MMLU calibration (expected calibration error)
Models answer an MMLU subset and their answer probabilities are compared with accuracy. Scored as expected calibration error.
Reported in the GPT-4 Technical Report for the pre-trained and post-trained models.
- Level
- University Undergraduates and entry-level professionals
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Multiple choice
GPT-4 leads with 0.07
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
- 1 GPT-4 Mar 2023 0.07
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-4 Mar 2023 | 0.07 | Mar 2023 | Model card |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Labs report it only in system cards
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark. Some system cards do, below.
One system card reports it
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 14 Mar 2023 | GPT-4 technical report | 0.074 | Calibration curve on an MMLU subset, post-trained (ppo) model ECE 0.074, pre-trained ECE 0.007 (Figure 8) | Hallucination |
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