Intended use
Answer a question from a passage the user provides. If the passage does not contain the answer, reply with exactly: The passage does not say.
Training
- Trainer: TRL
SFTTrainer
- Loss: completion tokens only
- LoRA rank 16, merged before upload
- The config file that produced these weights is named in the metrics section below
Evaluation
Greedy decoding. Strict accuracy requires the gold span in a short reply that does not abstain, or exactly The passage does not say. The table also reports normalized answer EM, token F1, and semantic abstention. Final numbers for a protocol run are the article-held-out test split. resolved.yaml and environment.json record the configuration and package versions.
Config: protocol.yaml.
Table with columns: Model, Strict acc., Answerable, Unanswerable, Answer EM, Answer F1, Semantic abstention| Model | Strict acc. | Answerable | Unanswerable | Answer EM | Answer F1 | Semantic abstention |
|---|
| base | 0.410 | 0.290 | 0.530 | 0.200 | 0.290 | 0.530 |
| always_abstain | 0.500 | 0.000 | 1.000 | 0.000 | 0.000 | 1.000 |
| sft | 0.550 | 0.310 | 0.790 | 0.300 | 0.346 | 0.790 |
| rloo | 0.475 | 0.590 | 0.360 | 0.520 | 0.616 | 0.360 |
Table with columns: Comparison, Reward-model win rate, Ties| Comparison | Reward-model win rate | Ties |
|---|
| rloo_vs_sft | 0.410 | 0.565 |
| rloo_vs_base | 0.510 | 0.340 |
| rloo_vs_always_abstain | 0.705 | 0.260 |
| sft_vs_base | 0.285 | 0.480 |
| sft_vs_always_abstain | 0.315 | 0.670 |
Limitations
This is a 0.5B research model. It is not a general assistant, and it was not trained with new human preference labels. It will miss answers, abstain when it should not, and copy a span when the passage does not support it.