Hacker News Reader

Comment by Cheer2171 | Hacker News Reader

That's because VADER is just a dictionary mapping each word to a single sentiment weight and adding it up with some basic logic for negations and such. There's an ocean of smaller NLP ML between that naive approach and LLMs. LLMs are trained to do everything. If all you need is a model trained to do sentiment analysis, using VADER over something like DistilBERT is NLP malpractice in 2025.

View on HN

> using VADER over something like DistilBERT is NLP malpractice in 2025.

Ouch. Was that necessary?

I used $1000 worth of GPU credits and threw in VADER because it’s basically free both in time and credits.

I usually do this on large dataset out of pure interest in how it correlates with expensive methods on English language text.

I am well aware of how VADER works and its limitations, I am also aware of the limitations of all sentiment analysis.

Sorry, I side with GP. Just because you don't want to use Llama/GPT because of cost, the middle-ground of DistilBERT etc (which can run on a single CPU) is a much more sensible cost/benefit tradeoff than VADER's decade old lexicon-based approach.

I can't really think of many NLP things that are one-decade old and don't have a better / faster / cheaper alternative.

I must have explained myself extremely poorly. I spent a fair bit of money ~$1,000 USD running a near SOTA fine-tuned llama model on cloud GPUs for this very particular task.

I think people do understand, but think you that your argument on price/performane uses two dataoint that are both far from a perceived better third option.

It's like saying I chose barefoot walking to get to the next town and while admittedly it was a painfull and not pleasant experience, it was free. I did try a helicopter service but that was very expensive for my use case.

People are pointing out you could have used a bicycle instead.

This was clear both other times you explained it, the other commenters seem to want to nitpick despite it.

Maybe I misinterpreted what he wrote, but sanity checking the shiny new tech against fossilized tech of yesteryear to assure the new tech actually justifies it's higher cost doesn't sound like malpractice to me?

I mean he did use the state of the art for his work, he just checked how much better it actually was in comparison to a much simpler algorithm and thought the cost/benefit ratio to be questionable... At least that's what I read from his comments

Curious how big your dataset was if you used $1000 of GPU credits on DistilBERT. I've run BERT on CPU on moderate cloud instances no problem for datasets I've worked with, but which admittedly are not huge.

If I'm reading correctly, they used $1000 running a Llama model, not DistilBERT.

You read it correctly. I obviously didn't explain myself well.

Price isn't a real issue in almost every imaginable use case either. Even a small open source model would outperform and you're going to get a lot of tokens per dollar with that.

> dictionary mapping each word to a single sentiment weight

That seems to me like it would flat out fail on sarcasm. How is that still considered a usable method today?

It's not.

Reply on news.ycombinator.com