Tech stack for fine-tuning LLMs
If you have tried training/fine-tuning LLMs on your data, what tech and infra stack did you use? My use case is training on data generated by my own activity
https://huggingface.co/docs/transformers/training
for both classification and regression problems with the caveats that (i) the default learning rate is too damn high (easy to fix) and (ii) with a great deal of effort I got the classification problem to perform as well as a classifier that uses
and an SVM from scikit-learn. You might get different results with another problem, but my problem is noisy and has an upper limit to what accuracy is possible. Fine-tuning a model takes maybe 30 minutes, the classical classifier is more like 30 seconds, and the ratio of development time that went into these is similar.