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Anyone care to comment on why the output of these models changes so dramatically given so little Q&A training? It's a 6 billion parameter model with only 50 tho
by aabajian 4y ago
Anyone care to comment on why the output of these models changes so dramatically given so little Q&A training? It's a 6 billion parameter model with only 50 thousand Q&A samples.
It's clear the model already "knows" the format of a Tweet (short length, attention-grabbing, contains hashtags). The model also knows stuff about language models (word2vec, tokenization), and can include entities from the question in its response (Dolly, Databricks). Yet, it just doesn't put these pieces together in the right way without the Q&A training.
Edit: For kicks, I asked GPT-4 this question: https://imgur.com/a/sM4uyBn https://imgur.com/a/sM4uyBn
- Davexon 4y agoJust like in Alpaca, the answer lies in the LLama dataset where the focus is on instruction following. GPT-J knows all the answers but just now was taught to understand the questions thoroughly before writing the answer.
- pwendell 4y agoYes this was a very surprising result... that the relatively small uptraining was able to unlock so much latent knowledge in the model.