Text Classification - Multiple Training Datasets
I ended up using huggingface's zero-shot classification.
Would there be “dilution” of accuracy if I train the same text classification model with multiple training datasets? For example, my end users would be providing (uploading) their own tagged CSVs to train the model and use the trained model in the future. The contexts of datasets would be different - L&D, Technology, Customer Support, etc.
If yes, how do I have a “separate instance or model” for each user?
I am using Python and would possibly use Gradio or Streamlit as the UI. Open to advice.