How to deal with imbalanced text data

I am working on a problem where I have to classify products into multiple classes (more than one) based on product descriptions. For instance:

“Tresemme shampoo and conditioner – sulfate-free” = Personal Hygiene
“Lavender-scented handwash with moisturizer” = Personal Hygiene
“Doritos Ranch flavor 18 oz mega party pack” = Snacks
“Painting and Craft kit for adults above 18” = Art and Craft

However, my training dataset is highly imbalanced. A few classes have only 10 records while there is one that has 3000 records. 50000 records overall.

Can anyone suggest any good techniques to deal with the imbalance in text data?

Thanks,
GD