In correct nouns , dates, facts and figures #55
Description
Hello ,
hope you are fine. I am working on text generation module of Grover and have successfully trained Grover's mega network on common crawl data with different parameters. Its generating results better then before but still I am facing following issues,
- Sometimes it changes the person's name or gender entirely
- sometime makes spelling mistakes in it.
- It changes the dates and time mention in original news articles to something else
Can I solve these issues by more training or hyper parameter tuning? or it is issue not at all?
Is there any other way I can make my model from making spelling mistakes and generating incorrect facts ad figures