Azure AutoML Model Accuracy Metrics

Question

Hello Everyone , I have deployed a ML Model over a REST Endpoint successfully and the model is trained using Azure AutoML . I am successfully able to send data to the model via the endpoint and get back the predicted output . Sending of data is done in JSON format through a python script and the received data is print as output by the python script .I am able to view trained model metrics like accuracy , error rates , root mean squared errors etc .. through the Azure ML Studio User Interface but is there any way of accessing these error or accuracy metrics through the endpoint using a python script ? I know that there is ML flow but in that case the whole training should be done using a python script and that is not suitable for my case and the other one is logging APIs which don't give me error or accuracy metrics but give others which are not needed for my usage. In a nutshell I want to access model accuracy metrics of the already trained and deployed model via an API or endpoint . Also is there any place in azure storage where these accuracy metrics are stored and if they can be accessed via an Endpoint ? Please help me on this issue . Thank you all :)