Influential parameters for OPEN AI data processing

Key Parameters for AI Output Control

1. Temperature (Randomness)

   • Definition: Governs how exploratory the model is in generating text.
   • Range:
     • Low (e.g., 0.1): Prioritizes high-probability responses for deterministic outputs (useful for technical or factual tasks).
     • High (e.g., 1.5): Allows for more creative and diverse outputs by considering lower-probability options.
   • Implication: Balances between deterministic (precise) and stochastic (creative) responses.

2. Top-k Sampling

   • Definition: Limits the model to only consider the top k highest-probability tokens.
   • Range:
     • Low k (e.g., 5): Reduces diversity for focused responses.
     • High k (e.g., 50): Increases diversity but may risk incoherence.

3. Top-p (Nucleus) Sampling

   • Definition: Considers tokens from a probability distribution until their cumulative sum exceeds a threshold p.
   • Range:
     • Low p (e.g., 0.1): Restricts to highly probable options, ensuring coherent and focused outputs.
     • High p (e.g., 0.9): Expands choices for diverse and creative responses.

4. Repetition Penalty

   • Definition: Penalizes tokens that appear repeatedly to avoid redundancy.
   • Implication: Ensures variety in responses, especially in longer texts.

5. Frequency Penalty & Presence Penalty

   • Frequency Penalty: Penalizes frequently occurring tokens to encourage new vocabulary.
   • Presence Penalty: Penalizes tokens that have already been used, promoting novelty.
   • Use Case: Ensures diverse outputs in creative tasks while reducing repetition.

6. Maximum Tokens

   • Definition: Sets a limit on the length of the output.
   • Implication: Controls verbosity and ensures responses fit the desired length.

7. Stop Sequences

   • Definition: Specifies where the model should stop generating text.
   • Implication: Helps in formatting structured responses or ending outputs at logical points.

8. Beam Search Parameters

   • Beam Width: Number of sequences considered simultaneously during output generation.
   • Diversity Parameter: Introduces randomness into beam search for more varied outputs.
   • Implication: Improves response quality while balancing between diversity and coherence.

9. Temperature Decay

   • Definition: Reduces the temperature over time during generation.
   • Implication: Starts with creativity and transitions to determinism, useful for stepwise tasks.

10. Logit Clipping

    • Definition: Smooths out extreme token probabilities to avoid overly confident or extreme responses.
    • Implication: Produces balanced outputs with moderate probability distributions.

11. Context Window/Length

    • Definition: Determines the amount of input the model considers for generating a response.
    • Implication: Longer context windows improve coherence in lengthy discussions or documents.

12. Bias Adjustments

    • Token Bias: Adjusts token likelihoods to steer outputs (e.g., emphasizing positivity).
    • Implication: Customizes tone, style, or subject focus.

13. Multi-Pass Decoding

    • Definition: Generates multiple outputs for the same input and selects the best.
    • Implication: Increases quality and relevance at the expense of computational effort.

---

Integrated Use Case Example

Scenario: Assigning ICD-10 Codes

• Low Temperature: Ensures deterministic, accurate medical code generation.
• Top-p Sampling (0.3): Prioritizes relevant options while avoiding overly rigid outputs.
• Frequency Penalty (0.5): Reduces repetition in similar diagnostic codes.
• Stop Sequences: Ensures outputs are formatted as structured JSON for easier readability.

By understanding and combining these parameters, one can finely control the model’s behavior, balancing creativity, coherence, and precision to suit diverse applications. 

----- 

Further reading

https://www.prompthub.us/blog/understanding-openai-parameters-how-to-optimize-your-prompts-for-better-outputs

Collated by:  Dr M Khalid Munir, a Product Management professional working for the healthcare solutions industry for about two decades. email: khalid345 (at) g m a i l (dot) com