ModelTrainer doesn't propagate hyperparameters if SourceCode-command is used

**Describe the bug**
With ModelTrainer, when I'm using the command parameter in the SourceCode with an argument provided as part of the command, for example `python launcher.py -e test.py`, hyperparameters defined in the ModelTrainer are not passed to the training script.

**To reproduce**
A clear, step-by-step set of instructions to reproduce the bug.

```
from sagemaker.modules.configs import (
Compute,
OutputDataConfig,
RemoteDebugConfig,
SourceCode,
StoppingCondition,
)
from sagemaker.modules.train import ModelTrainer

# Define the script to be run
source_code = SourceCode(
source_dir="./scripts",
requirements="requirements.txt",
command="python launcher.py -e train.py",
)

# Define the compute
compute_configs = Compute(
instance_type=instance_type,
instance_count=instance_count,
keep_alive_period_in_seconds=0,
)

job_name = "train-ray-processing-train"

output_path = f"s3://{bucket_name}/{job_name}"

model_trainer = ModelTrainer(
training_image=image_uri,
source_code=source_code,
base_job_name=job_name,
compute=compute_configs,
hyperparameters={
"epochs": 25,
"learning_rate": 0.001,
"batch_size": 100,
},
stopping_condition=StoppingCondition(max_runtime_in_seconds=18000),
output_data_config=OutputDataConfig(
s3_output_path=output_path, compression_type="NONE"
),
role=role,
)
```

in the launcher.py:

```
from argparse import ArgumentParser, Namespace

def __read_params():
try:
parser = ArgumentParser()

parser.add_argument("-e", "--entrypoint", type=str)
parser.add_argument("--epochs", type=int, default=25)
parser.add_argument("--learning_rate", type=float, default=0.001)
parser.add_argument("--batch_size", type=int, default=100)

# Parse only the arguments we care about and ignore the rest
args, unknown = parser.parse_known_args()

return args, unknown
except Exception as e:

raise e

if __name__ == "__main__":
args, _ = __read_params()
```
**Expected behavior**
both the arguments passed as command in the SoureCode, and the hyperparameters provided in the ModelTrainer definition, should be passed to the training script

**Screenshots or logs**
If applicable, add screenshots or logs to help explain your problem.

**System information**
A description of your system. Please provide:
- **SageMaker Python SDK version**: 2.247.1
- **Framework name (eg. PyTorch) or algorithm (eg. KMeans)**: Any
- **Framework version**: Any
- **Python version**: 3.12
- **CPU or GPU**: CPU and GPU
- **Custom Docker image (Y/N)**: N

**Additional context**
Add any other context about the problem here.

Commencez par retracer comment ModelTrainer combine les hyperparamètres avec la commande SourceCode, en utilisant la reproduction dans launcher.py ainsi que les points d’entrée ModelTrainer et SourceCode du SageMaker SDK. Reproduisez le problème avec la configuration fournie, puis vérifiez que les arguments de la commande et les hyperparamètres de ModelTrainer parviennent bien au script d’entraînement.

Rédigé par le modèle d'indexation à partir du texte de l'issue.