Working on fine-tuning the Granite 3.2 model for a domain-specific application. While the base model performs well, the fine-tuned version seems to overfit on our dataset. Has anyone experienced similar challenges? What strategies did you employ to mitigate overfitting during fine-tuning?
Hello Uwe, After speaking with IBM support I was told there was not a way to extend a trial account.You could create a new account, but would need to use a different email address, if you elect to do that all information from your trial account does not transfer to the new account. Why not use a...
Hi, now that I have been working with the trial for almost 30 days, I am looking for ways to extend this? Or is there a way to get a cheap license as an IBM ISV? Unfortunately, our ISV partner support can't give us any information on this.
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When creating models in the Build model view of a Decision Optimization experiment, have you ever wished that you didn't have to type in the same basic code that is needed for all models? Well now you can use code snippets in Decision Optimization experiments in watsonx.ai as a Service or...
In Decision Optimization experiments you can create different visualizations for both input and output data. Sometimes data has several categories and you want to see the information aggregated or to see averages or other values. You can create your own pivot tables in the Visualization view...
When building Decision Optimization models you sometimes want to create different scenarios with different data sets, or make changes to your data and rerun your model to see the effect. Switching between scenarios is easy in a Decision Optimization experiment, but, when making changes to data...