:23:46]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m SageMaker Python SDK will collect telemetry to help us better  \u001b]8;id=719707;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/telemetry/telemetry_logging.py\u001b\\\u001b[2mtelemetry_logging.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=805235;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/telemetry/telemetry_logging.py#92\u001b\\\u001b[2m92\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[2;36m                    \u001b[0m         understand our user's needs, diagnose issues, and deliver      \u001b[2m                       \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         additional features.                                           \u001b[2m                       \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         To opt out of telemetry, please disable via TelemetryOptOut    \u001b[2m                       \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         parameter in SDK defaults config. For more information, refer  \u001b[2m                       \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         to                                                             \u001b[2m                       \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[4;38;2;0;105;255mhttps://sagemaker.readthedocs.io/en/stable/overview.html#confi\u001b[0m \u001b[2m                       \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[4;38;2;0;105;255mguring-and-using-defaults-with-the-sagemaker-python-sdk.\u001b[0m       \u001b[2m                       \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
[03/02/26 14:23:47] INFO     Role not provided. Using default role:                                  defaults.py:75\n",
+       "                             arn:aws:iam::529088288990:role/Admin                                                  \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m[03/02/26 14:23:47]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Role not provided. Using default role:                                  \u001b]8;id=193859;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/train/defaults.py\u001b\\\u001b[2mdefaults.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=892655;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/train/defaults.py#75\u001b\\\u001b[2m75\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[2;36m                    \u001b[0m         arn:aws:iam::\u001b[1;36m529088288990\u001b[0m:role/Admin                                    \u001b[2m              \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "521e87aea90849e48e5312e3160c5a23",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
Final Resource Status: Available\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "Final Resource Status: Available\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "TRAINING_DATASET ARN: arn:aws:sagemaker:us-east-1:529088288990:hub-content/G82247CBEQ6TN0FI3J1SAJU59UURMT3H3EKG48C6VQGDINNRNGU0/DataSet/demo-sft-dataset/3.0.0\n"
+     ]
+    }
+   ],
    "source": [
     "from sagemaker.ai_registry.dataset import DataSet\n",
     "from sagemaker.ai_registry.dataset_utils import CustomizationTechnique\n",
@@ -93,34 +216,34 @@
     "# Register dataset in SageMaker AI Registry. This creates a versioned dataset that can be referenced by ARN\n",
     "dataset = DataSet.create(\n",
     "    name=\"demo-sft-dataset\",\n",
-    "    source=\"s3://your-bucket/dataset/training_dataset.jsonl\", # source can be S3 or local path\n",
+    "    source=\"s3://sagemaker-us-east-1-529088288990/nova1_SFT.jsonl\", # source can be S3 or local path\n",
     "    #customization_technique=CUSTOMIZATION_TECHNIQUE.SFT # or DPO or RLVR\n",
     "        # Optional technique name for minimal dataset format check.\n",
     "    wait=True\n",
     ")\n",
     "\n",
     "print(f\"TRAINING_DATASET ARN: {dataset.arn}\")\n",
-    "# TRAINING_DATASET = dataset.arn"
+    "TRAINING_DATASET = dataset.arn"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "ea22bd22",
    "metadata": {},
    "outputs": [],
    "source": [
     "# Required Configs\n",
-    "BASE_MODEL = \"\"\n",
+    "BASE_MODEL = \"nova-textgeneration-micro\"\n",
     "\n",
     "# MODEL_PACKAGE_GROUP_NAME is same as CUSTOM_MODEL_NAME\n",
-    "MODEL_PACKAGE_GROUP_NAME = \"\"\n",
+    "MODEL_PACKAGE_GROUP_NAME = \"model-pacakge-group-nova4\"\n",
     "\n",
-    "TRAINING_DATASET = \"\"\n",
+    "# TRAINING_DATASET = \"\"\n",
     "\n",
-    "S3_OUTPUT_PATH = \"\"\n",
+    "S3_OUTPUT_PATH = \"s3://sagemaker-us-east-1-529088288990/output/\"\n",
     "\n",
-    "ROLE_ARN = \"\""
+    "ROLE_ARN = \"arn:aws:iam::529088288990:role/Admin\""
    ]
   },
   {
@@ -133,15 +256,68 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "90a1069d19eeee7",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
[03/02/26 14:23:59] INFO     Creating model_package_group resource.                              resources.py:25559\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m[03/02/26 14:23:59]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Creating model_package_group resource.                              \u001b]8;id=924503;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/resources.py\u001b\\\u001b[2mresources.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=629107;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/resources.py#25559\u001b\\\u001b[2m25559\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
                    WARNING  No region provided. Using default region.                                 utils.py:340\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;215;175;0mWARNING \u001b[0m No region provided. Using default region.                                 \u001b]8;id=617102;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/utils/utils.py\u001b\\\u001b[2mutils.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=566991;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/utils/utils.py#340\u001b\\\u001b[2m340\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
                    INFO     Runs on sagemaker prod, region:us-east-1                                  utils.py:354\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Runs on sagemaker prod, region:us-east-\u001b[1;36m1\u001b[0m                                  \u001b]8;id=132575;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/utils/utils.py\u001b\\\u001b[2mutils.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=459422;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/utils/utils.py#354\u001b\\\u001b[2m354\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
                    INFO     Found credentials in shared credentials file: ~/.aws/credentials   credentials.py:1392\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=803081;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=146617;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "from sagemaker.core.resources import ModelPackageGroup\n",
     "model_package_group = ModelPackageGroup.create(\n",
     "    model_package_group_name=MODEL_PACKAGE_GROUP_NAME,\n",
-    "    model_package_group_description='' # Required Description\n",
+    "    model_package_group_description='test nova textgeneration micro' # Required Description\n",
     ")"
    ]
   },
@@ -210,7 +386,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "062953d8",
    "metadata": {
     "editable": true,
@@ -401,10 +577,84 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "2f6eeb5e",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Default Finetuning Options:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "
{\n",
+       "│   'name': 'my-lora-run-wkxk5',\n",
+       "│   'global_batch_size': '64',\n",
+       "│   'max_epochs': '2',\n",
+       "│   'learning_rate': '1e-05',\n",
+       "│   'lora_alpha': '128',\n",
+       "│   'learning_rate_ratio': '16.0',\n",
+       "│   'max_context_length': '8192'\n",
+       "}\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'name'\u001b[0m: \u001b[38;2;0;135;0m'my-lora-run-wkxk5'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'global_batch_size'\u001b[0m: \u001b[38;2;0;135;0m'64'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_epochs'\u001b[0m: \u001b[38;2;0;135;0m'2'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'learning_rate'\u001b[0m: \u001b[38;2;0;135;0m'1e-05'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'lora_alpha'\u001b[0m: \u001b[38;2;0;135;0m'128'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'learning_rate_ratio'\u001b[0m: \u001b[38;2;0;135;0m'16.0'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_context_length'\u001b[0m: \u001b[38;2;0;135;0m'8192'\u001b[0m\n",
+       "\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Modified/User defined Options:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "
{\n",
+       "│   'name': 'my-lora-run-wkxk5',\n",
+       "│   'global_batch_size': '64',\n",
+       "│   'max_epochs': '2',\n",
+       "│   'learning_rate': '0.0002',\n",
+       "│   'lora_alpha': '128',\n",
+       "│   'learning_rate_ratio': '16.0',\n",
+       "│   'max_context_length': '8192'\n",
+       "}\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'name'\u001b[0m: \u001b[38;2;0;135;0m'my-lora-run-wkxk5'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'global_batch_size'\u001b[0m: \u001b[38;2;0;135;0m'64'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_epochs'\u001b[0m: \u001b[38;2;0;135;0m'2'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'learning_rate'\u001b[0m: \u001b[38;2;0;135;0m'0.0002'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'lora_alpha'\u001b[0m: \u001b[38;2;0;135;0m'128'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'learning_rate_ratio'\u001b[0m: \u001b[38;2;0;135;0m'16.0'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_context_length'\u001b[0m: \u001b[38;2;0;135;0m'8192'\u001b[0m\n",
+       "\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "print(\"Default Finetuning Options:\")\n",
     "pprint(trainer.hyperparameters.to_dict())\n",
@@ -426,10 +676,355 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "31690f41",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
╭────────────────────────────────── Training Job Status ───────────────────────────────────╮\n",
+       "│  TrainingJob Name      nova-textgeneration-micro-sft-20260302142433                      │\n",
+       "│                                                                                          │\n",
+       "│  Job Status            InProgress                                                        │\n",
+       "│  Secondary Status      Pending                                                           │\n",
+       "│  Elapsed Time          814.3s                                                            │\n",
+       "│                                                                                          │\n",
+       "│ Status Transitions                                                                       │\n",
+       "│                                                                                          │\n",
+       "│        Step              Details                               Duration                  │\n",
+       "│  ───────────────────────────────────────────────────────────────────────────             │\n",
+       "│   ✓    Starting          Starting the training job             2.2s                      │\n",
+       "│        Pending           Training job waiting for capacity                               │\n",
+       "│                                                                                          │\n",
+       "╰──────────────────────────────────────────────────────────────────────────────────────────╯\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;172m╭─\u001b[0m\u001b[38;5;172m─────────────────────────────────\u001b[0m\u001b[38;5;172m \u001b[0m\u001b[1;94mTraining Job Status\u001b[0m\u001b[38;5;172m \u001b[0m\u001b[38;5;172m──────────────────────────────────\u001b[0m\u001b[38;5;172m─╮\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mTrainingJob Name    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;32mnova-textgeneration-micro-sft-20260302142433\u001b[0m\u001b[37m \u001b[0m                     \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mJob Status          \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;38;5;172mInProgress\u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mSecondary Status    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;33mPending\u001b[0m\u001b[37m   \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mElapsed Time        \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;91m814.3s\u001b[0m\u001b[37m    \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;35mStatus Transitions\u001b[0m                                                                       \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[1;35m \u001b[0m\u001b[1;35m  \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mStep           \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mDetails                            \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mDuration    \u001b[0m\u001b[1;35m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  ───────────────────────────────────────────────────────────────────────────             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m✓ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mStarting       \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mStarting the training job          \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m2.2s        \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m  \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mPending        \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mTraining job waiting for capacity  \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m            \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m╰──────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra │\n",
+       "│ in/common_utils/trainer_wait.py:197 in wait                                                      │\n",
+       "│                                                                                                  │\n",
+       "│   194 │   │   │   │   │   iteration += 1                                                         │\n",
+       "│   195 │   │   │   │   │   time.sleep(1)                                                          │\n",
+       "│   196 │   │   │   │   │   if iteration == poll:                                                  │\n",
+       "│ ❱ 197 │   │   │   │   │   │   training_job.refresh()                                             │\n",
+       "│   198 │   │   │   │   │   │   iteration = 0                                                      │\n",
+       "│   199 │   │   │   │   │   clear_output(wait=True)                                                │\n",
+       "│   200                                                                                            │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor │\n",
+       "│ e/resources.py:143 in wrapper                                                                    │\n",
+       "│                                                                                                  │\n",
+       "│     140 │   │   @functools.wraps(func)                                                           │\n",
+       "│     141 │   │   def wrapper(*args, **kwargs):                                                    │\n",
+       "│     142 │   │   │   config = dict(arbitrary_types_allowed=True)                                  │\n",
+       "│ ❱   143 │   │   │   return validate_call(config=config)(func)(*args, **kwargs)                   │\n",
+       "│     144 │   │                                                                                    │\n",
+       "│     145 │   │   return wrapper                                                                   │\n",
+       "│     146                                                                                          │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/pydantic/_int │\n",
+       "│ ernal/_validate_call.py:39 in wrapper_function                                                   │\n",
+       "│                                                                                                  │\n",
+       "│    36 │   │                                                                                      │\n",
+       "│    37 │   │   @functools.wraps(wrapped)                                                          │\n",
+       "│    38 │   │   def wrapper_function(*args, **kwargs):                                             │\n",
+       "│ ❱  39 │   │   │   return wrapper(*args, **kwargs)                                                │\n",
+       "│    40 │                                                                                          │\n",
+       "│    41 │   # We need to manually update this because `partial` object has no `__name__` and `__   │\n",
+       "│    42 │   wrapper_function.__name__ = extract_function_name(wrapped)                             │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/pydantic/_int │\n",
+       "│ ernal/_validate_call.py:136 in __call__                                                          │\n",
+       "│                                                                                                  │\n",
+       "│   133 │   │   if not self.__pydantic_complete__:                                                 │\n",
+       "│   134 │   │   │   self._create_validators()                                                      │\n",
+       "│   135 │   │                                                                                      │\n",
+       "│ ❱ 136 │   │   res = self.__pydantic_validator__.validate_python(pydantic_core.ArgsKwargs(args,   │\n",
+       "│   137 │   │   if self.__return_pydantic_validator__:                                             │\n",
+       "│   138 │   │   │   return self.__return_pydantic_validator__(res)                                 │\n",
+       "│   139 │   │   else:                                                                              │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor │\n",
+       "│ e/resources.py:35682 in refresh                                                                  │\n",
+       "│                                                                                                  │\n",
+       "│   35679 │   │   logger.debug(f\"Serialized input request: {operation_input_args}\")                │\n",
+       "│   35680 │   │                                                                                    │\n",
+       "│   35681 │   │   client = Base.get_sagemaker_client()                                             │\n",
+       "│ ❱ 35682 │   │   response = client.describe_training_job(**operation_input_args)                  │\n",
+       "│   35683 │   │                                                                                    │\n",
+       "│   35684 │   │   # deserialize response and update self                                           │\n",
+       "│   35685 │   │   transform(response, \"DescribeTrainingJobResponse\", self)                         │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/clie │\n",
+       "│ nt.py:602 in _api_call                                                                           │\n",
+       "│                                                                                                  │\n",
+       "│    599 │   │   │   │   │   f\"{py_operation_name}() only accepts keyword arguments.\"              │\n",
+       "│    600 │   │   │   │   )                                                                         │\n",
+       "│    601 │   │   │   # The \"self\" in this scope is referring to the BaseClient.                    │\n",
+       "│ ❱  602 │   │   │   return self._make_api_call(operation_name, kwargs)                            │\n",
+       "│    603 │   │                                                                                     │\n",
+       "│    604 │   │   _api_call.__name__ = str(py_operation_name)                                       │\n",
+       "│    605                                                                                           │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/cont │\n",
+       "│ ext.py:123 in wrapper                                                                            │\n",
+       "│                                                                                                  │\n",
+       "│   120 │   │   │   with start_as_current_context():                                               │\n",
+       "│   121 │   │   │   │   if hook:                                                                   │\n",
+       "│   122 │   │   │   │   │   hook()                                                                 │\n",
+       "│ ❱ 123 │   │   │   │   return func(*args, **kwargs)                                               │\n",
+       "│   124 │   │                                                                                      │\n",
+       "│   125 │   │   return wrapper                                                                     │\n",
+       "│   126                                                                                            │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/clie │\n",
+       "│ nt.py:1078 in _make_api_call                                                                     │\n",
+       "│                                                                                                  │\n",
+       "│   1075 │   │   │   │   'error_code_override'                                                     │\n",
+       "│   1076 │   │   │   ) or error_info.get(\"Code\")                                                   │\n",
+       "│   1077 │   │   │   error_class = self.exceptions.from_code(error_code)                           │\n",
+       "│ ❱ 1078 │   │   │   raise error_class(parsed_response, operation_name)                            │\n",
+       "│   1079 │   │   else:                                                                             │\n",
+       "│   1080 │   │   │   return parsed_response                                                        │\n",
+       "│   1081                                                                                           │\n",
+       "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
+       "ClientError: An error occurred (ExpiredTokenException) when calling the DescribeTrainingJob operation: The security\n",
+       "token included in the request is expired\n",
+       "\n",
+       "The above exception was the direct cause of the following exception:\n",
+       "\n",
+       "╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮\n",
+       "│ in <module>:1                                                                                    │\n",
+       "│                                                                                                  │\n",
+       "│ ❱ 1 training_job = trainer.train(wait=True)                                                      │\n",
+       "│   2                                                                                              │\n",
+       "│   3 TRAINING_JOB_NAME = training_job.training_job_name                                           │\n",
+       "│   4                                                                                              │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor │\n",
+       "│ e/telemetry/telemetry_logging.py:168 in wrapper                                                  │\n",
+       "│                                                                                                  │\n",
+       "│   165 │   │   │   │   │   caught_ex = e                                                          │\n",
+       "│   166 │   │   │   │   finally:                                                                   │\n",
+       "│   167 │   │   │   │   │   if caught_ex:                                                          │\n",
+       "│ ❱ 168 │   │   │   │   │   │   raise caught_ex                                                    │\n",
+       "│   169 │   │   │   │   │   return response  # pylint: disable=W0150                               │\n",
+       "│   170 │   │   │   else:                                                                          │\n",
+       "│   171 │   │   │   │   logger.debug(                                                              │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor │\n",
+       "│ e/telemetry/telemetry_logging.py:139 in wrapper                                                  │\n",
+       "│                                                                                                  │\n",
+       "│   136 │   │   │   │   start_timer = perf_counter()                                               │\n",
+       "│   137 │   │   │   │   try:                                                                       │\n",
+       "│   138 │   │   │   │   │   # Call the original function                                           │\n",
+       "│ ❱ 139 │   │   │   │   │   response = func(*args, **kwargs)                                       │\n",
+       "│   140 │   │   │   │   │   stop_timer = perf_counter()                                            │\n",
+       "│   141 │   │   │   │   │   elapsed = stop_timer - start_timer                                     │\n",
+       "│   142 │   │   │   │   │   extra += f\"&x-latency={round(elapsed, 2)}\"                             │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra │\n",
+       "│ in/sft_trainer.py:267 in train                                                                   │\n",
+       "│                                                                                                  │\n",
+       "│   264 │   │   │   from sagemaker.train.common_utils.trainer_wait import wait as _wait            │\n",
+       "│   265 │   │   │   from sagemaker.core.utils.exceptions import TimeoutExceededError               │\n",
+       "│   266 │   │   │   try :                                                                          │\n",
+       "│ ❱ 267 │   │   │   │   _wait(training_job)                                                        │\n",
+       "│   268 │   │   │   except TimeoutExceededError as e:                                              │\n",
+       "│   269 │   │   │   │   logger.error(\"Error: %s\", e)                                               │\n",
+       "│   270                                                                                            │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra │\n",
+       "│ in/common_utils/trainer_wait.py:374 in wait                                                      │\n",
+       "│                                                                                                  │\n",
+       "│   371 │   except (FailedStatusError, TimeoutExceededError):                                      │\n",
+       "│   372 │   │   raise                                                                              │\n",
+       "│   373 │   except Exception as e:                                                                 │\n",
+       "│ ❱ 374 │   │   raise RuntimeError(f\"Training job monitoring failed: {e}\") from e                  │\n",
+       "│   375                                                                                            │\n",
+       "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
+       "RuntimeError: Training job monitoring failed: An error occurred (ExpiredTokenException) when calling the \n",
+       "DescribeTrainingJob operation: The security token included in the request is expired\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[38;2;255;0;0m╭─\u001b[0m\u001b[38;2;255;0;0m──────────────────────────────\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[1;38;2;255;0;0mTraceback \u001b[0m\u001b[1;2;38;2;255;0;0m(most recent call last)\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[38;2;255;0;0m───────────────────────────────\u001b[0m\u001b[38;2;255;0;0m─╮\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33min/common_utils/\u001b[0m\u001b[1;33mtrainer_wait.py\u001b[0m:\u001b[94m197\u001b[0m in \u001b[92mwait\u001b[0m                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m194 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0miteration += \u001b[94m1\u001b[0m                                                         \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m195 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mtime.sleep(\u001b[94m1\u001b[0m)                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m196 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mif\u001b[0m iteration == poll:                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m197 \u001b[2m│   │   │   │   │   │   \u001b[0mtraining_job.refresh()                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m198 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0miteration = \u001b[94m0\u001b[0m                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m199 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mclear_output(wait=\u001b[94mTrue\u001b[0m)                                                \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m200 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33me/\u001b[0m\u001b[1;33mresources.py\u001b[0m:\u001b[94m143\u001b[0m in \u001b[92mwrapper\u001b[0m                                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  140 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[1;95m@functools\u001b[0m.wraps(func)                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  141 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mdef\u001b[0m\u001b[90m \u001b[0m\u001b[92mwrapper\u001b[0m(*args, **kwargs):                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  142 \u001b[0m\u001b[2m│   │   │   \u001b[0mconfig = \u001b[96mdict\u001b[0m(arbitrary_types_allowed=\u001b[94mTrue\u001b[0m)                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m  143 \u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m validate_call(config=config)(func)(*args, **kwargs)                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  144 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  145 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m wrapper                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  146 \u001b[0m                                                                                         \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/pydantic/_int\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mernal/\u001b[0m\u001b[1;33m_validate_call.py\u001b[0m:\u001b[94m39\u001b[0m in \u001b[92mwrapper_function\u001b[0m                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 36 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 37 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[1;95m@functools\u001b[0m.wraps(wrapped)                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 38 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mdef\u001b[0m\u001b[90m \u001b[0m\u001b[92mwrapper_function\u001b[0m(*args, **kwargs):                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m 39 \u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m wrapper(*args, **kwargs)                                                \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 40 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 41 \u001b[0m\u001b[2m│   \u001b[0m\u001b[2m# We need to manually update this because `partial` object has no `__name__` and `__\u001b[0m   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 42 \u001b[0m\u001b[2m│   \u001b[0mwrapper_function.\u001b[91m__name__\u001b[0m = extract_function_name(wrapped)                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/pydantic/_int\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mernal/\u001b[0m\u001b[1;33m_validate_call.py\u001b[0m:\u001b[94m136\u001b[0m in \u001b[92m__call__\u001b[0m                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m133 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[95mnot\u001b[0m \u001b[96mself\u001b[0m.__pydantic_complete__:                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m134 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m._create_validators()                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m135 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m136 \u001b[2m│   │   \u001b[0mres = \u001b[96mself\u001b[0m.__pydantic_validator__.validate_python(pydantic_core.ArgsKwargs(args,   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m137 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mself\u001b[0m.__return_pydantic_validator__:                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m138 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mself\u001b[0m.__return_pydantic_validator__(res)                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m139 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33me/\u001b[0m\u001b[1;33mresources.py\u001b[0m:\u001b[94m35682\u001b[0m in \u001b[92mrefresh\u001b[0m                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35679 \u001b[0m\u001b[2m│   │   \u001b[0mlogger.debug(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33mSerialized input request: \u001b[0m\u001b[33m{\u001b[0moperation_input_args\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m)                \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35680 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35681 \u001b[0m\u001b[2m│   │   \u001b[0mclient = Base.get_sagemaker_client()                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m35682 \u001b[2m│   │   \u001b[0mresponse = client.describe_training_job(**operation_input_args)                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35683 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35684 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[2m# deserialize response and update self\u001b[0m                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35685 \u001b[0m\u001b[2m│   │   \u001b[0mtransform(response, \u001b[33m\"\u001b[0m\u001b[33mDescribeTrainingJobResponse\u001b[0m\u001b[33m\"\u001b[0m, \u001b[96mself\u001b[0m)                         \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/\u001b[0m\u001b[1;33mclie\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[1;33mnt.py\u001b[0m:\u001b[94m602\u001b[0m in \u001b[92m_api_call\u001b[0m                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 599 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m{\u001b[0mpy_operation_name\u001b[33m}\u001b[0m\u001b[33m() only accepts keyword arguments.\u001b[0m\u001b[33m\"\u001b[0m              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 600 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m)                                                                         \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 601 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# The \"self\" in this scope is referring to the BaseClient.\u001b[0m                    \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m 602 \u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mself\u001b[0m._make_api_call(operation_name, kwargs)                            \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 603 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 604 \u001b[0m\u001b[2m│   │   \u001b[0m_api_call.\u001b[91m__name__\u001b[0m = \u001b[96mstr\u001b[0m(py_operation_name)                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 605 \u001b[0m                                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/\u001b[0m\u001b[1;33mcont\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[1;33mext.py\u001b[0m:\u001b[94m123\u001b[0m in \u001b[92mwrapper\u001b[0m                                                                            \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m120 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mwith\u001b[0m start_as_current_context():                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m121 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m hook:                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m122 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mhook()                                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m123 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m func(*args, **kwargs)                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m124 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m125 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m wrapper                                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m126 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/\u001b[0m\u001b[1;33mclie\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[1;33mnt.py\u001b[0m:\u001b[94m1078\u001b[0m in \u001b[92m_make_api_call\u001b[0m                                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1075 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[33m'\u001b[0m\u001b[33merror_code_override\u001b[0m\u001b[33m'\u001b[0m                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1076 \u001b[0m\u001b[2m│   │   │   \u001b[0m) \u001b[95mor\u001b[0m error_info.get(\u001b[33m\"\u001b[0m\u001b[33mCode\u001b[0m\u001b[33m\"\u001b[0m)                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1077 \u001b[0m\u001b[2m│   │   │   \u001b[0merror_class = \u001b[96mself\u001b[0m.exceptions.from_code(error_code)                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m1078 \u001b[2m│   │   │   \u001b[0m\u001b[94mraise\u001b[0m error_class(parsed_response, operation_name)                            \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1079 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1080 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m parsed_response                                                        \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1081 \u001b[0m                                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
+       "\u001b[1;91mClientError: \u001b[0mAn error occurred \u001b[1m(\u001b[0mExpiredTokenException\u001b[1m)\u001b[0m when calling the DescribeTrainingJob operation: The security\n",
+       "token included in the request is expired\n",
+       "\n",
+       "\u001b[3mThe above exception was the direct cause of the following exception:\u001b[0m\n",
+       "\n",
+       "\u001b[38;2;255;0;0m╭─\u001b[0m\u001b[38;2;255;0;0m──────────────────────────────\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[1;38;2;255;0;0mTraceback \u001b[0m\u001b[1;2;38;2;255;0;0m(most recent call last)\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[38;2;255;0;0m───────────────────────────────\u001b[0m\u001b[38;2;255;0;0m─╮\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m in \u001b[92m\u001b[0m:\u001b[94m1\u001b[0m                                                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m1 training_job = trainer.train(wait=\u001b[94mTrue\u001b[0m)                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m2 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m3 \u001b[0mTRAINING_JOB_NAME = training_job.training_job_name                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m4 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33me/telemetry/\u001b[0m\u001b[1;33mtelemetry_logging.py\u001b[0m:\u001b[94m168\u001b[0m in \u001b[92mwrapper\u001b[0m                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m165 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mcaught_ex = e                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m166 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mfinally\u001b[0m:                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m167 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mif\u001b[0m caught_ex:                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m168 \u001b[2m│   │   │   │   │   │   \u001b[0m\u001b[94mraise\u001b[0m caught_ex                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m169 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m response  \u001b[2m# pylint: disable=W0150\u001b[0m                               \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m170 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m171 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mlogger.debug(                                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33me/telemetry/\u001b[0m\u001b[1;33mtelemetry_logging.py\u001b[0m:\u001b[94m139\u001b[0m in \u001b[92mwrapper\u001b[0m                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m136 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mstart_timer = perf_counter()                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m137 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m138 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[2m# Call the original function\u001b[0m                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m139 \u001b[2m│   │   │   │   │   \u001b[0mresponse = func(*args, **kwargs)                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m140 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mstop_timer = perf_counter()                                            \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m141 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0melapsed = stop_timer - start_timer                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m142 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mextra += \u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m&x-latency=\u001b[0m\u001b[33m{\u001b[0m\u001b[96mround\u001b[0m(elapsed,\u001b[90m \u001b[0m\u001b[94m2\u001b[0m)\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33min/\u001b[0m\u001b[1;33msft_trainer.py\u001b[0m:\u001b[94m267\u001b[0m in \u001b[92mtrain\u001b[0m                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m264 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mfrom\u001b[0m\u001b[90m \u001b[0m\u001b[4;96msagemaker\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mtrain\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mcommon_utils\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mtrainer_wait\u001b[0m\u001b[90m \u001b[0m\u001b[94mimport\u001b[0m wait \u001b[94mas\u001b[0m _wait            \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m265 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mfrom\u001b[0m\u001b[90m \u001b[0m\u001b[4;96msagemaker\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mcore\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mutils\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mexceptions\u001b[0m\u001b[90m \u001b[0m\u001b[94mimport\u001b[0m TimeoutExceededError               \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m266 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mtry\u001b[0m :                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m267 \u001b[2m│   │   │   │   \u001b[0m_wait(training_job)                                                        \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m268 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mexcept\u001b[0m TimeoutExceededError \u001b[94mas\u001b[0m e:                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m269 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mlogger.error(\u001b[33m\"\u001b[0m\u001b[33mError: \u001b[0m\u001b[33m%s\u001b[0m\u001b[33m\"\u001b[0m, e)                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m270 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33min/common_utils/\u001b[0m\u001b[1;33mtrainer_wait.py\u001b[0m:\u001b[94m374\u001b[0m in \u001b[92mwait\u001b[0m                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m371 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mexcept\u001b[0m (FailedStatusError, TimeoutExceededError):                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m372 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mraise\u001b[0m                                                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m373 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mexcept\u001b[0m \u001b[96mException\u001b[0m \u001b[94mas\u001b[0m e:                                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m374 \u001b[2m│   │   \u001b[0m\u001b[94mraise\u001b[0m \u001b[96mRuntimeError\u001b[0m(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33mTraining job monitoring failed: \u001b[0m\u001b[33m{\u001b[0me\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m) \u001b[94mfrom\u001b[0m\u001b[90m \u001b[0m\u001b[4;96me\u001b[0m                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m375 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
+       "\u001b[1;91mRuntimeError: \u001b[0mTraining job monitoring failed: An error occurred \u001b[1m(\u001b[0mExpiredTokenException\u001b[1m)\u001b[0m when calling the \n",
+       "DescribeTrainingJob operation: The security token included in the request is expired\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "training_job = trainer.train(wait=True)\n",
     "\n",
@@ -1069,7 +1664,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.11"
+   "version": "3.10.14"
   }
  },
  "nbformat": 4,

From 7b5f8b14c42ec0a387c76837a38d809f32cdb2b2 Mon Sep 17 00:00:00 2001
From: Molly He 
Date: Tue, 10 Mar 2026 17:55:52 -0700
Subject: [PATCH 02/11] Evaluation job update

---
 .../evaluate/benchmark_demo.ipynb             | 549 +++++++++++++++++-
 .../train/common_utils/metrics_visualizer.py  | 102 +++-
 .../src/sagemaker/train/evaluate/execution.py |  69 ++-
 .../train/evaluate/pipeline_templates.py      |   9 +-
 ...uning_example_notebook_pysdk_prod_v3.ipynb | 222 +++----
 5 files changed, 757 insertions(+), 194 deletions(-)

diff --git a/sagemaker-train/example_notebooks/evaluate/benchmark_demo.ipynb b/sagemaker-train/example_notebooks/evaluate/benchmark_demo.ipynb
index e0133a9272..b78d35b8e9 100644
--- a/sagemaker-train/example_notebooks/evaluate/benchmark_demo.ipynb
+++ b/sagemaker-train/example_notebooks/evaluate/benchmark_demo.ipynb
@@ -24,23 +24,94 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
+   "source": [
+    "import logging\n",
+    "logging.basicConfig(level=logging.WARNING)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
[\n",
+       "│   <_Benchmark.MMLU: 'mmlu'>,\n",
+       "│   <_Benchmark.MMLU_PRO: 'mmlu_pro'>,\n",
+       "│   <_Benchmark.BBH: 'bbh'>,\n",
+       "│   <_Benchmark.GPQA: 'gpqa'>,\n",
+       "│   <_Benchmark.MATH: 'math'>,\n",
+       "│   <_Benchmark.STRONG_REJECT: 'strong_reject'>,\n",
+       "│   <_Benchmark.IFEVAL: 'ifeval'>,\n",
+       "│   <_Benchmark.MMMU: 'mmmu'>,\n",
+       "│   <_Benchmark.LLM_JUDGE: 'llm_judge'>\n",
+       "]\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[1m[\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[1m<\u001b[0m\u001b[1;38;2;225;0;225m_Benchmark.MMLU:\u001b[0m\u001b[39m \u001b[0m\u001b[38;2;0;135;0m'mmlu'\u001b[0m\u001b[39m>,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.MMLU_PRO: \u001b[0m\u001b[38;2;0;135;0m'mmlu_pro'\u001b[0m\u001b[39m>,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.BBH: \u001b[0m\u001b[38;2;0;135;0m'bbh'\u001b[0m\u001b[39m>,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.GPQA: \u001b[0m\u001b[38;2;0;135;0m'gpqa'\u001b[0m\u001b[39m>,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.MATH: \u001b[0m\u001b[38;2;0;135;0m'math'\u001b[0m\u001b[39m>,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.STRONG_REJECT: \u001b[0m\u001b[38;2;0;135;0m'strong_reject'\u001b[0m\u001b[39m>,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.IFEVAL: \u001b[0m\u001b[38;2;0;135;0m'ifeval'\u001b[0m\u001b[39m>,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.MMMU: \u001b[0m\u001b[38;2;0;135;0m'mmmu'\u001b[0m\u001b[39m>,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.LLM_JUDGE: \u001b[0m\u001b[38;2;0;135;0m'llm_judge'\u001b[0m\u001b[1m>\u001b[0m\n",
+       "\u001b[1m]\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
{\n",
+       "│   'modality': 'Text',\n",
+       "│   'description': 'General Physics Question Answering – Assesses comprehension of physics concepts and related problem-solving abilities.',\n",
+       "│   'metrics': ['accuracy'],\n",
+       "│   'strategy': 'zs_cot',\n",
+       "│   'subtask_available': False,\n",
+       "│   'subtasks': None\n",
+       "}\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'modality'\u001b[0m: \u001b[38;2;0;135;0m'Text'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'description'\u001b[0m: \u001b[38;2;0;135;0m'General Physics Question Answering – Assesses comprehension of physics concepts and related problem-solving abilities.'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'metrics'\u001b[0m: \u001b[1m[\u001b[0m\u001b[38;2;0;135;0m'accuracy'\u001b[0m\u001b[1m]\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'strategy'\u001b[0m: \u001b[38;2;0;135;0m'zs_cot'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'subtask_available'\u001b[0m: \u001b[3;38;2;215;0;0mFalse\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'subtasks'\u001b[0m: \u001b[3;38;2;225;0;225mNone\u001b[0m\n",
+       "\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "from sagemaker.train.evaluate import get_benchmarks, get_benchmark_properties\n",
     "from rich.pretty import pprint\n",
     "\n",
     "# Configure logging to show INFO messages\n",
-    "import logging\n",
-    "logging.basicConfig(\n",
-    "    level=logging.INFO,\n",
-    "    format='%(levelname)s - %(name)s - %(message)s'\n",
-    ")\n",
+    "# import logging\n",
+    "# logging.basicConfig(\n",
+    "#     level=logging.INFO,\n",
+    "#     format='%(levelname)s - %(name)s - %(message)s'\n",
+    "# )\n",
     "\n",
     "# Get available benchmarks\n",
     "Benchmark = get_benchmarks()\n",
     "pprint(list(Benchmark))\n",
     "\n",
     "# Print properties for a specific benchmark\n",
-    "pprint(get_benchmark_properties(benchmark=Benchmark.GEN_QA))"
+    "pprint(get_benchmark_properties(benchmark=Benchmark.GPQA))"
    ]
   },
   {
@@ -67,22 +138,200 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING:sagemaker.core.utils.utils:No region provided. Using default region.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "model_package_group_name='model-package-group-nova13' model_package_group_arn='arn:aws:sagemaker:us-east-1:529088288990:model-package-group/model-package-group-nova13' model_package_group_description=Unassigned() creation_time=datetime.datetime(2026, 3, 4, 13, 13, 33, 33000, tzinfo=tzlocal()) created_by=UserContext(user_profile_arn=Unassigned(), user_profile_name=Unassigned(), domain_id=Unassigned(), iam_identity=IamIdentity(arn='arn:aws:sts::529088288990:assumed-role/Admin/mollyhe-Isengard', principal_id='AROAXWMA6TDPKWL3QDB2W:mollyhe-Isengard', source_identity=Unassigned())) model_package_group_status='Completed'\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sagemaker.core.resources import ModelPackage, ModelPackageGroup\n",
+    "\n",
+    "# model_package_group=ModelPackageGroup.create(model_package_group_name=\"model-package-group-nova13\")\n",
+    "model_package_group=ModelPackageGroup.get(model_package_group_name=\"model-package-group-nova13\")\n",
+    "print(model_package_group)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
+   "source": [
+    "\n",
+    "import json\n",
+    "import re\n",
+    "from sagemaker.core.utils.utils import Unassigned\n",
+    "\n",
+    "def pretty_print(obj):\n",
+    "    def parse_unassigned(item):\n",
+    "        if isinstance(item, Unassigned):\n",
+    "            return None\n",
+    "        if isinstance(item, dict):\n",
+    "            return {k: parse_unassigned(v) for k, v in item.items() if parse_unassigned(v) is not None}\n",
+    "        if isinstance(item, list):\n",
+    "            return [parse_unassigned(x) for x in item if parse_unassigned(x) is not None]\n",
+    "        if isinstance(item, str) and \"Unassigned object\" in item:\n",
+    "            pairs = re.findall(r\"(\\w+)=([^<][^=]*?)(?=\\s+\\w+=|$)\", item)\n",
+    "            result = {k: v.strip(\"'\\\"\") for k, v in pairs}\n",
+    "            return result if result else None\n",
+    "        return item\n",
+    "\n",
+    "    cleaned = parse_unassigned(obj.__dict__ if hasattr(obj, '__dict__') else obj)\n",
+    "    print(json.dumps(cleaned, indent=2, default=str))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\n",
+      "  \"training_job_name\": \"nova-textgeneration-micro-sft-20260302144611\",\n",
+      "  \"training_job_arn\": \"arn:aws:sagemaker:us-east-1:529088288990:training-job/nova-textgeneration-micro-sft-20260302144611\",\n",
+      "  \"model_artifacts\": \"s3_model_artifacts='s3://sagemaker-us-east-1-529088288990/output/nova-textgeneration-micro-sft-20260302144611/output/model'\",\n",
+      "  \"training_job_output\": \"s3_training_job_output='s3://sagemaker-us-east-1-529088288990/output/nova-textgeneration-micro-sft-20260302144611/output/output'\",\n",
+      "  \"training_job_status\": \"Completed\",\n",
+      "  \"secondary_status\": \"Completed\",\n",
+      "  \"hyper_parameters\": {\n",
+      "    \"global_batch_size\": \"64\",\n",
+      "    \"learning_rate\": \"1e-05\",\n",
+      "    \"learning_rate_ratio\": \"16.0\",\n",
+      "    \"lora_alpha\": \"128\",\n",
+      "    \"max_context_length\": \"8192\",\n",
+      "    \"max_epochs\": \"2\",\n",
+      "    \"name\": \"my-lora-run-wkxk5\"\n",
+      "  },\n",
+      "  \"role_arn\": \"arn:aws:iam::529088288990:role/Admin\",\n",
+      "  \"input_data_config\": [\n",
+      "    \"channel_name='train' data_source=DataSource(s3_data_source=Unassigned(), file_system_data_source=Unassigned(), dataset_source=DatasetSource(dataset_arn='arn:aws:sagemaker:us-east-1:529088288990:hub-content/G82247CBEQ6TN0FI3J1SAJU59UURMT3H3EKG48C6VQGDINNRNGU0/DataSet/demo-1/5.0.0')) content_type=Unassigned() compression_type='None' record_wrapper_type='None' input_mode=Unassigned() shuffle_config=Unassigned() enable_ffm=False\"\n",
+      "  ],\n",
+      "  \"output_data_config\": \"s3_output_path='s3://sagemaker-us-east-1-529088288990/output/' kms_key_id='' compression_type='NONE' remove_job_name_from_s3_output_path=False disable_model_upload=False channels=Unassigned()\",\n",
+      "  \"stopping_condition\": \"max_runtime_in_seconds=86400 max_wait_time_in_seconds=Unassigned() max_pending_time_in_seconds=Unassigned()\",\n",
+      "  \"creation_time\": \"2026-03-02 14:46:12.873000-08:00\",\n",
+      "  \"training_start_time\": \"2026-03-02 14:58:59.629000-08:00\",\n",
+      "  \"training_end_time\": \"2026-03-02 15:22:26.851000-08:00\",\n",
+      "  \"last_modified_time\": \"2026-03-02 15:22:26.851000-08:00\",\n",
+      "  \"secondary_status_transitions\": [\n",
+      "    \"status='Starting' start_time=datetime.datetime(2026, 3, 2, 14, 46, 12, 873000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 14, 46, 14, 829000, tzinfo=tzlocal()) status_message='Starting the training job'\",\n",
+      "    \"status='Pending' start_time=datetime.datetime(2026, 3, 2, 14, 46, 14, 829000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 14, 58, 59, 629000, tzinfo=tzlocal()) status_message='Preparing the instances for training'\",\n",
+      "    \"status='Downloading' start_time=datetime.datetime(2026, 3, 2, 14, 58, 59, 629000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 15, 7, 4, 705000, tzinfo=tzlocal()) status_message='Downloading the training image'\",\n",
+      "    \"status='Training' start_time=datetime.datetime(2026, 3, 2, 15, 7, 4, 705000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 15, 21, 2, 752000, tzinfo=tzlocal()) status_message='Training image download completed. Training in progress.'\",\n",
+      "    \"status='Uploading' start_time=datetime.datetime(2026, 3, 2, 15, 21, 2, 752000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 15, 22, 26, 851000, tzinfo=tzlocal()) status_message='Uploading generated training model'\",\n",
+      "    \"status='Completed' start_time=datetime.datetime(2026, 3, 2, 15, 22, 26, 851000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 15, 22, 26, 851000, tzinfo=tzlocal()) status_message='Training job completed'\"\n",
+      "  ],\n",
+      "  \"enable_network_isolation\": false,\n",
+      "  \"enable_inter_container_traffic_encryption\": false,\n",
+      "  \"enable_managed_spot_training\": false,\n",
+      "  \"training_time_in_seconds\": 1407,\n",
+      "  \"billable_time_in_seconds\": 0,\n",
+      "  \"billable_token_count\": 153604,\n",
+      "  \"disable_efa\": false,\n",
+      "  \"image_metadata\": \"image_type='BYOImage'\",\n",
+      "  \"serverless_job_config\": \"base_model_arn='arn:aws:sagemaker:us-east-1:aws:hub-content/SageMakerPublicHub/Model/nova-textgeneration-micro/2.45.1' job_type='FineTuning' accept_eula=True customization_technique='SFT' peft='LORA' evaluation_type=Unassigned() evaluator_arn=Unassigned() job_spec=Unassigned()\",\n",
+      "  \"mlflow_config\": \"mlflow_resource_arn='arn:aws:sagemaker:us-east-1:529088288990:mlflow-app/app-2SV6Q35HTCBO' mlflow_tracking_server_arn=Unassigned() mlflow_experiment_name='test-finetuned-models-exp' mlflow_run_name='test-finetuned-models-run'\",\n",
+      "  \"model_package_config\": \"model_package_group_arn='arn:aws:sagemaker:us-east-1:529088288990:model-package-group/model-package-group-nova6' source_model_package_arn=Unassigned()\",\n",
+      "  \"mlflow_details\": \"mlflow_experiment_id='2' mlflow_run_id='1f13027c62db4ac198a7d8452a682d5d'\",\n",
+      "  \"progress_info\": \"total_step_count_per_epoch=1 current_step=1 current_epoch=2 max_epoch=2\",\n",
+      "  \"output_model_package_arn\": \"arn:aws:sagemaker:us-east-1:529088288990:model-package/model-package-group-nova6/1\"\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sagemaker.core.resources import TrainingJob\n",
+    "\n",
+    "response = TrainingJob.get(training_job_name=\"nova-textgeneration-micro-sft-20260302144611\")\n",
+    "pretty_print(response)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "sagemaker.config INFO - Not applying SDK defaults from location: /Library/Application Support/sagemaker/config.yaml\n",
+      "sagemaker.config INFO - Not applying SDK defaults from location: /Users/mollyhe/Library/Application Support/sagemaker/config.yaml\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "
BenchMarkEvaluator(\n",
+       "│   region=None,\n",
+       "│   sagemaker_session=<sagemaker.core.helper.session_helper.Session object at 0x17252afe0>,\n",
+       "│   model='arn:aws:sagemaker:us-east-1:529088288990:model-package/model-package-group-nova6/1',\n",
+       "│   base_eval_name='gpqa-eval-demo',\n",
+       "│   s3_output_path='s3://sagemaker-us-east-1-529088288990/eval',\n",
+       "│   mlflow_resource_arn='arn:aws:sagemaker:us-east-1:529088288990:mlflow-app/app-2SV6Q35HTCBO',\n",
+       "│   mlflow_experiment_name='test-eval-models-exp',\n",
+       "│   mlflow_run_name=None,\n",
+       "│   networking=None,\n",
+       "│   kms_key_id=None,\n",
+       "│   model_package_group='arn:aws:sagemaker:us-east-1:529088288990:model-package-group/model-package-group-nova13',\n",
+       "│   benchmark=<_Benchmark.GPQA: 'gpqa'>,\n",
+       "│   subtasks=None,\n",
+       "│   evaluate_base_model=False\n",
+       ")\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[1;38;2;225;0;225mBenchMarkEvaluator\u001b[0m\u001b[1m(\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mregion\u001b[0m=\u001b[3;38;2;225;0;225mNone\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0msagemaker_session\u001b[0m=\u001b[1m<\u001b[0m\u001b[1;38;2;225;0;225msagemaker.core.helper.session_helper.Session\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x17252afe0\u001b[0m\u001b[39m>,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mmodel\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m'arn:aws:sagemaker:us-east-1:529088288990:model-package/model-package-group-nova6/1'\u001b[0m\u001b[39m,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mbase_eval_name\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m'gpqa-eval-demo'\u001b[0m\u001b[39m,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0ms3_output_path\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m's3://sagemaker-us-east-1-529088288990/eval'\u001b[0m\u001b[39m,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mmlflow_resource_arn\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m'arn:aws:sagemaker:us-east-1:529088288990:mlflow-app/app-2SV6Q35HTCBO'\u001b[0m\u001b[39m,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mmlflow_experiment_name\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m'test-eval-models-exp'\u001b[0m\u001b[39m,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mmlflow_run_name\u001b[0m\u001b[39m=\u001b[0m\u001b[3;38;2;225;0;225mNone\u001b[0m\u001b[39m,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mnetworking\u001b[0m\u001b[39m=\u001b[0m\u001b[3;38;2;225;0;225mNone\u001b[0m\u001b[39m,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mkms_key_id\u001b[0m\u001b[39m=\u001b[0m\u001b[3;38;2;225;0;225mNone\u001b[0m\u001b[39m,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mmodel_package_group\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m'arn:aws:sagemaker:us-east-1:529088288990:model-package-group/model-package-group-nova13'\u001b[0m\u001b[39m,\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mbenchmark\u001b[0m\u001b[39m=<_Benchmark.GPQA: \u001b[0m\u001b[38;2;0;135;0m'gpqa'\u001b[0m\u001b[1m>\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0msubtasks\u001b[0m=\u001b[3;38;2;225;0;225mNone\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mevaluate_base_model\u001b[0m=\u001b[3;38;2;215;0;0mFalse\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "from sagemaker.train.evaluate import BenchMarkEvaluator\n",
     "\n",
     "# Create evaluator with GEN_QA benchmark\n",
     "# These values match our successfully tested configuration\n",
     "evaluator = BenchMarkEvaluator(\n",
-    "    benchmark=Benchmark.GEN_QA,\n",
-    "    model=\"arn:aws:sagemaker:us-west-2:052150106756:model-package/test-finetuned-models-gamma/28\",\n",
-    "    s3_output_path=\"s3://mufi-test-serverless-smtj/eval/\",\n",
-    "    mlflow_resource_arn=\"arn:aws:sagemaker:us-west-2:052150106756:mlflow-tracking-server/mmlu-eval-experiment\",\n",
-    "    dataset=\"s3://sagemaker-us-west-2-052150106756/studio-users/d20251107t195443/datasets/2025-11-07T19-55-37-609Z/zc_test.jsonl\",\n",
-    "    model_package_group=\"arn:aws:sagemaker:us-west-2:052150106756:model-package-group/example-name-aovqo\", # Optional inferred from model if model package\n",
-    "    base_eval_name=\"gen-qa-eval-demo\",\n",
+    "    benchmark=Benchmark.GPQA,\n",
+    "    model=\"arn:aws:sagemaker:us-east-1:529088288990:model-package/model-package-group-nova6/1\",\n",
+    "    s3_output_path=\"s3://sagemaker-us-east-1-529088288990/eval\",\n",
+    "    mlflow_experiment_name=\"test-eval-models-exp\", \n",
+    "    # mlflow_resource_arn=\"arn:aws:sagemaker:us-west-2:052150106756:mlflow-tracking-server/mmlu-eval-experiment\",\n",
+    "    dataset=\"s3://sagemaker-us-east-1-529088288990/eval.jsonl\",\n",
+    "    model_package_group=\"arn:aws:sagemaker:us-east-1:529088288990:model-package-group/model-package-group-nova13\", # Optional inferred from model if model package\n",
+    "    base_eval_name=\"gpqa-eval-demo\",\n",
     "    # Note: sagemaker_session is optional and will be auto-created if not provided\n",
     "    # Note: region is optional and will be auto deduced using environment variables - SAGEMAKER_REGION, AWS_REGION\n",
     ")\n",
@@ -92,7 +341,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -119,7 +368,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -155,9 +404,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
{'max_new_tokens': '8196', 'temperature': '0', 'top_k': '-1', 'top_p': '1.0'}\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\u001b[38;2;0;135;0m'max_new_tokens'\u001b[0m: \u001b[38;2;0;135;0m'8196'\u001b[0m, \u001b[38;2;0;135;0m'temperature'\u001b[0m: \u001b[38;2;0;135;0m'0'\u001b[0m, \u001b[38;2;0;135;0m'top_k'\u001b[0m: \u001b[38;2;0;135;0m'-1'\u001b[0m, \u001b[38;2;0;135;0m'top_p'\u001b[0m: \u001b[38;2;0;135;0m'1.0'\u001b[0m\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "pprint(evaluator.hyperparameters.to_dict())\n",
     "\n",
@@ -188,9 +451,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
BenchmarkEvaluationExecution(\n",
+       "│   arn='arn:aws:sagemaker:us-east-1:529088288990:pipeline/SagemakerEvaluation-BenchmarkEvaluation-d47edc79-1d45-4b8f-9ff6-df8e2c8c92be/execution/ab0k65fkztid',\n",
+       "│   name='gpqa-eval-demo',\n",
+       "│   status=PipelineExecutionStatus(overall_status='Executing', step_details=[], failure_reason=None),\n",
+       "│   last_modified_time=datetime.datetime(2026, 3, 10, 17, 48, 10, 308000, tzinfo=tzlocal()),\n",
+       "│   eval_type=<EvalType.BENCHMARK: 'benchmark'>,\n",
+       "│   s3_output_path='s3://sagemaker-us-east-1-529088288990/eval',\n",
+       "│   steps=[]\n",
+       ")\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[1;38;2;225;0;225mBenchmarkEvaluationExecution\u001b[0m\u001b[1m(\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0marn\u001b[0m=\u001b[38;2;0;135;0m'arn:aws:sagemaker:us-east-1:529088288990:pipeline/SagemakerEvaluation-BenchmarkEvaluation-d47edc79-1d45-4b8f-9ff6-df8e2c8c92be/execution/ab0k65fkztid'\u001b[0m,\n",
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+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mstatus\u001b[0m=\u001b[1;38;2;225;0;225mPipelineExecutionStatus\u001b[0m\u001b[1m(\u001b[0m\u001b[38;2;215;175;0moverall_status\u001b[0m=\u001b[38;2;0;135;0m'Executing'\u001b[0m, \u001b[38;2;215;175;0mstep_details\u001b[0m=\u001b[1m[\u001b[0m\u001b[1m]\u001b[0m, \u001b[38;2;215;175;0mfailure_reason\u001b[0m=\u001b[3;38;2;225;0;225mNone\u001b[0m\u001b[1m)\u001b[0m,\n",
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+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0msteps\u001b[0m=\u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
+       "\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Pipeline Execution ARN: arn:aws:sagemaker:us-east-1:529088288990:pipeline/SagemakerEvaluation-BenchmarkEvaluation-d47edc79-1d45-4b8f-9ff6-df8e2c8c92be/execution/ab0k65fkztid\n",
+      "Initial Status: Executing\n"
+     ]
+    }
+   ],
    "source": [
     "# Run evaluation with configured parameters\n",
     "execution = evaluator.evaluate()\n",
@@ -211,7 +513,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -231,9 +533,79 @@
   },
   {
    "cell_type": "code",
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    "metadata": {},
-   "outputs": [],
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+       "\u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[1m]\u001b[0m,\n",
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+       "\u001b[1m)\u001b[0m\n"
+      ]
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+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Step Details:\n",
+      "  CreateEvaluationAction: Starting\n",
+      "  EvaluateCustomModel: Starting\n"
+     ]
+    }
+   ],
    "source": [
     "# Refresh status\n",
     "execution.refresh()\n",
@@ -259,9 +631,128 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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╭─────────────────────────────────────────── Pipeline Execution Status ───────────────────────────────────────────╮\n",
+       "│  Overall Status        Executing                                                                                │\n",
+       "│  Target Status         Succeeded                                                                                │\n",
+       "│  Elapsed Time          33.4s                                                                                    │\n",
+       "│                                                                                                                 │\n",
+       "│ Pipeline Steps                                                                                                  │\n",
+       "│  Step Name                       Status           Duration                                                      │\n",
+       "│  CreateEvaluationAction          Succeeded        1.1s                                                          │\n",
+       "│  EvaluateCustomModel             Executing        Running...                                                    │\n",
+       "│                                                                                                                 │\n",
+       "│ Job ARNs                                                                                                        │\n",
+       "│  Step                  Job Link      Job ARN                                                                    │\n",
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+       "│                                      tid-EvaluateCustomModel-5XaO1EW1hQ                                         │\n",
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+       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
+       "\u001b[34m│\u001b[0m \u001b[1;35mJob ARNs\u001b[0m                                                                                                        \u001b[34m│\u001b[0m\n",
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+       "\u001b[34m│\u001b[0m \u001b[36m \u001b[0m\u001b[36mEvaluateCustomModel \u001b[0m\u001b[36m \u001b[0m \u001b]8;id=840181;https://studio-d-ingyyaeglvki.studio.us-east-1.sagemaker.aws/jobs/train/pipelines-ab0k65fkztid-EvaluateCustomModel-5XaO1EW1hQ\u001b\\🔗 link\u001b]8;;\u001b\\      \u001b[2m \u001b[0m\u001b[2marn:aws:sagemaker:us-east-1:529088288990:training-job/pipelines-ab0k65fkz\u001b[0m\u001b[2m \u001b[0m \u001b[34m│\u001b[0m\n",
+       "\u001b[34m│\u001b[0m \u001b[36m                      \u001b[0m              \u001b[2m \u001b[0m\u001b[2mtid-EvaluateCustomModel-5XaO1EW1hQ                                       \u001b[0m\u001b[2m \u001b[0m \u001b[34m│\u001b[0m\n",
+       "\u001b[34m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
+      ]
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╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮\n",
+       "│ in <module>:3                                                                                    │\n",
+       "│                                                                                                  │\n",
+       "│   1 # Wait for job completion with progress updates                                              │\n",
+       "│   2 # This will show a rich progress display in Jupyter                                          │\n",
+       "│ ❱ 3 execution.wait(target_status=\"Succeeded\", poll=5, timeout=3600)                              │\n",
+       "│   4                                                                                              │\n",
+       "│   5 print(f\"\\nFinal Status: {execution.status.overall_status}\")                                  │\n",
+       "│   6                                                                                              │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk/sagemaker-core/src/sagemaker/core/teleme │\n",
+       "│ try/telemetry_logging.py:180 in wrapper                                                          │\n",
+       "│                                                                                                  │\n",
+       "│   177 │   │   │   │   │   \"sagemaker_session is not provided or not valid.\",                     │\n",
+       "│   178 │   │   │   │   │   func_name,                                                             │\n",
+       "│   179 │   │   │   │   )                                                                          │\n",
+       "│ ❱ 180 │   │   │   │   return func(*args, **kwargs)                                               │\n",
+       "│   181 │   │                                                                                      │\n",
+       "│   182 │   │   return wrapper                                                                     │\n",
+       "│   183                                                                                            │\n",
+       "│                                                                                                  │\n",
+       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai │\n",
+       "│ n/evaluate/execution.py:1061 in wait                                                             │\n",
+       "│                                                                                                  │\n",
+       "│   1058 │   │   │   │   │   │   status=current_status                                             │\n",
+       "│   1059 │   │   │   │   │   )                                                                     │\n",
+       "│   1060 │   │   │   │                                                                             │\n",
+       "│ ❱ 1061 │   │   │   │   time.sleep(poll)                                                          │\n",
+       "│   1062 │   │   else:                                                                             │\n",
+       "│   1063 │   │   │   # Terminal experience with rich library                                       │\n",
+       "│   1064 │   │   │   try:                                                                          │\n",
+       "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
+       "KeyboardInterrupt\n",
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+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m3 execution.wait(target_status=\u001b[33m\"\u001b[0m\u001b[33mSucceeded\u001b[0m\u001b[33m\"\u001b[0m, poll=\u001b[94m5\u001b[0m, timeout=\u001b[94m3600\u001b[0m)                              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m4 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m5 \u001b[0m\u001b[96mprint\u001b[0m(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m\\n\u001b[0m\u001b[33mFinal Status: \u001b[0m\u001b[33m{\u001b[0mexecution.status.overall_status\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m)                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m6 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk/sagemaker-core/src/sagemaker/core/teleme\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mtry/\u001b[0m\u001b[1;33mtelemetry_logging.py\u001b[0m:\u001b[94m180\u001b[0m in \u001b[92mwrapper\u001b[0m                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m177 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[33m\"\u001b[0m\u001b[33msagemaker_session is not provided or not valid.\u001b[0m\u001b[33m\"\u001b[0m,                     \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m178 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mfunc_name,                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m179 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m)                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m180 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m func(*args, **kwargs)                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m181 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m182 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m wrapper                                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m183 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mn/evaluate/\u001b[0m\u001b[1;33mexecution.py\u001b[0m:\u001b[94m1061\u001b[0m in \u001b[92mwait\u001b[0m                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1058 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0mstatus=current_status                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1059 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m)                                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1060 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m1061 \u001b[2m│   │   │   │   \u001b[0mtime.sleep(poll)                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1062 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1063 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# Terminal experience with rich library\u001b[0m                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1064 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
+       "\u001b[1;91mKeyboardInterrupt\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Wait for job completion with progress updates\n",
     "# This will show a rich progress display in Jupyter\n",
@@ -338,13 +829,13 @@
     "\n",
     "# Get an existing job by ARN\n",
     "# Replace with your actual pipeline execution ARN\n",
-    "existing_arn = \"arn:aws:sagemaker:us-west-2:052150106756:pipeline/SagemakerEvaluation-BenchmarkEvaluation-c344c91d-6f62-4907-85cc-7e6b29171c42/execution/inlsexrd7jes\"\n",
+    "existing_arn = \"arn:aws:sagemaker:us-east-1:529088288990:pipeline/SagemakerEvaluation-BenchmarkEvaluation-d47edc79-1d45-4b8f-9ff6-df8e2c8c92be/execution/bhtdxm5tenya\"\n",
     "\n",
     "# base model only example\n",
     "# existing_arn = \"arn:aws:sagemaker:us-west-2:052150106756:pipeline/SagemakerEvaluation-benchmark/execution/gdp9f4dbv2vi\"\n",
     "existing_execution = EvaluationPipelineExecution.get(\n",
     "    arn=existing_arn,\n",
-    "    region=\"us-west-2\"\n",
+    "    region=\"us-east-1\"\n",
     ")\n",
     "\n",
     "pprint(existing_execution)\n",
@@ -442,7 +933,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "py3.10.14",
    "language": "python",
    "name": "python3"
   },
@@ -456,7 +947,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.10.14"
   }
  },
  "nbformat": 4,
diff --git a/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py b/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
index 0b617601e2..2b48149871 100644
--- a/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
+++ b/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
@@ -8,25 +8,40 @@
 logger = logging.getLogger(__name__)
 
 
-def get_studio_url(training_job: TrainingJob, domain_id: str = None) -> str:
+def get_studio_url(training_job, domain_id: str = None) -> str:
     """Get SageMaker Studio URL for training job logs.
     
     Args:
-        training_job: SageMaker TrainingJob object or job name string
+        training_job: SageMaker TrainingJob object, job name string, or job ARN string
         domain_id: Studio domain ID (e.g., 'd-xxxxxxxxxxxx'). If not provided, attempts to auto-detect
         
     Returns:
-        Studio URL pointing to the training job details
+        Studio URL pointing to the training job details, or empty string if not resolvable
         
     Example:
         >>> from sagemaker.train import get_studio_url
         >>> url = get_studio_url('my-training-job')
+        >>> url = get_studio_url('arn:aws:sagemaker:us-east-1:123456789:training-job/my-job')
     """
+    import re
+
+    # Handle ARN string — extract region and job name directly
     if isinstance(training_job, str):
-        training_job = TrainingJob.get(training_job_name=training_job)
-    
-    region = training_job.region if hasattr(training_job, 'region') and training_job.region else 'us-east-1'
-    job_name = training_job.training_job_name
+        arn_match = re.match(
+            r'arn:aws(?:-[a-z]+)?:sagemaker:([a-z0-9-]+):\d+:training-job/(.+)',
+            training_job,
+        )
+        if arn_match:
+            region = arn_match.group(1)
+            job_name = arn_match.group(2)
+        else:
+            # Treat as job name, need to fetch the object
+            training_job = TrainingJob.get(training_job_name=training_job)
+            region = training_job.region if hasattr(training_job, 'region') and training_job.region else 'us-east-1'
+            job_name = training_job.training_job_name
+    else:
+        region = training_job.region if hasattr(training_job, 'region') and training_job.region else 'us-east-1'
+        job_name = training_job.training_job_name
     
     sm_client = boto3.client('sagemaker', region_name=region)
     
@@ -40,13 +55,82 @@ def get_studio_url(training_job: TrainingJob, domain_id: str = None) -> str:
             pass
     
     if not domain_id:
-        # Fallback to console URL
-        return f"https://{region}.console.aws.amazon.com/sagemaker/home?region={region}#/jobs/{job_name}"
+        return ""
     
     # Studio URL format: https://studio-{domain_id}.studio.{region}.sagemaker.aws/jobs/train/{job_name}
     return f"https://studio-{domain_id}.studio.{region}.sagemaker.aws/jobs/train/{job_name}"
 
 
+def display_job_links_html(rows: list, as_html: bool = False):
+    """Render job/resource links with copy-to-clipboard buttons as a Jupyter HTML table.
+
+    Args:
+        rows: List of dicts, each with keys:
+            - label (str): Row label (e.g. step name, "Training Job", "MLflow Experiment")
+            - arn (str): The ARN or URI to display and copy
+            - url (Optional[str]): Clickable link URL. If None, resolved via get_studio_url for job ARNs.
+            - url_text (Optional[str]): Link display text. Defaults to "🔗 link"
+            - url_hint (Optional[str]): Hint text after link. Defaults to "(please sign in to Studio first)"
+        as_html: If True, return HTML object instead of displaying it.
+
+    Returns:
+        HTML object if as_html=True, otherwise None.
+    """
+    from IPython.display import display, HTML
+    import html as html_mod
+
+    html_rows = ""
+    for row in rows:
+        escaped_arn = html_mod.escape(row['arn'])
+        escaped_label = html_mod.escape(row['label'])
+
+        url = row.get('url')
+        if url is None:
+            url = get_studio_url(row['arn'])
+        url_text = row.get('url_text', '🔗 link')
+        url_hint = row.get('url_hint', '(please sign in to Studio first)')
+
+        link_html = ""
+        if url:
+            link_html = (
+                f'{html_mod.escape(url_text)}'
+                f' {html_mod.escape(url_hint)}'
+            )
+
+        copy_btn = (
+            f''
+        )
+
+        html_rows += (
+            f''
+            f'{escaped_label}'
+            f'{link_html}'
+            f''
+            f'{escaped_arn}'
+            f' {copy_btn}'
+            f''
+        )
+
+    result = HTML(
+        f''
+        f''
+        f''
+        f''
+        f''
+        f'{html_rows}
StepJob LinkJob ARN
'
+    )
+
+    if as_html:
+        return result
+    display(result)
+
+
 def plot_training_metrics(
     training_job: TrainingJob,
     metrics: Optional[List[str]] = None,
diff --git a/sagemaker-train/src/sagemaker/train/evaluate/execution.py b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
index e2388ef313..38dc63b4ec 100644
--- a/sagemaker-train/src/sagemaker/train/evaluate/execution.py
+++ b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
@@ -447,6 +447,7 @@ class StepDetail(BaseModel):
     end_time: Optional[str] = Field(None, description="Step end time")
     display_name: Optional[str] = Field(None, description="Display name for the step")
     failure_reason: Optional[str] = Field(None, description="Reason for failure if step failed")
+    job_arn: Optional[str] = Field(None, description="ARN of the underlying job (training, processing, transform, etc.)")
 
 
 class PipelineExecutionStatus(BaseModel):
@@ -938,7 +939,6 @@ def wait(
                 
                 # Create steps table if steps exist
                 if self.status.step_details:
-                    # Check if any step has a failure
                     has_failures = any(step.failure_reason for step in self.status.step_details)
                     
                     steps_table = Table(show_header=True, header_style="bold magenta", box=None, padding=(0, 1))
@@ -946,10 +946,10 @@ def wait(
                     steps_table.add_column("Status", style="yellow", width=15)
                     steps_table.add_column("Duration", style="green", width=12)
                     
-                    failed_steps = []  # Track steps with failures for detailed display
+                    failed_steps = []
+                    job_arn_entries = []
                     
                     for step in self.status.step_details:
-                        # Calculate duration if both times are available
                         duration = ""
                         if step.start_time and step.end_time:
                             try:
@@ -963,7 +963,6 @@ def wait(
                         elif step.start_time:
                             duration = "Running..."
                         
-                        # Color code status
                         status_display = step.status
                         if "succeeded" in step.status.lower() or "completed" in step.status.lower():
                             status_display = f"[green]{step.status}[/green]"
@@ -972,14 +971,18 @@ def wait(
                         elif "executing" in step.status.lower() or "running" in step.status.lower():
                             status_display = f"[yellow]{step.status}[/yellow]"
                         
-                        # Build row data
+                        if step.job_arn:
+                            job_arn_entries.append({
+                                'step_name': step.display_name or step.name,
+                                'job_arn': step.job_arn,
+                            })
+                        
                         row_data = [
                             step.display_name or step.name,
                             status_display,
                             duration
                         ]
                         
-                        # Add error indicator if failures exist
                         if has_failures:
                             if step.failure_reason:
                                 row_data.append("❌")
@@ -989,35 +992,47 @@ def wait(
                         
                         steps_table.add_row(*row_data)
                     
-                    # Build combined content
                     from rich.console import Group
                     content_parts = [
                         status_table,
-                        Text(""),  # Empty line for spacing
+                        Text(""),
                         Text("Pipeline Steps", style="bold magenta"),
                         steps_table
                     ]
                     
-                    # Add failure details section if there are any failures
                     if failed_steps:
-                        content_parts.append(Text(""))  # Empty line
+                        content_parts.append(Text(""))
                         content_parts.append(Text("Step Failure Details", style="bold red"))
                         
                         for step in failed_steps:
-                            content_parts.append(Text(""))  # Empty line before each failure
+                            content_parts.append(Text(""))
                             content_parts.append(Text(f"• {step.display_name or step.name}:", style="bold red"))
                             content_parts.append(Text(f"  {step.failure_reason}", style="red"))
                     
-                    combined_content = Group(*content_parts)
+                    # Add job links table if any steps have ARNs
+                    if job_arn_entries:
+                        links_table = Table(show_header=True, header_style="bold magenta", box=None, padding=(0, 1))
+                        links_table.add_column("Step", style="cyan", width=20)
+                        links_table.add_column("Job Link", width=12)
+                        links_table.add_column("Job ARN", style="dim", overflow="fold")
+                        for entry in job_arn_entries:
+                            try:
+                                from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
+                                url = get_studio_url(entry['job_arn'])
+                                link_col = f"[link={url}]🔗 link[/link]" if url else ""
+                            except Exception:
+                                link_col = ""
+                            links_table.add_row(entry['step_name'], link_col, entry['job_arn'])
+                        content_parts.append(Text(""))
+                        content_parts.append(Text("Job ARNs", style="bold magenta"))
+                        content_parts.append(links_table)
                     
-                    # Display combined content in a single panel
                     console.print(Panel(
-                        combined_content,
+                        Group(*content_parts),
                         title="[bold blue]Pipeline Execution Status[/bold blue]",
                         border_style="blue"
                     ))
                 else:
-                    # Display only status table if no steps
                     console.print(Panel(
                         status_table,
                         title="[bold blue]Pipeline Execution Status[/bold blue]",
@@ -1204,7 +1219,22 @@ def _convert_to_subclass(self, eval_type: EvalType) -> 'EvaluationPipelineExecut
         execution._pipeline_execution = pipeline_execution_ref
         
         return execution
-    
+
+    @staticmethod
+    def _extract_job_arn_from_metadata(step) -> Optional[str]:
+        """Extract the underlying job ARN from a pipeline step's metadata."""
+        metadata = getattr(step, 'metadata', None)
+        if metadata is None or 'Unassigned' in metadata.__class__.__name__:
+            return None
+        for attr in ('training_job', 'processing_job', 'transform_job', 'tuning_job',
+                     'auto_ml_job', 'compilation_job'):
+            job_meta = getattr(metadata, attr, None)
+            if job_meta is not None and not ('Unassigned' in job_meta.__class__.__name__):
+                arn = getattr(job_meta, 'arn', None)
+                if arn and not ('Unassigned' in arn.__class__.__name__):
+                    return str(arn)
+        return None
+
     def _update_step_details_from_raw_steps(self, raw_steps: List[Any]) -> None:
         """Internal method to update step_details from raw pipeline execution steps
         
@@ -1246,7 +1276,8 @@ def _update_step_details_from_raw_steps(self, raw_steps: List[Any]) -> None:
                     start_time=start_time,
                     end_time=end_time,
                     display_name=step_display_name,
-                    failure_reason=failure_reason
+                    failure_reason=failure_reason,
+                    job_arn=self._extract_job_arn_from_metadata(step)
                 )
                 
                 step_details.append(step_detail)
@@ -1256,8 +1287,8 @@ def _update_step_details_from_raw_steps(self, raw_steps: List[Any]) -> None:
                 logger.warning(f"Failed to process pipeline step: {str(e)}")
                 continue
         
-        # Update the job's step details
-        self.status.step_details = step_details
+        # Update the job's step details (reverse so earliest step appears first)
+        self.status.step_details = list(reversed(step_details))
 
 
 # ============================================================================
diff --git a/sagemaker-train/src/sagemaker/train/evaluate/pipeline_templates.py b/sagemaker-train/src/sagemaker/train/evaluate/pipeline_templates.py
index b14145ff31..9112856ce6 100644
--- a/sagemaker-train/src/sagemaker/train/evaluate/pipeline_templates.py
+++ b/sagemaker-train/src/sagemaker/train/evaluate/pipeline_templates.py
@@ -11,8 +11,7 @@
     "Metadata": {},
     "MlflowConfig": {
         "MlflowResourceArn": "{{ mlflow_resource_arn }}"{% if mlflow_experiment_name %},
-        "MlflowExperimentName": "{{ mlflow_experiment_name }}"{% endif %}{% if mlflow_run_name %},
-        "MlflowRunName": "{{ mlflow_run_name }}"{% endif %}
+        "MlflowExperimentName": "{{ mlflow_experiment_name }}"{% endif %}
     },
     "Parameters": [],
     "Steps": [
@@ -531,8 +530,7 @@
     "Metadata": {},
     "MlflowConfig": {
         "MlflowResourceArn": "{{ mlflow_resource_arn }}"{% if mlflow_experiment_name %},
-        "MlflowExperimentName": "{{ mlflow_experiment_name }}"{% endif %}{% if mlflow_run_name %},
-        "MlflowRunName": "{{ mlflow_run_name }}"{% endif %}
+        "MlflowExperimentName": "{{ mlflow_experiment_name }}"{% endif %}
     },
     "Parameters": [],
     "Steps": [
@@ -925,8 +923,7 @@
     "Metadata": {},
     "MlflowConfig": {
         "MlflowResourceArn": "{{ mlflow_resource_arn }}"{% if mlflow_experiment_name %},
-        "MlflowExperimentName": "{{ mlflow_experiment_name }}"{% endif %}{% if mlflow_run_name %},
-        "MlflowRunName": "{{ mlflow_run_name }}"{% endif %}
+        "MlflowExperimentName": "{{ mlflow_experiment_name }}"{% endif %}
     },
     "Parameters": [],
     "Steps": [
diff --git a/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb b/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb
index 887f60a3d9..7b4348d0e4 100644
--- a/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb
+++ b/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb
@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "87aa2004556ad7c6",
    "metadata": {},
    "outputs": [],
@@ -35,7 +35,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "id": "989646bf",
    "metadata": {},
    "outputs": [],
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "a51be0b5-fd33-4fa0-af2b-d08ce0dc7a8e",
    "metadata": {},
    "outputs": [
@@ -96,14 +96,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "ef4f0e61-de4d-4228-b7a1-ea7497dad547",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b7310bb3f485478f905417b421e7ae11",
+       "model_id": "e98bb5da0450400ab462efafe4fd3bb8",
        "version_major": 2,
        "version_minor": 0
       },
@@ -141,7 +141,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Dataset ARN: arn:aws:sagemaker:us-east-1:529088288990:hub-content/G82247CBEQ6TN0FI3J1SAJU59UURMT3H3EKG48C6VQGDINNRNGU0/DataSet/demo-1/28.0.0\n"
+      "Dataset ARN: arn:aws:sagemaker:us-east-1:529088288990:hub-content/G82247CBEQ6TN0FI3J1SAJU59UURMT3H3EKG48C6VQGDINNRNGU0/DataSet/demo-1/45.0.0\n"
      ]
     }
    ],
@@ -172,7 +172,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "d6937550-f721-43ff-82dd-c513c328dd17",
    "metadata": {},
    "outputs": [
@@ -224,7 +224,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "88fe8360-de50-481d-932f-564a32be66a0",
    "metadata": {},
    "outputs": [],
@@ -254,12 +254,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "de183042-bb92-4947-9acd-78d7231bda13",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Default Finetuning Options:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "
{\n",
+       "│   'name': 'my-fullrank-run-k3174',\n",
+       "│   'global_batch_size': '16',\n",
+       "│   'max_epochs': '1',\n",
+       "│   'learning_rate': '5e-06',\n",
+       "│   'max_context_length': '8192'\n",
+       "}\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[1m{\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'name'\u001b[0m: \u001b[38;2;0;135;0m'my-fullrank-run-k3174'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'global_batch_size'\u001b[0m: \u001b[38;2;0;135;0m'16'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_epochs'\u001b[0m: \u001b[38;2;0;135;0m'1'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'learning_rate'\u001b[0m: \u001b[38;2;0;135;0m'5e-06'\u001b[0m,\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_context_length'\u001b[0m: \u001b[38;2;0;135;0m'8192'\u001b[0m\n",
+       "\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "print(\"Default Finetuning Options:\")\n",
     "pprint(sft_trainer.hyperparameters.to_dict()) # rename as hyperparameters"
@@ -267,7 +300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "6b57838f-81ac-4fbe-9ddf-5588e42bcce1",
    "metadata": {
     "scrolled": true
@@ -288,7 +321,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
    "id": "4d3b6441-9abb-447b-9307-9606a8c0fabd",
    "metadata": {
     "jupyter": {
@@ -301,42 +334,50 @@
      "data": {
       "text/html": [
        "
╭────────────────────────────────── Training Job Status ───────────────────────────────────╮\n",
-       "│  TrainingJob Name      🔗 nova-textgeneration-lite-sft-20260305152839                    │\n",
+       "│  TrainingJob Name      🔗 nova-textgeneration-lite-sft-20260310173212                    │\n",
        "│  TrainingJob ARN       arn:aws:sagemaker:us-east-1:529088288990:training-job/nova-textg  │\n",
-       "│                        eneration-lite-sft-20260305152839                                 │\n",
-       "│  MLflow Experiment     🔗 test-finetuned-models-exp                                      │\n",
+       "│                        eneration-lite-sft-20260310173212                                 │\n",
+       "│  MLflow Experiment     🔗 test-finetuned-models-exp                                      │\n",
        "│                                                                                          │\n",
        "│  Job Status            InProgress                                                        │\n",
-       "│  Secondary Status      Pending                                                           │\n",
-       "│  Elapsed Time          10.3s                                                             │\n",
+       "│  Secondary Status      Training                                                          │\n",
+       "│  Elapsed Time          990.7s                                                            │\n",
        "│                                                                                          │\n",
        "│ Status Transitions                                                                       │\n",
        "│                                                                                          │\n",
        "│        Step              Details                               Duration                  │\n",
        "│  ───────────────────────────────────────────────────────────────────────────             │\n",
-       "│   ✓    Starting          Starting the training job             1.8s                      │\n",
-       "│   ⋯    Pending           Training job waiting for capacity     Running...                │\n",
+       "│   ✓    Starting          Starting the training job             4.7s                      │\n",
+       "│   ✓    Pending           Preparing the instances for           656.3s                    │\n",
+       "│                          training                                                        │\n",
+       "│   ✓    Downloading       Downloading the training image        253.4s                    │\n",
+       "│   ⋯    Training          Training image download completed.    Running...                │\n",
+       "│                          Training in progress.                                           │\n",
        "│                                                                                          │\n",
        "╰──────────────────────────────────────────────────────────────────────────────────────────╯\n",
        "
\n"
       ],
       "text/plain": [
        "\u001b[38;5;172m╭─\u001b[0m\u001b[38;5;172m─────────────────────────────────\u001b[0m\u001b[38;5;172m \u001b[0m\u001b[1;94mTraining Job Status\u001b[0m\u001b[38;5;172m \u001b[0m\u001b[38;5;172m──────────────────────────────────\u001b[0m\u001b[38;5;172m─╮\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mTrainingJob Name    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b]8;id=315550;https://studio-d-ingyyaeglvki.studio.us-east-1.sagemaker.aws/jobs/train/nova-textgeneration-lite-sft-20260305152839\u001b\\\u001b[37m🔗 nova-textgeneration-lite-sft-20260305152839\u001b[0m\u001b]8;;\u001b\\\u001b[37m                  \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mTrainingJob Name    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b]8;id=225350;https://studio-d-ingyyaeglvki.studio.us-east-1.sagemaker.aws/jobs/train/nova-textgeneration-lite-sft-20260310173212\u001b\\\u001b[37m🔗 nova-textgeneration-lite-sft-20260310173212\u001b[0m\u001b]8;;\u001b\\\u001b[37m                  \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
        "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mTrainingJob ARN     \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[2;37marn:aws:sagemaker:us-east-1:529088288990:training-job/nova-textg\u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m                      \u001b[0m\u001b[37m \u001b[0m\u001b[2;37meneration-lite-sft-20260305152839\u001b[0m\u001b[37m                               \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mMLflow Experiment   \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b]8;id=794600;https://app-2SV6Q35HTCBO.mlflow.sagemaker.us-east-1.app.aws/auth?authToken=eyJhbGciOiJIUzI1NiJ9.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.X2ERSgvF5-bTlp7a-wWjG7vQiNNi9RJ-dreP8RUI4n8#/experiments/2\u001b\\\u001b[37m🔗 test-finetuned-models-exp\u001b[0m\u001b]8;;\u001b\\\u001b[37m                                    \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m                      \u001b[0m\u001b[37m \u001b[0m\u001b[2;37meneration-lite-sft-20260310173212\u001b[0m\u001b[37m                               \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mMLflow Experiment   \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b]8;id=448259;https://app-2SV6Q35HTCBO.mlflow.sagemaker.us-east-1.app.aws/auth?authToken=eyJhbGciOiJIUzI1NiJ9.eyJhdXRoVG9rZW5JZCI6IlRZTENXRiIsImZhc0NyZWRlbnRpYWxzIjoiQWdWNEs1RzV1QVRWaHc1T21BK041d1VlQkFpOGtrQVVBMWpWWjlGZFpUMjc5UFVBWHdBQkFCVmhkM010WTNKNWNIUnZMWEIxWW14cFl5MXJaWGtBUkVGeE9IRjRZa04xWm1FMmVFWnROWFJDUTJSUGIydGhVazFXYm1FNWNIUlhWM1JUSzFCdWFHVTJkMFJFYmpOWmRFVlRjbVEzTTJSMWJEZHpTelY1ZVZCdFFUMDlBQUVBQjJGM2N5MXJiWE1BUzJGeWJqcGhkM002YTIxek9uVnpMV1ZoYzNRdE1Ub3pNVFF4TkRZek1EWTBPREk2YTJWNUx6Y3dOMkpoTmpjeExUUXpZamd0TkRFeU5DMWhaVFUzTFRrMFlqTXdZbUptT1RJNU13QzRBUUlCQUhnQjRVMDBTK3ErVE51d1gydlFlaGtxQnVneWQ3YnNrb0pWdWQ2NmZjVENVd0dxdHBxTHRyRmNNVTVGNzVWampMTENBQUFBZmpCOEJna3Foa2lHOXcwQkJ3YWdiekJ0QWdFQU1HZ0dDU3FHU0liM0RRRUhBVEFlQmdsZ2hrZ0JaUU1FQVM0d0VRUU1Tek05SFM3Wjl2MkFlNnBnQWdFUWdEdEsxTkVFSm9weW96cWVtcmNEM05kUDdwcERFclplMmVFRWx2UFVhY2JzNTZnekF2USs2eWl1cmR0d0pwYjZydTBoSldweDBiQnR4ZHJqR0FJQUFCQUFzVW5xcysxdnpBV1luNFducGhQSENXb2YyamFkOHhqYWg2Zmg3OUl6Z0FEdE5lMno1eDAwUkF0OXRrRGRIWkMzLy8vLy93QUFBQUVBQUFBQUFBQUFBQUFBQUFFQUFBUkRNT01zOUUyaENlOUpCc0RraWFTMG8wam54bnYzVzVwUU5Fak15bXVsS1JtZDdlRlJTWkJKQmRRTDJ0eUdZdTNmUStQZFhjeWFNYk5FcUN6VTZaM3RPM3c3RGlIVHV6Q0gvamFJNWNjaFRIL1hIdWZsc0NpS2NwaUphMVV5MEZESVhDc2FDKzVIbVBlUmloZHNkdEFibk5LRGp3WXB6NEYwZklVc2VVSmFDTm10NkxmdjM5Ky9VTktVbU9PSXFqQWJvUllqVTh6eW9Bdnc3cUUrMVptbXA2YWtrVXcvVzBNZGJmRGtsK0U4bmFJNG5NZEtkNDVCU2hpYXR1YUpNUnhZbTd0UFRvZHdJRTdCWWVOaUd4R0thSkZiVkNmTXg1WXNqZ1VZcHlTbUF2ZzU3RTdtOGw0cWp0ZnlGVDNKT2NQaUwra3c4NWdrQ1lIclpoYnVhTzlvSzFUVS96QUxPb0dmOHlQbEN5Ym1kVFJReEE2V3ZQREROWkJFcWg5YlZUSGNOQnk2K1JPWjBOWDVMYUNtdDYxY1Y0SUZtNlFRVTFCRVBmWFhIVFhqd3ZYMEVLUXpNM2VjOTNhRHVKcWJFMldFaXl3VHE2R3dNSTR3WG9YMzUwb1NZc2VVZ2RwcWNPWFgxME1tU2dtQUtuUnZrQkc5NElyUzNTV1BIZ0NKb3A3K3pxNVlIZE1EcXVpR04zVlJhWHZDRFlRK0dQRHlOWFBnc0NsZE9rdWdPWmdVV0FVNTloOHp2VGJlOGY2ZmdDdmNCcnVsWTFKeWl4WGpESnd2WTJBeXRzMkdncUh1Z25BZWlwWUdldkVnN2hsV2pvQmwwY3ZxR0w0WGtlMFY4WGpXT1Q2MW1EVVdXOVlwNi9HdXlaUUVKdHZQaFBzT2ZTTjNSamdwaXVNWGM0UzdmR2pxbjYzY3Vnenl3cVRYcDVmaEtJUVFMUzBaWEVPUjdMT2V3WTl4WlczQTgyd2k3MnYyR2FNS1JRSy9MNFZNSjl3QWQ3bWtzQ21OZVNKeVlaS0RlQlVwSGoyYS83dHNQNVNDdXNMMitnaHZLbW03Q3RWQnRLbjlDZ1NJUVBkWEU4U1drai9CVkx0SEp0VG1iSlhXSlNYS2tkRjgwVitud2VaR0FTMUl6RHZNWnlmYXY3WTdzTGlHdWJsRHoxenh3WkxZZ3JHMy9ObUVVbWdxM0hXNDF1QzVWK1NKWE10WEdCbk13SUZ2aS95ZVcya1ZPT2htTWFJV1hXSHhYK2p5cVl0NGl0amVZYWZiZW5qUytCMUJOdERBT29JS0ZMck9rbUYzZTRkcEdCaG9wSXZpenIxcG1TRXNZVFVrOGQwTE5TWEt4Mm41QzNNV3krc1JEUmRtOHhTaXBxYmhvbzdqbWRzQ3Fkb3BvNm5qYkl2SU00M2V5eGF3WC9ZT1o0YXhYTTNGTGZ0Q1M0UWZNL0ZNNGhPRUNXdHRtYVlQN0ZUTjIwUzRWMTB0QUNVbzJERHdoOU1nRTBGZlBucUpXOEw2SzJqVmhSQjRiVjhYZEd0OVNKdWt3N3RSZnhjVU1sM0Vmd2YxWU50YzJ6L24xYzhHU0VtSC9SRUNrc3IwaHRDRmhaZXZBZGR1Qm5GTmxlQ3l5MXdaWnR2VGM4K2QzK1hwU3laOUk1Qk5ndzVyMTF5aUlEaENaWlU4WGxjVmtkNkdqaEkveWxrb2swVGpBTFFMYk83MjcyVEsxbXJsb3NLODkxaEN1RTUrS2s5UktYMktIZ3BsZEVDUU1jeWwvWjBXTy9vUGVQejNKUnMzSk9VUkpBV3k4ZlJZWDlCMm0zOE9yenFzaGtDOVkvN2xHQmVKKzU1Zit2NVo3MWpLZmN6SUE1bEN5YjNqdm1sZjhELy9jMCtEYys3QWgyK2hTSnozYnZYWnBZSFVNdGFzdlhSVEVUUlRVT284am04WVpGSTR4UmtPTGdtQ0FBSzdiMFhIUkMwUVMySDBBR2N3WlFJd1ZRczVHT1I3OW5YV044MldXV3F3dnNjY1p1ZmduZlFRbkRrdjg4bEg3V0dFalpva3dTR3QvWDY3YjRBWDRqSk9BakVBOXJRKzNGOWN4M3FiRWFhcHo3TWhIVHpRRFpKdEJQc201dHIzR08yQ293Sk02UnFVYWRRaU5jNGlBTWRXQjVkVCIsImNpcGhlclRleHQiOiJBUUlCQUhnQjRVMDBTK3ErVE51d1gydlFlaGtxQnVneWQ3YnNrb0pWdWQ2NmZjVENVd0UwS2ZNVEVXU0RzdHE5aWRmWk1zSGRBQUFBb2pDQm53WUpLb1pJaHZjTkFRY0dvSUdSTUlHT0FnRUFNSUdJQmdrcWhraUc5dzBCQndFd0hnWUpZSVpJQVdVREJBRXVNQkVFRExMY0xVTXkrSGpuWlB4YTFBSUJFSUJiMFhWc0RjcWovZVN5WVh5QlJKMFdnQ2xmT0RVY2dLWmJSUlVlNkc1OCsxZkNaTDU2TmoydEx3c1U4V0lwUkVqNkxya1hBb0pnRWVtTUZLMnJwcTVpZmJrMHgySjEwYVd2aFZSQWtMS2lFTDZDMmxJRDhvVEhSSko5Qnc9PSIsInN1YiI6ImFybjphd3M6c2FnZW1ha2VyOnVzLWVhc3QtMTo1MjkwODgyODg5OTA6bWxmbG93LWFwcC9hcHAtMlNWNlEzNUhUQ0JPIiwiaWF0IjoxNzczMTkwMTAxLCJleHAiOjE3NzMxOTA0MDF9._WYatAneAubx7fMUElOyogdDg5Ktk_Y_AT-tgBKt1bQ#/experiments/2\u001b\\\u001b[37m🔗 test-finetuned-models-exp\u001b[0m\u001b]8;;\u001b\\\u001b[37m                                    \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
        "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
        "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mJob Status          \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;38;5;172mInProgress\u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mSecondary Status    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;33mPending\u001b[0m\u001b[37m   \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mElapsed Time        \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;91m10.3s\u001b[0m\u001b[37m     \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mSecondary Status    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;33mTraining\u001b[0m\u001b[37m  \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mElapsed Time        \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;91m990.7s\u001b[0m\u001b[37m    \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
        "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
        "\u001b[38;5;172m│\u001b[0m \u001b[1;35mStatus Transitions\u001b[0m                                                                       \u001b[38;5;172m│\u001b[0m\n",
        "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
        "\u001b[38;5;172m│\u001b[0m  \u001b[1;35m \u001b[0m\u001b[1;35m  \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mStep           \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mDetails                            \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mDuration    \u001b[0m\u001b[1;35m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
        "\u001b[38;5;172m│\u001b[0m  ───────────────────────────────────────────────────────────────────────────             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m✓ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mStarting       \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mStarting the training job          \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m1.8s        \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m⋯ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mPending        \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mTraining job waiting for capacity  \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32mRunning...  \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m✓ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mStarting       \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mStarting the training job          \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m4.7s        \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m✓ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mPending        \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mPreparing the instances for        \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m656.3s      \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[32m    \u001b[0m \u001b[36m                 \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mtraining                           \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m              \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m✓ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mDownloading    \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mDownloading the training image     \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m253.4s      \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m⋯ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mTraining       \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mTraining image download completed. \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32mRunning...  \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
+       "\u001b[38;5;172m│\u001b[0m  \u001b[32m    \u001b[0m \u001b[36m                 \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mTraining in progress.              \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m              \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
        "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
        "\u001b[38;5;172m╰──────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
       ]
@@ -355,8 +396,8 @@
        "│   3 )                                                                                            │\n",
        "│   4                                                                                              │\n",
        "│                                                                                                  │\n",
-       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/ │\n",
-       "│ telemetry/telemetry_logging.py:180 in wrapper                                                    │\n",
+       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk/sagemaker-core/src/sagemaker/core/teleme │\n",
+       "│ try/telemetry_logging.py:180 in wrapper                                                          │\n",
        "│                                                                                                  │\n",
        "│   177 │   │   │   │   │   \"sagemaker_session is not provided or not valid.\",                     │\n",
        "│   178 │   │   │   │   │   func_name,                                                             │\n",
@@ -378,15 +419,15 @@
        "│   283                                                                                            │\n",
        "│                                                                                                  │\n",
        "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai │\n",
-       "│ n/common_utils/trainer_wait.py:272 in wait                                                       │\n",
+       "│ n/common_utils/trainer_wait.py:278 in wait                                                       │\n",
        "│                                                                                                  │\n",
-       "│   269 │   │   │   │   iteration = 0                                                              │\n",
-       "│   270 │   │   │   │   while True:                                                                │\n",
-       "│   271 │   │   │   │   │   iteration += 1                                                         │\n",
-       "│ ❱ 272 │   │   │   │   │   time.sleep(0.5)                                                        │\n",
-       "│   273 │   │   │   │   │   if iteration >= poll * 2:                                              │\n",
-       "│   274 │   │   │   │   │   │   training_job.refresh()                                             │\n",
-       "│   275 │   │   │   │   │   │   iteration = 0                                                      │\n",
+       "│   275 │   │   │   │   iteration = 0                                                              │\n",
+       "│   276 │   │   │   │   while True:                                                                │\n",
+       "│   277 │   │   │   │   │   iteration += 1                                                         │\n",
+       "│ ❱ 278 │   │   │   │   │   time.sleep(0.5)                                                        │\n",
+       "│   279 │   │   │   │   │   if iteration >= poll * 2:                                              │\n",
+       "│   280 │   │   │   │   │   │   training_job.refresh()                                             │\n",
+       "│   281 │   │   │   │   │   │   iteration = 0                                                      │\n",
        "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
        "KeyboardInterrupt\n",
        "\n"
@@ -400,8 +441,8 @@
        "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m3 \u001b[0m)                                                                                            \u001b[38;2;255;0;0m│\u001b[0m\n",
        "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m4 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
        "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mtelemetry/\u001b[0m\u001b[1;33mtelemetry_logging.py\u001b[0m:\u001b[94m180\u001b[0m in \u001b[92mwrapper\u001b[0m                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk/sagemaker-core/src/sagemaker/core/teleme\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mtry/\u001b[0m\u001b[1;33mtelemetry_logging.py\u001b[0m:\u001b[94m180\u001b[0m in \u001b[92mwrapper\u001b[0m                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
        "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
        "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m177 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[33m\"\u001b[0m\u001b[33msagemaker_session is not provided or not valid.\u001b[0m\u001b[33m\"\u001b[0m,                     \u001b[38;2;255;0;0m│\u001b[0m\n",
        "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m178 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mfunc_name,                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
@@ -423,15 +464,15 @@
        "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m283 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
        "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
        "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mn/common_utils/\u001b[0m\u001b[1;33mtrainer_wait.py\u001b[0m:\u001b[94m272\u001b[0m in \u001b[92mwait\u001b[0m                                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mn/common_utils/\u001b[0m\u001b[1;33mtrainer_wait.py\u001b[0m:\u001b[94m278\u001b[0m in \u001b[92mwait\u001b[0m                                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
        "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m269 \u001b[0m\u001b[2m│   │   │   │   \u001b[0miteration = \u001b[94m0\u001b[0m                                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m270 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mwhile\u001b[0m \u001b[94mTrue\u001b[0m:                                                                \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m271 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0miteration += \u001b[94m1\u001b[0m                                                         \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m272 \u001b[2m│   │   │   │   │   \u001b[0mtime.sleep(\u001b[94m0.5\u001b[0m)                                                        \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m273 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mif\u001b[0m iteration >= poll * \u001b[94m2\u001b[0m:                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m274 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0mtraining_job.refresh()                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m275 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0miteration = \u001b[94m0\u001b[0m                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m275 \u001b[0m\u001b[2m│   │   │   │   \u001b[0miteration = \u001b[94m0\u001b[0m                                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m276 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mwhile\u001b[0m \u001b[94mTrue\u001b[0m:                                                                \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m277 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0miteration += \u001b[94m1\u001b[0m                                                         \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m278 \u001b[2m│   │   │   │   │   \u001b[0mtime.sleep(\u001b[94m0.5\u001b[0m)                                                        \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m279 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mif\u001b[0m iteration >= poll * \u001b[94m2\u001b[0m:                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m280 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0mtraining_job.refresh()                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
+       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m281 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0miteration = \u001b[94m0\u001b[0m                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
        "\u001b[38;2;255;0;0m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
        "\u001b[1;91mKeyboardInterrupt\u001b[0m\n"
       ]
@@ -448,83 +489,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "64d68d6f",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
[03/05/26 15:52:42] WARNING  No region provided. Using default region.                                 utils.py:356\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m[03/05/26 15:52:42]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;215;175;0mWARNING \u001b[0m No region provided. Using default region.                                 \u001b]8;id=398978;file:///Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/utils/utils.py\u001b\\\u001b[2mutils.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=927295;file:///Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/utils/utils.py#356\u001b\\\u001b[2m356\u001b[0m\u001b]8;;\u001b\\\n"
-      ]
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-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
                    INFO     Runs on sagemaker prod, region:us-east-1                                  utils.py:370\n",
-       "
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-      "text/plain": [
-       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Runs on sagemaker prod, region:us-east-\u001b[1;36m1\u001b[0m                                  \u001b]8;id=459862;file:///Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/utils/utils.py\u001b\\\u001b[2mutils.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=910567;file:///Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-core/src/sagemaker/core/utils/utils.py#370\u001b\\\u001b[2m370\u001b[0m\u001b]8;;\u001b\\\n"
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-     "metadata": {},
-     "output_type": "display_data"
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-    {
-     "data": {
-      "text/html": [
-       "
                    INFO     Found credentials in shared credentials file: ~/.aws/credentials   credentials.py:1392\n",
-       "
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-      ],
-      "text/plain": [
-       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=500109;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=207687;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
-      ]
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-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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                    INFO     Found credentials in shared credentials file: ~/.aws/credentials   credentials.py:1392\n",
-       "
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-      "text/plain": [
-       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=615220;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=20168;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
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-    {
-     "data": {
-      "text/html": [
-       "
[03/05/26 15:52:46] INFO     Found credentials in shared credentials file: ~/.aws/credentials   credentials.py:1392\n",
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-      ],
-      "text/plain": [
-       "\u001b[2;36m[03/05/26 15:52:46]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=639090;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=958918;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "https://app-2SV6Q35HTCBO.mlflow.sagemaker.us-east-1.app.aws/auth?authToken=eyJhbGciOiJIUzI1NiJ9.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.4TwUDjNP53N-JIHofgyV8hq_6HKftycvEWoOxoqk7fc#/experiments/2\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from sagemaker.train import get_mlflow_url\n",
     "\n",
@@ -535,18 +503,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "fef3d01d",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "https://studio-d-ingyyaeglvki.studio.us-east-1.sagemaker.aws/jobs/train/nova-textgeneration-micro-sft-20260302144611\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from sagemaker.train import get_studio_url\n",
     "\n",

From ec76bffd908a3d00add44eea90d4cc0f1ce9b838 Mon Sep 17 00:00:00 2001
From: Molly He 
Date: Wed, 11 Mar 2026 12:08:34 -0700
Subject: [PATCH 03/11] Fix studio domain mismatch for url, update text color,
 add link of evaluation job

---
 .../train/common_utils/metrics_visualizer.py  | 16 +++++-
 .../train/common_utils/trainer_wait.py        |  4 +-
 .../src/sagemaker/train/evaluate/execution.py | 52 +++++++++++++++----
 3 files changed, 58 insertions(+), 14 deletions(-)

diff --git a/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py b/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
index 2b48149871..8d98964c1b 100644
--- a/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
+++ b/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
@@ -43,13 +43,25 @@ def get_studio_url(training_job, domain_id: str = None) -> str:
         region = training_job.region if hasattr(training_job, 'region') and training_job.region else 'us-east-1'
         job_name = training_job.training_job_name
     
-    sm_client = boto3.client('sagemaker', region_name=region)
-    
     # Auto-detect domain if not provided
     if not domain_id:
+        # First try Studio metadata (when running inside Studio)
+        try:
+            import os, json as _json
+            metadata_path = '/opt/ml/metadata/resource-metadata.json'
+            if os.path.exists(metadata_path):
+                with open(metadata_path, 'r') as f:
+                    domain_id = _json.load(f).get('DomainId')
+        except Exception:
+            pass
+
+    if not domain_id:
+        # Fall back to list_domains, sorted by creation time for deterministic results
         try:
+            sm_client = boto3.client('sagemaker', region_name=region)
             domains = sm_client.list_domains()['Domains']
             if domains:
+                domains.sort(key=lambda d: d.get('CreationTime', ''))
                 domain_id = domains[0]['DomainId']
         except Exception:
             pass
diff --git a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
index 002793fab1..b99014d07c 100644
--- a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
+++ b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
@@ -302,7 +302,7 @@ def get_cached_mlflow_url():
                     # Header section with training job name
                     header_table = Table(show_header=False, box=None, padding=(0, 1))
                     header_table.add_column("Property", style="cyan bold", width=20)
-                    header_table.add_column("Value", style="white", overflow="fold")
+                    header_table.add_column("Value", style="dim", overflow="fold")
                     
                     # Add Studio job link
                     try:
@@ -330,7 +330,7 @@ def get_cached_mlflow_url():
 
                     status_table = Table(show_header=False, box=None, padding=(0, 1))
                     status_table.add_column("Property", style="cyan bold", width=20)
-                    status_table.add_column("Value", style="white")
+                    status_table.add_column("Value", style="dim")
 
                     status_table.add_row("Job Status", f"[bold][orange3]{status}[/][/]")
                     status_table.add_row("Secondary Status", f"[bold yellow]{secondary_status}[/bold yellow]")
diff --git a/sagemaker-train/src/sagemaker/train/evaluate/execution.py b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
index 38dc63b4ec..0bf53bb782 100644
--- a/sagemaker-train/src/sagemaker/train/evaluate/execution.py
+++ b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
@@ -915,6 +915,7 @@ def wait(
             from rich.panel import Panel
             from rich.text import Text
             from rich.layout import Layout
+            from rich.console import Group
             
             # Create console with Jupyter support
             console = Console(force_jupyter=True)
@@ -925,14 +926,45 @@ def wait(
                 current_status = self.status.overall_status
                 elapsed = time.time() - start_time
                 
+                # Create header table with pipeline name link
+                header_table = Table(show_header=False, box=None, padding=(0, 1))
+                header_table.add_column("Property", style="cyan bold", width=20)
+                header_table.add_column("Value", style="dim", overflow="fold")
+
+                # Extract pipeline name from execution ARN and build Studio link
+                pipeline_name = None
+                exec_id = ''
+                if self.arn:
+                    arn_parts = self.arn.split('/')
+                    if len(arn_parts) >= 4:
+                        pipeline_name = arn_parts[-3]
+                        exec_id = arn_parts[-1]
+                # Use execution display name if available, fall back to self.name
+                display_name = self.name
+                if self._pipeline_execution:
+                    dn = getattr(self._pipeline_execution, 'pipeline_execution_display_name', None)
+                    if dn and not (hasattr(dn, '__class__') and 'Unassigned' in dn.__class__.__name__):
+                        display_name = dn
+                try:
+                    from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
+                    dummy_url = get_studio_url(self.arn.split('/')[0].replace(':pipeline', ':training-job') + '/dummy' if self.arn else 'dummy')
+                    if dummy_url and pipeline_name:
+                        base = dummy_url.rsplit('/jobs/train/', 1)[0]
+                        pipeline_url = f"{base}/jobs/evaluation/detail?pipeline_name={pipeline_name}&execution_id={exec_id}"
+                        header_table.add_row("Evaluation Job", f"[link={pipeline_url}]🔗 {display_name}[/link]")
+                    else:
+                        header_table.add_row("Evaluation Job", str(display_name))
+                except Exception:
+                    header_table.add_row("Evaluation Job", str(display_name))
+
                 # Create main status table
                 status_table = Table(show_header=False, box=None, padding=(0, 1))
                 status_table.add_column("Property", style="cyan bold", width=20)
-                status_table.add_column("Value", style="white")
+                status_table.add_column("Value", style="dim")
                 
-                status_table.add_row("Overall Status", f"[bold]{current_status}[/bold]")
-                status_table.add_row("Target Status", f"[bold]{target_status}[/bold]")
-                status_table.add_row("Elapsed Time", f"{elapsed:.1f}s")
+                status_table.add_row("Overall Status", f"[bold][orange3]{current_status}[/][/]")
+                status_table.add_row("Target Status", f"[bold yellow]{target_status}[/bold yellow]")
+                status_table.add_row("Elapsed Time", f"[bold bright_red]{elapsed:.1f}s[/bold bright_red]")
                 
                 if self.status.failure_reason:
                     status_table.add_row("Failure Reason", f"[red]{self.status.failure_reason}[/red]")
@@ -1028,15 +1060,15 @@ def wait(
                         content_parts.append(links_table)
                     
                     console.print(Panel(
-                        Group(*content_parts),
-                        title="[bold blue]Pipeline Execution Status[/bold blue]",
-                        border_style="blue"
+                        Group(header_table, *content_parts),
+                        title="[bold bright_blue]Pipeline Execution Status[/bold bright_blue]",
+                        border_style="orange3"
                     ))
                 else:
                     console.print(Panel(
-                        status_table,
-                        title="[bold blue]Pipeline Execution Status[/bold blue]",
-                        border_style="blue"
+                        Group(header_table, status_table),
+                        title="[bold bright_blue]Pipeline Execution Status[/bold bright_blue]",
+                        border_style="orange3"
                     ))
                 
                 if target_status == current_status:

From 0297d0a282af0ab976226fd8a06baead3e337c48 Mon Sep 17 00:00:00 2001
From: Molly He 
Date: Wed, 18 Mar 2026 11:48:22 -0700
Subject: [PATCH 04/11] Add underscore to fine-tune and eval job links

---
 .../src/sagemaker/train/common_utils/trainer_wait.py          | 4 ++--
 sagemaker-train/src/sagemaker/train/evaluate/execution.py     | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
index b99014d07c..a61d3eba56 100644
--- a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
+++ b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
@@ -308,7 +308,7 @@ def get_cached_mlflow_url():
                     try:
                         from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
                         studio_url = get_studio_url(training_job)
-                        header_table.add_row("TrainingJob Name", f"[link={studio_url}]🔗 {training_job.training_job_name}[/link]")
+                        header_table.add_row("TrainingJob Name", f"[underline][link={studio_url}]🔗 {training_job.training_job_name}[/link][/underline]")
                     except Exception:
                         header_table.add_row("TrainingJob Name", f"[bold green]{training_job.training_job_name}[/bold green]")
                     
@@ -324,7 +324,7 @@ def get_cached_mlflow_url():
                             else:
                                 link_text = "MLflow Experiment"
                             
-                            header_table.add_row("MLflow Experiment", f"[link={cached_url}]🔗 {link_text}[/link]")
+                            header_table.add_row("MLflow Experiment", f"[underline][link={cached_url}]🔗 {link_text}[/link][/underline]")
                         elif mlflow_link_cache['error']:
                             header_table.add_row("MLflow Experiment", f"[red]{mlflow_link_cache['error']}[/red]")
 
diff --git a/sagemaker-train/src/sagemaker/train/evaluate/execution.py b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
index 0bf53bb782..4945a2318e 100644
--- a/sagemaker-train/src/sagemaker/train/evaluate/execution.py
+++ b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
@@ -951,7 +951,7 @@ def wait(
                     if dummy_url and pipeline_name:
                         base = dummy_url.rsplit('/jobs/train/', 1)[0]
                         pipeline_url = f"{base}/jobs/evaluation/detail?pipeline_name={pipeline_name}&execution_id={exec_id}"
-                        header_table.add_row("Evaluation Job", f"[link={pipeline_url}]🔗 {display_name}[/link]")
+                        header_table.add_row("Evaluation Job", f"[underline][link={pipeline_url}]🔗 {display_name}[/link][/underline]")
                     else:
                         header_table.add_row("Evaluation Job", str(display_name))
                 except Exception:
@@ -1051,7 +1051,7 @@ def wait(
                             try:
                                 from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
                                 url = get_studio_url(entry['job_arn'])
-                                link_col = f"[link={url}]🔗 link[/link]" if url else ""
+                                link_col = f"[underline][link={url}]🔗 link[/link][/underline]" if url else ""
                             except Exception:
                                 link_col = ""
                             links_table.add_row(entry['step_name'], link_col, entry['job_arn'])

From b34d0d88981f1bde569eaaa366e9d08e82c63406 Mon Sep 17 00:00:00 2001
From: Molly He 
Date: Wed, 18 Mar 2026 16:04:24 -0700
Subject: [PATCH 05/11] Update link to console, conditionally display studio
 link, update link color to blue

---
 .gitignore                                    |   1 +
 .../train/common_utils/metrics_visualizer.py  | 105 +++++++++++++-----
 .../train/common_utils/trainer_wait.py        |  45 +++++---
 .../src/sagemaker/train/evaluate/execution.py |  67 ++++++++---
 4 files changed, 157 insertions(+), 61 deletions(-)

diff --git a/.gitignore b/.gitignore
index 7428f4f025..f87727e33e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -40,3 +40,4 @@ env/
 sagemaker_train/src/**/container_drivers/sm_train.sh
 sagemaker_train/src/**/container_drivers/sourcecode.json
 sagemaker_train/src/**/container_drivers/distributed.json
+.kiro
diff --git a/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py b/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
index 8d98964c1b..fe861d0646 100644
--- a/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
+++ b/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
@@ -2,12 +2,85 @@
 
 import logging
 from typing import Optional, List, Dict, Any
-import boto3
 from sagemaker.core.resources import TrainingJob
 
 logger = logging.getLogger(__name__)
 
 
+def _is_in_studio() -> bool:
+    """Check if running inside SageMaker Studio."""
+    from sagemaker.train.common_utils.finetune_utils import _read_domain_id_from_metadata
+    return _read_domain_id_from_metadata() is not None
+
+
+def _get_studio_base_url(region: str) -> str:
+    """Get Studio base URL, or empty string if domain not resolvable."""
+    from sagemaker.train.common_utils.finetune_utils import _read_domain_id_from_metadata
+    domain_id = _read_domain_id_from_metadata()
+    if not domain_id or not region:
+        return ""
+    return f"https://studio-{domain_id}.studio.{region}.sagemaker.aws"
+
+
+def _parse_job_arn(job_arn: str):
+    """Parse a SageMaker job ARN into (region, resource) or None."""
+    import re
+    m = re.match(r'arn:aws(?:-[a-z]+)?:sagemaker:([a-z0-9-]+):\d+:(\S+)', job_arn)
+    return (m.group(1), m.group(2)) if m else None
+
+
+def get_console_job_url(job_arn: str) -> str:
+    """Get AWS Console URL for a SageMaker job ARN.
+    
+    Args:
+        job_arn: Full ARN like arn:aws:sagemaker:us-east-1:123:training-job/my-job
+        
+    Returns:
+        Console URL or empty string.
+    """
+    parsed = _parse_job_arn(job_arn)
+    if not parsed:
+        return ""
+    region, resource = parsed
+    job_type_map = {
+        "training-job/": "#/jobs/",
+        "processing-job/": "#/processing-jobs/",
+        "transform-job/": "#/transform-jobs/",
+    }
+    for prefix, fragment in job_type_map.items():
+        if resource.startswith(prefix):
+            job_name = resource.split("/", 1)[1]
+            return f"https://{region}.console.aws.amazon.com/sagemaker/home?region={region}{fragment}{job_name}"
+    return ""
+
+
+def get_cloudwatch_logs_url(job_arn: str) -> str:
+    """Get CloudWatch Logs console URL for a SageMaker job ARN.
+    
+    Returns:
+        CloudWatch console URL or empty string.
+    """
+    parsed = _parse_job_arn(job_arn)
+    if not parsed:
+        return ""
+    region, resource = parsed
+    log_group_map = {
+        "training-job/": "/aws/sagemaker/TrainingJobs",
+        "processing-job/": "/aws/sagemaker/ProcessingJobs",
+        "transform-job/": "/aws/sagemaker/TransformJobs",
+    }
+    for prefix, log_group in log_group_map.items():
+        if resource.startswith(prefix):
+            job_name = resource.split("/", 1)[1]
+            encoded_group = log_group.replace("/", "$252F")
+            return (
+                f"https://{region}.console.aws.amazon.com/cloudwatch/home?region={region}"
+                f"#logsV2:log-groups/log-group/{encoded_group}"
+                f"$3FlogStreamNameFilter$3D{job_name}"
+            )
+    return ""
+
+
 def get_studio_url(training_job, domain_id: str = None) -> str:
     """Get SageMaker Studio URL for training job logs.
     
@@ -43,34 +116,10 @@ def get_studio_url(training_job, domain_id: str = None) -> str:
         region = training_job.region if hasattr(training_job, 'region') and training_job.region else 'us-east-1'
         job_name = training_job.training_job_name
     
-    # Auto-detect domain if not provided
-    if not domain_id:
-        # First try Studio metadata (when running inside Studio)
-        try:
-            import os, json as _json
-            metadata_path = '/opt/ml/metadata/resource-metadata.json'
-            if os.path.exists(metadata_path):
-                with open(metadata_path, 'r') as f:
-                    domain_id = _json.load(f).get('DomainId')
-        except Exception:
-            pass
-
-    if not domain_id:
-        # Fall back to list_domains, sorted by creation time for deterministic results
-        try:
-            sm_client = boto3.client('sagemaker', region_name=region)
-            domains = sm_client.list_domains()['Domains']
-            if domains:
-                domains.sort(key=lambda d: d.get('CreationTime', ''))
-                domain_id = domains[0]['DomainId']
-        except Exception:
-            pass
-    
-    if not domain_id:
+    base = _get_studio_base_url(region)
+    if not base:
         return ""
-    
-    # Studio URL format: https://studio-{domain_id}.studio.{region}.sagemaker.aws/jobs/train/{job_name}
-    return f"https://studio-{domain_id}.studio.{region}.sagemaker.aws/jobs/train/{job_name}"
+    return f"{base}/jobs/train/{job_name}"
 
 
 def display_job_links_html(rows: list, as_html: bool = False):
diff --git a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
index a61d3eba56..8b0e6c2f3c 100644
--- a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
+++ b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
@@ -299,34 +299,45 @@ def get_cached_mlflow_url():
                     
                     clear_output(wait=True)
 
-                    # Header section with training job name
+                    # Header section with training job info
                     header_table = Table(show_header=False, box=None, padding=(0, 1))
                     header_table.add_column("Property", style="cyan bold", width=20)
                     header_table.add_column("Value", style="dim", overflow="fold")
                     
-                    # Add Studio job link
-                    try:
-                        from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
-                        studio_url = get_studio_url(training_job)
-                        header_table.add_row("TrainingJob Name", f"[underline][link={studio_url}]🔗 {training_job.training_job_name}[/link][/underline]")
-                    except Exception:
-                        header_table.add_row("TrainingJob Name", f"[bold green]{training_job.training_job_name}[/bold green]")
-                    
+                    header_table.add_row("TrainingJob Name", f"[bold green]{training_job.training_job_name}[/bold green]")
                     header_table.add_row("TrainingJob ARN", f"[dim]{training_job.training_job_arn}[/dim]")
                     
-                    # Add MLflow link to header if available
+                    # Build links row
+                    links = []
+                    try:
+                        from sagemaker.train.common_utils.metrics_visualizer import (
+                            _is_in_studio, get_console_job_url, get_cloudwatch_logs_url, get_studio_url
+                        )
+                        if _is_in_studio():
+                            studio_url = get_studio_url(training_job)
+                            if studio_url:
+                                links.append(f"[bright_blue underline][link={studio_url}]🔗 Training Job (Studio)[/link][/bright_blue underline]")
+                        else:
+                            console_url = get_console_job_url(training_job.training_job_arn)
+                            if console_url:
+                                links.append(f"[bright_blue underline][link={console_url}]🔗 Training Job[/link][/bright_blue underline]")
+                        cw_url = get_cloudwatch_logs_url(training_job.training_job_arn)
+                        if cw_url:
+                            links.append(f"[bright_blue underline][link={cw_url}]🔗 CloudWatch Logs[/link][/bright_blue underline]")
+                    except Exception:
+                        pass
                     if has_mlflow_config:
                         cached_url = get_cached_mlflow_url()
                         if cached_url:
-                            exp_name = training_job.mlflow_config.mlflow_experiment_name if hasattr(training_job, 'mlflow_config') else None
-                            if exp_name and not _is_unassigned_attribute(exp_name):
-                                link_text = exp_name
-                            else:
-                                link_text = "MLflow Experiment"
-                            
-                            header_table.add_row("MLflow Experiment", f"[underline][link={cached_url}]🔗 {link_text}[/link][/underline]")
+                            links.append(f"[bright_blue underline][link={cached_url}]🔗 MLflow Experiment[/link][/bright_blue underline]")
                         elif mlflow_link_cache['error']:
                             header_table.add_row("MLflow Experiment", f"[red]{mlflow_link_cache['error']}[/red]")
+                    if has_mlflow_config:
+                        exp_name = training_job.mlflow_config.mlflow_experiment_name if hasattr(training_job, 'mlflow_config') else None
+                        if exp_name and not _is_unassigned_attribute(exp_name):
+                            header_table.add_row("MLflow Experiment", f"{exp_name}")
+                    if links:
+                        header_table.add_row("Links", " | ".join(links))
 
                     status_table = Table(show_header=False, box=None, padding=(0, 1))
                     status_table.add_column("Property", style="cyan bold", width=20)
diff --git a/sagemaker-train/src/sagemaker/train/evaluate/execution.py b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
index 4945a2318e..c1630ea4c6 100644
--- a/sagemaker-train/src/sagemaker/train/evaluate/execution.py
+++ b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
@@ -931,31 +931,37 @@ def wait(
                 header_table.add_column("Property", style="cyan bold", width=20)
                 header_table.add_column("Value", style="dim", overflow="fold")
 
-                # Extract pipeline name from execution ARN and build Studio link
+                # Extract pipeline name and region from execution ARN
                 pipeline_name = None
                 exec_id = ''
+                region = None
                 if self.arn:
                     arn_parts = self.arn.split('/')
                     if len(arn_parts) >= 4:
                         pipeline_name = arn_parts[-3]
                         exec_id = arn_parts[-1]
+                    region = self.arn.split(":")[3] if len(self.arn.split(":")) > 3 else None
                 # Use execution display name if available, fall back to self.name
                 display_name = self.name
                 if self._pipeline_execution:
                     dn = getattr(self._pipeline_execution, 'pipeline_execution_display_name', None)
                     if dn and not (hasattr(dn, '__class__') and 'Unassigned' in dn.__class__.__name__):
                         display_name = dn
+                header_table.add_row("Evaluation Job", str(display_name))
+
+                # Build links row
+                links = []
                 try:
-                    from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
-                    dummy_url = get_studio_url(self.arn.split('/')[0].replace(':pipeline', ':training-job') + '/dummy' if self.arn else 'dummy')
-                    if dummy_url and pipeline_name:
-                        base = dummy_url.rsplit('/jobs/train/', 1)[0]
-                        pipeline_url = f"{base}/jobs/evaluation/detail?pipeline_name={pipeline_name}&execution_id={exec_id}"
-                        header_table.add_row("Evaluation Job", f"[underline][link={pipeline_url}]🔗 {display_name}[/link][/underline]")
-                    else:
-                        header_table.add_row("Evaluation Job", str(display_name))
+                    from sagemaker.train.common_utils.metrics_visualizer import _is_in_studio, _get_studio_base_url
+                    if region and pipeline_name and _is_in_studio():
+                        base = _get_studio_base_url(region)
+                        if base:
+                            pipeline_url = f"{base}/jobs/evaluation/detail?pipeline_name={pipeline_name}&execution_id={exec_id}"
+                            links.append(f"[bright_blue underline][link={pipeline_url}]🔗 Pipeline Execution (Studio)[/link][/bright_blue underline]")
                 except Exception:
-                    header_table.add_row("Evaluation Job", str(display_name))
+                    pass
+                if links:
+                    header_table.add_row("Links", " | ".join(links))
 
                 # Create main status table
                 status_table = Table(show_header=False, box=None, padding=(0, 1))
@@ -1045,16 +1051,45 @@ def wait(
                     if job_arn_entries:
                         links_table = Table(show_header=True, header_style="bold magenta", box=None, padding=(0, 1))
                         links_table.add_column("Step", style="cyan", width=20)
-                        links_table.add_column("Job Link", width=12)
+                        links_table.add_column("Job Link", style="dim")
+                        links_table.add_column("Logs", style="dim")
                         links_table.add_column("Job ARN", style="dim", overflow="fold")
+                        from sagemaker.train.common_utils.metrics_visualizer import (
+                            _is_in_studio, _parse_job_arn, _get_studio_base_url,
+                            get_console_job_url, get_cloudwatch_logs_url,
+                        )
+                        in_studio = _is_in_studio()
+                        studio_base = _get_studio_base_url(region) if in_studio else ""
+                        studio_path_map = {
+                            "training-job/": "jobs/train/",
+                            "processing-job/": "jobs/processing/",
+                            "transform-job/": "jobs/transform/",
+                        }
                         for entry in job_arn_entries:
+                            job_link = ""
+                            logs_link = ""
                             try:
-                                from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
-                                url = get_studio_url(entry['job_arn'])
-                                link_col = f"[underline][link={url}]🔗 link[/link][/underline]" if url else ""
+                                arn = entry['job_arn']
+                                if in_studio and studio_base:
+                                    parsed = _parse_job_arn(arn)
+                                    if parsed:
+                                        _, resource = parsed
+                                        for prefix, path in studio_path_map.items():
+                                            if resource.startswith(prefix):
+                                                job_name = resource.split("/", 1)[1]
+                                                url = f"{studio_base}/{path}{job_name}"
+                                                job_link = f"[bright_blue underline][link={url}]🔗 link[/link][/bright_blue underline]"
+                                                break
+                                else:
+                                    url = get_console_job_url(arn)
+                                    if url:
+                                        job_link = f"[bright_blue underline][link={url}]🔗 link[/link][/bright_blue underline]"
+                                cw_url = get_cloudwatch_logs_url(arn)
+                                if cw_url:
+                                    logs_link = f"[bright_blue underline][link={cw_url}]🔗 logs[/link][/bright_blue underline]"
                             except Exception:
-                                link_col = ""
-                            links_table.add_row(entry['step_name'], link_col, entry['job_arn'])
+                                pass
+                            links_table.add_row(entry['step_name'], job_link, logs_link, entry['job_arn'])
                         content_parts.append(Text(""))
                         content_parts.append(Text("Job ARNs", style="bold magenta"))
                         content_parts.append(links_table)

From 1adce4ff95ae58e3c9c220dffc0307a86db6ffac Mon Sep 17 00:00:00 2001
From: Molly He 
Date: Wed, 18 Mar 2026 16:33:14 -0700
Subject: [PATCH 06/11] Always show console link, conditional show studio link

---
 .../train/common_utils/trainer_wait.py        | 24 +++++++------
 .../src/sagemaker/train/evaluate/execution.py | 34 +++++++++++--------
 2 files changed, 33 insertions(+), 25 deletions(-)

diff --git a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
index 8b0e6c2f3c..72537874f5 100644
--- a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
+++ b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
@@ -307,37 +307,39 @@ def get_cached_mlflow_url():
                     header_table.add_row("TrainingJob Name", f"[bold green]{training_job.training_job_name}[/bold green]")
                     header_table.add_row("TrainingJob ARN", f"[dim]{training_job.training_job_arn}[/dim]")
                     
-                    # Build links row
-                    links = []
+                    # Build links rows
+                    links_row1 = []
+                    links_row2 = []
                     try:
                         from sagemaker.train.common_utils.metrics_visualizer import (
                             _is_in_studio, get_console_job_url, get_cloudwatch_logs_url, get_studio_url
                         )
+                        console_url = get_console_job_url(training_job.training_job_arn)
+                        if console_url:
+                            links_row1.append(f"[bright_blue underline][link={console_url}]🔗 Training Job (Console)[/link][/bright_blue underline]")
                         if _is_in_studio():
                             studio_url = get_studio_url(training_job)
                             if studio_url:
-                                links.append(f"[bright_blue underline][link={studio_url}]🔗 Training Job (Studio)[/link][/bright_blue underline]")
-                        else:
-                            console_url = get_console_job_url(training_job.training_job_arn)
-                            if console_url:
-                                links.append(f"[bright_blue underline][link={console_url}]🔗 Training Job[/link][/bright_blue underline]")
+                                links_row1.append(f"[bright_blue underline][link={studio_url}]🔗 Training Job (Studio)[/link][/bright_blue underline]")
                         cw_url = get_cloudwatch_logs_url(training_job.training_job_arn)
                         if cw_url:
-                            links.append(f"[bright_blue underline][link={cw_url}]🔗 CloudWatch Logs[/link][/bright_blue underline]")
+                            links_row2.append(f"[bright_blue underline][link={cw_url}]🔗 CloudWatch Logs[/link][/bright_blue underline]")
                     except Exception:
                         pass
                     if has_mlflow_config:
                         cached_url = get_cached_mlflow_url()
                         if cached_url:
-                            links.append(f"[bright_blue underline][link={cached_url}]🔗 MLflow Experiment[/link][/bright_blue underline]")
+                            links_row2.append(f"[bright_blue underline][link={cached_url}]🔗 MLflow Experiment[/link][/bright_blue underline]")
                         elif mlflow_link_cache['error']:
                             header_table.add_row("MLflow Experiment", f"[red]{mlflow_link_cache['error']}[/red]")
                     if has_mlflow_config:
                         exp_name = training_job.mlflow_config.mlflow_experiment_name if hasattr(training_job, 'mlflow_config') else None
                         if exp_name and not _is_unassigned_attribute(exp_name):
                             header_table.add_row("MLflow Experiment", f"{exp_name}")
-                    if links:
-                        header_table.add_row("Links", " | ".join(links))
+                    if links_row1:
+                        header_table.add_row("Links", " | ".join(links_row1))
+                    if links_row2:
+                        header_table.add_row("" if links_row1 else "Links", " | ".join(links_row2))
 
                     status_table = Table(show_header=False, box=None, padding=(0, 1))
                     status_table.add_column("Property", style="cyan bold", width=20)
diff --git a/sagemaker-train/src/sagemaker/train/evaluate/execution.py b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
index c1630ea4c6..9d683edd84 100644
--- a/sagemaker-train/src/sagemaker/train/evaluate/execution.py
+++ b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
@@ -1051,25 +1051,34 @@ def wait(
                     if job_arn_entries:
                         links_table = Table(show_header=True, header_style="bold magenta", box=None, padding=(0, 1))
                         links_table.add_column("Step", style="cyan", width=20)
-                        links_table.add_column("Job Link", style="dim")
-                        links_table.add_column("Logs", style="dim")
-                        links_table.add_column("Job ARN", style="dim", overflow="fold")
+                        links_table.add_column("Console", style="dim")
                         from sagemaker.train.common_utils.metrics_visualizer import (
                             _is_in_studio, _parse_job_arn, _get_studio_base_url,
                             get_console_job_url, get_cloudwatch_logs_url,
                         )
                         in_studio = _is_in_studio()
                         studio_base = _get_studio_base_url(region) if in_studio else ""
+                        if in_studio:
+                            links_table.add_column("Studio", style="dim")
+                        links_table.add_column("Logs", style="dim")
+                        links_table.add_column("Job ARN", style="dim", overflow="fold")
                         studio_path_map = {
                             "training-job/": "jobs/train/",
                             "processing-job/": "jobs/processing/",
                             "transform-job/": "jobs/transform/",
                         }
                         for entry in job_arn_entries:
-                            job_link = ""
+                            console_link = ""
                             logs_link = ""
+                            studio_link = ""
                             try:
                                 arn = entry['job_arn']
+                                url = get_console_job_url(arn)
+                                if url:
+                                    console_link = f"[bright_blue underline][link={url}]🔗 link[/link][/bright_blue underline]"
+                                cw_url = get_cloudwatch_logs_url(arn)
+                                if cw_url:
+                                    logs_link = f"[bright_blue underline][link={cw_url}]🔗 logs[/link][/bright_blue underline]"
                                 if in_studio and studio_base:
                                     parsed = _parse_job_arn(arn)
                                     if parsed:
@@ -1077,19 +1086,16 @@ def wait(
                                         for prefix, path in studio_path_map.items():
                                             if resource.startswith(prefix):
                                                 job_name = resource.split("/", 1)[1]
-                                                url = f"{studio_base}/{path}{job_name}"
-                                                job_link = f"[bright_blue underline][link={url}]🔗 link[/link][/bright_blue underline]"
+                                                s_url = f"{studio_base}/{path}{job_name}"
+                                                studio_link = f"[bright_blue underline][link={s_url}]🔗 studio[/link][/bright_blue underline]"
                                                 break
-                                else:
-                                    url = get_console_job_url(arn)
-                                    if url:
-                                        job_link = f"[bright_blue underline][link={url}]🔗 link[/link][/bright_blue underline]"
-                                cw_url = get_cloudwatch_logs_url(arn)
-                                if cw_url:
-                                    logs_link = f"[bright_blue underline][link={cw_url}]🔗 logs[/link][/bright_blue underline]"
                             except Exception:
                                 pass
-                            links_table.add_row(entry['step_name'], job_link, logs_link, entry['job_arn'])
+                            row = [entry['step_name'], console_link]
+                            if in_studio:
+                                row.append(studio_link)
+                            row.extend([logs_link, entry['job_arn']])
+                            links_table.add_row(*row)
                         content_parts.append(Text(""))
                         content_parts.append(Text("Job ARNs", style="bold magenta"))
                         content_parts.append(links_table)

From 928204bdf88307999b5ebcf1f29161bf065f5bf8 Mon Sep 17 00:00:00 2001
From: Molly He 
Date: Wed, 18 Mar 2026 16:37:01 -0700
Subject: [PATCH 07/11] Minor update to execution link names

---
 sagemaker-train/src/sagemaker/train/evaluate/execution.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/sagemaker-train/src/sagemaker/train/evaluate/execution.py b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
index 9d683edd84..722461bb6c 100644
--- a/sagemaker-train/src/sagemaker/train/evaluate/execution.py
+++ b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
@@ -1078,7 +1078,7 @@ def wait(
                                     console_link = f"[bright_blue underline][link={url}]🔗 link[/link][/bright_blue underline]"
                                 cw_url = get_cloudwatch_logs_url(arn)
                                 if cw_url:
-                                    logs_link = f"[bright_blue underline][link={cw_url}]🔗 logs[/link][/bright_blue underline]"
+                                    logs_link = f"[bright_blue underline][link={cw_url}]🔗 link[/link][/bright_blue underline]"
                                 if in_studio and studio_base:
                                     parsed = _parse_job_arn(arn)
                                     if parsed:
@@ -1087,7 +1087,7 @@ def wait(
                                             if resource.startswith(prefix):
                                                 job_name = resource.split("/", 1)[1]
                                                 s_url = f"{studio_base}/{path}{job_name}"
-                                                studio_link = f"[bright_blue underline][link={s_url}]🔗 studio[/link][/bright_blue underline]"
+                                                studio_link = f"[bright_blue underline][link={s_url}]🔗 link[/link][/bright_blue underline]"
                                                 break
                             except Exception:
                                 pass

From cd1658af8e0391abf180f45793b921418e0e4619 Mon Sep 17 00:00:00 2001
From: Molly He 
Date: Fri, 20 Mar 2026 16:00:25 -0700
Subject: [PATCH 08/11] Fix region issue for studio url

---
 .../train/common_utils/metrics_visualizer.py          | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py b/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
index fe861d0646..fe837a91fc 100644
--- a/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
+++ b/sagemaker-train/src/sagemaker/train/common_utils/metrics_visualizer.py
@@ -94,11 +94,10 @@ def get_studio_url(training_job, domain_id: str = None) -> str:
     Example:
         >>> from sagemaker.train import get_studio_url
         >>> url = get_studio_url('my-training-job')
-        >>> url = get_studio_url('arn:aws:sagemaker:us-east-1:123456789:training-job/my-job')
+        >>> url = get_studio_url('arn:aws:sagemaker:us-west-2:123456789:training-job/my-job')
     """
     import re
 
-    # Handle ARN string — extract region and job name directly
     if isinstance(training_job, str):
         arn_match = re.match(
             r'arn:aws(?:-[a-z]+)?:sagemaker:([a-z0-9-]+):\d+:training-job/(.+)',
@@ -108,12 +107,14 @@ def get_studio_url(training_job, domain_id: str = None) -> str:
             region = arn_match.group(1)
             job_name = arn_match.group(2)
         else:
-            # Treat as job name, need to fetch the object
+            # Plain job name — use session region
             training_job = TrainingJob.get(training_job_name=training_job)
-            region = training_job.region if hasattr(training_job, 'region') and training_job.region else 'us-east-1'
+            from sagemaker.core.utils.utils import SageMakerClient
+            region = SageMakerClient().region_name
             job_name = training_job.training_job_name
     else:
-        region = training_job.region if hasattr(training_job, 'region') and training_job.region else 'us-east-1'
+        from sagemaker.core.utils.utils import SageMakerClient
+        region = SageMakerClient().region_name
         job_name = training_job.training_job_name
     
     base = _get_studio_base_url(region)

From c6ba964b986c2bf2d864ec710389d35e3a1c01e9 Mon Sep 17 00:00:00 2001
From: Molly He 
Date: Fri, 20 Mar 2026 16:47:30 -0700
Subject: [PATCH 09/11] Revert notebook change to original

---
 .../evaluate/benchmark_demo.ipynb             | 545 +--------------
 ...dpo_trainer_example_notebook_v3_prod.ipynb |   6 +-
 ...uning_example_notebook_pysdk_prod_v3.ipynb | 477 ++-----------
 ...io-nova-training-job-sample-notebook.ipynb | 637 +-----------------
 4 files changed, 105 insertions(+), 1560 deletions(-)

diff --git a/sagemaker-train/example_notebooks/evaluate/benchmark_demo.ipynb b/sagemaker-train/example_notebooks/evaluate/benchmark_demo.ipynb
index b78d35b8e9..0719cbbab2 100644
--- a/sagemaker-train/example_notebooks/evaluate/benchmark_demo.ipynb
+++ b/sagemaker-train/example_notebooks/evaluate/benchmark_demo.ipynb
@@ -24,94 +24,23 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "import logging\n",
-    "logging.basicConfig(level=logging.WARNING)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
[\n",
-       "│   <_Benchmark.MMLU: 'mmlu'>,\n",
-       "│   <_Benchmark.MMLU_PRO: 'mmlu_pro'>,\n",
-       "│   <_Benchmark.BBH: 'bbh'>,\n",
-       "│   <_Benchmark.GPQA: 'gpqa'>,\n",
-       "│   <_Benchmark.MATH: 'math'>,\n",
-       "│   <_Benchmark.STRONG_REJECT: 'strong_reject'>,\n",
-       "│   <_Benchmark.IFEVAL: 'ifeval'>,\n",
-       "│   <_Benchmark.MMMU: 'mmmu'>,\n",
-       "│   <_Benchmark.LLM_JUDGE: 'llm_judge'>\n",
-       "]\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[1m[\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[1m<\u001b[0m\u001b[1;38;2;225;0;225m_Benchmark.MMLU:\u001b[0m\u001b[39m \u001b[0m\u001b[38;2;0;135;0m'mmlu'\u001b[0m\u001b[39m>,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.MMLU_PRO: \u001b[0m\u001b[38;2;0;135;0m'mmlu_pro'\u001b[0m\u001b[39m>,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.BBH: \u001b[0m\u001b[38;2;0;135;0m'bbh'\u001b[0m\u001b[39m>,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.GPQA: \u001b[0m\u001b[38;2;0;135;0m'gpqa'\u001b[0m\u001b[39m>,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.MATH: \u001b[0m\u001b[38;2;0;135;0m'math'\u001b[0m\u001b[39m>,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.STRONG_REJECT: \u001b[0m\u001b[38;2;0;135;0m'strong_reject'\u001b[0m\u001b[39m>,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.IFEVAL: \u001b[0m\u001b[38;2;0;135;0m'ifeval'\u001b[0m\u001b[39m>,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.MMMU: \u001b[0m\u001b[38;2;0;135;0m'mmmu'\u001b[0m\u001b[39m>,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[39m<_Benchmark.LLM_JUDGE: \u001b[0m\u001b[38;2;0;135;0m'llm_judge'\u001b[0m\u001b[1m>\u001b[0m\n",
-       "\u001b[1m]\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
{\n",
-       "│   'modality': 'Text',\n",
-       "│   'description': 'General Physics Question Answering – Assesses comprehension of physics concepts and related problem-solving abilities.',\n",
-       "│   'metrics': ['accuracy'],\n",
-       "│   'strategy': 'zs_cot',\n",
-       "│   'subtask_available': False,\n",
-       "│   'subtasks': None\n",
-       "}\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[1m{\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'modality'\u001b[0m: \u001b[38;2;0;135;0m'Text'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'description'\u001b[0m: \u001b[38;2;0;135;0m'General Physics Question Answering – Assesses comprehension of physics concepts and related problem-solving abilities.'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'metrics'\u001b[0m: \u001b[1m[\u001b[0m\u001b[38;2;0;135;0m'accuracy'\u001b[0m\u001b[1m]\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'strategy'\u001b[0m: \u001b[38;2;0;135;0m'zs_cot'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'subtask_available'\u001b[0m: \u001b[3;38;2;215;0;0mFalse\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'subtasks'\u001b[0m: \u001b[3;38;2;225;0;225mNone\u001b[0m\n",
-       "\u001b[1m}\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
    "source": [
     "from sagemaker.train.evaluate import get_benchmarks, get_benchmark_properties\n",
     "from rich.pretty import pprint\n",
     "\n",
     "# Configure logging to show INFO messages\n",
-    "# import logging\n",
-    "# logging.basicConfig(\n",
-    "#     level=logging.INFO,\n",
-    "#     format='%(levelname)s - %(name)s - %(message)s'\n",
-    "# )\n",
+    "import logging\n",
+    "logging.basicConfig(\n",
+    "    level=logging.INFO,\n",
+    "    format='%(levelname)s - %(name)s - %(message)s'\n",
+    ")\n",
     "\n",
     "# Get available benchmarks\n",
     "Benchmark = get_benchmarks()\n",
     "pprint(list(Benchmark))\n",
     "\n",
     "# Print properties for a specific benchmark\n",
-    "pprint(get_benchmark_properties(benchmark=Benchmark.GPQA))"
+    "pprint(get_benchmark_properties(benchmark=Benchmark.GEN_QA))"
    ]
   },
   {
@@ -138,200 +67,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING:sagemaker.core.utils.utils:No region provided. Using default region.\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "model_package_group_name='model-package-group-nova13' model_package_group_arn='arn:aws:sagemaker:us-east-1:529088288990:model-package-group/model-package-group-nova13' model_package_group_description=Unassigned() creation_time=datetime.datetime(2026, 3, 4, 13, 13, 33, 33000, tzinfo=tzlocal()) created_by=UserContext(user_profile_arn=Unassigned(), user_profile_name=Unassigned(), domain_id=Unassigned(), iam_identity=IamIdentity(arn='arn:aws:sts::529088288990:assumed-role/Admin/mollyhe-Isengard', principal_id='AROAXWMA6TDPKWL3QDB2W:mollyhe-Isengard', source_identity=Unassigned())) model_package_group_status='Completed'\n"
-     ]
-    }
-   ],
-   "source": [
-    "from sagemaker.core.resources import ModelPackage, ModelPackageGroup\n",
-    "\n",
-    "# model_package_group=ModelPackageGroup.create(model_package_group_name=\"model-package-group-nova13\")\n",
-    "model_package_group=ModelPackageGroup.get(model_package_group_name=\"model-package-group-nova13\")\n",
-    "print(model_package_group)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "\n",
-    "import json\n",
-    "import re\n",
-    "from sagemaker.core.utils.utils import Unassigned\n",
-    "\n",
-    "def pretty_print(obj):\n",
-    "    def parse_unassigned(item):\n",
-    "        if isinstance(item, Unassigned):\n",
-    "            return None\n",
-    "        if isinstance(item, dict):\n",
-    "            return {k: parse_unassigned(v) for k, v in item.items() if parse_unassigned(v) is not None}\n",
-    "        if isinstance(item, list):\n",
-    "            return [parse_unassigned(x) for x in item if parse_unassigned(x) is not None]\n",
-    "        if isinstance(item, str) and \"Unassigned object\" in item:\n",
-    "            pairs = re.findall(r\"(\\w+)=([^<][^=]*?)(?=\\s+\\w+=|$)\", item)\n",
-    "            result = {k: v.strip(\"'\\\"\") for k, v in pairs}\n",
-    "            return result if result else None\n",
-    "        return item\n",
-    "\n",
-    "    cleaned = parse_unassigned(obj.__dict__ if hasattr(obj, '__dict__') else obj)\n",
-    "    print(json.dumps(cleaned, indent=2, default=str))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{\n",
-      "  \"training_job_name\": \"nova-textgeneration-micro-sft-20260302144611\",\n",
-      "  \"training_job_arn\": \"arn:aws:sagemaker:us-east-1:529088288990:training-job/nova-textgeneration-micro-sft-20260302144611\",\n",
-      "  \"model_artifacts\": \"s3_model_artifacts='s3://sagemaker-us-east-1-529088288990/output/nova-textgeneration-micro-sft-20260302144611/output/model'\",\n",
-      "  \"training_job_output\": \"s3_training_job_output='s3://sagemaker-us-east-1-529088288990/output/nova-textgeneration-micro-sft-20260302144611/output/output'\",\n",
-      "  \"training_job_status\": \"Completed\",\n",
-      "  \"secondary_status\": \"Completed\",\n",
-      "  \"hyper_parameters\": {\n",
-      "    \"global_batch_size\": \"64\",\n",
-      "    \"learning_rate\": \"1e-05\",\n",
-      "    \"learning_rate_ratio\": \"16.0\",\n",
-      "    \"lora_alpha\": \"128\",\n",
-      "    \"max_context_length\": \"8192\",\n",
-      "    \"max_epochs\": \"2\",\n",
-      "    \"name\": \"my-lora-run-wkxk5\"\n",
-      "  },\n",
-      "  \"role_arn\": \"arn:aws:iam::529088288990:role/Admin\",\n",
-      "  \"input_data_config\": [\n",
-      "    \"channel_name='train' data_source=DataSource(s3_data_source=Unassigned(), file_system_data_source=Unassigned(), dataset_source=DatasetSource(dataset_arn='arn:aws:sagemaker:us-east-1:529088288990:hub-content/G82247CBEQ6TN0FI3J1SAJU59UURMT3H3EKG48C6VQGDINNRNGU0/DataSet/demo-1/5.0.0')) content_type=Unassigned() compression_type='None' record_wrapper_type='None' input_mode=Unassigned() shuffle_config=Unassigned() enable_ffm=False\"\n",
-      "  ],\n",
-      "  \"output_data_config\": \"s3_output_path='s3://sagemaker-us-east-1-529088288990/output/' kms_key_id='' compression_type='NONE' remove_job_name_from_s3_output_path=False disable_model_upload=False channels=Unassigned()\",\n",
-      "  \"stopping_condition\": \"max_runtime_in_seconds=86400 max_wait_time_in_seconds=Unassigned() max_pending_time_in_seconds=Unassigned()\",\n",
-      "  \"creation_time\": \"2026-03-02 14:46:12.873000-08:00\",\n",
-      "  \"training_start_time\": \"2026-03-02 14:58:59.629000-08:00\",\n",
-      "  \"training_end_time\": \"2026-03-02 15:22:26.851000-08:00\",\n",
-      "  \"last_modified_time\": \"2026-03-02 15:22:26.851000-08:00\",\n",
-      "  \"secondary_status_transitions\": [\n",
-      "    \"status='Starting' start_time=datetime.datetime(2026, 3, 2, 14, 46, 12, 873000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 14, 46, 14, 829000, tzinfo=tzlocal()) status_message='Starting the training job'\",\n",
-      "    \"status='Pending' start_time=datetime.datetime(2026, 3, 2, 14, 46, 14, 829000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 14, 58, 59, 629000, tzinfo=tzlocal()) status_message='Preparing the instances for training'\",\n",
-      "    \"status='Downloading' start_time=datetime.datetime(2026, 3, 2, 14, 58, 59, 629000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 15, 7, 4, 705000, tzinfo=tzlocal()) status_message='Downloading the training image'\",\n",
-      "    \"status='Training' start_time=datetime.datetime(2026, 3, 2, 15, 7, 4, 705000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 15, 21, 2, 752000, tzinfo=tzlocal()) status_message='Training image download completed. Training in progress.'\",\n",
-      "    \"status='Uploading' start_time=datetime.datetime(2026, 3, 2, 15, 21, 2, 752000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 15, 22, 26, 851000, tzinfo=tzlocal()) status_message='Uploading generated training model'\",\n",
-      "    \"status='Completed' start_time=datetime.datetime(2026, 3, 2, 15, 22, 26, 851000, tzinfo=tzlocal()) end_time=datetime.datetime(2026, 3, 2, 15, 22, 26, 851000, tzinfo=tzlocal()) status_message='Training job completed'\"\n",
-      "  ],\n",
-      "  \"enable_network_isolation\": false,\n",
-      "  \"enable_inter_container_traffic_encryption\": false,\n",
-      "  \"enable_managed_spot_training\": false,\n",
-      "  \"training_time_in_seconds\": 1407,\n",
-      "  \"billable_time_in_seconds\": 0,\n",
-      "  \"billable_token_count\": 153604,\n",
-      "  \"disable_efa\": false,\n",
-      "  \"image_metadata\": \"image_type='BYOImage'\",\n",
-      "  \"serverless_job_config\": \"base_model_arn='arn:aws:sagemaker:us-east-1:aws:hub-content/SageMakerPublicHub/Model/nova-textgeneration-micro/2.45.1' job_type='FineTuning' accept_eula=True customization_technique='SFT' peft='LORA' evaluation_type=Unassigned() evaluator_arn=Unassigned() job_spec=Unassigned()\",\n",
-      "  \"mlflow_config\": \"mlflow_resource_arn='arn:aws:sagemaker:us-east-1:529088288990:mlflow-app/app-2SV6Q35HTCBO' mlflow_tracking_server_arn=Unassigned() mlflow_experiment_name='test-finetuned-models-exp' mlflow_run_name='test-finetuned-models-run'\",\n",
-      "  \"model_package_config\": \"model_package_group_arn='arn:aws:sagemaker:us-east-1:529088288990:model-package-group/model-package-group-nova6' source_model_package_arn=Unassigned()\",\n",
-      "  \"mlflow_details\": \"mlflow_experiment_id='2' mlflow_run_id='1f13027c62db4ac198a7d8452a682d5d'\",\n",
-      "  \"progress_info\": \"total_step_count_per_epoch=1 current_step=1 current_epoch=2 max_epoch=2\",\n",
-      "  \"output_model_package_arn\": \"arn:aws:sagemaker:us-east-1:529088288990:model-package/model-package-group-nova6/1\"\n",
-      "}\n"
-     ]
-    }
-   ],
-   "source": [
-    "from sagemaker.core.resources import TrainingJob\n",
-    "\n",
-    "response = TrainingJob.get(training_job_name=\"nova-textgeneration-micro-sft-20260302144611\")\n",
-    "pretty_print(response)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "sagemaker.config INFO - Not applying SDK defaults from location: /Library/Application Support/sagemaker/config.yaml\n",
-      "sagemaker.config INFO - Not applying SDK defaults from location: /Users/mollyhe/Library/Application Support/sagemaker/config.yaml\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "
BenchMarkEvaluator(\n",
-       "│   region=None,\n",
-       "│   sagemaker_session=<sagemaker.core.helper.session_helper.Session object at 0x17252afe0>,\n",
-       "│   model='arn:aws:sagemaker:us-east-1:529088288990:model-package/model-package-group-nova6/1',\n",
-       "│   base_eval_name='gpqa-eval-demo',\n",
-       "│   s3_output_path='s3://sagemaker-us-east-1-529088288990/eval',\n",
-       "│   mlflow_resource_arn='arn:aws:sagemaker:us-east-1:529088288990:mlflow-app/app-2SV6Q35HTCBO',\n",
-       "│   mlflow_experiment_name='test-eval-models-exp',\n",
-       "│   mlflow_run_name=None,\n",
-       "│   networking=None,\n",
-       "│   kms_key_id=None,\n",
-       "│   model_package_group='arn:aws:sagemaker:us-east-1:529088288990:model-package-group/model-package-group-nova13',\n",
-       "│   benchmark=<_Benchmark.GPQA: 'gpqa'>,\n",
-       "│   subtasks=None,\n",
-       "│   evaluate_base_model=False\n",
-       ")\n",
-       "
\n"
-      ],
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-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mbase_eval_name\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m'gpqa-eval-demo'\u001b[0m\u001b[39m,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0ms3_output_path\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m's3://sagemaker-us-east-1-529088288990/eval'\u001b[0m\u001b[39m,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mmlflow_resource_arn\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m'arn:aws:sagemaker:us-east-1:529088288990:mlflow-app/app-2SV6Q35HTCBO'\u001b[0m\u001b[39m,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mmlflow_experiment_name\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m'test-eval-models-exp'\u001b[0m\u001b[39m,\u001b[0m\n",
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-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mnetworking\u001b[0m\u001b[39m=\u001b[0m\u001b[3;38;2;225;0;225mNone\u001b[0m\u001b[39m,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mkms_key_id\u001b[0m\u001b[39m=\u001b[0m\u001b[3;38;2;225;0;225mNone\u001b[0m\u001b[39m,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mmodel_package_group\u001b[0m\u001b[39m=\u001b[0m\u001b[38;2;0;135;0m'arn:aws:sagemaker:us-east-1:529088288990:model-package-group/model-package-group-nova13'\u001b[0m\u001b[39m,\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mbenchmark\u001b[0m\u001b[39m=<_Benchmark.GPQA: \u001b[0m\u001b[38;2;0;135;0m'gpqa'\u001b[0m\u001b[1m>\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0msubtasks\u001b[0m=\u001b[3;38;2;225;0;225mNone\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mevaluate_base_model\u001b[0m=\u001b[3;38;2;215;0;0mFalse\u001b[0m\n",
-       "\u001b[1m)\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
    "source": [
     "from sagemaker.train.evaluate import BenchMarkEvaluator\n",
     "\n",
     "# Create evaluator with GEN_QA benchmark\n",
     "# These values match our successfully tested configuration\n",
     "evaluator = BenchMarkEvaluator(\n",
-    "    benchmark=Benchmark.GPQA,\n",
-    "    model=\"arn:aws:sagemaker:us-east-1:529088288990:model-package/model-package-group-nova6/1\",\n",
-    "    s3_output_path=\"s3://sagemaker-us-east-1-529088288990/eval\",\n",
-    "    mlflow_experiment_name=\"test-eval-models-exp\", \n",
-    "    # mlflow_resource_arn=\"arn:aws:sagemaker:us-west-2:052150106756:mlflow-tracking-server/mmlu-eval-experiment\",\n",
-    "    dataset=\"s3://sagemaker-us-east-1-529088288990/eval.jsonl\",\n",
-    "    model_package_group=\"arn:aws:sagemaker:us-east-1:529088288990:model-package-group/model-package-group-nova13\", # Optional inferred from model if model package\n",
-    "    base_eval_name=\"gpqa-eval-demo\",\n",
+    "    benchmark=Benchmark.GEN_QA,\n",
+    "    model=\"arn:aws:sagemaker:us-west-2:052150106756:model-package/test-finetuned-models-gamma/28\",\n",
+    "    s3_output_path=\"s3://mufi-test-serverless-smtj/eval/\",\n",
+    "    mlflow_resource_arn=\"arn:aws:sagemaker:us-west-2:052150106756:mlflow-tracking-server/mmlu-eval-experiment\",\n",
+    "    dataset=\"s3://sagemaker-us-west-2-052150106756/studio-users/d20251107t195443/datasets/2025-11-07T19-55-37-609Z/zc_test.jsonl\",\n",
+    "    model_package_group=\"arn:aws:sagemaker:us-west-2:052150106756:model-package-group/example-name-aovqo\", # Optional inferred from model if model package\n",
+    "    base_eval_name=\"gen-qa-eval-demo\",\n",
     "    # Note: sagemaker_session is optional and will be auto-created if not provided\n",
     "    # Note: region is optional and will be auto deduced using environment variables - SAGEMAKER_REGION, AWS_REGION\n",
     ")\n",
@@ -341,7 +92,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -368,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -404,23 +155,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
{'max_new_tokens': '8196', 'temperature': '0', 'top_k': '-1', 'top_p': '1.0'}\n",
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-      ],
-      "text/plain": [
-       "\u001b[1m{\u001b[0m\u001b[38;2;0;135;0m'max_new_tokens'\u001b[0m: \u001b[38;2;0;135;0m'8196'\u001b[0m, \u001b[38;2;0;135;0m'temperature'\u001b[0m: \u001b[38;2;0;135;0m'0'\u001b[0m, \u001b[38;2;0;135;0m'top_k'\u001b[0m: \u001b[38;2;0;135;0m'-1'\u001b[0m, \u001b[38;2;0;135;0m'top_p'\u001b[0m: \u001b[38;2;0;135;0m'1.0'\u001b[0m\u001b[1m}\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "pprint(evaluator.hyperparameters.to_dict())\n",
     "\n",
@@ -451,48 +188,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
BenchmarkEvaluationExecution(\n",
-       "│   arn='arn:aws:sagemaker:us-east-1:529088288990:pipeline/SagemakerEvaluation-BenchmarkEvaluation-d47edc79-1d45-4b8f-9ff6-df8e2c8c92be/execution/ab0k65fkztid',\n",
-       "│   name='gpqa-eval-demo',\n",
-       "│   status=PipelineExecutionStatus(overall_status='Executing', step_details=[], failure_reason=None),\n",
-       "│   last_modified_time=datetime.datetime(2026, 3, 10, 17, 48, 10, 308000, tzinfo=tzlocal()),\n",
-       "│   eval_type=<EvalType.BENCHMARK: 'benchmark'>,\n",
-       "│   s3_output_path='s3://sagemaker-us-east-1-529088288990/eval',\n",
-       "│   steps=[]\n",
-       ")\n",
-       "
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-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0meval_type\u001b[0m=\u001b[1m<\u001b[0m\u001b[1;38;2;225;0;225mEvalType.BENCHMARK:\u001b[0m\u001b[39m \u001b[0m\u001b[38;2;0;135;0m'benchmark'\u001b[0m\u001b[1m>\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0ms3_output_path\u001b[0m=\u001b[38;2;0;135;0m's3://sagemaker-us-east-1-529088288990/eval'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0msteps\u001b[0m=\u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
-       "\u001b[1m)\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "Pipeline Execution ARN: arn:aws:sagemaker:us-east-1:529088288990:pipeline/SagemakerEvaluation-BenchmarkEvaluation-d47edc79-1d45-4b8f-9ff6-df8e2c8c92be/execution/ab0k65fkztid\n",
-      "Initial Status: Executing\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Run evaluation with configured parameters\n",
     "execution = evaluator.evaluate()\n",
@@ -513,7 +211,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -533,79 +231,9 @@
   },
   {
    "cell_type": "code",
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+   "execution_count": null,
    "metadata": {},
-   "outputs": [
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-      "text/html": [
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-       "│   │   ),\n",
-       "│   │   StepDetail(\n",
-       "│   │   │   name='EvaluateCustomModel',\n",
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-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[38;2;215;175;0mdisplay_name\u001b[0m=\u001b[3;38;2;225;0;225mNone\u001b[0m,\n",
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-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[38;2;215;175;0mjob_arn\u001b[0m=\u001b[3;38;2;225;0;225mNone\u001b[0m\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,\n",
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-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[38;2;215;175;0mstatus\u001b[0m=\u001b[38;2;0;135;0m'Starting'\u001b[0m,\n",
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-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[38;2;215;175;0mdisplay_name\u001b[0m=\u001b[3;38;2;225;0;225mNone\u001b[0m,\n",
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-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[38;2;215;175;0mjob_arn\u001b[0m=\u001b[3;38;2;225;0;225mNone\u001b[0m\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[1m]\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;215;175;0mfailure_reason\u001b[0m=\u001b[3;38;2;225;0;225mNone\u001b[0m\n",
-       "\u001b[1m)\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "Step Details:\n",
-      "  CreateEvaluationAction: Starting\n",
-      "  EvaluateCustomModel: Starting\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Refresh status\n",
     "execution.refresh()\n",
@@ -631,128 +259,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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╭─────────────────────────────────────────── Pipeline Execution Status ───────────────────────────────────────────╮\n",
-       "│  Overall Status        Executing                                                                                │\n",
-       "│  Target Status         Succeeded                                                                                │\n",
-       "│  Elapsed Time          33.4s                                                                                    │\n",
-       "│                                                                                                                 │\n",
-       "│ Pipeline Steps                                                                                                  │\n",
-       "│  Step Name                       Status           Duration                                                      │\n",
-       "│  CreateEvaluationAction          Succeeded        1.1s                                                          │\n",
-       "│  EvaluateCustomModel             Executing        Running...                                                    │\n",
-       "│                                                                                                                 │\n",
-       "│ Job ARNs                                                                                                        │\n",
-       "│  Step                  Job Link      Job ARN                                                                    │\n",
-       "│  EvaluateCustomModel   🔗 link       arn:aws:sagemaker:us-east-1:529088288990:training-job/pipelines-ab0k65fkz  │\n",
-       "│                                      tid-EvaluateCustomModel-5XaO1EW1hQ                                         │\n",
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-       "\u001b[34m│\u001b[0m \u001b[36m \u001b[0m\u001b[36mEvaluateCustomModel           \u001b[0m\u001b[36m \u001b[0m\u001b[33m \u001b[0m\u001b[33mExecuting\u001b[0m\u001b[33m      \u001b[0m\u001b[33m \u001b[0m\u001b[32m \u001b[0m\u001b[32mRunning...  \u001b[0m\u001b[32m \u001b[0m                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[1;35mJob ARNs\u001b[0m                                                                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mStep                \u001b[0m\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m\u001b[1;35mJob Link    \u001b[0m\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m\u001b[1;35mJob ARN                                                                  \u001b[0m\u001b[1;35m \u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[36m \u001b[0m\u001b[36mEvaluateCustomModel \u001b[0m\u001b[36m \u001b[0m \u001b]8;id=840181;https://studio-d-ingyyaeglvki.studio.us-east-1.sagemaker.aws/jobs/train/pipelines-ab0k65fkztid-EvaluateCustomModel-5XaO1EW1hQ\u001b\\🔗 link\u001b]8;;\u001b\\      \u001b[2m \u001b[0m\u001b[2marn:aws:sagemaker:us-east-1:529088288990:training-job/pipelines-ab0k65fkz\u001b[0m\u001b[2m \u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[36m                      \u001b[0m              \u001b[2m \u001b[0m\u001b[2mtid-EvaluateCustomModel-5XaO1EW1hQ                                       \u001b[0m\u001b[2m \u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮\n",
-       "│ in <module>:3                                                                                    │\n",
-       "│                                                                                                  │\n",
-       "│   1 # Wait for job completion with progress updates                                              │\n",
-       "│   2 # This will show a rich progress display in Jupyter                                          │\n",
-       "│ ❱ 3 execution.wait(target_status=\"Succeeded\", poll=5, timeout=3600)                              │\n",
-       "│   4                                                                                              │\n",
-       "│   5 print(f\"\\nFinal Status: {execution.status.overall_status}\")                                  │\n",
-       "│   6                                                                                              │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk/sagemaker-core/src/sagemaker/core/teleme │\n",
-       "│ try/telemetry_logging.py:180 in wrapper                                                          │\n",
-       "│                                                                                                  │\n",
-       "│   177 │   │   │   │   │   \"sagemaker_session is not provided or not valid.\",                     │\n",
-       "│   178 │   │   │   │   │   func_name,                                                             │\n",
-       "│   179 │   │   │   │   )                                                                          │\n",
-       "│ ❱ 180 │   │   │   │   return func(*args, **kwargs)                                               │\n",
-       "│   181 │   │                                                                                      │\n",
-       "│   182 │   │   return wrapper                                                                     │\n",
-       "│   183                                                                                            │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai │\n",
-       "│ n/evaluate/execution.py:1061 in wait                                                             │\n",
-       "│                                                                                                  │\n",
-       "│   1058 │   │   │   │   │   │   status=current_status                                             │\n",
-       "│   1059 │   │   │   │   │   )                                                                     │\n",
-       "│   1060 │   │   │   │                                                                             │\n",
-       "│ ❱ 1061 │   │   │   │   time.sleep(poll)                                                          │\n",
-       "│   1062 │   │   else:                                                                             │\n",
-       "│   1063 │   │   │   # Terminal experience with rich library                                       │\n",
-       "│   1064 │   │   │   try:                                                                          │\n",
-       "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "KeyboardInterrupt\n",
-       "
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-      ],
-      "text/plain": [
-       "\u001b[38;2;255;0;0m╭─\u001b[0m\u001b[38;2;255;0;0m──────────────────────────────\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[1;38;2;255;0;0mTraceback \u001b[0m\u001b[1;2;38;2;255;0;0m(most recent call last)\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[38;2;255;0;0m───────────────────────────────\u001b[0m\u001b[38;2;255;0;0m─╮\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m in \u001b[92m\u001b[0m:\u001b[94m3\u001b[0m                                                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1 \u001b[0m\u001b[2m# Wait for job completion with progress updates\u001b[0m                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m2 \u001b[0m\u001b[2m# This will show a rich progress display in Jupyter\u001b[0m                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m3 execution.wait(target_status=\u001b[33m\"\u001b[0m\u001b[33mSucceeded\u001b[0m\u001b[33m\"\u001b[0m, poll=\u001b[94m5\u001b[0m, timeout=\u001b[94m3600\u001b[0m)                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m4 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m5 \u001b[0m\u001b[96mprint\u001b[0m(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m\\n\u001b[0m\u001b[33mFinal Status: \u001b[0m\u001b[33m{\u001b[0mexecution.status.overall_status\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m)                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m6 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk/sagemaker-core/src/sagemaker/core/teleme\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mtry/\u001b[0m\u001b[1;33mtelemetry_logging.py\u001b[0m:\u001b[94m180\u001b[0m in \u001b[92mwrapper\u001b[0m                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m177 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[33m\"\u001b[0m\u001b[33msagemaker_session is not provided or not valid.\u001b[0m\u001b[33m\"\u001b[0m,                     \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m178 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mfunc_name,                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m179 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m)                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m180 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m func(*args, **kwargs)                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m181 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m182 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m wrapper                                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m183 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mn/evaluate/\u001b[0m\u001b[1;33mexecution.py\u001b[0m:\u001b[94m1061\u001b[0m in \u001b[92mwait\u001b[0m                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1058 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0mstatus=current_status                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1059 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m)                                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1060 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m1061 \u001b[2m│   │   │   │   \u001b[0mtime.sleep(poll)                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1062 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1063 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# Terminal experience with rich library\u001b[0m                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1064 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
-       "\u001b[1;91mKeyboardInterrupt\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Wait for job completion with progress updates\n",
     "# This will show a rich progress display in Jupyter\n",
@@ -829,13 +338,13 @@
     "\n",
     "# Get an existing job by ARN\n",
     "# Replace with your actual pipeline execution ARN\n",
-    "existing_arn = \"arn:aws:sagemaker:us-east-1:529088288990:pipeline/SagemakerEvaluation-BenchmarkEvaluation-d47edc79-1d45-4b8f-9ff6-df8e2c8c92be/execution/bhtdxm5tenya\"\n",
+    "existing_arn = \"arn:aws:sagemaker:us-west-2:052150106756:pipeline/SagemakerEvaluation-BenchmarkEvaluation-c344c91d-6f62-4907-85cc-7e6b29171c42/execution/inlsexrd7jes\"\n",
     "\n",
     "# base model only example\n",
     "# existing_arn = \"arn:aws:sagemaker:us-west-2:052150106756:pipeline/SagemakerEvaluation-benchmark/execution/gdp9f4dbv2vi\"\n",
     "existing_execution = EvaluationPipelineExecution.get(\n",
     "    arn=existing_arn,\n",
-    "    region=\"us-east-1\"\n",
+    "    region=\"us-west-2\"\n",
     ")\n",
     "\n",
     "pprint(existing_execution)\n",
diff --git a/v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod.ipynb b/v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod.ipynb
index 130991834a..e5fbe4cd99 100644
--- a/v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod.ipynb
+++ b/v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod.ipynb
@@ -58,8 +58,8 @@
     "# This creates a versioned dataset that can be referenced by ARN\n",
     "# Provide a source (it can be local file path or S3 URL)\n",
     "dataset = DataSet.create(\n",
-    "    name=\"demo-2\",\n",
-    "    source=\"s3://sagemaker-us-west-2-529088288990/dataset/preference_dataset_train_256.jsonl\"\n",
+    "    name=\"demo-6\",\n",
+    "    source=\"s3://nova-mlflow-us-west-2/dataset/preference_dataset_train_256.jsonl\"\n",
     ")\n",
     "\n",
     "print(f\"Dataset ARN: {dataset.arn}\")"
@@ -292,7 +292,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.14"
+   "version": "3.12.10"
   }
  },
  "nbformat": 4,
diff --git a/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb b/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb
index 7b4348d0e4..946debc7d7 100644
--- a/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb
+++ b/v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb
@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "87aa2004556ad7c6",
    "metadata": {},
    "outputs": [],
@@ -35,30 +35,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "id": "989646bf",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import logging\n",
-    "logging.basicConfig(level=logging.WARNING)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "a51be0b5-fd33-4fa0-af2b-d08ce0dc7a8e",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "sagemaker.config INFO - Not applying SDK defaults from location: /Library/Application Support/sagemaker/config.yaml\n",
-      "sagemaker.config INFO - Not applying SDK defaults from location: /Users/mollyhe/Library/Application Support/sagemaker/config.yaml\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from sagemaker.train.sft_trainer import SFTTrainer\n",
     "from sagemaker.train.common import TrainingType\n",
@@ -73,7 +53,7 @@
     "\n",
     "\n",
     "# For MLFlow native metrics in Trainer wait, run below line with approriate region\n",
-    "os.environ[\"SAGEMAKER_MLFLOW_CUSTOM_ENDPOINT\"] = \"https://mlflow.sagemaker.us-east-1.app.aws\"\n",
+    "os.environ[\"SAGEMAKER_MLFLOW_CUSTOM_ENDPOINT\"] = \"https://mlflow.sagemaker.us-west-2.app.aws\"\n",
     "\n"
    ]
   },
@@ -96,55 +76,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "ef4f0e61-de4d-4228-b7a1-ea7497dad547",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e98bb5da0450400ab462efafe4fd3bb8",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
Final Resource Status: Available\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "Final Resource Status: Available\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Dataset ARN: arn:aws:sagemaker:us-east-1:529088288990:hub-content/G82247CBEQ6TN0FI3J1SAJU59UURMT3H3EKG48C6VQGDINNRNGU0/DataSet/demo-1/45.0.0\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from sagemaker.ai_registry.dataset import DataSet\n",
     "from sagemaker.ai_registry.dataset_utils import CustomizationTechnique\n",
@@ -156,7 +91,7 @@
     "# Provide a source (it can be local file path or S3 URL)\n",
     "dataset = DataSet.create(\n",
     "    name=\"demo-1\",\n",
-    "    source=\"s3://sagemaker-us-east-1-529088288990/nova1_SFT.jsonl\"\n",
+    "    source=\"s3://mc-flows-sdk-testing/input_data/sft/sample_data_256_final.jsonl\"\n",
     ")\n",
     "\n",
     "print(f\"Dataset ARN: {dataset.arn}\")"
@@ -172,23 +107,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "d6937550-f721-43ff-82dd-c513c328dd17",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING:sagemaker.core.utils.utils:No region provided. Using default region.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from sagemaker.core.resources import ModelPackage, ModelPackageGroup\n",
     "\n",
-    "# model_package_group=ModelPackageGroup.create(model_package_group_name=\"model-package-group-nova13\")\n",
-    "model_package_group=ModelPackageGroup.get(model_package_group_name=\"model-package-group-nova13\")"
+    "model_package_group=ModelPackageGroup.create(model_package_group_name=\"test-model-package-group\")"
    ]
   },
   {
@@ -224,20 +150,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "88fe8360-de50-481d-932f-564a32be66a0",
    "metadata": {},
    "outputs": [],
    "source": [
     "# For fine-tuning \n",
     "sft_trainer = SFTTrainer(\n",
-    "    model=\"nova-textgeneration-lite\", \n",
-    "    training_type=TrainingType.FULL, \n",
+    "    model=\"meta-textgeneration-llama-3-2-1b-instruct\", \n",
+    "    training_type=TrainingType.LORA, \n",
     "    model_package_group=model_package_group, # or use an existing model package group arn\n",
     "    mlflow_experiment_name=\"test-finetuned-models-exp\", \n",
     "    mlflow_run_name=\"test-finetuned-models-run\", \n",
     "    training_dataset=dataset.arn, \n",
-    "    s3_output_path=\"s3://sagemaker-us-east-1-529088288990/output/\",\n",
+    "    s3_output_path=\"s3://mc-flows-sdk-testing/output/\",\n",
     "    accept_eula=True\n",
     ")\n"
    ]
@@ -254,45 +180,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "de183042-bb92-4947-9acd-78d7231bda13",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Default Finetuning Options:\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "
{\n",
-       "│   'name': 'my-fullrank-run-k3174',\n",
-       "│   'global_batch_size': '16',\n",
-       "│   'max_epochs': '1',\n",
-       "│   'learning_rate': '5e-06',\n",
-       "│   'max_context_length': '8192'\n",
-       "}\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[1m{\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'name'\u001b[0m: \u001b[38;2;0;135;0m'my-fullrank-run-k3174'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'global_batch_size'\u001b[0m: \u001b[38;2;0;135;0m'16'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_epochs'\u001b[0m: \u001b[38;2;0;135;0m'1'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'learning_rate'\u001b[0m: \u001b[38;2;0;135;0m'5e-06'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_context_length'\u001b[0m: \u001b[38;2;0;135;0m'8192'\u001b[0m\n",
-       "\u001b[1m}\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(\"Default Finetuning Options:\")\n",
     "pprint(sft_trainer.hyperparameters.to_dict()) # rename as hyperparameters"
@@ -300,7 +193,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "6b57838f-81ac-4fbe-9ddf-5588e42bcce1",
    "metadata": {
     "scrolled": true
@@ -308,7 +201,7 @@
    "outputs": [],
    "source": [
     "# To update any hyperparameter, simply assign the value, example:\n",
-    "sft_trainer.hyperparameters.global_batch_size=32"
+    "sft_trainer.hyperparameters.global_batch_size=16"
    ]
   },
   {
@@ -321,7 +214,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "4d3b6441-9abb-447b-9307-9606a8c0fabd",
    "metadata": {
     "jupyter": {
@@ -329,243 +222,13 @@
     },
     "scrolled": true
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
╭────────────────────────────────── Training Job Status ───────────────────────────────────╮\n",
-       "│  TrainingJob Name      🔗 nova-textgeneration-lite-sft-20260310173212                    │\n",
-       "│  TrainingJob ARN       arn:aws:sagemaker:us-east-1:529088288990:training-job/nova-textg  │\n",
-       "│                        eneration-lite-sft-20260310173212                                 │\n",
-       "│  MLflow Experiment     🔗 test-finetuned-models-exp                                      │\n",
-       "│                                                                                          │\n",
-       "│  Job Status            InProgress                                                        │\n",
-       "│  Secondary Status      Training                                                          │\n",
-       "│  Elapsed Time          990.7s                                                            │\n",
-       "│                                                                                          │\n",
-       "│ Status Transitions                                                                       │\n",
-       "│                                                                                          │\n",
-       "│        Step              Details                               Duration                  │\n",
-       "│  ───────────────────────────────────────────────────────────────────────────             │\n",
-       "│   ✓    Starting          Starting the training job             4.7s                      │\n",
-       "│   ✓    Pending           Preparing the instances for           656.3s                    │\n",
-       "│                          training                                                        │\n",
-       "│   ✓    Downloading       Downloading the training image        253.4s                    │\n",
-       "│   ⋯    Training          Training image download completed.    Running...                │\n",
-       "│                          Training in progress.                                           │\n",
-       "│                                                                                          │\n",
-       "╰──────────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[38;5;172m╭─\u001b[0m\u001b[38;5;172m─────────────────────────────────\u001b[0m\u001b[38;5;172m \u001b[0m\u001b[1;94mTraining Job Status\u001b[0m\u001b[38;5;172m \u001b[0m\u001b[38;5;172m──────────────────────────────────\u001b[0m\u001b[38;5;172m─╮\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mTrainingJob Name    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b]8;id=225350;https://studio-d-ingyyaeglvki.studio.us-east-1.sagemaker.aws/jobs/train/nova-textgeneration-lite-sft-20260310173212\u001b\\\u001b[37m🔗 nova-textgeneration-lite-sft-20260310173212\u001b[0m\u001b]8;;\u001b\\\u001b[37m                  \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mTrainingJob ARN     \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[2;37marn:aws:sagemaker:us-east-1:529088288990:training-job/nova-textg\u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m                      \u001b[0m\u001b[37m \u001b[0m\u001b[2;37meneration-lite-sft-20260310173212\u001b[0m\u001b[37m                               \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mMLflow Experiment   \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b]8;id=448259;https://app-2SV6Q35HTCBO.mlflow.sagemaker.us-east-1.app.aws/auth?authToken=eyJhbGciOiJIUzI1NiJ9.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._WYatAneAubx7fMUElOyogdDg5Ktk_Y_AT-tgBKt1bQ#/experiments/2\u001b\\\u001b[37m🔗 test-finetuned-models-exp\u001b[0m\u001b]8;;\u001b\\\u001b[37m                                    \u001b[0m\u001b[37m \u001b[0m \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mJob Status          \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;38;5;172mInProgress\u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mSecondary Status    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;33mTraining\u001b[0m\u001b[37m  \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mElapsed Time        \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;91m990.7s\u001b[0m\u001b[37m    \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;35mStatus Transitions\u001b[0m                                                                       \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[1;35m \u001b[0m\u001b[1;35m  \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mStep           \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mDetails                            \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mDuration    \u001b[0m\u001b[1;35m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  ───────────────────────────────────────────────────────────────────────────             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m✓ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mStarting       \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mStarting the training job          \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m4.7s        \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m✓ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mPending        \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mPreparing the instances for        \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m656.3s      \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[32m    \u001b[0m \u001b[36m                 \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mtraining                           \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m              \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m✓ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mDownloading    \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mDownloading the training image     \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m253.4s      \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m⋯ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mTraining       \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mTraining image download completed. \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32mRunning...  \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[32m    \u001b[0m \u001b[36m                 \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mTraining in progress.              \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m              \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m╰──────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮\n",
-       "│ in <module>:1                                                                                    │\n",
-       "│                                                                                                  │\n",
-       "│ ❱ 1 training_job = sft_trainer.train(                                                            │\n",
-       "│   2 │   wait=True                                                                                │\n",
-       "│   3 )                                                                                            │\n",
-       "│   4                                                                                              │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk/sagemaker-core/src/sagemaker/core/teleme │\n",
-       "│ try/telemetry_logging.py:180 in wrapper                                                          │\n",
-       "│                                                                                                  │\n",
-       "│   177 │   │   │   │   │   \"sagemaker_session is not provided or not valid.\",                     │\n",
-       "│   178 │   │   │   │   │   func_name,                                                             │\n",
-       "│   179 │   │   │   │   )                                                                          │\n",
-       "│ ❱ 180 │   │   │   │   return func(*args, **kwargs)                                               │\n",
-       "│   181 │   │                                                                                      │\n",
-       "│   182 │   │   return wrapper                                                                     │\n",
-       "│   183                                                                                            │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai │\n",
-       "│ n/sft_trainer.py:280 in train                                                                    │\n",
-       "│                                                                                                  │\n",
-       "│   277 │   │   │   from sagemaker.train.common_utils.trainer_wait import wait as _wait            │\n",
-       "│   278 │   │   │   from sagemaker.core.utils.exceptions import TimeoutExceededError               │\n",
-       "│   279 │   │   │   try :                                                                          │\n",
-       "│ ❱ 280 │   │   │   │   _wait(training_job)                                                        │\n",
-       "│   281 │   │   │   except TimeoutExceededError as e:                                              │\n",
-       "│   282 │   │   │   │   logger.error(\"Error: %s\", e)                                               │\n",
-       "│   283                                                                                            │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai │\n",
-       "│ n/common_utils/trainer_wait.py:278 in wait                                                       │\n",
-       "│                                                                                                  │\n",
-       "│   275 │   │   │   │   iteration = 0                                                              │\n",
-       "│   276 │   │   │   │   while True:                                                                │\n",
-       "│   277 │   │   │   │   │   iteration += 1                                                         │\n",
-       "│ ❱ 278 │   │   │   │   │   time.sleep(0.5)                                                        │\n",
-       "│   279 │   │   │   │   │   if iteration >= poll * 2:                                              │\n",
-       "│   280 │   │   │   │   │   │   training_job.refresh()                                             │\n",
-       "│   281 │   │   │   │   │   │   iteration = 0                                                      │\n",
-       "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "KeyboardInterrupt\n",
-       "
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-      ],
-      "text/plain": [
-       "\u001b[38;2;255;0;0m╭─\u001b[0m\u001b[38;2;255;0;0m──────────────────────────────\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[1;38;2;255;0;0mTraceback \u001b[0m\u001b[1;2;38;2;255;0;0m(most recent call last)\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[38;2;255;0;0m───────────────────────────────\u001b[0m\u001b[38;2;255;0;0m─╮\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m in \u001b[92m\u001b[0m:\u001b[94m1\u001b[0m                                                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m1 training_job = sft_trainer.train(                                                            \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m2 \u001b[0m\u001b[2m│   \u001b[0mwait=\u001b[94mTrue\u001b[0m                                                                                \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m3 \u001b[0m)                                                                                            \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m4 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk/sagemaker-core/src/sagemaker/core/teleme\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mtry/\u001b[0m\u001b[1;33mtelemetry_logging.py\u001b[0m:\u001b[94m180\u001b[0m in \u001b[92mwrapper\u001b[0m                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m177 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[33m\"\u001b[0m\u001b[33msagemaker_session is not provided or not valid.\u001b[0m\u001b[33m\"\u001b[0m,                     \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m178 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mfunc_name,                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m179 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m)                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m180 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m func(*args, **kwargs)                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m181 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m182 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m wrapper                                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m183 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mn/\u001b[0m\u001b[1;33msft_trainer.py\u001b[0m:\u001b[94m280\u001b[0m in \u001b[92mtrain\u001b[0m                                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m277 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mfrom\u001b[0m\u001b[90m \u001b[0m\u001b[4;96msagemaker\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mtrain\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mcommon_utils\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mtrainer_wait\u001b[0m\u001b[90m \u001b[0m\u001b[94mimport\u001b[0m wait \u001b[94mas\u001b[0m _wait            \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m278 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mfrom\u001b[0m\u001b[90m \u001b[0m\u001b[4;96msagemaker\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mcore\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mutils\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mexceptions\u001b[0m\u001b[90m \u001b[0m\u001b[94mimport\u001b[0m TimeoutExceededError               \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m279 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mtry\u001b[0m :                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m280 \u001b[2m│   │   │   │   \u001b[0m_wait(training_job)                                                        \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m281 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mexcept\u001b[0m TimeoutExceededError \u001b[94mas\u001b[0m e:                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m282 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mlogger.error(\u001b[33m\"\u001b[0m\u001b[33mError: \u001b[0m\u001b[33m%s\u001b[0m\u001b[33m\"\u001b[0m, e)                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m283 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/Documents/SageMaker/sagemaker-python-sdk-molly/sagemaker-train/src/sagemaker/trai\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mn/common_utils/\u001b[0m\u001b[1;33mtrainer_wait.py\u001b[0m:\u001b[94m278\u001b[0m in \u001b[92mwait\u001b[0m                                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m275 \u001b[0m\u001b[2m│   │   │   │   \u001b[0miteration = \u001b[94m0\u001b[0m                                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m276 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mwhile\u001b[0m \u001b[94mTrue\u001b[0m:                                                                \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m277 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0miteration += \u001b[94m1\u001b[0m                                                         \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m278 \u001b[2m│   │   │   │   │   \u001b[0mtime.sleep(\u001b[94m0.5\u001b[0m)                                                        \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m279 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mif\u001b[0m iteration >= poll * \u001b[94m2\u001b[0m:                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m280 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0mtraining_job.refresh()                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m281 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0miteration = \u001b[94m0\u001b[0m                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
-       "\u001b[1;91mKeyboardInterrupt\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "training_job = sft_trainer.train(\n",
-    "    wait=True\n",
+    "    wait=True,\n",
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "64d68d6f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sagemaker.train import get_mlflow_url\n",
-    "\n",
-    "# Get MLflow URL for a training job\n",
-    "url = get_mlflow_url(\"nova-textgeneration-micro-sft-20260303164831\")\n",
-    "print(url)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fef3d01d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sagemaker.train import get_studio_url\n",
-    "\n",
-    "\n",
-    "# Still working on getting the specific training job\n",
-    "url = get_studio_url('nova-textgeneration-micro-sft-20260302144611')\n",
-    "print(url)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9b50b630",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sagemaker.core.resources import TrainingJob\n",
-    "\n",
-    "training_job = TrainingJob.get(training_job_name='nova-textgeneration-micro-sft-20260303161941')\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8fa20618",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sagemaker.train import get_studio_url\n",
-    "\n",
-    "# Studio URL (job details)\n",
-    "studio_url = get_studio_url(training_job)\n",
-    "print(studio_url)\n",
-    "\n",
-    "# CloudWatch Logs URL (view logs directly)\n",
-    "url = get_studio_url(training_job, direct=True)\n",
-    "print(url)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "591d5e98",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "job.stop()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "da489ad0-36b8-44e7-9f65-2ffd359e5225",
-   "metadata": {},
-   "source": [
-    "### View any Training job details\n",
-    "\n",
-    "We can get any training job details and its status with TrainingJob.get(...)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -573,10 +236,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "\n",
     "\n",
     "import json\n",
     "import re\n",
     "from sagemaker.core.utils.utils import Unassigned\n",
+    "from sagemaker.core.resources import TrainingJob\n",
+    "\n",
+    "response = TrainingJob.get(training_job_name=\"meta-textgeneration-llama-3-2-1b-instruct-sft-20251201114921\")\n",
     "\n",
     "def pretty_print(obj):\n",
     "    def parse_unassigned(item):\n",
@@ -593,78 +260,62 @@
     "        return item\n",
     "\n",
     "    cleaned = parse_unassigned(obj.__dict__ if hasattr(obj, '__dict__') else obj)\n",
-    "    print(json.dumps(cleaned, indent=2, default=str))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6bbe96b4-c8cd-4de3-b4c0-a66fd3086eb2",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
-    "from sagemaker.core.resources import TrainingJob\n",
+    "    print(json.dumps(cleaned, indent=2, default=str))\n",
     "\n",
-    "response = TrainingJob.get(training_job_name=\"nova-textgeneration-micro-sft-20260302144611\")\n",
     "pretty_print(response)"
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "8d25735e",
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e9ee7f8e-b26c-4579-9dbc-f08124f2e944",
    "metadata": {},
+   "outputs": [],
    "source": [
-    "## Visualize Training Metrics\n",
+    "#In order to skip waiting and monitor the training Job later\n",
     "\n",
-    "After training completes, you can visualize metrics logged to MLflow:\n",
-    "\n",
-    "- **`get_available_metrics(job)`** - List all available metrics\n",
-    "- **`plot_training_metrics(job)`** - Plot all metrics\n",
-    "- **`plot_training_metrics(job, metrics=['reduced_train_loss', 'global_step'])`** - Plot specific metrics"
+    "'''\n",
+    "training_job = sft_trainer.train(\n",
+    "    wait=False,\n",
+    ")\n",
+    "'''"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b8a9256c",
-   "metadata": {},
+   "id": "0d99f212-f0bd-43c1-be21-30202fb4a152",
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
    "source": [
-    "from sagemaker.train import get_available_metrics\n",
-    "\n",
-    "get_available_metrics('nova-textgeneration-micro-sft-20260302144611')"
+    "pretty_print(training_job)"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f1a794ba",
+   "cell_type": "markdown",
+   "id": "da489ad0-36b8-44e7-9f65-2ffd359e5225",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "from sagemaker.train import plot_training_metrics\n",
+    "### View any Training job details\n",
     "\n",
-    "# Simple - plot all metrics\n",
-    "plot_training_metrics('nova-textgeneration-micro-sft-20260302144611')"
+    "We can get any training job details and its status with TrainingJob.get(...)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2f7ed9d7",
-   "metadata": {},
+   "id": "6bbe96b4-c8cd-4de3-b4c0-a66fd3086eb2",
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
    "source": [
-    "from sagemaker.train import plot_training_metrics\n",
+    "from sagemaker.core.resources import TrainingJob\n",
     "\n",
-    "# Advanced - plot specific metrics\n",
-    "plot_training_metrics(\n",
-    "    training_job='nova-textgeneration-micro-sft-20260302144611',\n",
-    "    metrics=['reduced_train_loss', 'global_step'],\n",
-    "    figsize=(14, 6)\n",
-    ")"
+    "response = TrainingJob.get(training_job_name=\"meta-textgeneration-llama-3-2-1b-instruct-sft-20251123162832\")\n",
+    "pretty_print(response)"
    ]
   },
   {
@@ -813,31 +464,11 @@
     "    wait=True,\n",
     ")"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "be4dc095",
-   "metadata": {},
-   "source": [
-    "### Stop Training Job"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fb92815b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sagemaker.core.resources import TrainingJob\n",
-    "job = TrainingJob.get(training_job_name='nova-textgeneration-pro-sft-20260304135114')\n",
-    "job.stop()"
-   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "py3.10.14",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -851,7 +482,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.14"
+   "version": "3.12.10"
   }
  },
  "nbformat": 4,
diff --git a/v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook.ipynb b/v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook.ipynb
index a5f83647cc..6645f2b7d2 100644
--- a/v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook.ipynb
+++ b/v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook.ipynb
@@ -47,33 +47,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "234f7398-fd6b-4d02-a406-0491924c461d",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\u001b[2;36m[03/02/26 14:23:42]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=981430;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=408099;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "sagemaker.config INFO - Not applying SDK defaults from location: /Library/Application Support/sagemaker/config.yaml\n",
-      "sagemaker.config INFO - Not applying SDK defaults from location: /Users/mollyhe/Library/Application Support/sagemaker/config.yaml\n",
-      "Region: us-east-1\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "\n",
     "import os\n",
@@ -105,110 +82,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "39aaeb1d",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m[03/02/26 14:23:45]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=437588;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=570403;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
[03/02/26 14:23:46] INFO     SageMaker Python SDK will collect telemetry to help us better  telemetry_logging.py:92\n",
-       "                             understand our user's needs, diagnose issues, and deliver                             \n",
-       "                             additional features.                                                                  \n",
-       "                             To opt out of telemetry, please disable via TelemetryOptOut                           \n",
-       "                             parameter in SDK defaults config. For more information, refer                         \n",
-       "                             to                                                                                    \n",
-       "                             https://sagemaker.readthedocs.io/en/stable/overview.html#confi                        \n",
-       "                             guring-and-using-defaults-with-the-sagemaker-python-sdk.                              \n",
-       "
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-      ],
-      "text/plain": [
-       "\u001b[2;36m[03/02/26 14:23:46]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m SageMaker Python SDK will collect telemetry to help us better  \u001b]8;id=719707;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/telemetry/telemetry_logging.py\u001b\\\u001b[2mtelemetry_logging.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=805235;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/telemetry/telemetry_logging.py#92\u001b\\\u001b[2m92\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                    \u001b[0m         understand our user's needs, diagnose issues, and deliver      \u001b[2m                       \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         additional features.                                           \u001b[2m                       \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         To opt out of telemetry, please disable via TelemetryOptOut    \u001b[2m                       \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         parameter in SDK defaults config. For more information, refer  \u001b[2m                       \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         to                                                             \u001b[2m                       \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[4;38;2;0;105;255mhttps://sagemaker.readthedocs.io/en/stable/overview.html#confi\u001b[0m \u001b[2m                       \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[4;38;2;0;105;255mguring-and-using-defaults-with-the-sagemaker-python-sdk.\u001b[0m       \u001b[2m                       \u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
[03/02/26 14:23:47] INFO     Role not provided. Using default role:                                  defaults.py:75\n",
-       "                             arn:aws:iam::529088288990:role/Admin                                                  \n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m[03/02/26 14:23:47]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Role not provided. Using default role:                                  \u001b]8;id=193859;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/train/defaults.py\u001b\\\u001b[2mdefaults.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=892655;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/train/defaults.py#75\u001b\\\u001b[2m75\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                    \u001b[0m         arn:aws:iam::\u001b[1;36m529088288990\u001b[0m:role/Admin                                    \u001b[2m              \u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "521e87aea90849e48e5312e3160c5a23",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
Final Resource Status: Available\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "Final Resource Status: Available\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "TRAINING_DATASET ARN: arn:aws:sagemaker:us-east-1:529088288990:hub-content/G82247CBEQ6TN0FI3J1SAJU59UURMT3H3EKG48C6VQGDINNRNGU0/DataSet/demo-sft-dataset/3.0.0\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from sagemaker.ai_registry.dataset import DataSet\n",
     "from sagemaker.ai_registry.dataset_utils import CustomizationTechnique\n",
@@ -216,34 +93,34 @@
     "# Register dataset in SageMaker AI Registry. This creates a versioned dataset that can be referenced by ARN\n",
     "dataset = DataSet.create(\n",
     "    name=\"demo-sft-dataset\",\n",
-    "    source=\"s3://sagemaker-us-east-1-529088288990/nova1_SFT.jsonl\", # source can be S3 or local path\n",
+    "    source=\"s3://your-bucket/dataset/training_dataset.jsonl\", # source can be S3 or local path\n",
     "    #customization_technique=CUSTOMIZATION_TECHNIQUE.SFT # or DPO or RLVR\n",
     "        # Optional technique name for minimal dataset format check.\n",
     "    wait=True\n",
     ")\n",
     "\n",
     "print(f\"TRAINING_DATASET ARN: {dataset.arn}\")\n",
-    "TRAINING_DATASET = dataset.arn"
+    "# TRAINING_DATASET = dataset.arn"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "ea22bd22",
    "metadata": {},
    "outputs": [],
    "source": [
     "# Required Configs\n",
-    "BASE_MODEL = \"nova-textgeneration-micro\"\n",
+    "BASE_MODEL = \"\"\n",
     "\n",
     "# MODEL_PACKAGE_GROUP_NAME is same as CUSTOM_MODEL_NAME\n",
-    "MODEL_PACKAGE_GROUP_NAME = \"model-pacakge-group-nova4\"\n",
+    "MODEL_PACKAGE_GROUP_NAME = \"\"\n",
     "\n",
-    "# TRAINING_DATASET = \"\"\n",
+    "TRAINING_DATASET = \"\"\n",
     "\n",
-    "S3_OUTPUT_PATH = \"s3://sagemaker-us-east-1-529088288990/output/\"\n",
+    "S3_OUTPUT_PATH = \"\"\n",
     "\n",
-    "ROLE_ARN = \"arn:aws:iam::529088288990:role/Admin\""
+    "ROLE_ARN = \"\""
    ]
   },
   {
@@ -256,68 +133,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "90a1069d19eeee7",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\u001b[2;36m[03/02/26 14:23:59]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Creating model_package_group resource.                              \u001b]8;id=924503;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/resources.py\u001b\\\u001b[2mresources.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=629107;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/resources.py#25559\u001b\\\u001b[2m25559\u001b[0m\u001b]8;;\u001b\\\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
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-       "
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-       "
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-      ],
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-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
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-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Runs on sagemaker prod, region:us-east-\u001b[1;36m1\u001b[0m                                  \u001b]8;id=132575;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/utils/utils.py\u001b\\\u001b[2mutils.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=459422;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/core/utils/utils.py#354\u001b\\\u001b[2m354\u001b[0m\u001b]8;;\u001b\\\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\u001b[2;36m                   \u001b[0m\u001b[2;36m \u001b[0m\u001b[1;38;2;0;105;255mINFO    \u001b[0m Found credentials in shared credentials file: ~\u001b[38;2;225;0;225m/.aws/\u001b[0m\u001b[38;2;225;0;225mcredentials\u001b[0m   \u001b]8;id=803081;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py\u001b\\\u001b[2mcredentials.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=146617;file:///Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/credentials.py#1392\u001b\\\u001b[2m1392\u001b[0m\u001b]8;;\u001b\\\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from sagemaker.core.resources import ModelPackageGroup\n",
     "model_package_group = ModelPackageGroup.create(\n",
     "    model_package_group_name=MODEL_PACKAGE_GROUP_NAME,\n",
-    "    model_package_group_description='test nova textgeneration micro' # Required Description\n",
+    "    model_package_group_description='' # Required Description\n",
     ")"
    ]
   },
@@ -386,7 +210,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "062953d8",
    "metadata": {
     "editable": true,
@@ -577,84 +401,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "2f6eeb5e",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Default Finetuning Options:\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "
{\n",
-       "│   'name': 'my-lora-run-wkxk5',\n",
-       "│   'global_batch_size': '64',\n",
-       "│   'max_epochs': '2',\n",
-       "│   'learning_rate': '1e-05',\n",
-       "│   'lora_alpha': '128',\n",
-       "│   'learning_rate_ratio': '16.0',\n",
-       "│   'max_context_length': '8192'\n",
-       "}\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[1m{\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'name'\u001b[0m: \u001b[38;2;0;135;0m'my-lora-run-wkxk5'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'global_batch_size'\u001b[0m: \u001b[38;2;0;135;0m'64'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_epochs'\u001b[0m: \u001b[38;2;0;135;0m'2'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'learning_rate'\u001b[0m: \u001b[38;2;0;135;0m'1e-05'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'lora_alpha'\u001b[0m: \u001b[38;2;0;135;0m'128'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'learning_rate_ratio'\u001b[0m: \u001b[38;2;0;135;0m'16.0'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_context_length'\u001b[0m: \u001b[38;2;0;135;0m'8192'\u001b[0m\n",
-       "\u001b[1m}\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "Modified/User defined Options:\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "
{\n",
-       "│   'name': 'my-lora-run-wkxk5',\n",
-       "│   'global_batch_size': '64',\n",
-       "│   'max_epochs': '2',\n",
-       "│   'learning_rate': '0.0002',\n",
-       "│   'lora_alpha': '128',\n",
-       "│   'learning_rate_ratio': '16.0',\n",
-       "│   'max_context_length': '8192'\n",
-       "}\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[1m{\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'name'\u001b[0m: \u001b[38;2;0;135;0m'my-lora-run-wkxk5'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'global_batch_size'\u001b[0m: \u001b[38;2;0;135;0m'64'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_epochs'\u001b[0m: \u001b[38;2;0;135;0m'2'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'learning_rate'\u001b[0m: \u001b[38;2;0;135;0m'0.0002'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'lora_alpha'\u001b[0m: \u001b[38;2;0;135;0m'128'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'learning_rate_ratio'\u001b[0m: \u001b[38;2;0;135;0m'16.0'\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[38;2;0;135;0m'max_context_length'\u001b[0m: \u001b[38;2;0;135;0m'8192'\u001b[0m\n",
-       "\u001b[1m}\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(\"Default Finetuning Options:\")\n",
     "pprint(trainer.hyperparameters.to_dict())\n",
@@ -676,355 +426,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "31690f41",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
╭────────────────────────────────── Training Job Status ───────────────────────────────────╮\n",
-       "│  TrainingJob Name      nova-textgeneration-micro-sft-20260302142433                      │\n",
-       "│                                                                                          │\n",
-       "│  Job Status            InProgress                                                        │\n",
-       "│  Secondary Status      Pending                                                           │\n",
-       "│  Elapsed Time          814.3s                                                            │\n",
-       "│                                                                                          │\n",
-       "│ Status Transitions                                                                       │\n",
-       "│                                                                                          │\n",
-       "│        Step              Details                               Duration                  │\n",
-       "│  ───────────────────────────────────────────────────────────────────────────             │\n",
-       "│   ✓    Starting          Starting the training job             2.2s                      │\n",
-       "│        Pending           Training job waiting for capacity                               │\n",
-       "│                                                                                          │\n",
-       "╰──────────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "
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-      ],
-      "text/plain": [
-       "\u001b[38;5;172m╭─\u001b[0m\u001b[38;5;172m─────────────────────────────────\u001b[0m\u001b[38;5;172m \u001b[0m\u001b[1;94mTraining Job Status\u001b[0m\u001b[38;5;172m \u001b[0m\u001b[38;5;172m──────────────────────────────────\u001b[0m\u001b[38;5;172m─╮\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mTrainingJob Name    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;32mnova-textgeneration-micro-sft-20260302142433\u001b[0m\u001b[37m \u001b[0m                     \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mJob Status          \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;38;5;172mInProgress\u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mSecondary Status    \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;33mPending\u001b[0m\u001b[37m   \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;36m \u001b[0m\u001b[1;36mElapsed Time        \u001b[0m\u001b[1;36m \u001b[0m\u001b[37m \u001b[0m\u001b[1;91m814.3s\u001b[0m\u001b[37m    \u001b[0m\u001b[37m \u001b[0m                                                       \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m \u001b[1;35mStatus Transitions\u001b[0m                                                                       \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[1;35m \u001b[0m\u001b[1;35m  \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mStep           \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mDetails                            \u001b[0m\u001b[1;35m \u001b[0m \u001b[1;35m \u001b[0m\u001b[1;35mDuration    \u001b[0m\u001b[1;35m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  ───────────────────────────────────────────────────────────────────────────             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m✓ \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mStarting       \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mStarting the training job          \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m2.2s        \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m  \u001b[32m \u001b[0m\u001b[32m  \u001b[0m\u001b[32m \u001b[0m \u001b[36m \u001b[0m\u001b[36mPending        \u001b[0m\u001b[36m \u001b[0m \u001b[38;5;172m \u001b[0m\u001b[38;5;172mTraining job waiting for capacity  \u001b[0m\u001b[38;5;172m \u001b[0m \u001b[32m \u001b[0m\u001b[32m            \u001b[0m\u001b[32m \u001b[0m             \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m│\u001b[0m                                                                                          \u001b[38;5;172m│\u001b[0m\n",
-       "\u001b[38;5;172m╰──────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra │\n",
-       "│ in/common_utils/trainer_wait.py:197 in wait                                                      │\n",
-       "│                                                                                                  │\n",
-       "│   194 │   │   │   │   │   iteration += 1                                                         │\n",
-       "│   195 │   │   │   │   │   time.sleep(1)                                                          │\n",
-       "│   196 │   │   │   │   │   if iteration == poll:                                                  │\n",
-       "│ ❱ 197 │   │   │   │   │   │   training_job.refresh()                                             │\n",
-       "│   198 │   │   │   │   │   │   iteration = 0                                                      │\n",
-       "│   199 │   │   │   │   │   clear_output(wait=True)                                                │\n",
-       "│   200                                                                                            │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor │\n",
-       "│ e/resources.py:143 in wrapper                                                                    │\n",
-       "│                                                                                                  │\n",
-       "│     140 │   │   @functools.wraps(func)                                                           │\n",
-       "│     141 │   │   def wrapper(*args, **kwargs):                                                    │\n",
-       "│     142 │   │   │   config = dict(arbitrary_types_allowed=True)                                  │\n",
-       "│ ❱   143 │   │   │   return validate_call(config=config)(func)(*args, **kwargs)                   │\n",
-       "│     144 │   │                                                                                    │\n",
-       "│     145 │   │   return wrapper                                                                   │\n",
-       "│     146                                                                                          │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/pydantic/_int │\n",
-       "│ ernal/_validate_call.py:39 in wrapper_function                                                   │\n",
-       "│                                                                                                  │\n",
-       "│    36 │   │                                                                                      │\n",
-       "│    37 │   │   @functools.wraps(wrapped)                                                          │\n",
-       "│    38 │   │   def wrapper_function(*args, **kwargs):                                             │\n",
-       "│ ❱  39 │   │   │   return wrapper(*args, **kwargs)                                                │\n",
-       "│    40 │                                                                                          │\n",
-       "│    41 │   # We need to manually update this because `partial` object has no `__name__` and `__   │\n",
-       "│    42 │   wrapper_function.__name__ = extract_function_name(wrapped)                             │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/pydantic/_int │\n",
-       "│ ernal/_validate_call.py:136 in __call__                                                          │\n",
-       "│                                                                                                  │\n",
-       "│   133 │   │   if not self.__pydantic_complete__:                                                 │\n",
-       "│   134 │   │   │   self._create_validators()                                                      │\n",
-       "│   135 │   │                                                                                      │\n",
-       "│ ❱ 136 │   │   res = self.__pydantic_validator__.validate_python(pydantic_core.ArgsKwargs(args,   │\n",
-       "│   137 │   │   if self.__return_pydantic_validator__:                                             │\n",
-       "│   138 │   │   │   return self.__return_pydantic_validator__(res)                                 │\n",
-       "│   139 │   │   else:                                                                              │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor │\n",
-       "│ e/resources.py:35682 in refresh                                                                  │\n",
-       "│                                                                                                  │\n",
-       "│   35679 │   │   logger.debug(f\"Serialized input request: {operation_input_args}\")                │\n",
-       "│   35680 │   │                                                                                    │\n",
-       "│   35681 │   │   client = Base.get_sagemaker_client()                                             │\n",
-       "│ ❱ 35682 │   │   response = client.describe_training_job(**operation_input_args)                  │\n",
-       "│   35683 │   │                                                                                    │\n",
-       "│   35684 │   │   # deserialize response and update self                                           │\n",
-       "│   35685 │   │   transform(response, \"DescribeTrainingJobResponse\", self)                         │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/clie │\n",
-       "│ nt.py:602 in _api_call                                                                           │\n",
-       "│                                                                                                  │\n",
-       "│    599 │   │   │   │   │   f\"{py_operation_name}() only accepts keyword arguments.\"              │\n",
-       "│    600 │   │   │   │   )                                                                         │\n",
-       "│    601 │   │   │   # The \"self\" in this scope is referring to the BaseClient.                    │\n",
-       "│ ❱  602 │   │   │   return self._make_api_call(operation_name, kwargs)                            │\n",
-       "│    603 │   │                                                                                     │\n",
-       "│    604 │   │   _api_call.__name__ = str(py_operation_name)                                       │\n",
-       "│    605                                                                                           │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/cont │\n",
-       "│ ext.py:123 in wrapper                                                                            │\n",
-       "│                                                                                                  │\n",
-       "│   120 │   │   │   with start_as_current_context():                                               │\n",
-       "│   121 │   │   │   │   if hook:                                                                   │\n",
-       "│   122 │   │   │   │   │   hook()                                                                 │\n",
-       "│ ❱ 123 │   │   │   │   return func(*args, **kwargs)                                               │\n",
-       "│   124 │   │                                                                                      │\n",
-       "│   125 │   │   return wrapper                                                                     │\n",
-       "│   126                                                                                            │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/clie │\n",
-       "│ nt.py:1078 in _make_api_call                                                                     │\n",
-       "│                                                                                                  │\n",
-       "│   1075 │   │   │   │   'error_code_override'                                                     │\n",
-       "│   1076 │   │   │   ) or error_info.get(\"Code\")                                                   │\n",
-       "│   1077 │   │   │   error_class = self.exceptions.from_code(error_code)                           │\n",
-       "│ ❱ 1078 │   │   │   raise error_class(parsed_response, operation_name)                            │\n",
-       "│   1079 │   │   else:                                                                             │\n",
-       "│   1080 │   │   │   return parsed_response                                                        │\n",
-       "│   1081                                                                                           │\n",
-       "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "ClientError: An error occurred (ExpiredTokenException) when calling the DescribeTrainingJob operation: The security\n",
-       "token included in the request is expired\n",
-       "\n",
-       "The above exception was the direct cause of the following exception:\n",
-       "\n",
-       "╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮\n",
-       "│ in <module>:1                                                                                    │\n",
-       "│                                                                                                  │\n",
-       "│ ❱ 1 training_job = trainer.train(wait=True)                                                      │\n",
-       "│   2                                                                                              │\n",
-       "│   3 TRAINING_JOB_NAME = training_job.training_job_name                                           │\n",
-       "│   4                                                                                              │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor │\n",
-       "│ e/telemetry/telemetry_logging.py:168 in wrapper                                                  │\n",
-       "│                                                                                                  │\n",
-       "│   165 │   │   │   │   │   caught_ex = e                                                          │\n",
-       "│   166 │   │   │   │   finally:                                                                   │\n",
-       "│   167 │   │   │   │   │   if caught_ex:                                                          │\n",
-       "│ ❱ 168 │   │   │   │   │   │   raise caught_ex                                                    │\n",
-       "│   169 │   │   │   │   │   return response  # pylint: disable=W0150                               │\n",
-       "│   170 │   │   │   else:                                                                          │\n",
-       "│   171 │   │   │   │   logger.debug(                                                              │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor │\n",
-       "│ e/telemetry/telemetry_logging.py:139 in wrapper                                                  │\n",
-       "│                                                                                                  │\n",
-       "│   136 │   │   │   │   start_timer = perf_counter()                                               │\n",
-       "│   137 │   │   │   │   try:                                                                       │\n",
-       "│   138 │   │   │   │   │   # Call the original function                                           │\n",
-       "│ ❱ 139 │   │   │   │   │   response = func(*args, **kwargs)                                       │\n",
-       "│   140 │   │   │   │   │   stop_timer = perf_counter()                                            │\n",
-       "│   141 │   │   │   │   │   elapsed = stop_timer - start_timer                                     │\n",
-       "│   142 │   │   │   │   │   extra += f\"&x-latency={round(elapsed, 2)}\"                             │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra │\n",
-       "│ in/sft_trainer.py:267 in train                                                                   │\n",
-       "│                                                                                                  │\n",
-       "│   264 │   │   │   from sagemaker.train.common_utils.trainer_wait import wait as _wait            │\n",
-       "│   265 │   │   │   from sagemaker.core.utils.exceptions import TimeoutExceededError               │\n",
-       "│   266 │   │   │   try :                                                                          │\n",
-       "│ ❱ 267 │   │   │   │   _wait(training_job)                                                        │\n",
-       "│   268 │   │   │   except TimeoutExceededError as e:                                              │\n",
-       "│   269 │   │   │   │   logger.error(\"Error: %s\", e)                                               │\n",
-       "│   270                                                                                            │\n",
-       "│                                                                                                  │\n",
-       "│ /Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra │\n",
-       "│ in/common_utils/trainer_wait.py:374 in wait                                                      │\n",
-       "│                                                                                                  │\n",
-       "│   371 │   except (FailedStatusError, TimeoutExceededError):                                      │\n",
-       "│   372 │   │   raise                                                                              │\n",
-       "│   373 │   except Exception as e:                                                                 │\n",
-       "│ ❱ 374 │   │   raise RuntimeError(f\"Training job monitoring failed: {e}\") from e                  │\n",
-       "│   375                                                                                            │\n",
-       "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "RuntimeError: Training job monitoring failed: An error occurred (ExpiredTokenException) when calling the \n",
-       "DescribeTrainingJob operation: The security token included in the request is expired\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[38;2;255;0;0m╭─\u001b[0m\u001b[38;2;255;0;0m──────────────────────────────\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[1;38;2;255;0;0mTraceback \u001b[0m\u001b[1;2;38;2;255;0;0m(most recent call last)\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[38;2;255;0;0m───────────────────────────────\u001b[0m\u001b[38;2;255;0;0m─╮\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33min/common_utils/\u001b[0m\u001b[1;33mtrainer_wait.py\u001b[0m:\u001b[94m197\u001b[0m in \u001b[92mwait\u001b[0m                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m194 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0miteration += \u001b[94m1\u001b[0m                                                         \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m195 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mtime.sleep(\u001b[94m1\u001b[0m)                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m196 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mif\u001b[0m iteration == poll:                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m197 \u001b[2m│   │   │   │   │   │   \u001b[0mtraining_job.refresh()                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m198 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0miteration = \u001b[94m0\u001b[0m                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m199 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mclear_output(wait=\u001b[94mTrue\u001b[0m)                                                \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m200 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33me/\u001b[0m\u001b[1;33mresources.py\u001b[0m:\u001b[94m143\u001b[0m in \u001b[92mwrapper\u001b[0m                                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  140 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[1;95m@functools\u001b[0m.wraps(func)                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  141 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mdef\u001b[0m\u001b[90m \u001b[0m\u001b[92mwrapper\u001b[0m(*args, **kwargs):                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  142 \u001b[0m\u001b[2m│   │   │   \u001b[0mconfig = \u001b[96mdict\u001b[0m(arbitrary_types_allowed=\u001b[94mTrue\u001b[0m)                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m  143 \u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m validate_call(config=config)(func)(*args, **kwargs)                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  144 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  145 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m wrapper                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m  146 \u001b[0m                                                                                         \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/pydantic/_int\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mernal/\u001b[0m\u001b[1;33m_validate_call.py\u001b[0m:\u001b[94m39\u001b[0m in \u001b[92mwrapper_function\u001b[0m                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 36 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 37 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[1;95m@functools\u001b[0m.wraps(wrapped)                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 38 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mdef\u001b[0m\u001b[90m \u001b[0m\u001b[92mwrapper_function\u001b[0m(*args, **kwargs):                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m 39 \u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m wrapper(*args, **kwargs)                                                \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 40 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 41 \u001b[0m\u001b[2m│   \u001b[0m\u001b[2m# We need to manually update this because `partial` object has no `__name__` and `__\u001b[0m   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 42 \u001b[0m\u001b[2m│   \u001b[0mwrapper_function.\u001b[91m__name__\u001b[0m = extract_function_name(wrapped)                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/pydantic/_int\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33mernal/\u001b[0m\u001b[1;33m_validate_call.py\u001b[0m:\u001b[94m136\u001b[0m in \u001b[92m__call__\u001b[0m                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m133 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[95mnot\u001b[0m \u001b[96mself\u001b[0m.__pydantic_complete__:                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m134 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m._create_validators()                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m135 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m136 \u001b[2m│   │   \u001b[0mres = \u001b[96mself\u001b[0m.__pydantic_validator__.validate_python(pydantic_core.ArgsKwargs(args,   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m137 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mself\u001b[0m.__return_pydantic_validator__:                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m138 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mself\u001b[0m.__return_pydantic_validator__(res)                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m139 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33me/\u001b[0m\u001b[1;33mresources.py\u001b[0m:\u001b[94m35682\u001b[0m in \u001b[92mrefresh\u001b[0m                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35679 \u001b[0m\u001b[2m│   │   \u001b[0mlogger.debug(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33mSerialized input request: \u001b[0m\u001b[33m{\u001b[0moperation_input_args\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m)                \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35680 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35681 \u001b[0m\u001b[2m│   │   \u001b[0mclient = Base.get_sagemaker_client()                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m35682 \u001b[2m│   │   \u001b[0mresponse = client.describe_training_job(**operation_input_args)                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35683 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35684 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[2m# deserialize response and update self\u001b[0m                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m35685 \u001b[0m\u001b[2m│   │   \u001b[0mtransform(response, \u001b[33m\"\u001b[0m\u001b[33mDescribeTrainingJobResponse\u001b[0m\u001b[33m\"\u001b[0m, \u001b[96mself\u001b[0m)                         \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/\u001b[0m\u001b[1;33mclie\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[1;33mnt.py\u001b[0m:\u001b[94m602\u001b[0m in \u001b[92m_api_call\u001b[0m                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 599 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m{\u001b[0mpy_operation_name\u001b[33m}\u001b[0m\u001b[33m() only accepts keyword arguments.\u001b[0m\u001b[33m\"\u001b[0m              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 600 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m)                                                                         \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 601 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# The \"self\" in this scope is referring to the BaseClient.\u001b[0m                    \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m 602 \u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mself\u001b[0m._make_api_call(operation_name, kwargs)                            \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 603 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 604 \u001b[0m\u001b[2m│   │   \u001b[0m_api_call.\u001b[91m__name__\u001b[0m = \u001b[96mstr\u001b[0m(py_operation_name)                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m 605 \u001b[0m                                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/\u001b[0m\u001b[1;33mcont\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[1;33mext.py\u001b[0m:\u001b[94m123\u001b[0m in \u001b[92mwrapper\u001b[0m                                                                            \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m120 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mwith\u001b[0m start_as_current_context():                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m121 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m hook:                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m122 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mhook()                                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m123 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m func(*args, **kwargs)                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m124 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m125 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m wrapper                                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m126 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/botocore/\u001b[0m\u001b[1;33mclie\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[1;33mnt.py\u001b[0m:\u001b[94m1078\u001b[0m in \u001b[92m_make_api_call\u001b[0m                                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1075 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[33m'\u001b[0m\u001b[33merror_code_override\u001b[0m\u001b[33m'\u001b[0m                                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1076 \u001b[0m\u001b[2m│   │   │   \u001b[0m) \u001b[95mor\u001b[0m error_info.get(\u001b[33m\"\u001b[0m\u001b[33mCode\u001b[0m\u001b[33m\"\u001b[0m)                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1077 \u001b[0m\u001b[2m│   │   │   \u001b[0merror_class = \u001b[96mself\u001b[0m.exceptions.from_code(error_code)                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m1078 \u001b[2m│   │   │   \u001b[0m\u001b[94mraise\u001b[0m error_class(parsed_response, operation_name)                            \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1079 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1080 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m parsed_response                                                        \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m1081 \u001b[0m                                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
-       "\u001b[1;91mClientError: \u001b[0mAn error occurred \u001b[1m(\u001b[0mExpiredTokenException\u001b[1m)\u001b[0m when calling the DescribeTrainingJob operation: The security\n",
-       "token included in the request is expired\n",
-       "\n",
-       "\u001b[3mThe above exception was the direct cause of the following exception:\u001b[0m\n",
-       "\n",
-       "\u001b[38;2;255;0;0m╭─\u001b[0m\u001b[38;2;255;0;0m──────────────────────────────\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[1;38;2;255;0;0mTraceback \u001b[0m\u001b[1;2;38;2;255;0;0m(most recent call last)\u001b[0m\u001b[38;2;255;0;0m \u001b[0m\u001b[38;2;255;0;0m───────────────────────────────\u001b[0m\u001b[38;2;255;0;0m─╮\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m in \u001b[92m\u001b[0m:\u001b[94m1\u001b[0m                                                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m1 training_job = trainer.train(wait=\u001b[94mTrue\u001b[0m)                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m2 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m3 \u001b[0mTRAINING_JOB_NAME = training_job.training_job_name                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m4 \u001b[0m                                                                                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33me/telemetry/\u001b[0m\u001b[1;33mtelemetry_logging.py\u001b[0m:\u001b[94m168\u001b[0m in \u001b[92mwrapper\u001b[0m                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m165 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mcaught_ex = e                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m166 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mfinally\u001b[0m:                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m167 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mif\u001b[0m caught_ex:                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m168 \u001b[2m│   │   │   │   │   │   \u001b[0m\u001b[94mraise\u001b[0m caught_ex                                                    \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m169 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m response  \u001b[2m# pylint: disable=W0150\u001b[0m                               \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m170 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m171 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mlogger.debug(                                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/cor\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33me/telemetry/\u001b[0m\u001b[1;33mtelemetry_logging.py\u001b[0m:\u001b[94m139\u001b[0m in \u001b[92mwrapper\u001b[0m                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m136 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mstart_timer = perf_counter()                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m137 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m138 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[2m# Call the original function\u001b[0m                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m139 \u001b[2m│   │   │   │   │   \u001b[0mresponse = func(*args, **kwargs)                                       \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m140 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mstop_timer = perf_counter()                                            \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m141 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0melapsed = stop_timer - start_timer                                     \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m142 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mextra += \u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m&x-latency=\u001b[0m\u001b[33m{\u001b[0m\u001b[96mround\u001b[0m(elapsed,\u001b[90m \u001b[0m\u001b[94m2\u001b[0m)\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m                             \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33min/\u001b[0m\u001b[1;33msft_trainer.py\u001b[0m:\u001b[94m267\u001b[0m in \u001b[92mtrain\u001b[0m                                                                   \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m264 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mfrom\u001b[0m\u001b[90m \u001b[0m\u001b[4;96msagemaker\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mtrain\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mcommon_utils\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mtrainer_wait\u001b[0m\u001b[90m \u001b[0m\u001b[94mimport\u001b[0m wait \u001b[94mas\u001b[0m _wait            \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m265 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mfrom\u001b[0m\u001b[90m \u001b[0m\u001b[4;96msagemaker\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mcore\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mutils\u001b[0m\u001b[4;96m.\u001b[0m\u001b[4;96mexceptions\u001b[0m\u001b[90m \u001b[0m\u001b[94mimport\u001b[0m TimeoutExceededError               \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m266 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mtry\u001b[0m :                                                                          \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m267 \u001b[2m│   │   │   │   \u001b[0m_wait(training_job)                                                        \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m268 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mexcept\u001b[0m TimeoutExceededError \u001b[94mas\u001b[0m e:                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m269 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mlogger.error(\u001b[33m\"\u001b[0m\u001b[33mError: \u001b[0m\u001b[33m%s\u001b[0m\u001b[33m\"\u001b[0m, e)                                               \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m270 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33m/Users/mollyhe/.pyenv/versions/3.10.14/envs/py3.10.14/lib/python3.10/site-packages/sagemaker/tra\u001b[0m \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[2;33min/common_utils/\u001b[0m\u001b[1;33mtrainer_wait.py\u001b[0m:\u001b[94m374\u001b[0m in \u001b[92mwait\u001b[0m                                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m                                                                                                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m371 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mexcept\u001b[0m (FailedStatusError, TimeoutExceededError):                                      \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m372 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mraise\u001b[0m                                                                              \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m373 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mexcept\u001b[0m \u001b[96mException\u001b[0m \u001b[94mas\u001b[0m e:                                                                 \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m \u001b[31m❱ \u001b[0m374 \u001b[2m│   │   \u001b[0m\u001b[94mraise\u001b[0m \u001b[96mRuntimeError\u001b[0m(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33mTraining job monitoring failed: \u001b[0m\u001b[33m{\u001b[0me\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m) \u001b[94mfrom\u001b[0m\u001b[90m \u001b[0m\u001b[4;96me\u001b[0m                  \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m│\u001b[0m   \u001b[2m375 \u001b[0m                                                                                           \u001b[38;2;255;0;0m│\u001b[0m\n",
-       "\u001b[38;2;255;0;0m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
-       "\u001b[1;91mRuntimeError: \u001b[0mTraining job monitoring failed: An error occurred \u001b[1m(\u001b[0mExpiredTokenException\u001b[1m)\u001b[0m when calling the \n",
-       "DescribeTrainingJob operation: The security token included in the request is expired\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "training_job = trainer.train(wait=True)\n",
     "\n",
@@ -1650,7 +1055,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "py3.10.14",
    "language": "python",
    "name": "python3"
   },

From 41ccc9cb6637834698a0cedbb82123ec5022d433 Mon Sep 17 00:00:00 2001
From: Molly He 
Date: Fri, 20 Mar 2026 17:06:39 -0700
Subject: [PATCH 10/11] Address PR readiness

---
 sagemaker-train/pyproject.toml                |   8 +-
 .../train/common_utils/trainer_wait.py        |   8 +-
 .../src/sagemaker/train/evaluate/execution.py |  18 +--
 .../common_utils/test_metrics_visualizer.py   | 121 ++++++++++++++++++
 4 files changed, 140 insertions(+), 15 deletions(-)
 create mode 100644 sagemaker-train/tests/unit/train/common_utils/test_metrics_visualizer.py

diff --git a/sagemaker-train/pyproject.toml b/sagemaker-train/pyproject.toml
index e85eb97b1e..648994b5eb 100644
--- a/sagemaker-train/pyproject.toml
+++ b/sagemaker-train/pyproject.toml
@@ -43,9 +43,6 @@ dependencies = [
     "sagemaker-mlflow>=0.0.1,<1.0.0",
     "mlflow>=3.0.0,<4.0.0",
     "nest_asyncio>=1.5.0",
-    "ipywidgets>=8.0.0",
-    "rich>=13.0.0",
-    "matplotlib>=3.5.0",
 ]
 
 [project.urls]
@@ -64,6 +61,11 @@ test = [
     "graphene",
     "IPython"
 ]
+notebook = [
+    "ipywidgets>=8.0.0",
+    "rich>=13.0.0",
+    "matplotlib>=3.5.0",
+]
 
 [tool.setuptools.packages.find]
 where = ["src/"]
diff --git a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
index 72537874f5..59adcdfbfc 100644
--- a/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
+++ b/sagemaker-train/src/sagemaker/train/common_utils/trainer_wait.py
@@ -182,16 +182,16 @@ def get_mlflow_url(training_job) -> str:
     if not hasattr(training_job, 'mlflow_config') or _is_unassigned_attribute(training_job.mlflow_config):
         raise ValueError("Training job does not have MLflow configured")
     
-    import boto3
     import os
     from mlflow.tracking import MlflowClient
     import mlflow
-    
+    from sagemaker.core.utils.utils import SageMakerClient
+
     mlflow_arn = training_job.mlflow_config.mlflow_resource_arn
     exp_name = training_job.mlflow_config.mlflow_experiment_name
-    
+
     # Get presigned base URL
-    sm_client = boto3.client('sagemaker')
+    sm_client = SageMakerClient().sagemaker_client
     response = sm_client.create_presigned_mlflow_app_url(Arn=mlflow_arn)
     base_url = response.get('AuthorizedUrl')
     
diff --git a/sagemaker-train/src/sagemaker/train/evaluate/execution.py b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
index 722461bb6c..d5e50f86b5 100644
--- a/sagemaker-train/src/sagemaker/train/evaluate/execution.py
+++ b/sagemaker-train/src/sagemaker/train/evaluate/execution.py
@@ -931,16 +931,14 @@ def wait(
                 header_table.add_column("Property", style="cyan bold", width=20)
                 header_table.add_column("Value", style="dim", overflow="fold")
 
-                # Extract pipeline name and region from execution ARN
+                # Extract pipeline name and exec_id from execution ARN
                 pipeline_name = None
                 exec_id = ''
-                region = None
                 if self.arn:
                     arn_parts = self.arn.split('/')
                     if len(arn_parts) >= 4:
                         pipeline_name = arn_parts[-3]
                         exec_id = arn_parts[-1]
-                    region = self.arn.split(":")[3] if len(self.arn.split(":")) > 3 else None
                 # Use execution display name if available, fall back to self.name
                 display_name = self.name
                 if self._pipeline_execution:
@@ -952,8 +950,10 @@ def wait(
                 # Build links row
                 links = []
                 try:
+                    from sagemaker.core.utils.utils import SageMakerClient
                     from sagemaker.train.common_utils.metrics_visualizer import _is_in_studio, _get_studio_base_url
-                    if region and pipeline_name and _is_in_studio():
+                    if pipeline_name and _is_in_studio():
+                        region = SageMakerClient().region_name
                         base = _get_studio_base_url(region)
                         if base:
                             pipeline_url = f"{base}/jobs/evaluation/detail?pipeline_name={pipeline_name}&execution_id={exec_id}"
@@ -1052,12 +1052,13 @@ def wait(
                         links_table = Table(show_header=True, header_style="bold magenta", box=None, padding=(0, 1))
                         links_table.add_column("Step", style="cyan", width=20)
                         links_table.add_column("Console", style="dim")
+                        from sagemaker.core.utils.utils import SageMakerClient
                         from sagemaker.train.common_utils.metrics_visualizer import (
                             _is_in_studio, _parse_job_arn, _get_studio_base_url,
                             get_console_job_url, get_cloudwatch_logs_url,
                         )
                         in_studio = _is_in_studio()
-                        studio_base = _get_studio_base_url(region) if in_studio else ""
+                        studio_base = _get_studio_base_url(SageMakerClient().region_name) if in_studio else ""
                         if in_studio:
                             links_table.add_column("Studio", style="dim")
                         links_table.add_column("Logs", style="dim")
@@ -1296,15 +1297,16 @@ def _convert_to_subclass(self, eval_type: EvalType) -> 'EvaluationPipelineExecut
     @staticmethod
     def _extract_job_arn_from_metadata(step) -> Optional[str]:
         """Extract the underlying job ARN from a pipeline step's metadata."""
+        from sagemaker.train.common_utils.trainer_wait import _is_unassigned_attribute
         metadata = getattr(step, 'metadata', None)
-        if metadata is None or 'Unassigned' in metadata.__class__.__name__:
+        if metadata is None or _is_unassigned_attribute(metadata):
             return None
         for attr in ('training_job', 'processing_job', 'transform_job', 'tuning_job',
                      'auto_ml_job', 'compilation_job'):
             job_meta = getattr(metadata, attr, None)
-            if job_meta is not None and not ('Unassigned' in job_meta.__class__.__name__):
+            if job_meta is not None and not _is_unassigned_attribute(job_meta):
                 arn = getattr(job_meta, 'arn', None)
-                if arn and not ('Unassigned' in arn.__class__.__name__):
+                if arn and not _is_unassigned_attribute(arn):
                     return str(arn)
         return None
 
diff --git a/sagemaker-train/tests/unit/train/common_utils/test_metrics_visualizer.py b/sagemaker-train/tests/unit/train/common_utils/test_metrics_visualizer.py
new file mode 100644
index 0000000000..9b7b804055
--- /dev/null
+++ b/sagemaker-train/tests/unit/train/common_utils/test_metrics_visualizer.py
@@ -0,0 +1,121 @@
+"""Unit tests for metrics_visualizer module."""
+import pytest
+from unittest.mock import Mock, patch, MagicMock
+
+
+class TestParseJobArn:
+    def test_training_job_arn(self):
+        from sagemaker.train.common_utils.metrics_visualizer import _parse_job_arn
+        result = _parse_job_arn("arn:aws:sagemaker:us-west-2:123456789012:training-job/my-job")
+        assert result == ("us-west-2", "training-job/my-job")
+
+    def test_processing_job_arn(self):
+        from sagemaker.train.common_utils.metrics_visualizer import _parse_job_arn
+        result = _parse_job_arn("arn:aws:sagemaker:us-east-1:123456789012:processing-job/my-job")
+        assert result == ("us-east-1", "processing-job/my-job")
+
+    def test_invalid_arn_returns_none(self):
+        from sagemaker.train.common_utils.metrics_visualizer import _parse_job_arn
+        assert _parse_job_arn("not-an-arn") is None
+
+
+class TestGetConsoleJobUrl:
+    def test_training_job(self):
+        from sagemaker.train.common_utils.metrics_visualizer import get_console_job_url
+        url = get_console_job_url("arn:aws:sagemaker:us-west-2:123456789012:training-job/my-job")
+        assert url == "https://us-west-2.console.aws.amazon.com/sagemaker/home?region=us-west-2#/jobs/my-job"
+
+    def test_invalid_arn_returns_empty(self):
+        from sagemaker.train.common_utils.metrics_visualizer import get_console_job_url
+        assert get_console_job_url("not-an-arn") == ""
+
+    def test_unknown_job_type_returns_empty(self):
+        from sagemaker.train.common_utils.metrics_visualizer import get_console_job_url
+        assert get_console_job_url("arn:aws:sagemaker:us-west-2:123456789012:unknown-job/my-job") == ""
+
+
+class TestGetCloudwatchLogsUrl:
+    def test_training_job(self):
+        from sagemaker.train.common_utils.metrics_visualizer import get_cloudwatch_logs_url
+        url = get_cloudwatch_logs_url("arn:aws:sagemaker:us-west-2:123456789012:training-job/my-job")
+        assert "us-west-2" in url
+        assert "TrainingJobs" in url
+        assert "my-job" in url
+
+    def test_invalid_arn_returns_empty(self):
+        from sagemaker.train.common_utils.metrics_visualizer import get_cloudwatch_logs_url
+        assert get_cloudwatch_logs_url("not-an-arn") == ""
+
+
+class TestGetStudioUrl:
+    @patch("sagemaker.train.common_utils.metrics_visualizer._get_studio_base_url")
+    @patch("sagemaker.core.utils.utils.SageMakerClient")
+    def test_with_training_job_object(self, mock_client_cls, mock_base_url):
+        from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
+        mock_client_cls.return_value.region_name = "us-west-2"
+        mock_base_url.return_value = "https://studio-d-abc.studio.us-west-2.sagemaker.aws"
+
+        mock_job = Mock()
+        mock_job.training_job_name = "my-job"
+
+        url = get_studio_url(mock_job)
+        assert url == "https://studio-d-abc.studio.us-west-2.sagemaker.aws/jobs/train/my-job"
+        mock_base_url.assert_called_once_with("us-west-2")
+
+    @patch("sagemaker.train.common_utils.metrics_visualizer._get_studio_base_url")
+    def test_with_arn_string(self, mock_base_url):
+        from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
+        mock_base_url.return_value = "https://studio-d-abc.studio.us-west-2.sagemaker.aws"
+
+        url = get_studio_url("arn:aws:sagemaker:us-west-2:123456789012:training-job/my-job")
+        assert url == "https://studio-d-abc.studio.us-west-2.sagemaker.aws/jobs/train/my-job"
+        mock_base_url.assert_called_once_with("us-west-2")
+
+    @patch("sagemaker.train.common_utils.metrics_visualizer._get_studio_base_url")
+    @patch("sagemaker.core.utils.utils.SageMakerClient")
+    @patch("sagemaker.train.common_utils.metrics_visualizer.TrainingJob")
+    def test_with_job_name_string(self, mock_tj_cls, mock_client_cls, mock_base_url):
+        from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
+        mock_client_cls.return_value.region_name = "us-west-2"
+        mock_base_url.return_value = "https://studio-d-abc.studio.us-west-2.sagemaker.aws"
+        mock_tj_cls.get.return_value.training_job_name = "my-job"
+
+        url = get_studio_url("my-job")
+        assert url == "https://studio-d-abc.studio.us-west-2.sagemaker.aws/jobs/train/my-job"
+
+    @patch("sagemaker.train.common_utils.metrics_visualizer._get_studio_base_url")
+    @patch("sagemaker.core.utils.utils.SageMakerClient")
+    def test_returns_empty_when_no_domain(self, mock_client_cls, mock_base_url):
+        from sagemaker.train.common_utils.metrics_visualizer import get_studio_url
+        mock_client_cls.return_value.region_name = "us-west-2"
+        mock_base_url.return_value = ""
+
+        url = get_studio_url(Mock(training_job_name="my-job"))
+        assert url == ""
+
+
+class TestGetAvailableMetrics:
+    @patch("sagemaker.train.common_utils.metrics_visualizer.TrainingJob")
+    def test_returns_empty_when_no_mlflow_config(self, _):
+        from sagemaker.train.common_utils.metrics_visualizer import get_available_metrics
+        mock_job = Mock(spec=[])  # no mlflow_config attribute
+        assert get_available_metrics(mock_job) == []
+
+    @patch("sagemaker.train.common_utils.metrics_visualizer.TrainingJob")
+    def test_returns_empty_when_mlflow_config_falsy(self, _):
+        from sagemaker.train.common_utils.metrics_visualizer import get_available_metrics
+        mock_job = Mock()
+        mock_job.mlflow_config = None
+        assert get_available_metrics(mock_job) == []
+
+    @patch("mlflow.get_run")
+    @patch("mlflow.set_tracking_uri")
+    def test_returns_metric_names(self, mock_set_uri, mock_get_run):
+        from sagemaker.train.common_utils.metrics_visualizer import get_available_metrics
+        mock_job = Mock()
+        mock_job.mlflow_config.mlflow_resource_arn = "arn:aws:sagemaker:us-west-2:123:mlflow-tracking/abc"
+        mock_job.mlflow_details.mlflow_run_id = "run-123"
+        mock_get_run.return_value.data.metrics = {"loss": 0.5, "accuracy": 0.9}
+
+        result = get_available_metrics(mock_job)
+        assert set(result) == {"loss", "accuracy"}

From d03de045d7ae072e096bb2d9408cd8245c5d28a0 Mon Sep 17 00:00:00 2001
From: Molly He 
Date: Mon, 23 Mar 2026 10:43:09 -0700
Subject: [PATCH 11/11] Fix sagemaker-train unit tst

---
 .../tests/unit/train/evaluate/test_pipeline_templates.py         | 1 -
 1 file changed, 1 deletion(-)

diff --git a/sagemaker-train/tests/unit/train/evaluate/test_pipeline_templates.py b/sagemaker-train/tests/unit/train/evaluate/test_pipeline_templates.py
index 136ac022cd..36092fbeb3 100644
--- a/sagemaker-train/tests/unit/train/evaluate/test_pipeline_templates.py
+++ b/sagemaker-train/tests/unit/train/evaluate/test_pipeline_templates.py
@@ -121,7 +121,6 @@ def test_deterministic_template_with_optional_mlflow_params(self):
         pipeline_def = json.loads(rendered)
         
         assert pipeline_def["MlflowConfig"]["MlflowExperimentName"] == "test-experiment"
-        assert pipeline_def["MlflowConfig"]["MlflowRunName"] == "test-run"
 
     def test_deterministic_template_with_all_hyperparameters(self):
         """Test DETERMINISTIC_TEMPLATE with all optional hyperparameters."""