Update README.md

README.md

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 ## Bias, Risks, and Limitations
 
 - **Weak safety generalization.** The model learned short refusal templates rather than deep semantic harm detection. Paraphrased or novel harmful prompts frequently bypass refusals.
-- **Terse outputs.** The base Stentor-30M had a persistent tendency to keep generating text well past a natural stopping point rather than terminating cleanly on its own. The stop-calibration phase was specifically designed to reinforce the behavior of ending a response once the answer is complete, so short and clean outputs are intentional.
+- **Rare self termination.** Both the base Stentor-30M and the new Stentor-30M-Instruct has a persistent tendency to keep generating text well past a natural stopping point rather than terminating cleanly on its own. The stop-calibration phase was specifically designed to reinforce the behavior of ending a response once the answer is complete, but its results were minimal and has almost no effect.
 - **All base model limitations apply.** 512-token context, limited world knowledge, occasional hallucination — see the [Stentor-30M model card](https://huggingface.co/StentorLabs/Stentor-30M) for full details.
 - **No RLHF.** SFT only — no preference-based alignment was applied.
 - **Dataset biases.** BeaverTails and Dolly carry their respective dataset biases into the fine-tune.