Azure AI Custom Image Analysis model not returning performance metrics

> Please provide us with the following information:
> ---------------------------------------------------------------

### This issue is for a: (mark with an `x`)
```
- [x] bug report -> please search issues before submitting
- [ ] feature request
- [ ] documentation issue or request
- [ ] regression (a behavior that used to work and stopped in a new release)
```

### Minimal steps to reproduce
Trained and working Azure AI Custom Image Analysis model.

### Any log messages given by the failure
`Status: Error(code={'code': 'InternalServerError', 'message': 'Batch did not complete successfully. OutputResultWriteFailed: An unexpected error was encountered.'}, message='', target='', details=[])`

### Expected/desired behavior
The following code from this guideline - https://github.com/Azure-Samples/cognitive-service-vision-model-customization-python-samples/blob/main/docs/cognitive_service_vision_model_customization.ipynb - do not return any performance metrics.

```
from cognitive_service_vision_model_customization_python_samples import Evaluation
eval_dataset_name = '{specify_your_eval_dataset_name}'
evaluation_name = '{specify_your_eval_run_name}'

evaluation = Evaluation(evaluation_name, model_name, eval_dataset_name)
training_client.evaluate_model(evaluation)

evaluation = training_client.wait_for_evaluation_completion(model_name, evaluation_name)
```

### OS and Version?
> Windows 10

### Versions
>

### Mention any other details that might be useful
I've created a question in the Q&A section of Microsoft - https://learn.microsoft.com/en-us/answers/questions/1880298/azure-ai-custom-image-analysis-model-not-returning?page=1&orderby=helpful&comment=answer-1665959. However the community couldn't help.


> ---------------------------------------------------------------
> Thanks! We'll be in touch soon.

Start with docs/cognitive_service_vision_model_customization.ipynb and the Evaluation/evaluate_model flow shown in the report. Reproduce the evaluation with a trained Custom Image Analysis model, then inspect the InternalServerError/OutputResultWriteFailed response and compare it with the linked Microsoft Q&A thread. Done means determining why metrics are absent and documenting the confirmed resolution or limitation.

Written by the indexing model from the issue text.