FActScore ↗47.7%
Alpaca 13B · FActScore · estimator A · Unlabeled entity-biography evaluation ↗
Reported model / MODEL EVIDENCE
Alpaca 13B
2 benchmarks · 2 observations · 2 sources
Scores at a glance
2 benchmarks · large dot: Alpaca 13B; small dots: closest models where reported
MT-Bench & MT-Bench-101 ↗4.53 / 10
Alpaca-13B · MT-Bench & MT-Bench-101 · GPT-4 judge score · original model variants ↗
Closest models by score
Similar positions on shared benchmark leaderboards. Smaller gaps are closer.
GPT-4 →OpenAI
2 of 2 shared benchmark comparisons
How similarity is measured
Mean absolute gap in percentile positions on shared benchmark settings; lower is closer. At least 60% overlap is required, with a minimum of three when available. Independent evaluations are used when there are at least three; otherwise published report comparisons are used. Repeated model observations within one setting are averaged before ranking. Writing-style traits and composite indices are excluded. This describes similarity, not an overall quality ranking.
Sources
Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.
- Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena — published result table ↗
All 13 authors
Zheng, Lianmin, Chiang, Wei-Lin, Sheng, Ying, Zhuang, Siyuan, Wu, Zhanghao, Zhuang, Yonghao, Lin, Zi, Li, Zhuohan, Li, Dacheng, Xing, Eric P., Zhang, Hao, Gonzalez, Joseph E., Stoica, Ion
- FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation — published result table ↗
All 9 authors
Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, Hannaneh Hajishirzi
Names used in source tables
Alpaca 13B · Alpaca-13B