AzureML model predictions do not match scored model

James Beresford 0 Reputation points
2022-02-11T03:56:31.223+00:00

I have deployed a model to an endpoint but the predictions that come back do not match what is output from the scored model in the experiment.

The model is a Multiclass Neural Network for classifying emails - it takes approx. 1,000 elements of text and puts them into one of about 18 possible categories.

Reviewing the scored model outputs in the experiment, the accuracy is reasonable; however once deployed it always predicts any input into a single category with near 100% confidence. The input is correctly formatted (this is validated in the model output) so I'm assuming something is misconfigured in the model deployment, but I'm not seeing any indication as to what.

Appreciate any help from MSFT in investigating this issue.

Cheers, James

Azure Machine Learning
Azure Machine Learning
An Azure machine learning service for building and deploying models.
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  1. Ramr-msft 17,641 Reputation points
    2022-02-11T11:43:59.53+00:00

    anonymous user Thanks for the question. There are multiple ways to create a multiclass DNN on various AzureML products. Is this from some tensorflow or pytorch code, or from the AML Designer? Screenshots or sample notebooks might help a lot.