Jev: The Text Classifier That Surprised Even a Skeptic
Language models for text classification: From bag-of-words to Jev
Sebastian Raschka traces text classification from bag-of-words and logistic regression through RNNs and ULMFiT to the newly released Jev model. Initially skeptical that Jev was 'just a classifier,' he found it works better than expected, offering a faster, cheaper alternative to LLMs for classification tasks while being more general than task-specific models.
My thoughts went from 'classifiers used to be my bread & butter; I can easily build this myself' to 'wow, this actually works better than I thought.'
- jacek-123
Thats very nice, I always explain LLMs to ppl starting from old-school language models and then just replacing the predictor from bag-of-words to transformers to etc.) I think its a cool framing
- nzoschke
Great article. This matches my feelings:
> Like ChatGPT in 2022 was exciting because it was a general-purpose chat model that could generate all kinds of texts, one of the reasons the tech community is excited about Jev is that it is the ChatGPT moment for classification, where it can cheaply classify all kinds of text inputs without having to fine-tune a custom classifier for each task.
We've been comparing strategies for classifying email and Jev is looking promising. I compared some strategies here: https://housecat.com/blog/classifying-email
- tomrod
Dr. Raschka is wonderful. Great article.