Fixing Mistral Nemo Repetition Loops | Generated by AI
When a model like Mistral-Nemo keeps repeating itself, it’s usually a symptom of a generation loop — a feedback cycle in the model’s output. This can happen for several technical reasons:
1. Weak “stopping” signals in the context If the prompt or conversation doesn’t give the model a clear signal about when to stop or change topic, it may keep producing similar tokens because that’s the most statistically likely continuation it “sees.”
2. Token-level feedback loops
Language models predict one token at a time, each prediction based on the tokens so far.
If the recent sequence has high probability of repeating (like "educational educational"), the model might fall into a high-confidence repetition loop because each repetition increases the probability of doing it again.
3. Low diversity in decoding settings If temperature is low (e.g., 0–0.2) and top-k/top-p sampling is too restrictive, the model will choose the most likely token every time, reinforcing loops instead of breaking out. On the other hand, too high temperature can also cause random but still repetitive noise.
4. Prompt artifacts If the input text already has partial repetition, the model can “latch onto” it, thinking it’s a stylistic choice or important emphasis — so it mirrors and extends it.
5. Model limitations or fine-tuning bias Some open models, especially if fine-tuned on chat-style or synthetic data, may have learned patterns where repetition is overrepresented (for emphasis or reinforcement), making them more prone to this in edge cases.
6. No repetition penalty applied
Some frameworks (like Hugging Face transformers) allow a repetition_penalty or frequency_penalty to discourage reusing the same tokens.
If these are set to 1.0 (no penalty), the model has no “cost” for repeating.
How to reduce this behavior in Mistral-Nemo
- Add a repetition penalty (1.1–1.3)
- Increase top-k (e.g., 50–100) or adjust top-p (0.9–0.95)
- Raise temperature slightly if too low (0.7–0.9)
- Avoid giving it repeated phrases in the prompt unless necessary
- Provide clear instructions or an explicit stop sequence
If you like, I can give you a step-by-step config example for Mistral-Nemo that reduces these loops. That way, you can test directly and see the difference.