Performance of Best of N Baseline for Various N and Sample Responses and GPT-4 Judgments | HackerNoon
Briefly

from Hackernoon1 year ago
The Best of N baseline, though computationally expensive, shows strong performance in our experiments. It requires multiple sampling iterations but provides valuable comparative insights.
Hackernoonhttps://hackernoon.com/performance-of-best-of-n-baseline-for-various-n-and-sample-responses-and-gpt-4-judgments?source=rss
In our experiments, we evaluate DPO against PPO and find it advantageous in generating dialogue responses and summarizations, effectively comparing distinct model outputs.
Hackernoonhttps://hackernoon.com/performance-of-best-of-n-baseline-for-various-n-and-sample-responses-and-gpt-4-judgments?source=rss
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#research #machine-learning #direct-preference-optimization #natural-language-processing #stanford-university
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