Hi All,
Let me know your inputs on how to increase performance score for the AI builder custom model "Classify texts into custom categories". I fed around 200 data into the source data table. My current version of the model has a performance score of 55 which is not enough to proceed to use the model. I'll be adding more data to the data table. Please let me know any tips that helped you in increasing the performance score of this model
Hi @arun_kj ,
One option will be to create your custom prompt with your own data in a prompt to classify your text into a given categories, so no need to build or train a model.
Use your own data in a prompt | Microsoft Learn
Regards,
Philippe
Hi @plarrue ,
I have tried that as well. However I was not clear on how to use data part in the prompt. Could you please give me the right idea? The attached image shows the prompt I created. Wrt Data part, I have a Dataverse table which already has some data on categorization. Like around 200 mail bodies and the corresponding categorization already done. This is selected in the 'Data used' section. How can I use the Filter attribute and Filter Value fields to help the prompt to provide better predictions.
Regards,
Arun K J
Hi @arun_kj ,
Happy to read that you want to explore prompts for your scenario.
I believe Email Classification2 is your Dataverse table with data, so in your prompt you'll need to specify that you want to classify the input text into of the input categories from the <Table>.
Some Docs and a learning module that can help you
Use your own data in a prompt | Microsoft Learn
Create AI Builder grounded prompts with Dataverse data - Training | Microsoft Learn
Regards,
Philippe
Okay so to clarify, the table data we give in prompt is used only for getting reference. It is not used to train the prompt like how dataverse table data is used to train an AI model. Is that right?
Regards,
Arun K J
The Dataverse table in your prompt is referenced as a data source.
There is not any training model process in the prompt.
here's some example of scenarios
Email
into one of these Category.Name
matching based on Category.Description
.
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