How To Fix ML_CAI_MESSAGE065 - Service is not available. The model(&1) is still in the training process.


SAP Error Message - Details

  • Message type: E = Error

  • Message class: ML_CAI_MESSAGE -

  • Message number: 065

  • Message text: Service is not available. The model(&1) is still in the training process.

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  • Self-Explanatory Message

    Since SAP believes that this specific error message is 'self-explanatory,' no more information has been given.The majority of messages in the SAP system have a message text, however this is frequently insufficient to comprehend or resolve the problem.

    To make things easier, more detailed information is frequently added to describe the issue, how to fix it, and the necessary steps or configuration modifications.

    Unfortunately, there isn't any extra information in this error notice.



    What else can you do?

    First, use our AnswerBot below to get a possible cause and solution (requires a premium subscription).

    Also, review the in-depth Common Questions & Answers listed below; you could discover a solution there or be able to connect with others who have faced similar challenges.

    You can also try searching the SAP support portal (support.sap.com) but you need a special user ID to access it. It is possible that an SAP support note exists that provides additional details about the mistake or even steps for fixing it.


Smart SAP Assistant

  • What is the cause and solution for SAP error message ML_CAI_MESSAGE065 - Service is not available. The model(&1) is still in the training process. ?

    The SAP error message ML_CAI_MESSAGE065 indicates that a machine learning model is still in the training process and is not yet available for use. This typically occurs in the context of SAP's machine learning capabilities, where models are trained on data before they can be deployed for predictions or other operations.

    Cause:

    1. Model Training in Progress: The primary cause of this error is that the model you are trying to access is still being trained. During this time, the model is not available for any operations, including predictions or evaluations.
    2. Long Training Time: Depending on the complexity of the model and the amount of data being processed, the training process can take a significant amount of time.
    3. Resource Constraints: If the system is under heavy load or if there are insufficient resources (CPU, memory), the training process may take longer than expected.

    Solution:

    1. Wait for Training to Complete: The simplest solution is to wait until the training process is finished. You can monitor the status of the model in the SAP system to see when it becomes available.
    2. Check Model Status: Use transaction codes or relevant SAP Fiori apps to check the status of the model. This will help you determine if the model is still training or if there are any issues.
    3. Review Logs: Check the logs for any errors or warnings that might indicate why the training is taking longer than expected. This can provide insights into potential issues that need to be addressed.
    4. Optimize Training Process: If the training process is consistently taking too long, consider optimizing the training data or the model parameters. This may involve:
      • Reducing the size of the training dataset.
      • Simplifying the model architecture.
      • Ensuring that the system has adequate resources allocated for training.
    5. Consult Documentation: Refer to SAP documentation or support resources for specific guidance on managing machine learning models and troubleshooting training issues.

    Related Information:

    • SAP Machine Learning Foundation: Familiarize yourself with the SAP Machine Learning Foundation, which provides tools and frameworks for building and deploying machine learning models.
    • SAP Notes and Knowledge Base Articles: Check SAP Notes for any known issues or updates related to the specific version of SAP you are using.
    • Community Forums: Engage with the SAP community forums or support channels to see if others have encountered similar issues and what solutions they found effective.

    By following these steps, you should be able to address the error and ensure that your machine learning model is successfully trained and available for use.

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